bluuebunny/crossref_metadata_2025 huggingface dataset:
RNF185 control of COL3A1 expression limits prostate cancer migration and metastatic potential
Authors: Van Espen Benjamin , Oo Htoo Zarni , Collins Colin , Fazli Ladan , Molinolo Alfredo , Murad Rabi , Gleave Martin , Ronai Ze’ev A.
Published: July 2023

RNF185 is a RING finger domain-containing ubiquitin ligase implicated in ER-associated degradation. Prostate tumor patient data analysis revealed a negative correlation between RNF185 expression and prostate cancer progression and metastasis. Likewise, several prostate cancer cell lines exhibited greater migration and invasion capabilities in culture upon RNF185 depletion. Subcutaneous inoculation of mouse prostate cancer MPC3 cells stably expressing shRNA against RNF185 into mice resulted in larger tumors and more frequent lung metastases. RNA-sequencing and Ingenuity Pathway Analysis identified wound healing and cellular movement among the most significant pathways upregulated in RNF185-depleted, compared to control prostate cancer cells. Gene Set Enrichment Analyses performed in samples from patients harboring low RNF185 expression and in RNF185-depleted lines confirmed the deregulation of genes implicated in EMT. Among those, COL3A1 was identified as the primary mediator of RNF185’s ability to impact migration phenotypes. Correspondingly, enhanced migration and metastasis of RNF185 KD prostate cancer cells were attenuated upon co-inhibition of COL3A1. Our results identify RNF185 as a gatekeeper of prostate cancer metastasis, partlyviaits control of COL3A1 availability.
A more expressive spline representation for SBML models improves code generation performance in AMICI
Authors: Contento Lorenzo , Stapor Paul , Weindl Daniel , Hasenauer Jan
Published: July 2023

Abstracts

Spline interpolants are commonly used for discretizing and estimating functions in mathematical models. While splines can be encoded in the Systems Biology Markup Language (SBML) using piecewise functions, the resulting formulas are very complex and difficult to derive by hand. Tools to create such formulas exist but only deal with numeric data and thus cannot be used for function estimation. Similarly, simulation tools suffer from several limitations when handling splines. For example, in the AMICI library splines with large numbers of nodes lead to long model import times.

We have developed a set of SBML annotations to mark assignment rules as spline formulas. These compact representations are human-readable and easy to edit, in contrast to the piecewise representation. Different boundary conditions and extrapolation methods can also be specified. By extending AMICI to create and recognize these annotations, model import can be sped up significantly. This allows practitioners to increase the expressivity of their models.

While the performance improvement is limited to AMICI, our tools for creating spline formulas can be used for other tools as well and our syntax for compact spline representation may be a starting point for an SBML-native way to represent spline interpolants.
XPA tumor variants lead to defects in NER that sensitize cells to cisplatin
Authors: Blee Alexandra M. , Gallagher Kaitlyn S. , Kim Hyun-Suk , Kim Mihyun , Troll Christina R. , D’Souza Areetha , Park Jiyoung , Neufer P. Drew , Schärer Orlando D. , Chazin Walter J.
Published: July 2023

Nucleotide excision repair (NER) neutralizes treatment with platinum (Pt)-based chemotherapy by removing Pt lesions from DNA. Previous study has identified that missense mutation or loss of either of the NER genes Excision Repair Cross Complementation Group 1 and 2 (ERCC1andERCC2) leads to improved patient outcomes after treatment with Pt-based chemotherapies. Although most NER gene alterations found in patient tumors are missense mutations, the impact of such mutations in the remaining nearly 20 NER genes is unknown. Towards this goal, we previously developed a machine learning strategy to predict genetic variants in an essential NER scaffold protein, Xeroderma Pigmentosum Complementation Group A (XPA), that disrupt repair activity on a UV-damaged substrate. In this study, we report in-depth analyses of a subset of the predicted NER-deficient XPA variants, includingin vitroanalyses of purified recombinant protein and cell-based assays to test Pt agent sensitivity in cells and determine mechanisms of NER dysfunction. The most NER deficient variant Y148D had reduced protein stability, weaker DNA binding, disrupted recruitment to damage, and degradation resulting from tumor missense mutation. Our findings demonstrate that tumor mutations in XPA impact cell survival after cisplatin treatment and provide valuable mechanistic insights to further improve variant effect prediction efforts. More broadly, these findings suggest XPA tumor variants should be considered when predicting patient response to Pt-based chemotherapy.

Significance

A destabilized, readily degraded tumor variant identified in the NER scaffold protein XPA sensitizes cells to cisplatin, suggesting that XPA variants can be used to predict response to chemotherapy.
Flexible Protein-Protein Docking with a Multi-Track Iterative Transformer
Authors: Chu Lee-Shin , Ruffolo Jeffrey A. , Harmalkar Ameya , Gray Jeffrey J.
Published: July 2023

Conventional protein-protein docking algorithms usually rely on heavy candidate sampling and re-ranking, but these steps are time-consuming and hinder applications that require high-throughput complex structure prediction, e.g., structure-based virtual screening. Existing deep learning methods for protein-protein docking, despite being much faster, suffer from low docking success rates. In addition, they simplify the problem to assume no conformational changes within any protein upon binding (rigid docking). This assumption precludes applications when binding-induced conformational changes play a role, such as allosteric inhibition or docking from uncertain unbound model structures. To address these limitations, we present GeoDock, a multi-track iterative transformer network to predict a docked structure from separate docking partners. Unlike deep learning models for protein structure prediction that input multiple sequence alignments (MSAs), GeoDock inputs just the sequences and structures of the docking partners, which suits the tasks when the individual structures are given. GeoDock is flexible at the protein residue level, allowing the prediction of conformational changes upon binding. For a benchmark set of rigid targets, GeoDock obtains a 41% success rate, outperforming all the other tested methods. For a more challenging benchmark set of flexible targets, GeoDock achieves a similar number of top-model successes as the traditional method ClusPro [1], but fewer than ReplicaDock2 [2]. GeoDock attains an average inference speed of under one second on a single GPU, enabling its application in large-scale structure screening. Although binding-induced conformational changes are still a challenge owing to limited training and evaluation data, our architecture sets up the foundation to capture this backbone flexibility. Code and a demonstration Jupyter notebook are available athttps://github.com/Graylab/GeoDock.
Inferring Neuron-level Brain Circuit Connection via Graph Neural Network Amidst Small Established Connections
Authors: Wan Guojia , Liao Minghui , Zhao Dong , Wang Zengmao , Pan Shirui , Du Bo
Published: July 2023

Motivation

Reconstructing neuron-level brain circuit network is a universally recognized formidable task. A significant impediment involves discerning the intricate interconnections among multitudinous neurons in a complex brain network. However, the majority of current methodologies only rely on learning local visual synapse features while neglecting the incorporation of comprehensive global topological connectivity information. In this paper, we consider the perspective of network connectivity and introduce graph neural networks to learn the topological features of brain networks. As a result, we propose Neuronal Circuit Prediction Network (NCPNet), a simple and effective model to jointly learn node structural representation and neighborhood representation, constructing neuronal connection pair feature for inferring neuron-level connections in a brain circuit network.

Results

We use a small number of connections randomly selected from a single brain circuit network as training data, expecting NCPNet to extrapolate known connections to unseen instances. We evaluated our model onDrosophilaconnectome andC. elegansworm connectome. The numerical results demonstrate that our model achieves a prediction accuracy of 91.88% for neuronal connections in theDrosophilaconnectome when utilizing only 5% of known connections. Similarly, under the condition of 5% known connections inC. elegans, our model achieves an accuracy of 93.79%. Additional qualitative analysis conducted on the learned representation vectors of Kenyon cells indicates that NCPNet successfully acquires meaningful features that enable the discrimination of neuronal sub-types. Our project is available athttps://github.com/mxz12119/NCPNet.
Shape-changing electrode array for minimally invasive large-scale intracranial brain activity mapping
Authors: Wei Shiyuan , Jiang Anqi , Sun Hongji , Zhu Jingjun , Liu Xiaojun , Xu Zheng , Zhang Jing , Jia Shengyi , Shang Yuanyuan , Fu Xuefeng , Li Gen , Wang Puxin , Xia Zhiyuan , Jiang Tianzi , Cao Anyuan , Duan Xiaojie
Published: July 2023

Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.
Applying Artificial Intelligence to Identify Common Targets for Treatment of Asthma, Eczema, and Food Allergy
Authors: Man Liu Bonnie Hei , Rayner Andre , Mendelsohn Andrew R. , Shneyderman Anastasia , Chen Michelle , Pun Frank W.
Published: July 2023

Allergic disorders are common diseases marked by the abnormal immune response towards foreign antigens that are not pathogens. Often patients with food allergy also suffer from asthma and eczema. Given the similarities of these diseases and a shortage of effective treatments, developing novel therapeutics against common targets of multiple allergies would offer an efficient and cost-effective treatment for patients. Herein, we employed the artificial intelligence-driven target discovery platform, PandaOmics, to identify common targets for treating asthma, eczema, and food allergy. Thirty-two case-control comparisons were generated from 15, 11, and 6 transcriptomics datasets related to asthma (558 cases, 315 controls), eczema (441 cases, 371 controls), and food allergy (208 cases, 106 controls) respectively, and allocated into three meta-analyses for target identification. Top-100 high-confidence targets and Top-100 novel targets were prioritized by PandaOmics for each allergic disease. Six common high-confidence targets (i.e.,IL4R,IL5,JAK1,JAK2,JAK3, andNR3C1) across all three allergic diseases have approved drugs for treating asthma and eczema. Based on the targets’ dysregulated expression profiles and their mechanism of action in allergic diseases, three potential therapeutic targets were proposed.IL5was selected as a high-confidence target due to its strong involvement in allergies.PTAFRwas identified for drug repurposing, whileRNF19Bwas selected as a novel target for therapeutic innovation. Analysis of the dysregulated pathways commonly identified across asthma, eczema, and food allergy revealed the well-characterized disease signature and novel biological processes that may underlie the pathophysiology of allergies. Altogether, our study dissects the shared pathophysiology of allergic disorders and reveals the power of artificial intelligence in the exploration of novel therapeutic targets.
Exploiting the therapeutic vulnerability of IDH-mutant gliomas with zotiraciclib
Authors: Pang Ying , Li Qi , Sergi Zach , Yu Guangyang , Sang Xueyu , Kim Olga , Wang Herui , Ranjan Alice , Merchant Mythili , Oudit Belene , Robey Robert W. , Soheilian Ferri , Tran Bao , Núñez Felipe J. , Zhang Meili , Song Hua , Zhang Wei , Davis Dionne , Gilbert Mark R. , Gottesman Michael M. , Liu Zhenggang , Khan Javed , Thomas Craig J. , Castro Maria G. , Gujral Taranjit S. , Wu Jing
Published: July 2023

Isocitrate dehydrogenase (IDH)-mutant gliomas have distinctive metabolic and biological traits that may render them susceptible to targeted treatments. Here, by conducting a high-throughput drug screen, we pinpointed a specific susceptibility of IDH-mutant gliomas to zotiraciclib (ZTR). ZTR exhibited selective growth inhibition across multiple IDH-mutant gliomain vitroandin vivomodels. Mechanistically, ZTR at low doses suppressed CDK9 and RNA Pol II phosphorylation in IDH-mutant cells, disrupting mitochondrial function and NAD+ production, causing oxidative stress. Integrated biochemical profiling of ZTR kinase targets and transcriptomics unveiled that ZTR-induced bioenergetic failure was linked to the suppression of PIM kinase activity. We posit that the combination of mitochondrial dysfunction and an inability to adapt to oxidative stress resulted in significant cell death upon ZTR treatment, ultimately increasing the therapeutic vulnerability of IDH-mutant gliomas. These findings prompted a clinical trial evaluating ZTR in IDH-mutant gliomas towards precision medicine (NCT05588141).

Highlights

Zotiraciclib (ZTR), a CDK9 inhibitor, hinders IDH-mutant glioma growthin vitroandin vivo.

ZTR halts cell cycle, disrupts respiration, and induces oxidative stress in IDH-mutant cells.

ZTR unexpectedly inhibits PIM kinases, impacting mitochondria and causing bioenergetic failure.

These findings led to the clinical trial NCT 05588141, evaluating ZTR for IDH-mutant gliomas.
Proteomic associations with forced expiratory volume – a Mendelian randomisation study
Authors: Axelsson GT , Jonmundsson T , Woo YJ , Frick EA , Aspelund T , Loureiro JJ , Orth AP , Jennings LL , Gudmundsson G , Emilsson V , Gudmundsdottir V , Gudnason V
Published: July 2023

A decline in forced expiratory volume (FEV1) is a hallmark of obstructive respiratory diseases, an important cause of morbidity among the elderly. While some data exist on biomarkers that are related to FEV1, we sought to do a systematic analysis of causal relations of biomarkers with FEV1.

Data from the general population-based AGES-Reykjavik study were used. Proteomic measurements were done using 4,782 DNA aptamers (SOMAmers). Data from 1,648 participants with spirometric data were used to assess the association of SOMAmer measurements with FEV1 using linear regression. Bi-directional Mendelian randomisation (MR) analyses were done to assess causal relations of observationally associated SOMAmers with FEV1, using genotype and SOMAmer data from 5,368 AGES-Reykjavik participants and genetic associations with FEV1 from a publicly available GWAS (n = 400,102).

In observational analyses, 473 SOMAmers were associated with FEV1 after multiple testing adjustment. The most significant were R-Spondin 4, Alkaline Phosphatase, Placental Like 2 and Retinoic Acid Receptor Responder 2. Of the 235 SOMAmers with genetic data, eight were associated with FEV1 in MR analyses. Three were directionally consistent with the observational estimate, Thrombospondin 2 (THBS2), Endoplasmic Reticulum Oxidoreductase 1 Beta and Apolipoprotein M. THBS2 was further supported by a colocalization analysis. Analyses in the reverse direction, testing whether changes in SOMAmer levels were caused by changes in FEV1, were performed but no significant associations were found after multiple testing adjustments.

In summary, this large scale proteogenomic analyses of FEV1 reveals protein markers of FEV1, as well as several proteins with potential causality to lung function.
S4D-ECG: A shallow state-of-the-art model for cardiac abnormality classification
Authors: Huang Zhaojing , Contrera Luis Fernando Herbozo , Yu Leping , Truong Nhan Duy , Nikpour Armin , Kavehei Omid
Published: July 2023

An algorithm for processing raw 12-lead ECG data has been developed and validated in this study that is based on the S4D model. Among the notable features of this algorithm is its strong resilience to noise, enabling the algorithm to achieve an average F1-score of 81.2% and an AUROC of 95.5%. It is characterized by the elimination of pre-processing features as well as the availability of a low-complexity architecture that makes it suitable for implementation on numerous computing devices because it is easily implementable. Consequently, this algorithm exhibits considerable potential for practical applications in analyzing real-world ECG data.
Pre-pandemic activity on a myalgic encephalomyelitis/chronic fatigue syndrome support forum is highly associated with later activity on a long COVID support forum for a variety of reasons: a mixed methods study
Authors: Meyerson William U , Hoyle Rick H
Published: July 2023

Encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID share some clinical and social characteristics. We predicted that this would lead to an increased interaction between pre-pandemic members of an ME/CFS online support community and a long COVID community. We performed a mixed-methods retrospective observational study of the Reddit activity of 7,544 users active on Reddit’s long COVID forum. From among 1600 forums, pre-pandemic activity specifically on a ME/CFS forum is the top predictor of later participation on the long COVID forum versus an acute COVID support forum. In the qualitative portion, motives for this co-participation included seeking mutual support and dual identification with both conditions. Some of this effect may be explained by pre-existing ME/CFS possibly being a risk factor for long COVID and/or SARS-CoV-2 infection being a cause of ME/CFS relapse. The high rate of ME/CFS patients seeking mutual support on a long COVID forum speaks to the longsuffering experience of these patients not feeling heard or respected, and the hope of some ME/CFS patients to gain legitimacy through the public’s growing recognition of long COVID.
A Mendelian randomization study with clinical follow-up links metabolites to risk and severity of pulmonary arterial hypertension
Authors: Alhathli Elham , Julian Thomas , Girach Zain Ul Abideen , Thompson A A Roger , Rhodes Christopher , Gräf Stefan , Errington Niamh , Wilkins Martin R , Lawrie Allan , Wang Dennis , Cooper-Knock Johnathan
Published: July 2023

Pulmonary arterial hypertension (PAH) exhibits phenotypic heterogeneity and variable response to therapy. The metabolome has been implicated in the pathogenesis of PAH, but previous works have lacked power to implicate specific metabolites. Mendelian randomisation (MR) is a method for causal inference between exposures and outcomes. Using GWAS summary statistics, we implemented hypothesis-free MR methodology to test for causal relationships between serum concentration of 575 metabolites and PAH. Unbiased MR causally associated five metabolites with risk of PAH after stringent multiple testing correction; of the five candidates, serine and homostachydrine were validated in a different larger PAH GWAS, and associated with clinical severity of PAH via direct measurement in an independent clinical cohort of 449 PAH patients. We used conditional and orthogonal approaches to explore the biology underlying our lead metabolites. A rare variant analysis demonstrated that loss of function (LOF) mutations within ATF4, a transcription factor responsible for upregulation of serine synthesis under conditions of serine starvation, are associated with higher risk for PAH. Homostachydrine is a xenobiotic metabolite that is structurally related to L-proline betaine, which has been previously linked to modulation of inflammation and tissue remodelling in PAH. Our MVMR analysis suggests that the effect of L-proline betaine is actually mediated indirectly via homostachydrine. Our data presents a new method for study of the metabolome in the context of PAH, and suggests several candidates for further evaluation and translational research.
Modified Rankin Scale Disability Status at Day 4 Poststroke is an Informative Predictor of Long-Term Day 90 Outcome
Authors: Taleb Shayandokht , Lee Jenny Ji-hyun , Asanad Samuel , Starkman Sidney , Hamilton Scott , Conwit Robin A. , Sanossian Nerses , Saver Jeffrey L
Published: July 2023

Background

Long-term disability after stroke is standardly assessed 3 months post-onset, using the modified Rankin Scale (mRS). The value of an early, day 4 mRS assessment for projecting the 3-month disability outcome has not been formally investigated.

Methods

In this cohort of patients with acute cerebral ischemia and intracranial hemorrhage, we analyzed day 4 and day 90 mRS assessments in the NIH Field Administration of Stroke Therapy– Magnesium (FAST-MAG) Phase 3 trial. The performance of day 4 mRS, alone and as part of multivariate models, in predicting day 90 mRS was assessed using correlation coefficients, percent agreement, and the kappa statistics.

Results

Among the 1573 acute cerebrovascular disease (ACVD) patients, 1206 (76.7%) had acute cerebral ischemia (ACI), while 367 (23.3%) had intracranial hemorrhage. Among all 1573 ACVD patients, day 4 mRS and day 90 mRS correlated strongly, Spearman’s rho=0.79, in unadjusted analysis with weighted kappa of 0.59. For dichotomized outcomes, simple carry-forward of the day 4 mRS performed fairly well in agreeing with day 90 mRS: mRS 0-1 (k=0.67), 85.4%; mRS 0-2 (k=0.59), 79.5%; fatal outcome, 88.3% (k=0.33). Correlations of 4d and 90d mRS were stronger for ACI than ICH patients, 0.76 vs 0.71.

Conclusions

In this acute cerebrovascular disease patient cohort, assessment of global disability performed on day 4 is highly informative regarding long-term, 3-month mRS disability outcome, alone, and even more strongly in combination with baseline prognostic variables. The day 4 mRS is a useful measure for imputing the final patient disability outcome in clinical trials and quality improvement programs.
Specific gut pathobionts escape antibody coating and are enriched during flares in patients with severe Crohn’s disease
Authors: Eriksen Carsten , Danneskiold-Samsøe Niels B. , Moll Janne M. , Myers Pernille N. , Bondegaard Pi W. , Vejrum Simone , Hansen Tine B. , Rosholm Lisbeth B. , Rausch Philipp , Allin Kristine H. , Jess Tine , Kristiansen Karsten , Penders John , Jonkers Daisy MAE. , Brix Susanne
Published: July 2023

Patients with Crohn’s disease (CD) exhibit great heterogeneity in disease presentation and treatment responses, where distinct gut microbiota-host interplays may play part in the yet unresolved disease etiology. We here characterized absolute and relative single and multi-coating of gut bacteria with immunoglobulin (Ig)A, IgG1, IgG2, IgG3 and IgG4 in CD patients and healthy controls. Patients with severe disease exhibited distinctly higher gut bacterial IgG2-coating. IgG2-coated bacteria included both known pathogenic and non-pathogenic bacteria that co-existed in communities with two non-coated gut pathobiontsCampylobacterandMannheimia. These latter two exhibited low prevalence, rarely coincided, and were strongly enriched during disease flares in CD patients across independent and geographically distant cohorts. Since antibody-coating of gut pathobionts diminishes epithelial invasion and inflammatory processes, escape from coating by specific gut pathobionts may be a mechanism related to disease flares in the subgroup of CD patients with severe disease.
Restriction of the growth and biofilm formation ofESKAPEpathogens by caprine gut-derived probiotic bacteria
Authors: Saini Prerna , Ayyanna Repally , Kumar Rishi , Bhowmick Sayan Kumar , Dey Bappaditya
Published: July 2023

The accelerated rise of antimicrobial resistance (AMR) poses a significant global health risk, necessitating the exploration of alternative strategies for combating pathogenic infections. Biofilm-related infections, which are unresponsive to standard antibiotics, often require the use of higher-order antimicrobials with toxic side effects and a potential for disrupting the microbiome. Probiotic therapy, with its diverse benefits and inherent safety, is emerging as a promising approach for preventing and treating various infections and as an alternative to antibiotic therapy. In this study, we isolated novel probiotic bacteria from the gut of domestic goats (Capra hircus) and evaluated their antimicrobial and antibiofilm activities against the ‘ESKAPE’ group of pathogens. We performed comprehensive microbiological, biochemical, and molecular characterizations, including analysis of the 16S-rRNA gene V1-V3 region and the 16S-23S ISR region, on 20 caprine gut-derived lactic acid bacteria (LAB). Among these, six selected LABs demonstrated substantial biofilm formation in anaerobic conditions, and exhibited robust cell surface hydrophobicity and autoaggregation properties highlighting their superior enteric colonization capability. Notably, these LAB isolates exhibited broad-spectrum growth inhibitory and anti-biofilm properties against ‘ESKAPE’ pathogens. Additionally, the LAB isolates were susceptible to antibiotics listed by the European Food Safety Authority (EFSA), within the prescribed Minimum Inhibitory Concentration limits, suggesting their safety as feed additives. The remarkable probiotic characteristics exhibited by the caprine gut-derived LAB isolates in this study strongly endorse their potential as compelling alternatives to antibiotics and as direct-fed microbial (DFM) feed supplements in the livestock industry, addressing the escalating need for antibiotic-free animal products.
Objective QC for diffusion MRI data: artefact detection using normative modelling
Authors: Cirstian Ramona , Forde Natalie J. , Andersson Jesper L.R. , Sotiropoulos Stamatios N. , Beckmann Christian F. , Marquand Andre F.
Published: July 2023

Diffusion MRI is a neuroimaging modality used to evaluate brain structure at a microscopic level and can be exploited to map white matter fibre bundles and microstructure in the brain. One common issue is the presence of artefacts, such as acquisition artefacts, physiological artefacts, distortions or image processing-related artefacts. These may lead to problems with other downstream processes and can bias subsequent analyses. In this work we use normative modelling to create a semi-automated pipeline for detecting diffusion imaging artefacts and errors by modelling 24 white matter imaging derived phenotypes from the UK Biobank dataset. The considered features comprised 4 microstructural features (from models with different complexity such as fractional anisotropy and mean diffusivity from a diffusion tensor model and parameters from neurite orientation, dispersion and density models), each within six pre-selected white matter tracts of various sizes and geometrical complexity (corpus callosum, bilateral corticospinal tract and uncinate fasciculus and fornix). Our method was compared to two traditional quality control approaches: a visual quality control protocol performed on 500 subjects and quantitative quality control using metrics derived from image pre-processing. The normative modelling framework proves to be comprehensive and efficient in detecting diffusion imaging artefacts arising from various sources (such as susceptibility induced distortions or motion), as well as outliers resulting from inaccurate processing (such as erroneous spatial registrations). This is an important contribution by virtue of this methods’ ability to identify the two problem sources (i) image artefacts and (ii) processing errors, which subsequently allows for a better understanding of our data and informs on inclusion/exclusion criteria of participants.
Effects of blood meal source and seasonality on reproductive traits ofCulex quinquefasciatus(Diptera: Culicidae)
Authors: Rucci Kevin Alen , Barco Gabriel , Onorato Andrea , Beranek Mauricio , Pueta Mariana , Díaz Adrián
Published: July 2023

Host selection by mosquitoes is a keystone to understanding viral circulation and predicting future infection outbreaks.Culexmosquitoes frequently feed on birds during spring and early summer, shifting into mammals towards late summer and autumn. This host switch may be due to changes in mosquito fitness. The aim of this study was to assess if the interaction effect of blood meal source and seasonality may influence reproductive traits ofCulex quinquefasciatusmosquitoes. For this purpose,Cx. quinquefasciatusmosquitoes were reared in simulated summer and autumn conditions and fed on two different hosts, chickens and mice, in a factorial design. Fecundity, fertility, and hatchability during two consecutive gonotrophic cycles were estimated. We found greater fecundity and fertility for mosquitoes fed upon birds than mammals. Fecundity and fertility did not vary between seasons for chicken-fed mosquitoes, whereas in autumn they decreased for mouse-fed mosquitoes. These traits decreased in the second gonotrophic cycle for mouse-fed mosquitoes, whereas they did not vary between cycles for chicken-fed mosquitoes. There was no statistically significant variation of hatchability among treatments. These results indicate a statistically significant interaction effect of blood meal source and seasonality on fecundity and fertility. However, the pattern was opposite in relation to our hypothesis, suggesting that further studies are needed to confirm and expand our knowledge about mosquito biology and its relationship with seasonal host use shifting.
Independent component analysis reveals the transcriptional regulatory modules inBradyrhizobium diazoefficiensUSDA110
Authors: Gao Zhi-Peng , Gu Wei-Cheng , Li Jie , Qiu Qin-Tian , Ma Bin-Guang
Published: July 2023

The dynamic adaptation of bacteria to environmental changes is achieved through the coordinated expression of many genes, which constitutes a transcriptional regulatory network (TRN).Bradyrhizobium diazoefficiensUSDA110 is an important model strain for the study of symbiotic nitrogen fixation (SNF), and its SNF ability largely depends on the TRN. In this study, independent component analysis was applied to 226 high-quality gene expression profiles ofB. diazoefficiensUSDA110 microarray datasets, from which 64 iModulons were identified. Using these iModulons and their condition-specific activity levels, we (1) provided new insights into the connection between the FixLJ-FixK2-FixK1regulatory cascade and quorum sensing, (2) discovered the independence of the FixLJ-FixK2-FixK1and NifA/RpoN regulatory cascades in response to oxygen, (3) identified the FixLJ-FixK2cascade as a mediator connecting the FixK2-2 iModulon and the Phenylalanine iModulon, (4) described the differential activation of iModulons inB. diazoefficiensUSDA110 under different environmental conditions, and (5) proposed a notion of active-TRN based on the changes in iModulon activity to better illustrate the relationship between gene regulation and environmental condition. In sum, this research offered an iModulon-based TRN forB. diazoefficiensUSDA110, which formed a foundation for comprehensively understanding the intricate transcriptional regulation during SNF.
Concise functional enrichment of ranked gene lists
Authors: Jia Xinglin , Phan An , Kadelka Claus
Published: July 2023

Genome-wide expression data has become ubiquitous within the last two decades. Given such data, functional enrichment methods identify functional categories (e.g., biological processes) that preferentially annotate differentially expressed genes. However, many existing methods operate in a binary manner, disregarding valuable information contained in the gene ranking. The few methods that consider the ranking often return redundant or non-specific functional categories.

To address these limitations, we developed a novel method called Concise Ranked Functional Enrichment (CRFE), which effectively leverages the ranking information in gene expression data to compute a non-redundant set of specific functional categories that are notably enriched for highly ranked genes. A particularly useful feature of CRFE is a tunable parameter that defines how much focus should be given to the most highly ranked genes. Using four treatment-control RNA-seq datasets, we compared the performance of CRFE with the two most widely used types of functional enrichment methods, Gene Set Enrichment Analysis and over-representation analysis. We evaluated the methods based on their ability to utilize ranking information, generate non-redundant results, and return functional categories with high information content. CRFE excelled in all evaluated criteria, outperforming the existing methods, each of which exhibits deficiencies in at least one aspect. Using lung adenocarcinoma data, we further showed that the functional categories identified by CRFE are biologically meaningful.

In conclusion, CRFE computes an informative set of functional categories that summarizes genome-wide expression data. With its superior performance over existing methods, CRFE harbors great promise to become a widely used functional enrichment method.

Author summary

Given a list of differentially expressed genes as input, functional enrichment methods reveal which functional categories (e.g., biological processes) were likely activated by the cell and are responsible for the differential expression. We developed a new such method, called Concise Ranked Functional Enrichment (CRFE), which addresses the limitations of current approaches by incorporating gene ranking information to compute a concise and specific set of enriched functional categories. Using four treatment-control RNA-seq datasets, we evaluate how well CRFE and the two currently most widely used methods perform in three criteria. We find that CRFE outperforms each of the alternative methods in at least one of the evaluated criteria, demonstrating its superiority. A high-level interpretation of the functional categories identified by CRFE for lung adenocarcinoma datasets highlights its usefulness for experimentalists. Overall, CRFE harnesses the power of ranked gene lists to generate a focused and non-redundant set of enriched functional categories. Our study positions CRFE as a promising method for functional enrichment analysis, with the potential to advance research in this field.
Timed sequence task: a new paradigm to study motor learning and flexibility in mice
Authors: Urushadze Anna , Janicek Milan , Abbondanza Alice , Janickova Helena
Published: July 2023

Motor learning and flexibility allow animals to perform routine actions efficiently while keeping them flexible. There is a number of paradigms used to test cognitive flexibility but not many of them focus specifically on learning of complex motor sequences and their flexibility. While many tests use operant or touchscreen boxes that offer high throughput and reproducibility, the motor actions themselves are mostly simple presses of a designated lever. To focus more on motor actions during the operant task and to probe the flexibility of these well-trained actions, we developed a new operant paradigm for mice, the, “timed sequence task”. The task requires mice to learn a sequence of lever presses that have to be emitted in precisely defined time limits. After training, the required pressing sequence and/or timing of individual presses is modified to test the ability of mice to alter their previously trained motor actions. We provide a code for the new protocol that can be used and adapted to common types of operant boxes. In addition, we provide a set of scripts that allow automatic extraction and analysis of numerous parameters recorded during each session. We demonstrate that the analysis of multiple performance parameters is necessary for detailed insight into animals’ behavior during the task. We validate our paradigm in an experiment using the valproate model of autism as a model of cognitive inflexibility. We show that the valproate mice show superior performance at specific stages of the task, paradoxically due to their propensity to more stereotypic behavior.

Significance Statement

Cognitive flexibility impairment is a crucial component of many neurological disorders and it is frequently evaluated in animal models. As the commonly used tests usually do not focus on motor learning and the ability to adapt motor sequences, we designed a new paradigm to evaluate motor learning and its flexibility. The timed sequence task is automatized and easily accessible as it is based on widely available operant boxes. During the training, the task requires precise timing of each action to force stereotypic performance. Its relative complexity allows detailed analysis of multiple parameters and therefore detailed insight into animal’s behavior. The task can be used to reveal and understand subtle differences in motor and operant learning and flexibility.

Graphical Abstract
An automated approach for systematic detection of Key Biodiversity Areas
Authors: Nania Dario , Ficetola Gentile Francesco , Falaschi Mattia , Pacifici Michela , Lumbierres Maria , Rondinini Carlo
Published: July 2023

The new Key Biodiversity Areas (KBA) standard is an important method for identifying regions of the planet hosting unique biodiversity. KBAs are identified through the implementation of threshold-based criteria that can be applied to any target species and region. Efficient methods to rapidly assess the existence of potential KBAs in different areas of the planet are still missing, although they are needed to accelerate the KBA identification process for large numbers of species globally. We developed a methodology to scan geographical regions and detect potential KBAs under multiple criteria. We tested the methodology on 59 species of reptiles and amphibians in Italy through the application of selected KBA criteria. Potential KBAs were identified for multiple species under most criteria, covering 1.4% to 12% of the study area, depending on analytical settings. Unit size used to identify KBAs played an important role in shaping the distribution of potential KBAs, also affecting the degree of overlap between areas triggered by different criteria. New potential KBAs identified in this study are only partially nested within current KBAs in Italy (previously identified for birds) and within the national protected areas.
Differential modulation of miR-122 transcription by TGFβ1/BMP6: implications for nonresolving inflammation and hepatocarcinogenesis
Authors: Paluschinski Martha , Kordes Claus , Vucur Mihael , Buettner Veronika , Roderburg Christoph , Xu Haifeng C , Shinte Prashant , Lang Philipp A , Luedde Tom , Castoldi Mirco
Published: July 2023

Chronic inflammation is widely recognized as a significant factor that promotes and worsens the development of malignancies, including hepatocellular carcinoma. This study aimed to explore the potential role of microRNAs in inflammation-associated nonresolving hepatocarcinogenesis. By conducting a comprehensive analysis of altered microRNAs in animal models with liver cancer of various etiologies, we identified miR-122 as the most significantly downregulated microRNA in the liver of animals with inflammation-associated liver cancer. Although previous research has indicated the importance of miR-122 in maintaining hepatocyte function, its specific role as either the trigger or the consequence of underlying diseases remains unclear. Through extensive analysis of animals andin vitromodels, we have successfully demonstrated thatMIR122transcription is differentially regulated by the immunoregulatory cytokines by the transforming growth factor-beta 1 (TGFβ1) and the bone morphogenetic protein-

6 (BMP6). Furthermore, we presented convincing evidence directly linking reducedMIR122transcription to inflammation and in chronic liver diseases. The results of this study strongly suggest that prolonged activation of signaling pathways, leading to disruption of cytokine-mediated regulation ofMIR122, may significantly contribute to the onset and exacerbation of chronic liver disease.
P-PPI: accurate prediction of peroxisomal protein-protein interactions (P-PPI) using deep learning-based protein sequence embeddings
Authors: Anteghini Marco , Martins dos Santos Vitor AP , Saccenti Edoardo
Published: July 2023

Protein-protein interactions (PPIs) are crucial for various biological processes, and their prediction is typically accomplished through experimental methods, which can be time-consuming and costly. Computational methods provide a faster and more cost-effective approach, leveraging protein sequences and other data sources to infer PPIs. Deep learning (DL) approaches have shown promising results in various protein-related tasks, including PPI prediction. However, DL-based embeddings are often not thoroughly compared or evaluated against state-of-the-art tools. Additionally, existing PPI predictors incorporate different types of information beyond protein sequence representation, making it important to assess the effectiveness of DL-based embeddings solely relying on protein sequences. In this work, we benchmark and compare commonly used DL-based embeddings for PPI prediction based solely on protein sequence information. We utilize high-quality training data, including experimentally validated negative interactions from the Negatome database. The best model, obtained through double cross-validation and hyperparameter optimization, is selected and evaluated to predict peroxisomal PPIs. The resulting tool, P-PPI, is further enhanced by combining AlphaFold2-Multimer predictions with the P-PPI model, leveraging DL-based embeddings and protein structure predictions for a comprehensive analysis of peroxisomal PPIs. This integrated approach holds significant potential to advance our understanding of complex protein networks and their functions.
E-PoSa: a novel and effective tool for sampling pollen directly from flowers
Authors: Pioltelli E. , Guzzetti L. , Tonietti L. , Copetta A. , Biella P. , Campone L. , Galimberti A.
Published: July 2023

Pollinator insects are declining worldwide also due to the alteration of their diet with severe implications on their health status. Pollinators diet relies mainly on flower rewards (i.e., pollen and nectar) and a precise characterization of their chemical composition is crucial in defining pollinators’ nutritional ecology. In this context, the pollen represents a challenging source to investigate, especially due to operative challenges during collection operations and to the small amounts produced per flower.

Here, we designed and tested a novel, easy-to-assemble tool for pollen sampling: E-PoSa (Electronic Pollen Sampler), based on the use of a portable vacuum cleaner. We compared it with some of the most used sampling methods for pollen (i.e., anthers sieving and sampling of the whole anthers) by looking at the differences in their quantitative recovery and nutritional profile. Its applicability in ecological studies was also corroborated by an assessment of its recovery rate obtained from a panel of wildflowers species in an operational environment.

The data obtained showed a significantly higher pollen recovery capacity of E-PoSa compared to the conventional sieving approach and the success in retrieving enough pollen to conduct phytochemical analyses from a broad range of flower morphologies in the field. Our results also demonstrated that high purity pollen can be collected with E-PoSa and that the device does not introduce any significant variation in the nutritional analysis compared to the conventional sieving.

This new sampling approach represents a cheap and easy-to-assemble tool encouraging its future use not only in the field of pollen nutrition but also in a wide variety of other contexts related to pollination ecology. Acknowledging the potential influences of the sampling techniques and moving towards shared standardized field protocols will advance the comprehension of species interactions and foraging patterns of pollinators and their nutritional needs.
SplicingLore : a web resource for studying the regulation of cassette exons by human splicing factors
Authors: Polvèche Hélène , Valat Jessica , Fontrodona Nicolas , Lapendry Audrey , Janczarski Stéphane , Mortreux Franck , Auboeuf Didier , Bourgeois Cyril F.
Published: July 2023

One challenge faced by scientists from the alternative RNA splicing field is to decode the cooperative or antagonistic effects of splicing factors to understand and eventually predict splicing outcomes on a genome-wide scale. In this manuscript, we introduce SplicingLore, an open access database and web resource that help to fill this gap in a straightforward manner. The database contains a collection of RNA-seq-derived lists of alternative exons regulated by a total of 75 different splicing factors. All datasets were processed in a standardized manner, ensuring valid comparisons and correlation analyses. The user can easily retrieve a factor-specific set of differentially included exons from the database, or provide a list of exons and search which splicing factor(s) control(s) their inclusion. Our simple workflow is fast and easy to run, and it ensures a reliable calculation of correlation scores between the tested datasets. As a proof of concept, we predicted and experimentally validated a novel functional cooperation between the RNA helicases DDX17 and DDX5 and the HNRNPC protein. SplicingLore is available athttps://splicinglore.ens-lyon.fr/.
Bird Species diversity from the Southern West part of West Bengal, India
Authors: Dinda Sourav Ch. , Pal Arabinda , Sarkar Moulik , Das Paresh Chandra , Mondal Niladri
Published: July 2023

Birds are essential for stabilizing the balance between various ecosystems. To estimate their diversity, we studied species distribution and made an annotated checklist along with their feeding habitats in the Southwest part of West Bengal, India. We studied the bird diversity using the point count method on various habitats, including agroforest, grassland, sub-tropical forest, and plateau forest regions. A total of 343 species were identified during our study period (2015-2019). We found high species diversity and sightings in the study sites, with 55 new records for the region. The whole study was conducted using a citizen science approach and amateur bird watchers’ community. This study will emphasize the future biodiversity conservation practice for the avifauna.