bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractBackgroundYoga 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.Methods41 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.ResultsImproved 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.ConclusionYoga 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

AbstractINTRODUCTIONPeople 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.METHODSWe 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.RESULTSWe 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).DISCUSSIONMulti-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 REGISTRATIONCRD42021248486
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

AbstractBackgroundCancer 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.MethodsWe 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.Results109,207 (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).ConclusionA 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

AbstractBackgroundAnemia 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 methods1460 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.ResultsThe 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.ConclusionThe 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

AbstractThe 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

AbstractHeart 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

AbstractDeciphering 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.HighlightsHematopoietic 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

AbstractPurposeTo develop a 3D downfield magnetic resonance spectroscopic imaging (DF-MRSI) protocol with whole brain coverage and post-processing pipeline for creation of metabolite maps.MethodsA 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.ResultsLCModel 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.Conclusion3D 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

AbstractBrain 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

AbstractThe 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

AbstractG-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

AbstractStudying 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.