bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data-Driven Feed Optimization for Sustainable Aquaculture through Integrated Omics Analysis and Two-stage Bayesian optimization
Authors: Terayama Kei , Soma Satoshi , Furuita Hirofumi , Shimizu Tomohito , Iwasaki Takashi , Sakata Kenji , Akagi Ken-ichi , Asakura Taiga , Sanda Tetsuya , Yamaguchi Tomofumi , Fujikura Yuji , Hongo Yuki , Shima Hideaki , Yokota Hideo , Kikuchi Jun , Yasuike Motoshige , Mekuchi Miyuki 
Published: January 2025

AbstractIn aquaculture and livestock farming, developing feed that promotes efficient growth while minimizing environmental impact is crucial for sustainability. We developed a data-driven feed optimization system (DFOS) that integrates omics analysis with machine learning-based optimization technologies. First, DFOS employed Bayesian optimization (BO) to identify the optimal proportions of proteins and lipids, which are crucial feed components. Simultaneously, omics analysis was conducted to assess the physiological response of the targets to a given feed and identify key dietary components essential for growth. Next, BO was used to efficiently modify the combination and proportion of the specific additives identified in the first stage. We demonstrated the efficacy of DFOS by applying it to develop a new feed for the high-demand leopard coral grouper (Plectropomus leopardus) in Southeast Asia. This system provides an efficient data-driven framework for feed optimization across aquaculture and livestock, contributing significantly to more sustainable and productive farming practices.
Effectiveness of Computer-Aided interventions and Virtual Reality in Wrist and Hand rehabilitation: a Scoping Review Protocol
Authors: Tonial Nicola , Scalise Valentina , Maselli Filippo , Benedettini Elena , Pili Michela , Santandrea Sheila 
Published: January 2025

AbstractBackgroundTo date, advances in the technological and medical fields have increased the application of virtual reality tools, smartphone apps, and computer-aided therapy in clinical and rehabilitation settings. These tools have been shown to enhance patient involvement and improve self-efficacy in their treatment pathways. However, in orthopaedic and rheumatology fields, studies remain limited, and comprehensive reviews providing an exhaustive overview are lacking.ObjectiveThe purpose of this Scoping Review is to provide a general overview of the use of virtual reality and computer aided equipment in musculoskeletal and rheumatological rehabilitation of the wrist and hand, outlining the main types of instruments used, how they are applied, describing any gaps in the literature and possible future developments on the use of VR and PC-aided treatments.Eligibility criteriaThis study will contain articles that included a population with hand and/or wrist deficits attributable to musculoskeletal and/or rheumatological pathologies or traumas and who undertook a rehabilitation programme focusing on virtual reality or computer aided devices. All studies with subjects suffering from neurological pathologies, such as stroke or Parkinson’s disease, will be excluded.MethodsThis scoping review will be carried out following the guidance of the Joanna Briggs Institute (JBI). Articles will be searched in databases such as PubMed (Medline), Cochrane central, Scopus, Pedro and CINHALcomplete from December 2024. Additional studies will be selected through grey literature, such as Google Scholar. Article selection and data mining will be done by three reviewers, while a fourth will resolve any discrepancies or disputes. No restrictions on type of publication will apply; only articles written since 2014 and written in Italian or English will be considered.Ethics and disseminationEthical approval is unnecessary for this study.
Prevalence and drug-resistance patterns of methicillin-resistantStaphylococcus aureusand extended-spectrum β-lactamase producingEnterobacteriaceaeamong raw vegetables
Authors: Ahmed Duressa Shafi , Gebre Alemitu Beyene , Erancho Hadbacho Tsegaye , Shinato Habtamu Teshale , Ormago Moges Desta 
Published: January 2025

AbstractBackgroundAntimicrobial resistance is a top global public health and development threat. Antibiotic-resistant bacteria in food items, such as vegetables, have become a public health issue. Contamination of vegetables sold in various places can cause foodborne illnesses in many countries, including Ethiopia, and affect the health of consumers. Many bacterial pathogens are now resistant to multiple drugs. In recent years, several multi-drug resistant bacterial pathogens with epidemiological significance have emerged, such as MRSA and ESBL-PE.MethodsA cross-sectional study was conducted in Aroge Gebeya Market, Hawassa City, from March to May 2024. Six types of raw vegetables with a total of 216 (6×36) were collected. Identification of methicillin-resistantStaphylococcus aureusand extended-spectrum β-lactamase producingEnterobacteriaceaeand drug resistance patterns were done by using the Kirby-Bauer disk diffusion method. Data on sociodemographic variables and hygiene practices were collected using semi-structured questionnaires on Kobo Toolbox Software and imported to SPSS Software Version 29.0.1 for analysis.ResultsThe overall prevalence of MRSA and/or ESBL-PE among vegetables was 18.1% (39/216). Among the isolates, 56.9% (91/160) were MDR, 29.2% (14/48) were MRSA, and 24.1% (27/112) were ESBL producers. The most frequently detected isolates wereS. aureus30.0% (48/160),Enterobacter spp.15.6% (25/160),Citrobacter spp.15.0% (24/160),E. coli10.6% (17/160),Salmonella spp.10.0% (16/160) andKlebsiella spp.8.1% (13/160). The highest frequency of bacterial isolates was found in tomatoes 21.9% (35/160), kale 18.1% (29/160), and lettuce 16.9% (27/160). Vegetables bought from vendors with untrimmed nails were significantly more likely to have a higher prevalence of MRSA and/or ESBL-PE compared to those from vendors with trimmed nails (AOR = 4.123; 95% CI: 1.681 - 10.109, p = 0.002).ConclusionThis study found that vegetables were notable for the presence of MDR bacteria, specifically ESBL-PE and MRSA. Consequently, we strongly recommend that local health authorities develop and implement effective control strategies to mitigate these resistant bacteria among vegetables.
Proteomic associations with fluctuation and long-term changes in BMI: A 40-year follow-up study
Authors: Obeso Alvaro , Drouard Gabin , Palviainen Teemu , Wang Xiaoling , Ollikainen Miina , Silventoinen Karri , Kaprio Jaakko 
Published: January 2025

AbstractIntroductionWhile some studies have explored associations between weight change and blood proteins, most have been intervention-based, offering limited insight into proteomic associations with long-term weight gain. It remains unclear whether plasma proteins are related to BMI fluctuation over time. This study investigates associations of long-term BMI changes and fluctuations with over 1,000 plasma proteins involved in cardiometabolic and inflammation functions.Data and MethodsThe study included 304 Finnish adult twins (117 men) born before 1958 from the Older Finnish Twin Cohort, with BMI data spanning five time points (1975, 1981, 1990, 2011, and 2012–2014). Proteomic data were derived from blood samples collected at the last BMI measurement. Linear mixed-effects models analyzed individual BMI trajectories, producing intercepts (baseline BMI) and slopes (BMI change rates). BMI fluctuation was calculated as the average squared deviation from expected BMI across time points. Associations between BMI changes/fluctuation and (i) 1,231 plasma proteins related to cardiometabolic and inflammatory functions and (ii) polygenic risk scores for BMI (PRSBMI), as well as interaction effects between PRSBMIand baseline BMI on protein-BMI relationships were studied. Within-pair analyses using monozygotic twins were conducted to account for shared confounding factors.ResultsA total of 135 proteins were associated with changes in BMI over 40 years, while 17 proteins were linked to fluctuation in BMI: 12 associations (10 with BMI changes and 2 with fluctuation) remained significant in within-twin pair analyses. PRSBMIassociated with BMI changes but not with fluctuations. PRSBMI-protein interactions explaining BMI changes or fluctuation was found, though a single interaction between the CD72 protein and baseline BMI was observed.ConclusionThis study highlights significant associations between plasma proteins and long-term BMI changes and fluctuations, with no evidence of PRSBMI-protein interactions influencing BMI trends. These findings underscore the substantial role of environmental factors in shaping proteome-BMI associations over adulthood.
Critically ill patients with a reverse blood pressure dipping phenotype at increased risk for delirium and death
Authors: El Jamal Nadim , Brooks Thomas G. , Mrcela Antonijo , Genuardi Michael V. , FitzGerald Garret A. , Skarke Carsten 
Published: January 2025

AbstractBackgroundThe ICU environment is disruptive to a patient’s biological rhythms where sleep-wake cycles are often desynchronized from the environmental day-night changes. This puts patients at increased risk to develop delirium with consequent fiscal pressure for the health care system. An underappreciated dimension is how time-specific patient phenotypes in the critical care environment relate to clinical outcomes. We set out to analyze how rhythmic components (or the lack thereof) in physiological data streams sampled at high resolution in the ICU were associated with the future incidence of delirium and death. To offer cues for further interrogation into mechanism and risk prognosis, we examined differences in 24-hour fluctuations of clinical labs in ICU patient populations at risk.MethodsRhythmic components using dipping ratios and JTK_CYCLE statistics were derived from 24-hour blood pressure and heart rate measurements available from ICU patient admissions recorded in the MIMIC IV database. Logistic adjusted regression models assessed the association between disrupted vital sign rhythms and the future incidence of delirium during the same hospital admission and death. Aggregation of numeric clinical lab measurements across the first 24 hours from all patient admissions allowed modelling of rhythmic patterns and subsequent association studies to link potential biochemical mechanisms to perturbed vital sign rhythms and adverse ICU outcomes.ResultsPatients with reverse blood pressure dipping were at a 40% higher risk to have a diagnosis of delirium (Odds Ratio: 1.40, 95% CI: 1.14-1.72) and a 13% increased risk of death (Odds Ratio: 1.13, 95% CI: 1.02-1.26). Compared to the patient population with nocturnal blood pressure dip, reverse dippers showed 24-hour biochemistry profiles suggestive of altered circadian programs specifically in clinical parameters of renal, metabolic, and hemostatic function.ConclusionsReverse blood pressure dipping can be an early sign for the future development of delirium in the ICU and is accompanied by disrupted biorhythms across multiple organ systems. Dampened and reversed heart rate and blood pressure rhythms are associated with a higher risk for death in ICU patients. Considering the inclusion of these risk factors in preventive care may improve patient outcomes and reduce burden on the health care system.
Phylogeny-based estimates of epidemic population substructure outperform time series approaches
Authors: Spencer Julie A. , Goldberg Emma E. , Alexander Prescott C. , Del Valle Sara Y. 
Published: January 2025

AbstractImproving infectious disease models plays a crucial role in mitigating global health impacts. Population-level models have been essential for understanding and anticipating impacts of infectious diseases, but their accuracy has often been limited due to changing environments, rapid pathogen evolution, and insufficient access to detailed transmission data. In particular, due to the lack of granular transmission data, many epidemiological models assume homogeneous disease transmission rather than acknowledge differences between groups within the host population. To address this gap, we conducted a simulation study to assess the potential for inferring group-structured viral transmission dynamics from phylogenetic data and to demonstrate how age structure can be incorporated in case projections. Using a synthetic dataset of 800 age-structured viral phylogenies and their associated case time series, we estimated transmission rates within and between age groups. Our results show that the estimates derived from phylogenies are more accurate than those from case counts alone, although both approaches enabled recovery of age-specific transmission differences. These results suggest that viral phylogenies and case-count time series each provide valuable data that can improve our understanding of population-level disease dynamics, ultimately contributing to more accurate and effective models for informing public policy and reducing disease burden.
Patient Reported Tolerance of 90 Days of Pre-Operative Endocrine Therapy: Results from the POWER Trial
Authors: Millard Trish , Turkheimer Lena , Schlefman Jenna , Petroni Gina , Brighton David , Showalter Shayna 
Published: January 2025

AbstractBackgroundProspective randomized data supports radiation omission in women ≥ 65 years who take adjuvant endocrine therapy (AET) following breast-conserving surgery. Many patients who omit radiation stop AET early due to side effects. In the POWER trial, a prospective single-arm study, patients took 90 days of pre-operative endocrine therapy (pre-ET) to assess tolerance before making adjuvant treatment decisions. We hypothesized that patient-reported outcomes (PROs) during pre-ET would be heterogeneous and that 90 days was sufficient time for symptoms to develop.Patients and MethodsPRO data from POWER trial participants was obtained before, during, and after pre-ET, including health-related quality of life (HRQoL), depression, and ET symptoms using the EORTC-QLQ, CESD-R, and BCPT-SCL tools. PRO assessments were further analyzed after stratifying patients by high or low perceived sensitivity to medicine (PSM).ResultsPre-ET PROs were assessed for 75 participants. The majority (73.3%) reported symptoms during pre-ET. Only 10.7% had symptoms severe enough to stop pre-ET before 90 days. Vasomotor (42.7%) and musculoskeletal (41.3%) symptoms were the most common. HRQoL was preserved for 66.6% participants. Patients with high PSM had more ET side effects.ConclusionPatients developed similar side effects during pre-ET as those typically seen with AET. PROs and the impact of pre-ET on HRQoL were patient-dependent. A 90-day course of pre-ET is sufficient for patients to develop symptoms reflective of long-term AET. Future analyses will assess the association of pre-ET PROs with AET initiation and adherence.
Modeling the Economic Impact of a CIZ1B Biomarker Blood Test for Lung Cancer Screening in High-Risk Populations
Authors: Hinkel Jennifer , Kavade Rutuja , Joshi Madhura 
Published: January 2025

AbstractBackgroundThis study evaluates the economic implications of incorporating a CIZ1B biomarker blood test into lung cancer screening protocols for Medicare-eligible high-risk populations. Despite the proven mortality reduction benefits of low-dose computed tomography (LDCT), its adoption remains low. Barriers such as access disparities, logistical challenges, and the high rate of false positives necessitating invasive follow-up limit LDCT’s broader acceptance. The addition of a blood-based biomarker test like CIZ1B could address these barriers by enhancing screening precision, reducing unnecessary diagnostic procedures, and increasing screening participation.MethodsAn economic model was developed to assess the cost savings and public health benefits of integrating CIZ1B in three scenarios: (1) sequential screening with LDCT following a positive biomarker test; (2) using CIZ1B to confirm LDCT-positive cases; and (3) an expanded screening paradigm where CIZ1B reduces barriers, increasing overall screening uptake. The model incorporates Medicare reimbursement rates, prevalence and screening sensitivity data, and cost estimates adjusted for inflation.ResultsResults indicate that integrating CIZ1B testing can yield net savings in the range of $500 Million by avoiding unnecessary biopsies and enabling earlier lung cancer detection and treatment. The expanded screening scenario projects additional savings through higher participation rates. This study highlights the potential of the CIZ1B biomarker to address critical challenges in lung cancer screening, reduce healthcare costs, and improve outcomes for high-risk populations.
Interferon Dependent Immune Memory during HSV-1 Neuronal Latency Results in Increased H3K9me3 and Restriction of Reactivation by ATRX
Authors: Whitford Abigail L. , Auguste Gaelle , Francois Alison K. , Boutell Chris , Miller Clint , Dremel Sarah , Cliffe Anna. R 
Published: January 2025

AbstractHerpes simplex virus-1 (HSV-1) establishes a lifelong latent infection in neurons and reactivation from this latent state is the cause of recurrent oral and ocular infections, herpes simplex keratitis, and encephalitis. Neuronal conditions during initial HSV-1 infection have a long-term impact on latency, modulating how responsive latent genomes are to reactivation and, therefore, their ability to cause disease. Type I interferon (IFNα) exposure during initial infection results in promyelocytic leukemia nuclear-body (PML-NB) formation and a more restrictive form of HSV-1 latency. Here we demonstrate that IFNα induced PML-NBs recruit histone chaperones to the viral genome and promote the deposition of the repressive heterochromatin mark, histone H3 lysine 9 tri-methylation (H3K9me3), and its reader, ATRX (alpha-thalassemia/mental retardation, X-linked). This work reveals the mechanism by which immune signaling during initial infection induces an epigenetic memory on HSV-1 genomes that is maintained during latency and inhibits reactivation. ATRX is highly abundant in neurons and is essential for maintaining cellular heterochromatin during neuronal stress. Here we find that ATRX prevents transcription, and subsequent reactivation, from H3K9me3-bound latent genomes by remaining associated with viral chromatin following stress-induced phosphorylation of histone H3. This indicates that H3K9me3-associated viral genomes are refractory to reactivation when read by ATRX. This work demonstrates that ATRX acts as a neuronal restriction factor against HSV-1 reactivation, elucidating a new potential target for inhibiting HSV-1 reactivation and subsequent human disease.
KV1.8 (Kcna10) potassium channels enhance fast, linear signaling in vestibular hair cells and facilitate vestibulomotor reflexes and balance
Authors: Martin Hannah R. , Verdone Brandie Morris , López-Ramírez Omar , Green Merrill , Silvian Dana , Scott Emily , Cullen Kathleen E. , Eatock Ruth Anne 
Published: January 2025

AbstractVestibular hair cells (HCs) faithfully and rapidly detect head motions and gravity, driving motor reflexes that stabilize balance and gaze during locomotion. With the transition from water to land, the amniote vestibular inner ear added type I HCs, which differ from amniote type II HCs and anamniote HCs by their large calyx afferent synapse, non-quantal afferent transmission, and a large, low-voltage-activated K+conductance (gK,L). We recently showed that both gK,Land the major type II K+conductances (A-type and delayed rectifier) require KV1.8 (Kcna10) subunits. Here we compared KV1.8-null (Kcna10−/−) and control animals to see how KV1.8 affects function as measured by receptor potentials and nonquantal postsynaptic potentials evoked by direct hair bundle motions, and by vestibulomotor behaviors. Recordings were taken from extrastriolar zones of the utricle. In both HC types, KV1.8 affected receptor potentials by reducing response time and gain, increasing dampening, and expanding the frequency bandwidth toward high frequencies. Effects are most prominent in type I HCs: lowpass corner frequencies of receptor potentials inKcna10−/−HCs of both types were ∼20 Hz,vs. ∼400 Hz in control type I and ∼70 Hz in control type II. We recorded nonquantal postsynaptic potentials from extrastriolar calyces, and found that the synaptic transfer function had lower gain and greater phase lag inKcna10−/−mice. In behavioral tests,Kcna10−/−mice had vestibular-ocular reflexes with different response dynamics at low frequencies, impaired performance on a narrow balance beam, abnormal body posture and abnormal head motions in water and on land, and also rarely assumed bipedal stances. These vestibulomotor deficits inKcna10−/−mice likely reflect the changes noted in HCs, where KV1.8 expression is concentrated; that is, slower signaling of high-frequency head motions byKcna10−/−HCs fails to fully stabilize body and head position during locomotion. Thus, gK,L(KV1.8) contributes to fast signal transmission in the amniote vestibular inner ear and supports improved performance on challenging vestibulomotor tasks.Graphical Abstract
DeepSynBa: Actionable Drug Combination Prediction with Complete Dose-Response Profiles
Authors: Kuru Halil Ibrahim , Zhang Haoting , Rattray Magnus , Ek Carl Henrik , Cicek A. Ercument , Tastan Oznur , Milo Marta 
Published: January 2025

AbstractMotivationMany cancer monotherapies demonstrate limited clinical efficacy, making combination therapies a relevant treatment strategy. The extensive number of potential drug combinations and context-specific response profiles complicates the prediction of drug combination responses. Existing computational models are typically trained to predict a single aggregated synergy score, which summarises drug responses across different dosage combinations, such as Bliss or Loewe scores. This oversimplification of the drug-response surface leads to high prediction uncertainty and limited actionability because these models fail to differentiate between potency and efficacy.ResultsWe introduce DeepSynBa, an actionable model that predicts the complete dose-response matrix of drug pairs instead of relying on an aggregated synergy score. This is achieved by predicting parameters describing the response surface as an intermediate layer in the model. We evaluated DeepSynBa on the NCI-ALMANAC dataset, which comprises nearly 300,000 drug pair–cell line combinations. DeepSynBa outperforms the state-of-the-art methods in the dose-response matrix prediction task across multiple evaluation scenarios, including testing on novel drug combinations, cell lines, and drugs, across nine different tissue types. We also show that DeepSynBa yields reliable synergy score predictions. More importantly, DeepSynBa can predict drug combination responses across different dosages for untested combinations. The intermediate dose-response parameter layer allows for separating efficacy from potency, which informs the selection of dosage ranges that optimise efficacy while limiting off-target toxicity in experimental screens. The predictive capability and the downstream actionability make DeepSynBa a powerful tool for advancing drug combination research beyond the limitations of the current approaches.AvailabilityThe code and the dataset for DeepSynBa are available athttps://github.com/hikuru/DeepSynBa.Contactmarta.milo@astrazeneca.comorotastan@sabanciuniv.edu