bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultra-Fast Bioorthogonal Spin-Labeling and Distance Measurements in Mammalian Cells Using Small, Genetically Encoded Tetrazine Amino Acids
Authors: Jana Subhashis , Evans Eric G. B. , Jang Hyo Sang , Zhang Shuyang , Zhang Hui , Rajca Andrzej , Gordon Sharona E. , Zagotta William N. , Stoll Stefan , Mehl Ryan A.
Published: January 2023

Studying protein structures and dynamics directly in the cellular environments in which they function is essential to fully understand the molecular mechanisms underlying cellular processes. Site-directed spin-labeling (SDSL)—in combination with double electron–electron resonance (DEER) spectroscopy—has emerged as a powerful technique for determining both the structural states and the conformational equilibria of biomacromolecules. In-cell DEER spectroscopy on proteins in mammalian cells has thus far not been possible due to the notable challenges of spin-labeling in live cells. In-cell SDSL requires exquisite biorthogonality, high labeling reaction rates and low background signal from unreacted residual spin label. While the bioorthogonal reaction must be highly specific and proceed under physiological conditions, many spin labels display time-dependent instability in the reducing cellular environment. Additionally, high concentrations of spin label can be toxic. Thus, an exceptionally fast bioorthogonal reaction is required that can allow for complete labeling with low concentrations of spin-label prior to loss of signal. Here we utilized genetic code expansion to site-specifically encode a novel family of small, tetrazine-bearing non-canonical amino acids (Tet-v4.0) at multiple sites in green fluorescent protein (GFP) and maltose binding protein (MBP) expressed both inE. coliand in human HEK293T cells. We achieved specific and quantitative spin-labeling of Tet-v4.0-containing proteins by developing a series of strainedtrans-cyclooctene (sTCO)-functionalized nitroxides—including agem-diethyl-substituted nitroxide with enhanced stability in cells—with rate constants that can exceed 106M−1s−1. The remarkable speed of the Tet-v4.0/sTCO reaction allowed efficient spin-labeling of proteins in live HEK293T cells within minutes, requiring only sub-micromolar concentrations of sTCO–nitroxide added directly to the culture medium. DEER recorded from intact cells revealed distance distributions in good agreement with those measured from proteins purified and labeledin vitro. Furthermore, DEER was able to resolve the maltose-dependent conformational change of Tet-v4.0-incorporated and spin-labeled MBPin vitroand successfully discerned the conformational state of MBP within HEK293T cells. We anticipate the exceptional reaction rates of this system, combined with the relatively short and rigid side chains of the resulting spin labels, will enable structure/function studies of proteins directly in cells, without any requirements for protein purification.

TOC
Considering dynamic nature of the brain: the clinical importance of connectivity variability in machine learning classification and prediction
Authors: Song Inuk , Lee Tae-Ho
Published: January 2023

The brain connectivity of resting-state fMRI (rs-fMRI) represents an intrinsic state of brain architecture, and it has been used as a useful neural marker for detecting psychiatric conditions as well as for predicting psychosocial characteristics. However, most studies using brain connectivity have focused more on the strength of functional connectivity over time (static-FC) but less attention to temporal characteristics of connectivity changes (FC-variability). The primary goal of the current study was to investigate the effectiveness of using the FC-variability in classifying an individual’s pathological characteristics from others and predicting psychosocial characteristics. In addition, the current study aimed to prove that benefits of the FC-variability are reliable across various analysis procedures. To this end, three open public large resting-state fMRI datasets including individuals with Autism Spectrum Disorder (ABIDE;N= 1249), Schizophrenia disorder (COBRE;N= 145), and typical development (NKI;N= 672) were utilized for the machine learning (ML) classification and prediction based on their static-FC and the FC-variability metrics. To confirm the robustness of FC-variability utility, we benchmarked the ML classification and prediction with various brain parcellations and sliding window parameters. As a result, we found that the ML performances were significantly improved when the ML included FC-variability features in classifying pathological populations from controls (e.g., individuals with autism spectrum disorder vs. typical development) and predicting psychiatric severity (e.g., score of autism diagnostic observation schedule), regardless of parcellation selection and sliding window size. Additionally, the ML performance deterioration was significantly prevented with FC-variability features when excessive features were inputted into the ML models, yielding more reliable results. In conclusion, the current finding proved the usefulness of the FC-variability and its reliability.
Top-down Proteomics of Myosin Light Chain Isoforms Define Chamber-Specific Expression in the Human Heart
Authors: Bayne Elizabeth F. , Rossler Kalina J. , Gregorich Zachery R. , Aballo Timothy J. , Roberts David S. , Chapman Emily A. , Guo Wei , Ralphe J. Carter , Kamp Timothy J. , Ge Ying
Published: January 2023

Myosin functions as the “molecular motor” of the sarcomere and generates the contractile force necessary for cardiac muscle contraction. Myosin light chains 1 and 2 (MLC-1 and -2) play important functional roles in regulating the structure of the hexameric myosin molecule. Each of these light chains has an ‘atrial’ and ‘ventricular’ isoform, so called because they are believed to exhibit chamber-restricted expression in the heart. However, recently the chamber-specific expression of MLC isoforms in the human heart has been questioned. Herein, we analyzed the expression of MLC-1 and -2 atrial and ventricular isoforms in each of the four cardiac chambers in adult non-failing donor hearts using top-down mass spectrometry (MS)-based proteomics. Strikingly, we detected an isoform thought to be ventricular, MLC-2v, in the atria and confirmed the protein sequence using tandem MS (MS/MS). For the first time, a putative deamidation post-translation modification (PTM) located on MLC-2v in atrial tissue was localized to amino acid N13. MLC-1v and MLC-2a were the only MLC isoforms exhibiting chamber-restricted expression patterns across all donor hearts. Importantly, our results unambiguously show that MLC-1v, not MLC-2v, is ventricle-specific in adult human hearts. Overall, top-down proteomics allowed us an unbiased analysis of MLC isoform expression throughout the human heart, uncovering previously unexpected isoform expression patterns and PTMs.
Emergence of distributed working memory in a human brain network model
Authors: Feng Mengli , Bandyopadhyay Abhirup , Mejias Jorge F.
Published: January 2023

Working memory is a fundamental cognitive function which allows to transiently store and manipulate relevant information in memory. While it has been traditionally linked to activity in specific prefrontal cortical areas, recent electrophysiological and imaging evidence has shown co-occurrent activities in different brain regions during working memory. To dissect the mechanisms behind the emergence of such distributed working memory activity in the human brain, we built and analyzed a detailed, data-constrained model of the human brain combining multiple sources of large-scale brain data. The model reveals the emergence of distributed working memory patterns which rely on long-range synaptic projections, differing from classical models where working memory emerges due to local recurrent connectivity. When compared to existing evidence regarding areas linked to working memory, our model explains almost 80% of the observed variability across brain areas. Our results predict important differences between the distributed working memory in human and non-human primates, and propose a potential solution for the debate regarding the role of early visual areas in working memory encoding. This work provides a novel approach to simulate the human brain which combines the richness of large-scale brain dynamics with the insight of mechanistic models of cognitive functions.
A unified hypothesis-free feature extraction framework for diverse epigenomic data
Authors: Balcı Ali Tuğrul , Chikina Maria
Published: January 2023

Motivation

Epigenetic assays using next-generation sequencing (NGS) have furthered our understanding of the functional genomic regions and the mechanisms of gene regulation. However, a single assay produces billions of data represented by nucleotide resolution signal tracks. The signal strength at a given nucleotide is subject to numerous sources of technical and biological noise and thus conveys limited information about the underlying biological state. In order to draw biological conclusions, data is typically summarized into higher order patterns. Numerous specialized algorithms for summarizing epigenetic signal have been proposed and include methods for peak calling or finding differentially methylated regions. A key unifying principle underlying these approaches is that they all leverage the strong prior that signal must be locally consistent.

Results

We proposeL0segmentation as a universal framework for extracting locally coherent signals for diverse epigenetic sources.L0serves to both compress and smooth the input signal by approximating it as piece-wise constant. We implement a highly scalableL0segmentation with additional loss functions designed for NGS epigenetic data types including Poisson loss for single tracks and binomial loss for methylation/coverage data. We show that theL0segmentation approach retains the salient features of the data yet can identify subtle features, such as transcription end sites, missed by other analytic approaches.

Availability

Our approach is implemented as an R package “l01segmentation” with a C++ backend. Available athttps://github.com/boooooogey/l01segmentation.
Genetic perturbation of mitochondrial function reveals functional role for specific mitonuclear genes, metabolites and pathways that regulate lifespan
Authors: Phua Cheryl Zi Jin , Zhao Xiaqing , Turcios-Hernandez Lesly , McKernan Morrigan , Abyadeh Morteza , Ma Siming , Promislow Daniel , Kaeberlein Matt , Kaya Alaattin
Published: January 2023

Altered mitochondrial function is tightly linked to lifespan regulation, but underlying mechanisms remain unclear. Here, we report the chronological and replicative lifespan variation across 168 yeast knock-out strains, each lacking a single nuclear-coded mitochondrial gene, including 144 genes with human homologs, many associated with diseases. We dissected the signatures of observed lifespan differences by analyzing profiles of each strain’s proteome, lipidome, and metabolome under fermentative and respiratory culture conditions, which correspond to the metabolic states of replicative and chronologically aging cells, respectively. Examination of the relationships among extended longevity phenotypes, protein, and metabolite levels revealed that although many of these nuclear-encoded mitochondrial genes carry out different functions, their inhibition attenuates a common mechanism that controls cytosolic ribosomal protein abundance, actin dynamics, and proteasome function to regulate lifespan. The principles of lifespan control learned through this work may be applicable to the regulation of lifespan in more complex organisms, since many aspects of mitochondrial function are highly conserved among eukaryotes.
Hunger signalling in the olfactory bulb primes exploration, food-seeking and peripheral metabolism
Authors: Stark Romana , Dempsey Harry , Kleeman Elizabeth , Sassi Martina , Davies Jeffrey , Zigman Jeffrey M. , Andrews Zane B.
Published: January 2023

Growing evidence highlights a complex interaction between olfaction and metabolism with impaired olfactory function observed in obesity and increased olfactory sensitivity during hunger. The mechanisms linking metabolic state and olfaction remain unknown, but increased accessibility of hormones, such as ghrelin, and the diverse expression of hormone receptors such as those for ghrelin (GHSRs) in the olfactory system suggests an underappreciated neuroendocrine role. Here, we examined the hypothesis that GHSRs in the olfactory bulb (OB) link hunger with olfactory sensitivity to influence foraging behaviours and metabolism. Selective deletion of OBGHSRsin adult male mice was achieved with adeno-associated viral expression of cre-recombinase in the OB of floxed-Ghsrmice. OBGHSRdeletion significantly affected olfactory discrimination and habituation to both food and pheromone odours, with greatest effect under fasted conditions. Anxiety-like and depression-like behaviour was significantly greater after OBGHSRdeletion using 3 independent anxiety behavioural tasks and testing for anhedonia, whereas exploratory behaviour was reduced. No effect on spatial navigation and memory was observed. Although OBGHSRdeletion did not affect cumulative food intake, it significantly impacted feeding behaviour as evidenced by altered bout number and duration. Moreover, food-finding after fasting or ip ghrelin was attenuated. Intriguingly, OBGHSRdeletion caused an increase in body weight and fat mass, spared fat utilisation on a chow diet and impaired glucose metabolism indicating metabolic dysfunction. We conclude that OBGHSRsmaintain olfactory sensitivity, particularly during hunger, and facilitate behavioural adaptations that optimise food-seeking in anxiogenic environments, priming metabolic pathways in preparation for food consumption.
Assessing the functional impact of protein binding site definition
Authors: Nandigrami Prithviraj , Fiser Andras
Published: January 2023

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data this approach generates, it also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also provides guidance on the minimum expected accuracy of interface definition that is required to capture the biological function of a protein.

AUTHOR SUMMARY

The residue level description or prediction of protein interfaces is a critical input for protein engineering and classification of function. However, different parametrizations of the same methods and especially alternative methods used to define the interface of a protein can return substantially different sets of residues. Typical experimental or computational methods employ mutational studies to verify interface definitions, but all these approaches inherently suffer from the problem that in order to probe the importance of any one position of an interface, an unknown amount of alteration is introduced into the very interface being studied. In this work, we employ a pharmacophore-based approach to computationally explore the consequences of defining alternative binding sites. The pharmacophore generates a hypothesis for the complementary protein binding interface, which then can be used in a search to identify the corresponding ligand from a library of candidates. The accurate ranking of cognate ligands can inform us about the biological accuracy of the interface definition. This study also provides a guideline about the minimum required accuracy of protein interface definitions that still provides a statistically significant recognition of cognate ligands above random expectation, which in turn sets a minimum expectation for interface prediction methods.
The Effect of Electrical Resonance in Neurons upon the Instability of Electrical Nerve Stimulations
Authors: Yu Shoujun , Yue Wenji , Guo Tianruo , Liu Yonghong , Zhang Yapeng , Khademi Sara , Zhou Tian , Xu Zhen , Song Bing , Wu Tianzhun , Liu Fenglin , Tai Yanlong , Yu Xuefei , Wang Hao
Published: January 2023

Repetitive electrical nerve stimulation can induce a long-lasting perturbation of the axon’s membrane potential, resulting in unstable stimulus-response relationships. Despite being observed in electrophysiology, the precise mechanisms underlying stimulus-induced instability is still an open question due to the lack of a proper theoretical model. This study proposes a new method based on a Circuit-Probability theory to reveal the interlinkages between the electrical resonance of neurons and the instability of neural response. Supported by in vivo investigations, this new model predicts several key characteristics of stimulus-induced instability and proposes a stimulation method to minimize the instability. This model provides a powerful tool to improve our understanding of the interaction between the external electric field and the complexity of the biophysical characteristics of axons.
Ensemble Approach for Predicting the Diagnosis of Osteoarthritis Using Soft Voting Classifier
Authors: Kim Jun-hee
Published: January 2023

Background

Osteoarthritis (OA) is a common degenerative disease of the joints. Risk factors for OA include non-modifiable factors such as age and gender and modifiable factors such as physical activity.

Purpose

This study aimed to construct a soft voting ensemble model to predict OA diagnosis using variables related to individual characteristics and physical activity and to identify important variables in constructing the model through permutation importance.

Method

Using the RFECV technique, the variables with the best predictive performance were selected among variables, and an ensemble model combining the RandomForest, XGBoost, and LightGBM algorithms was constructed, and the predictive performance and permutation importance of each variable were evaluated.

Result

The variables selected to construct the model were age, gender, grip strength, and quality of life, and the accuracy of the ensemble model was 0.828. The most important variable in constructing the model was age (0.199), followed by grip strength (0.053), quality of life (0.043), and gender (0.034).

Conclusion

The performance of the model for predicting OA was relatively good, and if this model is continuously used and updated, this model could readily be used to predict OA diagnosis and the predictive performance of OA may be further improved.
Improved Sleep, Cognitive Processing and Enhanced Learning and Memory Task Accuracy with Yoga Nidra Practice in Novices
Authors: Datta Karuna , Bhutambare Anna , Mamatha VL , Narawade Yogita Ankush , Rajagopal Srinath , Kanitkar Madhuri
Published: January 2023

Background

Yoga nidra practice in novices is known to improve sleep. Its effect on objective parameters on sleep and on cognitive performance is not well known. The aim of the study was to study the effect of yoga nidra practice on cognition and night time sleep using objective parameters.

Methods

41 healthy volunteers were enrolled and baseline sleep diary collected. Subjects underwent overnight polysomnography and cognition testing battery comprising of Motor praxis test (MPT), emotion recognition task (ERT), digital symbol substitution task (DSST), visual object learning task (VOLT), abstract matching (AIM), line orientation task (LOT), matrix reasoning task (MRT), fractal-2-back test (NBACK), psychomotor vigilance task (PVT-10 min) and balloon analog risk task (BART). Yoga nidra was practiced for two weeks after training. Cognition testing battery was done at baseline and at one and two weeks of practice to compare. The cognitive tasks were further analysed using Python library and power spectra density values (PSD) calculated for EEG frequencies at central, frontal and occipital locations. Repeat sleep diary and polysomnography to assess pre-post yoga nidra intervention effects were studied.

Results

Improved reaction times for all 10 cognition tasks was seen. Polysomnography (PSG) revealed significant difference in post intervention as compared to baseline. Data in change (95%CI; p-value) showed change in sleep efficiency, wake after sleep onset and delta μV2in deep sleep : +3.62% (0.3, 5.15; p-value=0.03), -20min (−35.78, -5.02; p=0.003) and +4.19 (0.5, 9.5; p=0.04) respectively. Accuracy was found to be significantly increased for VOLT (95% CI: 0.08, 0.17; p=0.002), AIM (95% CI: 0.03, 0.12; p= 0.02) after two weeks of practice and NBACK (95% CI: 0.02, 0.13; p=0.04) with one week of yoga nidra practice. ERT accuracy scores with yoga nidra practice showed increased recognition scores in happy, fear and anger stimuli (95% CI: 0.07, 0.24; p=0.004) but reduced scores with neutral stimuli (95% CI: -0.3, -0.05; p=0.04) after two weeks of yoga nidra practice.

Conclusion

Yoga nidra practice improves cognitive processing and helps improve night-time sleep in healthy novices.
Treatment for radiographically active, sputum culture-negative pulmonary tuberculosis: a systematic review and meta-analysis
Authors: Gray Adam Thorburn , Macpherson Liana , Carlin Ffion , Sossen Bianca , Richards Alexandra S , Kik Sandra V , Houben Rein M G J , MacPherson Peter , Quartagno Matteo , Rogozińska Ewelina , Esmail Hanif
Published: January 2023

INTRODUCTION

People with radiographic evidence for pulmonary tuberculosis (TB), but negative sputum cultures, have increased risk of developing culture-positive TB. Recent expansion of X-ray screening is leading to increased identification of this group. We set out to synthesise the evidence for treatment to prevent progression to culture-positive disease.

METHODS

We searched for prospective trials evaluating the efficacy of TB regimens against placebo, observation, or alternative regimens, for the treatment of adults and children with radiographic evidence of TB but culture-negative respiratory samples. Databases were searched up to 18 Oct 2022. Study quality was assessed using ROB 2.0 and ROBINS-I. The primary outcome was progression to culture-positive TB. Meta-analysis with a random effects model was conducted to estimate pooled efficacy.

RESULTS

We included 13 trials (32,568 individuals) conducted between 1955 and 2018. Radiographic and bacteriological criteria for inclusion varied. 19.1% to 57.9% of participants with active x-ray changes and no treatment progressed to culture-positive disease. Progression was reduced with any treatment (6 studies, risk ratio [RR] 0.27, 95%CI 0.13-0.56); multi-drug TB treatment (RR 0.11, 95%CI 0.05 - 0.23), was significantly more effective than isoniazid treatment (RR 0.63, 95%CI 0.35-1.13) (p=0.0002).

DISCUSSION

Multi-drug regimens were associated with significantly reduced risk of progression to TB disease for individuals with radiographically apparent, but culture-negative TB. However, most studies were old, conducted prior to the HIV epidemic and with outdated regimens. New clinical trials are required to identify the optimal treatment approach.

STUDY REGISTRATION

CRD42021248486
Early death after a diagnosis of metastatic solid cancer – raising awareness and identifying risk factors from the SEER database
Authors: Globus Opher , Sagie Shira , Lavine Noy , Barchana Daniel Itshak , Urban Damien
Published: January 2023

Background

Cancer death rates are declining, in part due to smoking cessation, better detection and new treatments; nevertheless, a large fraction of metastatic cancer patients die soon after diagnosis. Few studies and interventions focus on these patients. Our study aims characterize early mortality in a wide range of metastatic solid tumors.

Methods

We retrieved data on adult patients diagnosed with pathologically confirmedde-novometastatic solid tumors between the years 2004-2016 from the Surveillance, Epidemiology, and End Results database (SEER). Our primary outcome was cancer specific early death rate (defined as death within two months of diagnosis). Additional data extracted included socio-demographical data, tumor primary, sites of metastases, and cause of death.

Results

109,207 (20.8%) died of cancer within two months of diagnosis. The highest rates of early death were found in hepatic (36%), pancreato-biliary (31%) and lung (25%) primaries. Factors associated with early death included primary site, liver and brain metastases, increasing age and lower income. Cancer was the cause of death in 92.1% of all early deaths. Two-month mortality rates have improved during the study period (from 22.4% in 2004 to 18.8% in 2016).

Conclusion

A fifth of metastatic cancer patients die soon after diagnosis, with little improvement over the last decade. Further research is required to better classify and identify patients at risk for early mortality, which patients might benefit from faster diagnostic tracks, and which might avoid invasive and futile diagnostic procedures.
High burden of anemia and malnutrition in two tribal populations of Northeast India
Authors: Vungneihchoi Joycy , Sachdeva M.P.
Published: January 2023

Background

Anemia is a deficiency of red blood cells and a public health burden in India. There needs to be more reporting of the prevalence of this condition in adults consisting of both males and females in a rural setting. Hence, this study is undertaken to address this gap.

Materials and methods

1460 participants were recruited during a household survey in the Churachandpur district of Manipur. Data on personal, social demographic, and lifestyle variables were collected along with anthropometric measurements. Anemia status was tested with the help of a standardized portable hemoglobinometer.

Results

The prevalence of anemia was 42% and 46.4% among Kuki and Paite tribal communities of Manipur, respectively, which is significant within the communities. Type of occupation and lifestyle factors were also found to contribute to anemia. Age was also found to be inversely proportional to the prevalence of anemia.

Conclusion

The present study found a high prevalence of anemia and malnutrition, a matter of concern. The studied population, the tribals, are the deprived section of society that needs to be taken care of to achieve the United Nations Sustainable Developmental Goals (SDGs). They stay in remote areas which are not easily accessible, and hence they should be prioritized in terms of health and various other developments. Also, this high prevalence of anemia can lead to various health complications like cardiovascular diseases if not treated. Iron supplements should act as an intervention for the high prevalence of anemia and should be delivered timely to vulnerable populations.
Agent-based modeling and phylogenetic analysis suggests that COVID-19 will remain a low-severity albeit highly transmissible disease
Authors: Toledo-Roy Juan C. , García-Peña Gabriel E. , Valdes Ana M , Hoeflich Alejandro Frank
Published: January 2023

The ongoing COVID-19 pandemic is still producing hundreds of thousands of cases worldwide. However, the currently dominant Omicron variant (and its sub-variants) have proven to be less virulent than previous dominant variants, resulting in proportionately fewer severe cases, hospitalizations and deaths. Nonetheless, a persistent concern is that new mutations of the SARS-CoV-2 virus may yet produce more virulent variants. In the present study we provide evidence supporting the hypothesis that this is unlikely, and that COVID-19 will remain a low-severity although highly transmissible disease. Three complementary pieces of evidence support our argument. First, empirical observations suggest that the transmission advantage that Omicron (sub)variants enjoy is in large part due to their cell tropism in the upper respiratory tract, which renders them less virulent. Second, when a negative link between transmissibility and virulence is included in agent-based epidemiological models, viruses evolve towards lower virulence. Third, genetic diversification of SARS-CoV-2 suggests that epistasis in the Omicron family reduces the diversity of successful variants. Taken together these observations point to a high likelihood that the severity of COVID-19 will remain sufficiently low for an endemic status to be reached, provided that vaccination campaigns and sensible hygiene and social measures continue worldwide, as suggested by the World Health Organization.
Predicting Physiological Response in Heart Failure Management: A Graph Representation Learning Approach using Electronic Health Records
Authors: Chowdhury Shaika , Chen Yongbin , Wen Andrew , Ma Xiao , Dai Qiying , Yu Yue , Fu Sunyang , Jiang Xiaoqian , Zong Nansu
Published: January 2023

Heart failure management is challenging due to the complex and heterogenous nature of its pathophysiology which makes the conventional treatments based on the “one size fits all” ideology not suitable. Coupling the longitudinal medical data with novel deep learning and network-based analytics will enable identifying the distinct patient phenotypic characteristics to help individualize the treatment regimen through the accurate prediction of the physiological response. In this study, we develop a graph representation learning framework that integrates the heterogeneous clinical events in the electronic health records (EHR) as graph format data, in which the patient-specific patterns and features are naturally infused for personalized predictions of lab test response. The framework includes a novel Graph Transformer Network that is equipped with a self-attention mechanism to model the underlying spatial interdependencies among the clinical events characterizing the cardiac physiological interactions in the heart failure treatment and a graph neural network (GNN) layer to incorporate the explicit temporality of each clinical event, that would help summarize the therapeutic effects induced on the physiological variables, and subsequently on the patient’s health status as the heart failure condition progresses over time. We introduce a global attention mask that is computed based on event co-occurrences and is aggregated across all patient records to enhance the guidance of neighbor selection in graph representation learning. We test the feasibility of our model through detailed quantitative and qualitative evaluations on observational EHR data.
Redefining hematopoietic progenitor cells and reforming the hierarchy of hematopoiesis
Authors: Chen Lipeng , Sun Qing , Li Guoqiang , Huang Qijun , Chen Sujin , Fu Yingyun , Yue Yongjian
Published: January 2023

Deciphering the mechanisms underlying progenitor cell differentiation and cell-fate decisions is critical for answering fundamental questions regarding hematopoietic lineage commitment. Here, we redefine the entire spectrum of original hematopoietic progenitor cells (HPCs) using a comprehensive transcriptional atlas that effectively delineates the transitional progenitors. This is the first study to fully distinguish the transitional state along hematopoietic progenitor cell differentiation, reconciling previous controversial definitions of common myeloid progenitors (CMPs), granulocyte–monocyte progenitors (GMPs), and lymphoid-primed multipotent progenitors (LMPPs). Moreover, plasma progenitor cells are identified and defined. Transcription factors associated with key cell-fate decisions are identified at each level of the hematopoietic hierarchy, providing novel insights into the underlying molecular mechanisms. The hematopoietic hierarchy roadmap was reformed that reconciles previous models concerning pathways and branches of hematopoiesis commitment. Initial hematopoietic progenitors are simultaneously primed into megakaryocytic–erythroid, lymphoid, and neutrophilic progenitors during the first differentiation stage of hematopoiesis. During initial progenitor commitment,GATA2,HOPX, andCSF3Rdetermine the co-segregation of the three transitional lineage branches. Two types of lineage-commitment processes occur during hematopoiesis: the megakaryocytic–erythroid lineage commitment process is continuous, while the lymphoid-lineage commitment is stepwise. Collectively, these results raise numerous possibilities for precisely controlling progenitor cell differentiation, facilitating advancements in regenerative medicine and disease treatment.

Highlights

Hematopoietic progenitors are redefined using a comprehensive transcriptional atlas.

Cell fate decision-related transcription factors are revealed in the hematopoietic hierarchy.

Progenitor lineage commitment includes continuous and stepwise processes.

The initial hematopoietic hierarchy is simultaneously primed into three lineages.
Downfield Proton MRSI with whole-brain coverage at 3T
Authors: Özdemir İpek , Ganji Sandeep , Joseph Gillen B.S. , Etyemez Semra , Považan Michal , Barker Peter B.
Published: January 2023

Purpose

To develop a 3D downfield magnetic resonance spectroscopic imaging (DF-MRSI) protocol with whole brain coverage and post-processing pipeline for creation of metabolite maps.

Methods

A 3D, circularly phase-encoded version of the previously developed 2D DF-MRSI sequence withspectral-spatial excitation and frequency selective refocusing was implemented and tested in 5 healthy volunteers at 3T. Downfield metabolite maps with a nominal spatial resolution of 0.7 cm3were recorded in 8 slices at 3T in a scan time of 22m 40s. An MRSI post-processing pipeline was developed to create DF metabolite maps. Metabolite concentrations and uncertainty estimates were compared between region differences for nine downfield peaks.

Results

LCModel analysis showed CRLB average values of 3-4% for protein amide resonances in the three selected regions (anterior cingulate (ACC), dorsolateral prefrontal cortex (DLPFC), and centrum semiovale (CSO)); CRLBs were somewhat higher for individual peaks but for the most part were less than 20%. While DF concentration maps were visually quite homogeneous throughout the brain, general linear regression analysis corrected for multiple comparisons found significant differences between CSO and DLPFC for peaks at 7.09 ppm (p= 0.014), 7.90 ppm (p=0.009), 8.18 ppm (p=0.009), combined amides (p=0.009), and between ACC and DLPFC for the 7.30 ppm peak (p=0.020). CRLB values were not significantly different between brain regions for any of the DF peaks.

Conclusion

3D DF-MRSI of the human brain at 3T with wide spatial coverage for the mapping of exchangeable amide and other resonances is feasible at a nominal spatial resolution of 0.7 cm3.
The proteomic landscape of synaptic diversity across brain regions and cell types
Authors: van Oostrum Marc , Blok Thomas , Giandomenico Stefano L. , Dieck Susanne tom , Tushev Georgi , Fürst Nicole , Langer Julian , Schuman Erin M.
Published: January 2023

Brain function relies on communication via neuronal synapses. Neurons build and diversify synaptic contacts using different protein combinations that define the specificity, function and plasticity potential of synapses. More than a thousand proteins have been globally identified in both pre- and postsynaptic compartments, providing substantial potential for synaptic diversity. While there is ample evidence of diverse synaptic structures, states or functional properties, the diversity of the underlying individual synaptic proteomes remains largely unexplored. Here we used 7 different Cre-driver mouse lines crossed with a floxed mouse line in which the presynaptic terminals were fluorescently labeled (SypTOM) to identify the proteomes that underlie synaptic diversity. We combined microdissection of 5 different brain regions with fluorescent-activated synaptosome sorting to isolate and analyze using quantitative mass spectrometry 18 types of synapses and their underlying synaptic proteomes. We discovered ~1’800 unique synapse type-enriched proteins and allocated thousands of proteins to different types of synapses. We identify commonly shared synaptic protein modules and highlight the hotspots for proteome specialization. A protein-protein correlation network classifies proteins into modules and their association with synaptic traits reveals synaptic protein communities that correlate with either neurotransmitter glutamate or GABA. Finally, we reveal specializations and commonalities of the striatal dopaminergic proteome and outline the proteome diversity of synapses formed by parvalbumin, somatostatin and vasoactive intestinal peptide-expressing cortical interneuron subtypes, highlighting proteome signatures that relate to their functional properties. This study opens the door for molecular systems-biology analysis of synapses and provides a framework to integrate proteomic information for synapse subtypes of interest with cellular or circuit-level experiments.
Cannabidiol sensitizes TRPV2 channels to activation by 2-APB
Authors: Gochman Aaron , Tan Xiaofeng , Bae Chanhyung , Chen Helen , Swartz Kenton J. , Jara-Oseguera Andrés
Published: January 2023

The cation-permeable TRPV2 channel is essential for cardiac and immune cells. Cannabidiol (CBD), a non-psychoactive cannabinoid of clinical relevance, is one of the few molecules known to activate TRPV2. Using the patch-clamp technique we discover that CBD can sensitize current responses of the rat TRPV2 channel to the synthetic agonist 2-aminoethoxydiphenyl borate (2- APB) by over two orders of magnitude, without sensitizing channels to activation by moderate (40 ⁰C) heat. Using cryo-EM we uncover a new small-molecule binding site in the pore domain of rTRPV2 that can be occupied by CBD in addition to a nearby CBD site that had already been reported. The TRPV1 and TRPV3 channels share >40% sequence identity with TRPV2 are also activated by 2-APB and CBD, but we only find a strong sensitizing effect of CBD on the response of mouse TRPV3 to 2-APB. Mutations at non-conserved positions between rTRPV2 and rTRPV1 in either the pore domain or the CBD sites failed to confer strong sensitization by CBD in mutant rTRPV1 channels. Together, our results indicate that CBD-dependent sensitization of TRPV2 channels engages multiple channel regions and possibly involves more than one CBD and 2-APB sites. The remarkably robust effect of CBD on TRPV2 and TRPV3 channels offers a promising new tool to both understand and overcome one of the major roadblocks in the study of these channels – their resilience to activation.
Functional Optimization of Light-Activatable Opto-GPCRs: Illuminating the Importance of the Proximal C-terminus in G-protein Specificity
Authors: Leemann Siri , Kleinlogel Sonja
Published: January 2023

G-protein coupled receptors (GPCRs) are the largest family of human receptors that transmit signals from natural ligands and pharmaceutical drugs into essentially every physiological process. One main characteristic of GPCRs is their ability to specifically couple with different families of G-proteins, thereby triggering specific downstream signaling pathways. While an abundance of structural information is available on GPCR interactions with G-proteins, little is known about the GPCR domains functionally mediating G-protein specificity, in particular the proximal C-terminus, the structure which cannot be predicted with high confidentiality due to its flexibility. In this study, we exploited OptoGPCR chimeras between light-gated GPCRs (opsins) and ligand-gated GCPRs to systematically investigate the involvement of the C-terminus steering G-protein specificity. We employed rhodopsin-beta2-adrenoceptor and melanopsin-mGluR6 chimeras. We discovered a dominant role of the proximal C-terminus, dictating G-protein selectivity in the melanopsin-mGluR6 chimera, whereas it is the intracellular loop 3, which steers G-protein tropism in the rhodopsin-beta2-adrenoceptor. From the functional results and structural predictions, melanopsin and mGluR6 use a different mechanism to bRhod and b2AR to couple to a selective G-protein. Collectively, this work adds knowledge to the GPCR domains mediating G-protein selectivity, ultimately paving the way to optogenetically elicited specific G-protein signaling on demand.
Quantifying single cell lipid signaling kinetics after photo-stimulation
Authors: Gonzales David T. , Schuhmacher Milena , Lennartz H. Mathilda , Iglesias-Artola Juan M. , Kuhn Sascha M. , Barahtjan Pavel , Zechner Christoph , Nadler André
Published: January 2023

Studying the role of molecularly distinct lipid species in cell signaling remains challenging due to a scarcity of methods for performing quantitative lipid biochemistry in living cells. We have recently used lipid uncaging to quantify lipid-protein affinities and rates of lipid transbilayer movement and turnover in the diacylglycerol signaling pathway using population average time series data. So far, this approach does not allow to account for the cell-to-cell variability of cellular signaling responses. We here report a framework that allows to uniquely identify model parameters such diacylglycerol-protein affinities and transbilayer movement rates at the single cell level for a broad variety of structurally different diacylglycerol species. We find that lipid unsaturation degree and longer side chains generally correlate with faster lipid transbilayer movement and turnover and higher lipid-protein affinities. In summary, our work demonstrates how rate parameters and lipid-protein affinities can be quantified from single cell signaling trajectories with sufficient sensitivity to resolve the subtle kinetic differences caused by the chemical diversity of cellular signaling lipid pools.
Peripheral macrophages causally contribute to disease onset and progression in theNdufs4(KO) model of Leigh syndrome
Authors: Hanaford Allison R , Khanna Asheema , James Katerina , Chen Yihan , Mulholland Michael , Kayser Bernhard , Truong Vivian , Sedensky Margaret , Morgan Phil , Kalia Vandana , Baerchst Nathan , Sarkar Surojit , Johnson Simon C
Published: January 2023

Subacute necrotizing encephalopathy, or Leigh syndrome (LS), is the most common paediatric presentation of genetic mitochondrial disease. LS is a multi-system disorder with severe neurologic, metabolic, and musculoskeletal symptoms. The presence of progressive, symmetric, necrotizing lesions in the brainstem are a defining feature of the disease, and the major cause of morbidity and mortality, but the mechanisms underlying their pathogenesis have been elusive. Recently, we demonstrated that high-dose pexidartinib, a CSF1R inhibitor, prevents LS CNS lesions and systemic disease in theNdufs4(-/-) mouse model of LS. While the dose-response in this study implicated peripheral immune cells, the immune populations involved have not yet been elucidated. Here, we used a targeted genetic tool, deletion of the colony stimulating factor 1 receptor (CSF1R) macrophage super-enhancer FIRE (Csf1rΔFIRE), to specifically deplete microglia and define the role of microglia in the pathogenesis of LS. Homozygosity for theCsf1rΔFIRE allele ablates microglia in both control andNdufs4(-/-) animals, but onset of CNS lesions and sequalae in theNdufs4(-/-), including mortality, are only marginally impacted by microglia depletion. The overall development of necrotizing CNS lesions is not altered, though microglia remain absent. Finally, histologic analysis of brainstem lesions provides direct evidence of a causal role for peripheral macrophages in the characteristic CNS lesions. These data demonstrate that peripheral macrophages play a key role in the pathogenesis disease in theNdufs4(-/-) model.
Mycobacterium tuberculosisSecA2-dependent activation of host Rig-I/MAVs signaling is not conserved inMycobacterium marinum
Authors: Serene Lindsay G. , Champion Patricia A. , Schorey Jeffrey S.
Published: January 2023

Retinoic acid inducible gene I (Rig-I) is a cytosolic pattern recognition receptor canonically described for its important role in sensing viral RNAs. Increasingly, bacterially-derived RNA from intracellular bacteria such asMycobacterium tuberculosis, have been shown to activate the same host Rig-I/Mitochondrial antiviral sensing protein (MAVS) signaling pathway to drive a type-I interferon response that contributes to bacterial pathogenesisin vivo. InM. tuberculosis, this response is mediated by the protein secretion system SecA2, but little is known about whether this process is conserved in other pathogenic mycobacteria or the mechanism by which these nucleic acids gain access to the host cytoplasm. Because theM. tuberculosisandM. marinumSecA2 protein secretion systems share a high degree of genetic and functional conservation, we hypothesized that Rig-I/MAVS activation and subsequent induction of IFN-β secretion by host macrophages will also be conserved between these two mycobacterial species. To test this, we generated a ΔsecA2 M. marinumstrain along with complementation strains expressing either theM. marinumorM. tuberculosis secA2genes. Our results suggest that the ΔsecA2strain has a growth defectin vitrobut not in host macrophages. These intracellular growth curves also suggested that the calculation applied to estimate the number of bacteria added to macrophage monolayers in infection assays underestimates bacterial inputs for the ΔsecA2strain. Therefore, to better examine secreted IFN-β levels when bacterial infection levels are equal across strains, we plated bacterial CFUs at 2hpi alongside our ELISA based infections. This enabled us to normalize secreted levels of IFN-β to a standard number of bacteria. Applying this approach to both WT and MAVS-/-bone marrow derived macrophages we observed equal or higher levels of secreted IFN-β from macrophages infected with the ΔsecA2 M. marinumstrain as compared to WT. Together our findings suggest that activation of host Rig-I/MAVS cytosolic sensors and subsequent induction of IFN-β response in a SecA2-dependent manner is not conserved inM. marinumunder the conditions tested.
A better brain? Alternative spliced STIM2 in hominoids arises with synapse formation and creates a gain-of-function variant
Authors: Poth Vanessa , Trang Do Hoang Thu , Förderer Kathrin , Tschernig Thomas , Alansary Dalia , Helms Volkhard , Niemeyer Barbara A.
Published: January 2023

Balanced Ca2+homeostasis is essential for cellular functions. STIM2 mediated Store-Operated Ca2+Entry (SOCE) regulates cytosolic and ER Ca2+concentrations, stabilizes dendritic spine formation and drives presynaptic spontaneous transmission and ER stress in neurons. Recently identified alternative spliced variants expand the STIM protein repertoire, uncover unique functions and facilitate our understanding of tissue specific regulation of SOCE. Here, we describe an addition to this repertoire, a unique short STIM2 variant (STIM2.3/STIM2G) present only in old world monkeys and humans with expression in humans starting with the beginning of brainwave activity and upon synapse formation within the cerebral cortex. In contrast to the short STIM1B variant, STIM2.3/STIM2G increases SOCE upon stimulation independently of specific spliced in residues. Basal cluster formation is reduced and analyses of several additional deletion and point mutations delineate the role of functional motifs for Ca2+entry, NFAT activation and changes in neuronal gene expression. In addition, STIM2.3/STIM2G shows reduced binding and activation of the energy sensor AMPK. In the context of reduced STIM2.3 splicing seen in postmortem brains of patients with Huntington’s disease, our data suggests that STIM2.3/STIM2G is an important regulator of neuronal Ca2+homeostasis, potentially involved in synapse formation/maintenance and evolutionary expansion of brain complexity.