Dissecting errors of the exogenously-driven and endogenously-driven saccadic tasks in the common marmosets Various saccadic tasks used traditionally in oculomotor research, including both exogenously-driven and endogenously-driven saccades, have been proposed as clinical diagnostic for human movement disorders. Recently, common marmosets have been proven to be a good primate model for these movement disorders. However, whether similar saccadic measurements can be used for marmosets was not tested. Here, we trained three marmosets on the gap task, an exogenously-driven saccadic task, and the oculomotor delayed response (ODR) task, an endogenously-driven saccadic task. We demonstrated that with long-term training, they were able to learn and switch between the two tasks. The marmosets showed undershooting tendency in the gap and both under- and overshooting tendency in the ODR task when they made saccades to the target. We also categorized the error trails into distractive, impulsive, and visuomotor errors, depending on when a false saccade happened concerning the task progression, and interpreted possible causes of errors based on the saccade response time and the task history. Each error category may indicate specific failures in a particular aspect of cognitive or sensorimotor processes. Finally, and critically, we found that saccades from successful trials exhibited the highest saccade peak velocity and the shortest saccade duration comparing to the same saccade amplitude from error trials. Taken together, we showed the potential of training the same marmoset on conflicting oculomotor tasks simultaneously. We documented the baseline performance and compared successful and error trials in both gap and ODR tasks from the same animals. We propose that analyzing the error trials in sync with successful trials could provide a further understanding of the marmosets cognitive and sensorimotor processes in both healthy and disease conditions.
An enhanced inverted encoding model for neural reconstructions Here we present a more interpretable and flexible approach for reconstructing the contents of perception, attention, and memory from neuroimaging data. Our enhanced inverted encoding model (eIEM) incorporates methodological improvements including proper accounting of population-level tuning functions and a trial-by-trial prediction error-based metric where reconstruction quality is measured in meaningful units. Improved flexibility is further gained via eIEMs novel goodness-of-fit feature: for trial-by-trial reconstructions, goodness-of-fits are obtained independently (non-circularly) to prediction error and can be applied to any IEM procedure or decoding metric, resulting in improved reconstruction quality and brain-behavior correlations. We validate eIEM from methodological principles, simulated neuroimaging datasets, and three pre-existing fMRI datasets spanning perception, attention, and working memory. Notably, eIEM is easy to apply and broadly accessible - our Python package (https://pypi.org/project/inverted-encoding) implements eIEM in one line of code - and is easily modifiable to compare performance metrics and/or scale up to more complex models.
Improved AlphaFold modeling with implicit experimental information Machine learning prediction algorithms such as AlphaFold1 and RoseTTAFold2 can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy3-6. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation. Analyses of symbiotic bacterial communities in the plant pest Bemisia tabaci reveal high prevalence of Candidatus Hemipteriphilus asiaticus on the African continent AO_SCPLOWBSTRACTC_SCPLOWMicrobial symbionts are widespread in insects and some of them have been associated to adaptive changes. Primary symbionts (P-symbionts) have a nutritional role that allows their hosts to feed on unbalanced diets (plant sap, wood, blood). Most of them have undergone genome reduction, but their genomes still retain genes involved in pathways that are necessary to synthesize the nutrients that their hosts need. However, in some P-symbionts, essential pathways are incomplete and secondary symbionts (S-symbionts) are required to complete parts of their degenerated functions. The P-symbiont of the phloem sap-feeder Bemisia tabaci, Candidatus Portiera aleyrodidarium, lacks genes involved in the synthesis of vitamins, cofactors, and also of some essential amino-acids. Seven S-symbionts have been detected in the B. tabaci species complex. Phenotypic and genomic analyses have revealed various effects, from reproductive manipulation to fitness benefits, notably some of them have complementary metabolic capabilities to Candidatus Portiera aleyrodidarium, suggesting that their presence may be obligatory. In order to get the full picture of the symbiotic community of this pest, we investigated, through metabarcoding approaches, the symbiont content of individuals from Burkina Faso, a West African country where B. tabaci induces severe crop damage. While no new putative B. tabaci S-symbiont was identified, Candidatus Hemipteriphilus asiaticus, a symbiont only described in B. tabaci populations from Asia, was detected for the first time on this continent. Phylogenetic analyses however reveal that it is a different strain than the reference found in Asia. Specific diagnostic PCRs showed a high prevalence of these S-symbionts and especially of Candidatus Hemipteriphilus asiaticus in different genetic groups. These results suggest that Candidatus Hemipteriphilus asiaticus may affect the biology of B. tabaci and provide fitness advantage in some B. tabaci populations. Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers By using TGIRT-seq, we identified >8,500 short full-length excised linear intron (FLEXI) RNAs in human cells. Subsets of FLEXIs accumulated in a cell-type specific manner, and [~]200 corresponded to agotrons or mirtrons or encoded snoRNAs. Analysis of CLIP-seq datasets identified potential interactions between FLEXIs and >100 different RNA-binding proteins (RBPs), 53 of which had binding sites in [&ge;]30 different FLEXIs. In addition to proteins that function in RNA splicing, these 53 RBPs included transcription factors, chromatin remodeling proteins, and cellular growth regulators that impacted FLEXI host gene alternative splicing and/or mRNA levels in knockdown datasets. We computationally identified six groups of RBPs whose binding sites were enriched in different subsets of FLEXIs: AGO1-4 and DICER associated with agotrons and mirtrons; AATF, DKC1, NOLCI, and SMNDC1 associated with snoRNA-encoding FLEXIs; two different combinations of alternative splicing factors found in stress granules; and two novel RBP-intron combinations, one including LARP4 and PABC4, which function together in the cytoplasm to regulate ribosomal protein translation. Our results suggest a model in which proteins involved in transcriptional regulation, alternative splicing, or post-splicing secondary functions bind and stabilize cell-type specific subsets of FLEXIs that perform different biological functions and have potential utility as biomarkers. Neprosin belongs to a new family of glutamic peptidase family based on in silico evidence Neprosin was first discovered in the insectivorous tropical pitcher plants of Nepenthes species as a novel protease with prolyl endopeptidase (PEP) activity. Neprosin has two uncharacterized domains of neprosin activation peptide and neprosin. A previous study has shown neprosin activity in hydrolyzing proline-rich gliadin, a gluten component that triggers celiac disease. In this study, we performed in silico structure-function analysis to investigate the catalytic mechanism of neprosin. Neprosin sequences lack the catalytic triad and motifs of PEP family S9. Protein structures of neprosins from Nepenthes x ventrata (NvNpr) and N. rafflesiana (NrNpr1) were generated by ab initio methods and comparatively assessed to obtain high-quality models. Structural alignment of models to experimental structures in the Protein Data Bank (PDB) found a high structural similarity to glutamic peptidases. Further investigations reveal other resemblances to the glutamic peptidases with low optimum pH that activates the enzyme via autoproteolysis for maturation. Two highly conserved glutamic acid residues, which are stable according to the molecular dynamics simulation, can be found at the active site of the substrate cleft. Protein docking demonstrated that mature neprosins bind well with potent antigen I-gliadin at the putative active site. Taken together, neprosins represent a new glutamic peptidase family, with a putative catalytic dyad of two glutamic acids. This study illustrates a hypothetical enzymatic mechanism of the neprosin family and demonstrates the useful application of an accurate ab initio protein structure prediction in the structure-function study of a novel protein family. TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. Python-Microscope: A new open source Python library for the control of microscopes Custom built microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a solution that is scalable to complex systems and translatable between components from different manufacturers. Here we report Python-Microscope, a free and open source Python library for high performance control of arbitrarily complex and scalable custom microscope systems. Python-Microscope offers simple to use Python-based tools, abstracting differences between physical devices by providing a defined interface for different device types. Concrete implementations are provided for a range of specific hardware and a framework exists for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architecture choices of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: its integration in user facing projects, namely in the Microscope-Cockpit project; in controlling complex microscopes at high speed while using the Python programming language; and as a microscope simulation tool for software development. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. CellKb Immune: a manually curated database of mammalian hematopoietic marker gene sets for rapid cell type identification Using single-cell RNA sequencing, it is now possible to get the detailed gene expression pattern in each cell for millions of cells in a single experiment under varying conditions. Annotating cells by assigning a type or state to them is important for correct interpretation of results. In spite of current advances in technology, assigning cell types in single-cell datasets remains a bottleneck due to the lack of a comprehensive reference database and an accurate search method in a single tool. CellKb Immune is a knowledgebase of manually collected, curated and annotated marker gene sets representing cell types in the immune response in mouse. It allows users to find matching cell types in literature given a list of genes. We evaluated the contents and search methodology of CellKb Immune using a leave-one-out approach. We further used CellKb Immune to annotate previously defined marker gene sets from a bulk RNA-seq dataset to confirm its accuracy and coverage. CellKb Immune provides an easy-to-use online tool with a reliable method to find matching cell types and annotate cells in single-cell experiments. It is available at https://www.cellkb.com/immune. Embracing imperfection: machine-assisted invertebrate classification in difficult datasets O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.
C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.
C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.
C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the  long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
C_LI Chromosome counting in the mouse zygote using low-invasive super-resolution live-cell imaging In preimplantation embryos, an abnormal chromosome number causes developmental failure and a reduction in the pregnancy rate. Conventional chromosome testing methods requiring biopsy reduce the risk of associated genetic diseases; nevertheless, the reduction in cell number also reduces the pregnancy rate. Therefore, we attempted to count the chromosomes in mouse (Slc:ICR) embryos using super-resolution live-cell imaging as a new method of chromosome counting that does not reduce the cell number or viability. We counted the forty chromosomes at the first mitosis by injecting embryos with histone H2B-mCherry mRNA under conditions by which pups could be obtained; however, the results were often an underestimation of chromosome number and varied by embryo and time point. Therefore, we developed a method to count the chromosomes via CRISPR/dCas-mediated live-cell fluorescence in situ hybridization targeting the sequence of the centromere region, enabling us to count the chromosomes more accurately in mouse embryos. The methodology presented here may provide useful information for assisted reproductive technologies, such as those used in livestock animals/humans, as a technique for assessing the chromosomal integrity of embryos prior to transfer.

Impact StatementLow-toxic super-resolution observation enables chromosome counting in preimplantation embryos without cell collection. A new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice 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. Variation in female songbird state determines signal strength needed to evoke copulation It is the female response to male signals that determines courtship success. In most songbirds, females control reproduction via the copulation solicitation display (CSD), an innate, stereotyped posture produced in direct response to male displays. Because CSD can be elicited in the absence of males by the presentation of recorded song, CSD production enables investigations into the effects of underlying signal features and behavioral state on female mating preferences. Using computer vision to quantify CSD trajectory in female brown-headed cowbirds (Molothrus ater), we show that both song quality and a females internal state predict CSD production, as well as the onset latency and duration of the display. We also show that CSD can be produced in a graded fashion based on both signal strength and internal state. These results emphasize the importance of underlying receiver state in determining behavioral responses and suggest that female responsiveness acts in conjunction with male signal strength to determine the efficacy of male courtship. Inhibitors of ERp44, PDIA1, and AGR2 induce disulfide-mediated oligomerization of Death Receptors 4 and 5 and cancer cell death Breast cancer mortality remains unacceptably high, indicating a need for safer and more effective therapeutic agents. Disulfide bond Disrupting Agents (DDAs) were previously identified as a novel class of anticancer compounds that selectively kill cancers that overexpress the Epidermal Growth Factor Receptor (EGFR) or its family member HER2. DDAs kill EGFR+ and HER2+ cancer cells via the parallel downregulation of EGFR, HER2, and HER3 and activation/oligomerization of Death Receptors 4 and 5 (DR4/5). However, the mechanisms by which DDAs mediate these effects are unknown. Affinity purification analyses employing biotinylated-DDAs reveal that the Protein Disulfide Isomerase (PDI) family members AGR2, PDIA1, and ERp44 are DDA target proteins. Further analyses demonstrate that shRNA-mediated knockdown of AGR2 and ERp44, or expression of ERp44 mutants, enhance basal and DDA-induced DR5 oligomerization. DDA treatment of breast cancer cells disrupts PDIA1 and ERp44 mixed disulfide bonds with their client proteins. Together, the results herein reveal DDAs as the first small molecule, active site inhibitors of AGR2 and ERp44, and demonstrate roles for AGR2 and ERp44 in regulating the activity, stability, and localization of DR4 and DR5, and activation of Caspase 8. Comprehensive analysis of pyroptosis-associated in molecular classification, immunity and prognostic of glioma Integrative analysis was performed in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas to describe the pyroptosis-associated molecular classification and prognostic signature in glioma. Pyroptosis-related genes were used for consensus clustering and to develop a prognostic signature. The immune statuses, molecular alterations and clinical features of differentially expressed genes were analyzed among different subclasses and risk groups. A lncRNA-miRNA-mRNA network was built, and drug sensitivity analysis was used to identify small molecular drugs for the identified genes. Glioma can be divided into two subclasses using 30 pyroptosis-related genes. Cluster 1 displayed high immune signatures and poor prognosis as well as high immune-related function scores. A prognostic signature based on 15 pyroptosis-related genes of the CGGA cohort can predict the overall survival of glioma and was well validated in the TCGA cohort. Cluster 1 had higher risk scores. The high-risk group had high immune cell and function scores and low DNA methylation of pyroptosis-related genes. The differences in pyroptosis-related gene mutations and somatic copy numbers were significant between the high-risk and low-risk groups. The ceRNA regulatory network uncovered the regulatory patterns of different risk groups in glioma. Nine pairs of target genes and drugs were identified. In vitro, CASP8 promotes the progression of glioma cells. Pyroptosis-related genes can reflect the molecular biological and clinical features of glioma subclasses. The established prognostic signature can predict prognosis and distinguish molecular alterations in glioma patients. Our comprehensive analyses provide valuable guidelines for improving glioma patient management and individualized therapy. Natural variants in SARS-CoV-2 S protein pinpoint structural and functional hotspots; implications for prophylaxis and therapeutics strategies In December 2019, a novel coronavirus, termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the cause of pneumonia with severe respiratory distress and outbreaks in Wuhan, China. The rapid and global spread of SARS-CoV-2 resulted in the coronavirus 2019 (COVID-19) pandemic. Earlier during the pandemic, there were limited genetic viral variations. As millions of people became infected, multiple single amino acid substitutions emerged. Many of these substitutions have no consequences. However, some of the new variants show a greater infection rate, more severe disease, and reduced sensitivity to current prophylaxes and treatments. Of particular importance in SARS-CoV-2 transmission are mutations that occur in the Spike (S) protein, the protein on the viral outer envelope that binds to the human angiotensin-converting enzyme receptor (hACE2). Here, we conducted a comprehensive analysis of 441,168 individual virus sequences isolated from humans throughout the world. From the individual sequences, we identified 3,540 unique amino acid substitutions in the S protein. Analysis of these different variants in the S protein pinpointed important functional and structural sites in the protein. This information may guide the development of effective vaccines and therapeutics to help arrest the spread of the COVID-19 pandemic. The cardiac TRPA1 channel drives calcium-mediated mechano-arrhythmogenesis SUMMARY PARAGRAPHMaintenance of cardiac function involves a regulatory loop in which electrical excitation causes the heart to contract through excitation-contraction coupling (ECC),1 and the mechanical state of the heart directly affects its electrical activity through mechano-electric coupling (MEC).2 However, in pathological states such as acute ischaemia that alter early or late electro-mechanical coordination (i.e., disturbances in ECC or repolarisation-relaxation coupling, RRC), MEC may contribute to the initiation and / or sustenance of arrhythmias (mechano-arrhythmogenesis).3 The molecular identity of specific factor(s) underlying mechano-arrhythmogenesis in acute ischaemia, however, remain undefined.4 By rapid stretch of rabbit single left ventricular cardiomyocytes, we show that upon ATP-sensitive potassium channel-induced alterations of RRC, overall vulnerability to mechano-arrhythmogenesis is increased, with mechano-sensitive5-11 transient receptor potential kinase ankyrin 1 (TRPA1) channels12 acting as the molecular driver through a Ca2+-mediated mechanism. Specifically, TRPA1 activation drives stretch-induced excitation and creates a substrate for self-sustained arrhythmias, which are maintained by increased cytosolic free Ca2+ concentration ([Ca2+]i) and spontaneous [Ca2+]i oscillations. This TRPA1-dependent mechano-arrhythmogenesis involves microtubules, and can be prevented by block of TRPA1 or buffering of [Ca2+]i. Thus, in cardiac pathologies with disturbed RRC dynamics and / or augmented TRPA1 activity, TRPA1 may represent an anti-arrhythmic target with untapped therapeutic potential.13-17 Reduced metabolic activity in established Gardnerella spp. biofilms contributes to protection from the bactericidal effects of metronidazole Gardnerella spp. can form biofilm and it has been suggested that failure of antibiotic treatment of bacterial vaginosis and recurrent vaginosis are linked to this property, however no specific mechanisms have been identified. Here, we performed broth microdilution assays to measure the minimum inhibitory concentration (MIC) of metronidazole for thirty-five Gardnerella isolates in one medium in which Gardnerella spp. grow primarily as biofilm and another in which growth is primarily planktonic. The MIC of isolates in the two conditions were highly correlated (R2= 0.69, p <0.001). No significant reduction in viable cell count of 7/9 isolates was observed when established biofilms were exposed to metronidazole at levels double the MIC. Subsequent measurements of metabolic activity in established biofilms formed by a larger collection of 31 isolates showed reduced metabolic activity following treatment with 128 g/ml of metronidazole relative to untreated controls in 27/31 cases. The amount of biofilm produced by Gardnerella isolates was not enhanced by metronidazole exposure, even at sub-MIC levels. Our results suggest that reduced metabolic activity in Gardnerella spp. growing in established biofilms may be a mechanism of protection from the bactericidal effects of metronidazole. The Functional Nanopore Screen: A Versatile High-throughput Assay to Study and Engineer Protein Nanopores in Escherichia coli Nanopores comprise a versatile class of membrane proteins that carry out a range of key physiological functions and are increasingly developed for different biotechnological applications. Yet, a capacity to study and engineer protein nanopores by combinatorial means has so far been hampered by a lack of suitable assays that combine sufficient experimental resolution with throughput. Addressing this technological gap, the Functional Nanopore (FuN) screen now provides a quantitative and dynamic read-out of nanopore assembly and function in E. coli. The assay is based on genetically-encoded fluorescent protein sensors that resolve the nanopore-dependent influx of Ca2+ across the inner membrane of E. coli. Illustrating its versatile capacity, the FuN screen is first applied to dissect the molecular features that underlie the assembly and stability of nanopores formed by the S2168 holin. In a subsequent step, nanopores are engineered by recombining the transmembrane module of S2168 with different ring-shaped oligomeric protein structures that feature defined hexa-, hepta- and octameric geometries. Library screening highlights substantial plasticity in the ability of the S2168 transmembrane module to oligomerize in alternative geometries while the functional properties of the resultant nanopores can be fine-tuned through the identity of the connecting linkers. Overall, the FuN screen is anticipated to facilitate both fundamental studies and complex nanopore engineering endeavors with many potential applications in biomedicine, biotechnology and synthetic biology. Differences in gait stability and acceleration characteristics between healthy young and older females Our aim was to evaluate differences in gait acceleration intensity, variability and stability of feet and trunk between older females and young females using inertial sensors. Twenty older females (OF; mean age 68.4, SD 4.1 years) and eighteen young females (YF; mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics and their variability, as well as trunk stability using the local divergence exponent (LDE). Two-way analysis of variance (including the factors foot and age), Students t-test, and Mann-Whitney U test were used to compare statistical differences of measures between groups. Cohens d effects were calculated for each variable. Foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in mediolateral acceleration, mediolateral and vertical angular velocity of the trunk. Even though we measured healthy older females, these participants showed lower vertical foot accelerations with higher vertical trunk acceleration, lower trunk-foot vertical acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed. Bone marrow haematopoietic stem cells influence liver homeostatic networks and cancer development In fatty liver disease, systemic homeostasis is perturbed. While pre-clinical models are used to understand its pathogenesis, translating this knowledge to patients is difficult. However, by focusing on the most preserved homeostasis systems between species and models, novel disease dimensions can be unearthed. We interrogated core liver gene co-expression networks in a mouse model of liver cancer following dietary challenge. Immunometabolic modules showed temporal changes under the influence of diet duration and aging. The behaviour of immune network in tumours mirrored their counterparts in non-tumour liver. A high immune response network was associated with a lower tumour burden in mice and humans. This module in mice was enriched for genes related to haematopoietic cell differentiation. Consistently, the bone marrow haematopoietic stem and progenitor cells response was reflective of the liver immune response. Linking haematopoiesis to hepatic homeostasis uncovers a hitherto unexplored dimension of tissue crosstalk that can inform pathogenesis. Autophagosomes fuse to phagosomes and facilitate the degradation of apoptotic cells in Caenorhabditis elegans Autophagosomes are double-membrane intracellular vesicles that degrade protein aggregates, intracellular organelles, and other cellular components. During the development of the nematode Caenorhabditis elegans, many somatic and germ cells undergo apoptosis. These cells are engulfed and degraded by their neighboring cells. We discovered a novel role of autophagosomes in facilitating the degradation of apoptotic cells using a real-time imaging technique. Specifically, the double-membrane autophagosomes in engulfing cells are recruited to the surfaces of phagosomes containing apoptotic cells and subsequently fuse to phagosomes, allowing the inner vesicle to enter the phagosomal lumen. Mutants defective in the production of autophagosomes display significant defects in the degradation of apoptotic cells, demonstrating the importance of autophagosomes to this process. The signaling pathway led by the phagocytic receptor CED-1, the adaptor protein CED-6, and the large GTPase dynamin (DYN-1) promotes the recruitment of autophagosomes to phagosomes. Moreover, the subsequent fusion of autophagosomes with phagosomes requires the functions of the small GTPase RAB-7 and the HOPS complex components. Further observations suggest that autophagosomes provide apoptotic cell-degradation activities in addition to and in parallel of lysosomes. Our findings reveal that, unlike the single-membrane, LC3-associated phagocytosis (LAP) vesicles reported for mammalian phagocytes, the canonical double-membrane autophagosomes facilitate the clearance of C. elegans apoptotic cells. These findings add autophagosomes to the collection of intracellular organelles that contribute to phagosome maturation, identify novel crosstalk between the autophagy and phagosome maturation pathways, and discover the upstream signaling molecules that initiate this crosstalk. Protein contact map prediction using multiple sequence alignment dropout and consistency learning for sequences with fewer homologs The prediction of protein contact map needs enough normalized number of effective sequence (Nf) in multiple sequence alignment (MSA). When Nf is small, the predicted contact maps are often not satisfactory. To solve this problem, we randomly selected a small part of sequence homologs for proteins with large Nf to generate MSAs with small Nf. From these MSAs, input features were generated and were passed through a consistency learning network, aiming to get the same results when using the features generated from the MSA with large Nf. The results showed that this method effectively improves the prediction accuracy of protein contact maps with small Nf.