bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alcohol use and dementia: new research directions
Authors: Visontay Rachel , Rao Rahul Tony , Mewton Louise 
Published: December 2020

Purpose of review
Alcohol is gaining increased recognition as an important risk factor for dementia. This review summarises recent evidence on the relationship between alcohol use and dementia, focusing on studies published from January 2019 to August 2020.

Recent findings
Epidemiological data continues to yield results consistent with protective effects of low-to-moderate alcohol consumption for dementia and cognitive function. However, recent literature highlights the methodological limitations of existing observational studies. The effects of chronic, heavy alcohol use are clearer, with excessive consumption causing alcohol-related brain damage. Several pathways to this damage have been suggested, including the neurotoxic effects of thiamine deficiency, ethanol and acetaldehyde.

Summary
Future research would benefit from greater implementation of analytical and design-based approaches to robustly model the alcohol use-dementia relationship in the general population, and should make use of large, consortia-level data. Early intervention to prevent dementia is critical: thiamine substitution has shown potential but requires more research, and psychosocial interventions to treat harmful alcohol use have proven effective. Finally, diagnostic criteria for alcohol-related dementia require formal validation to ensure usefulness in clinical practice.
Laboratory findings in coronavirus disease 2019 (COVID-19) patients: a comprehensive systematic review and meta-analysis
Authors: Karimian Mohammad , Jamshidbeigi Amirreza , Badfar Gholamreza , Azami Milad 
Published: December 2020

AbstractBackgroundIn early December 2019, the first patient with COVID-19 pneumonia was found in Wuhan, Hubei Province, China. Recent studies have suggested the role of primary laboratory tests in addition to clinical symptoms for suspected patients, which play a significant role in the diagnosis of COVID-19. Therefore, the present study was conducted to evaluate laboratory findings in COVID-19 patients.Data SourcesPubMed/Medline, Scopus, EMBASE, Web of Science (ISI), Cochrane Library, Ovid, Science Direct, CINAHL and EBSCO.Study SelectionCross-sectional of adverse outcomes stratified by the status of ICLs were selected.Data ExtractionThe prevalence of available variables for laboratory tests were extracted.ResultsFinally, 52 studies involving 5490 patients with COVID-19 entered the meta-analysis process. The prevalence of leukopenia, lymphopenia, elevated c-reactive protein (CRP), elevated erythrocyte sedimentation rate (ESR), elevated serum amyloid A, elevated ferritin was estimated to be 20.9% (95%CI: 17.9-24.3), 51.6% (95%CI: 44.0-59.1), 63.6% (95%CI: 57.0-69.8), 62.5% (95%CI: 50.1-73.5), 63.6% (95%CI: 57.0-69.8), 62.5% (95%CI: 50.1-73.5), 74.7% (95%CI: 50.0-89.7), and 72.6% (95%CI: 58.1-83.5), respectively. The prevalence of elevated interleukin-6 was 59.9% (95%CI: 48.2-70.5), CD3 was 68.3% (95%CI: 50.1-82.2), reduced CD4 was 62.0% (95%CI: 51.1-71.6), reduced CD8 was 42.7% (95%CI: 32.2-53.9). The prevalence of elevated troponin-I was 20.6% (95%CI: 9.0-40.5), elevated creatine kinase-MB (CKMB) was 14.7% (95%CI: 7.1-28.0), elevated brain natriuretic peptide (BNP) was 48.9% (95%CI: 30.4-67.7), elevated blood urea nitrogen was 13.1% (95%CI: 6.6-24.4),, elevated creatinine was 7.2% (95%CI: 4.4-11.8), elevated lactate dehydrogenase (LDH) was 53.1% (95%CI: 43.6-62.4), hyperglycemia was 41.1% (95% CI: 28.2-55.5), elevated total bilirubin was 48.9% (95%CI: 30.4-67.7), reduced albumin was 54.7% (95%CI: 38.1-70.2), reduced pre-albumin was 49.0% (95%CI: 26.6-71.8), and reduced PT was 53.1% (95% CI: 43.6-62.4), and D-dimer was 44.9% (95%CI: 31.0-59.6).ConclusionThis study provides a comprehensive description of laboratory characteristics in patients with COVID-19. The results show that lymphopenia, elevated CRP, elevated ESR, elevated ferritin, elevated serum amyloid A, elevated BNP, reduced albumin, reduced pre-albumin, reduced CD3, reduced CD4, reduced CD8, elevated D-dimer, reduced PT, elevated interleukin-2, elevated interleukin-6, elevated LDH and hyperglycemia are the common findings at the time of admission.
rTPCandnls.multstart: a new pipeline to fit thermal performance curves inR
Authors: Padfield Daniel , O’Sullivan Hannah , Pawar Samraat 
Published: December 2020

AbstractThe quantification of thermal performance curves (TPCs) for biological rates has many applications to problems such as predicting species’ responses to climate change. There is currently no widely used open-source pipeline to fit mathematical TPC models to data, which limits the transparency and reproducibility of the curve fitting process underlying applications of TPCs.We present a new pipeline inRthat currently allows for reproducible fitting of 24 different TPC models using non-linear least squares (NLLS) regression. The pipeline consists of two packages –rTPCandnls. multstart– that allow multiple start values for NLLS fitting and provides helper functions for setting start parameters. This pipeline overcomes previous problems that have made NLLS fitting and estimation of key parameters difficult or unreliable.We demonstrate howrTPCandnls.multstartcan be combined with other packages inRto robustly and reproducibly fit multiple models to multiple TPC datasets at once. In addition, we show how model selection or averaging, weighted model fitting, and bootstrapping can easily be implemented within the pipeline.This new pipeline provides a flexible and reproducible approach that makes the challenging task of fitting multiple TPC models to data accessible to a wide range of users.
The alleviation of neuropathic pain behaviours by a single injection of a synthetic substance P-botulinum conjugate persists for up to 120d and can be restored with a second injection of conjugate
Authors: Maiarù Maria , Leese Charlotte , Davletov Bazbek , Hunt Stephen P. 
Published: December 2020

AbstractThere is an urgent need for new pain-relieving therapies. We have previously shown using mouse models of persistent pain that a single intrathecal injection of substance P conjugated to the light chain of botulinum toxin (SP-BOT) silenced neurons in the dorsal horn of the spinal cord and alleviated mechanical hypersensitivity. The SP-BOT construct selectively silenced neurokinin 1 receptor positive (NK1R+) neurons in the superficial dorsal horn of the spinal cord. A subset of these NK1R+ neurons are nociceptive projection neurons and convey injury-related information to the brainstem, initiating and maintaining programmes of escape and recovery essential for healing. Previously, we observed a reduction in mechanical hypersensitivity in a spared nerve injury (SNI) model of neuropathic pain state after intrathecal injection of SP-BOT over the lumbar spinal cord and lasting for up to 40 days. In this latest study, we have extended these observations and now show that thermal and affective measures of pain behaviour were also alleviated by a single intrathecal injection of SP-BOT. By introducing SNI 30 days, 60 days, 90 days or 120 days after injection of SP-BOT we have established that NK1R+ spinal neurons in the superficial lamina of the dorsal horn were silenced for up to 120 days following a single intrathecal injection of the botulinum construct. We also show that behavioural alleviation of neuropathic pain symptoms could be reinstated by a second injection of SP-BOT at 120 days. Taken together this research demonstrates that this recently developed botulinum toxin conjugate provides a powerful new way of providing long term pain relief without toxicity following a single injection and also has a therapeutic potential for repeated dosing when pain begins to return.
The phagocytosis oxidase/Bem1p (PB1) domain-containing protein PB1CP negatively regulates the NADPH oxidase RBOHD in plant immunity
Authors: Goto Yukihisa , Maki Noriko , Sklenar Jan , Derbyshire Paul , Menke Frank L.H. , Zipfel Cyril , Kadota Yasuhiro , Shirasu Ken 
Published: December 2020

SummaryPerception of pathogen-associated molecular patterns (PAMPs) by surface-localized pattern-recognition receptors activates RESPIRATORY BURST OXIDASE HOMOLOG D (RBOHD) through direct phosphorylation by BOTRYTIS-INDUCED KINASE 1 (BIK1) and induces the production of reactive oxygen species (ROS). ROS have direct antimicrobial properties but also serve as signaling molecules to activate additional defense responses such as stomatal closure. RBOHD activity must be tightly controlled to avoid the detrimental effects of ROS, but little is known about RBOHD downregulation.To better understand the regulation of RBOHD, we used co-immunoprecipitation of RBOHD coupled with mass spectrometry analysis to identify RBOHD-associated proteins.Among RBOHD-associated proteins, we identified PHAGOCYTOSIS OXIDASE/ BEM1P (PB1) DOMAIN-CONTAINING PROTEIN (PB1CP). We found that PB1CP negatively regulates RBOHD and the resistance against the fungal pathogenColletotrichum higginsianum. PB1CP directly interacts with RBOHDin vitro, and PAMP treatment increases the interactionin vivo. PB1CP is localized at the cell periphery and in cytoplasm, but PAMP treatment induces PB1CP relocalization to small endomembrane compartments.PB1CPoverexpression reduces plasma membrane localization of RBOHD, suggesting that PB1CP down-regulates RBOHD function by relocalizing it away from the plasma membrane.We reveal a novel negative regulation mechanism of ROS production through the relocalization of RBOHD by PB1CP.
GENERATION AND CHARACTERIZATION OF IMMORTALIZED MOUSE CORTICAL ASTROCYTES FROM WILDTYPE AND CONNEXIN43 KNOCKOUT MICE
Authors: Cibelli Antonio , Lopez-Quintero Sandra Veronica , McCutcheon Sean , Scemes Eliana , Spray David C. , Stout Randy F. , Suadicani Sylvia O. , Thi Mia M. , Urban-Maldonado Marcia 
Published: December 2020

ABSTRACTWe transduced mouse cortical astrocytes cultured from four litters of embryonic wildtype (WT) and connexin43 (Cx43) null mouse pups with lentiviral vector encoding hTERT and measured expression of astrocyte-specific markers up to passage 10 (p10). The immortalized cell lines thus generated (designated IWCA and IKOCA, respectively) expressed biomarkers consistent with those of neonatal astrocytes, including Cx43 from wildtype but not from Cx43-null mice, lack of Cx30, and presence of Cx26. AQP4, the water channel that is found in high abundance in astrocyte end-feet, was expressed at moderately high levels in early passages, and its mRNA and protein declined to low but still detectable levels by p10. The mRNA levels of the astrocyte biomarkers aldehyde dehydrogenase 1 (ALDH1), glutamine synthetase (GS) and glial fibrillary acidic protein (GFAP) remained relatively constant during successive passages. GS protein expression was maintained while GFAP declined with cell passaging but was still detectable at p10. Both mRNA and protein levels of glutamate transporter 1 (GLT-1) declined with passage number. Immunostaining at corresponding times was consistent with the data from Western blots and provided evidence that these proteins were expressed at appropriate intracellular locations. Consistent with our goal of generating immortalized cell lines in which Cx43 was either functionally expressed or absent, IWCA cells were found to be well coupled with respect to intercellular dye transfer and similar to primary astrocyte cultures in terms of time course of junction formation, electrical coupling strength and voltage sensitivity. Moreover, barrier function was enhanced in co-culture of the IWCA cell line with bEnd.3 microvascular endothelial cells. In addition, immunostaining revealed oblate endogenous Cx43 gap junction plaques in IWCA that were similar in appearance to those plaques obtained following transfection of IKOCA cells with fluorescent protein tagged Cx43. Re-expression of Cx43 in IKOCA cells allows experimental manipulation of connexins and live imaging of interactions between connexins and other proteins. We conclude that properties of these cell lines resemble those of primary cultured astrocytes, and they may provide useful tools in functional studies by facilitating genetic and pharmacological manipulations in the context of an astrocyte-appropriate cellular environment.
Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-fluorodeoxyglucose Positron Emission Tomography
Authors: He Wuxian , Tang Hongtu , Li Jia , Hou Chenze , Shen Xiaoyan , Li Chenrui , Liu Huafeng , Yu Weichuan 
Published: December 2020

AbstractBackgroundThe association between brain metabolic change and ischemic stroke has attracted a lot of attention in the research community. 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging is widely used to measure the metabolism. In experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure is of vital importance. However, an assessment method based on FDG PET images is still lacking. Herein, we propose an image feature-based protocol to assess the quality of the procedure.MethodsWe performed permanent MCAO to a total of 161 Sprague-Dawley rats. FDG micro-PET images were acquired both before and after the MCAO procedure. Triphenyl tetrazolium chloride (TTC) staining was also conducted to obtain ground truth of the infarct volume. After preprocessing of the PET images, a combination of 3D scale invariant feature transform (SIFT) and support vector machine (SVM) was applied to extract features and train a classifier that can assess the quality of the MCAO procedure.Results106 rats and 212 images were used as training data to construct the classification model. The SVM classifier achieved over 98% accuracy in cross validation. 10 rats with TTC results showing infarction in the ipsilateral brain region served as validation data. Their images were tested by the classifier and all of them were categorized into the correct group. Finally, the remaining 45 rats from a separate experiment were treated as independent test data. The prediction accuracy for these 90 images reached the level of 91%. An online interface was constructed for users to upload their images and obtain the assessment results.ConclusionThis feature-based protocol provides a convenient, accurate and reliable tool to assess the quality of the MCAO procedure in FDG PET study.
ProALIGN: Directly learning alignments for protein structure prediction via exploiting context-specific alignment motifs
Authors: Kong Lupeng , Ju Fusong , Zheng Wei-Mou , Zhu Jianwei , Sun Shiwei , Xu Jinbo , Bu Dongbo 
Published: December 2020

AbstractTemplate-based modeling (TBM), including homology modeling and protein threading, is one of the most reliable techniques for protein structure prediction. It predicts protein structure by building an alignment between the query sequence under prediction and the templates with solved structures. However, it is still very challenging to build the optimal sequence-template alignment, especially when only distantly-related templates are available. Here we report a novel deep learning approach ProALIGN that can predict much more accurate sequence-template alignment. Like protein sequences consisting of sequence motifs, protein alignments are also composed of frequently-occurring alignment motifs with characteristic patterns. Alignment motifs are context-specific as their characteristic patterns are tightly related to sequence contexts of the aligned regions. Inspired by this observation, we represent a protein alignment as a binary matrix (in which 1 denotes an aligned residue pair) and then use a deep convolutional neural network to predict the optimal alignment from the query protein and its template. The trained neural network implicitly but effectively encodes an alignment scoring function, which reduces inaccuracies in the handcrafted scoring functions widely used by the current threading approaches. For a query protein and a template, we apply the neural network to directly infer likelihoods of all possible residue pairs in their entirety, which could effectively consider the correlations among multiple residues. We further construct the alignment with maximum likelihood, and finally build structure model according to the alignment.Tested on three independent datasets with in total 6,688 protein alignment targets and 80 CASP13 TBM targets, our method achieved much better alignments and 3D structure models than the existing methods including HHpred, CNFpred, CEthreader and DeepThreader. These results clearly demonstrate the effectiveness of exploiting the context-specific alignment motifs by deep learning for protein threading.
Technical Note: A fast and robust integrator of delay differential equations in DCM for electrophysiological data
Authors: Schöbi Dario , Do Cao-Tri , Frässle Stefan , Tittgemeyer Marc , Heinzle Jakob , Stephan Klaas Enno 
Published: December 2020

AbstractDynamic causal models (DCMs) of electrophysiological data allow, in principle, for inference on hidden, bulk synaptic function in neural circuits. The directed influences between the neuronal elements of modeled circuits are subject to delays due to the finite transmission speed of axonal connections. Ordinary differential equations are therefore not adequate to capture the ensuing circuit dynamics, and delay differential equations (DDEs) are required instead. Previous work has illustrated that the integration of DDEs in DCMs benefits from sophisticated integration schemes in order to ensure rigorous parameter estimation and correct model identification. However, integration schemes that have been proposed for DCMs either emphasise speed (at the possible expense of accuracy) or robustness (but with computational costs that are problematic in practice).In this technical note, we propose an alternative integration scheme that overcomes these shortcomings and offers high computational efficiency while correctly preserving the nature of delayed effects. This integration scheme is available as open-source code in the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) toolbox and can be easily integrated into existing software (SPM) for the analysis of DCMs for electrophysiological data. While this paper focuses on its application to the convolution-based formalism of DCMs, the new integration scheme can be equally applied to more advanced formulations of DCMs (e.g. conductance based models). Our method provides a new option for electrophysiological DCMs that offers the speed required for scientific projects, but also the accuracy required for rigorous translational applications, e.g. in computational psychiatry.
neoDL: A novel neoantigen intrinsic feature-based deep learning model identifies IDH wild-type glioblastomas with the longest survival
Authors: Sun Ting , He Yufei , Li Wendong , Liu Guang , Li Lin , Wang Lu , Xiao Zixuan , Han Xiaohan , Wen Hao , Liu Yong , Chen Yifan , Wang Haoyu , Li Jing , Fan Yubo , Zhang Wei , Zhang Jing 
Published: December 2020

AbstractBackgroundIDH wild-type glioblastoma (GBM) is the most aggressive tumor in the central nervous system in spite of extensive therapies. Neoantigen based personalized immune therapies achieve promising results in melanoma and lung cancer, but few neoantigen based models perform well in IDH wild-type GBM. Unlike the neoantigen load and occurrence that are well studied and often found useless, the association between neoantigen intrinsic features and prognosis remain unclear in IDH wild-type GBM.ResultsWe presented a novel neoantigen intrinsic feature-based deep learning model (neoDL) to stratify IDH wild-type GBMs into subgroups with different survivals. We first calculated a total of 2928 intrinsic features for each neoantigen and filtered out those not associated with survival, followed by applying neoDL in the TCGA data cohort. Leave one out cross validation (LOOCV) in the TCGA demonstrated that neoDL successfully classified IDH wild-type GBMs into different prognostic subgroups, which was further validated in an independent data cohorts from Asian population. Long-term survival IDH wild-type GBMs identified by neoDL were found characterized by 12 protective neoantigen intrinsic features and enriched in development and cell cycle.ConclusionsOur results provide a novel model, neoDL, that can be therapeutically exploited to identify IDH wild-type GBM with good prognosis who will most likely benefit from neoantigen based personalized immunetherapy.
Variation in mtDNA haplotypes suggests a complex history of reproductive strategy inCannabis sativa
Authors: Attia Ziv , Pogoda Cloe S. , Vergara Daniela , Kane Nolan C. 
Published: December 2020

ABSTRACTCannabisis one example in angiosperms that appears to have a recent origin of dioecy and X/Y sex chromosomes. Several evolutionary explanations for this transition have been proposed, with the most parsimonious beginning with a mitochondrial mutation leading to cytoplasmic male sterility (CMS). Our study utilized 73Cannabis sativawhole genome shotgun libraries to reveal eight different mtDNA haplotypes. The most common haplotype contained 60 of the 73 individuals studied and was composed of only dioecious individuals. However, other haplotypes contained a mix of dioecious and monoecious individuals, so haplotype alone does not predict dioecy. From these haplotype groupings we further examined the fully annotated mitochondrial genomes of four hemp individuals and looked for genetic variation affecting reproductive strategy (e.g., monoecious vs. dioecious strategies). Specifically, we searched for markers associated with CMS and for gene rearrangements within these mitochondrial genomes. Our results revealed highly syntenic mitochondrial genomes that contained approximately 60 identifiable sequences for protein coding genes, tRNAs and rRNAs and no obvious rearrangements or chimeric genes. We find no clear evidence that the different reproductive patterns are due to easily identifiable CMS mutations. Our results refute the simplest hypothesis that there was a single recent origin of dioecy in a monoecious ancestor. Instead, the story of the evolution of dioecy is likely much more complex. Further exploration of the nuclear and mitochondrial genomes and their interaction is required to fully understandCannabis’ mating strategies and the possible existence of CMS in this species.
Multiple timescales of sensory-evidence accumulation across the dorsal cortex
Authors: Pinto Lucas , Tank David W. , Brody Carlos D. 
Published: December 2020

AbstractCortical areas seem to form a hierarchy of intrinsic timescales, but whether this is causal to cognitive behavior remains unknown. In particular, decisions requiring the gradual accrual of sensory evidence over time recruit widespread areas across this hierarchy. Here, we causally tested the hypothesis that this recruitment is related to the intrinsic integration timescales of these widespread areas. We trained mice to accumulate evidence over seconds while navigating in virtual reality, and optogenetically silenced the activity of many cortical areas during different brief trial epochs. We found that the inactivation of different areas primarily affected the evidence-accumulation computation per se, rather than other decision-related processes. Specifically, we observed selective changes in the weighting of evidence over time, such that frontal inactivations led to deficits on longer timescales than posterior cortical ones. Likewise, large-scale cortical Ca2+ activity during task performance displayed different temporal integration windows matching the effects of inactivation. Our findings suggest that distributed cortical areas accumulate evidence by leveraging their hierarchy of intrinsic timescales.