Phylogenomic evidence for the Origin of Obligately Anaerobic Anammox Bacteria around the Great Oxidation Event The anaerobic ammonium oxidation (anammox) bacteria could transform ammonium and nitrite to dinitrogen gas, and this obligate anaerobic process accounts for up to half of the global nitrogen loss in surface environments. Yet its origin and evolution, which may give important insights into the biogeochemistry of early Earth, remains enigmatic. Here, we performed comprehensive phylogenomic analysis and showed a single origin of anammox bacteria within the phylum Planctomycetes. After accommodating the uncertainties and factors influencing time estimates, which includes implementing both a traditional cyanobacteria-based and a recently developed mitochondria-based approach, we estimated that anammox bacteria originated at early Proterozoic and most likely around the so-called Great Oxidation Event (GOE; 2.32 to 2.5 billion years ago [Ga]) which fundamentally changed global biogeochemical cycles. We further showed that during the origin of anammox bacteria, genes involved in oxidative stress, bioenergetics and anammox granules formation were recruited, which might have contributed to their survival on an increasingly oxic Earth. Our findings suggest the rising levels of atmospheric oxygen, which made nitrite increasingly available, was a potential driving force for the emergence of anammox bacteria. This is one of the first studies that link the GOE to the evolution of obligate anaerobic bacteria.
Nelfinavir markedly improves lung pathology in SARS-CoV-2-infected Syrian hamsters despite lack of an antiviral effect In response to the ongoing COVID-19 pandemic, repurposing of drugs for the treatment of SARS-CoV-2 infections is being explored. The HIV protease inhibitor Nelfinavir, widely prescribed in combination with other HIV inhibitors, has been shown to inhibit in vitro SARS-CoV-2 replication. We here report on the effect of Nelfinavir in the Syrian hamster SARS-CoV-2 infection model. Although treatment of infected hamsters with either 15 or 50 mg/kg BID Nelfinavir [for four consecutive days, initiated on the day of infection] does not reduce viral RNA loads nor infectious virus titres in the lungs compared to the vehicle control, the drug reduced virus-induced lung pathology to nearly the baseline scores of healthy animals. A substantial interstitial infiltration of neutrophils is observed in the lungs of treated (both infected and uninfected) animals. The protective effect of Nelfinavir on SARS-CoV-2-induced lung pathology (at doses that are well tolerated and that result in exposures nearing those observed in HIV-infected patients) may lay the foundation for clinical studies with this widely used drug.
Mitochondrial double-stranded RNAs as a pivotal mediator in the pathogenesis of Sjogrens syndrome ObjectiveSjogrens syndrome (SS) is a systemic autoimmune disease that targets the exocrine glands, resulting in impaired saliva and tear secretion. To date, type I interferons (I-IFNs) are increasingly recognized as pivotal mediators in SS, but their endogenous drivers have not been elucidated. This study investigates the role of mitochondrial double-stranded RNAs (mt-dsRNAs) in regulating I-IFN response in SS.

MethodsSaliva and tear from SS patients and controls (n=73 for saliva and n=16 for tear), the salivary glands of the SS-prone-non-obese-diabetic mouse, and primary human salivary glandular cells were screened for mt-dsRNAs by RT-qPCR. The human salivary cell line (NS-SV-AC) grown as three-dimensional spheroids were subject to dsRNA stress to measure mt-dsRNA induction and recapitulation of SS glandular inflammatory features. Acetylcholine, SS-IgG, upadacitinib (JAK1 inhibitor), or 2-C'-methyladenosine (mitochondrial transcription inhibitor) were applied to characterize the roles of mt-dsRNAs. To identify endogenous dsRNA-sensor and confirm the mitochondrial origin of cytoplasmic dsRNAs, the immunoprecipitation of dsRNAs was performed.

Resultsmt-dsRNAs were elevated in the SS specimens with salivary ND5 and tear CYTB1 being statistically associated with secretory dysfunction/inflammation and corneal/conjunctival damage, respectively. Stimulation of the spheroids with dsRNA stress of poly I:C induced mt-dsRNAs, p-PKR, and I-IFNS via the JAK1/STAT pathway whereas the inhibition of mt-RNA synthesis or JAK1 attenuated the glandular signature. The inhibitory effect of acetylcholine on mt-dsRNAs and I-IFNS induction was reversed by SS-IgG.

Conclusionmt-dsRNAs amplify the impact of dsRNA stress on SS glandular signatures in vitro, potentially propagating a pseudo-viral signal in the SS target tissue.

SummaryMitochondrial double-stranded RNA levels were elevated in the tear and saliva of SS patients, which was associated with secretory dysfunction and tissue inflammation. These RNAs amplified type I interferon signature as well as glandular phenotypes reported in SS. Inhibitors of mitochondrial RNA transcription or JAK1 in salivary gland acinar cell spheroids attenuated the mitochondrial RNA-mediated changes. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. A cell cycle-dependent GARP-like transcriptional repressor regulates the initiation of differentiation in Giardia lamblia Transcriptional regulation of differentiation is critical for parasitic pathogens to adapt to environmental changes and regulate transmission. In response to encystation stimuli, Giardia lamblia cells shift from G1+S phase of the cell cycle to G2+M. By 2-4 hours, cyst wall proteins are upregulated, indicating that key regulatory steps occur within the first four hours of encystation. However, all characterized transcription factors (TFs) in Giardia have only been investigated at later time points of encystation. How TFs initiate encystation and link it to the cell cycle remains enigmatic. Here, we systematically screened six putative early upregulated TFs for nuclear localization, established their dynamic expression profiles, and determined their functional role in regulating encystation. We found a critical repressor, GLP4 that increases rapidly after 30 min of encystation stimuli and downregulates encystation specific markers, including Cyst Wall Proteins (CWPs) and enzymes in the cyst N-acetyl galactosamine (GalNAc) pathway. Depletion of GLP4 increases cyst production. Importantly, we observe that G2+M cells exhibit higher levels of CWP1 resulting from the activation of MYB2, a TF previously linked to encystation in Giardia. GLP4 upregulation occurs in G1+S cells, suggesting a role in repressing MYB2 and encystation specific genes in the G1+S phase of the cell cycle. Furthermore, we demonstrate that depletion of GLP4 upregulates MYB2 and promotes encystation while overexpression of GLP4 downregulates MYB2 and represses encystation. Together, these results suggest that Giardia employs a dose-dependent transcriptional response that involves the cell cycle regulated repressor GLP4 to orchestrate MYB2 and entry into the encystation pathway.

ImportanceTransition between life cycle stages is a common feature among parasitic pathogens and its regulation must be optimized to balance persistence of infection with transmission. The early transcription factors (TFs) regulating commitment to differentiate are totally unknown in Giardia. In this work, we identified GLP4, a previously uncharacterized GARP-like TF, as an early-acting transcriptional repressor that inhibits G1+S cells from entering the encystation pathway. GLP4 is therefore a key regulator controlling the balance between proliferative growth and terminal differentiation into infective cysts. Analysis of science journalism reveals gender and regional disparities in coverage Science journalism is a critical way in which the public can remain informed and benefit from new scientific findings. Such journalism also shapes the publics view of the current state of scientific findings and legitimizes experts. Those covering science can only cite and quote a limited number of sources. Sources may be identified by the journalists research or by recommendations by other scientists. In both cases, biases may influence who is identified and ultimately included as an expert. To analyze possible biases in science journalism, we analyzed 22,001 non-research articles published by Nature. We chose to analyze Nature non-research articles since its research articles provide a natural comparator. Our analysis considered two possible sources of disparity: gender and name origin. To explore these sources of disparity, we extracted cited authors names as well as extracted names of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then used the extracted names to predict gender and name origin of the cited authors and speakers.

In order to appropriately quantify the level of difference, we must identify a suitable reference set for comparison. We chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. In our analysis, we found a skew towards male quotation in Nature science journalism-related articles. However, quotation is trending toward equal representation at a faster rate than first and last authorship in academic publishing. Interestingly, we found that the gender disparity in Nature quotes was column-dependent, with the "Career Features" column reaching gender parity. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin. This finding was observed both in extracted quotes and journal citations, but dampened in citations. 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. Substrate specialization in microbes is driven by biochemical constraints of dynamic flux sensing Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic re-organization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa and Pseudomonas putida. We combined growth dynamics and dynamic changes of intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis and growth and uncovered fundamental limitations of the regulatory network: after nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Graphical synopsis O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

Standfirst textMicrobes face a series of fundamental trade-offs that limit their ability to optimize simultaneously for both glycolytic and gluconeogenic growth.

Bullet pointsO_LILag times between glycolysis and gluconeogenesis show asymmetry in many microbes: A long lag in one direction, but a short lag in the other.
C_LIO_LILong lag times are caused by an inability to sense fluxes after nutrient shifts.
C_LIO_LIWith existing regulation, lag time asymmetry can only be overcome by reducing either growth rate or increasing futile cycling in metabolism.
C_LI Development and Characterization of PAR-Trackers: New Tools for Detecting Poly(ADP-ribose) In Vitro and In Vivo AO_SCPLOWBSTRACTC_SCPLOWADP-ribosylation (ADPRylation) is a reversible post-translation modification resulting in the covalent attachment of ADP-ribose (ADPR) moieties on substrate proteins. Naturally-occurring protein motifs and domains, including WWEs, PBZs, and macrodomains, act as "readers" for protein-linked ADPR. Although recombinant, antibody-like ADPR detection reagents containing these readers have facilitated the detection of ADPR, they are limited in their ability to capture the dynamic nature of ADPRylation. Herein, we describe and characterize a set of poly(ADP-ribose) (PAR) Trackers (PAR-Ts) - optimized dimerization-dependent or split-protein reassembly PAR sensors in which a naturally occurring PAR binding domain, WWE, was fused to both halves of dimerization-dependent GFP (ddGFP) or split Nano Luciferase (NanoLuc), respectively. We demonstrate that these new tools allow the detection and quantification of PAR levels in extracts, living cells, and living tissues with greater sensitivity, as well as temporal and spatial precision. Importantly, these sensors detect changes in cellular ADPR levels in response to physiological cues (e.g., hormone-dependent induction of adipogenesis without DNA damage), as well as xenograft tumor tissues in living mice. Our results indicate that PAR Trackers have broad utility for detecting ADPR in many different experimental and biological systems. Bringing TrackMate into the era of machine-learning and deep-learning. TrackMate is an automated tracking software used to analyze bioimages and distributed as a Fiji plugin. Here we introduce a new version of TrackMate rewritten to improve performance and usability, and integrating several popular machine and deep learning algorithms to improve versatility. We illustrate how these new components can be used to efficiently track objects from brightfield and fluorescence microscopy images across a wide range of bio-imaging experiments. Pathfinder: A gamified measure to integrate general cognitive ability into the biological, medical, and behavioural sciences Genome-wide association (GWA) studies have uncovered DNA variants associated with individual differences in general cognitive ability (g), but these are far from capturing heritability estimates obtained from twin studies. A major barrier to finding more of this  missing heritability is assessment - the use of diverse measures across GWA studies as well as time and cost of assessment. In a series of four studies, we created a 15-minute (40-item), online, gamified measure of g that is highly reliable (alpha = .78; two-week test-retest reliability = .88), psychometrically valid and scalable; we called this new measure Pathfinder. In a fifth study, we administered this measure to 4,751 young adults from the Twins Early Development Study. This novel g measure, which also yields reliable verbal and nonverbal scores, correlated substantially with standard measures of g collected at previous ages (r ranging from .42 at age 7 to .57 at age 16). Pathfinder showed substantial twin heritability (.57, 95% CIs = .43, .68) and SNP heritability (.37, 95% CIs = .04, .70). A polygenic score computed from GWA studies of five cognitive and educational traits accounted for 12% of the variation in g, the strongest DNA-based prediction of g to date. Widespread use of this engaging new measure will advance research not only in genomics but throughout the biological, medical, and behavioural sciences. Reconsider phase reconstruction in signals with dynamic periodicity from the modern signal processing perspective Phase is the most fundamental physical quantity when we study an oscillatory time series. There are many tools aiming to estimate phase, most of them are developed based on the analytic function model. Unfortunately, this approach might not be suitable for modern signals with intrinsic nonstartionary structure, including multiple oscillatory components, each with time-varying frequency, amplitude, and non-sinusoidal oscillation, e.g., biomedical signals. Specifically, due to the lack of consensus of model and algorithm, phases estimated from signals simultaneously recorded from different sensors for the same physiological system from the same subject might be different. This fact might challenge reproducibility, communication, and scientific interpretation and thus we need a standardized approach with theoretical support over a unified model. In this paper, after summarizing existing models for phase and discussing the main challenge caused by the above-mentioned intrinsic nonstartionary structure, we introduce the adaptive non-harmonic model (ANHM), provide a definition of phase called fundamental phase, which is a vector-valued function describing the dynamics of all oscillatory components in the signal, and suggest a time-varying bandpass filter (tvBPF) scheme based on time-frequency analysis tools to estimate the fundamental phase. The proposed approach is validated with a simulated database and a real-world database with experts labels, and it is applied to two real-world databases, each of which has biomedical signals recorded from different sensors, to show how to standardize the definition of phase in the real-world experimental environment. Specifically, we report that the phase describing a physiological system, if properly modeled and extracted, is immune to the selected sensor for that system, while other approaches might fail. In conclusion, the proposed approach resolves the above-mentioned scientific challenge. We expect its scientific impact on a broad range of applications. Tardigrade CAHS Proteins Act as Molecular Swiss Army Knives to Mediate Desiccation Tolerance Through Multiple Mechanisms Tardigrades, also known as water bears, make up a phylum of small but extremely hardy animals, renowned for their ability to survive extreme stresses, including desiccation. How tardigrades survive desiccation is one of the enduring mysteries of animal physiology. Here we show that CAHS D, an intrinsically disordered protein belonging to a unique family of proteins possessed only by tardigrades, undergoes a liquid-to-gel phase transition in a concentration dependent manner. Unlike other gelling proteins, such as gelatin, our data support a mechanism in which gel formation of CAHS D is driven by intermolecular {beta}-{beta} interactions. We find that gel formation corresponds with strong coordination of water and slowing of water diffusion. The degree of water coordination correlates with the ability of CAHS D to protect lactate dehydrogenase from unfolding when dried. This implies that the mechanism for unfolding protection can be attributed to a combination of hydration and slowed molecular motion. Conversely, rapid diffusion leading to efficient molecular shielding appears to be the predominant mechanism preventing protein aggregation. Our study demonstrates that distinct mechanisms are required for holistic protection during desiccation, and that protectants, such as CAHS D, can act as molecular  Swiss Army Knives capable of providing protection through several different mechanisms simultaneously. 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. Construction of a new chromosome-scale, long-read reference genome assembly for the Syrian hamster, Mesocricetus auratus BackgroundThe Syrian hamster (Mesocricetus auratus) has been suggested as a useful mammalian model for a variety of diseases and infections, including infection with respiratory viruses such as SARS-CoV-2. The MesAur1.0 genome assembly was generated in 2013 using whole-genome shotgun sequencing with short-read sequence data. Current more advanced sequencing technologies and assembly methods now permit the generation of near-complete genome assemblies with higher quality and greater continuity.

FindingsHere, we report an improved assembly of the M. auratus genome (BCM_Maur_2.0) using Oxford Nanopore Technologies long-read sequencing to produce a chromosome-scale assembly. The total length of the new assembly is 2.46 Gbp, similar to the 2.50 Gbp length of a previous assembly of this genome, MesAur1.0. BCM_Maur_2.0 exhibits significantly improved continuity with a scaffold N50 that is 6.7 times greater than MesAur1.0. Furthermore, 21,616 protein coding genes and 10,459 noncoding genes are annotated in BCM_Maur_2.0 compared to 20,495 protein coding genes and 4,168 noncoding genes in MesAur1.0. This new assembly also improves the unresolved regions as measured by nucleotide ambiguities, where approximately 17.11% of bases in MesAur1.0 were unresolved compared to BCM_Maur_2.0 in which the number of unresolved bases is reduced to 3.00%.

ConclusionsAccess to a more complete reference genome with improved accuracy and continuity will facilitate more detailed, comprehensive, and meaningful research results for a wide variety of future studies using Syrian hamsters as models. Interactions and information: Exploring task allocation in ant colonies using network analysis In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individuals task - foraging, cleaning or nursing - and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.

HighlightsO_LIWe analysed the interaction networks of six Camponotus fellah colonies
C_LIO_LIWe tested how centrality and information flow were tied to task switching
C_LIO_LINode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups
C_LIO_LIInteractions were correlated with task switching, but the strength of the correlation differed across functional groups
C_LI Deep inference of seabird dives from GPS-only records: performance and generalization properties AO_SCPLOWBSTRACTC_SCPLOWAt-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as  fine-tuning. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation. To make easier such applications, we share online the different models we trained on the considered datasets (https://github.com/AmedeeRoy/BirdDL/models).

Author SummaryOver the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as  ready-to-use tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training. RadGenNets: Deep Learning-Based Radiogenomics Model For Gene Mutation Prediction In Lung Cancer AO_SCPLOWBSTRACTC_SCPLOWIn this paper, we present our methodology that can be used for predicting gene mutation in patients with non-small cell lung cancer (NSCLC). There are three major types of gene mutations that a NSCLC patients gene structure can change to: epidermal growth factor receptor (EGFR), Kirsten rat sarcoma virus (KRAS), and Anaplastic lymphoma kinase (ALK). We worked with the clinical and genomics data for each patient as well CT scans. We preprocessed all of the data and then built a novel pipeline to integrate both the image and tabular data. We built a novel pipeline that used a fusion of Convolutional Neural Networks and Dense Neural Networks. Also, using a search approach, we pick an ensemble of deep learning models to classify the separate gene mutations. These models include EfficientNets, SENet, and ResNeXt WSL, among others. Our model achieved a high area under curve (AUC) score of 94% in detecting gene mutation. Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites AO_SCPLOWBSTRACTC_SCPLOWThe traditional mechanistic trade-offs resulting in a negative correlation between transmission and virulence are the foundation of nearly all current theory on the evolution of parasite virulence. Several ecological factors have been shown to modulate the optimal virulence strategies predicted from mechanistic trade-off models, but these ecological factors have not yet been shown to be sufficient to explain the intermediate virulence strategies observed in any natural system. The timing of seasonal activity, or phenology, is a common factor that influences the types and impact of many ecological interactions but is difficult to incorporate into virulence evolution studies. We develop a mathematical model of a disease system with seasonal host activity to study the evolutionary consequences of host phenology on the virulence of obligate-killer parasite. Results from this model demonstrated that seasonal host activity is sufficient to drive the evolution of intermediate parasite virulence in some types of natural disease systems, even when a traditional mechanistic trade-off between transmission and virulence is not assumed in the modeling framework. The optimal virulence strategy in these systems can be determined by both the duration of the host activity period as well as the variation in the host emergence timing. Parasites with low virulence strategies are favored in environments with long host activity periods and in environments in which hosts emerge synchronously. The results demonstrate that host phenology can be sufficient to select for intermediate optimal virulence strategies, providing an alternative mechanism to account for virulence evolution in some natural systems. Classification of daily crop phenology in PhenoCams using deep learning and hidden markov models Near surface cameras, such as those in the PhenoCam network, are a common source of ground truth data in modelling and remote sensing studies. Despite having locations across numerous agricultural sites, few studies have used near surface cameras to track the unique phenology of croplands. Due to management activities, crops do not have a natural vegetation cycle which many phenological extraction methods are based on. For example, a field may experience abrupt changes due to harvesting and tillage throughout the year. A single camera can also record several different plants due to crop rotations, fallow fields, and cover crops. Current methods to estimate phenology metrics from image time series compress all image information into a relative greenness metric, which discards a large amount of contextual information. This can include the type of crop present, whether snow or water is present on the field, the crop phenology, or whether a field lacking green plants consists of bare soil, fully senesced plants, or plant residue. Here we developed a modelling workflow to create a daily time series of crop type and phenology, while also accounting for other factors such as obstructed images and snow covered fields. We used a mainstream deep learning image classification model, VGG16. Deep learning classification models do not have a temporal component, so to account for temporal correlation among images our workflow incorporates a hidden markov model in the post-processing. The initial image classification model had out of sample F1 scores of 0.83-0.85, which improved to 0.86-0.91 after all post-processing steps. The resulting time series show the progression of crops from emergence to harvest, and can serve as a daily, local scale dataset of field states and phenological stages for agricultural research. Glucose regulates expression of pro-inflammatory genes IL-1β and IL-12 through a mechanism involving hexosamine biosynthesis pathway dependent regulation of α-E catenin in the RAW 264.7 macrophage cell line High glucose levels are associated with changes in macrophage polarization and evidence indicates that the sustained or even short-term high glucose levels modulate inflammatory responses in macrophages. However, the mechanism by which macrophages can sense the changes in glucose levels are not clearly understood. We find that high glucose levels rapidly increase the -E catenin protein level in RAW264.7 macrophages. We also find an attenuation of glucose induced increase of -E catenin when hexosamine biosynthesis pathway is inhibited either with glutamine depletion or with the drugs azaserine and tunicamycin. This indicates the involvement of hexosamine biosynthesis pathway in this process. Then, we investigated the potential role of -E catenin in glucose induced macrophage polarization. We find that the reduction of -E catenin level using siRNA attenuates the glucose induced change of IL-1{beta} mRNA level under LPS stimulated condition. Further, we identified that the depletion of -E catenin also decreases the IL-12 gene expression in basal glucose conditions leading to a reduction of glucose induced changes in IL-12. Together this indicates that -E catenin can sense the changes in glucose levels in macrophages via hexosamine biosynthesis pathway and also can modulate the glucose induced gene expression of inflammatory markers such as IL-1-{beta} and IL-12. This identifies a new part of the mechanism by which macrophages are able to respond to changes in glucose levels. Inhibitory proteins block substrate access by occupying the active site cleft of Bacillus subtilis intramembrane metalloprotease SpoIVFB Intramembrane proteases function in numerous signaling pathways that impact health, but knowledge about regulation of intramembrane proteolysis is limited. We examined inhibition of intramembrane metalloprotease SpoIVFB by proteins BofA and SpoIVFA. We found that BofA residues in and near a predicted transmembrane segment are required for SpoIVFB inhibition, and cross-linking experiments indicated that this transmembrane segment occupies the SpoIVFB active site cleft. SpoIVFA is also required for SpoIVFB inhibition. The inhibitory proteins block access of the substrate N-terminal Proregion to the membrane-embedded SpoIVFB active site, based on additional cross-linking experiments; however, the inhibitory proteins did not prevent interaction between the substrate C-terminal region and the SpoIVFB soluble domain. A structural model was built of SpoIVFB in complex with BofA and parts of SpoIVFA and substrate, using partial homology and constraints from cross-linking and co-evolutionary analyses. The model predicts that conserved BofA residues interact to stabilize a transmembrane segment and a membrane-embedded C-terminal region. SpoIVFA is predicted to bridge the BofA C-terminal region and SpoIVFB, forming a membrane-embedded inhibition complex. Our results reveal a novel mechanism of intramembrane protease inhibition with clear implications for relief from inhibition in vivo and design of inhibitors as potential therapeutics. The compound of baicalein, wogonin, and oroxylin-A inhibiting 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. Single-dose AAV-based vaccine induces a high level of neutralizing antibodies against SARS-CoV-2 in rhesus macaques Coronavirus disease 2019 (COVID-19), which is triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, continues to threaten global public health. Developing a vaccine that only requires single immunization but provides long-term protection for the prevention and control of COVID-19 is important. Here, we developed an adeno-associated virus (AAV)-based vaccine expressing a stable receptor-binding domain (SRBD) protein. The vaccine requires only a single shot but provides effective neutralizing antibodies (NAbs) over 598 days in rhesus macaques (Macaca mulatta). Importantly, our results showed that the NAbs were kept in high level and long lasting against authentic wild-type SARS-CoV-2, Beta, Delta and Omicron variants using plaque reduction neutralization test. Of note, although we detected pre-existing AAV2/9 antibodies before immunization, the vaccine still induced high and effective NAbs against COVID-19 in rhesus macaques. AAV-SRBD immune serum also efficiently inhibited the binding of ACE2 with RBD in the SARS-CoV-2 B.1.1.7 (Alpha), B.1.351 (Beta), P.1/P.2 (Gamma), B.1.617.2 (Delta), B.1.617.1/3(Kappa), and C.37 (Lambda) variants. Thus, these data suggest that the vaccine has great potential to prevent the spread of SARS-CoV-2. Memory of split-belt walking endures weeks in young children and younger adults but less so in older adults Adults and children modify how they move to accommodate persistent changes in their surroundings, called motor adaptation. Walking-related motor adaption can be seen when one walks on a treadmill with two belts running at different speeds, a split-belt treadmill, where a new walking pattern is slowly adopted with practice. This has been suggested as a way to improve left-right symmetry in walking after a stroke. Central to using split-belt walking for rehabilitation is whether the adapted motor pattern is retained over days and weeks, and whether this motor memory is a function of the persons age. When first exposed to split-belt walking, the walking is asymmetric (initial error), resembling a limp. With subsequent exposure, the error is smaller than the initial error, indicating the adaptation was remembered. Here, we explored the persistence of this memory over 24 hours, one week, and two weeks, in young children (3-6 yr old), younger adults (20-30 yr old) and older adults (50-70 yr old). We found that the motor memory declines with the interval duration, but was still evident up to 2 weeks after initial exposure. Retention of the motor memory in children and younger adults was better than older adults. Further, forgetting between trials was seen on the first day of split-belt walking especially in children and older adults, but this forgetting diminished with repeated trials. The results indicate that long-term memory of motor adaptation on the split-belt treadmill is affected by age, but it may be possible to enhance the memory by more frequent and repeated exposure. This suggests that when using split-belt adaptation in rehabilitation, the sessions should ideally be less than one week apart. Extracellular Vesicle (EV) Mitochondria and EV/HSP27 Mixtures Protect the Ischemic Brain Endothelium Ischemic stroke causes brain endothelial cell (BEC) death and damages tight junction integrity of the blood-brain barrier (BBB). We harnessed the innate mitochondrial load of endothelial cell-derived extracellular vesicles (EVs) and utilized mixtures of EV/exogenous heat shock protein 27 (HSP27) as a one-two punch strategy to increase BEC survival (via EV mitochondria) and preserve their tight junction integrity (via HSP27 effects). We demonstrated that the medium-to-large (m/lEV) but not small EVs (sEV) transferred their mitochondrial load, which subsequently colocalized with the mitochondrial network of the recipient primary human BECs. BECs treated with m/lEVs increased relative ATP levels and displayed superior mitochondrial function. m/lEVs isolated from rotenone (mitochondrial complex I inhibitor) exposed BECs (RTN-m/lEVs) did not increase BECs ATP levels compared to naive m/lEVs. In contrast, RTN-sEVs functionality was minimally affected compared to naive sEVs. Compared to EV/HSP27 mixtures, PEG-DET/EV/HSP27 ternary mixtures increased HSP27 protein loading. (PEG-DET/HSP27)/EV ternary and EV/HSP27 binary mixtures decreased the paracellular permeability of small and large molecular mass fluorescent tracers in oxygen glucose-deprived primary human BECs. This one-two punch approach to increase BEC metabolic function and tight junction integrity is a promising strategy for BBB protection and prevention of long-term neurological dysfunction post-ischemic stroke.

Highlights[tpltrtarr] Medium-to-large extracellular vesicles (m/lEVs), not small EVs contain mitochondria
[tpltrtarr]m/lEVs increased ATP and mitochondrial function in brain endothelial cells (BECs)
[tpltrtarr]Donor m/lEV mitochondria colocalized with host mitochondria in recipient BECs
[tpltrtarr]m/lEVs from rotenone-exposed BECs did not increase recipient BEC ATP levels
[tpltrtarr]PEG-DET/EV/HSP27 ternary mixtures increase exogenous HSP27 protein loading


Graphical Abstract

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