Membrane remodeling due to mixture of multiple curvature proteins We present an extension of the Monte Carlo based mesoscopic membrane model, where the membrane is represented as a dynamically triangulated surface and the proteins are modeled as anisotropic inclusions formulated as in-plane nematic field variables adhering to the deformable elastic sheet. In the extended model, we have augmented the Hamiltonian to study membrane deformation due to a mixture of multiple types of curvature generating proteins. This feature opens the door for understanding how multiple kinds of curvature-generating proteins may be working in a coordinated manner to induce desired membrane morphologies. For example, among other things, we study membrane deformations and tubulation due to a mixture of positive and negative curvature proteins as mimics of various proteins from BAR domain family working together for curvature formation and stabilization. We also study the effect of membrane anisotropy, which manifests as membrane localization and differential binding affinity of a given curvature protein, leading to insights into the tightly regulated cargo sorting and transport processes. Our simulation results show different morphology of deformed vesicles that depend on the curvatures and densities of the participating proteins as well as on the protein-protein and membrane-proteins interactions.

SignificanceMembrane remodeling requires highly orchestrated interactions between several types of lipids and curvature proteins. Experimentally probing the membrane deformation intermediates is non-trivial. For example, it is not known exactly how two or more different kinds of BAR domain proteins work in concert to induce and stabilize certain membrane curvatures. In this work, we use mesoscopic continuum modeling and explore the factors that induce and stabilize a range of membrane deformation due to a mixture of positive and negative curvature proteins.
Membrane-catalyzed aggregation of islet amyloid polypeptide is dominated by secondary nucleation Type II diabetes is characterized by the loss of pancreatic {beta}-cells. This loss is thought to be a consequence of membrane disruption, caused by the aggregation of islet amyloid polypeptide (IAPP) into amyloid fibrils. However, the molecular mechanisms of IAPP aggregation in the presence of membranes have remained unclear. Here, we use kinetic analysis to elucidate the aggregation mechanism of IAPP in the presence of mixed zwitterionic and anionic lipid membranes. The results converge to a model in which aggregation on the membrane is strongly dominated by secondary nucleation, i.e. the formation of new nuclei on the surface of existing fibrils. The critical nucleus consists of a single IAPP molecule, and anionic lipids catalyze both primary and secondary nucleation, but not elongation. The fact that anionic lipids promote secondary nucleation implies that these events take place at the interface between the membrane and existing fibrils, demonstrating that fibril growth occurs at least to some extent on the membrane surface. These new insights into the mechanism of IAPP aggregation on membranes may help to understand IAPP toxicity and will be important for the development of therapeutics to prevent {beta}-cell death in type II diabetes.
A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. Tatajuba -- Exploring the distribution of homopolymer tracts Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialised bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source license GNU GPL version 3 from https://github.com/quadram-institute-bioscience/tatajuba. Coupled myovascular expansion directs cardiac growth and regeneration BackgroundHeart regeneration requires multiple cell types to enable cardiomyocyte (CM) proliferation. How these cells interact to create growth niches is unclear. Here we profile proliferation kinetics of cardiac endothelial cells (CECs) and CMs in the neonatal mouse heart and find that they are spatiotemporally coupled.

Methods and ResultsWe show that coupled myovascular expansion during cardiac growth or regeneration is dependent upon VEGF-VEGFR2 signaling, as genetic deletion of Vegfr2 from CECs or inhibition of VEGFA abrogates both CEC and CM proliferation. Repair of cryoinjury displays poor spatial coupling of CEC and CM proliferation. Boosting CEC density after cryoinjury with virus encoding Vegfa enhances regeneration. Using Mendelian randomization, we demonstrate that circulating VEGFA levels are positively linked with human myocardial mass, suggesting that Vegfa can stimulate human cardiac growth.

ConclusionsOur work demonstrates the importance of coupled CEC and CM expansion and reveals a myovascular niche that may be therapeutically targeted for heart regeneration. Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. Mitochondrial genomes of two parasitic Cuscuta species lack clear evidence of horizontal gene transfer and retain unusually fragmented ccmFC genes BackgroundThe intimate association between parasitic plants and their hosts favours the exchange of genetic material, potentially leading to horizontal gene transfer (HGT) between plants. With the recent publication of several parasitic plant nuclear genomes, there has been considerable focus on such non-sexual exchange of genes. To enhance the picture on HGT events in a widely distributed parasitic genus, Cuscuta (dodders), we assembled and analyzed the organellar genomes of two recently sequenced species, C. australis and C. campestris, making this the first account of complete mitochondrial genomes (mitogenomes) for this genus.

ResultsThe mitogenomes are 265,696 and 275,898 bp in length and contain a typical set of mitochondrial genes, with ten missing or pseudogenized genes often lost from angiosperm mitogenomes. Each mitogenome also possesses a structurally unusual ccmFC gene, which exhibits splitting of one exon and a shift to trans-splicing of its intron. Based on phylogenetic analysis of mitochondrial genes from across angiosperms and similarity-based searches, there is little to no indication of HGT into the Cuscuta mitogenomes. A few candidate regions for plastome-to-mitogenome transfer were identified, with one suggestive of possible HGT.

ConclusionsThe lack of HGT is surprising given examples from the nuclear genomes, and may be due in part to the relatively small size of the Cuscuta mitogenomes, limiting the capacity to integrate foreign sequences. Honeycomb crystallography: comb formation under geometric frustrations 1As honeybees build their nests in pre-existing tree cavities, they must deal with dealing with the presence of geometric constraints, resulting in non-regular hexagons and topological defects in the comb. In this work, we study how bees adapt to their environment in order to regulate the comb structure. Specifically, we identify the irregularities in honeycomb structure in the presence of various geometric frustrations. We 3D-print experimental frames with a variety of constraints imposed on the imprinted foundations. The combs constructed by the bees show clear evidence of reoccurring patterns built by bees in response to specific geometric frustrations on these starter frames. Furthermore, using an experimental-modeling framework, we demonstrate that these patterns can be successfully modeled and replicated through a simulated annealing process, in which the minimized potential is a variation of the Lennard-Jones potential that only considers first-neighbor interactions according to a Delaunay triangulation. Our simulation results not only confirm the connection between honeycomb structures and other crystal systems such as graphene, but also show that irregularities in the honeycomb structure can be explained as the result of local interactions between honeybees and their immediate surroundings, leading to emergent global order. Additionally, our computational model can be used to describe specific strategies that bees use to effectively solve each geometric mismatch problem while minimizing cost of comb building. Intermittent compression increases flow through a gel: a mechanical model perhaps relevant to flow of cerebrospinal fluid Exchange of molecules between cerebrospinal fluid (CSF) and brain cells contributes to brain function and protection from dementia. Despite widespread acceptance of the  glymphatic theory, the route by which CSF is brought close enough to the neural tissue for solutes to be exchanged by extracellular diffusion is not entirely clear. Exogenous molecules injected into CSF are observed to reach the basement lamina that surrounds the dense capillary network. Transport of solutes by diffusion along the basement lamina, a gel of macromolcules about 100 nm thick, would be too slow; bulk flow in a static geometry would require unphysiologically high pressures. However, it is known that the pulsation of blood aids transport of CSF, and we hypothesized that this is because the pulsation intermittently squeezes the pericapillary lamina. In a primitive mimicry, we have tested whether intermittent squeezing increases flow through an agar gel. In all but one of 216 tests, pulsation caused a reversible increase, sometimes by a factor of 100 or more. The enhancement was greatest for frequencies 5-11 Hz and, over the tested range of pressure heads (20 - 50 cmH2O), was greatest for the lowest pressure. The results suggest a reason why exercise slows the aging of the brain. Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits Despite the growing number of genome-wide association studies (GWAS), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWAS are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate although this is not significant, likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits. Naming of human diseases on the wrong side of history BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Rattus Economicus: A neural model for rational regulation of water-seeking effort in rodents In the laboratory, animals motivation to work tends to be positively correlated with reward magnitude. But in nature, rewards earned by work are essential to survival (e.g., working to find water), and the payoff of that work can vary on long timescales (e.g., seasonally). Under these constraints, the strategy of working less when rewards are small could be fatal. We found that instead, rats in a closed economy did more work for water rewards when the rewards were stably smaller, a phenomenon also observed in human labor supply curves. Like human consumers, rats also showed elasticity of demand, consuming far more water per day when its price in effort was lower. The neural mechanisms underlying such "rational" market behaviors remain largely unexplored. We propose a dynamic utility maximization model that can account for the dependence of rat labor supply (trials/day) on the wage rate (ml/trial), and also predict the temporal dynamics of when rats work. Based on data from mice, we hypothesize that SFOGLUT neurons in lamina terminalis continuously compute the instantaneous marginal utility of voluntary work for water reward, and causally determine the amount and timing of work. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Feline tooth resorption findings from a questionnaire survey on 8115 Finnish cats and a case-control study for a more defined population drawn from the survey Tooth resorption (TR) is one of the most common dental diseases in cats. It is a painful disease characterised by progressive dental destruction, which eventually results in loss of teeth. The aetiology of the disease remains unclear, but associations with old age, breed, other oral and dental diseases, and certain environmental factors have been suspected. We collected health and environmental information of 8115 Finnish cats from 41 breeds through an online survey for cat owners to study TR in Finland with an observational study. The frequency of TR that the owner reported as veterinarian-diagnosed was 3.9% in the entire data (316/8115) and 15% in cats that the owner reported as having veterinarian-diagnosed oral or dental disease (316/2070). We determined the risk factors and breed variation of feline TR by logistic regression with the entire data and a case-control study in a more defined population drawn from the entire data. In the entire data, we defined those cats that the owners had reported as being diagnosed with TR by a veterinarian as TR-cats and compared them to all other cats. In the case-control study, we included only cats with owner-reported veterinarian-diagnosed oral and dental diseases. We defined cats with TR-diagnosis made under sedation as TR-cases. Other veterinarian-diagnosed TR-cats were excluded. Cats with other oral and dental diseases were used as controls. The model with the entire population included 308 TR-cats compared with 7508 cats, and the case-control study included 198 TR-cats and 1683 controls. Although the diagnoses were reportedly made by a veterinarian, the owner answered the survey and might have understood, remembered, or interpreted the diagnoses in a way that could affect the results. The results indicated an increasing risk of TR with age. Dental calculus, gingivitis, and periodontitis were potential risk factors for TR. These findings and the interaction between dental calculus and gingivitis suggest that inflammatory changes caused by dental calculus increase the risk of TR. Keeping food available constantly was a potential protective factor. We found that Cornish Rex, European, and Ragdoll breeds were at higher risk for TR. The observed differences between breeds highlight a genetic contribution. One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction Machine learning (ML) is a key technology to enable accurate prediction of antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two orthogonal problems hinder the current application of ML to antibody-specificity prediction and the benchmarking thereof: (i) The lack of a unified formalized mapping of immunological antibody specificity prediction problems into ML notation and (ii) the unavailability of large-scale training datasets. Here, we developed the Absolut! software suite that allows the parameter-based unconstrained generation of synthetic lattice-based 3D-antibody-antigen binding structures with ground-truth access to conformational paratope, epitope, and affinity. We show that Absolut!-generated datasets recapitulate critical biological sequence and structural features that render antibody-antigen binding prediction challenging. To demonstrate the immediate, high-throughput, and large-scale applicability of Absolut!, we have created an online database of 1 billion antibody-antigen structures, the extension of which is only constrained by moderate computational resources. We translated immunological antibody specificity prediction problems into ML tasks and used our database to investigate paratope-epitope binding prediction accuracy as a function of structural information encoding, dataset size, and ML method, which is unfeasible with existing experimental data. Furthermore, we found that in silico investigated conditions, predicted to increase antibody specificity prediction accuracy, align with and extend conclusions drawn from experimental antibody-antigen structural data. In summary, the Absolut! framework enables the development and benchmarking of ML strategies for biotherapeutics discovery and design.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/451258v2_ufig1.gif" ALT="Figure 1">
View larger version (81K):
org.highwire.dtl.DTLVardef@14295d2org.highwire.dtl.DTLVardef@7a12bdorg.highwire.dtl.DTLVardef@647102org.highwire.dtl.DTLVardef@375112_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical abstractC_FLOATNO The software framework Absolut! enables (A,B) the generation of virtually arbitrarily large numbers of in silico 3D-antibody-antigen structures, (C,D) the formalization of antibody specificity as machine learning (ML) tasks as well as the exploration of ML strategies for paratope-epitope prediction.

C_FIG Highlights- Software framework Absolut! to generate an arbitrarily large number of in silico 3D-antibody-antigen structures
- Generation of one billion in silico antigen-antibody structures reflecting biological layers of complexity that make ML predictions challenging
- Immunological antibody specificity prediction problems formalized as machine learning tasks for which the in silico complexes are immediately usable as benchmark.
- Exploration of machine learning architectures for paratope-epitope interaction prediction accuracy as a function of neural network depth, dataset size, and sequence-structure encoding Mechanisms of splicing substrate definition by modulation of pre-mRNA 3D structural scaffolds Coordination of different serine-arginine-rich (SR) proteins - a class of critical splicing activators - facilitates recognition of the highly degenerate mammalian splice signal sequences against the background sequences. Yet, the mechanistic details of their actions remain unclear. Here we show that cooperative binding of SR proteins to exonic and intronic motifs remodels the pre-mRNA 3D structural scaffold. The scaffold generated by the pre-mRNA-specific combinations of different SR proteins in an appropriate stoichiometry is recognized by U1 snRNP - the 5' splice site recognizing factor. A large excess of U1 snRNP particles displaces majority of the bound SR protein molecules from the remodeled pre-mRNA. A higher than optimal stoichiometry of SR proteins occludes the binding sites on the pre-mRNA, raising the U1 snRNP levels required for SR protein displacement and potentially impeding spliceosome assembly. This novel splicing-related function of U1 snRNP is important for distinguishing the substrate and the non-substrate by U2AF65 - the primary 3' splice site-recognizing factor. Overall, this work elucidates early regulatory steps of mammalian splicing substrate definition by SR proteins. The compound of baicalein, wogonin, and oroxylin-A inhibits EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. Brain deletion of Serf2 shifts amyloid conformation in a mouse model Loss of protein homeostasis accelerates ageing and contributes to age-related brain diseases like Parkinsons and Alzheimers diseases. Disease-specific proteins become aggregation-prone and form amyloid deposits that characterize disease, but the biological mechanisms driving their transition in cells and tissues are poorly understood. MOAG-4/SERF accelerates aggregation and toxicity of disease-related proteins in worm- and cell models. Whether MOAG-4/SERF affects amyloid pathology in brain, however, has remained unknown. Here we show that brain-specific knockout of SERF2 is viable and shifts aggregation in a mouse model for amyloid-beta aggregation. Without affecting amyloid-beta levels, knockout of SERF2 redirects its assembly into structurally and morphologically distinct amyloid fibrils and deposits. Our results show that SERF modifies the structural outcome of the aggregation process in mammalian brain. With structural polymorphisms recently being associated with disease severity and progression, our results may help to understand the molecular basis for structural diversity and find possibilities for structure-based interventions.

HighlightsO_LILoss of SERF2 slows embryonic development and causes perinatal lethality
C_LIO_LISERF2 affects proliferation in a cell-autonomous fashion
C_LIO_LIBrain-specific Serf2 knockout does not affect viability or A{beta} production
C_LIO_LIBrain deletion of Serf2 shifts the amyloid conformation of A{beta}
C_LI Bioinspired Dual-Functional Solid Lipid Nanoformulations for Targeted Drug Delivery and Sustained Release for Enhancement of Potency of Albendazole, an Antihelminthic Drug Targeted delivery has not been achieved for anthelmintic treatment, resulting in the requirement of excess drugs dose leading to side effects and therapeutic resistance. Gastrointestinal helminths ingest lipid droplets from digestive fluid for energy production, development, and defense. Worms habit inspired us to develop biocompatible, oral administrable, bee-wax derived solid lipid nanoparticles (SLN) with excellent drug (albendazole) loading efficiency of 83.3 {+/-} 6.5 mg/g and sustained-release properties (86.4 {+/-} 3.9 % of drug released within 24 h). Rhodamine B-loaded SLN showed time-dependent release and distribution of dye in vivo in Haemonchous contortus. The intestinal sustained-release property was shown by the particles that caused enhancement of albendazole potency for up to 50 folds. Therefore, this formulation has immense potential as an anthelminthic drug delivery vehicle that will not only be able to reduce the dose but will also reduce the drug-induced side effects by enhancing the bioavailability of the drug.

HighlightsO_LIAlbendazole-loaded Solid Lipid Nanoparticles (SLN-A) were formulated using Beeswax as stating material showing high drug loading capacity of 83 mg/g with sustained-release properties and 84 {+/-} 3 % of drug release within 24 h.
C_LIO_LISLN-A particles showed 50 fold enhancement of Albendazole activity against Haemonchous contortus worm.
C_LIO_LIRhodamine B-loaded SLN particles showed the specific uptake and in-vivo sustained release of dye in the worm.
C_LI Living with high potassium: how plants balance nutrient acquisition during K-induced salt stress O_LIHigh potassium (K) in the growth medium is more toxic to plants than Na at similar concentrations. However, the molecular mechanisms underlying plant responses to K-induced salt stress are virtually unknown.
C_LIO_LIWe examined Arabidopsis thaliana and its extremophyte relative Schrenkiella parvula, using a comparative multi-omics approach to identify cellular processes affected by excess K and understand which deterministic regulatory pathways are active to avoid tissue damage while sustaining growth.
C_LIO_LIA. thaliana showed limited capacity to curb excess K accumulation and prevent nutrient depletion contrasting to S. parvula which could limit excess K accumulation without restricting nutrient uptake. Facilitated by a targeted transcriptomic response, promoting nitrogen uptake along with other key nutrients and uninterrupted N assimilation into primary metabolites during excess K-stress allowed S. parvula to boost its antioxidant and osmolyte pools concurrently leading to sustained growth. Antithetically, A. thaliana showed transcriptional responses indicative of a poor balance between stress signaling, increased ROS levels, and reduced photosynthesis, subsequently leading to inhibited growth.
C_LIO_LIThe ability to regulate independent nutrient uptake and a coordinated transcriptomic response to avoid non-specific stress signaling are two main deterministic steps towards building stress resilience to excess K+-induced salt stress.
C_LI Developing High-Affinity Decoy Receptor Optimized for Multiple Myeloma and Diffuse Large B Cell Lymphoma Treatment Recent T Cell therapies have been effective in the treatment of hematological cancers. However, immunotoxicity and treatment relapse pose significant clinical challenges. Here, we revealed distinctive requirement for neutralizing TNF receptor ligands APRIL and BAFF in MM and DLBCL. Furthermore, we investigated the use of BCMA decoy receptor (sBCMA-Fc) as a therapeutic inhibitor of ARPIL and BAFF. While wild-type sBCMA-Fc successfully blocked APRIL signaling with picomolar binding affinity, inhibiting tumor growth in MM models, it lacked efficacy in inhibiting DLBCL progression due to its weak binding for BAFF. To expand the therapeutic utility of sBCMA-Fc, using a protein engineering approach, we generated an affinity enhanced mutant sBCMA-Fc fusion molecule (sBCMA-Fc V3) with 4-folds and 500-folds enhancement in binding to APRIL and BAFF respectively. The sBCMA-Fc V3 clone significantly enhanced antitumor activity against both MM and DLBCL. Importantly, sBCMA-Fc V3 was proven to be a viable clinical candidate by showing adequate toxicity profile and on-target mechanism of action in nonhuman primates.

SUMMARYThis study demonstrates the dichotomous function of APRIL and BAFF in MM and DLBCL, that can be safely targeted by an engineered fusion protein designed to trap APRIL and BAFF with ultra-high binding affinity. Self-assembly of pericentriolar material in interphase cells lacking centrioles AbstractThe major microtubule-organizing center (MTOC) in animal cells, the centrosome, comprises a pair of centrioles surrounded by pericentriolar material (PCM), which nucleates and anchors microtubules. Centrosome assembly depends on PCM binding to centrioles, PCM self-association and dynein{-}mediated PCM transport, but the self-assembly properties of PCM in interphase cells are poorly understood. Here, we used experiments and modeling to study centriole-independent features of interphase PCM assembly. We showed that when centrioles are lost due to PLK4 depletion or inhibition, dynein-based PCM transport and PCM self-clustering are sufficient to form a single compact MTOC, which generates a dense radial microtubule array. Interphase PCM self-assembly depends on {gamma}-tubulin, pericentrin, CDK5RAP2 and ninein, but not NEDD1, CEP152 or CEP192. Formation of a compact acentriolar MTOC is inhibited by AKAP450-dependent PCM recruitment to the Golgi or by randomly organized CAMSAP2-stabilized microtubules, which keep PCM mobile and prevent its coalescence. Linking of CAMSAP2 to a minus-end-directed motor leads to the formation of an MTOC, but MTOC compaction requires cooperation with pericentrin-containing self-clustering PCM. Our data reveal that interphase PCM contains a set of components that can self-assemble into a compact structure and organize microtubules, but PCM self-organization is sensitive to motor-and microtubule-based rearrangement. Local fitness and epistatic effects lead to distinct patterns of linkagedisequilibrium in protein-coding genes Selected mutations interfere and interact with evolutionary processes at nearby loci, distorting allele frequency trajectories and creating correlations between pairs of mutations. A number of recent studies have used patterns of linkage disequilibrium (LD) between selected variants to test for selective interference and epistatic interactions, with some disagreement over interpreting observations from data. Interpretation is hindered by a lack of analytic or even numerical expectations for patterns of variation between pairs of loci under the combined effects of selection, dominance, epistasis, and demography. Here, I develop a numerical approach to compute the expected two-locus sampling distribution under diploid selection with arbitrary epistasis and dominance, recombination, and variable population size. I use this to explore how epistasis and dominance affect expected signed LD, including for non-steadystate demography relevant to human populations. Using whole-genome sequencing data from humans, I explore genome-wide patterns of LD within protein-coding genes. I show that positive LD between missense mutations within genes is driven by strong positive allele-frequency correlations between pairs of mutations that fall within the same annotated conserved domain, pointing to compensatory mutations or antagonistic epistasis as the prevailing mode of interaction within conserved genic elements. LD between missense mutations is reduced outside of conserved domains, as would expected under Hill-Robertson interference. This variation in both mutational fitness effects and selective interactions within proteincoding genes calls for more refined inferences of the joint distribution of fitness and interactive effects, and the methods presented here should prove useful in that pursuit. Differential fate of acellular vascular scaffolds in vivo involves macrophages and T-cell subsets Biological scaffold or implant is a popular choice for the preparation of tissue-engineered organs and has the potential to address donor shortage in the clinics. However, biological scaffolds prepared by physical or chemical agents cause damage to the extracellular matrix by potentially inducing immune responses after implantation. The current study explores an alternative route for the preparation of acellular scaffolds and explores the fate of the prepared scaffolds in a milieu of immune cells following implantation without using immunosuppressant. Using the syngeneic (Lewis male-Lewis female) and allogeneic (Brown Norway male-Lewis female) models and different tissue routes (subcutaneous vs omentum) for transplantation, normal blood vascular scaffolds were implanted which was converted to acellular vascular scaffolds by in vivo natural decellularization at the end of 2 months of observation. We also prepared chemically decellularized acellular scaffolds from normal untreated blood vascular scaffolds using a cocktail of chemicals which was also similarly placed in subcutaneous and omentum sites. Here, we applied in-depth quantitative proteomics along with histology and image analysis to comprehensively describe and compare the proteome of the natural and chemically decellularized scaffold. Our data confirm that site-specific advantages exist in modulating the ECM and regulating the immune responses (macrophage and T cells) following implantation, which possibly led to the production of an acellular scaffold (natural decellularization) under in vivo conditions. The current approach opens up the possibility to create tailor-made acellular scaffolds to build functional blood vessels. In addition, the identification of different tissue sites facilitates differential immune response against the scaffolds. This study provides a rich resource aimed toward an enhanced mechanistic understanding to study immune responses under similar settings in the field of transplantation and regenerative medicine.

Impact statementThe development of a scaffold helps in the preparation of a functional organ in the clinics. In the current study, we prepared an acellular vascular scaffold by utilizing site specific tissue changes and vis-a-vis compared with a conventionally chemically prepared biological scaffold at genomic and protein level, which helped us to identify immunological trigger following implantation. The current study which was carried out without any immunosuppressive agents could help to establish (a) alternative strategies for preparing biological scaffolds as well as (b) implantable sites as potential bioreactors to circumvent any adverse immune reactions for acceptance of the scaffold/implant post implantation. A novel Boolean network inference strategy to model early hematopoiesis aging Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. Energy efficient network activity from disparate circuit parameters Neural circuits can produce similar activity patterns from vastly different combinations of channel and synaptic conductances. These conductances are tuned for specific activity patterns but might also reflect additional constraints, such as metabolic cost or robustness to perturbations. How do such constraints influence the range of permissible conductances? Here, we investigate how metabolic cost affects the parameters of neural circuits with similar activity in a model of the pyloric network of the crab Cancer borealis. We use a novel machine learning method to identify a range of network models that can generate activity patterns matching experimental data, and find that neural circuits can consume largely different amounts of energy despite similar circuit activity. Furthermore, a reduced but still significant range of circuit parameters gives rise to energy-efficient circuits. We then examine the space of parameters of energy-efficient circuits and identify potential tuning strategies for low metabolic cost. Finally, we investigate the interaction between metabolic cost and temperature robustness. We show that metabolic cost can vary across temperatures, but that robustness to temperature changes does not necessarily incur an increased metabolic cost. Our analyses show that, despite metabolic efficiency and temperature robustness constraining circuit parameters, neural systems can generate functional, efficient, and robust network activity with widely disparate sets of conductances.