bluuebunny/crossref_metadata_2025 huggingface dataset:
Distinct 3D contacts and phenotypic consequences of adjacent non-coding loci in the epigenetically quiescent regions
Authors: Wu Peiyao , Wang Wei
Published: September 2023

Non-coding regions of the human genome are important for functional regulations, but their mechanisms remain elusive. We used machine learning to guide a CRISPR screening on hubs (i.e. non-coding loci forming many 3D contacts) and significantly increased the discovery rate of hubs essential for cell growth. We found no clear genetic or epigenetic differences between essential and nonessential hubs, but we observed that some neighboring hubs in the linear genome have distinct spatial contacts and opposite effects on cell growth. One such pair in an epigenetically quiescent region showed different impacts on gene expression, chromatin accessibility and chromatin organization. We also found that deleting the essential hub altered the genetic network activity and increased the entropy of chromatin accessibility, more severe than that caused by deletion of the nonessential hub, suggesting that they are critical for maintaining an ordered chromatin structure. Our study reveals new insights into the system-level roles of non-coding regions in the human genome.
Adaptive multipole models of OPM data
Authors: Tierney Tim M , Seedat Zelekha , Pier Kelly St. , Mellor Stephanie , Barnes Gareth R
Published: September 2023

Multipole expansions have been used extensively in the Magnetoencephalography (MEG) literature for mitigating environmental interference and modelling brain signal. However, their application to Optically Pumped Magnetometer (OPM) data is challenging due to the wide variety of existing OPM sensor and array designs. We therefore explore how such multipole models can be adapted to provide stable models of brain signal and interference across OPM systems. Firstly, we demonstrate how prolate spheroidal (rather than spherical) harmonics can provide a compact representation of brain signal when sampling on the scalp surface with as few as 100 channels. We then introduce a type of orthogonal projection incorporating this basis set, the Adaptive Multipole Models (AMM), which provides robust interference rejection across systems, even in the presence of spatially structured nonlinearity errors. This projection is always stable, as it is an orthogonal projection, and will only ever decrease the white noise in the data. However, for array designs that are suboptimal for spatially separating brain signal and interference, this method can remove brain signal components. We contrast these properties with the more typically used multipole expansion, Signal Space Separation (SSS), which never reduces brain signal amplitude but is less robust to the effect of sensor nonlinearity errors on interference rejection and can increase noise in the data if the system is sub-optimally designed (as it is an oblique projection). We conclude with an empirical example utilizing AMM to maximize signal to noise ratio (SNR) for the stimulus locked neuronal response to a flickering visual checkerboard in a 128-channel OPM system and demonstrate up to 40dB software shielding in real data.
Retracing Human Genetic Histories and Natural Selection Using Precise Local Ancestry Inference
Authors: Lerga-Jaso Jon , Novković Biljana , Unnikrishnan Deepu , Bamunusinghe Varuna , Hatorangan Marcelinus R. , Manson Charlie , Pedersen Haley , Osama Alex , Terpolovsky Andrew , Bohn Sandra , De Marino Adriano , Mahmoud Abdallah A. , Bircan Karatuğ O. , Khan Umar , Grabherr Manfred G. , Yazdi Puya G.
Published: September 2023

In an increasingly diverse world, including admixed individuals in genomic studies is imperative for equity and portability. A crucial first step is precise local ancestry inference (LAI). We have developed Orchestra, a LAI model with unprecedented accuracy, and trained on over 10,000 single-origin individuals from 35 worldwide populations. We employed Orchestra to delve into genetic relationships and demographic histories, with a focus on Latin Americans, a prime example of admixture, and the Ashkenazi Jewish, whose origins have long been debated. Finally, Orchestra enabled us to map signatures of selection, notably identifying trace Scandinavian ancestry in British samples and unveiling an immune-rich region linked to respiratory infections. Our work advances the field of LAI and holds promise for improvements in future applications for admixed populations.

One-Sentence Summary

Orchestra unveils Latino and Ashkenazi ancestral roots and a candidate Viking locus under selection in the British population
Programmed Cell Death Modifies Neural Circuits and Tunes Intrinsic Behavior
Authors: Kochersberger Alison , Torkashvand Mohammad Mahdi , Lee Dongyeop , Baskoylu Saba , Sengupta Titas , Koonce Noelle , Emerson Chloe E. , Patel Nandan V. , Colón-Ramos Daniel , Flavell Steven , Horvitz H. Robert , Venkatachalam Vivek , Hammarlund Marc
Published: September 2023

Programmed cell death is a common feature of animal development. During development of theC. eleganshermaphrodite, programmed cell death (PCD) removes 131 cells from stereotyped positions in the cell lineage, mostly in neuronal lineages. Blocking cell death results in supernumerary “undead” neurons. We find that undead neurons can be wired into circuits, can display activity, and can modify specific behaviors. The two undead RIM-like neurons participate in the RIM-containing circuit that computes movement. The addition of these two extra neurons results in animals that initiate fewer reversals and lengthens the duration of those reversals that do occur. We describe additional behavioral alterations of cell-death mutants, including in turning angle and pharyngeal pumping. These findings reveal that, like too much PCD, too little PCD can modify nervous system function and animal behavior.
Effectiveness of Canadian travel restrictions in reducing burden of SARS-CoV-2 variants of concern
Authors: McLaughlin Angela , Montoya Vincent , Miller Rachel L. ,   Canadian COVID-19 Genomics Network (CanCOGeN) Consortium, Worobey Michael , Joy Jeffrey B.
Published: September 2023

Evaluating travel restriction effectiveness in mitigating infectious disease burden is critical for informing public health policy. Here, we quantify where and when variants of SARS-CoV-2 were introduced into Canada to evaluate the extent to which travel restrictions averted viral introductions and COVID-19 case burden. Our results suggest that, across SARS-CoV-2 variants of concern subject to travel restrictions, at least 281 introductions were prevented, accounting for an averted burden of approximately 44,064 cases. This corresponds to approximately 441 averted hospitalizations, 24 averted deaths, and cost savings to Canadian health care systems of approximately 11.2 million Canadian dollars. Travel restrictions were found to be most effective when implemented rapidly during exponential case growth in the focal source and when global circulation was limited. Our analyses reveal that COVID-19 travel restrictions mitigated case burdens and highlight their value in future pandemic response.

COVID-19 travel restrictions against variants worked and were most effective when implemented rapidly and preceding new variants’ wider circulation.
Determinants of SARS-CoV-2 IgG response and decay in Canadian healthcare workers: a prospective cohort study
Authors: Cherry Nicola , Adisesh Anil , Burstyn Igor , Charlton Carmen , Chen Yan , Durand-Moreau Quentin , Labrèche France , Ruzycki Shannon , Turnbull LeeAnn , Zadunayski Tanis , Yasui Yutaka
Published: September 2023

Introduction

Healthcare workers (HCWs) from an interprovincial Canadian cohort were asked to give serial blood samples to identify factors associated with anti-receptor binding domain (anti-RBD) IgG response to the SARS-CoV-2 virus.

Methods

Members of the HCW cohort donated blood samples four months after their first SARS-CoV-2 immunization and again at 7, 10 and 13 months. Date and type of immunizations and dates of SARS-CoV-2 infection were collected at each of four contacts, together with information on immunologically-compromising conditions and current therapies. Blood samples were analyzed centrally for anti-RBD IgG and anti-nucleocapsid IgG (Abbott Architect, Abbott Diagnostics). Records of immunization and SARS-CoV-2 testing from public health agencies were used to assess the impact of reporting errors on estimates from the random-effects multivariable model fitted to the data.

Results

2752 of 4567 vaccinated cohort participants agreed to donate at least one blood sample. Modelling of anti-RBD IgG titer from 8903 samples showed an increase in IgG with each vaccine dose and with first infection. A decrease in IgG titer was found with the number of months since vaccination or infection, with the sharpest decline after the third dose. An immunization regime that included mRNA1273 (Moderna) resulted in higher anti-RBD IgG. Participants reporting multiple sclerosis, rheumatoid arthritis or taking selective immunosuppressants, tumor necrosis factor inhibitors, calcineurin inhibitors and antineoplastic agents had lower anti-RBD IgG. Supplementary analyses showed higher anti-RBD IgG in those reporting side-effects of vaccination, no relation of anti-RBD IgG to obesity and lower titers in women immunized early in pregnancy. Sensitivity analysis results suggested no important bias in the self-report data.

Conclusion

Creation of a prospective cohort was central to the credibility of results presented here. Serial serology assessments, with longitudinal analysis, provided effect estimates with enhanced accuracy and a clearer understanding of medical and other factors affecting response to vaccination.
Identification of Cancer Risk Groups through Multi-Omics Integration using Autoencoder and Tensor Analysis
Authors: Braytee Ali , He Sam , Tang Shuxian , Sun Yuxuan , Jiang Xiaoying , Yu Xuanding , Khatri Inder , Prasad Mukesh , Anaissi Ali
Published: September 2023

Identifying cancer risk groups by integrative multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes an integrative multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients’ risk groups using genomics.

Additional Key Words and Phrases: Multi-omics, Autoencoders, Tensors, Cancer risk groups
Functional connectome through the human life span
Authors: Sun Lianglong , Zhao Tengda , Liang Xinyuan , Xia Mingrui , Li Qiongling , Liao Xuhong , Gong Gaolang , Wang Qian , Pang Chenxuan , Yu Qian , Bi Yanchao , Chen Pindong , Chen Rui , Chen Yuan , Chen Taolin , Cheng Jingliang , Cheng Yuqi , Cui Zaixu , Dai Zhengjia , Deng Yao , Ding Yuyin , Dong Qi , Duan Dingna , Gao Jia-Hong , Gong Qiyong , Han Ying , Han Zaizhu , Huang Chu-Chung , Huang Ruiwang , Huo Ran , Li Lingjiang , Lin Ching-Po , Lin Qixiang , Liu Bangshan , Liu Chao , Liu Ningyu , Liu Ying , Liu Yong , Lu Jing , Ma Leilei , Men Weiwei , Qin Shaozheng , Qiu Jiang , Qiu Shijun , Si Tianmei , Tan Shuping , Tang Yanqing , Tao Sha , Wang Dawei , Wang Fei , Wang Jiali , Wang Pan , Wang Xiaoqin , Wang Yanpei , Wei Dongtao , Wu Yankun , Xie Peng , Xu Xiufeng , Xu Yuehua , Xu Zhilei , Yang Liyuan , Yuan Huishu , Zeng Zilong , Zhang Haibo , Zhang Xi , Zhao Gai , Zheng Yanting , Zhong Suyu ,   Alzheimer’s Disease Neuroimaging Initiative,   Cam-CAN,   Developing Human Connectome Project,   DIDA-MDD Working Group,   MCADI,   NSPN, He Yong
Published: September 2023

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer’s disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.
An interchange property for the rooted Phylogenetic Subnet Diversity on phylogenetic networks
Authors: Coronado Tomás M. , Riera Gabriel , Rosselló Francesc
Published: September 2023

Faith’s Phylogenetic Diversity (PD) on rooted phylogenetic trees satisfies the so-called strong exchange property that guarantees that, for every two sets of leaves of different cardinalities, a leaf can always be moved from the largest set to the smallest in such a way that the sum of the PD values does not decrease. This strong exchange property entails a simple polynomial-time greedy solution to the PD optimization problem on rooted phylogenetic trees. In this paper we obtain an exchange property for the rooted Phylogenetic Subnet Diversity (rPSD) on rooted phylogenetic networks of bounded level and reticulations’ in-degree, which involves a more complicated interchange of leaves. We derive from it a polynomial-time greedy solution to the rPSD optimization problem on rooted semibinary level-2 phylogenetic networks.
Lipid peroxidation drives liquid-liquid phase separation and disrupts raft protein partitioning in biological membranes
Authors: Balakrishnan Muthuraj , Kenworthy Anne K.
Published: September 2023

The peroxidation of membrane lipids by free radicals contributes to aging, numerous diseases, and ferroptosis, an iron-dependent form of cell death. Peroxidation changes the structure, conformation and physicochemical properties of lipids, leading to major membrane alterations including bilayer thinning, altered fluidity, and increased permeability. Whether and how lipid peroxidation impacts the lateral organization of proteins and lipids in biological membranes, however, remains poorly understood. Here, we employ cell-derived giant plasma membrane vesicles (GPMVs) as a model to investigate the impact of lipid peroxidation on ordered membrane domains, often termed membrane rafts. We show that lipid peroxidation induced by the Fenton reaction dramatically enhances phase separation propensity of GPMVs into co-existing liquid ordered (raft) and liquid disordered (non-raft) domains and increases the relative abundance of the disordered, non-raft phase. Peroxidation also leads to preferential accumulation of peroxidized lipids and 4-hydroxynonenal (4-HNE) adducts in the disordered phase, decreased lipid packing in both raft and non-raft domains, and translocation of multiple classes of proteins out of rafts. These findings indicate that peroxidation of plasma membrane lipids disturbs many aspects of membrane rafts, including their stability, abundance, packing, and protein and lipid composition. We propose that these disruptions contribute to the pathological consequences of lipid peroxidation during aging and disease, and thus serve as potential targets for therapeutic intervention.
Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox
Authors: Schertzer Megan D. , Stirn Andrew , Isaev Keren , Pereira Laura , Das Anjali , Harbison Claire , Park Stella H. , Wessels Hans-Hermann , Sanjana Neville E. , Knowles David A.
Published: September 2023

Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5’ and 3’ splice sites, and alternative starts and ends.
Real-world gait and turning in individuals scheduled for total knee arthroplasty
Authors: Boekesteijn R.J. , Keijsers N.L.W. , Defoort K. , Mancini M. , Bruning F.J. , El-Gohary M. , Geurts A.C.H. , Smulders K.
Published: September 2023

Objective

To compare real-world gait and turning between individuals scheduled for total knee arthroplasty (TKA) and healthy controls, using continuous monitoring with inertial measurement units (IMUs).

Design

Real-world gait and turning data were collected for 5-7 days in individuals scheduled for TKA (n=34) and healthy controls in the same age range (n=32) using IMUs on the feet and lower back. Gait and turning parameters were compared between groups using a linear regression model. Data was further analyzed by stratification of gait bouts based on bout length, and turns based on turning angle and turning direction.

Results

Dominant real-world gait speed was 0.21 m/s lower in individuals scheduled for TKA compared to healthy controls. The between-group difference in gait speed was -0.10 m/s for bouts containing 0-10 strides and -0.15 m/s for bouts with 160+ strides. Stride time was 0.05 s higher in individuals scheduled for TKA. Step time asymmetry was not different between the groups. Regarding walking activity, individuals scheduled for TKA walked 72 strides/hour less than healthy controls, and maximum bout length was 316 strides shorter. Irrespective of the size of the turn, turning velocity was lower in individuals scheduled for TKA. Turning velocity did not differ between turns over the affected leg compared to the unaffected leg.

Conclusion

Individuals scheduled for TKA showed specific walking and turning limitations in the real-world. Parameters derived from IMUs reflected a rich profile of real-world mobility measures indicative of walking limitation of individuals scheduled for TKA, which may provide a relevant outcome dimension for future studies.
Adverse Long-Term Outcomes and an Immune Suppressed Endotype in Sepsis Patients with Reduced Interferon-γ ELISpot: A Multicenter, Prospective Observational Study
Authors: Barrios Evan A. , Mazer Monty B. , McGonagill Patrick , Bergmann Christian B. , Goodman Michael D. , Gould Robert W. , Rao Mahil , Polcz Valerie , Davis Ruth , Del Toro Drew , Dirain Marvin , Dram Alexandra , Hale Lucas , Heidarian Mohammad , Kucaba Tamara A. , Lanz Jennifer P. , McCray Ashley , Meszaros Sandra , Miles Sydney , Nelson Candace , Rocha Ivanna , Silva Elvia E , Ungaro Ricardo , Walton Andrew , Xu Julie , Zeumer-Spataro Leilani , Drewry Anne M. , Liang Muxuan , Bible Letitia E. , Loftus Tyler , Turnbull Isaiah , Efron Philip A. , Remy Kenneth E. , Brakenridge Scott , Badovinac Vladimir P. , Griffith Thomas S. , Moldawer Lyle L. , Hotchkiss Richard S. , Caldwell Charles C.
Published: September 2023

Background

Sepsis remains a major clinical challenge for which successful treatment requires greater precision in identifying patients at increased risk of adverse outcomes requiring different therapeutic approaches. Predicting clinical outcomes and immunological endotyping of septic patients has generally relied on using blood protein or mRNA biomarkers, or static cell phenotyping. Here, we sought to determine whether functional immune responsiveness would yield improved precision.

Methods

Anex vivowhole blood enzyme-linked immunosorbent (ELISpot) assay for cellular production of interferon-γ (IFN-γ) was evaluated in 107 septic and 68 non-septic patients from five academic health centers using blood samples collected on days 1, 4 and 7 following ICU admission.

Results

Compared with 46 healthy subjects, unstimulated and stimulated whole blood IFNγ expression were either increased or unchanged, respectively, in septic and nonseptic ICU patients. However, in septic patients who did not survive 180 days, stimulated whole blood IFNγ expression was significantly reduced on ICU days 1, 4 and 7 (all p<0.05), due to both significant reductions in total number of IFNγ−producing cells and amount of IFNγ produced per cell (all p<0.05). Importantly, IFNγ total expression on day 1 and 4 after admission could discriminate 180-day mortality better than absolute lymphocyte count (ALC), IL-6 and procalcitonin. Septic patients with low IFNγ expression were older and had lower ALC and higher sPD-L1 and IL-10 concentrations, consistent with an immune suppressed endotype.

Conclusions

A whole blood IFNγ ELISpot assay can both identify septic patients at increased risk of late mortality, and identify immune-suppressed, sepsis patients.

Trial Registry

Because the study is a prospective observational study, and not a clinical trial, registration withclinical trials.govis not required.
Yield of genetic association signals from genomes, exomes, and imputation in the UK biobank
Authors: Gaynor Sheila M. , Joseph Tyler , Bai Xiaodong , Krasheninina Olga , Boutkov Boris , Maxwell Evan , Balasubramanian Suganthi , Marcketta Anthony , Backman Joshua ,   Regeneron Genetics Center, Reid Jeffrey G. , Overton John D. , Lotta Luca A. , Marchini Jonathan , Salerno William J. , Baras Aris , Abecasis Goncalo R. , Thornton Timothy A.
Published: September 2023

Whole genome sequencing (WGS), whole exome sequencing (WES), and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date there has been no systematic empirical assessment of the yield of these approaches when applied to 100,000s of samples to enable discovery of complex trait genetic signals. Using data for 100 complex traits in 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES+IMP) have the largest association yield. While WGS results in a ∼5-fold increase in the total number of assayed variants over WES+IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Since WES+IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES+IMP to larger samples. When we extend our WES+IMP analyses to 468,169 UK Biobank individuals, we observe a ∼4-fold increase in association signals with the ∼3-fold increase in sample size. We conclude that prioritizing WES+IMP and large sample sizes, rather than current short-read WGS alternatives, will maximize the number of discoveries in genetic association studies.
Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations
Authors: Argentieri M. Austin , Xiao Sihao , Bennett Derrick , Winchester Laura , Nevado-Holgado Alejo J. , Albukhari Ashwag , Yao Pang , Mazidi Mohsen , Lv Jun , Li Liming , Adams Cassandra J. , Clarke Robert , Amin Najaf , Chen Zhengming , van Duijn Cornelia M.
Published: September 2023

Circulating plasma proteins play key roles in human health and could be used to measure biological aging to predict risk of mortality, disease, and multimorbidity beyond chronological age. We developed a proteomic age clock using 1,459 plasma proteins (Olink Explore) in two prospective biobanks in the UK (n=45,117) and China (n=2,026) and explored its utility to predict incident risk of 26 major age-related diseases and all-cause mortality. We identified 226 proteins that accurately predicted chronological age (Pearson r=0.92). Individuals in the top versus bottom deciles of accelerated proteomic aging differed by approximately 10 years of biological aging. In the UK population, accelerated proteomic aging was associated with 25 aging phenotypes (e.g., telomere length, IGF-1, creatinine, cystatin C, hand grip strength, cognitive function, frailty index), 18 chronic diseases (e.g., diseases of the heart, liver, kidneys, lungs; diabetes; neurodegeneration; cancers), multimorbidity, and all-cause mortality. In the smaller Chinese population, accelerated proteomic aging was associated with ischemic heart disease, stroke, and all-cause mortality. Our results demonstrate that plasma proteins are a reliable instrument for prediction of multiple common diseases in diverse populations and can be used as a robust biochemical aging signature to improve early detection and management of common diseases.
Conventional and unconventional T cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients
Authors: Burton Ross J. , Raffray Loïc , Moet Linda M. , Cuff Simone M. , White Daniel A. , Baker Sarah E. , Moser Bernhard , O’Donnell Valerie B. , Ghazal Peter , Morgan Matt P. , Artemiou Andreas , Eberl Matthias
Published: September 2023

Sepsis is characterised by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility to identify integrative patterns from clinical parameters, plasma biomarkers and extensive phenotyping of blood immune cells. Whilst no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90 day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90 day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical and clinical parameters.
Neonatal outcomes after maternal biomarker-guided preterm birth intervention: the AVERT PRETERM trial
Authors: Hoffman Matthew K. , Kitto Carrie , Zhang Zugui , Shi Jing , Walker Michael G. , Shahbaba Babak , Ruhstaller Kelly
Published: September 2023

The AVERT PRETERM trial (NCT03151330) evaluated whether screening clinically low-risk pregnancies with a validated maternal blood biomarker test for spontaneous preterm birth (sPTB) risk, followed by preventive treatments for those screening positive, would improve neonatal outcomes compared to a clinically low-risk historical population that had received usual care. Prospective arm participants with singleton non-anomalous pregnancies and no PTB history were tested for sPTB risk at 191/7-206/7weeks’ gestation and followed through neonatal discharge. Screen-positive individuals (≥16% sPTB risk) were offered vaginal progesterone (200 mg) and aspirin (81 mg) daily, with twice-weekly nurse phone calls. Co-primary outcomes were neonatal morbidity and mortality, measured using a validated composite index (NMI), and neonatal hospital length of stay (NNLOS). Endpoints were assessed using survival analysis and logistic regression in a modified intent-to-treat population comprising screen-negative individuals and screen-positive individuals accepting treatment. Of 1460 eligible participants, 34.7% screened positive; of these, 56.4% accepted interventions and 43.6% declined. Compared to historical controls, prospective arm neonates whose mothers accepted treatment had lower NMI scores (odds ratio 0.81, 95% CI, 0.67-0.98, P=0.03) and an 18% reduction in severe morbidity. NNLOS was shorter (hazard ratio 0.73, 95% CI, 0.58-0.92,P=0.01), with a 21% mean stay decrease among neonates having the longest stays. Sensitivity analyses of the entire intent-to-treat population supported these findings. These results suggest that biomarker PTB risk stratification and preventive interventions can ameliorate PTB complications in singleton, often nulliparous, pregnancies historically deemed low risk.
Proteomic signaling of dual specificity phosphatase 4 (DUSP4) in Alzheimer’s disease
Authors: Wang Erming , Pan Allen L. , Bagchi Pritha , Ranjaraju Srikant , Seyfried Nicholas T. , Ehrlich Michelle E. , Salton Stephen R. , Zhang Bin
Published: September 2023

DUSP4 is a member of the DUSP (Dual-Specificity Phosphatase) subfamily that is selective to the mitogen-activated protein kinases (MAPK) and has been implicated in a range of biological processes and functions in Alzheimer’s disease (AD). In this study, we utilized stereotactic delivery of adeno-associated virus (AAV)-DUSP4 to overexpress DUSP4 in the dorsal hippocampus of 5×FAD and wildtype (WT) mice, then used mass spectrometry (MS)-based proteomics along with label-free quantification to profile the proteome and phosphoproteome in the hippocampus. We identified patterns of protein expression and phosphorylation that are modulated in 5×FAD mice and examined the sex-specific impact of DUSP4 overexpression on the 5×FAD proteome/phosphoproteome. In 5×FAD mice, a substantial number of proteins were up– or down-regulated in both male and female mice in comparison to age and sex-matched WT mice, many of which are involved in AD-related biological processes, such as the activated immune response or suppression of synaptic activities. Upon DUSP4 overexpression, significantly regulated proteins were found in pathways that were suppressed, such as the immune response, in male 5×FAD mice. In contrast, such a shift was absent in female mice. For the phosphoproteome, we detected an array of phosphorylation sites that are regulated in 5×FAD compared to WT, and are modulated by DUSP4 overexpression in each sex. Interestingly, the changes in 5×FAD– and DUSP4-associated phosphorylation occurred in opposite directions. Strikingly, both the 5×FAD– and DUSP4-associated phosphorylation changes were found for the most part in neurons, and play key roles in neuronal processes and synaptic function. Site-centric pathway analysis revealed that both the 5×FAD– and DUSP4-associated phosphorylation sites were enriched for a number of kinase sets in female, but only a limited number of sets of kinases in male mice. Taken together, our results suggest that male and female 5×FAD mice respond to DUSP4 overexpression via shared and sex-specific molecular mechanisms, which might underly similar reductions in amyloid pathology in both sexes, while learning deficits were reduced in only females with DUSP4 overexpression. Finally, we validated our findings with the sex-specific AD-associated proteomes in human cohorts and further developed DUSP4-centric proteomic network models and signaling maps for each sex.
Tissue-Specific Dependence of Th1 Cells on the Amino Acid Transporter SLC38A1 in Inflammation
Authors: Sugiura Ayaka , Beier Katherine L. , Chi Channing , Heintzman Darren R. , Ye Xiang , Wolf Melissa M. , Patterson Andrew R. , Cephus Jacqueline-Yvonne , Hong Hanna S. , Lyssiotis Costas A. , Newcomb Dawn C. , Rathmell Jeffrey C.
Published: September 2023

Amino acid (AA) uptake is essential for T cell metabolism and function, but how tissue sites and inflammation affect CD4+T cell subset requirements for specific AA remains uncertain. Here we tested CD4+T cell AA demands within vitroand multiplein vivoCRISPR screens and identify subset- and tissue-specific dependencies on the AA transporter SLC38A1 (SNAT1). While dispensable for T cell persistence and expansion over timein vitroandin vivolung inflammation, SLC38A1 was critical for Th1 but not Th17 cell-driven Experimental Autoimmune Encephalomyelitis (EAE) and contributed to Th1 cell-driven inflammatory bowel disease. SLC38A1 deficiency reduced mTORC1 signaling and glycolytic activity in Th1 cells, in part by reducing intracellular glutamine and disrupting hexosamine biosynthesis and redox regulation. Similarly, pharmacological inhibition of SLC38 transporters delayed EAE but did not affect lung inflammation. Subset- and tissue-specific dependencies of CD4+T cells on AA transporters may guide selective immunotherapies.

HIGHLIGHTS

T cells dynamically regulate glutamine amino acid transporters when activated

SLC38A1 supports Th1 cell mTORC1 and proliferation by redox and hexosamine pathways

Targeting SLC38A1 does not affect lung inflammation but delays IBD and EAE

Nutrient transporter needs of T cell subsets vary based on disease and tissue site
In vivoselection in non-human primates identifies superior AAV capsids for on-target CSF delivery to spinal cord
Authors: Hanlon Killian S. , Cheng Ming , De La Cruz Demitri , Patel Nikita , Santoscoy Miguel C. , Gong Yi , Ng Carrie , Nguyen Diane M. , Nammour Josette , Clark Sean W. , Kozarsky Karen , Maguire Casey A.
Published: September 2023

Systemic administration of adeno-associated virus (AAV) vectors for spinal cord gene therapy has challenges including toxicity at high doses and pre-existing immunity that reduces efficacy. Intrathecal delivery of AAV vectors into the cerebral spinal fluid (CSF) can avoid many of the issues of systemic delivery, although achieving broad distribution of the vector and transgene expression throughout the spinal cord is challenging and vector entry to the periphery occurs, sometimes initiating hepatotoxicity. Here we performed two rounds ofin vivobiopanning in non-human primates (NHPs) with an AAV9 peptide display library injected intrathecally and performed insert sequencing on DNA isolated from either whole tissue (conventional selection), isolated nuclei, or nuclei from transgene-expressing cells. A subsequent barcoded pool of candidates and AAV9 was compared at the DNA (biodistribution) and RNA (expression) level in spinal cord and liver of intrathecally injected NHPs. Most of the candidates displayed enhanced biodistribution compared to AAV9 at all levels of spinal cord ranging from 2 to 265-fold. Nuclear isolation or expression-based selection yielded 4 of 7 candidate capsids with enhanced transgene expression in spinal cord (up to 2.4-fold), while no capsid obtained by conventional selection achieved that level. Furthermore, several capsids displayed lower biodistribution to the liver of up to 1,250-fold, compared to AAV9, providing a remarkable on target/off target biodistribution ratio. These capsids may have potential for gene therapy programs directed at the spinal cord and the selection method described here should be useful in clinically relevant large animal models.
Genomic analysis ofCoccomyxa viridis, a common low-abundance alga associated with lichen symbioses
Authors: Tagirdzhanova Gulnara , Scharnagl Klara , Yan Xia , Talbot Nicholas J.
Published: September 2023

Lichen symbiosis is centered around a relationship between a fungus and a photosynthetic microbe, usually a green alga. In addition to their main photosynthetic partner (the photobiont), lichen symbioses can contain additional algae present in low abundance. The biology of these algae and the way they interact with the rest of lichen symbionts remains largely unknown. Here we present the first genome sequence of a non-photobiont lichen-associated alga.Coccomyxa viridiswas unexpectedly found in 12% of publicly available lichen metagenomes. With few exceptions, members of theCoccomyxa viridisclade occur in lichens as non-photobionts, potentially growing in thalli endophytically. The 45.7 Mbp genome ofC. viridiswas assembled into 18 near chromosome-level contigs, making it one of the most contiguous genomic assemblies for any lichen-associated algae. Comparing theC. viridisgenome to its close relatives revealed the presence of traits associated with the lichen lifestyle. The genome ofC. viridisprovides a new resource for exploring the evolution of the lichen symbiosis, and how symbiotic lifestyles shaped evolution in green algae.
Self-supervised deep learning uncovers the semantic landscape of drug-induced latent mitochondrial phenotypes
Authors: Natekar Parth , Wang Zichen , Arora Mehul , Hakozaki Hiroyuki , Schöneberg Johannes
Published: September 2023

Imaging-based high-content screening aims to identify substances that modulate cellular phenotypes. Traditional approaches screen compounds for their ability to shift disease phenotypes toward healthy phenotypes, but these end point-based screens lack an atlas-like mapping between phenotype and cell state that covers the full spectrum of possible phenotypic responses. In this study, we present MitoSpace: a novel mitochondrial phenotypic atlas that leverages self-supervised deep learning to create a semantically meaningful latent space from images without relying on any data labels for training. Our approach employs a dataset of ∼100,000 microscopy images of Cal27 and HeLa cells treated with 25 drugs affecting mitochondria, but can be generalized to any cell type, cell organelle, or drug library with no changes to the methodology. We demonstrate how MitoSpace enhances our understanding of the range of mitochondrial phenotypes induced by pharmacological interventions. We find that i) self-supervised learning can automatically uncover the semantic landscape of drug induced latent mitochondrial phenotypes and can map individual cells to the correct functional area of the drug they are treated with, ii) the traditional classification of mitochondrial morphology along a fragmented to fused axis is more complex than previously thought, with additional axes being identified, and iii) latent spaces trained in a self-supervised manner are superior to those trained with supervised models, and generalize to other cell types and drug conditions without explicit training on those cell types or drug conditions. Future applications of MitoSpace include creating mitochondrial biomarkers for drug discovery and determining the effects of unknown drugs and diseases for diagnostic purposes.
Optimizing the slicing pattern of stress-relief crystal analyzers for X-ray Raman scattering
Authors: Diao Qianshun , Zhang Yujun , Jin Shuoxue , He Shangming , Zeng Jianrong , Bian Fenggang , Yang Junliang , Hong Zhen , Lian Hongkai , Gan Xiaolong , Zhang Han , Li Ming , Liu Peng , Chen Dongliang , Guo Zhiying , Xu Wei
Published: September 2023

X-ray Raman scattering (XRS) spectroscopy is an emerging inelastic scattering technique used to measure local electronic structure and chemical bonding around low-Z atoms with hard X-rays. This technique is useful in environments where traditional soft X-ray techniques are not applicable. However, the small cross section of XRS requires that the spectrometer must simultaneously achieve large solid angles and good energy resolution. A large XRS spectrometer named `Qian Kun' is currently under construction at the High Energy Photon Source (HEPS) in China, which can hold up to 100 analyzers with an energy resolution in the range 0.4–1.0 eV. Here, the batch production and performance evaluation of the spherically bent crystal analyzers fabricated for this spectrometer are reported. The stress-relief effect of various dicing patterns and their impact on the reflectivity properties of crystal analyzers to achieve good energy resolution when studying the near-edge features of carbon and oxygen K edges were investigated. It was discovered that radially dicing the thin silicon wafers is more effective in relieving stress than conventional strip cuts in the case that the total number of divided blocks is roughly the same.
Impact of village saving groups on adoption intensity of sustainable agricultural practices among smallholder farmers in Northern region, Ghana
Authors: Alhassan Abdul-Karim , Boateng Vivian Fiatusey , Danso-Abbeam Gideon
Published: September 2023

Purpose

Access to formal financial services is one of the main obstacles to the adoption of agricultural technologies such as Sustainable Agricultural Practices (SAPs). In order to increase financial inclusion and lessen farmers' liquidity restrictions, Village Savings and Loans Associations (VSLA) are being promoted in rural farming communities. However, there extent to which VSLA contributes to the acceleration of agricultural practices, such as SAP, remains little explored in existing literature. The objective of this study was to quantitatively assess the impact of VSLA on the intensity of adoption of SAPs.

Design/methodology/approach

This study used cross-sectional data from 376 farming households in the East Gonja district of Ghana. An Endogenous Poisson Treatment Regression (EPTR) was applied to correct for self-selection bias that might emanate from both observed and unobserved differences in household characteristics.

Findings

The empirical results indicated that farmers' engagement in non-farm economic activities, ownership of land and size of agricultural land under cultivation positively and significantly influence the intensity of SAPs adoption. Moreover, participation in VSLA improves the adoption of SAPs, and that VSLA-participants adopted about three more SAPs than they would have if they did not participate in VSLA.

Practical implications

This study re-affirmed the significance of VSLA in rural farming communities and recommend that it should be promoted as an alternative to formal financial services to enhance financial inclusiveness, and consequently boost the uptake of SAPs.

Originality/value

In the search of literature, this study is the first to estimate the impact of VSLA on adoption of SAPs. The use of EPTR helps to bring out the true treatment effects of VSLA on SAPs.
Adivasi women temporary workers in tea gardens and the Covid-19 pandemic
Authors: Barhoi Poonam , Dayal Surbhi
Published: September 2023

Purpose

The tea plantation industry is characterized by the large-scale deployment of cheap women laborers and gender-blind practices that make the social positions of women workers vulnerable. This paper considers women temporary workers in tea gardens to study the exacerbated impact of Covid-19 on their lives. The impact of the pandemic on marginal tea garden women laborers has not received enough attention from researchers; hence, the authors have studied the gendered implications of the pandemic on Adivasi temporary women workers in tea gardens in India. “Adivasi” is an umbrella term to refer to all indigenous tribes in India.

Design/methodology/approach

The authors conducted a qualitative study with 26 in-depth interviews with women temporary workers who identify themselves as Adivasis. For the discussion, the authors have mainly borrowed from intersectionality and subalternity literature.

Findings

The analysis explored the intersectional experiences of the women temporary workers (1) as members of Tea Tribes who are compelled to continue working at tea gardens as wage laborers, (2) job insecurities at work due to their temporary worker status, (3) disadvantages faced by women workers for their gender identity and (4) the gendered impact of the pandemic on their lives.

Originality/value

This study has explored the gendered impact of the Covid-19 pandemic on the lives of temporary women workers who belong to ethnic minority groups in the global south. The exploitation of labor rights in the tea industry during the pandemic has not been discussed enough by researchers earlier.
Grey clustering and grey ranking of bank branches based on grey efficiency
Authors: Karimi Tooraj , Ahmadian Mohamad
Published: September 2023

Purpose

Competition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology for evaluating, clustering and ranking the performance of bank branches with imprecise and uncertain data in order to determine the relative status of each branch.

Design/methodology/approach

In this study, the two-stage data envelopment analysis model with grey data is applied to assess the efficiency of bank branches in terms of operations. The result of grey two-stage data envelopment analysis model is a grey number as efficiency value of each branch. In the following, the branches are classified into three grey categories of performance by grey clustering method, and the complete grey ranking of branches are performed using “minimax regret-based approach” and “whitening value rating”.

Findings

The results show that after grey clustering of 22 branches based on grey efficiency value obtained from the grey two-stage DEA model, 6 branches are assigned to “excellent” class, 4 branches to “good” class and 12 branches to “poor” class. Moreover, the results of MRA and whitening value rating models are integrated, and a complete ranking of 22 branches are presented.

Practical implications

Grey clustering of branches based on grey efficiency value can facilitate planning and policy-making for branches so that there is no need to plan separately for each branch. The grey ranking helps the branches find their current position compared to other branches, and the results can be a dashboard to find the best practices for benchmarking.

Originality/value

Compared with traditional DEA methods which use deterministic data and consider decision-making units as black boxes, in this research, a grey two-stage DEA model is proposed to evaluate the efficiency of bank branches. Furthermore, grey clustering and grey ranking of efficiency values are used as a novel solution for improving the accuracy of grey two-stage DEA results.