bluuebunny/crossref_metadata_2025 huggingface dataset:
Treating Posttraumatic Stress Disorder Symptoms With Low Amplitude Seizure Therapy (LAP-ST) Compared With Standard Right Unilateral Electroconvulsive Therapy
Authors: Youssef Nagy A. , Dhanani Sadiya , Rosenquist Peter B. , McCloud Laryssa , McCall William V.
Published: July 2020

Objectives

An important barrier to further studying electroconvulsive therapy (ECT) in posttraumatic stress disorder (PTSD) is the cognitive adverse effects. However, recent data suggest that low amplitude seizure therapy (LAP-ST) has no or minimal cognitive adverse effects. The aims of this report were to examine the efficacy of LAP-ST in PTSD and to compare LAP-ST with standard right unilateral (RUL) ECT using a pilot randomized clinical trial.

Methods

Patients were randomized to LAP-ST or RUL ECT. Posttraumatic stress disorder was assessed using clinical interview based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, and symptom severity with PTSD Checklist (PCL). The scores pertaining to PCL were analyzed using descriptive analysis for this pilot study.

Results

Eleven patients consented to be enrolled. Seven were randomly allocated to LAP-ST or RUL ECT. Five completed the study and had completed PCL before and after the course. In both groups, PTSD symptoms showed fast improvement. The effect size of improvement seems promising. The mean baseline PCL score for patients in the LAP-ST group was 42.5 (SD = 16.26) and the mean end point PCL score after treatment was 31 (SD = 15.56). The mean baseline PCL score for patients in the standard RUL ECT group was 64.7 (SD = 1.15) and the mean end point was 41 (SD = 15.62).

Conclusions

Both LAP-ST and standard RUL ECT showed reduction in PTSD symptoms with fast improvement. This first PTSD LAP-ST study adds support to the prior LAP-ST proof-of-concept clinical trial that LAP-ST can produce effective therapeutic outcomes. Replication of this trial is warranted in larger clinical trials (ClinicalTrials.gov ID: NCT02583490).
Need for Standardization of Measurement of Time to Reorientation as a Predictor of Cognitive Adverse Effects of Electroconvulsive Therapy
Authors: Tripathi Chidrup , Khan Bilal , Youssef Nagy A.
Published: July 2020

Testing for time to reorientation (TRO) after electroconvulsive therapy (ECT) has been one of the most predictive measures for cognitive adverse effects of ECT. However, measuring TRO varies between clinical trials, and there is no standardized approach on its measurement between studies. The objective of this report is to systematically review the literature on the different ways of measuring TRO. This would be a first step to establish a consensus on a standard method for TRO. We performed a systematic literature review from 1968 to October 2019 for clinical trials with a sample size of more than 50 and published in English that describe measures of TRO. We searched both PubMed and Web of Science databases. The literature search generated 12 clinical trials, which met the inclusion criteria. Studies measured TRO using 3-, 5-, or 10-item questionnaires. Most studies measured full orientation as answering 4/5 questions. Other studies smaller than 50 required 14/14 items to be answered correctly. There was wide variation between studies on how often and when orientation questions were initiated. These factors have obvious implications to the results and interpretation of the ECT literature.There was no clear consensus on measuring TRO in a uniform fashion. Research and clinical care would benefit from a standardized approach to measuring TRO. Measuring TRO using a 4/5 method seems the most common and quickest way, whereas using a 14/14 method seems to be the most rigorous and sensitive to change in trials.
Statements issued by academic medical institutions after George Floyd’s killing by police and subsequent unrest in the United States: cross-sectional study
Authors: Kiang Mathew V. , Tsai Alexander C.
Published: July 2020

Background

The horrific nature of George Floyd’s killing by a Minneapolis Police Department officer on May 25, 2020 has sparked more than a month of nationwide protests against police brutality and in support of the Black Lives Matter movement. At critical junctures of the nation’s public health such as these, academic medical institutions may exert leadership by issuing public statements to communicate institutional values.

Methods

We obtained statements issued by 56 leading U.S. medical schools relevant to George Floyd’s killing and subsequent protests. We tokenized statements into words, n-grams of sizes 2 and 3, and sentences; removed non-informative stop words and words that would compromise de-identification; and stemmed the remaining words using the Porter algorithm. We followed a predefined set of rules for identifying important elements of these statements related to leadership in antiracism and public health.

Results

Nearly all named George Floyd (50 [89%]), a majority noted the role of racism (43 [77%]) and acknowledged the Black community specifically (41 [73%]). Fewer ╌ slightly more than half ╌ referenced the act resulting in Floyd’s death (31 [55%]) or made explicit reference to the police (29 [52%]). Only 7 (13%) explicitly used terms denoting active support, like “antiracism” or “Black Lives Matter.” Most (45 [80%]) included references to negative sequelae resulting from racism like “disparities” or “inequality”. All included hopeful language.

Conclusion

Only a minority of institutions made reference to the killing of George Floyd by the police, and most failed to address this country’s targeted, historically engrained, and sustained oppression of Black people through white supremacy. Thus, our study identifies significant opportunities for U.S. medical schools to exert meaningful leadership in health.
SUV39 SET domains mediate crosstalk of heterochromatic histone marks
Authors: Stirpe Alessandro , Guidotti Nora , Northall Sarah J. , Kilic Sinan , Hainard Alexandre , Vadas Oscar , Fierz Beat , Schalch Thomas
Published: July 2020

The SUV39 class of methyltransferase enzymes deposits histone H3 lysine 9 di- and trimethylation (H3K9me2/3), the hallmark of constitutive heterochromatin. How these enzymes are regulated to mark specific genomic regions as heterochromatic is poorly understood. Clr4 is the sole H3K9me2/3 methyltransferase in the fission yeastS. pombeand recent evidence suggests that ubiquitination of lysine 14 on histone H3 (H3K14ub) plays a key role in H3K9 methylation. However, the molecular mechanism of this regulation and its role in heterochromatin formation remains to be determined. Our structure-function approach shows that the H3K14ub substrate binds specifically and tightly to the catalytic domain of Clr4, and thereby stimulates the enzyme by over 250-fold. Mutations that disrupt this mechanism lead to a loss of H3K9me2/3 and abolish heterochromatin silencing similar toclr4deletion. Comparison with mammalian SET domain proteins suggests that the Clr4 SET domain harbours a conserved sensor for H3K14ub, which mediates licensing of heterochromatin formation.
Organization of Areal Connectivity in the Monkey Frontoparietal Network
Authors: Conklin Bryan D.
Published: July 2020

Anatomical connectivity between cortical areas condition the set of observable functional activity in a neural network. The large-scale cortical monkey frontoparietal network (FPN) has been shown to facilitate complex cognitive functions. However, the organization of anatomical connectivity between areas in the FPN supporting such function is unknown. Here, a new connectivity matrix is proposed which shows the FPN utilizes a small-world architecture with an over-reliance on the M9 dynamical relay 3-node motif and degree distributions which can be characterized as single scale. The FPN uses its small-world architecture to achieve the kind of simultaneous integration and specialization of function which cognitive functions like attention and working memory require. Contrary to many real-world networks, the in and out single scale degree distributions illustrate the relatively homogeneous connectivity of each area in the FPN, suggesting an absence of hubs. Crucially, the M9 dynamical relay motif is the optimal arrangement for previously reported near-zero and non-zero phase synchrony to propagate through the network, serving as a candidate topological mechanism. These results signify the impact of the organization of anatomical connectivity in the FPN. They can serve as a benchmark to be used in the network-level treatment of neurological disorders where the types of cognition the FPN supports are impaired. Additionally, they can inform future neuromorphic circuit designs which aim to perform aspects of cognition.
Streamlining Data-Intensive Biology With Workflow Systems
Authors: Reiter Taylor , Brooks Phillip T. , Irber Luiz , Joslin Shannon E.K. , Reid Charles M. , Scott Camille , Brown C. Titus , Pierce N. Tessa
Published: July 2020

As the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter modifications. These workflows can produce hundreds to thousands of intermediate files and results that must be integrated for biological insight. Data-centric workflow systems that internally manage computational resources, software, and conditional execution of analysis steps are reshaping the landscape of biological data analysis, and empowering researchers to conduct reproducible analyses at scale. Adoption of these tools can facilitate and expedite robust data analysis, but knowledge of these techniques is still lacking. Here, we provide a series of practices and strategies for leveraging workflow systems with structured project, data, and resource management to streamline large-scale biological analysis. We present these strategies in the context of high-throughput sequencing data analysis, but the principles are broadly applicable to biologists working beyond this field.

Author Summary

We present a guide for workflow-enabled biological sequence data analysis, developed through our own teaching, training and analysis projects. We recognize that this is based on our own use cases and experiences, but we hope that our guide will contribute to a larger discussion within the open source and open science communities and lead to more comprehensive resources. Our main goal is to accelerate the research of scientists conducting sequence analyses by introducing them to organized workflow practices that not only benefit their own research but also facilitate open and reproducible science.
Negative screening for 12 rare LRRK2 pathogenic variants in a cohort of Nigerians with Parkinson’s disease
Authors: Rizig Mie , Ojo Oluwadamilola O. , Athanasiou-Fragkouli Alkyoni , Agabi Osigwe P. , Oshinaike Olajumoke O. , Houlden H , Okubadejo Njideka U.
Published: July 2020

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the most commonly identified genetic variants in familial and sporadic Parkinson’s disease (PD). Over three hundredLRRK2variants have been described in the literature, of which at least 17 have a confirmed or probable pathogenic role in PD. The distribution of these rare pathogenic variants has been shown to be different among ethnic groups including Caucasians, Latin Americans and East and South Asians. However, to date no PD-relatedLRRK2pathogenic variant has been described in persons of black African ancestry within or outside Africa. We previously reported that theLRRK2 p.gly2019sermutation was not found in 126 PD patients and 55 controls from Nigeria. Using Kompetitive Allele-Specific Polymerase chain reaction (KASP), we screened a new cohort of 92 Nigerians with PD and 210 healthy ethnically matched controls for 12 rareLRRK2variants (which have been shown to be pathogenic in other ethnic populations) including:p.gly2019ser, p.Arg1441His, p.Gly2385Arg, p.Ala419Val, p.Arg1628Pro, p.Pro755Leu, p.Ile2020ThrandTyr1699Cys. All 12 rare variants were absent in PD patients and controls from this cohort. These results endorse our previous findings and confirm that rareLRRK2pathogenic variants reported in Caucasians, Asians and persons of mixed ancestry are absent in West Africans. Applying next generation sequencing technologies in future studies is necessary to explore possible novelLRRK2variants indigenous to black Africans.
Synchronization and interaction of proline, ascorbate and oxidative stress pathways under abiotic stress combination in tomato plants
Authors: Lopez-Delacalle María , Silva Christian J , Mestre Teresa C , Martinez Vicente , Blanco-Ulate Barbara , Rivero Rosa M
Published: July 2020

Adverse environmental conditions have a devastating impact on plant productivity. In nature, multiple abiotic stresses occur simultaneously, and plants have evolved unique responses to cope against this combination of stresses. Here, we coupled genome-wide transcriptional profiling and untargeted metabolomics with physiological and biochemical analyses to characterize the effect of salinity and heat applied in combination on the metabolism of tomato plants. Our results demonstrate that this combination of stresses causes a unique reprogramming of metabolic pathways, including changes in the expression of 1,388 genes and the accumulation of 568 molecular features. Pathway enrichment analysis of transcript and metabolite data indicated that the proline and ascorbate pathways act synchronously to maintain cellular redox homeostasis, which was supported by measurements of enzymatic activity and oxidative stress markers. We also identified key transcription factors from the basic Leucine Zipper Domain (bZIP), Zinc Finger Cysteine-2/Histidine-2 (C2H2) and Trihelix families that are likely regulators of the identified up-regulated genes under salinity+heat combination. Our results expand the current understanding of how plants acclimate to environmental stresses in combination and unveils the synergy between key cellular metabolic pathways for effective ROS detoxification. Our study opens the door to elucidating the different signaling mechanisms for stress tolerance.

HIGHLIGHTS

The combination of salinity and heat causes a unique reprogramming of tomato metabolic pathways by changing the expression of specific genes and metabolic features.

Proline and ascorbate pathways act synchronously to maintain cellular redox homeostasis

Key transcription factors from the basic Leucine Zipper Domain (bZIP), Zinc Finger Cysteine-2/Histidine-2 (C2H2) and Trihelix families were identified as putative regulators of the identified up-regulated genes under salinity and heat combination.
A Parallel Implementation of the Finite State Projection Algorithm for the Solution of the Chemical Master Equation
Authors: Vo Huy , Munsky Brian
Published: July 2020

Stochastic reaction networks are a popular modeling framework for biochemical processes that treat the molecular copy numbers within a single cell as a continuous time Markov chain, whose forward Chapman-Kolmogorov equation is known in biochemistry literature as the chemical master equation (CME). The solution of the CME contains extremely useful information that can be compared to experimental data in order to improve the quantitative understanding of biochemical reaction networks within the cell. However, this solution is costly to compute as it requires integrating an enormous system of differential equations that grows exponentially with the number of chemical species. To address this issue, we introduce a novel multiple-sinks Finite State Projection algorithm that approximates the CME with an adaptive sequence of reduced-order models with an effecient parallelization based on MPI. The implementation is tested on models of sizable state spaces using a high-performance computing node on Amazon Web Services, showing favorable scalability.
Variance and limiting distribution of coalescence times in a diploid model of a consanguineous population
Authors: Severson Alissa L. , Carmi Shai , Rosenberg Noah A.
Published: July 2020

Recent modeling studies interested in runs of homozygosity (ROH) and identity by descent (IBD) have sought to connect these properties of genomic sharing to pairwise coalescence times. Here, we examine a variety of features of pairwise coalescence times in models that consider consanguinity. In particular, we extend a recent diploid analysis of mean coalescence times for lineage pairs within and between individuals in a consanguineous population to derive the variance of coalescence times, studying its dependence on the frequency of consanguinity and the kinship coefficient of consanguineous relationships. We also introduce a separation-of-time-scales approach that treats consanguinity models analogously to mathematically similar phenomena such as partial selfing, using this approach to obtain coalescence-time distributions. This approach shows that the consanguinity model behaves similarly to a standard coalescent, scaling population size by a factor 1 − 3c, wherecrepresents the kinship coefficient of a randomly chosen mating pair. It provides the explanation for an earlier result describing mean coalescence time in the consanguinity model in terms ofc. The results extend the potential to make predictions about ROH and IBD in relation to demographic parameters of diploid populations.
EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotes
Authors: Richter Daniel J. , Berney Cédric , Strassert Jürgen F. H. , Poh Yu-Ping , Herman Emily K. , Muñoz-Gómez Sergio A. , Wideman Jeremy G. , Burki Fabien , de Vargas Colomban
Published: July 2020

Abstract

EukProt is a database of published and publicly available predicted protein sets selected to represent the breadth of eukaryotic diversity, currently including 993 species from all major supergroups as well as orphan taxa. The goal of the database is to provide a single, convenient resource for gene-based research across the spectrum of eukaryotic life, such as phylogenomics and gene family evolution. Each species is placed within the UniEuk taxonomic framework in order to facilitate downstream analyses, and each data set is associated with a unique, persistent identifier to facilitate comparison and replication among analyses. The database is regularly updated, and all versions will be permanently stored and made available via FigShare. The current version has a number of updates, notably ‘The Comparative Set’ (TCS), a reduced taxonomic set with high estimated completeness while maintaining a substantial phylogenetic breadth, which comprises 196 predicted proteomes. A BLAST web server and graphical displays of data set completeness are available at http://evocellbio.com/eukprot/. We invite the community to provide suggestions for new data sets and new annotation features to be included in subsequent versions, with the goal of building a collaborative resource that will promote research to understand eukaryotic diversity and diversification.
Three times NO: no relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of three studies
Authors: Kołodziej Aleksandra , Magnuski Mikołaj , Ruban Anastasia , Brzezicka Aneta
Published: July 2020

For decades, the frontal alpha asymmetry (FAA) - a disproportion in EEG alpha oscillations power between right and left frontal channels - has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis - running many related analyses and testing the sensitivity of the effect to changes in the analytical approach - on data from three independent studies. Only two of the 81 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.
Resting-state functional connectivity predicts recovery from visually induced motion sickness
Authors: Miyazaki Jungo , Yamamoto Hiroki , Ichimura Yoshikatsu , Yamashiro Hiroyuki , Murase Tomokazu , Yamamoto Tetsuya , Umeda Masahiro , Higuchi Toshihiro
Published: July 2020

Movies depicting certain types of motion often provoke uncomfortable symptoms similar to motion sickness, termed visually induced motion sickness (VIMS). VIMS generally evolves slowly during the viewing of a motion stimulus and, when the stimulus is removed, the recovery proceeds over time. Recent human neuroimaging studies have provided new insights into the neural bases underlying the evolution of VIMS. In contrast, no study has investigated the neural bases underlying the recovery from VIMS. Study of the recovery process is critical for the development of a way to promote recovery and could provide further clues for understanding the mechanisms of VIMS. We thus investigated brain activity during the recovery from VIMS with functional connectivity (FC) magnetic resonance imaging. We found enhanced recovery-related FC patterns involving brain areas such as the insular, cingulate, and visual cortical regions, which have been suggested to play important roles in the emergence of VIMS. These regions also constituted large interactive networks. Furthermore, the increase in FC was correlated with the subjective awareness of recovery for the following 5 pairs of brain regions: insula–superior temporal gyrus, claustrum–left and right inferior parietal lobules, claustrum–superior temporal gyrus, and superior frontal gyrus–lentiform nucleus. Considering the previous findings on the functions of these regions and the present findings, it is suggested that the increase in FC may reflect brain processes such as enhanced interoceptive awareness to one’s own bodily state, a neuroplastic change in visual processing circuits, and/or the maintenance of visual spatial memory.
Epoxy fatty acid dysregulation and neuroinflammation in Alzheimer’s disease is resolved by a soluble epoxide hydrolase inhibitor
Authors: Ghosh Anamitra , Comerota Michele E. , Wan Debin , Chen Fading , Propson Nicholas E. , Hwang Sung Hee , Hammock Bruce D. , Zheng Hui
Published: July 2020

Neuroinflammation has been increasingly recognized to play critical roles in Alzheimer’s disease (AD). The epoxy fatty acids (EpFAs) are derivatives of the arachidonic acid metabolism with anti-inflammatory activities. However, their efficacy is limited due to the rapid hydrolysis by the soluble epoxide hydrolase (sEH). We found that sEH is predominantly expressed in astrocytes where its levels are significantly elevated in postmortem human AD brains and in β-amyloid mouse models, and the latter is correlated with drastic reductions of brain EpFA levels. Using a highly potent and specific small molecule sEH inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU), we report here that TPPU treatment potently protected against LPS-induced inflammation in vitro and in vivo. Long-term administration of TPPU to the 5xFAD mouse model via drinking water reversed microglia and astrocyte reactivity and immune pathway dysregulation, and this is associated with reduced β–amyloid pathology and improved synaptic integrity and cognitive function. Importantly, TPPU treatment reinstated and positively correlated EpFA levels in the 5xFAD mouse brain, demonstrating its brain penetration and target engagement. These findings support TPPU as a novel therapeutic target for the treatment of AD and related disorders.

One Sentence Summary

We show that soluble epoxide hydrolase is upregulated in AD patients and mouse models, and that inhibition of this lipid metabolic pathway using an orally bioavailable small molecule inhibitor is effective in restoring brain epoxy fatty acids, ameliorating AD neuropathology and improving synaptic and cognitive function.
Males deploy multifaceted strategies and hijack longevity pathways to induce premature demise of the opposite sex
Authors: Booth Lauren N. , Shi Cheng , Tantilert Cindy , Yeo Robin W. , Hebestreit Katja , Hollenhorst Cecilia N. , Murphy Coleen T. , Brunet Anne
Published: July 2020

Interactions between the sexes negatively impact health in many species, including mammals1–9. In mice, sexual interactions induce weight gain and shorten lifespan in females, independent of fertilization6,9. InCaenorhabditis, males shorten the lifespan of the opposite sex (females or hermaphrodites)1–3,8. However, the mechanisms underlying the negative influence of males on lifespan – and their overlap with known longevity pathways – are still largely unknown. Here, we use transcriptomic profiling and targeted screens to systematically uncover new conserved genes involved in male-induced demise. Interestingly, deficiency of these genes individually, and especially in combination, induces strong protection, highlighting the benefit of combining interventions to extend lifespan. Some genes (e.g.acbp-3, col-43) only extend hermaphrodite lifespan when knocked-down in the presence of males, suggesting specific protective mechanisms against male-induced demise. However, we also uncover two previously unknown longevity genes (sri-40anddelm-2) that, when knocked-down, extend hermaphrodite lifespan both with and without males, which points to new broad mechanisms of resistance. In sharp contrast, many classical long-lived mutants are actually short-lived in the presence of males, suggesting that males hijack and suppress known longevity pathways. This systematic analysis reveals striking differences in longevity in single sex versus mixed sex environments and uncovers the elaborate network of functional regulation elicited by sexual interactions, which could extend to other species.
Consistent cross-modal identification of cortical neurons with coupled autoencoders
Authors: Gala Rohan , Budzillo Agata , Baftizadeh Fahimeh , Miller Jeremy , Gouwens Nathan , Arkhipov Anton , Murphy Gabe , Tasic Bosiljka , Zeng Hongkui , Hawrylycz Michael , Sümbül Uygar
Published: July 2020

Consistent identification of neurons in different experimental modalities is a key problem in neuroscience. While methods to perform multimodal measurements in the same set of single neurons have become available, parsing complex relationships across different modalities to uncover neuronal identity is a growing challenge. Here, we present an optimization framework to learn coordinated representations of multimodal data, and apply it to a large multimodal dataset profiling mouse cortical interneurons. Our approach reveals strong alignment between transcriptomic and electrophysiological characterizations, enables accurate cross-modal data prediction, and identifies cell types that are consistent across modalities.

Highlights

Coupled autoencoders for multimodal assignment, Analysis of Patch-seq data consisting of more than 3000 cells
Tissue specific muscle extracellular matrix hydrogel improves skeletal muscle regenerationin vivoover non-matched tissue source
Authors: Ungerleider Jessica L. , Dzieciatkowska Monika , Hansen Kirk C. , Christman Karen L.
Published: July 2020

Decellularized extracellular matrix (ECM) hydrogels present a novel, clinical intervention for a myriad of regenerative medicine applications. The source of ECM is typically the same tissue to which the treatment is applied; however, the need for tissue specific ECM sources has not been rigorously studied. We hypothesized that tissue specific ECM would improve regeneration through preferentially stimulating physiologically relevant processes (e.g. progenitor cell proliferation and differentiation). One of two decellularized hydrogels (tissue specific skeletal muscle or non mesoderm-derived lung) or saline were injected intramuscularly two days after notexin injection in mice (n=7 per time point) and muscle was harvested at days 5 and 14 for histological and gene expression analysis. Both injectable hydrogels were decellularized using the same detergent and were controlled for donor characteristics (i.e. species, age). At day 5, the skeletal muscle ECM hydrogel significantly increased the density of Pax7+ satellite cells in the muscle. Gene expression analysis at day 5 showed that skeletal muscle ECM hydrogels increased expression of genes implicated in muscle contractility. By day 14, skeletal muscle ECM hydrogels improved muscle regeneration over saline and lung ECM hydrogels as shown through a shift in fiber cross sectional area distribution towards larger fibers. This data indicates a potential role for muscle-specific regenerative capacity of decellularized, injectable muscle hydrogels. Further transcriptomic analysis of whole muscle mRNA indicates the mechanism of tissue specific ECM-mediated tissue repair may be immune and metabolism pathway-driven. Taken together, this suggests there is benefit in using tissue specific ECM for regenerative medicine applications.
Computational Psychiatry Research Map (CPSYMAP): a New Database for Visualizing Research Papers
Authors: Kato Ayaka , Kunisato Yoshihiko , Katahira Kentaro , Okimura Tsukasa , Yamashita Yuichi
Published: July 2020

The field of computational psychiatry is growing in prominence along with the recent advances in computational neuroscience, machine learning, and the cumulative scientific evidence of psychiatric disorders. Computational approaches provide an understanding of disorders using psychological and neuroscience terms and help to determine treatment protocols based on high-dimensional data. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies. Computational psychiatry combines knowledge from neuroscience, psychiatry, and computation; thus, there is an emerging need for a platform to integrate and coordinate these perspectives. In this study, we developed a new database for visualizing research papers as a two-dimensional “map” called the Computational Psychiatry Research Map (CPSYMAP). This map shows the distribution of papers along neuroscientific, psychiatric, and computational dimensions to enable anyone to find niche research and deepen their understanding of the field.
Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome
Authors: Liu Xiaomin , Tong Xin , Zou Yuanqiang , Lin Xiaoqian , Zhao Hui , Tian Liu , Jie Zhuye , Wang Qi , Zhang Zhe , Lu Haorong , Xiao Liang , Qiu Xuemei , Zi Jin , Wang Rong , Xu Xun , Yang Huanming , Wang Jian , Zong Yang , Liu Weibin , Hou Yong , Zhu Shida , Jia Huijue , Zhang Tao
Published: July 2020

The gut microbiome has been implicated in a variety of physiological states, but controversy over causality remains unresolved. Here, we performed bidirectional Mendelian randomization (MR) analyses on 3,432 Chinese individuals with whole genome, whole metagenome, anthropometric, and blood metabolic trait data. We identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 of them. Increased relative abundances of fecalOscillibacterandAlistipeswere causally linked to decreased triglyceride concentration. Conversely, blood metabolites such as glutamic acid appeared to decrease fecalOxalobacter, and members ofProteobacteriawere influenced by metabolites such as 5-methyltetrahydrofolic acid, alanine, glutamate, and selenium. Two-sample MR with data from Biobank Japan partly corroborated results with triglyceride and with uric acid, and also provided causal support for published fecal bacterial markers for cancer and cardiovascular diseases. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies.
Lockdown measures and relative changes in the age-specific incidence of SARS-CoV-2 in Spain
Authors: De Salazar PM , Gómez-Barroso D , Pampaka D , Gil JM , Peñalver B , Fernández-Escobar C , Lipsitch M , Larrauri A , Goldstein E , Hernán MA
Published: July 2020

Background

The first months of the SARS-CoV-2 epidemic in Spain resulted in high incidence and mortality. A national sero-epidemiological survey suggests higher cumulative incidence of infection in older individuals than in younger individuals. However, little is known about the epidemic dynamics in different age groups, including the relative effect of the lockdown measures introduced on March 15, and strengthened on March 30 to April 14, 2020 when only essential workers continued to work.

Methods

We used data from the National Epidemiological Surveillance Network (RENAVE in Spanish) on the daily number of reported COVID-19 cases (by date of symptom onset) in eleven 5-year age groups: 15-19y through 65-69y. For each age group g, we computed the proportion E(g) of individuals in age group g among all reported cases aged 15-69y during the pre-lockdown period (March 1-10, 2020) and the corresponding proportion L(g) during two lockdown periods (March 25-April 3 and April 8-17, 2020). For each lockdown period, we computed the proportion ratios PR(g)= L(g)/E(g). For each pair of age groups g1,g2, PR(g1)>PR(g2) implies a relative increase in the incidence of detected SARS-CoV-2 infection in the age group g1 compared with g2 for the later vs. early period.

Results

For the first lockdown period, the highest PR values were in age groups 50-54y (PR=1.21; 95% CI: 1.12,1.30) and 55-59y (PR=1.19; 1.11,1.27). For the second lockdown period, the highest PR values were in age groups 15-19y (PR=1.26; 0.95,1.68) and 50-54y (PR=1.20; 1.09,1.31).

Conclusions

Our results suggest that different outbreak control measures led to different changes in the relative incidence by age group. During the first lockdown period, when non-essential work was allowed, individuals aged 40-64y, particularly those aged 50-59y presented with higher COVID-19 relative incidence compared to pre-lockdown period, while younger adults/older adolescents (together with persons aged 50-59y) had increased relative incidence during the later, strengthened lockdown. The role of different age groups during the epidemic should be considered when implementing future mitigation efforts.
Identifying main and interaction effects of risk factors to predict intensive care admission in patients hospitalized with COVID-19: a retrospective cohort study in Hong Kong
Authors: Zhou Jiandong , Tse Gary , Lee Sharen , Liu Tong , Wu William KK , Cao Zhidong , Zeng Daniel Dajun , Kei Wong Ian Chi , Zhang Qingpeng , Cheung Bernard Man Yung
Published: July 2020

Background

The coronavirus disease 2019 (COVID-19) has become a pandemic, placing significant burdens on the healthcare systems. In this study, we tested the hypothesis that a machine learning approach incorporating hidden nonlinear interactions can improve prediction for Intensive care unit (ICU) admission.

Methods

Consecutive patients admitted to public hospitals between 1st January and 24th May 2020 in Hong Kong with COVID-19 diagnosed by RT-PCR were included. The primary endpoint was ICU admission.

Results

This study included 1043 patients (median age 35 (IQR: 32-37; 54% male). Nineteen patients were admitted to ICU (median hospital length of stay (LOS): 30 days, median ICU LOS: 16 days). ICU patients were more likely to be prescribed angiotensin converting enzyme inhibitors/angiotensin receptor blockers, anti-retroviral drugs lopinavir/ritonavir and remdesivir, ribavirin, steroids, interferon-beta and hydroxychloroquine. Significant predictors of ICU admission were older age, male sex, prior coronary artery disease, respiratory diseases, diabetes, hypertension and chronic kidney disease, and activated partial thromboplastin time, red cell count, white cell count, albumin and serum sodium. A tree-based machine learning model identified most informative characteristics and hidden interactions that can predict ICU admission. These were: low red cells with 1) male, 2) older age, 3) low albumin, 4) low sodium or 5) prolonged APTT. A five-fold cross validation confirms superior performance of this model over baseline models including XGBoost, LightGBM, random forests, and multivariate logistic regression.

Conclusions

A machine learning model including baseline risk factors and their hidden interactions can accurately predict ICU admission in COVID-19.
Spatiotemporal Trends in Bed Bug Metrics, New York City
Authors: Hacker Kathryn P. , Greenlee Andrew J. , Hill Alison L. , Schneider Daniel , Levy Michael Z.
Published: July 2020

Bed bug outbreaks pose a major challenge in urban environments and cause significant strain on public resources. Few studies have systematically analyzed the epidemic or the potential effects of policies to combat bed bugs. Here we use three sources of administrative data to characterize the spatial-temporal trends of bed bug inquiries, complaints, and reports in New York City. From 2014–2020, Bed bug complaints have significantly decreased (p < 0.01), the absolute number of complaints per month dropping by half (875 average complaints per month to 440 average complaints per month); conversely cockroach-specific complaints increased over the same period. Despite the decrease of bed bug complaints, areas with reported high bed bug infestation tend to remain infested, highlighting the persistence of these pests. There are limitations to the datasets; still the evidence available suggests that interventions employed by New York City residents and lawmakers are stemming the bed bug epidemic and may serve as a model for other large cities.
Multitask learning from clinical text and acute physiological conditions differentially improve the prediction of mortality and diagnosis at the ICU
Authors: Reichmann L.G. , Valdes G. , Pirrachio Romain , Interian Y.
Published: July 2020

The prediction of mortality of critically ill patients has stimulated the development of many severity scoring algorithms. The majority of the models use physiological measurements obtained during the first hours of admission (i.e., heart rate, arterial blood pressure, or respiratory rate). In this study, we propose to improve the performance of current scoring system by including free text from patient’s medical history. Although the primary outcome was in-hospital mortality, we chose a model architecture to provide simultaneous assessment of ICD-9 codes and groupings. We hypothesized that including patients’ medical history with a multitask learning approach would improve model performance. We compared the predictive performance obtained with our approach to the best models previously proposed in the literature (baseline models). We used the MIMIC publicly available database which includes > 60,000 ICU admissions between 2001 and 2012. The patients’ condition at admission was accounted for by the preliminary diagnosis at admission and the medical history extracted from the discharge summaries notes. Unstructured data was processed through a Gated Recurrent Units layer with pre-trained word embeddings, and the hidden states were concatenated to the remaining structured-tabular data. Baseline models achieved similar results than in previously published work, but our artificial neural networks models showed significant improvement towards classification of mortality (AUC-ROC = 0.90). Including the medical history improved all tasks but relatively more the ICD-9 codes prediction than the mortality. The clinical prediction model presented here could be used to identify patients’ risk groups, which would improve the quality of ICU care, and further help to efficiently allocate hospital resources.
COVID-MATCH65 – A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2
Authors: Trubiano Jason A , Vogrin Sara , Smibert Olivia C , Marhoon Nada , Alexander Adrian A , Chua Kyra Y L , James Fiona L , Jones Nicholas RL , Grigg Sam E , Xu Cecilia LH , Moini Nasreen , Stanley Sam R , Birrell Michael T , Rose Morgan T , Gordon Claire L , Kwong Jason C , Holmes Natasha E
Published: July 2020

Due to the ongoing COVID-19 pandemic and increased pressure on testing resources, understanding the clinical and epidemiological features closely associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is vital at point of care to enable risk stratification. We demonstrate that an internally derived and validated clinical decision rule, COVID-MATCH65, has a high sensitivity (92.6%) and NPV (99.5%) for SARS-CoV-2 and could be used to aid COVID-19 risk-assessment and resource allocation for SARS-CoV-2 diagnostics.
Toward an early diagnostic marker of Parkinson’s: measuring iron in dopaminergic neurons with MR relaxometry
Authors: Brammerloh Malte , Morawski Markus , Weigelt Isabel , Reinert Tilo , Lange Charlotte , Pelicon Primož , Vavpetič Primož , Jankuhn Steffen , Jäger Carsten , Alkemade Anneke , Balesar Rawien , Pine Kerrin , Gavriilidis Filippos , Trampel Robert , Reimer Enrico , Arendt Thomas , Weiskopf Nikolaus , Kirilina Evgeniya
Published: July 2020

In Parkinson’s disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of thesubstantia nigraprecedes motor symptoms by two decades. Monitoring this neuronal depletion, at an early disease stage, is needed for early diagnosis. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to iron. However, the exact mechanisms of MRI contrast in nigrosome 1 are not well understood, hindering the development of powerful biomarkers. We demonstrate that the dominant contribution to the effective transverse MRI relaxation ratein nigrosome 1 originates from iron accumulated in dopaminergic neurons. We linkquantitatively to the product of cell density and local iron concentration in dopaminergic neurons, combining quantitative 3D iron histology, biophysical modeling, and quantitative MRI onpost mortembrain tissue. It is now theoretically possible to monitor dopaminergic neuron depletion,in vivo, as an early diagnostic tool for Parkinson’s disease.
Characterization of redox sensitive algal mannitol-1-phosphatases of the haloacid dehalogenase superfamily of proteins
Authors: Le Strat Yoran , Tonon Thierry , Leblanc Catherine , Groisillier Agnès
Published: July 2020

Macroalgae (or seaweeds) are the dominant primary producers in marine vegetated coastal habitats and largely contribute to global ocean carbon fluxes. They also represent attractive renewable production platforms for biofuels, food, feed, and bioactives, notably due to their diverse and peculiar polysaccharides and carbohydrates. Among seaweeds, brown algae produce alginates and sulfated fucans as constituents of their cell wall, and the photoassimilates laminarin and mannitol for carbon storage. Availability of brown algal genomes, including those of the kelpSaccharina japonicaand the filamentousEctocarpussp., has paved the way for biochemical characterization of recombinant enzymes involved in their polysaccharide and carbohydrates synthesis, notably mannitol. Biosynthesis of mannitol in brown algae starts from fructose-6-phospate, which is converted into mannitol-1-phosphate (M1P), and this intermediate is then hydrolysed by a haloacid dehalogenase type M1P phosphatase (M1Pase) to produce mannitol. We report here the biochemical characterization of a second M1Pase inEctocarpussp after heterologous expression inEscherichia coli. (EsM1Pase1). Our results show that bothEctocarpusM1Pases were redox sensitive, with EsM1Pase1 being active only in presence of reducing agent. Such catalytic properties have not been observed for any of the M1Pase characterized so far. EsM1Pases were specific to mannitol, in contrast toS. japonicaM1Pases that can use other phosphorylated sugars as substrates. Finally, brown algal M1Pases grouped into two well-supported clades, with potential different subcellular localization and physiological role(s) under diverse environmental conditions and/or stages of life cycle.
Recalled parental bonding interacts with oxytocin receptor gene polymorphism in modulating anxiety and avoidance in adult relationships
Authors: Cataldo Ilaria , Bonassi Andrea , Lepri Bruno , Foo Jia Nee , Setoh Peipei , Esposito Gianluca
Published: July 2020

Early interactions with significant individuals affect social experience throughout the course of a lifetime, as a repeated and prolonged perception of different levels of care, independence or control influences the modulation of emotional regulatory processes. As many factors play a role in shaping the expectations and features of social interaction, in this study we consider the influence of parental bonding and genetic allelic variation of oxytocin receptor gene polymorphism (rs53576) over levels of experienced anxiety and avoidance in 313 young adults belonging to two different cultural contexts, namely Italy and Singapore. Results highlight a major effect of maternal characteristics, care and overprotection, with differences between the two cultural groups. Additionally, the interaction between rs53576 and maternal overprotection suggest different environmental susceptibility in the Italian sample and the Singaporean one. Implication in clinical work and future steps are described in the conclusion.
Defining endogenous TACC3–chTOG–clathrin–GTSE1 interactions at the mitotic spindle using induced relocalization
Authors: Ryan Ellis L. , Shelford James , Massam-Wu Teresa , Bayliss Richard , Royle Stephen J.
Published: July 2020

A multiprotein complex containing TACC3, clathrin, and other proteins has been implicated in mitotic spindle stability. To disrupt this complex in an anti-cancer context, we need to understand the composition of the complex and the interactions between complex members and with microtubules. Induced relocalization of proteins in cells is a powerful way to analyze protein-protein interactions and additionally monitoring where and when these interactions occur. We used CRISPR/Cas9 gene-editing to add tandem FKBP-GFP tags to each complex member. The relocalization of endogenous tagged protein from the mitotic spindle to mitochondria and assessment of the effect on other proteins allowed us to establish that TACC3 and clathrin are core complex members and that chTOG and GTSE1 are ancillary to the complex, respectively binding to TACC3 and clathrin, but not each other. PIK3C2A, a membrane trafficking protein that binds clathrin, was previously proposed to also bind TACC3 and stabilize the TACC3–chTOG–clathrin–GTSE1 complex during mitosis. We show that PIK3C2A is not on the mitotic spindle and that knockout of this gene had no effect on the localization of the complex. We therefore conclude that PIK3C2A is not a member of the TACC3–chTOG–clathrin–GTSE1 complex. This work establishes that targeting the TACC3–clathrin interface or their microtubule-binding sites are the two strategies most likely to disrupt spindle stability mediated by this multiprotein complex.
Predictive Metabolic Pathways of Lactic Acid Bacterial Strains Isolated from Fermented Foods
Authors: Kharnaior Pynhunlang , Halami Prakash M. , Tamang Jyoti Prakash
Published: July 2020

We attempted to use PICTRUSt2 software and bioinformatics tool to infer the raw sequences obtained from pure strains of Lactococcus lactis and Lactobacillus plantarum isolated from some fermented foods in India, which were identified by 16S rRNA gene sequencing method. Predictive metabolic pathways of 16S sequences of LAB strains were predicted by PICRUSt2 mapped against KEGG database, which showed genes associated with metabolism (36.74%), environmental information processing (32.34%), genetic information processing (9.86%) and the unclassified (21.06%). KGGE database also showed the dominant genes related to predictive sub-pathways of metabolism at level-2 were membrane transport (31.16%) and carbohydrate metabolism (12.42%).