bluuebunny/crossref_metadata_2025 huggingface dataset:
Postinspiratory complex acts as a gating mechanism regulating swallow-breathing coordination and other laryngeal behaviors
Authors: Huff Alyssa , Karlen-Amarante Marlusa , Oliveira Luiz Marcelo , Ramirez Jan Marino
Published: January 2023

Breathing needs to be tightly coordinated with upper airway behaviors, such as swallowing. Discoordination leads to aspiration pneumonia, the leading cause of death in neurodegenerative diseases. Here we study the role of the postinspiratory complex, (PiCo) in coordinating breathing and swallowing. Using optogenetic approaches in freely breathing-anesthetized ChATcre, Vglut2cre and co-transmission of ChATcre/Vglut2FlpO mice reveals this small brainstem microcircuit acts as a central gating mechanism for airway protective behaviors. Activation of PiCo during inspiration or the beginning of postinspiration triggers swallow behavior, while there is a higher probability for stimulating laryngeal activation when activated further into expiration, suggesting PiCo’s role in swallow-breathing coordination. PiCo triggers consistent swallow behavior and preserves physiologic swallow motor sequence, while stimulates laryngeal activation variable to stimulation duration. Sufficient bilateral PiCo activation is necessary for gating function since activation of only a few PiCo neurons or unilateral activation leads to blurred behavioral response. Viral tracing experiments reveal projections from the caudal nucleus of the solitary tract (cNTS), the presumed swallow pattern generator (SPG), to PiCo and vice versa. However, PiCo does not directly connect to laryngeal muscles. Investigating PiCo’s role in swallow and laryngeal coordination will aid in understanding discoordination in breathing and neurological diseases.
Single-cell RNA sequencing reveals aortic cellular heterogeneity in MSC_ITGB3-treated ApoE-/- mice on a high-fat diet
Authors: Hu Haijuan , Liu Demin , Geng Xue , Han Mei , Cui Wei
Published: January 2023

The aorta contains various cell types that are involved in the development of vascular inflammation and atherosclerosis. However, the cellular atlas of heterogeneous aorta cells, cellular responses, and intercellular communication has not been investigated in the background of a high-fat diet (HFD) and treatment with integrin beta 3-modified mesenchymal stem cells (MSC_ITGB3). In this study, 33,782 individual cells from mouse aortas under HFD with or without MSC_ITGB3 treatment were subjected to single-cell RNA sequencing as an unbiased analysis strategy. We generated a compendium of 30 different clusters, mainly smooth muscle cells (SMCs), endothelial cells, and immune cells. The proportion of the different cell types was considerably influenced by HFD and MSC_ITGB3. In the HFD group, genes associated with proliferation, migration, and collagen were highly expressed in the major SMC subpopulations. However, the expression of contraction-related genes in SMC subpopulations was significantly higher in the MSC_ITGB3 group than in the HFD group. After HFD consumption, subpopulations of ECs with active PI3K-Akt signaling pathway, ECM-receptor interaction, and contraction-related genes were significantly enriched. In the MSC_ITGB3 group, the number of dendritic cells (DCs), which are positively correlated with atherosclerotic lesion progression and contribute to lipid accumulation, and levels of inflammatory factors notably decreased. Our findings provide data on the composition, signaling pathways, and cellular communication of the aorta cells following stem cell treatment as well as on the evolution and progression of atherosclerotic disease. The findings may help in improving the treatment of atherosclerosis.
Sas3-mediated histone acetylation regulates effector gene activation in a fungal plant pathogen
Authors: Suarez-Fernandez Marta , Álvarez-Aragón Rocío , Pastor-Mediavilla Ana , Maestre-Guillén Alejandro , del Olmo Ivan , De Francesco Agustina , Meile Lukas , Sánchez-Vallet Andrea
Published: January 2023

Effector proteins are secreted by plant pathogens to enable host colonization. Typically, effector genes are tightly regulated, have very low expression levels in axenic conditions, and are strongly induced during host colonization. Chromatin remodeling contributes to the activation of effector genesin plantaby still poorly known mechanisms. In this work we investigated the role of histone acetylation in effector gene derepression in plant pathogens. We usedZymoseptoria tritici, a major pathogen of wheat, as a model to determine the role of lysine acetyltransferases (KATs) in plant infection. We showed that effector gene activation is associated with chromatin remodeling, featuring increased acetylation levels of histone H3 lysine 9 (H3K9) and 14 (H3K14) in effector loci. We functionally characterized the role ofZ. triticiKATs and demonstrated their distinct contributions to growth, development, and infection. Sas3 is required for host colonization and pycnidia production, while Gcn5 has a major role in pycnidia production. Furthermore, we demonstrated that Sas3 is involved in acetylation of H3K9 and H3K14 in effector loci and in effector gene activation during plant infection. We propose that Sas3-mediated histone acetylation is required for spatiotemporal activation of effector genes and virulence ofZ. tritici.

IMPORTANCE

Pathogen infections require the production of effectors that enable host colonization. Effectors have diverse functions and are only expressed at certain stages of the infection cycle. Thus, effector genes are tightly regulated by several mechanisms, including chromatin remodeling. Here, we investigate the role of histone acetylation in effector gene activation in the fungal wheat pathogenZymoseptoria tritici. We demonstrated that lysine acetyltransferases (KATs) are essential for the spatiotemporal regulation of effector genes. We show that two KATs, Sas3 and Gcn5, are involved in leaf symptom development and pycnidia formation. Importantly, our results indicated that Sas3 controls histone acetylation of effector loci and is a regulator of effector gene activation during stomatal penetration. Overall, our work demonstrates the key role of histone acetylation in regulating gene expression associated with plant infection.
Cracking the black box of deep sequence-based protein-protein interaction prediction
Authors: Bernett Judith , Blumenthal David B. , List Markus
Published: January 2023

Identifying protein-protein interactions (PPIs) is crucial for deciphering biological pathways. Numerous prediction methods have been developed as cheap alternatives to biological experiments, reporting surprisingly high accuracy estimates. We systematically investigated how much reproducible deep learning models depend on data leakage, sequence similarities, and node degree information, and compared them to basic machine learning models. We found that overlaps between training and test sets resulting from random splitting lead to strongly overestimated performances. In this setting, models learn solely from sequence similarities and node degrees. When data leakage is avoided by minimizing sequence similarities between training and test set, performances become random. Moreover, baseline models directly leveraging sequence similarity and network topology show good performances at a fraction of the computational cost. Thus, we advocate that any improvements should be reported relative to baseline methods in the future. Our findings suggest that predicting protein-protein interactions remains an unsolved task for proteins showing little sequence similarity to previously studied proteins, highlighting that further experimental research into the “dark” protein interactome and better computational methods are needed.
Recursive Prefix-Free Parsing for Building Big BWTs
Authors: Oliva Marco , Gagie Travis , Boucher Christina
Published: January 2023

Prefix-free parsing is useful for a wide variety of purposes including building the BWT, constructing the suffix array, and supporting compressed suffix tree operations. This linear-time algorithm uses a rolling hash to break an input string into substrings, where the resulting set of unique substrings has the property that none of the substrings’ suffixes (of more than a certain length) is a proper prefix of any of the other substrings’ suffixes. Hence, the name prefix-free parsing. This set of unique substrings is referred to as thedictionary. Theparseis the ordered list of dictionary strings that defines the input string. Prior empirical results demonstrated the size of the parse is more burdensome than the size of the dictionary for large, repetitive inputs. Hence, the question arises as to how the size of the parse can scale satisfactorily with the input. Here, we describe our algorithm,recursive prefix-free parsing, which accomplishes this by computing the prefix-free parse of the parse produced by prefix-free parsing an input string. Although conceptually simple, building the BWT from the parse-of-the-parse and the dictionaries is significantly more challenging. We solve and implement this problem. Our experimental results show that recursive prefix-free parsing is extremely effective in reducing the memory needed to build the run-length encoded BWT of the input. Our implementation is open source and available athttps://github.com/marco-oliva/r-pfbwt.
lmeEEG: Mass linear mixed-effects modeling of EEG data with crossed random effects
Authors: Visalli Antonino , Montefinese Maria , Viviani Giada , Finos Livio , Vallesi Antonino , Ambrosini Ettore
Published: January 2023

Background

Mixed-effects models are the current standard for the analysis of behavioral studies in psycholinguistics and related fields, given their ability to simultaneously model crossed random effects for subjects and items. However, they are hardly applied in neuroimaging and psychophysiology, where the use of mass univariate analyses in combination with permutation testing would be too computationally demanding to be practicable with mixed models.

New method

Here, we propose and validate an analytical strategy that enables the use of linear mixed models (LMM) with crossed random intercepts in mass univariate analyses of EEG data (lmeEEG). It avoids the unfeasible computational costs that would arise from massive permutation testing with LMM using a simple solution: removing random-effects contributions from EEG data and performing mass univariate linear analysis and permutations on the obtained marginal EEG.

Results

lmeEEG showed excellent performance properties in terms of power and false positive rate.

Comparison with existing methods

lmeEEG overcomes the computational costs of standard available approaches (our method was indeed more than 300 times faster).

Conclusions

lmeEEG allows researchers to use mixed models with EEG mass univariate analyses. Thanks to the possibility offered by the method described here, we anticipate that LMM will become increasingly important in neuroscience. Data and codes are available atosf.io/kw87a. The codes and a tutorial are also available atgithub.com/antovis86/lmeEEG.
The phosphodiesterase 2A regulates lymphatic endothelial development via cGMP-mediated control of Notch signaling
Authors: Carlantoni Claudia , Liekfeld Leon , Hemkemeyer Sandra A. , Schreier Danny , Saygi Ceren , Kurelic Roberta , Cardarelli Silvia , Kalucka Joanna , Schulte Christian , Beerens Manu , Mailer Reiner , Schäffer Tilman , Naro Fabio , Pellegrini Manuela , Nikolaev Viacheslav O. , Renné Thomas , Frye Maike
Published: January 2023

During vascular development endothelial junctions mature and vessel integrity is established to form the endothelial barrier. The molecular mechanisms by which lymphatic vessels induce cell contact inhibition are not understood. Here, we uncover the cGMP-dependent phosphodiesterase 2A (PDE2A) as a selective regulator of lymphatic, but not blood endothelial contact inhibition. Conditional deletion ofPde2ain mouse embryos reveals severe lymphatic dysplasia, while large blood vessel architecture remains unaltered. In the absence of PDE2A, human lymphatic endothelial cells fail to induce mature junctions and cell cycle arrest, while cGMP levels, but not cAMP levels, are increased. Loss of PDE2A-mediated cGMP hydrolysis leads to downregulation of NOTCH signaling. Vice versa, DLL4-induced NOTCH activation restores junctional maturation in PDE2A-deficient lymphatic endothelial cells. Our data demonstrate that PDE2A selectively modulates a crosstalk between cGMP and NOTCH signaling to finetune lymphatic development and suggest that PDE2A may be a druggable target to control lymphatic leakage and regeneration.
Trial-history biases in evidence accumulation can give rise to apparent lapses
Authors: Gupta Diksha , DePasquale Brian , Kopec Charles D. , Brody Carlos D.
Published: January 2023

Trial history biases and lapses are two of the most common suboptimalities observed during perceptual decision-making. These suboptimalities are routinely assumed to arise from distinct processes. However, several hints in the literature suggest that they covary in their prevalence and that their proposed neural substrates overlap – what could underlie these links? Here we demonstrate that history biases and apparent lapses can both arise from a common cognitive process that is normative under misbeliefs about non-stationarity in the world. This corresponds to an accumulation- to-bound model with history-dependent updates to the initial state of the accumulator. We test our model’s predictions about the relative prevalence of history biases and lapses, and show that they are robustly borne out in two distinct rat decision-making datasets, including data from a novel reaction time task. Our model improves the ability to precisely predict decision-making dynamics within and across trials, by positing a process through which agents can generate quasi-stochastic choices.
Towards reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning
Authors: Zajzon Barna , Duarte Renato , Morrison Abigail
Published: January 2023

To acquire statistical regularities from the world, the brain must reliably process, and learn from, spatiotemporally structured information. Although an increasing number of computational models have attempted to explain how such sequence learning may be implemented in the neural hardware, many remain limited in functionality or lack biophysical plausibility. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of sequential processing in cortical circuits, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable. Here we illustrate the importance of these aspects by providing a thorough investigation of a recent model proposed by Cone and Shouval (2021). We re-implement the modular columnar architecture and reward-based learning rule in the open-source NEST simulator, and successfully replicate the main findings of the original study. Building on these, we perform an in-depth analysis of the model’s robustness to parameter settings and underlying assumptions, highlighting its strengths and weaknesses. We demonstrate a limitation of the model consisting in the hard-wiring of the sequence order in the connectivity patterns, and suggest possible solutions. Finally, we show that the core functionality of the model is retained under more biologically-plausible constraints.
A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning
Authors: Gebodh Nigel , Miskovic Vladimir , Laszlo Sarah , Datta Abhishek , Bikson Marom
Published: January 2023

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness – detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework’s decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.
Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables
Authors: Wang Ching-Hao , Vetsigian Kalin , Lin Chris , Firth Finnian , Bradley Glyn , Granovsky Lena , England Jeremy L.
Published: January 2023

Developments in high-content phenotypic screening with single-cell read-out hold the promise of revealing interactions and functional relationships between genes at the genomic scale scale. However, the high-dimensionality and noisiness of gene expression makes this endeavor highly challenging when treated as a conventional problem in causal machine learning, both because of the statistical power required and because of the limits on computational tractability. Here we take different tack, and propose a deep-learning approach that finds low-dimensional representations of gene expression in which the response to genetic perturbation is highly predictable. We demonstrate that the interactions between genes that are cooperative in these representations are highly consistent with known ground-truth in terms of causal ordering, functional relatedness, and synergistic impact on cell growth and death. Our novel, statistical physics-inspired approach provides a tractable means through which to examine the response the living cell to perturbation, employing coarse graining that reduces data requirements and focuses on identifying simple relationships between groups of genes.

Author summary

Understanding the causal relationships between genes and the functions of a cell’s molecular components has long been a challenge in biology and biomedicine. With recent advancements in technologies that manipulate and measure the activity of thousands of genes at once at the single-cell level, scientists are now afforded with the opportunity to interrogate such relationships at scale. However, extracting useful information from the vast readouts of these technologies is non-trivial, in part due to their many-dimensional and noisy nature. Here we develop a machine learning model that allows for the interpretation of complex genetic perturbations in terms of a simple set of causal relations. By analyzing cooperative groups of genes identified by our model, we demonstrate the model can group genes accurately based on their biological function, their relative ordering up- or downstream in the flow of causation, and how their activities combine to affect cell growth and death. Our approach complements existing machine learning methods in providing a simple way to interpret causal mechanism governing genetic interactions and functional states of cells.
Gravitational and mechanical forces drive mitochondrial translation
Authors: Wakigawa Taisei , Kimura Yusuke , Mito Mari , Tsubaki Toshiya , Lee Muhoon , Nakamura Koki , Khan Abdul Haseeb , Saito Hironori , Yamamori Tohru , Yamazaki Tomokazu , Higashibata Akira , Tsuboi Tatsuhisa , Hirabayashi Yusuke , Takeuchi-Tomita Nono , Saito Taku , Higashitani Atsushi , Shichino Yuichi , Iwasaki Shintaro
Published: January 2023

Life on Earth has evolved in a form suitable for the gravitational force of 1 ×g. Although the pivotal role of gravity in gene expression has been revealed by multiomics approaches in space-flown samples and astronauts, the molecular details of how mammalian cells harness gravity have remained unclear. Here, we showed that mitochondria utilize gravity to activate protein synthesis within the organelle. Genome-wide ribosome profiling revealed reduced mitochondrial translation in mammalian cells andCaenorhabditis elegansunder both microgravity at the International Space Station and simulated microgravity in a 3D-clinostat on the ground. We found that attenuation of cell adhesion through laminin–integrin interactions causes the phenotype. The downstream signaling pathway including FAK, RAC1, PAK1, BAD, and Bcl-2 family proteins in the cytosol, and mitochondrial fatty acid synthesis (mtFAS) pathway in the matrix maintain mitochondrial translation at high level. Mechanistically, a decreased level of mitochondrial malonyl-CoA, which is consumed by activated mtFAS, leads to a reduction in the malonylation of the translational machinery and an increase in the initiation and elongation ofin organellotranslation. Consistent with the role of integrin as a mechanosensor, we observed a decrease in mitochondrial translation via the minimization of mechanical stress in mouse skeletal muscle. Our work provides mechanistic insights into how cells convert gravitational and mechanical forces into translation in an energy-producing organelle.
A multi-kingdom genetic barcoding system for precise target clone isolation
Authors: Ishiguro Soh , Ishida Kana , Sakata Rina C. , Mori Hideto , Takana Mamoru , King Samuel , Bashth Omar , Ichiraku Minori , Masuyama Nanami , Takimoto Ren , Kijima Yusuke , Adel Arman , Toyoshima Hiromi , Seki Motoaki , Oh Ju Hee , Archambault Anne-Sophie , Nishida Keiji , Kondo Akihiko , Kuhara Satoru , Aburatani Hiroyuki , Klein Geltink Ramon I. , Takashima Yasuhiro , Shakiba Nika , Yachie Nozomu
Published: January 2023

Clonal heterogeneity underlies diverse biological processes, including cancer progression, cell differentiation, and microbial evolution. Cell tagging strategies with DNA barcodes have recently enabled analysis of clone size dynamics and clone-restricted transcriptomic landscapes of heterogeneous populations. However, isolating a target clone that displays a specific phenotype from a complex population remains challenging. Here, we present a new multi-kingdom genetic barcoding system, CloneSelect, in which a target cell clone can be triggered to express a reporter gene for isolation through barcode-specific CRISPR base editing. In CloneSelect, cells are first barcoded and propagated so their subpopulation can be subjected to a given experiment. A clone that shows a phenotype or genotype of interest at a given time can then be isolated from the initial or subsequent cell pools stored throughout the experimental timecourse. This novel CRISPR-barcode genetics platform provides many new ways of analyzing and manipulating mammalian, yeast, and bacterial systems.

Teaser

A multi-kingdom CRISPR-activatable barcoding system enables the precise isolation of target barcode-labeled clones from a complex cell population.
Predictors of sensorimotor adaption: insights from over 100,000 reaches
Authors: Tsay Jonathan S. , Asmerian Hrach , Germine Laura T. , Wilmer Jeremy , Ivry Richard B. , Nakayama Ken
Published: January 2023

Sensorimotor adaptation is essential for keeping our movements well-calibrated in response to changes in the body and environment. For over a century, we have studied sensorimotor adaptation in highly controlled laboratory settings that typically involve small sample sizes. While this approach has proven useful to characterize different learning processes, laboratory studies are typically very underpowered to generate data suited for exploring the myriad of factors that may modulate motor performance. Here, using a citizen science website (testmybrain.org), we collected over 2000 sessions on a visuomotor rotation task. This unique dataset has allowed us to replicate classic motor findings, reconcile controversial findings in the learning and memory literature, and discover novel constraints underlying dissociable implicit and explicit learning processes supporting sensorimotor adaptation. Taken together, this study suggests that large-scale motor learning studies hold enormous potential to advance sensorimotor neuroscience.
Metabolic responses of normal rat kidneys to a high salt intake
Authors: Shimada Satoshi , Hoffmann Brian R. , Yang Chun , Kurth Theresa , Greene Andrew S. , Liang Mingyu , Dash Ranjan K. , Cowley Allen W.
Published: January 2023

In the present study, novel methods were developed which allowed continuous (24/7) measurement of blood pressure (BP) and renal blood flow (RBF) in freely moving rats and the intermittent collection of arterial and renal venous blood to estimate kidney metabolic fluxes of O2and metabolites. The study determined the effects of a high salt (HS) diet upon whole kidney O2consumption and the metabolomic profiles of normal Sprague Dawley (SD) rats. A separate group of rats was studied to determine changes in the cortex (Cx) and outer medulla (OM) tissue metabolomic and mRNAseq profiles before and following the switch from a 0.4% to a 4.0% NaCl diet. Significant changes in the metabolomic and transcriptomic profiles occurred with feeding of the HS diet. A progressive increase of kidney O2consumption was found despite a reduction in expression of most of the mRNA encoding enzymes of TCA cycle. Increased glycolysis was evident with the elevation of mRNA expression encoding key glycolytic enzymes and release of pyruvate and lactate from the kidney in the renal venous blood. Glycolytic production of NADH is used in either the production of lactate or oxidized via the malate aspartate shuttle. Aerobic glycolysis (e.g., Warburg-effect) may account for the needed increase in cellular energy. The study provides evidence that kidney metabolism responds to a HS diet enabling enhanced energy production while protecting from oxidate stress and injury.
Intrathecal [64Cu]Cu-albumin PET reveals age-related decline of cerebrospinal fluid (CSF)-lymphatic efflux
Authors: Sarker Azmal , Suh Minseok , Choi Yoori , Park Ji Yong , Lee Yun-Sang , Lee Dong Soo
Published: January 2023

Age-related cognitive decline is associated with dysfunctional lymphatic efflux of cerebrospinal fluid (CSF) through meningeal lymphatic vessels. Intrathecal [64Cu]Cu-albumin positron emission tomography (PET) was applied in mice for the evaluation of lymphatic efflux of CSF and its age-related variation. [64Cu]Cu-albumin PET was done at multiple time points after intrathecal injection of [64Cu]Cu-albumin with the infusion speed of 700 nl/min in the adult and aged mice of 15–25 months old age. CSF clearance and paravertebral lymph nodes were quantified after injection and at later stationary phase. Representing perturbed state by 6 μl (1/7 of CSF volume with twice the production rate for 9 minutes of intrathecal injection) and at the next day of stationary return of CSF dynamics in mice, CSF clearance half-time from the subarachnoid space was 93.4 ± 19.7 in adult and 123.3 ± 15.6 minutes in aged mice (p = 0.01). The % injected dose at 4, 6 and 24 hours were higher in aged mice than in the adult mice (p < 0.05) and the visualized paravertebral lymph node activity tended to be lower in the aged, which was different from [64Cu]Cu-NOTA or [64Cu]Cu-ESION PET. [64Cu]Cu-albumin PET enabled quantification of CSF-lymphatic efflux over all the levels of brain spinal cords and visualization with quantifiability of lymph node activity. [64Cu]Cu-albumin PET revealed an age-related decrease in CSF-lymphatic efflux due to less efflux from the subarachnoid space, especially at stationary phase in the aged mice.
Sex chromosome evolution in beetles
Authors: Bracewell Ryan , Tran Anita , Chatla Kamalakar , Bachtrog Doris
Published: January 2023

Beetles are the most species-rich group of animals and harbor diverse karyotypes. Most species have XY sex chromosomes, but X0 sex determination mechanisms are also common in some groups. We generated a whole-chromosome assembly of a beetle species with a neo-sex chromosome and utilize eleven additional beetle genomes, to reconstruct karyotype evolution across Coleoptera. We identify ancestral linkage groups, termed Stevens elements, that share a conserved set of genes across beetles. While the ancestral X chromosome is maintained across beetles, we find independent additions of autosomes to the ancestral sex chromosomes. These neo-sex chromosomes evolve the stereotypical properties of sex chromosomes, including the evolution of dosage compensation, and a non-random distribution of genes with sex-biased expression. Beetles thus provide a novel model to gain a better understanding of the diverse forces driving sex chromosome evolution.
Targeted Screening and Identification of Chlorhexidine as a Pro-myogenic Circadian Clock Activator
Authors: Kiperman Tali , Li Weini , Xiong Xuekai , Li Hongzhi , Horne David , Ma Ke
Published: January 2023

Background

Circadian clock is an evolutionarily-conserved mechanism that exerts pervasive temporal control in stem cell behavior. This time-keeping machinery is required for orchestrating myogenic progenitor properties in regenerative myogenesis that ameliorates muscular dystrophy. Here we report a screening platform to discover circadian clock modulators that promote myogenesis, with the identification of chlorhexidine (CHX) as a clock-activating molecule with pro-myogenic activities.

Methods

A high-throughput molecular docking pipeline was applied to identify candidate compounds with a structural fit for a hydrophobic pocket within the key circadian transcription factor protein, Circadian Locomotor Output Cycles Kaput (CLOCK). Secondary biochemical screen for clock-modulatory activities of these molecules were preformed, together with functional validations of myogenic regulations to identify modulators with pro-myogenic properties.

Results

CHX was identified as a clock activator that promotes distinct aspects of myogenesis. CHX activated circadian clock that reduced cycling period length and augmented amplitude. This action was mediated by the targeted CLOCK structure via augmented interaction with heterodimer partner Bmal1, leading to enhanced CLOCK/Bmal1-controlled transcription with up-regulation of core clock genes. Consistent with its clock-activating function, CHX displayed robust effects on stimulating myogenic differentiation in a clock-dependent manner. In addition, CHX augmented the proliferative and migratory activities of myoblasts.

Conclusion

Our findings demonstrate the feasibility of a screening platform to discover clock modulators with myogenic regulatory activities. Discovery of CHX as a pro-myogenic molecule could be applicable to promote regenerative capacities in ameliorating dystrophic or degenerative muscle diseases.
Raman spectroscopy, used transcutaneously and non-invasively from a finger, to predict COVID-19: A feasibility, proof-of-concept study
Authors: Chefitz Allen B. , Birch Thomas , Yang Yongwu , Hussain Arib
Published: January 2023

BACKGROUND

A definitive COVID-19 infection typically is diagnosed by laboratory tests, including real-time, reverse-transcriptase Polymerase Chain Reaction (PCR)-based testing. These currently available COVID-19 tests require the patient to provide an extra-corporeal specimen and the results may not be immediate. Consequently, a variety of rapid antigen tests for COVID-19, all with a wide range of accuracy in terms of sensitivity and specificity, has proliferated (1,2). These rapid tests now represent a significantly larger proportion of all testing done for COVID-19, yet suffer from requiring a physical specimen from the nose or mouth and waiting 15 minutes for most.

As a solution, we propose a non-invasive, trans-cutaneous, real-time viral detection device, based on the principles of Raman spectroscopy and machine learning. It does not require any extra-corporeal specimens and can be configured for self-administration. It can be easily used by non-experts and does not require medical training. Our approach suggests that our non-invasive, transcutaneous method may be broadly useful not only in COVID-19 diagnosis, but also in other diagnoses.

METHODS

160 COVID positive (+) patients and 316 COVID negative (-) patients prospectively underwent nasal PCR testing concurrently with testing using our non-invasive, transcutaneous, immediate viral detector. Both the PCR and our experimental viral detector tests were performed side-by-side on outpatients (N=389) as well as inpatients (N= 87) at Holy Name Medical Center in Teaneck, NJ between June 2021 and August, 2022. The spectroscopic data were generated using an 830nm Raman System with SpectraSoft (W2 Innovations)and then, using machine learning, processed to provide an immediate prediction. A unique patient-interface for finger insertion enabled the application of Raman spectroscopy to viral detection in humans.

RESULTS

The data analysis algorithm demonstrates that there is an informative Raman spectrum output from the device, and that individual Raman peaks vary between cases and controls. Our proof-of-concept study yields encouraging results, with a specificity for COVID-19 of 0.75, and a sensitivity (including asymptomatic patients) of 0.80.

CONCLUSIONS

The combination of Raman spectroscopy, artificial intelligence, and our unique patient-interface admitting only a patient finger achieved test results of 0.75 specificity and 0.80 sensitivity for COVID-19 testing in this first in human proof-of-concept study. More significantly, the predictability improved with increasing data.
Assessing treatment effect modification due to comorbidity using individual participant data from industry-sponsored drug trials
Authors: Hanlon Peter , Butterly Elaine W , Shah Anoop SV , Hannigan Laurie J , Lewsey Jim , Mair Frances S , Kent David , Guthrie Bruce , Wild Sarah H , Welton Nicky J , Dias Sofia , McAllister David A
Published: January 2023

Background

People with comorbidities are under-represented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD).

Methods and Results

Using 126 industry-sponsored phase 3/4 trials across 23 index conditions, we performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition), (ii) presence or absence of the six commonest comorbid diseases for each index condition, and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular function).

Comorbidities were under-represented in trial participants and few had >2 comorbidities. We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for three conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., Sodium-glucose co-transporter inhibitors for type 2 diabetes – interaction term for comorbidity count 0.004, 95% CI - 0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma – interaction term -0.22, 95% CI -1.07 to 0.54).

Conclusion

For trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. Our findings support the assumption that estimates of treatment efficacy are constant, at least across modest levels of comorbidity.
Antenatal Care Dropout and Associated Factors in Ethiopia: A Systematic Review and Meta-Analysis
Authors: Sisay Gizaw , Mulat Tsion
Published: January 2023

Background

Antenatal care during pregnancy is one of the most important strategies for improving maternal and newborn health and preventing maternal and newborn mortality and morbidity. The prevalence and predictors of antenatal care dropout in Ethiopia were studied, and the results were inconsistent and showed considerable variation. Hence, this meta-analysis aimed at estimating the overall prevalence of antenatal care dropout and its associated factors in Ethiopia.

Methods

A comprehensive search of studies published before December 30, 2022, was explored by using distinct international databases such as (PubMed, DOJA, Embase, Cochrane library, African journals online, Google scholar, web of science and the institutional repository of Ethiopian universities were used to search relevant studies. Data were extracted using Microsoft Excel, and analysis was performed using STATA version 16. A random-effects model were used to estimate the overall prevalence of antenatal care drop-out and odd ratio for determinant factors.I2Test-statistics for to assessing heterogeneity and Egger’s test for assessing publication bias were used.

Results

A total of seven studies were included for this systematic review and meta-analysis with of 11839 study participants. The overall pooled prevalence of antenatal dropout in Ethiopia was found to be 41.37% with 95% CI: (35.04, 47.70). Distance from the health care facility (AOR = 2.55, 95% CI = 1.79, 3.31), pregnancy complication signs (AOR = 2.88, 95% CI= 2.41, 3.66), place of residence (AOR= 1.59, 95% CI = 1.31, 1.87), educational level (AOR=1.79, 95%CI = 1.37, 2.21), age group(30-49) (AOR=(AOR = 0.57, 95% CI = 0.26, 0.88) were significantly associated with antenatal care dropout.

Conclusion

Based on this systematic review and meta-analysis, 41% of Ethiopian women dropped out of antenatal care visits before the minimum recommended visit (four times). Hence, to reduce the number of ANC dropouts it is important to counsel and educate women at their first prenatal care. Issues of urban-rural disparity and locations identified as hotspots for incomplete ANC visits require that further attention.
Estimating The Uncertain Effect of the COVID Pandemic on Drug Overdoses
Authors: Moghtaderi Ali , Zocchi Mark S. , Pines Jesse M. , Venkat Arvind , Black Bernard
Published: January 2023

Objective

U.S. drug-related overdose deaths and Emergency Department (ED) visits rose in 2020 and again in 2021. Multiple studies and the news media attributed this rise primarily to increased drug use resulting from the societal disruptions related to the coronavirus (COVID-19) pandemic. A competing explanation is that higher overdose deaths and ED visits may instead have been a continuation of pre-pandemic trends in synthetic-opioid deaths. We assess the evidence on whether increases in overdose deaths and ED visits are likely to be causally related to the COVID-19 pandemic, increased synthetic-opioid use, or some of both.

Methods

We use national data from the Centers for Disease Control and Prevention (CDC) on rolling 12-month drug-related deaths (2015-2021); CDC data on monthly ED visits (2019-September 2020); and ED visit data across 21states from a national ED group (January 2016-June 2022). We study drug overdose deaths per 100,000 persons during the pandemic period, and ED visits for drug overdoses, compared to predicted levels based on pre-pandemic trends.

Results

Mortality

National overdose mortality increased from 21/100,000 in 2019 to 26/100,000 in 2020 and 30/100,000 in 2021. The 2020 increase is well-predicted by models that extrapolate pre-pandemic trends for rolling 12-month mortality to the pandemic period, consistent with higher mortality reflecting continuation of those trends. Placebo analyses (which assume the pandemic started earlier or later than March 2020) do not provide evidence for a change in trend in or soon after March 2020. State-level analyses of actual-minus-predicted mortality, relative to pre-pandemic trends, show no consistent pattern. The state-level results support state heterogeneity in overdose mortality trends, and do not support the pandemic being a major driver of overdose mortality.

ED visits

ED overdose visits rose during our sample period, reflecting a worsening opioid epidemic, but rose at similar rates during the pre-pandemic and pandemic periods.

Conclusion

The causes of rising overdose mortality in 2020 and 2021 cannot be definitely determined, but the observed increases can be largely explained by a continuation of pre-pandemic trends in synthetic-opioid deaths, principally fentanyl. In contrast to prior studies, we do not find support for the pandemic having been a principal driver of rising mortality. Policymakers need to directly address the synthetic opioid epidemic, and not expect a respite as the pandemic recedes.
CONSTANS alters the circadian clock inArabidopsis thaliana
Authors: de los Reyes Pedro , Romero-Campero Francisco J , Gao He , Serrano-Bueno Gloria , Romero Jose M , Valverde Federico
Published: January 2023

Abstract

Plants are sessile organisms that have acquired highly plastic developmental strategies to adapt to the environment. Among these processes, the floral transition is essential to ensure reproductive success and is finely regulated by several internal and external genetic networks. The photoperiodic pathway, which controls the plant response to day length, is one of the most important pathways controlling flowering. InArabidopsisphotoperiodic flowering,CONSTANS(CO) is the central gene activating the expression of the florigenFLOWERING LOCUS T(FT)in the leaves at the end of a long day.COexpression is strongly regulated by the circadian clock. However, to date, no evidence has been reported regarding a feedback loop from the photoperiod pathway back to the circadian clock. Using transcriptional networks, we have identified relevant network motifs regulating the interplay between the circadian clock and the photoperiod pathway. Gene expression, chromatin immunoprecipitation experiments and phenotypic analysis allowed us to elucidate the role of CO over the circadian clock. Plants with alteredCOexpression showed a different internal clock period, measured by daily rhythmic movements in the leaves. We show that CO is able to activate key genes related to the circadian clock, such asCCA1,LHY,PRR5andGI,at the end of a long day by binding to specific sites on their promoters. Moreover, a significant number of PRR5 repressed target genes are upregulated by CO, and this could explain the phase transition promoted by CO. The CO-PRR5 complex interacts with the bZIP transcription factor HY5 and helps to localize the complex in the promoters of clock genes. Our results indicate that there may be a feedback loop in which CO communicates back to the circadian clock, feeding seasonal information to the circadian system.
Insights into the Microbial Weathering of Chinese Wooden Ancestral Halls in Guangdong Province
Authors: Liu Manchun , Su Xining , Wen Qinqing , Yang Tongshu , Lin Muyuyang , Abudureyimu Paierzhati , Lon Jerome Rumdon , Luo Jianfei
Published: January 2023

Abstract

Wooden buildings are facing biodeterioration due to natural weathering. Ancestral halls are traditional Chinese wooden architecture with high artistic value. The research analyzed the microbial diversity of nine ancestral halls in Guangdong Province under subtropical monsoon climates. With amplicon sequencing, we found a common core microorganism group, includingBacillus,Pseudomonas,Paenibacillus,Acinetobacter,Toxicocladosporium,Cladosporium,Aspergillus, andEpicoccum. A total of 8 different species of bacteria and 7 different species of fungi were isolated from Chen Clan Ancestral halls, most of which were proven to be capable of degrading cellulose or lignin. The comparison between damaged and undamaged sites (whether the paint coating is flaked off) revealed similar microbial compositions but with differing abundances.FirmicutesandAscomycotadominated damaged surfaces, whileProteobacteriaandActinobacteriaprevailed in undamaged ones. Notably,Cladosporium, widely present in both sites, emerged as the primary cellulose-degrading genus. Given the similar microbial compositions between damaged and undamaged sites, it is suggested that using paint alone as the exclusive means to protect bare wood is insufficient. Apparent correlation between microorganisms on wooden surfaces and humans showed that the increase of visitor flow rates might impact the microbiota composition on cultural relics. We evaluated the effect of four representative biocides and determined the feasibility of low-concentration Isothiazolinone. This research facilitates a basic understanding of the microbial weathering of ancestral halls and add significant reference for preserving wooden structures.
Widespread distribution and evolution of poxviral entry-fusion complex proteins in giant viruses
Authors: Kao Sheng , Kao Chi-Fei , Chang Wen , Ku Chuan
Published: January 2023

Poxviruses are known to encode a set of proteins that form an entry-fusion complex (EFC) to mediate virus entry. However, the diversity, evolution, and origin of these EFC proteins remain poorly understood. Here we identify the EFC protein homologs in poxviruses and other giant viruses of phylumNucleocytoviricota. The 11 EFC genes are present in almost all pox-viruses, with the two smallest, G3 and O3, absent inEntomopoxvirinaeand basal lineages ofChordopoxvirinae. Five of the EFC genes are further grouped into two families, A16/G9/J5 and F9/L1, which are widely distributed across other major lineages ofNucleocytoviricota, including metagenome-assembled genomes, but are generally absent in viruses infecting algae or non-amoebozoan heterotrophic protists. The A16/G9/J5 and F9/L1 families co-occur, mostly as single copies, in 93% of the non-Poxviridaegiant viruses that have at least one of them. Distribution and phylogenetic patterns suggest that both families originated in the ancestor ofNucleocytoviricota. In addition to thePoxviridaegenes, homologs from each of the otherNucleo-cytoviricotafamilies are largely clustered together, suggesting their ancient presence and vertical inheritance. Despite deep sequence divergences, we observed noticeable conservation of cysteine residues and predicted structures between EFC proteins ofPoxviridaeand other families. Overall, our study reveals widespread distribution of these EFC protein homologs beyond pox-viruses, implies the existence of a conserved membrane fusion mechanism, and sheds light on host range and ancient evolution ofNucleocytoviricota.

Importance

Fusion between virus and host membranes is critical for viruses to release genetic materials and to initiate infection. Whereas most viruses use a single protein for membrane fusion, poxviruses employ a multi-protein entry-fusion complex (EFC). We report that two major families of the EFC proteins are widely distributed within the virus phylumNucleocytoviricota, which include poxviruses and other dsDNA “giant viruses” that infect animals, amoebozoans, algae, and various microbial eukaryotes. Each of these two protein families is structurally conserved, traces its origin to the root ofNucleocytoviricota, was passed down to the major subclades ofNucleocytoviricota, and is retained in most giant viruses known to infect animals and amoebozoans. The EFC proteins therefore represent a potential mechanism for virus entry in diverse giant viruses. We hypothesize that they may have facilitated the infection of an animal/amoebozoan-like host by the lastNucleocytoviricotacommon ancestor.