Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding.
First Report of Lactoria cornuta from Karnataka, West coast of India, Role of tropical cyclones in Range Extension India is known for its rich biodiversity and is fortunate to have several endemic species from different classes of vertebrates. India is home to 7.5% of the global fish diversity, with 91 endemic species of ray finned fishes, the actinopterygians. Some fish species have never been reported until recently, one such example is the long-horned Cowfish (Ostracidae), best known for inhabiting only certain areas of the Indo-Pacific oceans. However, this fish has been reported from Bay of Bengal, Costs of Goa and Lakshadweep. This is the first time this fish has been found on the Coasts of Karnataka, west coast of India. Given its morphology, the migration seems highly improbable since it can only endure lethargic swimming. In this article, we have explored the role of other external forces that could have contributed to its range extension in the east and west coast of India. In this paper we are exploring the role of Super Cyclones as a vital force in determining the expansion of its range. The fact of collection longhorn cowfish for the first time from the coast of Karwar coincides with the passage of Cyclone Ockhi on the west coast of India this suggests the possible role of super cyclone in its range extension. A year later, another specimen was recovered from a location very close to the first, which indicates the successful establishment of Lacturia cornuta in its new environment. Related morphometric and meristic studies of our specimens are consistent with previous studies reported in the Bay of Bengal.
Trypanosomal variant surface glycoprotein expression in human African trypanosomiasis patients Trypanosoma brucei gambiense, an extracellular protozoan parasite, is the primary causative agent of human African trypanosomiasis. T. b. gambiense is endemic to West and Central Africa, where it is transmitted by the bite of infected tsetse flies. In the bloodstream of an infected host, the parasite evades antibody recognition by altering the Variant Surface Glycoprotein (VSG) that forms a dense coat on its cell surface through a process known as antigenic variation. Each VSG has a variable N-terminal domain exposed to the host and a less variable C-terminal domain that is partially hidden from host antibodies. Our lab developed VSG-seq, a targeted RNA-seq method, to study VSG gene expression in T. brucei. Studies using VSG-seq to characterize antigenic variation in a mouse model have revealed marked diversity in VSG expression within parasite populations, but this finding has not yet been validated in a natural human infection. Here, we used VSG-seq to analyze VSGs expressed in the blood of 12 patients infected with T. b. gambiense. The number of VSGs identified per patient ranged from one to 14; notably, two VSGs were shared by more than one patient. Analysis of expressed VSG N-terminal domain types revealed that 82% of expressed VSGs encoded a type B N-terminus, a bias not seen in datasets from other T. brucei subspecies. C-terminal types in T. b. gambiense infection were also restricted. These results demonstrate a bias either in the underlying VSG repertoire of T. b. gambiense or in this subspecies expression of VSGs during infection. This work demonstrates the feasibility of using VSG-seq to study antigenic variation in human infections and highlights the importance of understanding VSG repertoires in the field.

Author SummaryHuman African Trypanosomiasis is a neglected tropical disease primarily caused by the extracellular parasite Trypanosoma brucei gambiense. To avoid elimination by the host, these parasites repeatedly replace their dense surface coat of Variant Surface Glycoprotein (VSG). Despite the important role of VSGs in prolonging infection, VSG expression during natural human infections is poorly understood. A better understanding of natural VSG gene expression dynamics can clarify the mechanisms that T. brucei uses to alter its VSG coat and improve how trypanosomiasis is diagnosed in humans. We analyzed the expressed VSGs detected in the blood of patients with trypanosomiasis. Our findings indicate that parasites in both natural and experimental infections express diverse sets of VSGs. Excitation and emission spectra of in silico red-shift predicted iLOV mutants iLOV is a flavin mononucleotide-binding fluorescent protein used for in vivo cellular imaging similar to the green fluorescent protein. To expand the range of applications of iLOV, spectrally tuned red-shifted variants are desirable to have reduced phototoxicity and better tissue penetration. In this report, we experimentally tested two iLOV mutants, iLOVL470T/Q489K and iLOVV392K/F410V/A426S, which were previously computationally proposed by Khrenova et al. (DOI: 10.1021/acs.jpcb.7b07533) to have red-shifted excitation and emission spectra. We found that mutants bearing the V392K mutation lost the ability to bind FMN. While iLOVL470T/Q489K is about 20% brighter compared to WT iLOV in vitro, it exhibits a blue shift in contrast to QM/MM predictions. Additionally, both mutants are expressed at low levels and have undetectable fluorescence in living cells, which prevents their utilization in imaging applications. Our results suggest that rational fluorescent protein design efforts can benefit from in silico protein stability and ligand affinity calculations. Characterization of methylation profiles in spontaneous preterm birth placental villous tissue Preterm birth is a global public health crisis which results in significant neonatal and maternal mortality. Yet little is known regarding the molecular mechanisms of idiopathic spontaneous preterm birth, and we have few diagnostic markers for adequate assessment of placental development and function. Previous studies of placental pathology and our transcriptomics studies suggest a role for placental maturity in idiopathic spontaneous preterm birth. It is known that placental DNA methylation changes over gestation. We hypothesized that if placental hypermaturity is present in our samples, we would observe a unique idiopathic spontaneous preterm birth DNA methylation profile potentially driving the gene expression differences we previously identified in our placental samples. Our results indicate the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern suggesting hypermaturity. Only seven significant differentially methylated regions fitting the idiopathic spontaneous preterm birth specific (relative to the controls) profile were identified, indicating unusually high similarity in DNA methylation between idiopathic spontaneous preterm birth and term birth samples. We identified an additional 1,718 significantly methylated regions in our gestational age matched controls were the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern, again indicating a striking level of similarity between the idiopathic spontaneous preterm birth and term birth samples. Pathway analysis of these regions revealed differences in genes within the WNT and Cadherin signaling pathways, both of which are essential in placental development and maturation. Taken together, these data demonstrate that the idiopathic spontaneous preterm birth samples are molecularly more mature than expected given their respective gestational age which likely impacts birth timing. Multivariate genome-wide association study on tissue-sensitive diffusion metrics identifies key molecular pathways for axonal growth, synaptogenesis, and astrocyte-mediated neuroinflammation The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discovered 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% were validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development were found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Cold stress upregulates the expression of heat shock and Frost genes, but the evolution of cold stress resistance is apparently not mediated through either heat shock or Frost genes in the cold stress selected populations of Drosophila melanogaster The ability to thermal adaptation can alter insects reproductive traits and physiologic response. A number of studies in Drosophila documented the higher expression levels of heat shock proteins (Hsps) and Frost (Fst) genes during the recovery phase of cold shock treatment and suggested that higher expression levels of these genes and lipids can protect from cold stress. However, these genes expression and cold adaptation have not been well studied. Therefore, understanding the molecular and biochemical basis of cold adaptation, we examined the levels of lipid and expression patterns of Hsp22, Hsp23, Hsp40, Hsp68, Hsp70, Hsp 83, and Fst genes under the cold stress or benign condition in the populations of Drosophila melanogaster selected for increased resistance to cold shock.

We observed the significant up-regulation of Hsp22, Hsp23, Hsp40, Hsp68, and Fst genes in the FSB and FCB populations during the recovery phase post cold shock compared to the no shock condition. However, there was not a significant change in the transcript levels of these genes between FSB and FCB under both the cold stress or no shock condition. Additionally, we noticed higher total lipid levels in the females from cold shock treatment than those from no shock treatment. This finding suggests that cold selected populations have different mechanisms to sustain cold stress. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Effects of a 33-ion sequential beam galactic cosmic ray analog on male mouse behavior and evaluation of CDDO-EA as a radiation countermeasure In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a  vehicle formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures. Relationship between shear wave velocity and muscle activation is inconsistent across different muscle types There is an increasing use of shear wave ultrasound elastography to quantify mechanical properties of muscles under various conditions such as changes muscle length and levels of activation in healthy and pathological muscle. However, little is known about the variability in shear wave velocity among muscles as most studies investigate one specific muscle. The purpose of this study was to determine if the relationship between SWV and muscle activation is consistent across muscles with different architectures: biceps brachii, tibialis anterior, and medial gastrocnemius, All measures were made at matching levels of activation and approximately at the optimal length for each muscle to control for length-dependent changes in the relationship between activation and force or stiffness. We also conducted a control experiment to determine how the passive force within a muscle alters the relationship between muscle activation and shear wave velocity. The relationship between shear wave velocity-squared and activation above 10% MVC differed across muscles, with biceps brachii and medial gastrocnemius showing a lower slope than tibialis anterior. Shear wave velocity-squared also differed between muscles at the shortest length (p<0.001) and the increase in shear wave velocity-squared with muscle lengthening also differed between muscle types (p = 0.005) Muscle-specific differences could not be explained by the architectural features such as pennation angle, fiber length, and physiological cross-sectional area. Our results demonstrate that there is not a unique relationship between muscle activation and shear wave velocity, highlighting the importance of understanding the many factors contributing to shear wave propagation in muscle before elastography can be used to make quantitative comparisons across muscle types. Predicting microbiome compositions from species assemblages through deep learning. Microbes can form complex communities that perform critical functions in maintaining the integrity of their environment or their hosts well-being. Rationally managing these microbial communities requires improving our ability to predict how different species assemblages affect the final species composition of the community. However, making such a prediction remains challenging because of our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. To overcome this challenge, here we present a deep learning framework that automatically learns the map between species assemblages and community compositions from training data only, without knowledge of any of the above processes. First, we systematically validate our framework using synthetic data generated by classical population dynamics models. Then, we apply it to experimental data of both in vitro and in vivo communities, including ocean and soil microbial communities, Drosophila melanogaster gut microbiota, and human gut and oral microbiota. In particular, we show how our framework learns to perform accurate out-of-sample predictions of complex community compositions from a small number of training samples. Our results demonstrate how deep learning can enable us to understand better and potentially manage complex microbial communities. Optogenetic dissection of actomyosin-dependent mechanics underlying tissue fluidity Rapid epithelial tissue flows are essential to building and shaping developing embryos. However, it is not well understood how the mechanical properties of tissues and the forces driving them to flow are jointly regulated to accommodate rapid tissue remodeling. To dissect the roles of actomyosin in the mechanics of epithelial tissue flows, here we use two optogenetic tools, optoGEF and optoGAP, to manipulate Rho/Rho-kinase signaling and actomyosin contractility in the germband epithelium, which flows via convergent extension movements during Drosophila body axis elongation. The ability to perturb actomyosin in the tissue allows us to analyze the effects of actomyosin on cell rearrangements, tissue tensions, and tissue mechanical properties. We find that either optogenetic activation or deactivation of Rho1 signaling and actomyosin contractility at the apical surface of the germband disrupts cell rearrangements and tissue-level flows. Rho1 activation leads to poorly oriented rearrangements that are associated with a redistribution of myosin II from the junctional to the medial-apical domain, whereas Rho1 deactivation leads to fewer, slower cell rearrangements that are associated with decreased junctional and medial myosin. By probing mechanical tensions in the tissue using laser ablation and inferring tissue mechanical properties from cell packings, we find that actomyosin influences both the anisotropic forces that drive tissue flow and the mechanical properties of the tissue that resist flow, leading to complex relationships between actomyosin activity and tissue fluidity. Moreover, our results link the subcellular distribution of myosin II to tissue tension and cell packings, revealing how junctional and medial myosin have differential roles in promoting and orienting cell rearrangements during tissue flow. 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. Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors - Dependencies and Novel Pitfalls Personalized Oncology is a rapidly evolving area and offers cancer patients therapy options more specific than ever. Yet, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation Projection (UMAP)) on three datasets of metastases (n=682 samples) with three different data transformations (unprocessed, log10 as well as log10+1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n=616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between site of resection and cluster formation outcome could be demonstrated, neither for datasets consisting of solely metastasis nor mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results indicate only minor transcriptional differences for metastases and corresponding primary tumors. Selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes. The functional role of episodic memory in spatial learning AO_SCPLOWBSTRACTC_SCPLOWEpisodic memory has been studied extensively in the past few decades, but so far little is understood about how it drives behavior. Here we propose that episodic memory can facilitate learning in two fundamentally different modes: retrieval and replay. We study their properties by comparing three learning paradigms using computational modeling based on visually-driven reinforcement learning. Firstly, episodic memory is retrieved to learn from single experiences (one-shot learning); secondly, episodic memory is replayed to facilitate learning of statistical regularities (replay learning); and, thirdly, learning occurs online as experiences arise with no access to past experiences (online learning). We found that episodic memory benefits spatial learning in a broad range of conditions, but the performance difference is meaningful only when the task is sufficiently complex and the number of learning trials is limited. Furthermore, the two modes of accessing episodic memory affect spatial learning distinctly. One-shot learning is initially faster than replay learning, but the latter reaches a better asymptotic performance. Our model accounts for experimental results where replay is inhibited, but the hippocampus, and hence episodic memory, is intact during learning. Understanding how episodic memory drives behavior will be an important step towards elucidating the nature of episodic memory. Ultrahigh-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Desorption Electrospray Ionization Mass Spectrometry Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultrahigh-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 M 1-hydroxymidazolam and 12 M dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with ~30s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115,200 samples from 300 microtiter plate reads consecutively over 5.54 hours with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high throughput compound screening.

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org.highwire.dtl.DTLVardef@5f916corg.highwire.dtl.DTLVardef@4473b4org.highwire.dtl.DTLVardef@82e8forg.highwire.dtl.DTLVardef@128b57b_HPS_FORMAT_FIGEXP  M_FIG C_FIG How to Approach Machine Learning-based Prediction of Drug/Compound-Target Interactions The identification of drug/compound-target interactions (DTIs) constitutes the basis of drug discovery, for which computational predictive approaches have been applied. As a relatively new data-driven paradigm, proteochemometric (PCM) modeling utilizes both protein and compound properties as a pair at the input level and processes them via statistical/machine learning. The representation of input samples (i.e., proteins and their ligands) in the form of quantitative feature vectors is crucial for the extraction of interaction-related properties during the artificial learning and subsequent prediction of DTIs. Lately, the representation learning approach, in which input samples are automatically featurized via training and applying a machine/deep learning model, has been utilized in biomedical sciences. In this study, we performed a comprehensive investigation of different computational approaches/techniques for protein featurization (including both conventional approaches and the novel learned embeddings), data preparation and exploration, machine learning-based modeling, and performance evaluation with the aim of achieving better data representations and more successful learning in DTI prediction. For this, we first constructed realistic and challenging benchmark datasets on small, medium, and large scales to be used as reliable gold standards for specific DTI modeling tasks. We developed and applied a network analysis-based splitting strategy to divide datasets into structurally different training and test folds. Using these datasets together with various featurization methods, we trained and tested DTI prediction models and evaluated their performance from different angles. Our main findings can be summarized under 3 items: (i) random splitting of datasets into train and test folds lead to near-complete data memorization and produce highly over-optimistic results, as a result, it should be avoided, (ii) learned protein sequence embeddings work well in DTI prediction and offer high potential, even though no information related to protein structures, interactions or biochemical properties is utilized during their generation, and (iii) PCM models tend to learn from compound features and leave out protein features, mostly due to the natural bias in DTI data, indicating the requirement for new and unbiased datasets. We hope this study will aid researchers in designing robust and high-performing data-driven DTI prediction systems that have real-world translational value in drug discovery. Stress-dependent cell stiffening by tardigrade tolerance proteins through reversible formation of cytoskeleton-like filamentous network and gel-transition Tardigrades are able to tolerate almost complete dehydration by entering a reversible ametabolic state called anhydrobiosis and resume their animation upon rehydration. Dehydrated tardigrades are exceptionally stable and withstand various physical extremes. Although trehalose and late embryogenesis abundant (LEA) proteins have been extensively studied as potent protectants against dehydration in other anhydrobiotic organisms, tardigrades produce high amounts of tardigrade-unique protective proteins. Cytoplasmic-abundant heat-soluble (CAHS) proteins are uniquely invented in the lineage of eutardigrades, a major class of the phylum Tardigrada and are essential for their anhydrobiotic survival. However, the precise mechanisms of their action in this protective role are not fully understood. In the present study, we first postulated the presence of tolerance proteins that form protective condensates via phase separation in a stress-dependent manner and searched for tardigrade proteins that reversibly form condensates upon dehydration-like stress. Through comprehensive analysis, we identified 336 such proteins, collectively dubbed "Desolvataion-induced ReversiblY condensing Proteins (DRYPs)". Unexpectedly, we rediscovered CAHS proteins as highly enriched in DRYPs, 3 of which were major components of DRYPs. We revealed that these CAHS proteins reversibly polymerize into many cytoskeleton-like filaments depending on hyperosmotic stress in cultured cells and undergo reversible gel-transition in vitro. CAHS filamentation increases cell stiffness to resist deformation and improves resistance to dehydration-like stress. The conserved putative helical C-terminal region is necessary and sufficient for filament formation by CAHS proteins, and mutations disrupting the secondary structure of this region impaired both the filament formation and the gel transition. On the basis of these results, we propose that CAHS proteins are novel cytoskeletal proteins that form filamentous networks and undergo gel-transition in a stress-dependent manner to provide on-demand physical stabilization of cell integrity against deformative forces during dehydration and also contribute to the exceptional physical stability in a dehydrated state. Cytokinin oxidase/dehydrogenase family genes exhibit functional divergence and overlap in rice growth and development Cytokinins play key roles in plant growth and development; hence, cytokinin biosynthesis and degradation have been extensively studied. Cytokinin oxidase/dehydrogenases (CKXs) are a group of enzymes that regulate oxidative cleavage to maintain cytokinin homeostasis. In rice, 11 OsCKX genes have been identified to date; however, most of their functions remain unknown. Here, we comprehensively analyzed the expression patterns and functions of OsCKX genes. Using CRISPR/Cas9 technology, we constructed mutants of all OsCKX genes to determine the functions of OsCKXs in rice development. The results revealed that the single osckx and higher-order osckx4 osckx9 mutant lines showed functional overlap and subfunctionalization. Notably, the osckx1 osckx2 and osckx4 osckx9 double mutants displayed contrasting phenotypic changes in tiller number and panicle size compared to the wild type. Moreover, we identified several genes with significantly altered expression in osckx4 and osckx9 single and double mutant plants. Many differentially expressed genes were found to be associated with auxin and cytokinin pathways. Additionally, the cytokinins in osckx4 osckx9 mutants were increased compared to the wild type. Overall, our findings provide new insights into the functions of OsCKX genes in rice growth and may be used as a foundation for future studies aimed at improving rice yield. Key words: Cytokinin, expression pattern, OsCKX, panicle, phenotype, rice, tiller

HighlightThe osckx4 osckx9 double mutant had a significantly greater number of tillers, whereas the osckx1 osckx2 double mutant showed the opposite phenotypic change, compared to the wild type An Essential Role of UBXN3B for B Lymphopoiesis Hematopoiesis is finely regulated to enable timely production of the right numbers and types of mature immune cells to maintain tissue homeostasis. Dysregulated hematopoiesis may compromise antiviral immunity and/or exacerbate immunopathogenesis. Herein, we report an essential role of UBXN3B in maintenance of hematopoietic homeostasis and restriction of immunopathogenesis during respiratory viral infection. Ubxn3b deficient (Ubxn3b-/-) mice are highly vulnerable to SARS-CoV-2 and influenza A infection, characterized by more severe lung immunopathology, lower virus-specific IgG, significantly fewer B cells, but more myeloid cells than Ubxn3b+/+ littermates. This aberrant immune compartmentalization is recapitulated in uninfected Ubxn3b-/- mice. Mechanistically, UBXN3B controls precursor B-I (pre-BI) transition to pre-BII and subsequent proliferation in a cell-intrinsic manner, by maintaining BLNK protein stability and pre-BCR signaling. These results reveal an essential role of UBXN3B for the early stage of B cell development. Assessment of Sex Bias in Housekeeping Gene Expression in Adipose Tissue Through the Massive Analysis of Transcriptomics Data As the housekeeping genes (HKGs) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, multiple studies indicate that not all HKGs display stable expression across cells and tissues and under various healthy and diseased conditions, which can introduce systematic errors into experimental results. The selection and validation of HKGs as controls for each studied condition represent crucial steps in ensuring the validity of obtained results; however, up till now, sex has not been typically considered as a biological variable.

In this study, we evaluate the expression profiles of six classical HKGs (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the stabile expression of genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database (GEO) to identify sex-unbiased HKGs suitable for use as internal controls. We perform a sex-based analysis to describe any sexual dimorphisms in mRNA expression stability.

A novel computational strategy based on meta-analysis techniques proves that certain classical HKGs fail to function adequately as controls when analyzing human adipose tissue (HAT) considering sex as a variable. The extensively used 18S gene displays sex-based variability in adipose tissue, although PPIA and RPL19 do not, and hence, represent robust HKGs. We propose new sex-unbiased human and mouse HKGs (suHKG) derived from sex-specific expression profiles, such as RPS8 and UBB. All results generated during this study are readily available by accessing an open web resource (https://bioinfo.cipf.es/metafun-HKG) for consultation and reuse in further studies. Co-infection of Candidatus Piscichlamydia trichopodus (order Chlamydiales) and Henneguya sp (Myxosporea, Myxobolidae) in snakeskin gourami Trichopodus pectoralis (Regan 1910) The present study describes a simultaneous infection of a novel Chlamydia-like organism (CLO) with a Myxozoa parasite, Henneguya sp. in snakeskin gourami Trichopodus pectoralis in Thailand. A new CLO is proposed "Candidatus Piscichlamydia trichopodus" (CPT) based on 16S rRNA phylogenetic analysis. Systemic intracellular CPT infection was confirmed by histological examination, in situ hybridization, PCR assay, and sequencing of 16S rRNA. This novel pathogen belongs to the order Chlamydiales but differs in certain aspects from other species. The histopathological changes associated with CPT infection were different from the typical pathological lesions of epitheliocystis caused by previously known CLO. Unlike other CLO, CPT localized in the connective tissue rather than in the epithelial cells and formed smaller clumps of intracellular bacteria that stained dark blue with hematoxylin. On the other hand, typical myxospores of the genus Henneguya with tails were observed in the gill sections. Infection with Henneguya sp. resulted in extensive destruction of the gill filaments, most likely leading to respiratory distress. Due to the frequency of co-infections and the unavailability of culture methods for CLO and Henneguya sp, it was difficult to determine which pathogens were directly responsible for the associated mortality. However, co-infections may increase the negative impact on the host and the severity of the disease. Given the commercial importance of the snakeskin gourami and its significant aquaculture potential, the findings of this study are important for further studies on disease prevention. The adenoviral E1B-55k protein present in HEK293 cells mediates abnormal accumulation of key WNT signaling proteins in large cytoplasmic aggregates. HEK293 cells are one of the most widely used cell lines in research and HEK293 cells are frequently used as an in vitro model for studying the WNT signaling pathway. The HEK293 cell line was originally established by transfection of human embryonic kidney cells with sheared adenovirus 5 DNA and it is known that that HEK293 cells stably express the adenoviral E1A and E1B-55k proteins. Here we show that HEK293 cells display an unexpected distribution of key components of the WNT/{beta}-catenin signaling pathway where AXIN1, APC, DVL2 and tankyrase are all co-localized in large spherical cytoplasmic aggregates. The cytoplasmic aggregates are enclosed by a narrow layer of the adenoviral E1B-55k protein. Reduction of E1B-55k protein levels leads to disappearance of the cytoplasmic aggregates thus corroborating an essential role of the E1B-55k protein in mediating the formation of the aggregates. Furthermore, HEK293 cells with reduced E1B-55k protein levels display reduced levels of transcriptional activation of WNT/{beta}-catenin signaling upon stimulation by the Wnt3A agonist. The demonstrated influence of the E1B-55k protein on the cellular localization of WNT/{beta}-catenin signaling components and on transcriptional regulation of WNT/{beta}-catenin signaling asks for caution in the interpretation of data derived from the HEK293 cell line. CDK9 and PP2A regulate RNA polymerase II transcription termination and coupled RNA maturation. CDK9 is a critical kinase required for the productive transcription of protein-coding genes by RNA polymerase II (pol II). As part of P-TEFb, CDK9 phosphorylates the carboxyl-terminal domain (CTD) of pol II and elongation factors, including SPT5, which allows pol II to elongate past the early elongation checkpoint (EEC) encountered soon after initiation. We show that, in addition to halting pol II at the EEC, loss of CDK9 activity causes premature termination of transcription across the last exon, loss of polyadenylation factors from chromatin, and loss of polyadenylation of nascent transcripts. Inhibition of the phosphatase PP2A abrogates the premature termination and loss of polyadenylation caused by CDK9 inhibition, indicating that this kinase/phosphatase pair regulates transcription elongation and RNA processing at the end of protein-coding genes. Our phosphoproteomic analyses after CDK9 inhibition, using either DRB or an analog-sensitive CDK9 cell line, confirm the splicing factor SF3B1 as an additional key target of this kinase. These results emphasize the important roles that CDK9 plays in coupling transcription elongation and termination to RNA maturation downstream of the EEC.