The possibility to control the charge, type, and density of domain walls allows properties of ferroelectric materials to be selectively enhanced or reduced. In ferroelectric–ferroelastic materials, two types of domain walls are possible: pure ferroelectric and ferroelastic–ferroelectric. In this paper, we demonstrated a strategy to control the selective ferroelectric or ferroelastic domain wall formation in the (111) single-domain rhombohedral PMN-PT single crystals at the nanoscale by varying the relative humidity level in a scanning probe microscopy chamber. The solution of the corresponding coupled electro-mechanical boundary problem allows explaining observed competition between ferroelastic and ferroelectric domain growth. The reduction in the ferroelastic domain density during local switching at elevated humidity has been attributed to changes in the electric field spatial distribution and screening effectiveness. The established mechanism is important because it reveals a kinetic nature of the final domain patterns in multiaxial materials and thus provides a general pathway to create desirable domain structure in ferroelectric materials for applications in piezoelectric and optical devices. Multiaxial ferroelectrics exhibit a coupling between spontaneous polarization and stress, which results in the formation of the ferroelastic and ferroelectric domain walls. The ferroelectric domain walls separate domains with opposite polarization directions, while domain walls with another angle between polarization directions are ferroelastic. The ferroelectric domain wall motion is activated by the application of the external electric field and is generally insensitive to mechanical stress, while ferroelastic domain walls react on both electric and elastic fields . The abic+-domain with upward-directed polarization to the c–-domain with downward-directed polarization predominantly occurs through the intermediate state of ferroelastic domain wall formation (growth of the a-domain), i.e., two 90-degree switching events in [001] cut tetragonal ferroelectrics [a-domains [c+- or c–-domain states on some timescale [a-domain formation [The dynamics of the 180-degree domain walls is comprehensively studied in the uniaxial crystals ,15. The lectrics ,22,23,24lectrics ,26,27. L-domains ,29,30. T-domains . The dir-domains ,32,33,34ormation , while tormation .a- and c-domain switching due to the significantly different energy barrier height [a-domains [a- and c-domains [Regardless of the discussed energy-conditioned driving forces of the ferroelectric–ferroelastic switching, the polarization reversal process is significantly determined by kinetic factors: screening, the interaction between domain walls, etc. . For exar height ,38, bothr height . Thereby-domains , and bet-domains , can occ-domains ,41,42,431/3Nb2/3)O3-0.28PbTiO3 (0.72PMN-0.28PT) ferroelectric single crystals, we detangle the complicated dynamics of the ferroelectric and ferroelastic domain walls during the local switching by SPM probe. The competition between ferroelectric and ferroelastic switching mechanisms was explored, which is controlled by the value and distribution of the electric field from the SPM probe. In a dry atmosphere mediating high localization in the electric field, complicated domain patterns are formed, with both ferroelectric and ferroelastic domain walls. Increasing the relative humidity leads to a stronger and more homogeneous electric field, which realizes switching with the formation of an isolated ferroelectric domain with 180-degree domain walls. The finite element simulations of the spatial distribution of the electric field and accompanying electromechanical stress allowed the electric field components to be studied, which drives local polarization reversal at the different stages of the domain dynamics. It was demonstrated that the formation of the 180-degree domain walls significantly reduces the stress components, thereby impeding ferroelastic switching. The competition between purely ferroelectric and ferroelectric–ferroelastic switching was revealed, which illustrates different possible pathways of polarization reversal in the multiaxial ferroelectrics controlled by switching kinetics.In this work, we reveal the role of domain dynamics in the formation of the domain structure during local polarization reversal in the multiaxial ferroelectric crystals. By the example of (111) 0.72Pb using a scanning probe microscope NTEGRA Aura  and MFP-3D-SA . The silicon NSC18 tips  with Ti/Pt conductive coating and a 35 nm nominal radius of curvature were used. 1.5 V AC voltage at a frequency near the first flexural contact resonance was applied to the tip. The variable relative humidity was controlled using a self-made humidifier.The macro-scale switching was carried out using a tungsten probe with the etch-sharpened tip (radius around 10 μm) as the top electrode and the saturated aqueous solution of lithium chloride as the bottom one. The triangular voltage pulse with a 40 V/s rate and a 2 s duration was generated with PCI-6251 multifunction input-output device  and amplified by a high-voltage amplifier 677B . The switching current was recorded using the self-made operational amplifier ammeter. The optical domain imaging was carried out using the optical microscope LMA10  and the high-speed Mini UX100 camera .zE) and mechanical stress (σ) produced by a biased conductive SPM tip was calculated by the solution of the coupled electrical and mechanical equations in the approximation of the static problem. The simulations were performed using the finite element method in the commercial software COMSOL Multiphysics . The relative permittivity, elastic, and piezoelectric coefficients for the (111) PMN-PT were taken from Ref. [c-domain was modeled by introducing the cylindrical-shaped c↓-domain under the probe with a radius ranging from 50 to 1000 nm.The spatial distribution of the polar component of the electric field  the web-like structure of a↓-domains oriented along c↑ domain, and the reversed c↓-, a↑-, and a↓-domains  direction of the lattice, it is reasonable to conclude that the zE component of the electric field should start the switching process. The field maximum is localized near the tip contact point. The corresponding distributions of the stress and volumetric strain are presented in zE component at (111) plane  simulations of the respective boundary problem a. The sizE component of the electric field and mechanical stress distribution  can be tuned as it is known to affect the distribution of the electric field from the SPM tip and maximize zE in the area near the contact [a-domains, and pure ferroelectric switching is realized for RH > 40% , the formation of the c↓-domain is likely in this area, but a further lateral expansion of the created domain is limited by the radius of the tip/meniscus where the maximum electric field is concentrated. a-domains can propagate at longer distances from the probe due to the much lower threshold field of such polarization reversal. As the SPM tip creates a non-uniform electric field, the threshold voltage for a-domain formation can be evaluated by comparing the average distance of the domain propagation and local values of the electric field at this given distance from the tip. The values of the surface area occupied by the c↓-, a↑-, and a↓-domains for the different humidity conditions were extracted from the experimental dependencies as a maximal distance from the SPM probe (averaged by the three branches), where respective domain structure was formed  cut PMN-PT single crystals. The circular-shaped ferroelectric domain formed immediately underneath the tip, while irregular-shaped ferroelastic domain patterns widely spread tens of microns far from the tip position. The possibility of controlling the switching process using varied relative humidity (RH) levels was demonstrated. For RH > 40%, the switching leads to the formation of the


The Mercator projection map of the world provides a useful, but distorted, view of the relative scale of countries. Current cellular models suffer from a similar distortion. Here, we undertook an in-depth structural analysis of the molecular dimensions in the cell’s computational machinery, the MeshCODE, that is assembled from a meshwork of binary switches in the scaffolding proteins talin and vinculin. Talin contains a series of force-dependent binary switches and each domain switching state introduces quantised step-changes in talin length on a micrometre scale. The average dendritic spine is 1 μm in diameter so this analysis identifies a plausible Gearbox-like mechanism for dynamic regulation of synaptic function, whereby the positioning of enzymes and substrates relative to each other, mechanically-encoded by the MeshCODE switch patterns, might control synaptic transmission. Based on biophysical rules and experimentally derived distances, this analysis yields a novel perspective on biological digital information. The MeshCODE theory proposes that the meshwork of talin and vinculin molecules scaffolding the synaptic junctions  represenvia the protein talin. Talin binds the cytoplasmic tails of integrins via an N-terminal FERM domain  files. Structural models collected from the EMBL AlphaFold2 database , Homo sapiens Talin2 (Q9Y4G6), Caenorhabditis elegans Talin (G5EGK1), Dictyostelium discoideum TalinA (P0CE95), and Danio rerio Talin1 (Q5U7N6) were gathered from UniProt (code in parentheses).To determine protein similarity, we used the NCBI blastp tool available at Talin has a complex mechanical response due to its 13 force-dependent binary switch domains, so we started this study with a detailed structural analysis of the properties of an individual binary switch as this represents a single bit of information in a digital view of a talin molecule.There are two types of talin switch: 4-helix and 5-helix bundles. In the absence of force, each switch exists in a compact, folded, 0 state with dimensions 5 × 2 nm, shown drawn to scale in switch undergoes a 10-fold change in length between the two states (9–11-fold for 4-helix and 10–12-fold for 5-helix switches). To illustrate this extreme change in the dimensions of a switch, Therefore, in the absence of vinculin, a switch opening will transition to a fully extended 1 state. The actual extension will vary, but under tension the contour length from fitting to single-molecule stretching data is ~0.38 nm/residue , relative to each other and their substrates, mechanically-encoded by the MeshCODE switch patterns. Transiently increasing the amount, activity, or localisation of one enzyme relative to the other is a way to ensure specificity of signal transduction at that site.The spatial organisation of enzymatic activity can be achieved via a spine neck region  and Cancer Research UK Program Grant (CRUK-A21671). SB is funded by the Max Planck Guest Scholarship program.


This study investigated the effects of high hydrostatic pressure (HHP) treatment on the physicochemical properties of rice flour according to its moisture levels in order to develop new materials for processed rice foods. The rice varieties used were the Samkwang variety  and the Shingil variety (processing and soft type). The moisture content of the rice flour was adjusted to 35–55% and it was treated with the HHP treatment at 400–600 MPa. The water absorption capacity, solubility, and swelling power of the rice flour increased as the moisture levels and pressure increased. The 600 MPa enzymatic hydrolysis-treated rice flour showed similar results to the heat-treated rice flour. Scanning electron microscopy showed few cavities, resulting in a dense structure. X-ray diffraction confirmed that the 23° peak, which indicates the degree of gelatinization, decreased with increasing moisture levels and pressure. The HHP treatment of the rice flour changed its physicochemical properties according to the moisture levels and pressure applied. These results can provide important information on the development and production of various foods. The high hydrostatic pressure (HHP) treatment is a method of delivering high pressure by sealing liquid or solid food in a flexible container and placing it in a device containing water . HHP treRice (Oryza sativa) is classified into the Indica and Japonica species, and its structure is comprised of the rice husk, pericarp, spermoderm, aleurone layer, endosperm, and embryo . Rice isThe Samkwang  and Shingil (processing type rice) rice varieties were provided by the Rural Development Administration in Korea. The Samkwang variety was wet-milled, and the Shingil variety was dry-milled at the Nongshim Flour Mills  using an air mill , and whole milled rice flour was used. The rice flour was mixed with distilled water to obtain a final moisture content of 35%, 45%, and 55%. The rice flour samples, with the adjusted moisture content, were vacuum-packed in polyethylene film (6 × 16 cm).The rice flour that was vacuum-packed in polyethylene films was subjected to HPP treatment using a high hydrostatic pressure treatment machine  at 400, 500, and 600 MPa for 10 min. The temperature of the pressure chamber was maintained at 25 °C. An HHP treatment machine is a reactor that applies isostatic pressure, using water as the pressure medium without the use of heat or gas. It is comprised of a high-pressure vessel, high-pressure pump, reservoir tank, safety device, alarm system, and control system.The rice flour suspension (rice flour content: 15%) was subjected to heat treatment by incubation in boiling water (100 °C) for 30 min. The heat-treated rice flour was completely gelatinized and used as a control. HHP treatment samples were analyzed in comparison with those subjected to heat treatment.The WAI was measured using the method proposed by Medcalf , with soThe solubility and swelling power were measured using a method modified from Medcalf . The HHPSEM was performed using a method described by Jin , with moX-ray diffraction was measured using a modified method described by Lee et al. . The HHPα-Amylase hydrolysis was measured using the method described by Xue et al. , with soPasting properties were evaluated using the approved AACC  method uAll analyses were repeated three times and expressed as the mean ± standard deviation. Statistical analyses were performed using the SPSS statistical program  to calculate the mean and standard deviation of each treatment group. Significance was tested at the 5% level using Duncan’s multiple range test.The water absorption index of the HHP-treated rice flour is shown in The solubility of HHP-treated rice flour is shown in The SEM images of rice flour subjected to different treatments are shown in The X-ray diffraction patterns of the HHP-treated rice flours are shown in The α-amylase hydrolysis of the HHP-treated rice flour is shown in The pasting properties of the HHP-treated rice flour are shown in This study investigated the effects of HHP treatment on the physicochemical properties of rice flour according to its moisture content to develop new materials for processed rice foods. The water absorption capacity, solubility, and swelling power of rice flour, according to the moisture content and HHP treatment, tended to increase with increases in moisture content and pressure. The 55% moisture content and 600 MPa-treated rice flour subjected to enzymatic hydrolysis showed similar results as those subjected to heat treatment. Few cavities were observed in the microstructure (SEM), resulting in a dense structure when the moisture content or pressure was low, and the starch granules collapsed and gelatinized as the moisture content and pressure increased. It was confirmed that the 23° peak, indicating the degree of gelatinization, decreased with increasing moisture content and pressure. The gelatinization temperature of the Shingil variety was significantly higher than that of the Samkwang variety, and its viscosity was low. The physicochemical properties of the HHP-treated rice flour changed according to the moisture levels and pressure. These results provide important information on the development and production of various foods.


Gastric neoplasms with fundic gland differentiation include oxyntic gland adenomas (OGAs) and gastric adenocarcinomas of fundic gland type (GA-FGs). Due to their well-differentiated and similar morphology with normal fundic glands, it is usually challenging to identify these lesions in pathological diagnosis, especially in biopsy specimens. This study aims to explore and verify the potential role of a newly developed monoclonal antibody (McAb) NJ001 (SP70) in differentiating fundic neoplasms from non-neoplastic fundic gland lesions.Twenty-three cases of histological confirmed gastric fundic gland neoplasms were obtained, including 12 cases of OGAs and 11 of GA-FGs. Fifty cases of fundic gland polyps (FGPs) were taken as the control group. Six cases of well-differentiated gastric neuroendocrine tumors (NETs) (easily misdiagnosed) were also obtained. Key clinicopathological information was collected. SP70 immunostaining was performed . The positive intensity and staining pattern of SP70 were analyzed and compared.P<0.0001). There was no difference in SP70 expression between OGAs  and GA-FGs  group (P>0.05). In these 6 NET cases, SP70 was weak to moderate intensity in the majority of tumor cells (with a different expression pattern).In normal gastric mucosa, SP70 was strongly and diffusely stained on the cytoplasm in fundic glands, but not in the foveolar epithelium. Therefore, a zonal distribution of SP70 was observed in normal mucosa. FGPs  shared a similar expression pattern with normal fundic glands. In fundic gland neoplasms, a significant down-expression of SP70 was observed in both OGAs and GA-FGs. The positive rate of SP70 in fundic gland neoplasms  was significantly lower than that in FGPs (100%) (Down-expression of SP70 is a specific feature to fundic gland neoplasms including OGAs and GA-FGs. Therefore, SP70 can serve as a potential biomarker in the identification and differential diagnosis of fundic gland neoplasms. Gastric neoplasm with differentiation toward the fundic gland is a novel entity . First dDue to its well histopathological differentiation, the morphological characters of gastric fundic gland neoplasms may resemble to that of normal fundic glands . DespiteSP70 is an antigen of non-small-cell lung cancer (NSCLC) specifically identified by the McAb NJ001 , 14. It Archival paraffin blocks of 23 cases of fundic gland neoplasms were obtained from Zhongshan Hospital, Fudan University , from Jan. 2017 to Dec. 2020, among which 12 cases were OGAs and 11 were GA-FGs. The adjacent normal fundic glands served as an internal control. Six cases of well-differentiated NETs  located in the gastric body were obtained. Fifty cases of FGPs were taken as the control group. The study protocol and the comprehensive written informed consent were assigned.Paraffin-embedded specimens were sectioned and were subjected to immunohistochemistry. Monoclonal antibodies were mouse mAb NJ001 . Besides, the markers for chief cell and parietal cell differentiation were used, including Pepsinogen-I , MUC 6 , MUC 5AC , and H+/K+-ATPase .SP70 was mainly localized in the cellular cytoplasm. Five hundred cells were assessed, and the percentage of SP70 positive cells was counted. The result was assigned as negative when the SP70 positive cells were <5% and ≥5% as positive.Histological features, immunohistochemical staining, and clinicopathological data were assessed. Histopathological reviews and immunohistochemical analysis were performed by three pathologists. Diagnostic criterion takes reference from the 5th edition of WHO classification of gastrointestinal tract tumors (2019) .χ2 test. The P-value <0.05 was significant.SPSS statistics 21.0 was used to carry out statistical analyses. The statistical differences between different groups were compared by the n=9) and corpus ventriculi (n=14) and measured 0.3–2.0 cm in diameter.Histopathological and clinical findings were presented in Table Endoscopic findings showed that 47.8% 11/23) tumors had a protruding type  .Immunohistochemical analysis of SP70 showed diffuse and strong positivity in the normal fundic glands, but not in gastric pit cells Fig. A1 and A2As for these 6 cases of NETs, SP70 expression was weak to moderate intensity in the majority of tumor cells  Fig. .Fig. 5ThSP70 specifically expresses in lung cancer cells, but rare positively or negatively reacts to human small-cell lung cancer (SCLC), pulmonary pseudotumor, and other epithelial tumors . It has SP70 has not been used as a diagnostic biomarker. In this study, we testified and compared the SP70 expression pattern in different lesions, including FGPs, OGAs, GA-FGs, and NETs. Our IHC analysis showed that the SP70 staining pattern of fundic gland neoplasms (OGAs and GA-FGs) differed from that of FGPs and NETs. Unlike diffuse and strong staining in the normal fundic glands and FGPs, as well as a weak to moderate positivity in NETs, a significant down-expression or complete loss of SP70 was observed in OGAs and GA-FGs. These findings indicated that SP70 could be used as a diagnostic biomarker with high sensitivity and specificity for the diagnosis of neoplasms with fundic gland differentiation.SP70, as an auxiliary biomarker, can be very helpful in the diagnosis of gastric neoplasm of the fundic gland differentiation. The challenges in pathological diagnosis lie in: first, it is a relatively rare entity; second, the extremely well differentiation; and third, cytological atypia is mild, despite discernible architectural abnormities. These features easily lead to misdiagnosis in inexperienced hands, especially in biopsy specimens. Particularly, it would be more difficult to discriminate GA-FGs from less commonly dysplastic FGPs (with mild atypia)  and OGAsThe differential diagnosis of fundic gland neoplasms and non-neoplastic lesions is clinically relevant. Although most of GA-FGs appear to show an indolent behavior, a small subset of these tumors with deeper submucosal invasion could transform into poorly differentiated adenocarcinomas , 17, 18.SP70 is the first diagnostic biomarker that can be used to distinguish gastric fundic gland neoplasms from non-neoplastic lesions. Based on the findings, we proposed a diagnosis flow chart which we believe could improve the accuracy and reliability of diagnosing the neoplasms in biopsy specimens. The specimens will be stained with currently used biomarkers including muc6, H+/K+-ATPase, and Pepsinogen-I to confirm the fundic gland differentiation. Subsequently, a diagnosis of a neoplasm or a non-neoplastic lesion can be made based on the expression of SP70 (Fig. There are several limitations. Firstly, its retrospective nature with relatively small sample number; Secondly, OGAs and GA-FGs share similar staining patterns and are not be able to distinguish by SP70. A morphological continuum exists from OGA to GA-FG, and there is an ongoing discussion on whether OGA should be regarded as an intramucosal component of GA-FG. Therefore, these two entities may share identical IHC phenotype and are unnecessary to differentiate them by IHC.In summary, it found that SP70 was strongly and diffused expressed in normal fundic glands and FGPs, while it showed a down-expression or loss of expression in fundic gland neoplasms, including OGPs and GA-FGs. Therefore, the down-expression of SP70 is a specific feature of gastric fundic gland neoplasms. The application of SP70 protein coupled with other fundic gland-associated markers could improve the diagnostic accuracy of neoplastic lesions with fundic gland differentiation. SP70 could be used as a new diagnostic biomarker to identify gastric fundic gland neoplasms.


The advent of stem cell-derived cerebral organoids has already advanced our understanding of disease mechanisms in neurological diseases. Despite this, many remain without effective treatments, resulting in significant personal and societal health burden. Antisense oligonucleotides (ASOs) are one of the most widely used approaches for targeting RNA and modifying gene expression, with significant advancements in clinical trials for epilepsy, neuromuscular disorders and other neurological conditions. ASOs have further potential to address the unmet need in other neurological diseases for novel therapies which directly target the causative genes, allowing precision treatment. Induced pluripotent stem cell (iPSC) derived cerebral organoids represent an ideal platform in which to evaluate novel ASO therapies. In patient-derived organoids, disease-causing mutations can be studied in the native genetic milieu, opening the door to test personalized ASO therapies and n-of-1 approaches. In addition, CRISPR-Cas9 can be used to generate isogenic iPSCs to assess the effects of ASOs, by either creating disease-specific mutations or correcting available disease iPSC lines. Currently, ASO therapies face a number of challenges to wider translation, including insufficient uptake by distinct and preferential cell types in central nervous system and inability to cross the blood brain barrier necessitating intrathecal administration. Cerebral organoids provide a practical model to address and improve these limitations. In this review we will address the current use of organoids to test ASO therapies, opportunities for future applications and challenges including those inherent to cerebral organoids, issues with organoid transfection and choice of appropriate read-outs. In vitro differentiation of iPSCs has allowed the generation of a vast array of cellular subtypes, recapitulating neuronal tissues which have until now been inaccessible  are one of the most widely used approaches for targeting RNA and modifying gene expression. ASOs are single stranded DNA analogs, usually 13–25 bases long, that are designed to hybridize with target genes and have high specificity to pathogenic targets, thus reducing adverse effects associated with off-target effects . ASOs maHowever, major challenges still remain for ASO treatment in neurological disorders, due to rapid degradation, low cellular uptake or undesirable uptake by cell types other than those more affected by disease, and the tight blood brain barrier which blocks the penetration of ASO to the brain .Significant progress has been made in oligonucleotide chemical modification in the last several decades . This haVarious delivery technologies have been developed to promote the delivery and uptake of ASOs in different organs. Nucleic acid carrier systems, also known as nano carriers, have been more widely used for both siRNA and ASOs . These iin vitro systems have yielded important results, however, their two dimensional nature and often single cell type, fails to replicate the complex architecture of the human brain  organoids have significantly advanced our ability to model neurodevelopment of the human brain . Variousin vitro models (reviewed in Fusion of organoids (assembloids) directed toward different brain regions, for example dorsal and ventral telencephalic organoids, have been successfully used to study migration of cortical interneurons, the formation of neural circuits and disruption thereof in disease . For exaOrganoids provide an innovative platform for drug discovery in neurological disease and have successfully been used to test small molecules and repurposed drugs for microcephalies, Zika virus , schizopA small number of studies have thus far used organoids to investigate the effect of ASOs on disease phenotypes. Organoid tumor models have been targeted with ASOs with promising results. Mammary tumor organoids were treated with ASOs targeting transcripts of Mammary Tumor Associated RNAs (MaTARs) achieving 30–68% knockdown . MaTARs MAPT mutant iPSC lines derived from frontotemporal dementia (FTD) patients and corresponding isogenic controls, telencephalic organoids were generated which replicated the selective loss of glutamatergic neurons and early dysfunction of the autophagy-lysosomal pathway observed in 2D neuronal cultures and in vivo  license to any author accepted manuscript version arising.via UCL Consultants for Biogen. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.AM has provided consultancy All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The object detection task usually assumes that the training and test samples obey the same distribution, and this assumption is not valid in reality, therefore the study of cross-domain object detection is proposed. Compared with image classification, the cross-domain object detection task presents the greater challenge, which requires both accurate classification and localization of samples in the target domain. The teacher–student framework (the student model is supervised by pseudo-labels from the teacher model) has produced a large accuracy improvement in cross-domain object detection. Feature-level adversarial training is used in the student model, which allows features in the source and target domains to share a similar distribution. However, the direction and gradient of the weights can be divided into domain-specific and domain-invariant features, and the purpose of domain adaptive is to focus on the domain-invariant features while eliminating interference from the domain-specific features. Inspired by this, we propose a teacher–student framework named dual adaptive branch (DAB), which uses domain adversarial learning to address the domain distribution. Specifically, we ensure that the student model aligns domain-invariant features and suppresses domain-specific features in this process. We further validate our method based on multiple domains. The experimental results demonstrate that our proposed method significantly improves the performance of cross-domain object detection and achieves the competitive experimental results on common benchmarks. With the development of deep neural networks, many computer vision tasks have achieved great success. The convolutional neural network-based object detection has achieved excellent performance on various benchmark datasets. However, these successes also depend on a large amount of labeled data . The colThe common domain adaptive methods include global feature adaptation , instancIn cross-domain object detection task, it generally contains a domain-invariant feature and a domain-specific feature. The domain-invariant feature is expressed as the composition of the object, and the domain-specific feature is expressed as whether the object has clear boundaries. As shown in A desirable domain adaptive method should achieve the alignment of the domain-invariant features. Otherwise, it might have a “negative migration” effect on the target domain. The distribution difference metric function can minimize the difference between source and target domains. We can assume that the domains have the same or similar feature distributions when the difference is sufficiently minimal. However, considering the feature alignment method in this way, we find that it does not distinguish the domain-invariant and domain-specific features of the downstream task. Inspired by the above, we propose to suppress domain-specific features in the model. There is more focus on learning domain-invariant features on higher-level semantic space.In this work, we propose a novel cross-domain object detection network with DAB structure. The purpose is to train a well performing model on a target domain with unknown domain annotations. We use adversarial learning and mutual learning to improve the detection performance of the target domain. Our model consists of two modules: a target-domain teacher model and a cross-domain student model. In the student model, we propose a domain-invariant feature alignment branch and a domain-specific feature suppression branch. A distribution difference measure function that focuses on domain invariant feature alignment while suppressing domain specific features is proposed. We map the features to a high-dimensional space and use discriminators with gradients for adversarial learning which adjusts the distribution differences between the source and target domains in the student model.(1)A novel cross-domain object detection framework with dual adaptive branch is designed, which we called DAB. This framework utilizes two branches, domain-invariant feature alignment branch and domain-specific feature suppression branch, to overcome errors and false positives in cross-domain object detection.(2)The feature alignment branch and feature suppression branch are designed, respectively. With the purpose of domain-invariant feature alignment, we propose to map the features into a high-dimensional space and restrict the gradient using a distribution difference measure function, which minimizes the difference of domain-invariant features between two domains. With the purpose of domain-specific feature suppression, we propose to impose constraints on domain-specific features, which eliminate the influence of domain-specific features on cross-domain object detection.(3)The extensive experiments are conducted on various cross-domain benchmarks, and the experimental results demonstrate that our method achieves a significant performance improvement.The main contributions of this paper are as follows:Object Detection. Early object detection methods were based on the sliding-window methods, which apply the hand-crafted features and classifiers on dense image grids to find objects ,8. HowevCross domain Object Detection. The purpose of cross-domain object detection is to detect objects in different domains. Xu et al.  have proIn summary, these methods have not properly addressed the potential contradiction between shift-ability and discrimin-ability in cross-domain object detectors. Therefore, we propose to design a novel dual adaptive branch, which addresses the domain-invariant feature alignment and domain-specific feature suppression in the cross-domain object detection task.As shown in The source domain image The feature encoder is to ensure that we can construct a feature space of all images, which is used to obtain the feature of the images. The DAB is designed to focuses on domain-invariant feature alignment while suppressing domain-specific feature. Additionally, the detector is used to output the predicted result. In particular, the purpose of the feature alignment branch is to minimize the differences between domain-invariant features using a measure function. The purpose of the feature suppression branch is to eliminate the influence of domain-specific feature.In cross-domain object detection, we have We set the feature of the source domain sample as Firstly, we map the features in the source and target domains based on the Gaussian distribution. The mean values with different distributions are calculated by finding a continuous function in the sample space, which is used to evaluate the difference in distribution between the source and target domains, as shown in Equations  and 2)..2).(1)FWe use the Frobenius norm to represent the mean of the samples with different distributions, as shown in Equation .(3)∣∣F^Therefore, the objective function for minimizing the difference in feature distribution can be denoted as Equation .(4)min∣As shown in Therefore, we design Equation .(5)min∣We define the domain adaptive kernel function Equation .(6)KKKLQFSecondly, we train the feature encoder for obtaining the features We design the feature alignment branch to align the domain-invariant feature in source and target domain. We can derive two distributions, the source anchor distribution Equation .(13)LclThe Equation  is used Equation .(14)ELreThe ground truth labels proposed for the target domain are unknown, and we use In the target domain, we train the feature encoder for obtaining the feature With the purpose of feature suppression branch, we measure the differences across domains and suppress the difference of domain-specific feature in source and target domain. The objective function is obtained, as shown in Equation .(16)LreIt is noted that the regression loss in the source domain is defined only for the bounding box corresponding to Equation  guides tEquation  reduces Equation .(17)LreWe perform experiments with popular benchmarks in cross-domain object detection. The details of the datasets are shown in Pascal VOC. It is a dataset collected from the real world and can be used for detection and segmentation. For the detection task, it mainly consists of 20 categories containing 2501 training images, 2510 validation images, and 4952 test images.Clipart. It is an artistic image created by manual production. Clipart contains 1000 images in a total of 20 categories.Watercolor. It contains watercolor style images, which consist of images from six categories.DT Clipart. It uses CycleGAN for style migration, which converts the Pascal VOC dataset to the style of the Clipart dataset. Therefore, the annotation information is identical to the original Pascal VOC dataset.Cityscapes. It is a semantic segmentation dataset consisting of 2975 training images, 500 validation images, and 1525 test images, each with a size of 1024 × 2048. Each image is annotated at pixel level and can be used for target detection tasks after conversion. The datasets are all urban scenes of different cities under normal weather, and the target objects are mainly pedestrians, vehicles, etc.Foggy Cityscapes. It is created by adding synthetic fog into the Cityscapes dataset. Therefore, the annotation information is exactly the same as the original Cityscapes dataset.We evaluate our method in two adaptation scenarios.Dissimilar domains. The purpose is to perform adaptation under dissimilar domains. Firstly, we use the Pascal VOC and Clipart as the source and target domains, respectively. The results are presented on the Clipart val set . Secondly, we use the Pascal VOC and DT Clipart as the source and target domains, respectively. The results are presented on the DT Clipart test set .Adverse weather. The purpose is to perform adaptation under different weather conditions. We use the Cityscapes and Foggy Cityscapes as the source and target domains, respectively. The results are presented on the Foggy Cityscapes val set (Cityscapes → Foggy Cityscapes).The source code and models were trained and evaluated on the Pytorch toolbox, which is based on the Python 3.6 platform. All experiments were implemented on a NVIDIA RTX 3090Ti GPU. We train the network with a batch size of 16. We use an initial learning rate of 0.125 and a decay rate of 0.1 every 400 K steps. The different scales of detection correspond to different perception fields, and there are a total of 10,647 proposal boxes. We transform the training set in the model by data augmentation, which enriches the training set and enhances the generalization ability. The four images are randomly cropped and scaled, and then randomly arranged and stitched to form a single image. While enriching the dataset, the data of four images are calculated at once during the normalization operation. Therefore, the memory requirement of the model is reduced.Firstly, we have reported the adaptive experiments on dissimilar domains. We use the Pascal VOC dataset as the source domain and the Clipart dataset as the target domain. Source only indicates a model trained with only source domain data, and oracle indicates a model trained with labeled data from the source and target domains. The FA branch only denotes the method with feature alignment branch only, FS branch only denotes the method with feature suppression branch only, and Proposed Method denotes the method with DAB.As shown in Although in the experiments mentioned above, our method does not perform best in some categories, such as . However, we can observe that their differences of average precision is actually not large, and the detection performance of Proposed Method outperforms the method using only feature alignment branch (FA branch only) and only feature suppression branch (FS branch only) in these categories. Additionally, with the confusion matrix in In addition, we use the Pascal VOC dataset as the source domain and the DT Clipart dataset as the target domain. As shown in We will further evaluate the generalization ability of our model on unknown domains. We trained the model on the source domain dataset with labels (PASCAL VOC) and another artistic dataset without labels (Watercolor). Then, we inferred the model on a target dataset (Clipart), which is unknown during training. We only trained the overlapping classes (six classes) between Clipart1k and Watercolor, and the results are given in Compared with AT  and MT , our modWe have reported the experimental results of domain adaptive object detection under adverse weather condition. Source only indicates a model trained with only source domain data, and oracle indicates a model trained with labeled data from the source and target domains.The FA branch only denotes the method with feature alignment branch only, FS branch only denotes the method with feature suppression branch only, and Proposed Method denotes the method with DAB.The confusion matrix for the source only method and our method are shown in In this study, we investigate the performance of various strategies for aligning feature representations. We have used Pascal VOC → Clipart to conduct the study. For a fair comparison, all experiments have been performed under the same settings.Trade-off parameter. Firstly, we investigate the effect of different trade-off parameters for the performance in domain adaptive object detection. We present the results of the ablation experiments for the trade-off parameter in We can observe that the trade-off parameter of EXP.2 achieves optimal performance. Both Scales. There is a potential scale shift between the source and target domain datasets. To investigate the effect of image scale on our method, we have changed the size of the image in the target domain, and the scale in the source domain is fixed at 640 pixels. We have plotted the detection performance at different image scales by changing the scales of the target domain images. The FA branch only denotes the method with feature alignment branch only, FS branch only denotes the method with feature suppression branch only, w/o DAB denotes the method without the DAB, and Proposed Method denotes the method with DAB.As shown in Comparing the two branch, we observe that the feature alignment branch is more robust to scale variation than the feature suppression branch. The reason is that scale variation is a global shift that affects all objects and backgrounds. While, in our method, the global domain shift is mainly solved by feature alignment branch to domain-invariant feature alignment, and the feature suppression branch is used to constraint domain-specific feature. When a significant global domain shift is present, the localization error is increased, and therefore the accuracy of the feature suppression branch is affected by the error in the domain-specific feature. Nevertheless, DAB consistently provide the optimal results at all scales.Conv kernel. The depth of the model might affect the performance of feature extraction. To investigate the effect of different model depths for our method, we conduct experiments with different convolution kernel conditions. The reported results are set with Pascal VOC → Clipart. We conducted experiments at the same image scale as shown in We can observe that the EXP.5 obtained the optimal performance, the Branch structure. To verify the effectiveness of our dual adaptive branch structure, we have performed a set of ablation studies. The reported results are set with Pascal VOC → Clipart. The results of the different experiments are shown in We use Proposed Method as the baseline. It can be observed that Proposed Method outperforms FA branch only in To create a meaningful distribution of errors and identify the components of the mAP, we separated all false positives and false negatives of model with four types. We will represent the overlap between the maximum IoU of a false positive and the ground truth of a given category as IoUmax. The foreground IoU threshold is denoted as ectively . IoUmax≥The error ratios for each model on Pascal VOC → Clipart are shown in In this work, we address the domain shift in high-level semantic features by proposing a novel DAB structure. The purpose of domain adaptation is to focus on domain-invariant features and to eliminate the interference of domain-specific features. Therefore, we propose feature alignment and feature suppression branches, respectively. The effect of feature shift is eliminated by this strategy, which reduces the probability of false positives and errors in detection. Specifically, we exploit a distribution difference metric function to improve prediction consistency. It allows the model to focus on the object-relevant features aligned in the high-level semantic space. Experimental results on the common benchmarks indicated that our model achieves a comparable performance with advanced methods, achieving 48.4% mAP and 47.4% mAP, outperforming the next best methods by +1.8% and +4.3%, respectively. The experimental results also indicated that our detector is highly robust in different scales, which is very effective and advantageous in cross-domain object detection.


Acylation of diverse carbohydrates occurs across all domains of life and can be catalysed by proteins with a membrane bound acyltransferase-3 (AT3) domain (PF01757). In bacteria, these proteins are essential in processes including symbiosis, resistance to viruses and antimicrobials, and biosynthesis of antibiotics, yet their structure and mechanism are largely unknown. In this study, evolutionary co-variance analysis was used to build a computational model of the structure of a bacterial O-antigen modifying acetyltransferase, OafB. The resulting structure exhibited a novel fold for the AT3 domain, which molecular dynamics simulations demonstrated is stable in the membrane. The AT3 domain contains 10 transmembrane helices arranged to form a large cytoplasmic cavity lined by residues known to be essential for function. Further molecular dynamics simulations support a model where the acyl-coA donor spans the membrane through accessing a pore created by movement of an important loop capping the inner cavity, enabling OafB to present the acetyl group close to the likely catalytic resides on the extracytoplasmic surface. Limited but important interactions with the fused SGNH domain in OafB are identified, and modelling suggests this domain is mobile and can both accept acyl-groups from the AT3 and then reach beyond the membrane to reach acceptor substrates. Together this new general model of AT3 function provides a framework for the development of inhibitors that could abrogate critical functions of bacterial pathogens. The fatty membrane that surrounds cells is an essential feature of all living things. It is a selective barrier, only allowing certain substances to enter and exit the cell, and it contains the proteins and carbohydrates that the cell uses to interact with its environment. In bacteria, the carbohydrates on the outer side of the membrane can become ‘tagged’ or modified with small chemical entities which often prove useful for the cell. Acyl groups, for example, allow disease-causing bacteria to evade the immune system and contribute to infections persisting in the body.As a rule, activated acyl groups are only found inside the cell, so they need to move across the membrane before they can be attached onto the carbohydrates at the surface. This transfer is performed by a group of proteins that sit within the membrane called the acyltransferase-3 (AT3) family. The structure of these proteins and the mechanism by which they facilitate membrane crossing have remained unclear.Salmonella typhimurium. The experimental data used by the team included information about which parts of OafB are necessary for this protein to acylate carbohydrates molecules.Newman, Tindall et al. combined computational and structural modelling techniques with existing experimental data to establish how this family of proteins moves acyl groups across the membrane. They focused on OafB, an AT3 protein from the foodborne bacterial pathogen In their experiments, Newman, Tindall et al. studied how different parts of OafB move, how they interact with the molecules that carry an acyl group to the membrane, and how the acyl group is then transferred to the carbohydrate acceptor. Their results suggest that AT3 family proteins have a central pore or hole, plugged by a loop. This loop moves and therefore ‘unplug’ the pore, resulting in the emergence of a channel across the membrane. This channel can accommodate the acyl-donating molecule, presenting the acyl group to the outer surface of the membrane where it can be transferred to the acceptor carbohydrate.The AT3 family of proteins participates in many cellular processes involving the membrane, and a range of bacterial pathogens rely on these proteins to successfully infect human hosts. The results of Newman Tindall et al. could therefore be used across the biological sciences to provide more detailed understanding of the membrane, and to inform the design of drugs to fight bacterial diseases. Acyl_transf_3, AT3) domain  containing proteins are found in all domains of life. These membrane-bound AT3 proteins are involved in acylation of a wide range of extracytoplasmic and surface bacterial polysaccharides  and OatA from S. aureus (an AT3-SGNH), respectively. Analysis by Salmonella ser. Typhimurium  are able to hydrolyse the acetyl group from acetyl-CoA and transfer it to the peptidoglycan-like acceptor substrate, effectively observing the entire catalytic cycle in vitro , where acetyl groups were shown to be required to elicit bactericidal antibodies  simulations. This model is integrated with the existing x-ray structure of the SGNH domain and published mutational data to allow additional structure-function analysis. Utilising both classical MD simulations and quantum mechanical calculations, we consider the acetyl donor and acceptor substrates to generate a refined functional model for this important family of membrane proteins.Herein, we use RaptorX to determine a computationally derived structure for the transmembrane region, including the 10-TMH AT3 domain, of OafB. We show this novel structure to be stable under physiological conditions Salmonella rhamnose O-acetyltransferase (OafB). This method has been successfully validated with numerous proteins , OatA from L. monocytogenes (OatA-LM), and PglI from Neisseria gonorrhoeae (PglI-NG) all closely resembled the OafB , WecH from Escherichia coli (WecH-EC), and IcaC from S. aureus (IcaC-SA) were analysed    similarlophilus) . Consistophilus) , in contophilus) .E. coli inner membrane in 150 mM KCl solution. When subjected to MD simulations of 50 and 100 ns at 320 and 303 K, respectively, the protein model remained stable within the membrane. There was no significant unfolding observed; secondary structure analysis indicates that the alpha-helical segments of the transmembrane domain are maintained throughout, and the RMSD of the protein backbone remained below 0.5 nm at both temperatures  was embedded in a model eratures . The rooeratures . Togethe3 can be observed in the AT3 protein on the cytoplasmic side, which is enclosed by TMH 1, 2, 9, and the unstructured loop between TMH 5 and 6  and both sit on the periplasmic face of the membrane. However, Glu334 is located on the cytoplasmic side very distant from His25 and Tyr194, suggesting that it is not part of a catalytic triad.In addition, Jones et al. performed site-directed mutagenesis on a number of residues in OatA from . aureus . These i. aureus . It is t. aureus , is invo. aureus . Similar. aureus , allowinTogether this mapping suggests two important sites in the protein, a mid-membrane region of positive charge created by three conserved Arg residues and a potential catalytic site on the periplasmic surface comprising at least His25 and Tyr194. In the RaptorX model, these two features of the protein are physically separated by the loop 3–4 region . During 3. To test this hypothesis, one molecule of acetyl-CoA was pulled into this channel (entrance delimited by the N-terminus and TMH9 and 10) from the cytoplasmic entrance of the AT3 domain of a hybrid full-length OafB model (assembly discussed in the following section) using steered MD (SMD). It was found that this channel could indeed accommodate acetyl-CoA ; these interactions are shown in Furthermore, energy decomposition analysis (EDA) using ONETEP  indicateWe calculated the electrostatic potential of the transmembrane domain and acetyl-CoA and found them to be complementary: the transmembrane domain displayed positive potentials, while the acetyl-CoA displayed negative potentials, of similar magnitudes . The greα-C dihedral angles  to generate proteins with differing relative conformations of the AT3 and SGNH domains . To investigate the flexibility of the hybrid structure, we used equilibrium MD simulations (see Methods).To learn more about the function of the model OafB proteins, which requires both the AT3 domain and its linked SGNH domain to function, we first constructed a hybrid structure that combined the RaptorX-predicted structure of the transmembrane domain (residues 1–376) with the x-ray crystal structure (380–640) of the SGNH-ext (380–421) and the SGNH domain (422–640). Residues 377–379 were added to the N-terminus of the SGNH domain using MODELLER 10.0 , and a px: the SGNH-ext remains structured and packed close to the SGNH domain throughout the 4×250 ns simulations, indicating this fold is stable under physiological conditions. Unfolding of the SGNH-ext to generate a longer flexible linker - such as that seen in the RaptorX-predicted structures of OatA-LM and OatA-SA - is not observed.The x-ray crystal structure of the SGNH-ext region of OafB   shows itA short stretch of only around 10 residues (residues ~370–380) remains that could form a flexible linker between the transmembrane and periplasmic domains. Indeed in the MD simulations, the periplasmic domain exhibits a wide range of orientations relative to the transmembrane domain . PrincipDespite these motions and the range of relative orientations, the SGNH and AT3 domains were not observed to spontaneously interact in the equilibrium simulations. This does not necessarily mean that the domains do not interact in vivo; given the short timescales of MD simulations and the vast conformational space available to the protein, sampling all possible conformations is an intractable problem. To direct computational efforts to the conformational space of interest, elastic network bonds were applied to pull the transmembrane and periplasmic domains together.x by pulling the periplasmic and transmembrane domains towards each other. The ‘bonds’ were added between residues likely to be proximal to one another as identified through coevolution analysis (see Methods). Around 75% of co-evolving residues have heavy atoms  within 5 Å of one another (x proteins resulted in the rapid and irreversible ‘closing’ of the protein (the closed state), for the duration of the simulation time that the elastic network bonds were applied.Elastic networks are a set of artificial harmonic ‘bonds’ added to a molecular model. These are commonly used in coarse-grained models to maintain the secondary structure of molecules ; here, w another . The sid100 system  of the subsequent equilibrium simulations revealed a minimum of 35 unique hydrogen bonds between the periplasmic and transmembrane domains across each simulation. When averaged across all four simulations, the number of hydrogen bonds between the two domains at any given time was 3.16±1.67 . Three o0 system  but do n0 system . Taken t3 and includes both the SGNH catalytic triad comprising residues Asp618, His621, and Ser430  would interact with open and closed ‘pedal bin’ model of OafB, working with two alternative hypotheses that the acceptor is presented either as a single or multiple O-antigen repeat unit(s) anchored to a lipid carrier or later after transfer to the lipid A core molecule.3 is an order of magnitude greater than the volume of the LPS O-antigen unit (volume of ~502 Å3); hence, one or more units could be manually placed within the cavity  in the membrane, which is then flipped placing the O-antigen unit in the periplasm. Lipid-linked O-antigen units are assembled to the final length in the periplasm before ligation to lipid A-core. Subsequently, the completed LPS molecule is transported to the outer membrane , meaning it is possible that the substrate diffuses laterally into the cavity, either with the pedal bin open or closed.To contextualise the OafB models with biologically relevant molecules, a system containing one molecule of the lipid carrier Und-PP attached to a single O-antigen unit was placed next to the OafB model . A distaThe analysis above suggests that acetylation could occur using single O-antigen units, before O-antigen polymerisation. Alternatively, acetylation occurs during or after polymerisation on the Und-PP carrier before transfer to the lipid A core (not shown). The distance of multimers of 9 Å (single O-antigen unit) stretching away from the membrane could possibly be accommodated by the open state of the pedal bin with the SGNH domain extending into the periplasm.Salmonella LPS was generated in CHARMM-GUI’s LPS Modeler and inserted into the periplasmic leaflet of the OafB100 system . Initially the modelled LPS adopts a quasi-linear conformation; the z-separation between the rhamnose moiety and the periplasmic membrane surface was found to be ~42 Å, as shown in 100 and the periplasmic leaflet is ~35 Å; hence, it is not inconceivable that the open pedal bin could function to deliver acetyl groups at a distance from the membrane. However, we note that in reality the full length O-antigen will be attached to the lipidA core, which would require significant, entropically unfavourable conformational rearrangement of the O-antigen for OafB to catalyse significant overall levels of O-acetylation across the whole polymer.To investigate the final model of acetylation after assembly onto the lipid A core, we built a model with LPS (with one O-antigen unit) and OafB-SPA embedded in the inner membrane, to assess the distances defined between the periplasmic leaflet surface and various groups within the system relevant to the acetylation . One molSMD was used to pull the rhamnose moiety of LPS and Ser 430 of OafB towards one another, and subsequent restrained MD simulations held the protein and LPS close to one another to assess possible interactions. Many hydrogen bonds were observed between the O-antigen and the periplasmic domain of OafB over the two replicates. Several of these were with residues from the SGNH-ext . Tyr389 and Tyr394 are both residues which were previously identified by FTMap in silico docking analysis as involved in binding to rhamnose sugars. Hydrogen bonding was also observed between the 3’ and 2’ hydroxy groups of the rhamnose moiety and Ser430. Even when all position restraints were removed in the MD simulations, this interaction persisted for a further 10 ns.Together these analyses indicate that O-acetylation of the O-antigen may occur either when a single O-antigen unit attached to a lipid carrier is presented in the periplasm, or when the O-antigen is polymerized, either on the lipid carrier, or when attached to the lipid A core.S. aureus  to conceivably be involved in catalysis, although the MD simulations cannot capture bond making or breaking (nor proton transfer). The loop between TMH 5 and 6, in which Tyr194 resides, shows significant mobility and the side chain of Tyr194 is observed to point inwards, towards the centre of the pore (and therefore towards acetyl-CoA). Given the conformational mobility of the 4’-phosphopantetheine segment of the coenzyme, and of the loop between TMH 5 and 6, it is not unreasonable to suggest that the thioester bond is accessible to both His25 and Tyr194 to aid the acetyl transfer in a mechanism such as that suggested by Bacteroidetes bacteria , mediating acylation of a diverse range of complex carbohydrates, has a novel fold. The stability of this structure was confirmed using MD simulations, which also enabled insights into the mechanism of action of AT3 domains. Importantly, for the first time, our model provides a solution to the problem of acetylation occurring in the periplasm using the cytoplasmic acetyl donor acetyl-CoA. We show a membrane-spanning pore occurs transiently in the AT3 domain which can accommodate acetyl-CoA, presenting the acyl group to the periplasmic side. This part of our model is supported by quantum-level calculations to probe the hypothesised protein-acetyl-CoA interactions, and the presence of key, conserved and essential residues that line the pore. The second cavity at the periplasmic side in OafB is able to accommodate the acceptor substrate O-antigen. Together, our data give important new insights into the family of AT3 domain containing proteins. Our well-supported model can support and drive targeted research to gain a full understanding of the mechanism of action of this family or membrane-bound acyltransferase proteins that mediate acylation of complex carbohydrates across the domains of life.OafB protein sequence (Uniprot accession A0A0H2WM30) was submitted to either the RaptorX contact prediction server  or AlphaAll simulations used the GROMACS simulation package (version 2020.3) . ResultsAtomistic simulations used the CHARMM36m forcefield  with theE. coli inner membrane: a symmetric bilayer of 18:1:1 POPE, POPG, and 1’,3’-bis[1-palmitoyl-2-oleoyl-sn-glycero-3-phospho]glycerol (cardiolipin). The bilayer system was subsequently solvated in 0.15 M KCl. The system was energy minimised in 5000 steps using the steepest descent method  was generated using the RaptorX webserver . Using tt method . The subP = 5.0 ps, compressibility of 4.5×10–5 bar–1).Each system was equilibrated using two NVT  phases followed by four NPT (isothermic-isobaric ensemble) phases. Details for the position restraints used are in α-C dihedral angle; values of 80, 100, 120, and 140° were used to give structures with different relative orientations of the two domains. The Cα-C-N-Cα dihedral was maintained at 170°. These proteins will henceforth be referred to as OafBx, where x is the C-N-Cα-C dihedral angle .The RaptorX transmembrane domain model and periplasmic domain crystal structure (PDB ID: 6SE1) were used to build a full OafB model. Missing linker residues (residues 377–379) were modelled into the N-terminus of the SGNH domain using MODELLER 10.0 . A peptiE. coli inner membrane model and solvated in the CHARMM-GUI membrane builder as described for the RaptorX model. Systems were energy minimised in 5000 steps using steepest descent algorithm, and subsequently, equilibrated using the protocol described above.The transmembrane domain of each model was embedded in an –1 nm–2) were generated between the alpha carbons of 10 residue pairs, identified through coevolution analysis, to be more than 50% likely to be proximal to one another  until the z-separation of the two groups was 0 (7.5 ns).A short SMD simulation was used to insert acetyl-CoA into the pore . Pulling at a rate of 0.5 nm nsThree variations on the final frame of the SMD were generated in VMD by rotating and translating acetyl-coA within this pore to use as starting conformations for equilibrium MD. These systems were energy minimised using the steepest descent algorithm to resolve steric clashes, and equilibrated as described above, with additional position restraints  on the aSalmonella spp. LPS was generated using the CHARMM-GUI LPS modeller (O9-4 core with one O-antigen unit). Using VMD as a tool to guide positioning, two POPE and two POPG molecules were removed from the periplasmic leaflet of the OafB100 system and the LPS lipid A moiety inserted in their place. Eight water molecules were replaced by potassium ions to neutralise the additional negative charge of the LPS. The system was energy minimised in 5000 steps via the steepest descent algorithm to resolve steric clashes. The system was equilibrated in six phases, as described for the other atomistic systems.One molecule of –1, the other with a pull rate of 1 nm ns–1; both with a pull force of 500 kJ mol–1). The final frame of each of these trajectories  was used as the starting conformation for three consecutive MD simulations at 303 K, of 20 ns each, with varying position restraints on the protein backbone  and LPS molecule . Hydrogen bond analysis was undertaken in VMD  to assess the interactions between the LPS and the SGNH domain.Steered MD was used to guide the rhamnose moiety of the LPS towards the Serine 430 residue  and the acetyl-CoA molecule were calculated in a vacuum using the linear-scaling density functional theory package, ONETEP , using tn ONETEP  was used By integrating a range of computational techniques, the authors made an important contribution by generating a structural model for the AT3 domain, which is predicted to adopt a new fold. The key features of the structural model are consistent with the activity of the enzyme as an acyltransferase, with a transmembrane channel that can accommodate an acyl-CoA donor, and an outer cavity formed with a second domain that can accommodate a nascent LPS molecule as substrate. Overall, the study is valuable as it will help stimulate specific experimental analyses that will further evaluate and improve the model for better mechanistic understanding of this class of enzymes. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, one of whom is a member of Our Board of Reviewing Editors, and the evaluation has been overseen by Volker Dötsch as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Josh V Vermaas (Reviewer #2).Thank you for submitting your article "A novel fold for acyltransferase-3 (AT3) proteins provides a framework for transmembrane acyl-group transfer" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1) Clarity of the presentation can be improved, and some results  can be made more robust with alternative simulation or analysis.2) Interaction energies reported need to be placed into the proper context, so that the mechanistic implications can be made clear.For details see the individual comments of the reviewers.Reviewer #1 (Recommendations for the authors):The combination of a broad range of computational models in the study is appropriate and powerful. The only comment/question I have concerns the quantum mechanical calculations, which revealed a very large  interaction energy. While I understand that this represents interaction energy rather than binding (free) energy, and that there are several charged groups involved, the magnitude is rather large. Is this due in part to the fact that calculations were conducted in vacuum?Reviewer #2 (Recommendations for the authors):eLife readership is unlikely to know what exactly MurNAc is, or what part gets acetylated. I think, based on the extensive introduction, that the best guess right now is that this enzyme, or related enzymes, add the acetyl group onto the glucosamine nitrogen (?). These are thought to be cytoplasmic reactions, however, so I am very confused as to where this fits into polysaccharide synthesis overall.I would have benefitted from a reaction diagram detailing the chemistry this enzyme is thought to facilitate. The broad Roughly how big is the dataset that is helping RaptorX with coevolutionary analysis? For fun, I ran this through alphafold, and indeed, the only pdb templates AlphaFold picks up on are for the soluble domain. This suggests to me that RaptorX and AlphaFold are basing the structure almost exclusively based on sequence alignments. How many sequences are close enough that the black box structural methods use them as inputs?I would love to see some context around the quantum calculations. -1000kcal/mol sounds impressive, but is completely irrelevant to the actual binding affinity, and the way the discussion is phrased would be highly misleading to a non-computational audience.The SI should have the sequence alignment. You clearly have computed one to know what the offset is between the current protein and other points of comparison listed in the text, but for the reader this is hard to grok the first time through, since we are naturally far less familiar with the protein sequences than you are.Figure S2C is… unfortunate? I know that this is a VMD default visualization using Timeline, but I think we can all agree that it isn't the most professional looking representation for the data. It also argues against the highlighting in S2B, since in S2C I count 13 helical regions, not 11.If you do an analysis that you comment on in the main text, the results should be shown. From page 15: "Principal component analysis (PCA) of the backbone atoms was used to extract the first 2 major motions (accounting for 77% or more of the variance) of the protein in the four equilibrium replicates." What is the sampled spread along these PCA dimensions? Are these even meaningful? In short simulations, this protein cannot really change its conformation, so all the PCA is measuring are the jiggles around the initial structure. The animations, while visually appealing, don't actually quantify the motions claimed in the paper. If this were framed in a more speculative fashion, I think it would be more appropriate, since the simulations are just nowhere close to exhaustive enough to prove or disprove this hypothesis.Page 16, where can I see the occupancies, other than the selected occupancies enumerated in the text? It is not hard to tabulate this similar to what is done in Table 2. Reviewer #1 (Recommendations for the authors):The combination of a broad range of computational models in the study is appropriate and powerful. The only comment/question I have concerns the quantum mechanical calculations, which revealed a very large  interaction energy. While I understand that this represents interaction energy rather than binding (free) energy, and that there are several charged groups involved, the magnitude is rather large. Is this due in part to the fact that calculations were conducted in vacuum?The reviewer is correct that this is, in part, due to the fact the calculation was conducted in vacuum. A clarifying statement has been added in the text (third paragraph of the subsection titled “The AT3 domain facilitates presentation of acyl-CoA molecules to the periplasm”) to reflect that this interaction energy is not a binding free energy, and that the magnitude is of less importance than the fact is energetically favourable (indicated by the negative sign).Reviewer #2 (Recommendations for the authors):I would have benefitted from a reaction diagram detailing the chemistry this enzyme is thought to facilitate.We have added a reaction diagram for OafB as a new Figure 1A, and in the Introduction have clarified the OafB relevant O-antigen is and the O-acetylation reaction.The broad eLife readership is unlikely to know what exactly MurNAc is, or what part gets acetylated. I think, based on the extensive introduction, that the best guess right now is that this enzyme, or related enzymes, add the acetyl group onto the glucosamine nitrogen (?).We thank the reviewer for the detailed interest. We now explicitly include in the introduction, and reiterate this as relevant, that the proteins mediate O-acetylation. The reviewer references MurNAc, a component of peptidoglycan which is O-acetylated by OatA, another bacterial AT3 protein that is mentioned in the Introduction. The model system and focus of this study however is the AT3 protein OafB, not OatA. OafB O-acetylates the O-antigen of the LPS. To enhance clarity further, as outlined in response to the first query, we have added a reaction diagram of the OafB mediated reaction , and explained the O-antigen context of rhamnose acceptor more clearly in the Introduction. We have emphasised that the acylation acceptor molecules for AT3 protein mediated reactions are diverse.These are thought to be cytoplasmic reactions, however, so I am very confused as to where this fits into polysaccharide synthesis overall.The reviewer is correct that many acetylation reactions are cytoplasmic. We have added a sentence in the introduction acknowledging this, (and mention Lipid A acylation since it too is part of the LPS). Importantly, we then contrast that with the reactions mediated by AT3 proteins where the body of evidence supports our working hypothesis that these reactions occur extra-cytoplasmically. Our manuscript under consideration here further strengthens this hypothesis by providing a plausible answer to the problem of a cytoplasmic acetyl group donor for an extra-cytoplasmic reaction.Roughly how big is the dataset that is helping RaptorX with coevolutionary analysis?An alignment of about 10,000 sequences was used.For fun, I ran this through alphafold, and indeed, the only pdb templates AlphaFold picks up on are for the soluble domain. This suggests to me that RaptorX and AlphaFold are basing the structure almost exclusively based on sequence alignments. How many sequences are close enough that the black box structural methods use them as inputs?Alphafold will use tens of thousands of sequences of related proteins to create matrix of co-evolution co-evolved amino acids to calculate the predicted structure, as outlined in the review Skolnick et al., J. Chem. Inf. Model. 2021, 61, 10, 4827–4831. Since our initial submission, Alphafold has gained a lot of attention, has been used many times in the literature, and has gone through multiple iterations. It is now a well-established and widely accepted tool to predict protein structure.I would love to see some context around the quantum calculations. -1000kcal/mol sounds impressive, but is completely irrelevant to the actual binding affinity, and the way the discussion is phrased would be highly misleading to a non-computational audience.A clarifying statement has been added in the text (third paragraph of the subsection titled “The AT3 domain facilitates presentation of acyl-CoA molecules to the periplasm”) to reflect that this interaction energy is not a binding free energy, and that the magnitude is of less importance than the fact it is energetically favourable (indicated by the negative sign).The SI should have the sequence alignment. You clearly have computed one to know what the offset is between the current protein and other points of comparison listed in the text, but for the reader this is hard to grok the first time through, since we are naturally far less familiar with the protein sequences than you are.A sequence alignment has been added as Figure 4-supplement figure 1. Note that this is a smaller alignment than that used in Pearson et al., (2020), only including AT3 modelled in the paper, but in fact this helps identify other conserved motifs possibly involved in the acyl-CoA pore. This is referenced and discussed in subsection titled “The AT3 domain from OafB has a cavity lined with essential residues forming a putative acetyl-CoA binding site”.Figure S2C is… unfortunate? I know that this is a VMD default visualization using Timeline, but I think we can all agree that it isn't the most professional looking representation for the data.This refers to what is now Figure 3- supplement figure 1C. We agree it is perhaps not the prettiest way to represent the data. However, this representation does effectively convey the secondary structural features as a function of time, and is widely used and accepted in the field. Articles published in journals such as Molecular BioSystems (DOI: 10.1039/C4MB00212A), Biomolecules (DOI: 10.3390/biom3010168), Immunologic Research (DOI: 10.1007/s12026-020-09130-y), and Nature Scientific Reports (DOI: 10.1038/srep41087) use this presentation, and as such we do not feel it necessary to change this figure.It also argues against the highlighting in S2B, since in S2C I count 13 helical regions, not 11.The reviewer is correct that there are 13 helices present in the transmembrane domain. However, only 11 of these are transmembrane helices, as depicted in Figure 1D. A clarifying sentence has been added to the caption of Figure 3- supplement figure 1C to reflect this: “13 helices are maintained across the simulation, 11 of which are transmembrane.”If you do an analysis that you comment on in the main text, the results should be shown. From page 15: "Principal component analysis (PCA) of the backbone atoms was used to extract the first 2 major motions (accounting for 77% or more of the variance) of the protein in the four equilibrium replicates." What is the sampled spread along these PCA dimensions?The percentage variance explained by each eigenvector has been tabulated and added to the manuscript (new Table 1).Are these even meaningful? In short simulations, this protein cannot really change its conformation, so all the PCA is measuring are the jiggles around the initial structure.Whilst we agree with the reviewer that the structured regions (AT3 and SGNH domains) are unlikely to change their conformations over the short timescales sampled, here we are referring to the motion about a flexible linker which itself does not have well-defined secondary structure. This linker allows the SGNH domain to explore a large volume in the periplasm, even in the short simulations. We have added a new figure, presented as Appendix 1-Figure 1 (since we do not think we can link figures to videos). Here, every 5th frame of a simulation has been overlaid to display the different relative orientations of the SGNH and transmembrane domains. We extended these simulations to 500 ns each, and found the first two major motions to be the same as those identified in the 250 ns simulations.The animations, while visually appealing, don't actually quantify the motions claimed in the paper. If this were framed in a more speculative fashion, I think it would be more appropriate, since the simulations are just nowhere close to exhaustive enough to prove or disprove this hypothesis.The videos show a qualitative view of the first two major motions – a pedal-bin lid type motion is shown in Video 1, and a rotation about the linker is shown in Video 2. To strengthen the explanation of these two motions we have included a figure with the porcupine plots (Appendix 1- figure 2). The two most extreme conformations observed in the trajectories along eigenvectors 1 and 2 were selected, and the transmembrane domain of each conformation superimposed. Porcupine plots were generated to show the direction of motion of the periplasmic domain α carbons between the two conformations along each of the selected eigenvectors. The spines indicate the magnitude and direction of these motions, and match those described in the text and shown in the animations.Page 16, where can I see the occupancies, other than the selected occupancies enumerated in the text? It is not hard to tabulate this similar to what is done in Table 2.A table containing these data has been added (new Table 2).


The quenching constants of HDADE by TNP, HBAPB, and HBPDA by p-NP are 6.29 × 104, 2.17 × 105, and 2.48 × 105 L·mol–1, respectively. The LODs of TNP and p-NP are 1.19 × 10−11, 6.91 × 10−12, and 6.05 × 10−12 mol·L−1. Their sensitivities increase with the linker length, which is better than the corresponding COFs composed of rigid linkers. There is only a photoinduced electron transfer mechanism in the fluorescence quenching of HBPDA by p-NP. Meanwhile, the mechanisms of photoinduced charge transfer and resonance energy transfer exist in the fluorescence quenching of HDADE by TNP and the fluorescence quenching of HBAPB by p-NP.Nitrophenols are important nitroaromatic compounds, both important environmental pollutants and dangerous explosives, posing a devastating danger and pollution threat to humans. It is vital to detect efficiently trace nitrophenols in the environment. In this contribution, a series of fully flexible cyclotriphosphazene-based COFs , prepared with both a flexible knot and flexible linkers of different lengths, were used for sensing 2,4,6-trinitrophenol (TNP) and  Nitrophenols, as a category of phenolic nitroaromatic compounds (NACs), have been in universal use in the intermediates of herbicide, pesticide, dyes, antiseptic, plastics, pharmacy, and other chemicals ,2. Becaup-Nitrophenol (p-NP) has been one of the most commonly used phenols worldwide for the manufacture of analgesics, dyes, and pesticides and for leather processing, thus attracting attention to public safety and environmental issues [p-NP’s lifetime health advisory (LHA) level in drinking water has been identified to be 60 µg L−1 [p-NP has high stability and solubility in aqueous medium and is one of the most harmful water pollutants. Not only does p-NP cause severe environmental problems, but it is also carcinogenic or genotoxic to mankind and wildlife [l issues ,3,4,5. Bp-NP and TNP is important for pollution control [2,4,6-Trinitrophenol (TNP) is both used as a powerful explosive and one of the environmental pollutants ,8. As th control .p-NP and DNP mainly consist of spectrophotometry, high-performance liquid chromatography (HPLC), surface-enhanced Raman spectroscopy, electrophoresis, gas chromatography-mass spectroscopy (GC-MS), mass spectrometry, and electrochemical methods [The traditional detection methods currently reported for trace  methods ,6. Among methods ,12, for  methods ,14.p-NP are relatively rare [The covalent organic frameworks (COFs) are emerging porous organic materials consisting of strong covalent bond connections between light elements . As one of the essential components of porous organic polymer (POP) in long-range ordered crystalline states, COFs have attracted widespread attention and developed fleetly since COFs were first discovered by Yaghi et al. in 2005 . Their hely rare .COFs, like conjugated microporous polymers (CMPs), and their building blocks are predominantly conjugated rigid units. Most COF structures containing rigid C=N bonds, while giving fixed-size regular pores and channels, cannot optimize the superiorities of both an active site and a functional group. To make full use of regular pores and a material uniform position in practice, a few flexible COFs are synthesized with the merits of elastic and adaptive ability ,32,33. Mp-NP, TNP, and other starting materials and chemicals were bought from Aladdin Co., Shanghai, China.FFCP COFs, HDADE, HBAPB, and HBPDA were synthesized, respectively with NOP-6-CHO- as a node, DADE, BAPB, and BPDA as linkers in our previous work  and are 13C NMR spectra of COFs were kept an account of by a Bruker Digital Avance III HD 400 WB (400 MHz) NMR spectrometer. Elemental analyses were performed on a Vario EL III CHN cube  elemental analyzer. TGA was performed with a CDR-4P TGA Thermal Analyzer under a N2 atmosphere from room temperature to 800 °C with a heating rate of 10 °C min−1. Powder X-ray diffraction (PXRD) analyses of COFs were performed on a Bruker AXS D8 Discover X-ray diffractometer in a 2θ range from 1.5° to 40°. The surface morphology of the materials was analyzed by scanning an electron microscope (SEM) on a S-3400 N microscope instrument. All the COFs were degassed at 100 °C for 6 h under vacuum before the analysis. The surface areas of the COFs were calculated with the Brunauer-Emmett-Teller (BET) and Langmuir model in the Rouquerol plots. The pore size distributions of the COFs were obtained from N2 isotherms in accordance with the nonlocal density functional theory (NLDFT) method.UV-VIS spectra were carried through on a Shimadzu UV-2501PC instrument. Fluorescence spectra were recorded on an LS55 spectrophotometer (PerkinElmer). IR spectral analyses were performed on KBr pellets using an iS50 FTIR instrument. Solid-state ex1. obtain the emission peak position λem1 and then use the emission wavelength λem1. In turn, the wavelength λex2 of the excitation peak was as excitation wavelength for doing emission spectrum. This is repeated until λem is obtained using the excitation wavelength λex, which is consistent with λex obtained using the emission wavelength λem. The final test yielded the solid-state excitation and emission spectra of the COF material.The COF material is fully ground and carefully loaded into the small device . Wipe the small device around and put it into the fluorescence spectrophotometer for testing the solid state fluorescence spectrum. First, set an excitation wavelength λ0. Gradually add the analyte, and take its fluorescence intensity at the maximum wavelength as I. The analyte solution volumes are added not more than 100 μL to avoid errors. The I0/I and analyte concentration curve was made, and the slope of the straight line part is the quenching constant.The fluorescence quenching conditions, such as the solvent, polymer concentration, excitation wavelength, scanning speed, slit width, and response time, were optimized, after which the fluorescence quenching experiments were performed. The fluorescence spectrum was measured by taking 2 mL of COF dispersion in a cuvette at a certain excitation wavelength, slit width and scanning speed, and the fluorescence intensity at the maximum absorption wavelength in the emission spectrum was taken as Ip-NP solution (0.1 mol L−1) was added into the volumetric flask to make the concentration of TNP or p-NP in the system 7.5 × 10−5, 5.0 × 10−5 mol L−1, or 7.5 × 10−5 mol L−1. The volumetric flask was shaken to make sure that the whole dispersion mixed well. Then, 2 mL dispersion was taken out into a cuvette to measure its fluorescent spectrum. That is the first cycling test. Afterward, the dispersion was retrieved. The whole dispersion was centrifuged, and the residual solid was washed successively with hot ethanol to remove the guest molecules of TNP or p-NP completely. The regenerated HDADE, HBAPB, or HBPDA was dispersed in 25 mL ACN, THF, or DOX in the volumetric flask to repeat the second cycling test. In the cycling test, it is important to make sure that the concentration of dispersion used for conducting the fluorescent spectrum was at the same level (1 mg mL−1), so we amplified the amount of the sample in this procedure to reduce the experimental error.An amount of 25 mg of HDADE, HBAPB, or HBPDA was dispersed in 25 mL ACN, THF, or DOX in a volumetric flask and stirred overnight to form well-distributed dispersion. Then, 2 mL dispersion was taken out into a cuvette to make a fluorescent measurement. After the measurement, the dispersion was carefully retrieved to the volumetric flask, and 18.75 μL or 12.5 μL TNP or 13C NMR, 39 The elemental analysis of HDADE and HBAPB showed that the contents of H were inconsistent experimental and theoretical values, which is a common phenomenon in porous organic polymers. It is because of the error caused by calculating the elemental contents by not considering the unreacted end groups or caused by inadequate combustion during elemental analysis. UV–VIS spectra indicated that the FFCP COFs extended the conjugated properties on their frameworks. However, the conjugacy of the FFCP COFs was lower than that of rigid-linker COFs [The structures of the obtained FFCP COFs were analyzed and characterized using Fourier-transform infrared spectra FTIR, , solid sker COFs ,36,39,412·g−1, which were higher than those of the rigid-linker COFs , acetonitrile (ACN), tetrahydrofuran (THF), ethanol (EtOH), and chloroform) on the fluorescence performance of the FFCP COFs (1.0 mg mL−1) at room temperature [We investigated the effects of different solvents , perature . For HDAperature ,46. HDADperature ,48,49,50perature ,53,54,55−5 mol L−1 TNP was mixed with 1.0 mg mL−1 ACN dispersion of HDADE, or 5.0 × 10−5 mol L−1p-NP was mixed with 1.0 mg mL−1 THF dispersion of HBAPB, or 7.5 × 10−5 mol L−1p-NP was mixed with DOX dispersion of HBPDA; their fluorescence was immediately quenched. The initial fluorescence intensities decreased substantially over time and remained unchanged after that [p-NP in real time [p-NP are because the π electrons can move rapidly in the conjugated networks, and the porous network structures allow TNP and p-NP to diffuse rapidly and approach the action sites on the networks [ter that . It is seal time . The insnetworks .p-NP, TNP, 2,4-dinitrotoluene (DNT), m-nitrophenol (m-NP), 2,4-dinitrophenol (DNP), 2-nitrophenol (o-NP), para-dinitrobenzene (p-DNB), nitrobenzene (NB), p-nitrotoluene (p-NT), and m-dinitrobenzene (m-DNB). The degree of reduction in the fluorescence intensity was related to the property of the NACs [p-NP quenched the fluorescence of HBAPB and HBPDA. The fluorescence intensities continued to decrease as the concentrations of TNP or p-NP increased (SV) of the TNP for HDADE, p-NP for HBAPB, and HBPDA were calculated from Stern-Volmer equations to be severally 6.29 × 104, 2.17 × 105, and 2.48 × 105 L mol−1, was similar to the other COF-based sensors . These NACs include the NACs . In thesncreased . The que sensors  [25,27,5p-NP were 1.19 × 10−11, 6.91 × 10−12, and 6.05 × 10−12 mol L−1 , LOD = 3 S/ρ, where S is the standard deviation and ρ is the slope of the S–V curve, that is, the Ksv value. The LODs for TNP and  mol L−1 , which aosensors  [8,58,59−5 mol L−1) to the 1.0 mg mL−1 ACN dispersion of HDADE, the fluorescence intensity of HDADE was significantly affected by TNP; DNT, m-DNB, and p-DNB had relatively some impact on the fluorescence intensity of HDADE; and other NACs showed relatively small fluorescence quenching of HDADE, which suggested that HDADE has some fluorescence sensing selectivity for TNP. The addition of the same concentration of NACs (5.0 × 10−5 mol L−1) to the 1.0 mg mL−1 dispersion of THF-HBAPB or DOX dispersion of HBPDA showed that p-NP greatly affected the fluorescence intensities of HBAPB and HBPDA, and TNP affected the fluorescence intensity of HBAPB. Other NACs have the relatively small fluorescence quenching of HBAPB and HBPDA, indicating a high fluorescence sensing selectivity for p-NP  and the highest occupied molecular orbital (HOMO) of the FFCP COFs and NACs  were synthesized with flexible NOP-6-CHO as the junction and flexible DADE, BAPB, and BPDA as the connecting agent. FFCP COFs have high thermal and chemical stability and are microporous materials of the crystalline structure. HDADE, HBAPB, and HBPDA exhibit excellent fluorescence performance in some organic solvent dispersions. HDADE, HBAPB, and HBPDA can sense TNP and


After the development of Cameleon, the first fluorescence resonance energy transfer (FRET)-based calcium indicator, a variety of FRET-based genetically encoded biosensors (GEBs) have visualized numerous target players to monitor their cell physiological dynamics spatiotemporally. Many attempts have been made to optimize GEBs, which require labor-intensive effort, novel approaches, and precedents to develop more sensitive and versatile biosensors. However, researchers face considerable trial and error in upgrading biosensors because examples and methods of improving FRET-based GEBs are not well documented. In this review, we organize various optimization strategies after assembling the existing cases in which the non-fluorescent components of biosensors are upgraded. In addition, promising areas to which optimized biosensors can be applied are briefly discussed. Therefore, this review could serve as a resource for researchers attempting FRET-based GEB optimization. Aequorea victoria and having it exogenously expressed in cells (After successful cloning of green fluorescent protein (GFP) originating from in cells , researcin cells . GEB is in cells . The advin cells . In thisFRET is a physical phenomenon of non-radiative energy transfer between two close chromophores with spectral overlap; an emission spectrum of donor fluorophore overlaps an excitation spectrum of acceptor fluorophore . When a Researchers have mainly optimized their biosensors using the following strategies. The first tactic is to adapt the improved FPs to their GEBs. The early FPs constituting the FRET pair, mainly cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP), have many disadvantages. The acceptor YFP has poor resistance to low pH and photostability . In the Here, we introduce several optimization strategies based on how the non-fluorescent components of FRET-based GEBs were refined by many researchers. At the end of this review, there is a brief introduction to fields where biosensors were newly applied as GEBs have been improved. Before starting this review, we define the components that compose a biosensor and have been optimized as follows . The senThe sensor domain, which directly interacts with cellular players to induce the conformational change of GEBs, plays a key role in the biosensor’s target sensing ability . To optiBiosensors can be optimized by increasing the affinity of the sensor domain to the target molecule. To produce an optimized FRET GEB detecting cyclic adenosine monophosphate (cAMP) with exchange protein directly activated by cAMP1 (EPAC1), Klarenbeek et al. examined several fluorescent protein pairs and residues in the sensor domain . In partBiosensors that measure kinase activity mainly use truncated peptide sequences, including phosphorylatable residues as the sensor domain. Recently, a case using a platform that combines FRET-seq, a method coupling FRET signals to next-generation sequencing (NGS), and mammalian cell libraries to increase the affinity of a consensus peptide to target kinase was reported . The fir2+ with high affinity was removed via the E104Q mutation , contains a calmodulin (CaM) in which one component reacting to Camutation . As a red) of 2 μM for maltose. To expand the range of the biosensor for maltose measurements, tryptophan residues of MBP were mutagenized to alanine to decrease substrate affinity  as the sensor domain . The priaffinity . FLIPmal2+ probe family uses two Zap1 zinc fingers as the sensor domain. One WT zinc finger detects Zn2+ using two cysteines and two histidines  to detect Ca to Mg2+ . Mank etdynamics .Depending on which ligand domain is included in the biosensor that measures kinase activity, amino acids around the phosphorylatable residue can be substituted to increase the affinity between the sensor and ligand domains. EKAREV, an extracellular signal-regulated kinase (ERK) activity biosensor, uses the WW domain as a ligand domain to detect phosphothreonine (pThr) . To incrBacillus subtilis FoF1-ATP synthase as sensor domain  status, uses ε subunit of r domain . However of 25°C . In 2013 20–25°C .2+, the efficiency of the biosensor was improved by adding one more sensor domain, and the advanced biosensor was called TN-XXL , and YFP. . BetweenCiona intestinalis as the sensor domain  originating from r domain . In 2012r domain . ResearcEscherichia coli as its sensor domain , can be derived from various proteins . Each SH2+ concentration in the CaM-rich regions such as the plasma membrane of neurons (2+ (Kd = 60 μM) and was not significantly affected by large concentrations of excess CaM. In 2006, Designs 2, 3, and 4 were released  value of the fluorescent protein pair was 8.3 nm, 1.5–1.7 times longer than that of the normal CFP-YFP pair. Therefore, a relatively longer linker was used to separate fluorescent proteins.In the case of the NIR-Rac1  biosensoIn the case of the Booster-PKA  biosensoIn the case of a linker-connected type, unimolecular biosensor (UnimB), because the ligand and sensor domains move together at a relatively constant distance, the sensor response is more constant than that in the separated type, bimolecular biosensor (BimB), in which the distance between domains is not constant and the possibility of interaction with endogenous proteins induces the noise in the FRET signal. In addition, because the unimolecular Biosensor is expressed from single vector, accurate measurement of FRET is possible because all compartments show the same expression level and are located in the same region  Figure .There are cases where the optimization was performed as UnimB using a linker because BimB did not react. An increase in the emission intensity of the acceptor by EGF treatment was observed when the PTB-EYFP/EGFR-ECFP bimolecular  biosenso2+ indicator, CFP-Atox1 and WD4-YFP, Van Dongen et al. compared the FRET ratio in each case by inserting two to nine GGSGGS repeat sequences between Atox1 and WD4, the metal-binding domains. Each biosensor had a unique Kd value and FRET ratio change range. In particular, CA-L2-WY containing (GGSGGS)2 showed the most remarkable FRET ratio change upon Zn2+ stimulation , YC2.60, and YC3.60 , had a sTension-sensing FRET biosensors are biosensors developed to measure various tensions within cells. To measure the physical force, these types of sensors use elastic linkers. Therefore, the linker itself acts as a force-sensing sensor domain. By modifying these linkers, researchers have diversified the range of force measurements.8, which is an elastic linker derived from spider silk protein. To adjust the force measurement range, Brenner et al. developed TSMod F25 and TSMod F50  activities depend on the plasma membrane microdomain  into the N-terminal of ZifCY1  . Drug scBy adding the function of the “activator” to the FRET-based GEB, it is possible to visualize the activity of the target player and manipulate the physiology of cells simultaneously. Sun et al. created the Shp2-integrated sensing and activating protein (Shp2-iSNAP), which not only detects the phosphorylation of SIRPα, a receptor of CD47 transmitting “don’t eat me” signal but also inhibits the SIRPα downstream signal with protein tyrosine phosphatase included in biosensor sequence . When boIn this review, we introduced examples where researchers have optimized biosensor components independently of FPs, and these are summarized in