bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocol for secondary data analysis of 4 UK cohorts examining youth adversity and mental health in the context of intersectionality
Authors: Hosang Georgina M. , Havers Laura , Shuai Ruichong , Fonagy Peter , Fazel Mina , Morgan Craig , Karamanos Alexis , Fancourt Daisy , McCrone Paul , Smuk Melanie , Bhui Kamaldeep , Shakoor Sania
Published: July 2023

Background

Youth adversity (e.g., abuse and bullying victimisation) is robust risk factor for later mental health problems (e.g., depression and anxiety). Research shows the prevalence of youth adversity and rates of mental health problems vary by individual characteristics, identity or social groups (e.g., gender and ethnicity). However, little is known about whether the impact of youth adversity on mental health problems differ across the intersections of these characteristics (e.g., white female). This paper reports on a component of the ATTUNE research programme (work package 2) which aims to investigate the impact and mechanisms of youth adversity on depressive and anxiety symptoms in young people by intersectionality profiles.

Methods

The data are from 4 UK adolescent cohorts: HeadStart Cornwall, Oxwell, REACH, and DASH. These cohorts were assembled for adolescents living in distinct geographical locations representing coastal, suburban and urban places in the UK. Youth adversity was assessed using a series of self-report questionnaires and official records. Validated self-report instruments measured depressive and anxiety symptoms. A range of different variables were classified as possible social and cognitive mechanisms.

Results and analysis

Structural equation modelling (e.g., multiple group models, latent growth models) and multilevel modelling will be used, with adaptation of methods to suit the specific available data, in accord with statistical and epidemiological conventions.

Discussion

The results from this research programme will broaden our understanding of the association between youth adversity and mental health, including new information about intersectionality and related mechanisms in young people in the UK. The findings will inform future research, clinical guidance, and policy to protect and promote the mental health of those most vulnerable to the negative consequences of youth adversity.
Accumulating Sedentary Time and Physical Activity from Childhood to Adolescence and Cardiac Function in Adolescence
Authors: Haapala Eero A. , Leppänen Marja H. , Lee Earric , Savonen Kai , Laukkanen Jari A. , Kähönen Mika , Brage Soren , Lakka Timo A.
Published: July 2023

Background

Little is known about the associations of a sedentary lifestyle from childhood with cardiac work and function during adolescence. We studied if cumulative sedentary time and physical activity from childhood to adolescence are associated with cardiac work and function in adolescence.

Methods

A total of 153 adolescents aged 15 years at the time of assessment of cardiac work and function participated. We assessed sedentary time and physical activity using a combined movement and heart rate sensor in childhood and adolescence (baseline, 2- and 8-year follow-ups) and cardiac work and function using impedance cardiography in adolescence (8-year follow-up).

Results

Cumulative sedentary time from baseline over the follow-up was directly (standardised regression coefficient β=0.245 to 0.246, 95% confidence intervals, CI=0.092 to 0.400) and moderate to vigorous physical activity (β=-0.355 to -0.323, 95% CI=-0.579 to - 0.119), and vigorous physical activity (β=-0.305 to -0.295, 95% CI=-0.524 to -0.083) from baseline over the follow-up was inversely associated with cardiac work at 8-year follow-up. Cumulative vigorous physical activity from baseline to 2- and 8-year follow-up was inversely associated with cardiac work index at 8-year follow-up (β=-0.225 to -0.218, 95% CI=-0.450 to 0.000). However, adiposity and other cardiometabolic risk factors partially explained these associations.

Conclusions

Higher levels of sedentary time and lower levels of moderate and/or vigorous-intensity physical activity during childhood were associated with higher cardiac work in adolescence. These findings highlight the importance of obesity prevention and weight management and promotion physically active lifestyle since childhood to prevent abnormalities in cardiac function later in life.

CLINICAL PERSPECTIVE

Sedentary lifestyle increases the risk of cardiovascular diseases, but little is known about the role of sedentary time and physical activity in cardiac work and function in youth.

We found that adolescents accumulating higher levels of sedentary time and lower levels of physical activity since childhood had higher cardiac workload compared to their more physically active peers. However, these associations were partly explained by adiposity and other cardiometabolic risk factors.

These findings highlight the importance of obesity prevention and weight management and promotion physically active lifestyle since childhood to prevent abnormalities in cardiac function later in life.
The machine learning algorithm identified COL7A1 as a diagnostic marker for LUSC and HNSC
Authors: Wang Chenyu , Ma Yongxin , Qi Jiaojiao , Jiang Xianglai
Published: July 2023

Squamous cell carcinomas (SCCs) comes from different parts, but there may be similar tumorigenic signaling pathways and metabolism, and different squamous cell carcinoma has a similar mutation landscape and squamous differentiation expression. Studying the expression profile of common SCCs is helpful to find biomarkers with diagnostic and prognostic significance for a variety of squamous cell carcinoma. Lung squamous cell carcinoma (LUSC), head and neck squamous cell carcinoma (HNSC), and ‘squamous cell cancer’ in esophageal carcinoma (ESCA) and cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) in The Cancer Genome Atlas (TCGA) database were used as training sets. The relevant data sets in the Gene Expression Omnibus (GEO) database were selected as validation sets. Machine learning algorithms were used to screen out factors with high accuracy in the diagnosis of SCCs as core genes, and explore their effects on patient prognosis and immunotherapy. COL7A1 (Collagen Type VII Alpha 1 Chain) has high accuracy in the diagnosis of LUSC and HCSC, whether in the training set (LUSC _ AUC: 0.987; HNSC _ AUC: 0.933) or validation set (LUSC _ AUC: 1.000; HNSC _ AUC: 0.967). Moreover, the expression of COL7A1 was significantly correlated with shorter OS and DSS in HNSC and LUSC patients, and was also significantly negatively correlated with IPS in LUSC patients treated with CTLA4 (-) PD1 (+), CTLA4 (+) PD1 (-) and CTLA4 (+) PD1 (+). COL7A1 has the potential to be used as a diagnostic and prognostic marker for LUSC and HNSC and to predict the efficacy of LUSC immunotherapy.
The epidemiological investigation of hypertension in northern Henan Province
Authors: Lu Xing , Lin Ziyang , Yang Junzheng
Published: July 2023

Background/purpose

To understand the epidemiological status and risk factors of hypertension in northern Henan province, aim to provide a basis for the prevention, diagnosis, and treatment of hypertension in northern Henan Province.

Methods

To collect the clinical data in Xinxiang Central Hospital from 2019-2021, those data were classified and analyzed according to the basic information of investigation subjects including gender, ethnicity, age, smoking, marital status, occupation, education, and potential risk factors including hyperlipidemia, diabetes mellitus, ischemic stroke, coronary heart disease, angina pectoris, myocardial infarction, heart failure, peripheral artery disease, chronic renal insufficiency, gastrointestinal ulcers, chronic obstructive pulmonary disease, cerebral hemorrhage.

Results

A total of 770 clinical data of investigation subjects were collected, there are 621 males and 149 females, accounting for 80.65% and 19.35%, respectively; age range of investigation subjects was 20-97 years old; there were 248 males with hypertension, accounting for 32.21% in the total population, and there were 92 females with hypertension, accounting for 27.06% in the total population; there were 329 people with a history of smoking, and 346 people were never smoking, accounting for 49.10% and 51.64% in the total investigation population, respectively; in this investigation, the proportion of married people is the highest (638/670, 95.22%); the main occupational population was peasant farmer (353/670, 52.69%), followed by (164/670, 24.48%); the number of people with middle school/vocational school education was the highest(338/670, 50.45%), followed by primary school education (249/670, 37.16%).

the results of statistical analysis demonstrated that the incidence of hypertension is related to gender (P<0.01), hyperlipidemia (P<0.05), diabetes mellitus (P<0.001) and ischemic stroke (P<0.001), and had no relation to smoking, family history of coronary heart disease, family history of angina pectoris, history of heart failure, history of coronary intervention, history of peripheral arterial disease, chronic renal insufficiency, history of peptic ulcer disease, history of Chronic obstructive pulmonary disease and history of cerebral hemorrhage (P>0.05).

Conclusion

There is a certain regional specificity in the epidemiology of hypertension in the northern Henan Province, and the incidence of hypertension was related to gender, age, occupation, hyperlipidemia, diabetes mellitus and ischemic stroke, those evidences may provide clinical significance for the prevention, diagnosis, and treatment of hypertension in northern Henan province.
Cognitive behavioural therapy-based interventions for gastroduodenal disorders of gut-brain interaction: A systematic review
Authors: Law Mikaela , Pickering Isabella , Bartlett Esme , Sebaratnam Gabrielle , Varghese Chris , Gharibans Armen , O’Grady Greg , Andrews Christopher N. , Calder Stefan
Published: July 2023

Objective

Cognitive behavioural therapy (CBT) is increasingly used to manage Disorders of Gut-Brain Interaction (DGBIs). This systematic review aimed to review the evidence for the effectiveness of CBT-based interventions for patients with gastroduodenal DGBIs.

Methods

Medline, Embase, PubMed, Cochrane Central, and Scopus were searched in July 2022. Studies were included if they investigated the effects of a CBT-based intervention on gastrointestinal symptoms and/or psychological outcomes pre- and post-intervention in patients with gastroduodenal DGBIs. Case studies, studies not in English, and studies with patients under 18 years were excluded. Results were synthesised narratively, and standardised effect sizes were calculated where possible.

Results

Nine studies (seven RCTs and two pre/post studies) were identified, with data reported in 10 articles (total N=602). The studies investigated patients with functional dyspepsia (n=7), rumination syndrome (n=1), and supragastric belching (n=1). The studies had heterogeneous interventions, methodologies, and outcomes, precluding meta-analysis, as well as a moderate-high risk of bias and high drop-outs rates. Findings demonstrated decreased gastrointestinal symptoms and improved anxiety, depression, and quality of life, from pre- to post-intervention, with medium to large effect sizes for symptoms and small to large effect sizes for psychological outcomes. Efficacy was maintained at follow-up, up to one year later.

Conclusions

This review suggests promising evidence that CBT effectively improves gastrointestinal symptoms and psychological outcomes in patients with gastroduodenal DGBIs. However, heterogeneity, risk of bias, and lack of statistical reporting were noted, indicating the need for more robust research and standardisation.
Spinal mobilization characteristics: a scoping literature review of biomechanical parameters
Authors: Gorrell Lindsay M , Nyirö Luana , Pasquier Mégane , Pagé Isabelle , Heneghan Nicola R , Schweinhardt Petra , Descarreaux Martin
Published: July 2023

Background

Spinal mobilization (SMob) is often included in the conservative management of spinal pain conditions as a recommended and effective treatment. While some studies quantify the biomechanical (kinetic) parameters of SMob, interpretation of findings is difficult due to poor reporting of methodological details. The aim of this study was to synthesise the literature describing biomechanical parameters of manually applied SMob.

Methods

This study is reported in accordance with the Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) statement. Databases were searched from inception to October 2022: MEDLINE (Ovid), Embase, CINAHL, ICL, PEDro and Cochrane Library. Data were extracted and reported descriptively for the following domains: general study characteristics, number of and characteristics of individuals who delivered/received SMob, region treated, equipment used and biomechanical parameters of SMob.

Results

Of 7,607 records identified, 36 (0.5%) were included in the analysis. Of these, SMob was delivered to the cervical spine in 13 (36.1%), the thoracic spine in 3 (8.3%) and the lumbopelvic spine in 18 (50.0%) studies. In 2 (5.6%) studies, spinal region was not specified. For SMob applied to all spinal regions, biomechanical parameters were: peak force (0-128N); duration (10-120s); frequency (0.1-4.5Hz); and force amplitude (1-102N).

Conclusions

This study reports considerable variability of the biomechanical parameters of SMob. In studies reporting biomechanical parameters, SMob was most frequently delivered to the lumbar and cervical spine of humans and most commonly peak force was reported. Future studies should focus on the detailed reporting of biomechanical parameters to facilitate the investigation of clinical dose-response effects.
Pneumococcal Serotype Prevalence in Southeast Asia: A Systematic Review and Meta-Analysis
Authors: Lister Alex J. J. , Dombay Evelin , Cleary David W. , Clarke Stuart C.
Published: July 2023

Background

The prevalence ofStreptococcus pneumoniaeserotypes in the ASEAN region is not well studied despite severe pneumococcal infections being a major cause of death among children in the region. This information is crucial for understanding the epidemiology of the disease and guiding vaccine policies. Our study aimed to provide a thorough analysis of the pneumococcal serotypes in ASEAN prior to vaccine introduction to assist countries in formulating evidence-based vaccine policies.

Methods

We conducted a systematic review and meta-analysis of studies reportingS. pneumoniaeserotypes from carriage, invasive disease (IPD) and non-invasive disease (non-IPD) published up until 31stDecember 2022 using PubMed, PubMed Central, Ovid MEDLINE and Scopus databases, reference lists and search engines. Data prior to the national introduction of conjugate vaccines in the ASEAN region were included. Non-English, animal, case studies, reviews, and studies on antibiotic resistance only were excluded. The quality of studies was examined using the CASP and the JBI’s Critical Appraisal Tools. The frequency of serogroups and serotypes was calculated, and vaccine coverage was estimated by the addition of vaccine serotypes as a fraction of the total number of isolates per age group. This study was registered with PROSPERO CRD42022243994.

Findings

A total of 940 studies were identified, and 99 and 84 relevant papers were included in the qualitative and quantitative analyses, respectively. A total of 16,396 isolates were identified, spread across all body sites and ages, with vaccine-covered serotypes 19F (n = 2,061, 12.57% [95%CI: 12.07 – 13.09]), 23F (n = 1,508, 9.20% [95%CI: 8.76 – 9.65]) and 6B (n = 1,160, 7.07% [95%CI: 6.69 – 7.48]) occurring most often. Non-vaccine typese.g., 6AB (n = 617, 3.76% [95%CI: 3.48 – 4.07]), 15BC (n = 35, 2.57% [95%CI: 2.33 – 2.82]) and 34 (n = 260, 1.59% [95%CI: 1.40 – 1.79]) were also frequently observed.

Interpretation

The most common serotypes found in IPD, non-IPD, and carriage in ASEAN are covered by currently available conjugate vaccines. This underscores the importance of vaccination and predicts future success in reducing the burden of pneumococcal disease. The data gathered offers important insights into pneumococcal serotype epidemiology across the different countries belonging to ASEAN.
CRISPR-Cas9 knockdown of ESR1 in preoptic GABA-kisspeptin neurons suppresses the preovulatory surge and estrous cycles in female mice
Authors: Clarkson Jenny , Yip Siew Hoong , Porteous Robert , Kauff Alexia , Heather Alison K. , Herbison Allan E.
Published: July 2023

Evidence suggests that estradiol-sensing preoptic area GABA neurons are involved in the pre-ovulatory surge mechanism necessary for ovulation. In vivo CRISPR-Cas9 editing was used to achieve a 60-70% knockdown in estrogen receptor alpha (ESR1) expression by GABA neurons located within the region of the rostral periventricular of the third ventricle (RP3V) and medial preoptic nuclei (MPN) in adult female mice. Mice exhibited variable reproductive phenotypes with the only significant finding being those mice with bilateral ESR1 deletion in RP3V GABA neurons that had reduced cFos expression in GnRH neurons at the time of the surge. One sub-population of RP3V GABA neurons expresses kisspeptin. Re-grouping ESR1-edited mice on the basis of their RP3V kisspeptin expression revealed a highly consistent phenotype; mice with a near complete loss of kisspeptin immunoreactivity displayed constant estrus and failed to exhibit surge activation but retained pulsatile LH secretion. These observations demonstrate ESR1-expressing GABA-kisspeptin neurons in the RP3V are essential for the murine preovulatory LH surge mechanism.
Contrasting roles of different mismatch repair proteins in basal-like breast cancer
Authors: Tithi Tanzia Islam , Mo Jiao , Borcherding Nicholas , Jo Sung , Cho Edward , Cash Kailey E. , Honda Masayoshi , Wang Lei , Ahmed Kawther K. , Shirlekar Kalyanee , Chen Li , Weigel Ronald , Kates Heather , Gibson-Corley Katherine , Spies Maria , kolb Ryan , Zhang Weizhou
Published: July 2023

The mismatch repair (MMR) pathway is known as a tumor suppressive pathway and genes involved in MMR are commonly mutated in hereditary colorectal or other cancer types. However, the function of MMR genes/proteins in breast cancer progression and metastasis are largely undefined. We found that MSH2, but not MLH1, is highly enriched in basal-like breast cancer (BLBC) and that its protein expression is inversely correlated with overall survival time (OS). MSH2 expression is frequently elevated due to genomic amplification or gain-of-expression in BLBC, which results in increased MSH2 protein to pair with MSH6 (collectively referred to as MutSalpha). Genetic deletion of MSH2 or MLH1 results in a contrasting phenotype in metastasis, with MSH2-deletion leading to reduced metastasis and MLH1-deletion to enhanced liver or lung metastasis. Mechanistically, MSH2, but not MLH1, binds to the promoter region of interferon alpha receptor 1 (IFNAR1) and suppresses its expression in BLBC. Deletion of MSH2 initiates a chain of immune reactions via the upregulation of IFNAR1 expression and the activation of type 1 interferon signaling, which explains a highly immune active tumor microenvironment in tumors with MSH2-deficiency. Our study supports the contrasting functions of MSH2 and MLH1 in BLBC progression and metastasis due to the differential regulation of IFNAR1 expression, which challenges the paradigm of the MMR pathway as a universal tumor suppressive mechanism.
PseudoCell: A Multi-Valued Logical Regulatory Network to Investigate Premature Senescence Dynamics and Heterogeneity
Authors: Pierdoná Vinícius , Lavandoski Patrícia , Maurmann Rafael Moura , Borges Guilherme Antônio , Mombach Jose Carlos Merino , Guma Fátima Theresinha Costa Rodrigues , Barbé-Tuana Florencia María
Published: July 2023

Premature cellular senescence is a pivotal process in aging and age-related diseases, triggered by various stressors. However, this is not a homogeneous phenotype, but a heterogeneous cellular state composed of multiple senescence programs with different compositions. Therefore, understanding the complex dynamics of senescence programs requires a systemic approach. We introduce PseudoCell, a multi-valued logical regulatory network designed to explore the molecular intricacies of premature senescence. PseudoCell integrates key senescence signaling pathways and molecular mechanisms, offering a versatile platform for investigating diverse premature senescence programs initiated by different stimuli. Validation through simulation of classical senescence programs, including oxidative stress-induced senescence (OSIS) and oncogene-induced senescence (OIS), demonstrates its ability to replicate molecular signatures consistent with empirical data. Additionally, we explore the role of CCL11, a novel senescence-associated molecule, through simulations that reveal potential pathways and mechanisms underlying CCL11-mediated senescence induction. In conclusion, PseudoCell provides a systematic approach to dissecting premature senescence programs and uncovering novel regulatory mechanisms.
A Motion Transformer for Single Particle Tracking in Fluorescence Microscopy Images
Authors: Zhang Yudong , Yang Ge
Published: July 2023

Single particle tracking is an important image analysis technique widely used in biomedical sciences to follow the movement of sub-cellular structures, which typically appear as individual particles in fluorescence microscopy images. In practice, the low signal-to-noise ratio (SNR) of fluorescence microscopy images as well as the high density and complex movement of subcellular structures pose substantial technical challenges for accurate and robust tracking. In this paper, we propose a novel Transformer-based single particle tracking method called Motion Transformer Tracker (MoTT). By using its attention mechanism to learn complex particle behaviors from past and hypothetical future tracklets (i.e., fragments of trajectories), MoTT estimates the matching probabilities between each live/established tracklet and its multiple hypothesis tracklets simultaneously, as well as the existence probability and position of each live tracklet. Global optimization is then used to find the overall best matching for all live tracklets. For those tracklets with high existence probabilities but missing detections due to e.g., low SNRs, MoTT utilizes its estimated particle positions to substitute for the missed detections, a strategy we refer to as relinking in this study. Experiments have confirmed that this strategy substantially alleviates the impact of missed detections and enhances the robustness of our tracking method. Overall, our method substantially outperforms competing state-of-the-art methods on the ISBI Particle Tracking Challenge datasets. It provides a powerful tool for studying the complex spatiotemporal behavior of subcellular structures. The source code is publicly available athttps://github.com/imzhangyd/MoTT.git.
Charting cellular differentiation trajectories with Ricci flow
Authors: Baptista Anthony , MacArthur Ben D. , Banerji Christopher R. S.
Published: July 2023

Complex biological processes, such as cellular differentiation, require an intricate rewiring of intra-cellular signalling networks. Previous characterisations of these networks revealed that promiscuity in signalling, quantified by a raised network entropy, underlies a less differentiated and malignant cell state. A theoretical connection between entropy and Ricci curvature has led to applications of discrete curvatures to characterise biological signalling networks at distinct time points during differentiation and malignancy. However, understanding and predicting the dynamics of biological network rewiring remains an open problem. Here we construct a framework to apply discrete Ricci curvature and Ricci flow to the problem of biological network rewiring. By investigating the relationship between network entropy and Forman-Ricci curvature, both theoretically and empirically on single-cell RNA-sequencing data, we demonstrate that the two measures do not always positively correlate, as has been previously suggested, and provide complementary rather than interchangeable information. We next employ discrete normalised Ricci flow, to derive network rewiring trajectories from transcriptomes of stem cells to differentiated cells, which accurately predict true intermediate time points of gene expression time courses. In summary, we present a differential geometry toolkit for investigation of dynamic network rewiring during cellular differentiation and cancer.
Dermonecrosis caused by spitting cobra snakebite results from toxin potentiation and is prevented by the repurposed drug varespladib
Authors: Bartlett Keirah E. , Hall Steven R. , Rasmussen Sean A. , Crittenden Edouard , Dawson Charlotte A. , Albulescu Laura-Oana , Laprade William , Harrison Robert A. , Saviola Anthony J. , Modahl Cassandra M. , Jenkins Timothy P. , Wilkinson Mark C. , Gutiérrez José María , Casewell Nicholas R.
Published: July 2023

Snakebite envenoming is a neglected tropical disease that causes substantial mortality and morbidity globally. The venom of African spitting cobras often causes permanent injury via tissue-destructive dermonecrosis at the bite site, which is ineffectively treated by current antivenoms. To address this therapeutic gap, we identified the aetiological venom toxins responsible for causing local dermonecrosis. While cytotoxic three-finger toxins were primarily responsible for causing spitting cobra cytotoxicity in cultured keratinocytes, their potentiation by phospholipases A2toxins was essential to cause dermonecrosisin vivo. This evidence of probable toxin synergism suggests that a single toxin-family inhibiting drug could prevent local envenoming. We show that local injection with the repurposed phospholipase A2-inhibiting drug varespladib significantly prevents local tissue damage caused by several spitting cobra venoms in murine models of envenoming. Our findings therefore provide a new therapeutic strategy to more effectively prevent life-changing morbidity caused by snakebite in rural Africa.

Significance Statement

Spitting cobra venoms cause extensive local tissue damage surrounding the site of a snakebite. This damage cannot be effectively prevented with current antivenom treatments, and patients are often left with life-changing wounds. In this study we used cellular and mouse experiments to determine which toxins in African spitting cobra venom are responsible for causing tissue damage, revealing that a combination of two different types of toxins are required to cause pathologyin vivo. We then showed that the repurposed drug, varespladib, which targets one of these toxin types, effectively prevents skin and muscle damage in mouse models of envenoming. Collectively these findings suggest that varespladib could be an effective new type of therapy for preventing snakebite morbidity in Africa.
PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements
Authors: Parizi Farzaneh M. , Marzella Dario F. , Ramakrishnan Gayatri , ‘t Hoen Peter A. C. , Karimi-Jafari Mohammad Hossein , Xue Li C
Published: July 2023

T-cell specificity to differentiate between self and non-self relies on T-cell receptor (TCR) recognition of peptides presented by the Major Histocompatibility Complex (MHC). Investigations into the three-dimensional (3D) structures of peptide:MHC (pMHC) complexes have provided valuable insights of MHC functions. Given the limited availability of experimental pMHC structures and considerable diversity of peptides and MHC alleles, it calls for the development of efficient and reliable computational approaches for modeling pMHC structures. Here we present an update of PANDORA and the systematic evaluation of its performance in modelling 3D structures of pMHC class II complexes (pMHC-II), which play a key role in the cancer immune response. PANDORA is a modelling software that can build low-energy models in a few minutes by restraining peptide residues inside the MHC-II binding groove. We benchmarked PANDORA on 136 experimentally determined pMHC-II structures covering 44 unique αβ chain pairs. Our pipeline achieves a median backbone Ligand-Root Mean Squared Deviation (L-RMSD) of 0.42 Å on the binding core and 0.88 Å on the whole peptide for the benchmark dataset. We incorporated software improvements to make PANDORA a pan-allele framework and improved the user interface and software quality. Its computational efficiency allows enriching the wealth of pMHC binding affinity and mass spectrometry data with 3D models. These models can be used as a starting point for molecular dynamics simulations or structure-boosted deep learning algorithms to identify MHC-binding peptides. PANDORA is available as a Python package through Conda or as a source installation athttps://github.com/X-lab-3D/PANDORA.
Efficient protein structure archiving using ProteStAr
Authors: Deorowicz Sebastian , Gudyś Adam
Published: July 2023

Motivation

The introduction of Deep Minds’ Alpha Fold 2 enabled prediction of protein structures at unprecedented scale. AlphaFold Protein Structure Database and ESM Metagenomic Atlas contain hundreds of millions of structures stored in CIF and/or PDB formats. When compressed with a general-purpose utility like gzip, this translates to tens of terabytes of data which hinders the effective use of predicted structures in large-scale analyses.

Results

Here, we present ProteStAr, a compressor dedicated to CIF/PDB as well as, supplementary PAE files. Its main contribution is a novel approach to predict atom coordinates on the basis of the previously analyzed atoms. This allows efficient encoding of the coordinates which are the largest component of the protein structure files. By default, the compression is lossless, though the lossy mode with a controlled maximum error of coordinates reconstruction is also present. Compared to the competing packages, i.e., BinaryCIF, Foldcomp, PDC, our approach offers superior compression ratio at established reconstruction accuracy. By the efficient use of threads at both compression and decompression stages, the algorithm takes advantage of multicore architecture of current central processing units and operates with speeds about 1 GB/s. The presence of C++ API further increases the usability of the presented method.

Availability and implementation

The source code of ProteStAr is available athttps://github.com/refresh-bio/protestar.
Identifying Clusters in Graph Representations of Genomes
Authors: Herencsárová Eva , Brejová Broňa
Published: July 2023

In many bioinformatics applications the task is to identify biologically significant locations in an individual genome. In our work, we are interested in finding high-density clusters of such biologically meaningful locations in a graph representation of a pangenome, which is a collection of related genomes. Different formulations of finding such clusters were previously studied for sequences. In this work, we study an extension of this problem for graphs, which we formalize as finding a set of vertex-disjoint paths with a maximum score in a weighted directed graph. We provide a linear-time algorithm for a special class of graphs corresponding to elastic-degenerate strings, one of pangenome representations. We also provide a fixed-parameter tractable algorithm for directed acyclic graphs with a special path decomposition of a limited width.
FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines
Authors: Winchell Jeff , Comolet Gabriel , Buckley-Herd Geoff , Hutson Dillion , Bose Neeloy , Paull Daniel , Migliori Bianca
Published: July 2023

The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potential of automation will thus require the design of robust analysis pipelines that span the entire workflow in question. Here we present FocA, a deep learning tool that, in near real-time, identifies in-focus and out-of-focus images generated on a fully automated cell biology research platform, the NYSCF Global Stem Cell Array®. The tool is trained on small patches of downsampled images to maximize computational efficiency without compromising accuracy, and optimized to make sure no sub-quality images are stored and used in downstream analyses. The tool automatically generates balanced and maximally diverse training sets to avoid bias. The resulting model correctly identifies 100% of out-of-focus and 98% of in-focus images in under 4 seconds per 96-well plate, and achieves this result even in heavily downsampled data (∼30 times smaller than native resolution). Integrating the tool into automated workflows minimizes the need for human verification as well as the collection and usage of low-quality data. FocA thus offers a solution to ensure reliable image data hygiene and improve the efficiency of automated imaging workflows using minimal computational resources.
Voyager: exploratory single-cell genomics data analysis with geospatial statistics
Authors: Moses Lambda , Einarsson Pétur Helgi , Jackson Kayla , Luebbert Laura , Booeshaghi A. Sina , Antonsson Sindri , Bray Nicolas , Melsted Páll , Pachter Lior
Published: July 2023

Exploratory spatial data analysis (ESDA) can be a powerful approach to understanding single-cell genomics datasets, but it is not yet part of standard data analysis workflows. In particular, geospatial analyses, which have been developed and refined for decades, have yet to be fully adapted and applied to spatial single-cell analysis. We introduce the Voyager platform, which systematically brings the geospatial ESDA tradition to (spatial) -omics, with local, bivariate, and multivariate spatial methods not yet commonly applied to spatial -omics, united by a uniform user interface. Using Voyager, we showcase biological insights that can be derived with its methods, such as biologically relevant negative spatial autocorrelation. Underlying Voyager is the SpatialFeatureExperiment data structure, which combines Simple Feature with SingleCellExperiment and AnnData to represent and operate on geometries bundled with gene expression data. Voyager has comprehensive tutorials demonstrating ESDA built on GitHub Actions to ensure reproducibility and scalability, using data from popular commercial technologies. Voyager is implemented in both R/Bioconductor and Python/PyPI, and features compatibility tests to ensure that both implementations return consistent results.
BuDDI:Bulk Deconvolution with Domain Invarianceto predict cell-type-specific perturbations from bulk
Authors: Davidson Natalie R. , Zhang Fan , Greene Casey S.
Published: July 2023

While single-cell experiments provide deep cellular resolution within a single sample, some single-cell experiments are inherently more challenging than bulk experiments due to dissociation difficulties, cost, or limited tissue availability. This creates a situation where we have deep cellular profiles of one sample or condition, and bulk profiles across multiple samples and conditions. To bridge this gap, we propose BuDDI (BUlk Deconvolution with Domain Invariance). BuDDI utilizes domain adaptation techniques to effectively integrate available corpora of case-control bulk and reference scRNA-seq observations to infer cell-type-specific perturbation effects. BuDDI achieves this by learning independent latent spaces within a single variational autoencoder (VAE) encompassing at least four sources of variability: 1) cell type proportion, 2) perturbation effect, 3) structured experimental variability, and 4) remaining variability. Since each latent space is encouraged to be independent, we simulate perturbation responses by independently composing each latent space to simulate cell-type-specific perturbation responses.

We evaluated BuDDI’s performance on simulated and real data with experimental designs of increasing complexity. We first validated that BuDDI could learn domain invariant latent spaces on data with matched samples across each source of variability. Then we validated that BuDDI could accurately predict cell-type-specific perturbation response when no single-cell perturbed profiles were used during training; instead, only bulk samples had both perturbed and non-perturbed observations. Finally, we validated BuDDI on predicting sex-specific differences, an experimental design where it is not possible to have matched samples. In each experiment, BuDDI outperformed all other comparative methods and baselines. As more reference atlases are completed, BuDDI provides a path to combine these resources with bulk-profiled treatment or disease signatures to study perturbations, sex differences, or other factors at single-cell resolution.
Predicting gene expression changes upon epigenomic drug treatment
Authors: Agrawal Piyush , Gopalan Vishaka , Hannenhalli Sridhar
Published: July 2023

Background

Tumors are characterized by global changes in epigenetic changes such as DNA methylation and histone modifications that are functionally linked to tumor progression. Accordingly, several drugs targeting the epigenome have been proposed for cancer therapy, notably, histone deacetylase inhibitors (HDACi) such asVorinostatisand DNA methyltransferase inhibitors (DNMTi) such asZebularine. However, a fundamental challenge with such approaches is the lack of genomic specificity, i.e., the transcriptional changes at different genomic loci can be highly variable thus making it difficult to predict the consequences on the global transcriptome and drug response. For instance, treatment with DNMTi may upregulate the expression of not only a tumor suppressor but also an oncogene leading to unintended adverse effect.

Methods

Given the pre-treatment transcriptome and epigenomic profile of a sample, we assessed the extent of predictability of locus-specific changes in gene expression upon treatment with HDACi using machine learning.

Results

We found that in two cell lines (HCT116 treated with Largazole at 8 doses and RH4 treated with Entinostat at 1µM) where the appropriate data (pre-treatment transcriptome and epigenome as well as post-treatment transcriptome) is available, our model distinguished the post-treatment up versus downregulated genes with high accuracy (up to ROC of 0.89). Furthermore, a model trained on one cell line is applicable to another cell line suggesting generalizability of the model.

Conclusions

Here we present a first assessment of the predictability of genome-wide transcriptomic changes upon treatment with HDACi. Lack of appropriate omics data from clinical trials of epigenetic drugs currently hampers the assessment of applicability of our approach in clinical setting.
The relationships between experimental task and questionnaire measures of reward/punishment sensitivity in attention deficit hyperactivity disorder (ADHD): protocol for a scoping review
Authors: Oguchi Mana , Furukawa Emi , Nagahama Naano , Perera Kokila Dilhani , Tripp Gail
Published: July 2023

Introduction

One of the purported underlying causal mechanisms of attention deficit hyperactivity disorder (ADHD) is altered motivational processes. Questionnaires have been used to identify the characteristics of reward and punishment sensitivity in individuals with ADHD. However, these questionnaires were initially developed to measure individual traits related to anxiety (inhibitory) and impulsivity (approach) tendencies or differences in pleasure-seeking. These reward and punishment sensitivity questionnaires are useful but might not capture all relevant aspects of altered motivational processes in ADHD. The proposed scoping review aims to: 1) examine which aspects of hypothesized altered reward and punishment sensitivity correspond to constructs measured by existing questionnaires, 2) characterize the relationships between ADHD symptomatology and reward and punishment sensitivity as measured by existing questionnaires, and 3) evaluate the consistency between the altered reward and punishment sensitivity as measured by existing questionnaires and experimental task performance.

Methods and analysis

This scoping review will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews and the Joanna Briggs Methodology for Scoping Reviews. Published English language literature will be searched in three electronic databases, with no restriction on the year of publication. Two researchers will independently screen all identified titles/abstracts and review the method sections of the identified papers to confirm their eligibility before proceeding to full-text review and data extraction. Methods, results, and conclusions will be tabulated by research questions. A narrative review, and summary conclusions will be presented. The evidence will be summarized as descriptive data in the Excel table.

Ethics and dissemination

This study reviews existing publications with ethical approval in place. Therefore, ethical approval is not required. Review results will be disseminated through academic conferences and peer-reviewed manuscripts. Scoping review results will also inform future research to measure and identify altered motivational processes in ADHD.

Strengths and limitations of this study

This scoping review is the first study to identify which aspects of ADHD reinforcement sensitivity have been measured by existing reward and punishment scales and comprehensively review studies reporting relationships between experimental task results and reward and punishment scales in ADHD. (strengths)

This study will be conducted according to PRISMA guidelines for systematic reviews. (strength)

Results will be summarized separately for children/adolescents and adults. (strength)

This review includes only published peer-reviewed English language studies. (limitation)
The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis
Authors: Smeland Olav B. , Kutrolli Gleda , Bahrami Shahram , Fominykh Vera , Parker Nadine , Hindley Guy F. L. , Rødevand Linn , Jaholkowski Piotr , Tesfaye Markos , Parekh Pravesh , Elvsåshagen Torbjørn , Grotzinger Andrew D. ,   The International Multiple Sclerosis Genetics Consortium (IMSGC),   The International Headache Genetics Consortium (IHGC), Steen Nils Eiel , der Meer Dennis van , O’Connell Kevin S. , Djurovic Srdjan , Dale Anders M. , Shadrin Alexey A. , Frei Oleksandr , Andreassen Ole A.
Published: July 2023

While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.
Mucosal and Systemic Immune Correlates of Viral Control following SARS-CoV-2 Infection Challenge in Seronegative Adults
Authors: Wagstaffe Helen R. , Thwaites Ryan S. , Reynaldi Arnold , Sidhu Jasmin K. , McKendry Richard , Ascough Stephanie , Papargyris Loukas , Collins Ashley M. , Xu Jiayun , Lemm Nana-Marie , Siggins Matthew K. , Chain Benny M. , Killingley Ben , Kalinova Mariya , Mann Alex , Catchpole Andrew , Davenport Miles P. , Openshaw Peter J.M. , Chiu Christopher
Published: July 2023

Human infection challenge permits characterisation of the associated immune response in unparalleled depth, enabling evaluation of early pre-symptomatic immune changes and the dynamic immune factors important for viral clearance. Here, 34 healthy young adult volunteers, seronegative to SARS-CoV-2, were inoculated with a D614G-containing pre-Alpha SARS-CoV-2 strain. Nasal and systemic soluble mediator and antibody responses, and peripheral blood T cell and B cell responses were measured by MesoScale Discovery and flow cytometry just before and up to 1 year after intra-nasal inoculation. In the 18 (53%) participants who became infected, both nasal and systemic mediator responses were dominated by interferons (IFN) but with divergent kinetics. T cell activation and proliferation in blood peaked at day 10 in CD4+T cells and day 14 in CD8+T cells, returning to baseline by day 28. Following infection, antigen-specific T cells were largely CD38+Ki67+and displayed central and effector memory phenotypes. T cells contracted after viral clearance with expanded antigen-specific memory T cell populations persisting past day 28. Both mucosal and systemic antibodies became detectable around day 10 but nasal antibodies plateaued after day 14 while circulating antibodies continued to rise. Using piecewise linear regression modelling, viral load related closely to the induction of type I IFN responses, moreover, CD8+T cell responses and early IgA responses were strongly associated with viral clearance. Detailed analysis of innate and adaptive immune responses to primary SARS-CoV-2 infection following human challenge thus revealed the relationship between immune kinetics and viral load as factors associated with resolution of infection.
Unraveling COVID-19 Relationship with Anxiety Disorders and Symptoms
Authors: Asgel Zeynep , Kouakou Manuela R. , Koller Dora , Pathak Gita A. , Cabrera-Mendoza Brenda , Polimanti Renato
Published: July 2023

Background

While COVID-19 outcomes are associated with increased anxiety, individuals affected by anxiety disorders are more likely to develop severe COVID-19 outcomes.

Methods

We used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls) to investigate possible causal effects and shared genetic mechanisms linking COVID-19 outcomes to anxiety disorders and symptoms.

Results

We observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg=0.35, p=2 × 10-4) and COVID-19 hospitalization (rg=0.31, p=7.2 × 10-4). Among anxiety symptoms, “Tense, sore, or aching muscles during worst period of anxiety” was genetically correlated with COVID-19 positive status (rg=0.33, p=0.001), while “Frequent trouble falling or staying asleep during worst period of anxiety” was genetically correlated with COVID-19 hospitalization (rg=0.24, p=0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status→“Recent easy annoyance or irritability” │gcp│=0.18, p=6.72 × 10-17). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 (│gcp│=0.38, p=3.17 × 10-9). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters.

Conclusions

This study provided important insights into the relationship between COVID-19 and mental health, differentiating the dynamics linking anxiety disorders to COVID-19 from the effect of COVID-19 on anxiety symptoms.