bluuebunny/crossref_metadata_2025_split huggingface dataset:
The transcription factor RppA regulates chlorophyll and carotenoid biosynthesis to improve photoprotection in cyanobacteria
Authors: Yu Chen , Xu Hai-Feng , Liu Yan-Ru , Yan Wei-Wei , Kong Xin-Ling , Zhang Zhong-Chun , Dai Guo-Zheng , Qiu Bao-Sheng 
Published: September 2024

Abstract
Chlorophyll is an essential photosynthetic pigment but also a strong photosensitizer. Excessive free chlorophyll and its precursors can cause oxidative damage to photosynthetic organisms. Cyanobacteria are the oldest oxygenic photosynthetic organisms and the ancestors of the chloroplast. Owing to their complex habitats, cyanobacteria require precise regulation of chlorophyll synthesis to respond to environmental factors, especially changes in light. Chlorophyll synthase, encoded by chlG, is the enzyme catalyzing the final step of chlorophyll biosynthesis, which is closely related to photosynthesis biogenesis. However, the transcriptional regulation on chlG remains unclear. Here, the transcription factor, regulator of photosynthesis and photopigment-related gene expression A (RppA), was identified to bind to the chlG promoter by screening a yeast 1-hybrid library in the cyanobacterium Synechocystis sp. PCC 6803. The rppA knockout mutant showed a phenotype of slow growth and severe oxidative damage under dark–light transition conditions. The upregulated transcriptional expression of chlG was significantly higher and more chlorophyll and its precursors accumulated in the rppA knockout mutant than those in the wild-type strain during the transition from darkness to light, indicating that RppA represses the expression of chlG in Synechocystis. Meanwhile, RppA could synchronously promote the transcription of carotenoids biosynthesis-related genes to enhance carotenoids synthesis during the dark–light transition. These results reveal synergistic regulation of chlorophyll and carotenoids biosynthesis in cyanobacteria in response to frequent dark–light transitions, which slows down chlorophyll biosynthesis while promoting carotenoids biosynthesis to avoid oxidative damage caused by excessive reactive oxygen species accumulation.
Impact of Segmental Lordosis Restoration During Degenerative Spinal Fusion on Two-Year Adjacent Segment Disease and Revision Rates
Authors: Singh Manjot , Kuharski Michael J. , Abdel-Megid Hazem , Balmaceno-Criss Mariah , Knebel Ashley , Daher Mohammad , Nassar Joseph E. , Basques Bryce , Kuris Eren O. , Diebo Bassel G. , Daniels Alan H. 
Published: September 2024

Study Design:
Retrospective cohort study.

Objective:
Assess the impact of inadequate correction of L4-S1 lordosis during transforaminal lumber interbody fusion (TLIF) on adjacent segment disease and revision rates.

Background:
Restoring alignment is an important consideration in spinal fusions. Failure to correct to level-specific alignment goals could promote the development of adjacent segment disease. As such, it is crucial to investigate the role of sagittal segmental alignment on clinical outcomes following short segment lumbar fusion.

Methods:
Patients who underwent 1- to 3-level transforaminal lumbar interbody fusion (TLIF) and had two-year outcomes data were included in this retrospective cohort study. Segmental lumbar lordosis was assessed in all patients with L3-L4, L4-L5, and L5-S1 constructs. Demographics, radiographic spinopelvic alignment, and complications were compared in a sub-group of patients fused at L4-S1 with adequate (i.e., within 35-45°) and inadequate (i.e., <35°) L4-S1 lordosis.

Results:
Among the 168 included patients, mean age was 61.7 years, 56.0% were female, and mean follow-up was 32.3 months. Segmental lumbar lordosis did not change significantly after TLIF of L3-L4, L4-L5, or L5-S1 (P>0.05). Two-year postoperatively, 32.7% developed adjacent segment disease and 19.6% underwent revisions. After stratification by adequate (N=15) or inadequate (N=54) restoration of L4-S1 lordosis following initial TLIF surgery, adequately-restored patients had higher preoperative L4-S1 lordosis (Adequately-Restored=39.3° vs Inadequately-Restored=29.5°, P<0.001) and lower two-year postoperative adjacent segment disease (6.7% vs. 33.3%, P=0.032) and revision (5.7% vs. 25.9%, P=0.l33) rates. Adjacent segment disease patients had higher implant-related complications (Adjacent Segment Disease=36.8% vs No Adjacent Segment Disease=8.0%, P=0.008) and subsequent revisions (61.1% vs. 8.7%, P<0.001).

Conclusions:
Adjacent segment disease and revisions after degenerative lumbar spinal fusion are common. In this cohort, suboptimal restoration of L4-S1 lordosis was associated with higher rates of adjacent segment disease and subsequent revisions, thus highlighting the importance of restoring sagittal alignment in degenerative spine surgery.

Level of Evidence:
III
The impact of high-fat, obesogenic diets on brain volume in a commercially available mouse model of fatty liver disease
Authors: Jiang Li , Elsaid Salaheldeen , Zhan Cindy , Li Xin , Xu Su , Tee Sui Seng 
Published: September 2024

ABSTRACTThe obesity pandemic poses significant health challenges, despite recent advancements in weight loss medications. Mouse models fed obesogenic diets serve as invaluable tools for dissecting the pleiotropic mechanisms underlying weight gain. Here, we utilize these models to analyze brain morphometrics using MRI techniques, inspired by similar findings in human studies linking obesity to brain volume changes. We hypothesize that the mouse model of obesity will exhibit brain volume alterations akin to those observed in obese humans, potentially shedding light on the neurological implications of obesity. To test our hypothesis, mice were provided free access to either regular chow or a diet consisting of high fat and high sugar and MRI scans for total brain volumes as well as volumes of specific brain regions were estimated and compared between obese and control mice. We found that obesogenic diets resulted in ∼13% greater weight gain compared to control chow diets. MRI brain scans revealed reduced total brain volume in obese mice that trended towards significance. In contrast, analysis of specific brain volumes showed an increase in neocortical regions of obese mice, that were significant when compared to controls. In conclusion, diet-induced obesity mouse models are a readily available avatar for studying the obesity epidemic, with significant increases in body weight within a reasonable timeframe. While weight gain among individual mice fed obesogenic diets showed some variability, MRI brain scans were able to reveal significant differences, especially within different anatomical regions of the brain.
Clinical Utility and Outcomes of Targeted Next-Generation Sequencing in Pediatric Respiratory Tract Infections: A Nine-Month Retrospective Study at a North Chinese Hospital
Authors: Wang Lixiang , Zhong Hui , Yang Lexia , Yang Xue 
Published: September 2024

AbstractBackground/ObjectivesChildren are at increased risk for respiratory tract infections (RTIs) due to their developing pulmonary functions and immune systems, highlighting the necessity of accurate and rapid pathogen diagnostic methods.MethodsIn this study, 940 pediatric hospitalized patients with RTIs were included to evaluate the clinical utility and outcomes of 107-pathogen targeted next-generation sequencing (tNGS) panel by comparing it with CMTs.ResultsOur study demonstrated that tNGS exhibited significantly higher sensitivity in pathogen detection compared to CMTs, with a detection rate of 91.38%. tNGS was capable of identifying a broader range of pathogens, including low-abundance and RNA viruses frequently missed by CMTs, and it was able to detect mixed infections, whereas CMTs typically identified only a single pathogen. Treatment adjustments based on tNGS results led to clinical improvements in the majority of patients, with 35.32% experiencing escalated treatment plans and 29.04% experiencing de-escalated treatment plans. Additionally, the analysis revealed significant variations in pathogen prevalence across different age groups and seasons, highlighting the need for tailored diagnostic, treatment, and prevention strategies.ConclusionsThe findings highlight the potential of tNGS to improve clinical outcomes in pediatric RTIs by providing more accurate and comprehensive pathogen detection.
Improved precision oncology question-answering using agentic LLM
Authors: Das Rangan , Maheswari K , Siddiqui Shaheen , Arora Nikita , Paul Ankush , Nanshi Jeet , Udbalkar Varun , Sarvade Apoorva , Chaturvedi Harsha , Shvartsman Tammy , Masih Shet , Thippeswamy R , Patil Shekar , Nirni S S , Garsson Brian , Bandyopadhyay Sanghamitra , Maulik Ujjwal , Farooq Mohammed , Sengupta Debarka 
Published: September 2024

ABSTRACTThe clinical adoption of Large Language Models (LLMs) in biomedical research has been limited by concerns regarding the quality, accuracy, and reliability of their outputs, particularly in precision oncology, where clinical decision-making demands high precision. Current models, often based on fine-tuned foundational LLMs, are prone to issues such as hallucinations, incoherent reasoning, and loss of context. In this work, we present GeneSilico Copilot, an advanced agent-based architecture that transforms LLMs from simple response synthesizers to clinical reasoning systems. Our approach is centred around a bespoke ReAct agent that orchestrates a suite of specialized tools for asynchronous information retrieval and synthesis. These tools access curated document vector stores containing clinical treatment guidelines, genomic insights, drug information, clinical trials, and breast cancer-specific literature. To leverage large context windows of current LLMs, we implement a hybrid search strategy that prioritizes key information and dynamically integrates summarized content, reducing context fragmentation. Incorporating additional metadata further allows for precise, transparent and evidence-backed reasoning at each step of the thought process. The system ensures that at every stage, the agent can synthesize meaningful, context-aware observations that contribute to a coherent and comprehensive final response that aligns with clinical standards. Evaluations on real-world breast cancer cases show that GeneSilico Copilot significantly improves response accuracy and personalization. This system represents a critical advancement toward making LLMs clinically deployable in precision oncology and has potential applications in broader medical domains requiring complex, data-driven decision-making.
Drinking motives and alcohol sensitivity mediate multi-dimensional genetic influences on alcohol use behaviors
Authors: Savage Jeanne E. ,   Spit for Science Working Group, Dick Danielle M. , Posthuma Danielle 
Published: September 2024

AbstractBackgroundGenetic influences account for a substantial proportion of individual differences in alcohol use behaviors (AUBs). However, multiple distinct sets of genes are linked to different AUBs, which may explain their dramatic variability in risk factors and manifestations. In this study, we explore whether intermediate neurobiological traits and alcohol-related cognitions mediate the relationship between polygenic scores (PGS) and multiple AUBs, with the aim to better understand processes captured by different genetic profiles.MethodsUsing results from prior genome-wide association studies, we derived PGS for 6 AUBs in participants from Spit for Science, a longitudinal study of college students in the U.S. (n=4,549). Self-report measures included personality traits, alcohol expectancies, drinking motivations, and alcohol sensitivity measures as well as drinking frequency, drinking quantity, alcohol use disorder (AUD) symptoms, and maximum drinks in 24 hours. Using linear regression and multiple mediation models, we investigated the direct and indirect effects of PGS on AUBs.ResultsIn univariable regression results, PGSs indexing broad AUB dimensions such as drinks per week (DPW) and AUD predicted higher levels of sensation-seeking and multiple drinking motives, whileBeerPrefPGSs (indexing a variable pattern of alcohol problems associated with a preference for beer) predicted higher negative urgency and lower alcohol sensitivity. Mediational models indicated strong direct and indirect effects of DPW PGSs on multiple AUBs via social/enhancement drinking motives and alcohol sensitivity, indirect effects of AUD PGSs on AUD symptoms via coping motives, and indirect effects ofBeerPrefPGS on all AUBs via the joint effect of mediators including alcohol sensitivity.ConclusionsThese findings provide initial evidence that the genetic influences on different AUBs are associated with and partially mediated by intermediate neurobiological and cognitive factors, which may be more amenable to intervention. Greater focus on drinking motives and alcohol sensitivity is warranted in genetic research, as well as attention to the heterogeneous pathways linking genes to alcohol use outcomes.
Improving ALS Detection and Cognitive Impairment Stratification with Attention-Enhanced Deep Learning Models
Authors: Xia Yuqing , Gregory Jenna M , Waldron Fergal M , Spence Holly , Vallejo Marta 
Published: September 2024

AbstractAmyotrophic lateral sclerosis (ALS) is a fatal neurological disease marked by motor deterioration and cognitive decline. Early diagnosis is challenging due to the complexity of sporadic ALS and the lack of a defined risk population. In this study, we developed Miniset-DenseSENet, a convolutional neural network combining DenseNet121 with a Squeeze-and-Excitation attention mechanism, using 190 autopsy brain images from the Gregory Laboratory at the University of Aberdeen. The model distinguishes ALS patients from controls with 97.37% accuracy and detects cognitive impairments, a critical but underdiagnosed feature of ALS. Miniset-DenseSENet outperformed other transfer learning models, achieving a sensitivity of 1 and specificity of 0.95. These findings suggest that integrating transfer learning and attention mechanisms into neuroimaging can enhance diagnostic accuracy, enabling earlier ALS detection and improving patient stratification. This model has the potential to guide clinical decisions and support personalized therapeutic strategies.
Personal Involvement with Celiac Disease as a Motive for Research among Celiac Disease Researchers
Authors: Banegas Marcela , Sprague Rebecca , Vigna Carolina , González Jose Emmanuel , Flores-Marín David , Palacios Cesar , Silvester Jocelyn , Therrien Amelie 
Published: September 2024

AbstractIntroductionWe investigated the frequency of personal involvement with celiac disease (CeD) among CeD researchers and their motive to pursue CeD research, compared to researchers in inflammatory bowel disease (IBD) or type 1 diabetes (T1D) research.MethodsAn online survey was sent to CeD, IBD and T1D researchers.Results42% of CeD researchers had an involvement with their research interest, which was similar to T1D (51%) and significantly higher than the IBD respondents (27%, p<0.02).DiscussionPersonal involvement is common among the CeD researchers. Personal involvement with the disease may be beneficial when conducting patient-oriented research.
Relationship between Retinal Vessels and OCT-Derived Retinal Neural Parameters
Authors: Yusufu Mayinuer , Weinreb Robert N. , Kang Mengtian , Vingrys Algis J. , Shang Xianwen , Zhang Lei , Shi Danli , He Mingguang 
Published: September 2024

AbstractObjectiveTo investigate structural relationships between retinal vasculometry derived from color fundus photography (CFP) and neural parameters obtained from Optical Coherence Tomography (OCT) scans and validate their causal relationships.DesignCross-sectional studyParticipantsParticipants with fundus photographs data and OCT data in the UK Biobank cohort studyMethodsWe used the Retina-based Microvascular Health Assessment System (RMHAS) to extract retinal vascular measurements in the 6*6mm area centered on the macular region. OCT parameters were available from the UK Biobank. First, pairwise correlations between individual retinal layers and vascular parameters were investigated. Canonical correlation analysis (CCA) was then used to examine associations between sets of variables. Lastly, bidirectional two-sample Mendelian randomization was employed to investigate potential causal relationships.Main Outcome MeasuresMeasurements of retinal vascular network and neural layersResultsData from 67,918 eyes of 43,029 participants were included. The Ganglion Cell-Inner Plexiform Layer (GC-IPL) thickness showed the strongest correlations with vascular Density and Complexity (r=0.199 for arterial Vessel Area Density and r=0.175 for Number of Segments). The Inner Nuclear Layer (INL) thickness showed positive correlations with Width (r=0.122) and Vessel Area Density (artery) (r=0.127). Mendelian randomization analysis indicated bidirectional causal relationships between retinal vascular features and layer thicknesses. Genetically predicted higher Vessel Density was associated with increased thickness across various retinal layers, with the strongest effect on Inner Segment/Outer Segment + Photoreceptor Segment thickness (standardized effect size 1.50, p<0.001). Genetically predicted increases in retinal layer thicknesses, particularly the Outer Plexiform Layer, were linked to higher Vessel Density (standardized effect size 0.45, p=0.002) and Fractal Dimension (standardized effect size 0.48, p<0.001).ConclusionsThe positive associations of macular thickness with vascular Density and Caliber measurements were mainly attributable to their associations with GC-IPL and INL. Multidimensional relationships revealed by CCA revealed a complementary nature between the two sets of parameters, highlighting their value as a composite biomarker. Mendelian Randomization uncovered a bidirectional causal relationship that should provide insights into novel therapeutic approaches targeting both vascular and neuronal components.
Engineered antibodies targeted to bacterial surface integrate effector functions with toxin neutralization to provide superior efficacy against bacterial infections
Authors: Adhikari Rajan P. , Alem Farhang , Kemboi Daniel , Kanipakala Tulasikumari , Sherchand Shardulendra P. , Kailasan Shweta , Purcell Bret K. , Heine Henry S. , Russell-Lodrigue Kasi , Etobayeva Irina , Howell Katie A. , Vu Hong , Shulenin Sergey , Holtsberg Frederick W. , Roy Chad J. , Hakami Ramin M. , Nelson Daniel C. , Aman M. Javad 
Published: September 2024

AbstractAnti-bacterial monoclonal antibody (mAb) therapies either rely on toxin neutralization or opsonophagocytic killing (OPK). Toxin neutralization protects the host from toxin-induced damage, while leaving the organism intact. OPK inducing antibodies clear the bacteria but leave the released toxins unencountered. Infection site targeted anti-toxin antibodies (ISTAbs) that we report here addresses this binary paradigm by combining both functionalities into a single molecule. ISTAbs consist of cell wall targeting (CWT) domains of bacteriophage endolysins fused to toxin neutralizing mAbs (IgG). CWT governs specific binding to the surface of bacteria while the IgG variable domain neutralizes the toxins as they are released. The complex is then cleared by phagocytic cells. As proof of concept, we generated several ISTAb prototypes targeting major toxins from two Gram-positive spore forming pathogens that have a high clinical significance;Clostridium difficile, causative agent of the most common hospital-acquired infection, andBacillus anthracis, a Category A select agent pathogen. Both groups of ISTAbs exhibited potent toxin neutralization, binding to their respective bacterial cells, and induction of opsonophagocytosis. In mice infected withB. anthracis, ISTAbs exhibit significantly higher efficacy than parental IgG in both pre- and post-challenge models. Furthermore, ISTAbs fully protected againstB. anthracisinfection in a nonhuman primate (NHP) aerosol challenge model. These findings establish that as a platform technology, ISTAbs are broadly applicable for therapeutic intervention against several toxigenic bacterial pathogens.
Sport Specialization, Injury and Illness: A Prospective Study of Elite Female Adolescent Soccer Players
Authors: Watson Andrew , Haraldsdottir Kristin 
Published: September 2024

ABSTRACTContextAlthough considerable cross-sectional evidence exists regarding the association between sport specialization and injury, sport-specific, prospective research is lacking. Similarly, sport specialization is associated with impairments in sleep and subjective well-being in youth athletes, but it is unknown whether this increases the risk of illness.ObjectiveTo determine the relationship between sport specialization status and in-season injury and illness risk in elite female adolescent soccer players.DesignProspective Cohort StudySettingPre-season evaluation of maximal aerobic capacity (VO2max) and sport specialization, and in-season self-reporting of daily training load (session-rating of perceived exertion), injury and illness resulting in lost sport participation time.Participants80 female youth soccer players (ages 13-18) from a local youth soccer organization.Main outcome measuresSport specialization status, injury and illness incidence during two 4-month competitive soccer seasons. Athletes were considered specialized if they participated in soccer exclusively versus multiple sports during the year. Mixed effects logistic regression models were used to individual injury and illness (yes/no) during the study period, using sport specialization, age, and training load as fixed effects and individual athlete as a random effect.ResultsSpecialized (n=46) athletes did not differ from non-specialized (n=34) athletes with respect to age, preseason physical activity, VO2maxor in-season training load (all p>0.05). No difference was seen in the proportion of individuals from each group that reported an in-season injury (specialized = 19% v 17%, p=0.83) or illness (40% v 38%, p=0.82). After adjusting for age and training load, the individual injuries (OR= 0.86 [0.26, 2.8], p=0.81) and illnesses were not significantly predicted by specialization (OR= 1.06 [0.45, 2.5], p=0.89).ConclusionsAfter adjusting for age and training load, sport specialization status was not associated with in-season injury or illness risk in elite female soccer players.Key pointsPrior research regarding the associations between sport specialization and health outcomes has been primarily cross-sectional and failed to account for the confounding role of training load.Among elite adolescent female soccer players with similar pre-season physical activity levels in-season training loads, sport specialization was not associated with injury or illness incidence across two competitive seasons.