bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of the Ten-valent Pneumococcal Conjugate Vaccine on Invasive Pneumococcal Disease and Pneumonia in Infants Younger Than Ten Weeks of Age in Southern Mozambique: A Population-based Prospective Surveillance Study
Authors: Massora Sérgio , Mucavele Hélio , Carvalho Maria da Gloria , Mandomando Inácio , Chaúque Alberto , Moiane Benild , Tembe Nelson , Omer Saad B. , Bassat Quique , Verani Jennifer R. , Menéndez Clara , Quintó Llorenç , Sigaúque Betuel , Bardají Azucena
Published: February 2025

Background:

Mozambique introduced 10-valent-pneumococcal conjugate vaccine (PCV10) in 2013. We aimed to evaluate the indirect effect of PCV10 on invasive pneumococcal disease (IPD) and clinical severe pneumonia (CSP) in infants aged less than 10 weeks.

Methods:

Routine surveillance data for IPD and CSP among admitted infants less than 10 weeks of age were analyzed to compare IPD and CSP incidence using demographic surveillance data from pre- and post-PCV10 periods. IPD was defined as isolation of pneumococcus from blood or cerebrospinal fluid, and CSP according to World Health Organization criteria.

Results:

The incidence of IPD and CSP among infants less than 10 weeks decreased by 87% [incidence rate ratio (IRR): 0.13; 95% confidence interval (CI): 0.02–0.95] from 283/100,000 in the pre-PCV to 36/100,000 children year at risk (CYAR) post-PCV, and by 62% (IRR: 0.38; 95% CI: 0.27–0.52) from 4100/100,000 pre-PCV to 1550/100,000 CYAR post-PCV periods, respectively. Vaccine-type IPD incidence declined by 92% (IRR: 0.18; 95% CI: 0.02–1.34) from 205/100,000 pre-PCV to 36/100,000 CYAR post-PCV, though the reduction was not statistically significant. The mortality rate due to IPD among infants less than 10 weeks declined from 47/100,000 CYAR in the pre-PCV to 0 in the post-PCV period. Mortality due to CSP declined by 29% (IRR: 0.71; 95% CI: 0.34–1.50), from 457/100,000 CYAR in the pre-PCV to 324/100,000 in the post-PCV periods.

Conclusions:

PCV10 introduction led to substantial declines in the incidence of IPD, CSP and associated mortality in infants too young to be vaccinated (less than 10 weeks) in Mozambique, suggesting indirect protection.
Antibody in Breastmilk Following Pertussis Vaccination in Three-time Windows in Pregnancy
Authors: Daniel Olwenn , Loughnan Myles , Quenby Miranda , Chawla Krina , Greening Vanessa , T. Heath Paul , Jones Christine E. , Khalil Asma , Ramkhelawon Laxmee , Calvert Anna , Le Doare Kirsty ,   on behalf of the MAMA/OpTIMUM breastmilk study group
Published: February 2025

Background:

Pertussis-containing vaccines are routinely offered in the UK at 16–32 weeks of gestation and have been shown to be safe and effective, but there remains debate about the best timing for vaccination. Most research into this has focused on serologic immunity, but breastmilk is also important in infant immunity, and the amount of IgA in breastmilk may impact mucosal immunity. It is important to understand if the timing of vaccination in pregnancy affects the concentration of IgA in breastmilk.

Methods:

Participants recruited as part of the MAMA (Maternal Antibody in Milk After Vaccination) and OpTIMUM (Optimizing the Timing of Whooping Cough Immunisations in Mums) trials received a pertussis-containing vaccine during pregnancy, either before 24 weeks, between 24 and 27+6 weeks or between 28 and 31+6 weeks. Samples of colostrum within 24 hours of delivery and breastmilk at 14 days were collected. Pertussis toxin, pertactin, tetanus toxoid and diphtheria toxoid specific-IgA levels were measured using a multiplex immunoassay.

Results:

There was no difference in specific IgA levels against pertussis toxin, pertactin, tetanus toxoid and diphtheria toxoid between the groups vaccinated within different time periods. For all antigens, there was decay in antigen-specific IgA levels between colostrum and breastmilk at 14 days.

Conclusion:

Our results suggest that the timing of administration of a pertussis-containing vaccine in pregnancy does not impact on antigen-specific IgA concentration in colostrum or breastmilk at 14 days.
Preliminary Results of First-in-Human Intravesical Cryotherapy of Nonmuscle-invasive Bladder Cancer
Authors: Hoffman Azik , Malshy Kamil , Sadeh Omer , Nativ Omri , Kochavi Eyal , Amiel Gilad E.
Published: February 2025

Introduction:

Cryotherapy with CO2 is commonly used to treat superficial papillary lesions of the skin for many years. Following preliminary results in an animal model, we present our first-in-human phase 1 clinical safety trial and preliminary results in treating low-grade noninvasive papillary lesions of the bladder with cryoablation.

Materials and Methods:

Patients with up to 3 papillary lesions and a maximum of 10 mm in size were recruited in a single institution. Patients with previous high-grade disease and/or positive cytology were excluded. Treatment included bladder CO2 insufflation and applying liquid CO2 cryospray to each lesion in 2 cycles of 15 seconds each, with 15 seconds of thawing between cycles. Cystoscopy and treatment site biopsy were performed 4-6 weeks after treatment. Routine surveillance with office cystoscopy was performed every 3 months for 1 year thereafter.

Results:

11 men and 2 women ages 59 to 79 years old were included. Overall, 24 lesions were treated. No complications were noted during treatment or follow-up. Pathological biopsy of the treatment sites 6 weeks after treatment detected residual low-grade TCC in three patients and high-grade TCC in one patient, which was attributed to suboptimal lesion freezing due to the initial learning curve in the first few patients, and misdiagnosis of high-grade disease in an additional patient. Two lesions were resected due to the inability to properly treat them with a rigid device. Overall, 20/24 of the lesions were negative for cancer on confirmatory biopsy (83%).

Conclusions:

Cryotherapy utilizing CO2 spraying for small low-grade NMIBC lesions is safe and feasible. Pathological analysis confirms efficacy in tumor eradication when properly selected and adequately treated by cryospray. This novel treatment may be used as an office procedure and might offer a potential paradigm shift in the treatment of low-grade non-muscle invasive bladder cancer.
Music Combined with Cognitive Behavioral Therapy Enhanced Functional Integration within the Frontal–Parietal–Temporal Brain Network in Patients with Chronic Subjective Tinnitus
Authors: Luo Yiwen , Gao Minqian , Xiao Yongtao , Yang Haidi
Published: February 2025

Background

This study was aimed at investigating the effectiveness of music combined with cognitive behavioral therapy (music-CBT) and its underlying therapeutic mechanisms in treating chronic subjective tinnitus.

Methods

Twenty-seven participants with chronic subjective tinnitus who underwent a 3-month music-CBT were initially involved in this retrospective study. The resting-state electroencephalograms (EEG) and behavioral assessments of pre- and post-music-CBT, including tinnitus handicap inventory (THI), tinnitus functional index (TFI), visual analog scales (VAS), Pittsburgh sleep quality index (PSQI), and Hamilton depression rating scale (HAMD-24) were collected and analyzed.

Results

Following music-CBT, there was a significant reduction in global behavioral assessment scores, with median changes of ΔTHI = 26.0 (p < 0.001), ΔTFI = 23.7 (p < 0.001), ΔVAS = 2.0 (p < 0.001), ΔPSQI = 2.0 (p = 0.002), and ΔHAMD-24 = 2.0 (p < 0.001). Enhanced functional connectivity was seen among the frontal, parietal, and temporal cortices and significantly decreased characteristic path length (ΔCPL in delta = 0.016, p = 0.031; ΔCPL in theta = 0.012, p = 0.013), increased global efficiency (ΔGE in delta = −0.014, p = 0.037; ΔGE in theta = −0.006, p = 0.021), and local efficiency (ΔLE in delta = −0.015, p = 0.037; ΔLE in theta = −0.012, p = 0.015) were also noted. Additionally, associations were identified between ΔPSQI and ΔTHI (rho = 0.546, p = 0.003) and ΔTFI (rho = 0.462, p = 0.015); between ΔHAMD-24 and ΔCPL (rho = −0.389, p = 0.045), ΔGE (rho = 0.395, p = 0.041), and ΔLE (rho = 0.405, p = 0.036).

Conclusion

Optimized cognitive and emotional responses to tinnitus are linked to functional integration within the frontal–parietal–temporal brain network. Early node indicators for tinnitus relief may be the precuneus, middle frontal gyrus, middle temporal gyrus, and the right inferior parietal lobule.
Long-Term Results of Cochlear Implantation in Single-Sided Deaf Patients: Influence of Duration of Deafness and Age at Onset of Deafness
Authors: Honeder Clemens , Gadenstaetter Anselm J. , Liepins Rudolfs , Auinger Alice B. , Riss Dominik , Arnoldner Christoph , Dahm Valerie
Published: February 2025

Objective

The aim of the current study was to investigate the influence of duration, time point, and etiology of deafness on cochlear implant user rates, and to investigate the long-term hearing performance in single-sided deaf patients.

Study Design

Retrospective study.

Setting

Tertiary care hospital.

Patients

77 subjects with single-sided deafness

Intervention

Unilateral cochlear implantation between 2009 and 2022.

Main Outcome Measures

Patients were categorized into users and nonusers. Duration of deafness, onset of deafness, etiology, and further demographic data were collected. Pure tone audiometry, Freiburg numbers, and monosyllables test were carried out at activation, as well as 1 year, 2 to 3 years, and 5 years after cochlear implant activation.

Results

Most patients who lost their hearing after the age of 10 years were cochlear implant users, while patients who lost their hearing earlier and were implanted with a significant delay were likely nonusers. Even patients implanted more than 10 years after the hearing loss regularly used the cochlear implant, if deafness occurred at the age of 10 years or later. Implanted patients showed an improvement of hearing from activation to 1 year postoperatively as well as stable hearing thresholds for 5 years.

Conclusions

The timing of hearing loss influences cochlear implant user rates. Patients who acquired single-sided deafness above the age of 10 years use the device regularly even if the duration of deafness was more than 10 years. This challenges the 10-year cutoff for cochlear implant indication. Furthermore, results show good long-term hearing thresholds and speech understanding for cochlear implant patients who use their device regularly.
The Possible Role of Biofilm Formation in Recidivism of Cholesteatomatous and Noncholesteatomatous Chronic Suppurative Otitis Media
Authors: Zeybek Sivas Zuhal , Yıldırım Nadir
Published: February 2025

Objective

Chronic suppurative otitis media (CSOM) is typically classified into two distinct types: CSOM (without cholestetoma) and CSOM with cholesteatoma (CCSOM). The main microbial agents in both types are Pseudomonas aeruginosa, Staphylococcus aureus, and Klebsiella pneumoniae. It is believed that the virulence of the infecting microorganisms and their biofilm production capacity play a role in the chronicity and persistence of the disease. The aim of this study was to investigate the pathogen microorganisms with their biofilm formation in CSOM, CCSOM, and their recidivism.

Materials and Methods

A cohort of 57 patients was separated into four subgroups as primary CSOM (CSOM, CCSOM) and postoperatively recurring/residual CSOM [(R)CSOM, (R)CCSOM] groups. A control group was formed of 10 patients who underwent tympanotomy for conductive hearing loss without any known past/present ear inflammation. In all 67 patients, ear swabs for culture and the tissue samples for biofilm studies were obtained pre- or intraoperatively.

Results

The most common bacteria grown in the culture mediums were Pseudomonas spp., S. aureus, coagulase-negative Staphylococcus, and coliform bacteria. In the SEM study, biofilms were detected in 9 of 15 CCSOM and 6 of 14 CSOM, and in 13 of 14 (R)CCSOM and 11 of 14 (R)CSOM ears. Statistical analysis showed significantly higher rates of biofilm formation in both recidivist cholesteatomatous and noncholesteatomatous CSOM groups than their primary counterpart groups.

Conclusion

The findings that biofilm is more prevalent in the recidivist cases substantiated that biofilm formation is correlated with the persistence and additionally aggressiveness of the disease in both CSOM types. S. aureus appeared as the leading biofilm-producing bacterium.
Cochlear Implant Outcomes: A Focused Way of Looking at Speech Perception and Health-Related Quality of Life
Authors: Severson Dylan , Brumer Nadav , Hazlewood Chantel , Elkins Elizabeth , Hillyer Jake , Parbery-Clark Alexandra
Published: February 2025

Introduction

The relationship between health-related quality of life (HRQoL) and speech perception in cochlear implant (CI) users is inconsistent across existing research. To investigate this relationship, we assessed HRQoL using the Glasgow Benefit Inventory (GBI) and speech perception using the Minimum Speech Test Battery (MSTB). The present study proposes an additional subscore to the GBI: CI global outcomes.

Methods

Seventeen bimodal CI users between the ages of 55 and 85 years participated in the study. All participants completed the GBI as well as the MSTB (e.g., AzBio sentence test in quiet and noise, the Bamford-Kowal-Bench Speech-in-Noise test [BKB-SIN], and the Consonant-Nucleus-Consonant test [CNC]). Correlations were calculated between HRQoL and speech perception measures.

Results

Improvement in QoL as measured by the GBI CI global outcomes subscore significantly related to better performance on the AzBio in noise. No other significant relationships between the GBI and CI speech perception ability were observed.

Conclusion

CI global outcomes significantly related to speech perception ability in noise (AzBio), suggesting that this novel metric may be useful for capturing bimodal CI patient-reported outcomes.
Novel biomarkers in asthma
Authors: Agrawal Nikita , Kraft Monica
Published: February 2025

Purpose of review

Asthma is a common global respiratory disease characterized by airway inflammation. It is a heterogenous group of disorders with overlapping biological mechanisms. This review will discuss the current state of the use of biomarkers in asthma with an eye to the future. The identification of biomarkers has advanced our understanding of inflammatory pathways in asthma and aided in development of targeted therapies. However, even with similar inflammatory biomarkers, not all patients respond uniformly. Thus, further research into novel biomarkers in asthma is needed.

Recent findings

Recent literature highlights several key themes in biomarker research for asthma. Biomarkers can be derived from various sources, including sputum, blood, urine, and exhaled breath. Historically, studies have focused on eosinophilic inflammation, yet total blood eosinophil counts do not capture asthma pathology and treatment responses. Recent investigations explore eosinophil activity as well as eosinophil subpopulations based on surface protein expressions. Mast cell involvement, their mediators, and club cell secretory protein are further being examined across different asthma molecular phenotypes.

The complexity of inflammatory pathways in asthma, influenced by various factors, underscores the inadequacy of relying on a single biomarker at one time point. Continued research is essential to identify appropriate biomarkers.
Evaluating Loon Lens Pro, an AI-Driven Tool for Full-Text Screening in Systematic Reviews: A Validation Study
Authors: Janoudi Ghayath , Uzun Mara , Jurdana Mia , Hutton Brian
Published: February 2025

Background: Systematic literature reviews (SLRs) are essential for evidence synthesis but are hampered by the resource-intensive full-text screening phase. Loon Lens Pro, a publicly available agentic AI tool, automates full-text screening without prior training by using user-defined inclusion/exclusion criteria and multiple specialized AI agents. This study validated Loon Lens Pro against human reviewers to assess its accuracy, efficiency, and confidence scoring in screening. Methods: In this comparative validation study, 84 full-text articles from eight SLRs were screened by both Loon Lens Pro and human reviewers (gold standard). The AI provided binary inclusion/exclusion decisions along with a transparent rationale and confidence ratings (low, medium, high). Performance metrics, including accuracy, sensitivity, specificity, negative predictive value, precision, and F1 score, were derived from a confusion matrix. Logistic regression with bootstrap resampling (1,000 iterations) evaluated the association between confidence scores and screening errors. Results: Loon Lens Pro correctly classified 70 of 84 full texts, achieving an accuracy of 83.3% (95% CI: 75.0 to 90.5%), sensitivity of 94.7% (95% CI: 82.4 to 100%), and specificity of 80.0% (95% CI: 70.1 to 89.2%). The negative predictive value was 98.1% (95% CI: 93.8 to 100%), with a precision of 58.1% (95% CI: 41.4 to 76.0%) and an F1 score of 0.72. Logistic regression revealed a strong inverse relationship between confidence level and error probability: low, medium, and high confidence decisions were associated with predicted error probabilities of 46.9%, 30.9%, and 3.5%, respectively (C-index = 0.87). Conclusion: Our study provides evidence that Loon Lens Pro is a viable and effective tool for automating the full-text screening phase of systematic reviews. Its high sensitivity, robust confidence scoring mechanism, and transparent rationale generation collectively support its potential to alleviate the burden of manual screening without compromising the quality of study selection.
CT-based Osteoporosis Classification and Bone-Muscle Interaction Mapping Using Multiple Interpretable Machine Learning Models with theBMINetFramework
Authors: Wang Jingran , Hao Ziyan , Lin Liyun , Liu Jiachen , Wang Jiarong , Tang Zaixiang , Geng Dechun , Ni Caifang , Yang Huilin , Li Kun , Du Jun
Published: February 2025

Background

Osteoporosis progresses through stages characterized by declining bone mineral density, vertebral deterioration, and muscle atrophy, with bone-muscle interactions driving synergistic degeneration.

Methods

This study retrospectively collected data from 444 patients aged 50 and older, who underwent DXA, CT, and MRI scans at the First Affiliated Hospital of Soochow University. CT values were measured for 6 vertebrae (L1-S1) and 30 adjacent muscle groups (psoas major, erector spinae, quadratus lumborum) to assess vertebral and muscle density. After analyzing changes in CT values across osteoporosis stages development to capture vertebrae and muscles degeneration pattern, we use multiple interpretable machine learning models to construct classification model and construct bone-muscle interaction network.

Results

This study found that osteoporosis progresses with age, with faster degeneration in females. Early stages show significant bone degradation, especially in L5 and S1 vertebrae, while later stages highlight muscle atrophy. Machine learning models, enhanced by Recursive Feature Elimination (RFE), effectively predicted disease progression (with Normal vs. Osteopenia 0.788, Normal vs. Osteoporosis 0.909, Normal vs. Osteoporotic fracture 0.942, Osteopenia vs. Osteoporosis 0.708, Osteopenia vs. Osteoporotic fracture 0.820 and Osteoporosis vs. Osteoporotic fracture 0.770). The Combined bone muscle interaction network reveals that vertebrae dominate early interactions, shifting to the muscle-clustered module in advanced stages, reflecting the complex degeneration of both bone and muscle.

Conclusion

This study develops classification models and analyze bone-muscle interactions in osteoporosis, uncovering synergistic degradation patterns across disease stages. The innovative BMINet toolkit offers an efficient, interpretable framework for personalized analysis, advancing precision medicine and integrated care for osteoporosis patients.
Detecting Non-linear Dependence through Genome Wide Analysis
Authors: Akingbuwa Wonuola A , Nivard Michel G
Published: February 2025

In the current study we introduce statistical methods based on trigonometry, to infer the shape of a (non)-linear bivariate genetic relationship. We do this based on a series of piecemeal GWASs of segments of a target (continuous) trait distribution, and the genetic correlations between those GWASs and a second trait. Simulations confirm that we are able to retrieve the shape of the relationship given certain assumptions about the nature of the relationship between the traits. We applied the method to the genetic relationship between BMI, sleep duration, and height, and psychiatric disorders (ADHD, anorexia nervosa, and depression) using data from approximately 450K individuals from UK Biobank.

In the relationship between BMI and psychiatric traits, we found that the expected value of depression is a nonlinear function of BMI i.e. there is a nonlinear genetic relationship between both traits. We observed similar findings for the genetic relationship between BMI and anorexia, sleep duration and depression, and sleep duration and ADHD. We observed no underlying nonlinearity in the genetic relationship between height and psychiatric traits.

Using a novel statistical approach, we show that nonlinear genetic relationships between traits are detectable and genetic associations as quantified using global estimators like genetic correlations are not informative about underlying complexities in these relationships. Our findings challenge assumptions of linearity in genetic epidemiology and suggest that bivariate genetic associations are not uniform across the phenotypic spectrum, which may have implications for the development of targeted interventions.
Juggling the Limits of Lucidity: Searching for Cognitive Constraints in Dream Motor Practice
Authors: Peters Emma , Fischer Kathrin , Erlacher Daniel
Published: February 2025

Lucid dreaming (LD), during which the dreamer becomes aware of the dream state, offers a unique opportunity for a variety of applications, including motor practice, personal well-being, and nightmare therapy. However, these applications largely depend on a dreamer's ability to control their dreams. While LD research has traditionally focused on induction techniques to increase dream frequency, the equally crucial skill of dream control remains underexplored. This study provides an initial investigation into the mechanisms of dream control and its potential influencing factors. We specifically examined whether a complex motor skill -juggling- could be performed within a lucid dream, creating a particularly challenging lucid dream task, which calls for a high level of dream control. Eight healthy participants (aged 24-50) underwent overnight polysomnography (PSG) at the University of Bern's Institute for Sports Science, provided detailed dream reports, and completed questionnaires assessing dream control, self-efficacy, personality traits, mindfulness, motivation, and intention setting. Of these, four participants experienced lucid dreams, and of these, two demonstrated high dream control with successful LD juggling attempts. Trait differences between non-lucid and lucid dreamers in the lab were examined, with a focus on low-to-no dream control versus high dream control among the lucid dreamers. The two lucid dream juggling attempts are described in detail, providing insight into the challenges of executing complex tasks within a lucid dream. While this study lacks in sample size, it highlights the potential roles of many psychological traits, such as belief, motivation, and self-efficacy, in shaping dream control abilities. This study helps to lay the groundwork for future research aimed at investigating lucid dream control and therefore optimizing LD applications in therapy, sports training, and cognitive science.
Probing the zooarchaeological record across time and space for ancient pathogens
Authors: Runge Anne Kathrine W. , Light-Maka Ian , Massy Ken , Keller Marcel , Trixl Simon , Kabral Helja , Kirkpatrick Casey L. , Bos Kirsten , Eger Jana , Ernée Michal , Kyselý René , Hochmuth Michael , Poradowski Dominik , Chrószcz Aleksander , Benecke Norbert , Daněček David , Klementová Jana , Nagler Anatoli , Kalmykov Alexey A. , Kantorovich Anatoly R. , Maslov Vladimir E. , Belinskiy Andrey B. , Scheib Christiana L. , Toderaş Meda , Hansen Svend , Stockhammer Philipp W. , Kaniuth Kai , Uhl Regina , Reinhold Sabine , Gillis Rosalind E. , Nelson Elizabeth A. , Pawlowska Kamilla , Key Felix M.
Published: February 2025

Zoonoses are among the greatest threats to human health, with many zoonotic pathogens believed to have emerged during prehistory. Palaeomicrobiological investigations of the zooarchaeological record hold potential to uncover the reservoirs, host ranges, and host adaptations of zoonotic pathogens but face challenges in identifying promising specimens and pathogen DNA preservation. We performed palaeopathological and genetic examinations of 346 skeletal elements from domesticated and wild animals collected from 34 Eurasian sites dating across the last six millennia. We identified 68 signatures of ancient (opportunistic) pathogens, including the important zoonotic pathogenSalmonella enterica, and found support that palaeopathological lesions provide guidance for specimen selection. For two pathogen species,Erysipelothrix rhusiopathiaeandStreptococcus lutetiensis, we confirmed their ancient authenticity using phylogenetics, showcasing an approach to explore the relationship between ancient low-coverage genomes and their modern-day relatives. Our work presents a pathway to understanding prehistoric zoonotic diseases by integrating zooarchaeological, palaeopathological, and genetic data.
Glucocorticoids modulate expression of perineuronal net component genes and parvalbumin during development of mouse cortical neurons
Authors: Yue Liang , Craig Michael T , Morris Brian J
Published: February 2025

Severe prenatal maternal stress is a risk factor for schizophrenia in offspring. Since parvalbumin-containing GABAergic interneuron function in cortex and hippocampus is compromised in schizophrenia, and perineuronal nets (PNNs) facilitate the functioning of these cells, we tested the hypothesis that glucocorticoids, as stress mediators that can access the foetal compartment, might influence the expression of PNN component genes. In cultured mouse cortical neurons, we detected effects of hydrocortisone on many PNN component genes, via diverse mechanisms. A rapid (<4h), glucocorticoid receptor (GR)-mediated suppression ofneurocanand hyaluronan synthase (Has) 1 and 3 mRNAs was observed at 7 daysin vitro(DIV), whereas at 14DIV,brevicanandversicanexpression was reduced by hydrocortisone without GR involvement, while GR inhibition elevatedHas1andHas2mRNA levels and suppressedaggrecanmRNA levels.Tenascin Rexpression was rapidly suppressed by hydrocortisone at 7DIV but not at 14. At 21DIV, PNN component gene expression had become insensitive to hydrocortisone, althoughparvalbuminexpression was reduced after 24h but not 4h exposure. Additionally, effects on protein levels were observed that were sometimes consistent with the mRNA changes (e.g. Has3, Gad1) and sometimes unrelated to them (e.g. elevated TnR levels at 14DIV after glucocorticoid receptor antagonism). We found that hydrocortisone could directly inhibit proteasome activity, potentially explaining the ability of hydrocortisone to increase Has2 levels. As expected from these results, the overall structure of the PNN was compromised by hydrocortisone exposure, with the length of proximal dendrite covered by PNN being reduced. Overall, the data demonstrate a complex and profound, but developmental stage-dependent, regulation of PNN component gene expression by glucocorticoids. This may contribute to the action of severe prenatal or perinatal stress to increase schizophrenia risk.
Deep generation of personalized connectomes based on individual attributes
Authors: Liu Yuanzhe , Seguin Caio , Mansour L. Sina , Tian Ye , Di Biase Maria A. , Zalesky Andrew
Published: February 2025

An individual's connectome is unique. Interindividual variation in connectome architecture associates with disease status, cognition, lifestyle factors, and other personal attributes. While models to predict personal attributes from a person's connectome are abundant, the inverse task-inferring connectome architecture from an individual's personal profile-has not been widely studied. Here, we introduce a deep model to generate a person's entire connectome exclusively based on their age, sex, body phenotypes, cognition, and lifestyle factors. Using the richly phenotyped UK Biobank connectome cohort (N=8,086), we demonstrate that our model can generate network architectures that closely recapitulate connectomes mapped empirically using diffusion MRI and tractography. We find that age, sex, and body phenotypes exert the strongest influence on the connectome generation process, with an impact approximately four times greater than that of cognition and lifestyle factors. Regional differences in the importance of measures were observed, including an increased importance of cognition in the association cortex relative to the visual system. We further show that generated connectomes can improve the training of machine learning models and reduce their predictive errors. Our work demonstrates the feasibility of inferring brain connectivity from an individual's personal data and enables future applications of connectome generation such as data augmentation and anonymous data sharing.
Bridging the rehabilitation data gap in Uganda: learning through the implementation of the WHO Routine Health Information System - Rehabilitation module
Authors: Hasan Md Zabir , Okello Gerald , Groote Wouter De , Omaren Abraham , Adair Tim , Bachani Abdulgafoor M
Published: February 2025

Background

The Health Management Information System (HMIS) of Uganda has historically lacked comprehensive, standardized, high-quality data on rehabilitation and assistive technology (AT) services. This data deficiency has hindered evidence-based decision-making for efficient resource allocation and hindered the contribution of rehabilitation and AT services to public health, limiting their integration and prioritization into health policy and strategic planning frameworks.

Approach

To address this gap, the Ministry of Health (MoH) of Uganda, in partnership with the Learning, Acting, and Building for Rehabilitation in Health Systems (ReLAB-HS) Consortium and the World Health Organization (WHO), integrated the WHO Routine Health Information System (RHIS) - Rehabilitation module into the existing HMIS. The process was facilitated by strategic engagement with national-level stakeholders, comprehensive readiness assessments of facilities, consensus building among stakeholders around a standard set of indicators, the development and pre-testing of HMIS tools, the configuration of District Health Information Software 2 (DHIS2), capacity-building activities, and the systematic deployment of the module.

Result

Since adopting DHIS2 in 2011, Uganda has primarily used paper-based data collection at healthcare facilities. Rehabilitation services are mainly offered at public National and Regional Referral Hospitals, private hospitals, and clinics in urban and peri-urban settings. Rural and underserved areas face significant challenges because of limited infrastructure and a lack of human resources, which hinder the delivery of rehabilitation services, effective data capture, and evidence-informed decision-making. In September 2024, six core rehabilitation indicators were successfully integrated into the HMIS. New data collection instruments were developed and rigorously field-tested, including a standalone outpatient rehabilitation register and an integrated inpatient register. Targeted training initiatives enhanced the capacity of rehabilitation personnel and HMIS focal points, and ongoing technical support ensured sustained data quality improvements and process adherence.

Conclusion

The integration process revealed the indispensable roles of stakeholder engagement, contextualized training, and continuous technical assistance. Persistent challenges included infrastructure deficits, workforce shortages, and competing health system priorities. Nonetheless, the initiative will significantly improve data availability, establishing a foundational framework for enhanced rehabilitation service delivery and strategic planning.
Putative breast cancer risk variants from populations of South Asian ancestry are under-represented in public variant classification databases
Authors: Rony Raveen , Deng Shenglong , Yang Sarah , Doig Ken , Goode David L
Published: February 2025

The majority of publicly available genomics data originates from populations of European ancestry. This limits understanding and detection of inherited genetic risk factors for breast cancer in other populations. To assess the extent to which deficits in knowledge of the genetics of breast cancer risk exist for populations of non-European ancestry, we compared data available on putative breast cancer risk variants in the ClinVar database for populations of different ancestry.

Protein-coding insertions and deletions (indels) and single-nucleotide polymorphisms (SNPs) private to populations of Non-Finnish European (NFE), African (AFR), Admixed American (AMR), East Asian (EAS) and South Asian (SAS) ancestry from the Genome Aggregation Consortium (gnomAD v4) were identified for nine established breast cancer risk genes. The percentage of private protein-coding variants listed as ‘Unreported’ by gnomAD in ClinVar were compared between populations.

The SAS population had the biggest knowledge deficit, as 43.4% of private SAS variants were not reported in ClinVar, compared to 20-30% for other populations. Proportionally fewer SAS variants were reported for all 9 genes, with the difference reaching an adjusted p < 0.05 for PALB2, ATM and BRCA2 when compared to NFE. In contrast, few genes had significantly lower ClinVar reporting rates for AFR, AMR and EAS than for NFE.

ClinVar reporting deficits in the SAS population were observed for both missense and protein-truncating variants. Unreported variants were usually very rare and largely absent in other public repositories. A substantial fraction of unreported variants were protein-truncating (17.2%), or missense with high predicted pathogenicity scores, representing novel candidate breast cancer risk alleles.

Our work demonstrates putative breast cancer risk variants from populations of South Asian ancestry are less likely to be reported in ClinVar. Defining and removing barriers to reporting potential risk variants for breast cancer from South Asian populations is needed to reduce this knowledge deficit.
Bacterial pathogen deploys iminosugar galactosyrin to manipulate plant glycobiology
Authors: Sanguankiattichai Nattapong , Chandrasekar Balakumaran , Sheng Yuewen , Hardenbrook Nathan , Tabak Werner W. A. , Krahn Daniel , Drapal Margit , Buscaill Pierre , Yamamoto Suzuka , Kato Atsushi , Nash Robert , Fleet George , Fraser Paul , Kaiser Markus , Zhang Peijun , Preston Gail M. , van der Hoorn Renier A. L.
Published: February 2025

The extracellular space (apoplast) of plants is an important molecular battleground during infection by many pathogens. We previously found that a plant-secreted β-galactosidase BGAL1 acts in immunity by facilitating the release of immunogenic peptides from bacterial flagellin and thatPseudomonas syringaesuppresses this enzyme by producing a small molecule inhibitor called galactosyrin. Here, we elucidated the structure and biosynthesis of galactosyrin and uncovered its multifunctional roles during infection. Structural elucidation by cryo-EM and chemical synthesis revealed that galactosyrin is an iminosugar featuring a unique geminal diol attached to the pyrrolidine moiety that mimics galactose binding to the β-galactosidase active site. Galactosyrin biosynthesis branches off from purine biosynthesis and involves three enzymes of which the first is a reductase that is unique in iminosugar biosynthesis. Besides inhibiting BGAL1 to avoid detection, galactosyrin also changes the glycoproteome and metabolome of the apoplast. The manipulation of host glycobiology may be common to plant-associated bacteria that carry putative iminosugar biosynthesis clusters.
Linking Transcriptional and Cellular Responses of Human and Murine Pneumococcal Pneumonia
Authors: Gorki Anna-Dorothea , Lakovits Karin , Hladik Anastasiya , Mesteri Ildiko , Gawish Riem , Martins Rui , Drobits Barbara , Menche Jörg , Knapp Sylvia , Widder Stefanie
Published: February 2025

Community-acquired pneumonia (CAP), often caused byStreptococcus pneumoniae, poses a significant global health challenge, especially among high-risk populations. This study investigates the temporal dynamics of pulmonary gene expression duringS. pneumoniae-induced pneumonia using a murine model to elucidate host-pathogen interactions and identify potential biomarkers of disease severity. Using bulk RNA sequencing, we analyzed lung tissues at early (1h, 8h) and acute infection (2d, 3d), as well as post-resolution (30d) time-points. At 2 days post-infection, differentially expressed genes (DEGs) revealed heightened innate immune responses, including chemokine and interferon signaling pathways. By 30 days post-infection, gene expression profiles and histological changes normalized, reflecting resolution of inflammation. Stratifying mice into recovered, sick, and moribund phenotypes during the acute infection phase highlighted significant transcriptional distinctions, including upregulated pro-inflammatory genes and Schlafen family members. Arginase 1 emerged as a predictive marker of disease severity, with elevated expression detectable as early as 8 hours post-infection. Comparative analyses revealed significant overlap between transcriptional responses in our model and those from a Gram-negativeAcinetobacter baumanniipneumonia model, implicating conserved pathways, such as IL-17 and Toll-like receptor signaling. Additionally, murine DEGs correlated with human plasma proteins associated with severe CAP, including CCL8 and CD14, suggesting translational relevance.

This study underscores phase-specific transcriptional reprogramming during pneumococcal pneumonia and identifies potential biomarkers and therapeutic targets for improving outcomes in severe CAP cases.
Metabolic Response of a Chemolithoautotrophic Archaeon to Carbon Limitation
Authors: Hodgskiss Logan H. , Kerou Melina , Luo Zhen-Hao , Bayer Barbara , Maier Andreas , Weckwerth Wolfram , Naegele Thomas , Schleper Christa
Published: February 2025

The ubiquitously distributed ammonia-oxidizing archaea generate energy from ammonia and build cell mass from inorganic carbon sources, thereby contributing to both the global nitrogen and carbon cycles. However, little is known about the regulation of their predicted core carbon metabolism. A thermodynamic model forNitrososphaera viennensiswas developed to estimate the consumption of inorganic carbon in relation to ammonia consumed for energy and was tested experimentally by growing cells in carbon-limited and excess conditions. A combined proteomic and metabolomic approach of the experimental conditions revealed distinct metabolic adaptation depending on the amount of carbon supplied, either in a catalase or pyruvate background as a reactive oxygen species scavenger. Integration of protein and metabolite dynamics revealed a cellular strategy under carbon limitation to maintain a pool of amino acids and an upregulation of proteins necessary for translation initiation to stay primed for protein synthesis. The combination of modelling and functional genomics fills gaps in the understanding of the central metabolism and its regulation in a chemolithoautotrophic, ammonia-oxidizing archaeon even in the absence of available genetic tools.
ROCker models for reliable detection and typing of short-read sequences carryingmcr,erm,mph, andlnuantibiotic resistance genes
Authors: Conrad Roth , Gerhardt Kenji , Konstantinidis Konstantinos T. , Williams-Newkirk Amanda J. , Huang Andrew
Published: February 2025

Quantitative monitoring of emerging antimicrobial resistance genes (ARGs) using short-read sequences remains challenging due to the high frequency of amino acid functional domains and motifs shared with related but functionally distinct (non-target) proteins. To facilitate ARG monitoring efforts using unassembled short-reads, we present novel ROCker models formcr,mph,erm, andlnuARG families as well as models for variants of special public health concern within these families includingmcr-1,mphA,ermB,lnuF, lnuB,andlnuGgenes. For this, we curated target gene sequence sets for model training and built these models using the recently updated ROCker V2 pipeline (Gerhardt et al., in review). To validate our models, we simulated reads from the whole genome of ARG-carrying isolates spanning a range of common read lengths and used them to challenge the filtering efficacy of ROCker vs. common static filtering approaches such as similarity searches using BLASTx with various e-value thresholds or hidden Markov models. ROCker models consistently showed F1 scores up to 10x higher (31% higher on average) and lower false-positive (by 30%, on average) and false-negative (by 16%, on average) rates based on 250 bp-long reads compared to alternative methods. The ROCker models and all related reference material and data are freely available throughhttp://enve-omics.ce.gatech.edu/rocker/models, further expanding the available model collection developed previously for other genes. Their application to short-read metagenomes, metatranscriptomes, and PCR amplicon data should facilitate more accurate classification and quantification of unassembled short-read sequences for these ARG families and specific genes.

Significance

Antimicrobial resistance gene families encodingermandmphgenes confer resistance to the macrolide class of antimicrobials used to treat a wide range of infections. Similarly, themcrgene family confers resistance to polymyxin E (colistin), a drug of last resort for many serious drug-resistant bacterial infections, and thelnugene family confers resistance to lincomycin, reserved for patients allergic to penicillin or where bacteria have developed resistance to other antimicrobials. Assessing the prevalence of these genes in clinical or environmental samples and monitoring their spreading to new pathogens are thus important for quantifying the associated public health risk. However, detecting these and other resistance genes in short-read sequence data is technically challenging. Our ROCker bioinformatic pipeline achieves reliable detection and typing of broad-range target gene sequences in complex data sets, and thus contributes toward solving an important problem in ongoing surveillance efforts of antimicrobial resistance.
Biofilm selection constitutively activates c-di-GMP synthesis by the bifunctional enzyme MbaA
Authors: Lorentzen Øyvind M. , Abel Sören , Johnsen Pål J. , Frøhlich Christopher
Published: February 2025

Biofilms, in which microbes are encased within a self-produced matrix, represent the primary mode of microbial life. Yet, our understanding of the molecular mechanisms governing biofilm formation remains incomplete, limiting the development of targeted interventions against biofilm-associated infections. By selecting forVibrio choleraebiofilms, we identified mutations in the polyamine-regulated, bifunctional enzyme MbaA that alter its enzymatic activity in metabolizing the conserved second messenger cyclic diguanylate (c-di-GMP). These mutations occur in both the c-di-GMP-producing GGDEF domain and the c-di-GMP- hydrolyzing EAL domain of MbaA. Mutagenesis and enzyme kinetic analyses revealed regulatory crosstalk between these domains, where mutations in either domain enhanced production of c-di-GMP by MbaA while concurrently reducing its hydrolytic activity. In the wild- type enzyme, c-di-GMP metabolism is regulated by specific polyamines. Biofilm-evolved mutations not only shift MbaA’s enzymatic activity but also disrupt this post-translational regulation, rendering the enzyme insensitive to external polyamine signaling. Our findings illustrate how evolutionary pressure can rewire existing enzymes, driving a transition from a planktonic to a biofilm-associated lifestyle.
SEEDS: Simulating Emergence of Errors in DNA Storage
Authors: Naznin Mst. Fahmida Sultana
Published: February 2025

Background: DNA storage is a nonvolatile memory technology for storing data as synthetic DNA strings which offers unprecedented storage density and durability. Yet, the application of DNA as a practical digital information storage medium remains an enigma, since this is extremely expensive and it takes a substantial amount of time to encode and decode data to/from synthetic DNA. More importantly, various phases of DNA storage pipeline (e.g., synthesis, sequencing, etc.) are error prone. Furthermore, DNA is subject to decay over time and the reliability of the synthetic DNA depends on various aspects, including preservation medium and temperature. To allow for the perfect storage and recovery of the information and thereby making it competitive with the existing flash or tape based technologies, advanced error protection schemes are necessary. However, evaluating and comparing various DNA storage technologies and error correcting codes under realistic model conditions - comprising a wide array of synthesis medium, sequencing technologies, temperature and duration - is prohibitively time consuming and expensive. Results: In this study, we present SEEDS, an error model based simulator to mimic the process of accumulating errors at different phases of DNA storage. SEEDS is the first known simulator which incorporates various empirically derived statistical (or stochastic?) error models, mimicking the generation and propagation of different types of errors at various phases in DNA storage. It was assessed for its validity against the data from a number of published wet-lab experiments. Conclusions: SEEDS is easy to use and offers flexible and comprehensive parameter settings to mimic the error models in DNA storage. Validation against in vitro experimental results suggests its promise for emulating the stochastic models of error generation and propagation in DNA storage. SEEDS is available as a web interface with a server side application, along with portable cross-platform native applications (available at givethelink).
Ancient dog introgression into the Iberian wolf genome may have facilitated adaptation to human-dominated landscapes
Authors: Lobo Diana , Morales Hernan E , Van Oosterhout Cock , Lopez-Bao Jose Vicente , Silva Pedro , Llaneza Luis , Pacheco Carolina , Castro Diana , Hernandez-Alonso German , Pacheco George Antunes , Archer John Patrick , Gilbert M. Thomas P. , Ferrand Nuno , Godinho Raquel
Published: February 2025

Understanding how large carnivores respond to increasingly human-dominated landscapes will determine their future adaptive potential. The Iberian wolf (Canis lupus signatus), a gray wolf subspecies endemic to the Iberian Peninsula (Portugal and Spain), has uniquely persisted in human-dominated landscapes, unlike many other wolf populations that faced widespread extinction across Europe during the 20th century. In this study, we conducted a comprehensive genome-wide analysis of 145 historical and contemporary Iberian wolf samples to investigate whether hybridization with domestic dogs resulted in genetic introgression. We identified a dog-derived block on Chromosome 2 in Iberian wolves, displaying signatures consistent with introgression and high nucleotide similarity among introgressed individuals. Additionally, our estimates place the average timing of introgression between 6,100 and 3,000 years ago, with low sequence divergence to dogs from the Iberian Peninsula suggesting a single local origin for the hybridization event. Using forward genetic simulations, we show that the introgressed haplotype is most likely being maintained in Iberian wolves by selection. The introgressed dog variants are located within theMAST4gene, which has been linked to neurological disorders, including cognitive and motor developmental delays, hinting at a potential role in cognitive behavior in Iberian wolves. This study uncovers a case of putative adaptive introgression from domestic dogs into wolves, offering new insights into wild canids' adaptation to human-dominated landscapes.