bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical Impact of High-dose Esomeprazole-amoxicillin Dual Therapy as Rescue Treatment for Helicobacter pylori Infection
Authors: Wang Chao , Wang He-Jie , Li Keng , Wang Yin , Lin Yuan-Yuan , Weng Cheng-Zhao , Chen Jie , Xie Shao-Hua , Jiang Wei , Zhu Yu-Cheng
Published: November 2024

Objective:

This study aimed to compare the effectiveness and safety of high-dose dual therapy (HDDT) using esomeprazole and amoxicillin to furazolidone-based quadruple therapy (FBQT) in treating nonresponsive patients with Helicobacter pylori (H. pylori) infection.

Materials and Methods:

A total of 209 patients with H. pylori infection, who had previously received ineffective treatment and visited an outpatient clinic, were randomly assigned to either the HDDT or FBQT groups. All patients underwent a 14-day treatment regimen, and the success rates of H. pylori eradication and safety of the treatment regimens were assessed 4 weeks posttreatment.

Results:

Following the 14-day treatment period, the intention-to-treat (ITT) analysis revealed eradication rates of 93.6% for HDDT and 86.9% for FBQT. In the per-protocol (PP) analysis, eradication rates were 94.5% for HDDT and 88.7% for FBQT. No significant difference in eradication rates was observed between the two groups. HDDT exhibited significantly lower rates of adverse reactions (9.1% in ITT and 9.2% in PP) compared with FBQT (58.6% in ITT and 59.8% in PP). Multivariate analysis identified interval time, alkaline phosphatase, and serum creatinine level as factors influencing the eradication rate. The area under the receiver operating curve of the interval time between the FBQT group and the HDDT group and the success of H. pylori eradication were 0.622 and 0.578, respectively. The optimal salvage treatment intervals were determined as 6 months for FBQT and 1 year for HDDT.

Conclusion:

HDDT using high-dose esomeprazole and amoxicillin demonstrated efficacy in treating H. pylori infection, with the added benefits of reduced side effects and improved medication compliance compared with FBQT. HDDT can be considered a rescue treatment option when other methods fail, with treatment intervals optimized accordingly.
Efficacy and safety of Qishen Yiqi dropping pills combined with modern medicine for coronary heart disease with ischemic heart failure: A systematic review and meta-analysis
Authors: Man Qiushan , Chen Shijian , Li Xingyu
Published: November 2024

Background:

Qishen Yiqi dropping pills combined with modern medicine have been widely used as a treatment for coronary heart disease with ischemic heart failure. Currently, there have been no robust studies addressing the efficacy and safety of Qishen Yiqi dropping pills combined with modern medicine for coronary heart disease with ischemic heart failure. Therefore, this systematic review and meta-analysis are conducted to fill in the gaps mentioned above.

Methods:

This systematic review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Relevant studies published from inception to April 17, 2023, in the 5 electronic databases: PubMed, The Cochrane Library, EMBASE, CNKI, and the Wanfang database were comprehensively searched. Weighted mean difference was used as the effect size for the continuous variables. Pooled odd ratios are presented if the results are binary variables. Additionally, we performed subgroup and sensitivity analyses to examine the source of heterogeneity. The funnel plot and the Egger test were used to estimate publication bias.

Results:

This meta-analysis included 46 studies involving 5843 participants. There is a significant difference in clinical efficacy, the 6-minute walk test (weighted mean difference = 50.10; 95% CI 28.19 to 72.02; I2
 = 98.9%, P = .000), the indexes of ultrasonic cardiogram, blood biochemical indexes, and adverse effects (odds ratios = 0.46; 95% CI 0.29 to 0.75; I2
 = 35.9%, P = .142). The sensitivity analysis and publication bias have demonstrated the robustness of the results (P = .702).

Conclusion:

Qishen Yiqi dropping pills combined with modern medicine could significantly improve clinical efficacy without incasement adverse effects. Further studies are required to identify the more comprise efficacy and safety results.
Relationship between myocardial infarction and atrial fibrillation: A bidirectional Mendelian randomization study
Authors: Rao Jin , Yu Yue , Cheng Pengchao , Wang Xuefu , Wang Pei , Wang Zhinong
Published: November 2024

Many studies have shown that myocardial infarction (MI) is significantly associated with atrial fibrillation (AF), but the causal relationship between MI and AF has not been established. Therefore, we performed this Mendelian randomization (MR) study to investigate the relationship between MI and AF. We used a publicly available summary statistical dataset for MI based on genome-wide analysis studies (GWAS; ebi-a-GCST011364; 14,825 cases and 2680 controls) and a summary statistical dataset for AF based on an European GWAS (finn-b-I9_AF_REIMB; 10,516 cases and 116,926 controls). The 2‐sample bidirectional MR analysis was performed using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods. The causal effect of MI on AF was analyzed using 30 MI-specific single nucleotide polymorphisms (SNPs) that were characterized as instrumental variables (IVs) based on the GWAS data. The causal effect of MI on AF was confirmed by the IVW (odds ratio [OR] 1.42; 95% confidence interval [CI] 1.27–1.58; P < .001), MR-Egger (OR: 1.49; 95% CI: 1.15–1.93; P = .005), and weighted median (OR: 1.42; 95% CI: 1.24–1.63; P < .001) analyses. Furthermore, in the reverse MR analyses, the causal effect of AF on MI was analyzed using 20 AF-specific SNPs that were screened as IVs. The causal effect of AF on MI was significant based on the results from the IVW method (OR: 1.05; 95% CI: 1.00–1.09; P = .033). In conclusion, the bidirectional MR analyses demonstrated a clear bidirectional causal association between MI and AF.
Treatment of trigeminal neuralgia by acupuncture combined with Chinese medicine from the perspective of modern medicine: A review
Authors: Liu Yue , Wang Dongyan , Li Shenwei , Dong Xu , Sun Jiajing , Li Jingyi , Zhang Ying , Han Yixiao
Published: November 2024

Trigeminal neuralgia (TN) is characterized by recurrent episodes of transient severe pain in its distribution area, with abrupt onset and termination. With the progression of the disease, patients are prone to concurrent psychiatric disorders, such as anxiety and depression, which seriously affect patients’ quality of life. Currently, anticonvulsant drugs are commonly used in clinical practice as the primary treatment, but long-term use of drugs is prone to drug resistance, limiting clinical application. Acupuncture and traditional Chinese medicine (TCM), as alternative and complementary therapies, can make up for the deficiencies in modern medicine and are accepted by patients with the advantages of safety and effectiveness. TCM therapy works by promoting the release of endogenous opioid peptides, adjusting the level of inflammatory factors, and improving negative emotions to exert analgesic effects. This paper discusses the clinical efficacy and safety of acupuncture combined with Chinese medicine in the treatment of TN from the perspective of modern medicine and provides a theoretical basis for seeking better therapeutic targets.
Effect of GLP-1 receptor agonists on weight and cardiovascular outcomes: A review
Authors: Raza Fatima Ali , Altaf Rafiya , Bashir Talha , Asghar Fatima , Altaf Rabiya , Tousif Sohaib , Goyal Aman , Mohammed Aisha , Mohammad Mahnoor Faisal , Anan Mahfuza , Ali Sajjad
Published: November 2024

Diet and lifestyle modifications remain the foundation of obesity treatment, but they have historically proven insufficient for significant, long-term weight loss. As a result, there is a high demand for new pharmacologic treatments to promote weight loss and prevent life-threatening diseases associated with obesity. Researchers are particularly interested in 1 type of drug, glucagon-like peptide 1 receptor agonists (GLP-1 RAs), because of its promising potential in addressing the limitations of non-pharmacologic treatments. In addition to their role in weight loss, these drugs have shown promising early evidence of cardiovascular benefits in obese patients, further enhancing their clinical relevance. Semaglutide and liraglutide, which were initially approved for the treatment of type 2 diabetes, have since been approved by the Food and Drug Administration as weight loss medications due to their effectiveness in promoting significant and sustained weight loss. In this narrative review, we will explore the mechanism of GLP-1 RAs, their effects on weight loss, cardiovascular risk factors and outcomes, common adverse effects, and strategies for managing these effects.
Prognostic nomogram models for elderly patients with differentiated thyroid carcinoma: A population-based study
Authors: Wang Dasong , Yang Yan , Yang Hongwei , He Yu , Wang Zhengyan , Chen Maoshan , Huang Yunhui , Yang Lei
Published: November 2024

This study aimed to develop and validate a prognostic model for elderly patients with differentiated thyroid carcinoma (DTC) based on various demographic and clinical parameters in order to accurately predict patient outcomes. Patients who were diagnosed with DTC and were over 55 years old between 2010 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The patients were then randomly divided into a training set and a validation set in a 7:3 ratio, and patients from our center were included as an external validation group. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors, which were then utilized to develop nomograms for predicting the prognosis. The discriminative ability of the nomograms was evaluated using the concordance index, and the calibration was assessed using calibration plots. The clinical usefulness and benefits of the predictive models were determined through decision curve analysis. The findings of the stepwise Cox regression analysis revealed that several variables, including age, marital status, sex, multifocality, T stage, N stage, and M stage, were significantly associated with overall survival in elderly patients with DTC. Additionally, age, tumor size, multifocality, T stage, N stage, and M stage were identified as the primary determinants of cancer specific survival in elderly patients with DTC. Using these predictors, nomograms were constructed to estimate the probability of overall survival and cancer specific survival. The nomograms demonstrated a high level of predictive accuracy, as evidenced by the concordance index, and the calibration plots indicated that the predicted outcomes were consistent with the actual outcomes. Furthermore, the decision curve analysis demonstrated that the nomograms provided substantial clinical net benefit, indicating their utility in clinical practice.
Novel scoring system for predicting stone-free rate after flexible ureteroscopy lithotripsy
Authors: Yang Bin , Sun Shiwei , Wang Jinyao , Wang Jingyu , Liu Shuqin , Wei Yangbing , Yang Xiaofeng
Published: November 2024

This study aims to investigate the factors affecting the stone-free rate (SFR) of flexible ureteroscopy and laser lithotripsy (fURSL) for renal stones and establish predictive models by identifying their prognostic factors. We retrospectively examined 252 patients with renal stones who were treated with fURSL between July 2020 and April 2022. We analyzed the relationship between the patient’s clinical data (sex, age, and body mass index), stone status (side, size, location, stone/transverse process pixel ratio [STPR], and the CT value of stone [SCTV]), and SFR to determine the relevant factors and analyze their influence. Additionally, a nomogram was constructed based on these prediction results. A total of 252 patients were enrolled based on the inclusion and exclusion criteria. They were reviewed 7, 30, and 90 days postoperatively, with 46, 23, and 10 patients failing to discharge stones, respectively. Univariate Cox proportional hazard regression results revealed that the SFR was correlated with stone location, diameter (D1, diameter of stone measured by computed tomography [CT]; D2, diameter of stone measured by kidney-ureter-bladder abdominal radiography), SCTV, STPR, and operation time. Multivariate Cox proportional hazard regression was used to develop 2 predictive models for the SFR. The influencing factors of model 1 included D1, location, and SCTV, whereas those of model 2 were D2, location, and STPR. The results are shown in the nomogram. Receiver operating characteristic curves showed no significant difference between models 1 and 2 (P = .498), indicating that the nomogram was highly predictive. After 1000 resamples and internal self-validation, the C-indices of models 1 and 2 were 0.924 and 0.895, respectively, showing that the stone clearance predicted by the nomogram matched the actual situation. Stone location, size, and density (SCTV and STPR) were significant predictors of SFR after fURSL. The scoring system based on these factors may be used to guide optimal treatment strategy selection.
Practicing health equity in kidney care by establishing improved access to timely disease management and kidney replacement therapy options: from providers to patients
Authors: Yerram Preethi , Edwards Dawn , Norris Keith C. , Molony Donald , Kalantar-Zadeh Kamyar , Landry Daniel L.
Published: November 2024

Purpose of review

The aim of this article is to review the current understanding of disparities in healthcare experienced by people living with kidney disease and emerging approaches to address root causes. Health equity for any disease state is an aspirational goal commonly sought out by the medical community, but all too often lacking the understanding and support required to improve the outcomes of people with complex conditions such as chronic kidney disease (CKD).

Recent findings

The main themes of the literature covered in this article include a review of the structural drivers of healthcare outcomes, a description of research in the fields of health literacy and patient activation for patients with CKD, and an analysis of the examples of healthcare disparities in CKD patients that include involuntary discharges from dialysis facilities as well as the toll taken from dialysis populations during natural disasters. The National Forum of the ESRD Networks is a coalition of 18 congressionally mandated ESRD network organizations committed to equitable access to home and in-center dialysis modalities and preemptive kidney transplantation. We conclude with the patient-centered story of a patient living with end-stage kidney disease for over 40 years and how her journey has helped shape her view on what she believes should encompass a ‘call to action’ to provide more equitable healthcare to people living with kidney disease.

The overarching implications of this article focus on improving the understanding of present-day healthcare inequality within the community of people living with kidney disease and providing a roadmap of resources and ideas that will help achieve more equitable outcomes. The National Forum of the ESRD Networks is committed to the effective implementation of ‘Practicing Health Equity in Kidney Care’ and improving access to dialysis modalities including home dialysis as well as kidney transplantation including preemptive transplant options.
K wire migration into spinal canal: an infrequent cause of neurological morbidity – a case report
Authors: Bhattarai Ashbin , Gurung Bijaya , Sherchan Binod , Rijal Badri , Karki Prasanna D.
Published: November 2024

Introduction:

K wire is one of the most common implants used for fixation of acromioclavicular joint dislocation. The migration of K wire from the AC joint to the spinal canal is a rare occurrence. In this report, the authors present a case of a young adult who presented with weakness of the left upper limb secondary to migration of the K wire from the AC joint to the spinal canal.

Case presentation:

A 46-year-old male farmer presented with complaints of pain in the neck, tingling sensation in the left upper limb, and a tender palpable swelling on the left side of his neck with weakness of finger flexors and abductors. He had had an open reduction and fixation with K wire for Acromioclavicular dislocation three months back. CT confirmed the K wire is passing through the neural foramen between C5 and C6 vertebra and extending across the entire diameter of the spinal canal. Under intravenous anesthesia, a transverse skin incision was made over the prominent swelling on the neck, and the wire was gently removed. Minimal seepage of spinal fluid was observed, which stopped on its own after a few days.

Discussion:

Although AC joint stabilization by K wire fixation provides a safe and easy fixation with low morbidity, complications such as a loss of fixation or loosening can occur. Migration of K wire into a spinal canal is a well-known but infrequent complication. Resorption of bone, muscle action, and negative intrathoracic pressures associated with respiration and heat necrosis causes progressive loosening and dislodgement. Spinal migration is very dangerous because it can cause serious damage to the dura mater, spinal cord, and vertebral artery.

Conclusion:

Early identification and removal of the K wire, once it has migrated from the site of use, is mandatory to prevent its grievous complications.
Pregnancy and trauma: What you need to know
Authors: Burruss Sigrid , Jebbia Mallory , Nahmias Jeffry
Published: November 2024

Nearly 4% of pregnant patients have an injury-related visit to the emergency department during their pregnancy. There are important physiologic changes that occur during pregnancy that make managing pregnant trauma patients different from the standard management of a nonpregnant patient. This review discusses these changes and the initial assessment, laboratory, and imaging workups for the pregnant trauma patient. In addition, management of specific injuries in pregnancy including pelvic fractures, hemorrhagic shock, and postpartum hemorrhage are reviewed as well as key points regarding resuscitative hysterotomy and fetal support that trauma surgeons should be aware of.
Influence of impurities on the use of Fe-based powder as sustainable fuel
Authors: Choisez Laurine , Van Ende Marie-Aline , Bruyr Zakarie , Contino Francesco , Jacques Pascal J.
Published: November 2024

Sustainable energy production, inherently transient and non-uniformly distributed around the world, requires the rapid development of sustainable energy storage technologies. Recently, pure iron powder was proposed as a high-energy density carrier. While promising, challenges are faced, such as nanoparticle emissions, micro-explosions or cavitation. In this work, a screening of the impact of the most common impurities in iron sources on these mechanisms was conducted through purely thermodynamic simulations. Two idealized models were considered to obtain a range of plausible flame temperatures and emitted gases when considering a purely diffusive regime in standard conditions and stoichiometric air–fuel mixture. The flame temperature and iron evaporation are increasing with the specific energy. A strong evaporation of C, S, Mo, Cu and P is also expected. Most impurities are predicted to decrease cavitation, except for Mn and MnO. The regeneration process by hydrogen-based direct reduction in fluidized bed reactors is also discussed. MgO and CaO are the most promising additions in terms of reducing nanoparticles and porosities, as well as to improve the fluidization and reduction kinetics of the combusted products. The potential of Fe powder as sustainable fuel, already very promising, could be further improved by the addition of selectively chosen impurities.

This article is part of the discussion meeting issue 'Sustainable metals: science and systems'.
Mining of primary raw materials as the critical foundation of ‘sustainable’ metals: a wicked problem for technology innovation clusters
Authors: Moore K. R. , Marquis E. , Shanks K. , Wall F.
Published: November 2024

A transition to a more sustainable human–nature system is inextricably linked to raw materials production, if economic growth is to be maintained or increased by the emergence of new, energy- and metal-hungry technology innovation clusters. The dependence on mined raw materials is a wicked problem for societies vulnerable to negative ecological impacts and for global power bases wanting to secure access to an increasing array of feedstocks. We interrogate the issue of what constitutes a sustainable metal from a triple perspective: (i) the characteristics of ore deposits and the primary extractive operations that supply critical raw materials; (ii) the impediments for complex and interacting supply chains to maintain critical (and other) metals in use; and (iii) the lack of transparency in supply chains that makes it challenging for customers to avoid resources that have been produced by unsustainable and poor practices. We examine existing and emerging structures for resource management to explain the limits to the circular economy and what constitutes a meaningful systemic structure for primary production by responsible mining. We call for the inclusion of a standardized statement of the ‘natural capital’ embodied in R&D for technological materials as a means to create transparency about what constitutes a sustainable metal.

This article is part of the discussion meeting issue ‘Sustainable metals: science and systems’.
Active learning strategies for the design of sustainable alloys
Authors: Rao Ziyuan , Bajpai Anurag , Zhang Hongbin
Published: November 2024

Active learning comprises machine learning-based approaches that integrate surrogate model inference, exploitation and exploration strategies with active experimental feedback into a closed-loop framework. This approach aims at describing and predicting specific material properties, without requiring lengthy, expensive or repetitive experiments. Recently, active learning has shown potential as an approach for the design of sustainable materials, such as scrap-compatible alloys, and for enhancing the longevity of metallic materials. However, in-depth investigations into suited best-practice strategies of active learning for sustainable materials science are still scarce. This study aims to present and discuss active learning strategies for developing and improving sustainable alloys, addressing single-objective and multi-objective learning and modelling scenarios. As model cases, we discuss active learning strategies for optimizing Invar and magnetic alloys, representing single-objective scenarios, and more general steel design approaches, exemplifying multi-objective optimization. We discuss the significance of finding the right balance between exploitation and exploration strategies in active learning and suggest strategies to reduce the number of iterations across diverse scenarios. This kind of research aims to find metrics for a more effective application of active learning and is used here to advance the field of sustainable alloy design.

This article is part of the discussion meeting issue ‘Sustainable metals: science and systems’.
PROBIOTIC POTENTIAL OF RIBOFLAVIN-OVERPRODUCING Bacillus subtilis ACU-I163MR AND ACU-I11MR, ISOLATED FROM FERMENTED AFRICAN LOCUST BEANS
Authors: Awotundun Theresa Abimbola , Olanbiwoninu Afolake Atinuke
Published: November 2024

Riboflavin (Vitamin B2) is a water-soluble compound that plays an important role in multiple cellular functions. This study evaluates the probiotic potential of riboflavin-overproducing Bacillus subtilis strains isolated from fermented African locust beans. After strain improvement, Bacillus subtilis ACU-I11MR and ACU-I163MR were selected due to their higher riboflavin production (0.01905±0.0005 mg/L to 0.0259±0.0077 mg/L and 0.0195±0.0054 mg/L to 0.0267±0.0013 mg/L, respectively). Their safety was confirmed through haemolytic assay, antibiotic susceptibility tests, and the absence of gelatinase and biogenic amine activity. Probiotic potential was assessed via in vitro assays including resistance to low pH, bile salts, phenol, temperature, and NaCl; auto-aggregation; cell hydrophobicity; biofilm formation; antibacterial activity; enzyme and exopolysaccharides production. Both strains were non-haemolytic, negative for gelatinase and biogenic amine activity. They showed significant viability at pH 2 (survival 85.05; 87.09%), 1% bile salts (survival 88.82; 87.64%), and 0.5% phenol (survival 48.80; 59.52%) respectively. ACU-I11MR was susceptible to 9 out of 12 antibiotics, while ACU-I163MR was 100% susceptible. The strains demonstrated strong cell surface adhesion and auto-aggregation, and inhibited several pathogenic bacteria. They produce amylase, protease, and exopolysaccharide, and thrived under various temperature and NaCl conditions. Bacillus subtilis ACU-I163MR, showing superior probiotic potential, could be a promising candidate for developing riboflavin-enriched Bacillus-fermented functional foods.
Genomic epidemiology of emerging terbinafine-resistant Trichophyton indotineae
Authors: Rhodes Johanna , Hui Sui Ting , Dellière Sarah , Summerbell Richard C. , Scott James A. , Kaur Amtoj , Barton Richard C. , Leitao Rodrigo , Hemmings Samuel , Goiriz Rebeca , Lambourne Jonathan , Farrer Rhys A. , Schelenz Silke , Hay Roderick J. , Borman Andrew M. , Chowdhary Anuradha , Abdolrasouli Alireza , Fisher Matthew C.
Published: November 2024

Dermatophyte skin infections affect around a quarter of the world’s population and are a growing public health concern due to increasing incidence of novel species causing severe infections that are resistant to antifungal treatments. Trichophyton species cause the greatest burden of dermatophytosis worldwide, with the T. mentagrophytes species complex being particularly associated with the emergence of new aggressive infections. One emerging species, T. indotineae (originally T. mentagrophytes genotype VIII) is notable for the extensive nature of the often inflammatory infection, its clinical resistance to terbinafine antifungal treatment, and its rapid global spread. To better understand the epidemiology of this disease, we sourced isolates from severe cases of dermatophytosis in the United Kingdom, Ireland, France, Canada and India for the period 2018-2023, including the type strain from Japan. We used whole-genome sequencing to confirm 90 isolates were T. indotineae, and antifungal susceptibility testing indicated that over half of these (62%) were resistant to terbinafine (MIC ≥1 mg/L). Pairwise genetic distances showed very high identity with only 147 (1-414) SNPs separating isolates that were nested within a monophyletic phylogeny, supporting a single evolutionary origin of T. indotineae. That no clear geographic clustering of isolates was observed confirms the rapid transcontinental spread of T. indotineae from its likely centre of diversity in Asia. Genome-wide analyses identified multiple non-synonymous SNPs in SQLE (ERG1), the squalene epoxidase target of terbinafine, that were associated with terbinafine in vitro resistance ≥1 mg/L. However, five isolates exhibited high MIC values without SQLE mutations, suggesting the presence of alternative resistance mechanisms. Our findings highlight the importance of better genomic surveillance to understand and manage this severe and rapidly emerging terbinafine-resistant dermatophyte.
MARVEL: Microenvironment Annotation by Supervised Graph Contrastive Learning
Authors: Cui Yan , Wen Hongzhi , Yang Robert , Luo Xi , Liu Hui , Xie Yuyin
Published: November 2024

Recent advancements inin situmolecular profiling technologies, including spatial proteomics and transcriptomics, have enabled detailed characterization of the microenvironment at cellular and subcellular levels. While these techniques provide rich information about individual cells’ spatial coordinates and expression profiles, extracting biologically meaningful spatial structures from the data remains a significant challenge. Current methodologies often rely on unsupervised clustering followed by cell type annotation based on differentially expressed genes within each cluster and most of the time will require other information as the reference (e.g., HE-stained images). This is labor-intensive and demands extensive domain knowledge. To address these challenges, we propose a supervised graph contrastive learning framework, MARVEL. MARVEL is a supervised graph contrastive learning method that can effectively embed local microenvironments represented by cell neighbor graphs into a continuous representation space, facilitating various downstream microenvironment annotation scenarios. By leveraging partially annotated examples as strong positives, our approach mitigates the common issues of false positives encountered in conventional graph contrastive learning. Using real-world annotated data, we demonstrate that MARVEL outperforms existing methods in three key microenvironment-related tasks: transductive microenvironment annotation, inductive microenvironment querying, and the identification of novel microenvironments across different slices.
drMD: Molecular Dynamics for Experimentalists
Authors: Shrimpton-Phoenix Eugene , Notari Evangelia , Wood Christopher W.
Published: November 2024

Molecular dynamics (MD) simulations can be used by protein scientists to investigate a wide array of biologically relevant properties such as the effects of mutations on a protein’s structure and activity, or probing intermolecular interactions with small molecule substrates or other macromolecules. Within the world of computational structural biology, several programs have become popular for running these simulations, but each of these programs requires a significant time investment from the researcher to run even simple simulations. Even after learning how to run and analyse simulations, many elements remain a “black box.” This greatly limits the accessibility of molecular dynamics simulations for non-experts.

Here we present drMD, an automated pipeline for running molecular dynamics simulations using the OpenMM molecular mechanics toolkit. We have created drMD with non-experts in computational biology in mind. The drMD codebase has several functions that automatically handle routine procedures associated with running molecular dynamics simulations. This greatly reduces the expertise required to run MD simulations. We have also introduced a series of quality-of-life features to make the process of running MD simulations both easier and more pleasant. Finally, drMD explains the steps it is taking interactively and, where useful, provides relevant references so the user can learn more. All these features make drMD an effective tool for learning molecular dynamics while running publication-quality simulations.

drMD is open source and can be found on GitHub:https://github.com/wells-wood-research/drMD.
Environmentally Relevant Lead Exposure Impacts Gene Expression in SH-SY5Y Cells Throughout Neuronal Differentiation
Authors: Morgan Rachel K. , Tapaswi Anagha , Polemi Katelyn M. , Tolrud Elizabeth C. , Bakulski Kelly M. , Svoboda Laurie K. , Dolinoy Dana C. , Colacino Justin A.
Published: November 2024

Lead (Pb) causes learning and memory impairments, but the molecular effects of continuous, environmentally relevant levels of exposure on key neurodevelopmental processes are not fully characterized. Here we examine the effects of a range of environmentally relevant Pb concentrations (0.16μM, 1.26μM, and 10μM Pb) relative to control on neural differentiation in the SH-SY5Y cell model. Pb exposure began on differentiation day 5 and was continuous for remaining days, after which we assessed the transcriptome via RNA sequencing at several time points. The bulk of detected changes in gene expression occurred with the 10μM Pb condition. Interestingly, changes associated with the lower two exposures were differentiation stage-specific, with aberrant expression of several genes (e.g.,COL3A1,HMOX1, andCCL2) observed during differentiation on days 9, 12, and 15 in both the 0.16μM and 1.26μM Pb conditions, and which disappeared by the time differentiation concluded on day 18. We observed six co-expression clusters of genes during differentiation, and 10uM Pb significantly perturbed two clusters, one involved in cell cycling and DNA repair and the other in protein synthesis. Benchmark concentration analysis identified many genes affected by levels of Pb at or below the current US standard (3.5μg/dL) and these genes were enriched for pathways including stress responses, DNA repair, misfolded protein response, mitosis, and neurotransmitter production. This work highlights potential new mechanisms by which environmentally relevant concentrations of Pb impact gene expression throughout neural differentiation and result in long-lasting implications for neural health and cognition.
To nest or not to nest: environmental cues for olive ridley mass nesting events in Odisha, India
Authors: Srikanthan Prahalad , Pusapati Chandana , Verma Akash , Dhal Gagan , Manoharakrishnan Muralidharan , Shanker Kartik
Published: November 2024

Sea turtles of the genusLepidochelystake part in synchronised nesting events, known asarribadas, where a large number of females emerge simultaneously from the sea to nest on the beach. Despite some evidence for the role of environmental factors, there is considerable uncertainty about both the factors that influence mass-nesting at an annual scale as well as the onset of individual events. We used a multi-decadal dataset from two olive ridley mass nesting beaches in Odisha, India, to identify the environmental factors associated with inter-annual nesting variation, nesting seasonality and the onset of arribadas. Interestingly, the two sites showed different patterns in inter-annual patterns associated with the non-occurrence of arribadas, despite being only 250 km apart. The nesting season was consistently during the dry and cooler part of the year. Arribada start dates were non-uniformly distributed across the lunar phase in Gahirmatha with most arribadas occurring during the first and third quarters. Fast Southern Winds characterised the period before and during the arribada at both sites. Machine learning models (XGBoost) identified the most important parameters for the onset of mass nesting and accurately predicted more than 75% of the start dates. Lunar phase, mean sea level pressure and wind speed and direction were important parameters at both sites. Differences in parameter importance between sites suggest that mass nesting is influenced by the interaction of several environmental parameters, along with site-specific characteristics. Insights into the triggers of mass nesting can thus provide guidance for site-specific management efforts.
Predicting the pathway involvement of metabolites annotated in the MetaCyc knowledgebase
Authors: Huckvale Erik D. , Moseley Hunter N.B.
Published: November 2024

The associations of metabolites with biochemical pathways are highly useful information for interpreting molecular datasets generated in biological and biomedical research. However, such pathway annotations are sparse in most molecular datasets, limiting their utility for pathway level interpretation. To address these shortcomings, several past publications have presented machine learning models for predicting the pathway association of small biomolecule (metabolite and zenobiotic) using data from the Kyoto Encyclopedia of Genes and Genomes (KEGG). But other similar knowledgebases exist, for example MetaCyc, which has more compound entries and pathway definitions than KEGG. As a logical next step, we trained and evaluated multilayer perceptron models on compound entries and pathway annotations obtained from MetaCyc. From the models trained on this dataset, we observed a mean Matthews correlation coefficient (MCC) of 0.845 with 0.0101 standard deviation, compared to a mean MCC of 0.847 with 0.0098 standard deviation for the KEGG dataset. These performance results are pragmatically the same, demonstrating that MetaCyc pathways can be effectively predicted at the current state-of-the-art performance level.

Author summary

Many thousands of different molecules play important roles in the processes of life. To generally handle the complexity of life, biological and biomedical researchers typically organize the molecular parts and pieces of biological processes into pathways of biomolecules and their myriad of molecular interactions. While the role of large macromolecules like proteins are well characterized within these pathways, the role of small biomolecules are not as comprehensively known. To close this knowledge gap, several machine learning models have been trained on data from a knowledgebase known as the Kyoto Encyclopedia of Genes and Genomes (KEGG) to predict which pathways a small biomolecule is associated with. More data generally improves these machine learning models. So in this work, we used the MetaCyc knowledgebase to increase the amount of data available by about ten-fold and then trained new machine learning models that demonstrate comparable prediction performance to models trained on KEGG, but covering 8-fold more pathways defined in MetaCyc vs KEGG.
Assessing the readiness of Oxford Nanopore sequencing for clinical genomics applications
Authors: Arres Judith , Elavalli Santosh , Behl Shalini , Matias Sanchez Daniel , Ali Ayesha Al , Ahmed Yehia Abdelaziz Saad Abdelrahman , Attia Azza , Minas Cyla , Pariyachery Sharika , Ahmed Shariq , Aldhuhoori Fatmah , Thulasidharan Nitu , Katagi Gurunath , Soliman Omar , Purohit Shilp , Kusuma Vinay , Cardoso Thyago , Paulin Luis F , Sanio Philippe , Mafofo Joseph , Wu Haiguo , Zvereff Val , El-Khani Albarah , Marzooqi Fahed Al , Magalhães Tiago R , Sedlazeck Fritz , Quilez Javier
Published: November 2024

Long-read sequencing (LRS) technologies, namely Oxford Nanopore Technologies (ONT) and Pacific Biosciences, have emerged as promising solutions to overcome the limitations of short-read sequencing (SRS). Nevertheless, the still higher sequencing error rates compared to SRS, need for customized pipelines, rapidly updating software and incipient scalability are proving the adoption of the ONT for standard clinical practice to be challenging. Here we assess the performance of ONT (R9 and R10 chemistries) in comparison to Illumina and MGI across 17 well-characterized reference samples with 11 clinical variants representing 9 different genetic diseases. To enable this, we have implemented a production-ready pipeline including SNV, INDEL, STR, SV and CNV detection together with reporting key summary metrics to ensure high quality of data at production sequencing level. Our results show high accuracy of ONT across SNV (F-score >0.975) and SV, but still several weaknesses across INDEL (F-score<0.80). However, we highlight that ONT accurately detected all four pathogenic INDELs as well as the performance improvement in exons and with the newer R10 chemistry. We further demonstrated the importance of long-reads to detect clinical-impacting variants such as aFMR1pathogenic expansion, often misclassified by SRS as premutation range. Some issues remain as long-read analysis reported the wrong CNV genotype in one of the medical case samples. Remarkably, our multi-platform analysis and Sanger validation discovered a 1-bp error in the Coriell annotation for a cystic fibrosis causing INDEL in GM07829. Overall, this work highlights the readiness of ONT for clinical applications and large-scale operations.
A synthetic data generation pipeline to reproducibly mirror high-resolution multi-variable peptidomics and real-patient clinical data
Authors: Jaimes Campos Mayra Alejandra , Kabić Stipe , Latosinska Agnieszka , Anicic Ena , Siwy Justyna , Dragušica Vinko , Rupprecht Harald , Catanese Lorenzo , Keller Felix , Perco Paul , Gomez- Gomez Enrique , Beige Joachim , Vlahou Antonia , Mischak Harald , Vukelić Davorin , Križan Tomislav , Frantzi Maria
Published: November 2024

Generating high quality, real-world clinical and molecular datasets is challenging, costly and time intensive. Consequently, such data should be shared with the scientific community, which however carries the risk of privacy breaches. The latter limitation hinders the scientific community’s ability to freely share and access high resolution and high quality data, which are essential especially in the context of personalised medicine. In this study, we present an algorithm based on Gaussian copulas to generate synthetic data that retain associations within high dimensional (peptidomics) datasets. For this purpose, 3,881 datasets from 10 cohorts were employed, containing clinical, demographic, molecular (> 21,500 peptide) variables, and outcome data for individuals with a kidney or a heart failure event. High dimensional copulas were developed to portray the distribution matrix between the clinical and peptidomics data in the dataset, and based on these distributions, a data matrix of 2,000 synthetic patients was developed. Synthetic data maintained the capacity to reproducibly correlate the peptidomics data with the clinical variables. Consequently, correlation of the rho-values of individual peptides with eGFR between the synthetic and the real-patient datasets was highly similar, both at the single peptide level (rho = 0.885, p < 2.2e-308) and after classification with machine learning models (rhosynthetic= -0.394, p = 5.21e-127; rhoreal= -0.396, p = 4.64e-67). External validation was performed, using independent multi-centric datasets (n = 2,964) of individuals with chronic kidney disease (CKD, defined as eGFR < 60 mL/min/1.73m²) or those with normal kidney function (eGFR > 90 mL/min/1.73m²). Similarly, the association of the rho-values of single peptides with eGFR between the synthetic and the external validation datasets was significantly reproduced (rho = 0.569, p = 1.8e-218). Subsequent development of classifiers by using the synthetic data matrices, resulted in highly predictive values in external real-patient datasets (AUC values of 0.803 and 0.867 for HF and CKD, respectively), demonstrating robustness of the developed method in the generation of synthetic patient data. The proposed pipeline represents a solution for high-dimensional sharing while maintaining patient confidentiality.
Overcoming the widespread flaws in the annotation of vertebrate selenoprotein genes in public databases
Authors: Ticó Max , Sullivan Emerson , Guigó Roderic , Mariotti Marco
Published: November 2024

Selenocysteine (Sec) is a non-canonical amino acid incorporated into selenoproteins, oxidoreductase enzymes carrying essential roles in redox homeostasis. Sec insertion is performed in response to the UGA codon, normally interpreted as a stop codon, but recoded in selenoprotein mRNAs. Owing to the dual function of UGA, the identification of selenoprotein genes poses a challenge.

We show here that the vertebrate selenoprotein genes are widely misannotated in the major public databases. In Ensembl, considered the gold standard of genomic annotation, our analysis shows that only ∼10% of selenoprotein genes are well annotated; ∼10% have no annotation at all, and ∼80% have flawed annotations which lack the Sec-encoding UGA. Only model organisms have correct selenoprotein annotations in Ensembl, ascribed to manual curation. At NCBI, ∼50% of selenoproteins are misannotated, mostly corresponding to families with C-terminal Sec residues.

We argue that selenoproteins must be correctly annotated in public database and that must occur via automated pipelines, to keep the pace with genome sequencing. To facilitate this task, we present a new version of Selenoprofiles, an homology based tool for prediction of selenoproteins that can be easily deployed and produce correct predictions with accuracy comparable to manual curation.
cOmicsArt – a customizable Omics Analysis and reporting tool
Authors: Seep Lea , Jost Paul Jonas , Lisowski Clivia , Huang Hao , Grein Stephan , Hermannsdottir Hildigunnur , Kuellmer Katharina , Fromme Tobias , Klingenspor Martin , Mass Elvira , Kurts Christian , Hasenauer Jan
Published: November 2024

Motivation

The availability of bulk-omic data is steadily increasing, necessitating collaborative efforts between experimental and computational researchers. While software tools with graphical user interfaces (GUIs) enable rapid and interactive data assessment, they are limited to pre-implemented methods, often requiring transitions to custom code for further adjustments. However, most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition.

Results

We introduce the customizable Omics Analysis and reporting tool – cOmicsArt. cOmicsArt aims to enhance collaboration through integration of GUI-based analysis with R. The GUI allows researchers to perform user-friendly exploratory and statistical analyses with interactive visualizations and automatic documentation. Downloadable R scripts and results ensure reproducibility and seamless integration with R, supporting both novice and experienced programmers by enabling easy customizations and serving as a foundation for more advanced analyses. This versatility also allows for usage in educational settings guiding students from GUI-based analysis to R Code.

Availability

cOmicsArt is freely available athttps://shiny.iaas.uni-bonn.de/cOmicsArt/

User documentation is available athttps://icb-dcm.github.io/cOmicsArt/

Source code is available on GitHubhttps://github.com/ICB-DCM/cOmicsArt

A docker image can be retrieved fromhttps://hub.docker.com/r/pauljonasjost/comicsart/tags

A snapshot upon publication can be found on Zenodo:https://zenodo.org/records/13740904

A screen recording of cOmicsArt is available at:https://www.youtube.com/watch?v=pTGjtIYQOakp

Contact

jan.hasenauer@uni-bonn.de

Supplementary information

Supplementary data are available online.