bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does Condylar Morphology Affect Maxillary Repositioning in Bimaxillary Orthognathic Surgery?
Authors: Takahara Namiaki , Tomomatsu Nobuyoshi , Kachi Hirokazu , Iwasaki Takuya , Maruta Noboru , Yoda Tetsuya 
Published: May 2024

This study aimed to measure the association between condylar morphology and a measure of the maxillary centroid following bimaxillary surgery using mandibular-dependent splints. The study included skeletal Class III and Class II malocclusion patients, excluding those with facial asymmetry. Based on computed tomography imaging patients were characterized into normal or abnormal temporomandibular joint (TMJ) groups. A computer-aided design/computer-aided manufacturing splints were fabricated to reposition the maxilla in Le Fort I osteotomy. The primary outcome measure was the absolute differences between the maxillary centroid’s the planned and actual postoperative positions calculated by superimposing computed tomography scans. The secondary outcome was the measure of other variations in linear and angular maxilla discrepancies. The demographic covariates included the age and sex of the patients. The operative covariates consisted of the dentofacial deformity and the planned movement of the maxilla. Seventy patients with skeletal maxillofacial deformities were included for analysis: 44 patients in the normal and 26 in the abnormal TMJ group. The average maxillary misalignment was 1.04±0.48 mm in the normal and 1.53±0.63 mm in the abnormal TMJ group (P<0.001). A statistically significant relationship existed between the discrepancies of the maxillary centroid and dentofacial deformity (η=0.656, P<0.001). These findings suggest an increased propensity for maxillary malposition in skeletal Class II patients. Furthermore, condylar morphology is a significant prognostic factor influencing maxillary repositioning errors in bimaxillary surgery with mandibular-dependent splints.
Microfluidic platform for microbial spore germination studies in multiple growth conditions
Authors: Bernier Léa S. , Estoppey Aislinn , Bindschedler Saskia , Stan Guy-Bart , Junier Pilar , Stanley Claire E. 
Published: May 2024

AbstractSpores are highly resistant dormant cells, adapted for survival and dispersal, that can withstand unfavourable environmental conditions for extended periods of time and later reactivate. Understanding the germination process of microbial spores is important in numerous areas including agriculture, food safety and health, and other sectors of biotechnology. Microfluidics combined with high-resolution microscopy allows to study spore germination at the single-cell level, revealing behaviours that would be hidden in standard population-level studies. Here, we present a microfluidic platform for germination studies where spores are confined to monolayers inside microchambers, allowing the testing of four growth conditions in parallel. This platform can be used with multiple species, including non-model organisms, and is compatible with existing image analysis software. In this study, we focused on three soil dwellers, two prokaryotes and one fungus, and revealed new insights into their germination. We studied endospores of the model bacteriumBacillus subtilisand demonstrated a correlation between spore density and germination in rich media. We then investigated the germination of the obligate-oxalotrophic environmental bacteriumAmmoniphilus oxalaticusin a concentration gradient of potassium oxalate, showing that lower concentrations result in more spores germinating compared to higher concentrations. We also used this microfluidic platform to study the soil beneficial filamentous fungusTrichoderma rossicum, showing for the first time that the size of the spores and hyphae increase in response to increased nutrient availability, while germination times remain the same. Our platform allows to better understand microbial behaviour at the single-cell level, under a variety of controlled conditions.One-Sentence SummaryA microfluidic platform developed for spore germination studies in multiple growth conditions provides new insights into the germination of spores at the cellular level from three soil dwellers.
Is the population of the Critically Endangered White-bellied Heron in Namdapha Tiger Reserve, India, declining?
Authors: Menzies Rohan K. , Suryawanshi Kulbhushansingh R. , Naniwadekar Rohit 
Published: May 2024

AbstractThe Critically Endangered White-bellied HeronArdea insignisis a large-bodied, range-restricted, piscivorous bird found in the Himalayan mountains. With fewer than 60 individuals remaining globally, regular monitoring efforts are required to understand the conservation status of this rare species better. Here, we present the results of river surveys from 2017 and 2023-24 for the White-bellied Heron in an important protected area, the Namdapha Tiger Reserve, in Arunachal Pradesh. The encounter rate in 2017 was 0.55 herons per km, however; we did not detect the bird during intensive river sampling in the same stretches in 2023-24. This area within the reserve was once a stronghold for the species and they currently appear to be declining or locally extinct. Given the declines within this Protected Area, the drivers for the same need to be determined. While repeated monitoring of rivers has helped reveal this decline, locating and conserving stretches of river utilised by the remaining individuals away from the core zone is now critical.[Supplementary material for this article can be found at https://doi.org/xxx]
How many segments are enough to biomechanically model the feet? A comparison of inverse kinematics and dynamics in multisegmented foot models
Authors: Nicolescu Julia , Gaudette Logan , Vogel Olivia , Davis Irene S. , Tenforde Adam S. , Troy Karen L. 
Published: May 2024

AbstractMultisegmented foot models (MSFMs) capture kinematic and kinetic data of specific regions of the foot instead of representing the foot as a single, rigid segment. Models differ by the number of segments and segment definitions, so there is no consensus for best practice. It is unknown whether MSFMs yield the same joint kinematic and kinetic data and what level of detail is necessary to accurately measure such values. We compared the angle, moment, and power measurements at the tibiotalar, midtarsal, and metatarsophalangeal joints of four MSFMs using motion capture data of young adult runners during stance phase of barefoot walking and jogging. Of these models, three were validated: Oxford Foot Model, Milwaukee Foot Model, and Ghent Foot Model. One model was developed based upon literature review of existing models: the “Vogel” model. We performed statistical parametric mapping comparing joint measurements from each model to the corresponding results from the Oxford Model, the most heavily studied MSFM. We found that the Oxford Foot Model, Milwaukee Foot Model, Vogel Foot Model, and Ghent Foot Model do not provide the same results. The changes in model segment definitions impact the degrees of freedom in ways that alter the measured kinematic function of the foot, which in turn impacts the kinetic results. We also found that dynamic function of the midfoot/arch may be better captured by MSFMs with a separate midfoot segment. The results of this study capture the variability in performance of MSFMs and indicate a need to standardize the design of MSFMs.
Loss-of-function of ALDH3B2 transdifferentiates human pancreatic duct cells into beta-like cells
Authors: Li Jian , Bode Kevin , Lee Yu-chi , Morrow Noelle , Ma Andy , Wei Siying , da Silva Pereira Jessica , Stewart Taylor , Lee-Papastavros Alexander , Hollister-Lock Jennifer , Sullivan Brooke , Bonner-Weir Susan , Yi Peng 
Published: May 2024

SUMMARYReplenishment of pancreatic beta cells is a key to the cure for diabetes. Beta cells regeneration is achieved predominantly by self-replication especially in rodents, but it was also shown that pancreatic duct cells can transdifferentiate into beta cells. How pancreatic duct cells undergo transdifferentiated and whether we could manipulate the transdifferentiation to replenish beta cell mass is not well understood. Using a genome-wide CRISPR screen, we discovered that loss-of-function of ALDH3B2 is sufficient to transdifferentiate human pancreatic duct cells into functional beta-like cells. The transdifferentiated cells have significant increase in beta cell marker genes expression, secrete insulin in response to glucose, and reduce blood glucose when transplanted into diabetic mice. Our study identifies a novel gene that could potentially be targeted in human pancreatic duct cells to replenish beta cell mass for diabetes therapy.
Canalization and competition: the cornerstone of genetic network’s dynamic stability and evolution
Authors: Yao Yuxiang , Huang Zi-Gang , Pei Duanqing 
Published: May 2024

AbstractGrasping the fundamental dynamic property is a crucial approach for understanding living systems. Here we conduct a comprehensive study into the relationship between regulatory modes and dynamic features of gene networks. Our findings indicate that conditional constraints and competition, corresponding to canalizing and threshold regulating modes respectively, play pivotal roles in driving gene networks towards criticality. Particularly, they effectively rescue biosystems from disordered area as source of evolutionary driving force. By employing variant Kauffman models, order parameters, and stability analysis, we provide sufficient numerical evidence demonstrating the diverse and distinctive capabilities of regulatory modes in stabilizing systems. Our findings give the most systematic analysis to date on the dynamic atlas of regulatory modes, offering a framework-independent proof of genetic networks operating at the edge of chaos with evolutionary implications. Furthermore, we discus the bridge between criticality and canalizing/threshold regulating modes and propose a reasonable scheme for generating model.
Predictive modeling of hematoma expansion from non-contrast computed tomography in spontaneous intracerebral hemorrhage patients
Authors: Ironside Natasha , El Naamani Kareem , Rizvi Tanvir , E-Rabbi Mohammed Shifat , Kundu Shinjini , Becceril-Gaitan Andrea , Pas Kristofor , Snyder Harrison , Chen Ching-Jen , Langefeld Carl D. , Woo Daniel , Mayer Stephan , Connolly E. Sander , Rohde Gustavo 
Published: May 2024

AbstractHematoma expansion is a consistent predictor of poor neurological outcome and mortality after spontaneous intracerebral hemorrhage (ICH). An incomplete understanding of its biophysiology has limited early preventative intervention. Transport-based morphometry (TBM) is a mathematical modeling technique that uses a physically meaningful metric to quantify and visualize discriminating image features that are not readily perceptible to the human eye. We hypothesized that TBM could discover relationships between hematoma morphology on initial Non-Contrast Computed Tomography (NCCT) and hematoma expansion. 170 spontaneous ICH patients enrolled in the multi-center international Virtual International Trials of Stroke Archive (VISTA-ICH) with time-series NCCT data were used for model derivation. Its performance was assessed on a test dataset of 170 patients from the Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study. A unique transport-based representation was produced from each presentation NCCT hematoma image to identify morphological features of expansion. The principal hematoma features identified by TBM were larger size, density heterogeneity, shape irregularity and peripheral density distribution. These were consistent with clinician-identified features of hematoma expansion, corroborating the hypothesis that morphological characteristics of the hematoma promote future growth. Incorporating these traits into a v achieved a AUROC of 0.71 for quantifying 24-hour hematoma expansion risk in the test dataset. This outperformed existing clinician protocols and alternate machine learning methods, suggesting that TBM detected features with improved precision than by visual inspection alone. This pre-clinical study presents a quantitative and interpretable method for discovery and visualization of NCCT biomarkers of hematoma expansion in ICH patients. Because TBM has a direct physical meaning, its modeling of NCCT hematoma features can inform hypotheses for hematoma expansion mechanisms. It has potential future application as a clinical risk stratification tool.
Optimal timing of booster doses in a highly vaccinated population with minimal natural exposure to COVID-19
Authors: Conway Eamon , Walker Camelia , Lydeamore Michael , Golding Nick , Ryan Gerard , Mavec Dario , Oates James , Kabashima Greg , Price David J , Shearer Freya , Cromer Deborah , Davenport Miles P , McCaw James , Eriksson Emily M , Hodgkin Philip D , Wu Logan , Le Thao P. , Baker Christopher M. , Mueller Ivo , McVernon Jodie 
Published: May 2024

AbstractPopulation-level waning of protection following immunising exposures is an important determinant of susceptibility to COVID-19 outbreaks. This work outlines an individual-based model (IBM) for the transmission and clinical impact of SARS-CoV-2 that explicitly represents the immunological response to vaccination and infection of each individual. The IBM evaluates waning of immunity to inform risk of infection and related clinical outcomes across a large freely mixing population over time by age and prior exposure status. Modelling immunological responses allows us to investigate the likely impact of immune escape variants based on the landscape in which they emerge. The model described in this paper was motivated by the need to anticipate health and societal impacts of COVID-19 in Australia following emergence of the Omicron variant, in the context of high national vaccine uptake but low infection exposure. It provides a flexible framework for modelling policy-relevant scenarios to inform preparedness and response actions as immunity in a population changes through time.
Cramming Protein Language Model Training in 24 GPU Hours
Authors: Frey Nathan C. , Joren Taylor , Ismail Aya Abdelsalam , Goodman Allen , Bonneau Richard , Cho Kyunghyun , Gligorijević Vladimir 
Published: May 2024

AbstractProtein language models (pLMs) are ubiquitous across biological machine learning research, but state-of-the-art models like ESM2 take hundreds of thousands of GPU hours to pre-train on the vast protein universe. Resource requirements for scaling up pLMs prevent fundamental investigations into how optimal modeling choices might differ from those used in natural language. Here, we define a “cramming” challenge for pLMs and train performant models in 24 hours on a single GPU. By re-examining many aspects of pLM training, we are able to train a 67 million parameter model in a single day that achieves comparable performance on downstream protein fitness landscape inference tasks to ESM-3B, a model trained for over 15, 000×more GPU hours than ours. We open source our library1for training and inference,LBSTER:Language models forBiologicalSequenceTransformation andEvolutionaryRepresentation.
The 18S rRNA Methyltransferase DIMT-1 Regulates Lifespan in the Germline Later in Life
Authors: Rothi M. Hafiz , Sarkar Gautam Chandra , Haddad Joseph Al , Mitchell Wayne , Ying Kejun , Pohl Nancy , Sotomayor-Mena Roberto G. , Natale Julia , Dellacono Scarlett , Gladyshev Vadim N. , Greer Eric Lieberman 
Published: May 2024

AbstractRibosome heterogeneity has emerged as an important regulatory control feature for determining which proteins are synthesized, however, the influence of age on ribosome heterogeneity is not fully understood. Whether mRNA transcripts are selectively translated in young versus old cells and whether dysregulation of this process drives organismal aging is unknown. Here we examined the role of ribosomal RNA (rRNA) methylation in maintaining appropriate translation as organisms age. In a directed RNAi screen, we identified the 18S rRNA N6’-dimethyl adenosine (m6,2A) methyltransferase,dimt-1,as a regulator ofC. eleganslifespan and stress resistance. Lifespan extension induced bydimt-1deficiency required a functional germline and was dependent on the known regulator of protein translation, the Rag GTPase,raga- 1,which links amino acid sensing to the mechanistic target of rapamycin complex (mTORC)1. Using an auxin-inducible degron tagged version ofdimt-1,we demonstrate that DIMT-1 functions in the germline after mid-life to regulate lifespan. We further found that knock-down ofdimt-1leads to selective translation of transcripts important for stress resistance and lifespan regulation in theC. elegansgermline in mid-life including the cytochrome P450daf-9,which synthesizes a steroid that signals from the germline to the soma to regulate lifespan. We found thatdimt-1induced lifespan extension was dependent on thedaf-9signaling pathway. This finding reveals a new layer of proteome dysfunction, beyond protein synthesis and degradation, as an important regulator of aging. Our findings highlight a new role for ribosome heterogeneity, and specific rRNA modifications, in maintaining appropriate translation later in life to promote healthy aging.
Benefits of spaced learning are predicted by re-encoding of past experience in ventromedial prefrontal cortex
Authors: Zou Futing , Kuhl Brice A. , DuBrow Sarah , Hutchinson J. Benjamin 
Published: May 2024

ABSTRACTMore than a century of research shows that spaced learning improves long-term memory. Yet, there remains debate concerning why. A major limitation to resolving theoretical debates is the lack of evidence for how neural representations change as a function of spacing. Here, leveraging a massive-scale 7T human fMRI dataset, we tracked neural representations and behavioral expressions of memory as participants viewed thousands of natural scene images that repeated at lags ranging from seconds to many months. We show that spaced learning increases the similarity of human ventromedial prefrontal cortex representations across stimulus encounters and, critically, these increases parallel and predict the behavioral benefits of spacing. Additionally, we show that these spacing benefits critically depend on remembering and, in turn, ‘re-encoding’ past experience. Collectively, our findings provide fundamental insight into how spaced learning influences neural representations and why spacing is beneficial.
Organomics: A concept reflecting the importance of PET/CT healthy organ radiomics in non-small cell lung cancer prognosis prediction using machine learning
Authors: Salimi Yazdan , Hajianfar Ghasem , Mansouri Zahra , Sanaat Amirhosein , Amini Mehdi , Shiri Isaac , Zaidi Habib 
Published: May 2024

AbstractPurposeNon-small cell lung cancer (NSCLC) is the most common subtype of lung cancer. Patient survival prediction using machine learning and radiomics analysis proved to provide promising outcomes. However, most studies reported in the literature focused on information extracted from malignant lesions. This study aims to explore the relevance and additional value of information extracted from healthy organs in addition to tumoral tissue using machine learning algorithms.MethodsThis study included PET/CT images of 154 patients collected from available online databases. The gross tumour volume (GTV) and 33 volumes of interest defined on healthy organs were segmented using nnU-Net deep learning-based segmentation. Subsequently, 107 radiomic features were extracted from PET and CT images (Organomics). Clinical information was combined with PET and CT radiomics from organs and GTVs considering 19 different combinations of inputs. Finally, different feature selection (FS, 5 methods) and machine learning (ML, 6 algorithms) algorithms were tested in a three-fold data split cross-validation scheme. The performance of the models was quantified in terms of the concordance index (C-index) metric.ResultsFor an input combination of all radiomics information, most of the selected features belonged to PET Organomics and CT Organomics. The highest C-Index (0.68) was achieved using univariate C-Index FS method and random survival forest ML model using CT Organomics + PET Organomics as input as well as minimum depth FS method and CoxPH ML model using PET Organomics as input. Considering all 17 combinations with C-Index higher than 0.65, Organomics from PET or CT images were used as input in 16 of them.ConclusionThe selected features and C-Indices demonstrated that the additional information extracted from healthy organs of both PET and CT imaging modalities improved the machine learning performance. Organomics could be a step toward exploiting the whole information available from multimodality medical images, contributing to the emerging field of digital twins in healthcare.
Managing Low Back Pain in Rural Uganda: A Qualitative Study Exploring the Perspectives and Practices of Frontline Health Workers regarding LBP Management in Primary Care
Authors: Harscouët Paul , Ndekezi Chimpaye Gloria , Kazibwe Herman , Kabakeynga Jerome , O’Callaghan Denise , Blake Catherine , Caulfield Brian , O’Sullivan Cliona 
Published: May 2024

AbstractBACKGROUND AND AIMSLow-back pain (LBP) is the main cause of years lived with disabilities (YLDs) worldwide and the second cause of YLDs in Uganda. In 2019, it was responsible for 7.4% of global YLDs and 5% of YLDs in Uganda. LBP takes a significant toll on people’s quality of life and disproportionately affects lower socioeconomic classes, elders, and women. In rural Uganda, LBP is managed in health centres by clinical officers and nurses with limited resources. This study aims to understand the perspectives and practices of these health workers.MethodA qualitative design using semi-structured focus-group discussions was employed. Purposive sampling allowed us to identify relevant participants based on their roles as healthcare professionals working in primary care context in rural South-West Uganda. Data was analysed using thematic analysis.FindingsLBP is a common and persistent complaint among patients presenting to rural health centres in Uganda. Manual labour and female specific health conditions were deemed to be common causes. There was a strong reliance on medication prescription, coupled with X-ray diagnosis, with little emphasis on education or exercise. Finally, findings highlighted major barriers for patients within the referral system to hospital care or rehabilitation.DiscussionEducation and training of frontline clinicians in terms of appropriate prescribing and rehabilitation for LBP is crucial. Evidence-based rehabilitation interventions need to be developed and adapted so that they can be delivered within the time and resource constraints of the health workforce, ensuring that they are acceptable and effective to patients in the context of rural Uganda.