Vocal markers of autism: assessing the generalizability of machine learning models Machine learning (ML) approaches show increasing promise in their ability to identify vocal markers of autism. Nonetheless, it is unclear to what extent such markers generalize to new speech samples collected e.g., using a different speech task or in a different language. In this paper, we systematically assess the generalizability of ML findings across a variety of contexts.

We train promising published ML models of vocal markers of autism on novel cross-linguistic datasets following a rigorous pipeline to minimize overfitting, including cross-validated training and ensemble models. We test the generalizability of the models by testing them on i) different participants from the same study, performing the same task; ii) the same participants, performing a different (but similar) task; iii) a different study with participants speaking a different language, performing the same type of task.

While model performance is similar to previously published findings when trained and tested on data from the same study (out-of-sample performance), there is considerable variance between studies. Crucially, the models do not generalize well to different, though similar, tasks and not at all to new languages. The ML pipeline is openly shared.

Generalizability of ML models of vocal markers of autism is an issue. We outline three recommendations for strategies researchers could take to be more explicit about generalizability and improve it in future studies.

LAY SUMMARYMachine learning approaches promise to be able to identify autism from voice only. These models underestimate how diverse the contexts in which we speak are, how diverse the languages used are and how diverse autistic voices are. Machine learning approaches need to be more careful in defining their limits and generalizability.
LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2 The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes ([~]30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Folds purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 and 3 UTRs ([~]29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.

Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus ([~]30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics.
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. Contribution of arm movements to balance recovery after tripping in older adults. Falls are common in daily life, often caused by trips and slips and, particularly in older adults, with serious consequences. Although arm movements play an important role in balance control, there is limited research into the role of arm movements during balance recovery after tripping in older adults. We investigated how older adults use their arms to recover from a trip and the difference in the effects of arm movements between fallers (n=5) and non-fallers (n=11).

Sixteen older males and females (69.7{+/-}2.3 years) walked along a walkway and were occasionally tripped over suddenly appearing obstacles. We analysed the first trip using a biomechanical model based on full-body kinematics and force-plate data to calculate whole body orientation during the trip and recovery phase. With this model, we simulated the effects of arm movements at foot-obstacle impact and during trip recovery on body orientation.

Apart from an increase in sagittal plane forward body rotation at touchdown in fallers, we found no significant differences between fallers and non-fallers in the effects of arm movements on trip recovery. Like earlier studies in young adults, we found that arm movements during the recovery phase had most favourable effects in the transverse plane: by delaying the transfer of angular momentum of the arms to the body, older adults rotated the tripped side more forward thereby allowing for a larger recovery step. Older adults that are prone to falling might improve their balance recovery after tripping by learning to prolong ongoing arm movements. Loss of histone methyltransferase SETD1B in oogenesis results in the redistribution of genomic histone 3 lysine 4 trimethylation Histone 3 lysine 4 trimethylation (H3K4me3) is an epigenetic mark found at gene promoters and CpG islands. H3K4me3 is essential for mammalian development, yet mechanisms underlying its genomic targeting are poorly understood. H3K4me3 methyltransferases SETD1B and MLL2 are essential for oogenesis. We investigated changes in H3K4me3 in Setd1b conditional knockout (cKO) oocytes using ultra-low input ChIP-seq, with comparisons to DNA methylation and gene expression analyses. H3K4me3 was redistributed in Setd1b cKO oocytes showing losses at active gene promoters associated with downregulated gene expression. Remarkably, many regions also gained H3K4me3, in particular those that were DNA hypomethylated, transcriptionally inactive and CpG-rich, which are hallmarks of MLL2 targets. Consequently, loss of SETD1B disrupts the balance between MLL2 and de novo DNA methyltransferases in determining the epigenetic landscape during oogenesis. Our work reveals two distinct, complementary mechanisms of genomic targeting of H3K4me3 in oogenesis, with SETD1B linked to gene expression and MLL2 to CpG content.

Graphical AbstractIn oogenesis, SETD1B and CXXC1 target H3K4me3 to actively transcribed gene promoters, while MLL2 targets transcriptionally inactive regions based on underlying CpG composition (upper panel). When SETD1B is ablated, H3K4me3 is lost at a subset of active promoters, resulting in downregulation of transcription (lower panel). Loss of SETD1B alters the activity of MLL2, permitting MLL2 to deposit H3K4me3 at CpG-rich regions, many of which should otherwise be DNA methylated. Thus, it is evident that MLL2 and de novo DNMTs compete for genomic occupancy late in oogenesis, and loss of SETD1B disrupts the balance of these mechanisms.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Speciation dynamics and extent of parallel evolution along a lake-stream environmental contrast in African cichlid fishes Understanding the drivers and dynamics of diversification is a central topic in evolutionary biology. Here, we investigated the dynamics of diversification in the cichlid fish Astatotilapia burtoni that diverged along a lake-stream environmental gradient. Whole-genome and morphometric analyses revealed that divergent selection was essential at the early stages of diversification, but that periods in allopatry were likely involved towards the completion of speciation. While morphological differentiation was continuous, genomic differentiation was not, as shown by two clearly separated categories of genomic differentiation. Reproductive isolation increased along a continuum of genomic divergence, with a "grey zone" of speciation at [~]0.1% net nucleotide divergence. The quantification of the extent of (non-)parallelism in nine lake-stream population pairs from four cichlid species by means of multivariate analyses revealed one parallel axis of genomic and morphological differentiation among seven lake-stream systems. Finally, we found that parallelism was higher when ancestral lake populations were more similar. Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics Data There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

Author summaryReconstruction of multiple association networks from high dimensional omics data is an important topic, especially in biology. Previous studies focused on estimating different networks and detecting common hubs among all classes. Integration of information over different classes of data while allowing difference in the hub nodes is also biologically plausible. Therefore, we propose a method, EDOHA, to jointly construct multiple interaction networks with capacity in finding different hub networks for each class of data. Simulation studies show the better performance over conventional methods. The method has been demonstrated in three real world data. 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. Including imprecisely georeferenced specimens improves accuracy of species distribution models and estimates of niche breadth: Don't let the perfect be the enemy of the good Museum and herbarium specimen records are frequently used to assess species conservation status and responses to climate change. Typically, records of occurrence with imprecise geolocality information are discarded because they cannot be matched confidently to environmental conditions, and are thus expected to increase uncertainty in downstream analyses. However, using only those records that can be precisely georeferenced risks undersampling of species environmental and geographic distributions. Using simulated and real species, we compared the effect of discarding versus retaining imprecise records on the accuracy of ecological niche models (ENMs), and estimates of niche breadth and extent of occurrence. Imprecise records were assigned to locations or climate values using a conservative approach. For simulated species, including imprecisely-georeferenced records alongside precisely-georeferenced records improved the accuracy of ENMs projected to the present and the future. Improvements were especially notable for species with <~20 precise occurrences, but accuracy continued to improve and eventually matched the accuracy of ENMs using all records with no georeferencing error. Using only precise records underestimated loss in suitable habitat and overestimated the amount of suitable habitat in both the present and future. Including imprecise records also improved univariate and multivariate estimates of niche breadth, and of species extent of occurrence. An analysis of 44 species in the genus Asclepias (milkweeds) revealed similarly large differences between cases using only precise records and those using precise plus imprecise records. Although the inclusion of imprecisely-georeferenced occurrence records may not always be appropriate, careful consideration must be made regarding the trade-offs between fidelity of the match between occurrences and the environment, versus sample size and how well precisely-geolocated records sample species environmental and geographic distributions. The preponderance of imprecisely georeferences specimens in museums and herbaria could be gainfully employed to address known shortfalls in sampling of species distributions and climatic niche tolerances. The first sheep graph-based pan-genome reveals the spectrum of structural variations and their effects on tail phenotypes Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here, we assembled 26 haplotype-resolved genome assemblies from 13 genetically diverse sheep using PacBio HiFi sequencing. We constructed a graph-based ovine pan-genome and discovered 142,422 biallelic insertions and deletions, 7,028 divergent alleles and 13,419 multiallelic variations. We then used a graph-based approach to genotype the biallelic SVs in 684 individuals from 45 domestic breeds and two wild species. Integration with RNA-seq data allows to identify candidate expression-associated SVs. We demonstrate a direct link of SVs and phenotypes by localizing the putative causative insertion in HOXB13 gene responsible for the long-tail trait and identifying multiple large SVs associated with the fat-tail. Beyond generating a benchmark resource for ovine structural variants, our study highlights that animal genetic research will greatly benefit from using a pan-genome graph rather than a single reference genome. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. Multi-omic analysis of the Arabidopsis clock activator mutant rve 4 6 8 reveals connections to carbohydrate metabolism and proteasome regulation Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE proteins (RVEs) are recently discovered members of the plant circadian circuitry that activate the evening complex and PRR genes to maintain regular circadian oscillation. The RVE 8 protein and its two homologs, RVE 4 and 6, have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw novel connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset, provides substantial new insights into the far reaching impact RVE8-like proteins have on the diel plant cell environment. Remarked Suppression of Aβ42 Protomer-protomer Dissociation Reaction via Pentamer Dimerization Multimeric protein complexes are molecular apparatuses to regulate biological systems and often determine their fate. Among proteins forming such molecular assemblies, amyloid proteins have drawn attention over a half-century since amyloid fibril formation of these proteins is supposed to be a common pathogenic cause for neurodegenerative diseases. This process is triggered by the accumulation of fibril-like aggregates, while the microscopic mechanisms are mostly elusive due to technical limitation of experimental methodologies in individually observing each of diverse aggregate species in the aqueous solution. We then addressed this problem by employing atomistic molecular dynamics simulations for the paradigmatic amyloid protein, amyloid-{beta} (1-42) (A{beta}42). Seven different dimeric forms of oligomeric A{beta}42 fibril-like aggregate in aqueous solution, ranging from tetramer to decamer, were considered. We found additive effects of the size of these fibril-like aggregates on their thermodynamic stability and have clarified kinetic suppression of protomer-protomer dissociation reactions at and beyond the point of pentamer dimer formation. This observation was obtained from the specific combination of the A{beta}42 protomer structure and the physicochemical condition that we here examined, while it is worthwhile to recall that several amyloid fibrils take dimeric forms of their protomers. We could thus conclude that the stable formation of fibril-like protomer dimer should be involved in a turning point where rapid growth of amyloid fibrils is triggered. Raman Signal Denoising using Fully Convolutional Encoder Decoder Network Raman spectroscopy is a vibrational method that gives molecular information rapidly and non-invasively. Despite its advantages, the weak intensity of Raman spectroscopy leads to low-quality signals, particularly with tissue samples. The requirement of high exposure times makes Raman a time-consuming process and diminishes its non-invasive property while studying living tissues. Novel denoising techniques using convolutional neural networks (CNN) have achieved remarkable results in image processing. Here, we propose a similar approach for noise reduction for the Raman spectra acquired with 10x lower exposure times. In this work, we developed fully convolutional encoder-decoder architecture (FCED) and trained them with noisy Raman signals. The results demonstrate that our model is superior (p-value < 0.0001) to the conventional denoising techniques such as the Savitzky-Golay filter and wavelet denoising. Improvement in the signal-to-noise ratio values ranges from 20% to 80%, depending on the initial signal-to-noise ratio. Thus, we proved that tissue analysis could be done in a shorter time without any need for instrumental enhancement. Avian haemosporidians (Plasmodium and Haemoproteus) status in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India and their phylogenetic relationships with other lineages of the world The avian haemosporidians (Plasmodium and Haemoproteus) are widely distributed and may affect the host populations from body damage at individual level to the extinction of a population. The knowledge about their status may help in future avifauna conservation plans. Hence, we examined the avian haemosporidians status, in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India, and their phylogenetic relationships with other known lineages of the world. We used the common genetic marker (Cytochrome b gene fragment of 479 bp) with information on the geographic distribution of parasite and host species available at MalAvi database. The prevalence of avian haemosporidians, from northern, eastern, and southern parts of India and phylogenetic genetic analysis of lineages was carried out to know the genetic relatedness among them at local and world level. The MCC tree revealed six Haemosporidian lineages in which one was common (H_MSP01) and five were unique (H_CYOPOL01, H_CHD01, H_CYORUB01, H_EUMTHA01, and P_GEOCIT01). The avian host richness Index was 2.0852. 9.9%, prevalence of Haemosporidian infection was found in 111 DNA samples belonging to 6 host species. The Haemoproteus prevalence was found to be 9.0 % across five host species (Phylloscopus trochiloides, Cyornis poliogenys, C. hainanus dialilaemus, C. rubeculoides, Eumiyas thalassinus) and Plasmodium prevalence was 0.9% in Geokichla citrina. Spatial phylogeny at global level showed H_MSP01 lineage, found in different host species in India, was genetically related to H. pallidus lineages (COLL2 and PFC1) in parts of Africa, Europe, North America, Malaysia, and Philippines. The Plasmodium lineage (P_GEOCIT01) was related to PADOM16 in Egypt with poor sequence similarity (93.89%). The statistical analysis suggested that the haemosporidians host species distribution range was directly and significantly associated with the altitude, minimum temperature, and relative humidity. H_MSP01 distribution was in accordance with H. pallidus having a wide geographic and host range. 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. Macroscopic control of synchronous electrical signaling with chemically-excited gene expression Excitable cells can convert electrical signals into chemical outputs to facilitate the active transport of information across larger distances. This electrical-to-chemical conversion requires a tightly regulated expression of ion channels. Alterations of ion channel expression provide landmarks of numerous pathological diseases, such as cardiac arrhythmia, epilepsy, or cancer. Although the activity of ion channels can be locally regulated by external light or chemical stimulus, it remains challenging to coordinate the expression of ion channels on extended spatial-temporal scales in a non-invasive manner. Here, we have engineered yeast S. cerevisiae to read and convert local chemical concentrations into a dynamic electrical field distributed across cell populations. The core mechanism encodes a chemically-excitable dual-feedback gene circuit that precisely tunes the expression domain of potassium channels, globally coordinating cyclic firing of the plasma membrane potential (PMP). We demonstrate that this mechanism leverages an engineered constitutively open bacterial potassium channel KcsA to directly couple chemical stimuli with ion flux through gene expression and it can interface with the host ion channels through the pulsatile production of toxins. Our study provides a robust synthetic transcriptional toolbox underlying the conversion of local chemical environments into spatiotemporally organized electrical impulses for various cellular engineering, synthetic biology, and potential therapeutic applications. Spontaneous differentiation leads to emergence of hybrid cell states relate to poor prognosis in oral cancer PurposeCellular dynamics between phenotypically heterogeneous subpopulations of cancer cells within individual tumor is shown to be responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Therefore, this study was undertaken to describe the dynamic phenotypic states among oral cancer cells, its influence on transcriptomic heterogeneity as well as its clinical significance.

Experimental DesignWe multiplexed phenotypic markers of putative oral-stem-like cancer cells (SLCCs) and characterized diversity among CD44-positive oral cancer cell subpopulations with respect to distinct expression of CD24 and aldehyde dehydrogenase (ALDH)-activity in multiple cell lines. Population trajectories were characterized by Markov model and cell states were defined based on the population specific RNA sequencing (RNAseq). ssGSEA based gene expression signatures were explore for prognostic significance.

ResultsOral cancer cells followed two distinct patterns of spontaneous repopulation dynamics with stochastic inter-conversions on  ALDH-axis, however a strict non-interconvertible transition on  CD24-axis. Interestingly, plastic  ALDH-axis was harnessed to enrich ALDHHigh subpopulations in response to Cisplatin treatment, to adapt a drug tolerant state. Phenotype-specific RNAseq results suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate states of stemness within the differentiating oral cancer cells. Further, survival analysis with each subpopulation-specific gene signature strongly suggested that the cell-state dynamics may act as possible mechanism to drive ITH, resulting in poor prognosis in patient.

ConclusionsOur results emphasized the prognostic power of the population dynamics in oral cancer. Importantly, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behaviour in oral cancer; which is a prerequisite knowledge important for precision treatment, however largely lacking for most solid tumors.

Graphical AbstractWe have characterized diversity among CD44-positive oral cancer cells lines with respect to distinct expression of CD24 and ALDH-activity. Subpopulations showed stochastic inter-conversions on ALDH-axis but a strict non-interconvertible transition of CD24Low to CD24High phenotype, even in response to chemotherapy-induced stress. RNAseq study suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate alternate states of stemness within the differentiating oral cancer cells. The described population dynamics demonstrtaed influence tumor behaviour possibly by increasing intratumoral heterogeneity in aggressive oral tumors.



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org.highwire.dtl.DTLVardef@1dc6a7org.highwire.dtl.DTLVardef@dd0948org.highwire.dtl.DTLVardef@18c9603org.highwire.dtl.DTLVardef@cca8fb_HPS_FORMAT_FIGEXP  M_FIG C_FIG Translational relevanceIntratumoral heterogeneity (ITH) has been the clinically important factor, impacting aggressive cancer behaviour, drug tolerance and overall poor prognosis. Recent high-throughput studies have provided better cellular and molecular resolution of ITH; however, the prerequisite knowledge which defines the composition of subpopulations critical for global tumor behaviour is majorly lacking for most of the solid tumors. By combining phenotypic markers, we have defined four subpopulations of oral cancer cells. These subpopulations showed stochastic inter-conversions as well as a strict non-interconvertible transition among them to acheive heterogeneity. Importantly, transcriptional states of each subpopulations indicated a clinically relevant signatures for patient prognosis. Also, we observed interconversions of these subpopulations in response to Cisplatin to accumulate drug-tolerant cell state, as rapid and reversible strategy to respond to chemotherapy induced stress. Thus, the characteristics of described phenotypic subgroups may be translated to the clinic for estimating the extent of intratumoral heterogeneity in oral cancer patients. Catchet-MS identifies IKZF1-targeting Thalidomide analogues as novel HIV-1 latency reversal agents A major pharmacological strategy toward HIV cure aims to reverse latency in infected cells as a first step leading to their elimination. While the unbiased identification of molecular targets physically associated with the latent HIV-1 provirus would be highly valuable to unravel the molecular determinants of HIV-1 transcriptional repression and latency reversal, due to technical limitations, this has not been possible. Here we use a dCas9 targeted chromatin and histone enrichment strategy coupled to mass spectrometry (Catchet-MS) to describe the protein composition of the latent and activated HIV-1 5LTR. Catchet-MS identified known and novel latent 5LTR-associated host factors. Among these, IKZF1 is a novel HIV-1 transcriptional repressor, required for Polycomb Repressive Complex 2 recruitment to the LTR. We find the clinically advanced thalidomide analogue iberdomide, and the FDA approved analogues lenalidomide and pomalidomide, to be novel LRAs that, by targeting IKZF1 for degradation, reverse HIV-1 latency in CD4+T-cells isolated from virally suppressed people living with HIV-1.

One Sentence SummarydCas9 targeted chromatin and histone enrichment for mass spectrometry (Catchet-MS) led to the identification of IKZF1-targeting thalidomide analogues as novel HIV-1 latency reversal agents Lytic phages displayed protective effects against soft rot-causing Pectobacterium sp. Soft rot caused by Pectobacterium sp. is responsible for significant losses in vegetable production worldwide. Methods for the effective control of soft rot are limited and are primarily based on good agricultural practices. The use of bacteriophages as biocontrol agents appears to be a promising alternative to combat phytopathogens. In this study, we investigated the efficacy of lytic phages recovered from symptomatic tissues and environmental samples against soft rot caused by Pectobacterium carotovorum subsp. carotovorum. Three bacteriophage isolates, designated as vB_PcaP-A3, vB_PcaM-D1, and vB_PcaM-J3, were observed to effectively lyse P. carotovorum subsp. carotovorum. Phage vB_PcaP-A3 exhibited virion morphology similar to the members of the podovirus group, while phages vB_PcaM-D1 and vB_PcaM-J3 showed myovirus morphology based on transmission electron microscopy. The optimal multiplicity of infection (MOI) differed greatly among the three phages. All three phages survived incubations at 30{degrees}C, 40{degrees}C and 50{degrees}C and pH conditions ranging from 3.0 to 9.0, but were all inactivated at 60{degrees}C and at pH 12. Both monophage and cocktail preparations were effective in inhibiting the growth of P. carotovorum subsp. carotovorum in the in vitro challenge tests. In the semi-in planta assays, while treatment with cocktail preparations completely inhibited the development of soft rot in tissue slices, monophage treatments not only resulted in significant reduction of tissue maceration in slices, but also showed protective effect against soft rot in tubers. Overall, these results demonstrate the efficacy of phages vB_PcaP-A3, vB_PcaM-D1, and vB_PcaM-J3 for the biocontrol of soft rot caused by P. carotovorum subsp. carotovorum. Excitatory and inhibitory motor cortical clusters account for balance, variability, and task performance Behaving animals have to process partial or incomplete information to plan movements. Neural activity and behavior of highly trained animals are strikingly variable across behavioral trials. In the present study, we show that incomplete information is reflected in both neural and behavioral variability. We study a mechanism for such variability in spiking neural network models with cluster topologies that enables multistability and attractor dynamics. Multistable attractors have been studied in spiking neural networks through clusters of strongly interconnected excitatory neurons. However, we show that existing models suffer from weak robustness and fail to reproduce the experimental findings. To overcome these problems, we introduce a novel architecture with excitatory and inhibitory clusters of spiking neurons. In contrast to earlier prominent models of excitatory clusters, this model ensures the local balance of excitation and inhibition and shows robust multistability across a wide range of network parameters. Furthermore, with the appropriate stimulation of network clusters, this network topology enables qualitatively and quantitatively reproducing in vivo firing rates, variability dynamics and behavioral reaction times for different task conditions as observed in recordings from the motor cortex of behaving monkeys. Coronavirus-associated molecular mimicry through homology to a SARS-CoV-2 peptide could be leading to susceptibility in patients with HLA-A*02:01 and HLA-A*24:02 serotypes This study aims to predict autoimmunity-related pathological mechanisms that possess risk for individuals with specific human leukocyte antigen (HLA) serotypes and shared by certain coronaviruses including SARS-CoV-2, based on homology to a SARS-CoV-2 peptide. With the given aim, 1-) coronavirus-associated sequences, which are homologous to the 15mer SARS-CoV-2 peptide CFLGYFCTCYFGLFC, are obtained. 2-) Human peptides that have at least 7 residue matches with those coronavirus sequences, and the SARS-CoV-2 15mer, are found. 3-) Epitope pairs, which are sourced by those aligned coronavirus and human sequences are identified. 4-) Epitope pairs that are predicted to bind strongly not only to the same HLA allele with each other but also to the same HLA allele as those of the respective alignment of the SARS-CoV-2 peptide are selected. Following are the identified proteins or peptides (with HLA-A*02:01 or HLA-A*24:02 epitopes), as described in 1-to-4: Immunoglobulin heavy chain junction regions, CRB1 isoform I precursor, slit homolog 2 protein, hCG1995581, hCG2028737, phospholipid phosphatase-related protein type 2. Among those, CRB1 isoform I precursor sequence with the predicted HLA-A*24:02 epitope aligns with the highest number of different sequences. Results imply autoimmunity risk in COVID-19 patients with HLA-A*02:01 and HLA-A*24:02 serotypes, through molecular mimicry, as a shared pathogenicity risk that can be prevalent upon getting infected with certain coronaviruses. These can pave way to improved risk groups assessment and autoimmunity treatment options, for COVID-19 and its associated diseases. Also, the approach in this study can be used to predict prospective pathologies of the transmissible variants in susceptible humans. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. 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. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. Medium-throughput zebrafish optogenetic platform identifies deficits in subsequent neural activity following brief early exposure to cannabidiol and Δ-9-tetrahydrocannabinol In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development.