bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing Low-cost Registration for Photographic Images to Computed Tomography
Authors: Kim Michael E. , Lee Ho Hin , Ramadass Karthik , Gao Chenyu , Van Schaik Katherine , Tkaczyk Eric , Spraggins Jeffrey , Moyer Daniel C. , Landman Bennett A. 
Published: September 2023

ABSTRACTMapping information from photographic images to volumetric medical imaging scans is essential for linking spaces with physical environments, such as in image-guided surgery. Current methods of accurate photographic image to computed tomography (CT) image mapping can be computationally intensive and/or require specialized hardware. For general purpose 3-D mapping of bulk specimens in histological processing, a cost-effective solution is necessary. Here, we compare the integration of a commercial 3-D camera and cell phone imaging with a surface registration pipeline. Using surgical implants and chuck-eye steak as phantom tests, we obtain 3-D CT reconstruction and sets of photographic images from two sources: Canfield Imaging’s H1 camera and an iPhone 14 Pro. We perform surface reconstruction from the photographic images using commercial tools and open-source code for Neural Radiance Fields (NeRF) respectively. We complete surface registration of the reconstructed surfaces with the iterative closest point (ICP) method. Manually placed landmarks were identified at three locations on each of the surfaces. Registration of the Canfield surfaces for three objects yields landmark distance errors of 1.747, 3.932, and 1.692 mm, while registration of the respective iPhone camera surfaces yields errors of 1.222, 2.061, and 5.155 mm. Photographic imaging of an organ sample prior to tissue sectioning provides a low-cost alternative to establish correspondence between histological samples and 3-D anatomical samples.
A redox-shifted fibroblast subpopulation emerges in the fibrotic lung
Authors: Link Patrick A. , Meridew Jeffrey A. , Caporarello Nunzia , Gao Ashley Y. , Peters Victor , Smith Gordon B. , Rojas Mauricio , Tschumperlin Daniel J. 
Published: September 2023

AbstractIdiopathic pulmonary fibrosis (IPF) is an aggressive and thus far incurable disease, characterized by aberrant fibroblast-mediated extracellular matrix deposition. Our understanding of the disease etiology is incomplete; however, there is consensus that a reduction-oxidation (redox) imbalance plays a role. In this study we use the autofluorescent properties of two redox molecules, NAD(P)H and FAD, to quantify changes in their relative abundance in living lung tissue of mice with experimental lung fibrosis, and in freshly isolated cells from mouse lungs and humans with IPF. Our results identify cell population-specific intracellular redox changes in the lungs in experimental and human fibrosis. We focus particularly on redox changes within collagen producing cells, where we identified a bimodal distribution of NAD(P)H concentrations, establishing NAD(P)Hhighand NAD(P)Hlowsub-populations. NAD(P)Hhighfibroblasts exhibited elevated pro-fibrotic gene expression and decreased collagenolytic protease activity relative to NAD(P)Hlowfibroblasts. The NAD(P)Hhighpopulation was present in healthy lungs but expanded with time after bleomycin injury suggesting a potential role in fibrosis progression. We identified a similar increased abundance of NAD(P)Hhighcells in freshly dissociated lungs of subjects with IPF relative to controls, and similar reductions in collagenolytic activity in this cell population. These data highlight the complexity of redox state changes in experimental and human pulmonary fibrosis and the need for selective approaches to restore redox imbalances in the fibrotic lung.
Moving Biosurveillance Beyond Coded Data: AI for Symptom Detection from Physician Notes
Authors: McMurry Andrew , Zipursky Amy R , Geva Alon , Olson Karen L , Jones James , Ignatov Vlad , Miller Timothy , Mandl Kenneth D 
Published: September 2023

AbstractBackgroundReal-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records.ObjectiveTo validate and test an artificial intelligence (AI) based Natural Language Processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes.MethodsSubjects in this retrospective cohort study are patients 21 years old and younger, who presented to a pediatric emergency department (ED) at a large academic children’s hospital between March 1, 2020 and May 31, 2022. ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on CDC criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F1=98.6; PPV=97.2; Recall=100.0). F1, PPV, and recall were used to compare the performance of both NLP and ICD-10 to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-Cov2 variant eras.ResultsThere were 85,678 ED encounters during the study period, 4.0% with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F1=79.6) than ICD-10 codes (F1=45.1%). NLP accuracy was higher for positive symptoms (recall=93%) than ICD-10 (recall=30%). However, ICD-10 accuracy was higher for negative symptoms (specificity=99.4%) than NLP (specificity=91.7%). Congestion or runny nose showed the highest accuracy difference: NLP F1=82.8%, ICD-10 F1=4.2%. Prevalence of NLP symptoms among patients with COVID-19 differed across variant eras. And patients with COVID-19 were more likely to have each symptom than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras.ConclusionsThis study establishes the value of AI based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance.
Automated Annotation of Disease Subtypes
Authors: Ofer Dan , Linial Michal 
Published: September 2023

AbstractBackgroundDistinguishing diseases into distinct subtypes is crucial for study and effective treatment strategies. The Open Targets Platform (OT) integrates biomedical, genetic, and biochemical datasets to empower disease ontologies, classifications, and potential gene targets. Nevertheless, many disease annotations are incomplete, requiring laborious expert medical input. This challenge is especially pronounced for rare and orphan diseases, where resources are scarce.MethodsWe present a machine learning approach to identifying diseases with potential subtypes, using the approximately 23,000 diseases documented in OT. We derive novel features for predicting diseases with subtypes using direct evidence. Machine learning models were applied to analyze feature importance and evaluate predictive performance for discovering both known and novel disease subtypes.ResultsOur model achieves a high (89.4%) ROC AUC (Area Under the Receiver Operating Characteristic Curve) in identifying known disease subtypes. We integrated pre-trained deep-learning language models and showed their benefits. Moreover, we identify 515 disease candidates predicted to possess previously unannotated subtypes.ConclusionsOur models can partition diseases into distinct subtypes. This methodology enables a robust, scalable approach for improving knowledge-based annotations and a comprehensive assessment of disease ontology tiers. Our candidates are attractive targets for further study and personalized medicine, potentially aiding in the unveiling of new therapeutic indications for sought-after targets.
Cost-Benefit Analysis for Universal Cataract Coverage in India
Authors: Arora Anoushka , Vuddemarry Madhurima , Reddy Chaitanya , Iyer Himanshu , Nimkar Pushkar , Zadey Siddhesh 
Published: September 2023

AbstractPurposeTo calculate the annual enhanced coverage costs for covering the total and unmet need of cataract in India. To calculate the economic benefits of cataract burden averted. To calculate the net benefits of covering cataract needs.SettingWe look at population-level data of India and its 30 states.DesignThis is a retrospective cross-sectional analysis for 2018-19.MethodsWe conducted a retrospective cross-sectional analysis for India and its 30 states. Data was taken from Global Burden of Disease 2019, the National Health Profile 2020, and the National Health Accounts 2021. We used ten per-capita surgical costs to calculate enhanced coverage costs. Enhanced coverage costs for the total need were calculated by multiplying prevalence with per-capita costs. For unmet need, the difference between the prevalence and surgeries achieved was used. For economic benefits of averted cataract burden, we multiplied disability-adjusted life-years (DALYs) with non-health GDP per capita, i.e., GDP - the government health expenditure. DALYs for unmet needs were calculated by multiplying DALYs with the ratio of unmet to total needs. For net benefits, we subtracted the enhanced coverage costs for meeting total and unmet needs from economic benefits.ResultsThe annual enhanced coverage costs for covering total cataract needs in India were 0.92 - 4.9 billion USD. Costs for covering unmet needs were 0.72 - 3.82 billion USD. Nationally, the economic benefit of averting the total cataract disease burden was 12.4 (95%UI: 8.9 - 16.7) billion USD, while the for covering the unmet burden was 9.7 (95%UI: 6.93 - 13) billion USD. Annual net benefits of covering total needs were 7.53 - 11.5 billion USD. Net benefits of covering unmet needs were 5.9 - 9 billion USD.ConclusionEnhancing coverage for cataract is cost-beneficial.
Longitudinal associations between mild behavioral impairment, sleep disturbance, and progression to dementia
Authors: Mudalige Dinithi , Guan Dylan X. , Ghahremani Maryam , Ismail Zahinoor 
Published: September 2023

ABSTRACTBackgroundClinical guidelines recommend incorporating non-cognitive markers like mild behavioral impairment (MBI) and sleep disturbance (SD) into dementia screening to improve detection.ObjectiveWe investigated the longitudinal associations between MBI, SD, and incident dementia.MethodsParticipant data were from the National Alzheimer’s Coordinating Center in the United States. MBI was derived from the Neuropsychiatric Inventory Questionnaire (NPI-Q) using a published algorithm. SD was determined using the NPI-Q nighttime behaviors item. Cox proportional hazard regressions with time-dependant variables for MBI, SD, and cognitive diagnosis were used to model associations between baseline 1) MBI and incident SD (n=11277); 2) SD and incident MBI (n=10535); 3) MBI with concurrent SD and incident dementia (n=13544); and 4) MBI without concurrent SD and incident dementia (n=11921). Models were adjusted for first-visit age, sex, education, cognitive diagnosis, race, and for multiple comparisons using the Benjamini-Hochberg method.ResultsThe rate of developing SD was 3.1-fold higher in older adults with MBI at baseline compared to those without MBI (95%CI: 2.8-3.3). The rate of developing MBI was 1.5-fold higher in older adults with baseline SD than those without SD (95%CI: 1.3-1.8). The rate of developing dementia was 2.2-fold greater in older adults with both MBI and SD, as opposed to SD alone (95%CI:1.9-2.6).ConclusionsThere is a bidirectional relationship between MBI and SD. Older adults with SD develop dementia at higher rates when co-occurring with MBI. Future studies should explore the mechanisms underlying these relationships, and dementia screening may be improved by assessing for both MBI and SD.
Work-Related Musculoskeletal Disorders among Nurses Working at Hospitals of Sudurpaschim Province, Nepal
Authors: Bhatta Deepa Kumari , Bhandari Gajananda Prakash , Duwadi Nirmal , Bhatta Bal Krishna , Gurung Ishwori , Dahal Alisha 
Published: September 2023

AbstractMusculoskeletal conditions have been ranked as the leading cause of disability worldwide. Low back pain is the single largest contributor in 160 countries including Nepal. Nurses working in hospitals in Nepal are overworked and at risk of developing musculoskeletal disorders. The study aimed to determine the 12-month periods and point prevalence of work-related musculoskeletal disorders (WMSDs); the predictors, and the perceived risk factors among nurses. A self-administered standard Nordic questionnaire was distributed among all eligible 118 nurses working at two hospitals. Bivariate and multivariate logistic regression analyses were applied to identify the predictors of WMSDs. Study findings revealed that nearly half (47.46%) of nurses had WMSDs most significantly affecting the lower back (18.93%). Nurses exceeding 30 years of age had almost seven times higher odds of having WMSDs compared to their counterparts aged less than 30 adjusting the effects of BMI, department, years of clinical experience, and type of hospital (OR= 6.92; CI =1.67-28.58). There was decreased odds of experiencing WMSDs by 0.33 times for nurses working in a private hospital than in a government hospital adjusting the effect of age, BMI, department, and years of clinical experience (OR=0.33; 95% CI=0.12-0.91). Similarly, nurses working in critical units had 5.24 times higher odds of having musculoskeletal disorders than in general units (OR=5.25; 95% CI=1.79-15.38). Nurses working for more than five years had 7.53 times higher odds of having WMSDs than those with less than and equal to five years of work experience (OR=7.53; CI 2.78-20.32). WMSDs are common among nurses primarily affecting the lower back and the odds of having MSDs is high with increasing age, BMI, and work experience, and for nurses who worked in critical care units and public hospital. Prompt preventive measures should be adopted to avoid risk factors of MSDs in work settings.Keywords:Works related to musculoskeletal disorders, nursing, prevention, perceived risk factors
Association between kidney measurements and cognitive performance in patients with ischemic stroke
Authors: Zhang Chunyan , Xue Guofang , Hou Yanjuan , Meng Pengfei , Gao Huizhong , Bai Bo , Li Dongfang 
Published: September 2023

AbstractBackgroundRelationships between low estimated glomerular filtration rate (eGFR) and albuminuria with poorer cognitive performance in patients with ischemic stroke are less clear. Our aim was to retrospectively ascertain the associations between these renal measures and cognitive performance in patients with ischemic stroke.MethodsRetrospective analysis was performed on 608 patients with acute ischemic stroke. Urine albumin-creatinine ratio (UACR) and eGFR were obtained from inpatient medical records. Global cognitive function via mini-mental state exam (MMSE) and Montreal Cognitive Assessment (MoCA) was determined one month after hospital discharge. The relationship between renal measures and cognitive performance was assessed using univariate and multiple linear regression analyses.ResultsPatients had an average age of 66.6±4.1 years, and 48% were females. Average eGFR and UACR were 88.4±12.9 ml/min/1.73m2and 83.6±314.2 mg/g, respectively. The number of patients with an eGFR of ≥90, 60 to 89, and <60 ml/min/1.73 m2were (371, 61%), (207, 34%) and (30, 5%) respectively. The proportions with a UACR <30 mg/g, 30-300mg/g and >300 mg/g were 56%, 39% and 5%. Multivariate adjusted models showed that eGFR was independently associated with MMSE (β= –0.4; 95% CI= –0.5,-0.4; p <0.001) and MoCA (β = –0.6; 95% CI= –0.7,-0.5; p <0.001). However, the correlations between UACR and MMSE and MoCA were statistically non-significant.ConclusionIn patients with ischemic stroke, reduced eGFR but not albuminuria was associated with lower cognitive performance. These results show that the eGFR decline could be an effective indicator of cognitive impairment after a stroke. Therefore, regular monitoring and early detection of mild renal dysfunction in patients with acute ischemic stroke might be needed.
Autophagic cargo in Lewy bodies: are Lewy bodies a compartment for spatial protein quality control?
Authors: Conod Phoebe , Charlesworth Nicola , Palmowski Pawel , Porter Andrew , Walker Lauren , El-Agnaf Omar , Korolchuk Viktor , Outeiro Tiago F. , Erskine Daniel 
Published: September 2023

ABSTRACTLewy bodies are neuropathologically associated with Lewy body dementia (LBD), but little is known about why they form or their role in the disease process. We previously reported Lewy bodies are a common feature of older individuals with primary mitochondrial diseases. However, as they are not an invariant finding, understanding differences between those with and without Lewy bodies may provide insights into factors that govern the formation of Lewy bodies in Lewy body disease (LBD). The present study sought to investigate whether deficient mitophagy in the context of mitochondrial dysfunction may underlie Lewy body formation.Post-mortemtissue was obtained from the cingulate gyrus and dorsal motor nucleus of the vagal nerve (DMV) of mitochondrial disease cases with Lewy bodies, primary mitochondrial disease cases without Lewy bodies, and control cases, in addition to LBD cases as comparison. An array of mitophagy and autophagy markers were quantified in 50 individual neurons per cingulate gyrus and all neurons per DMV using immunofluorescent analysis. No significant differences were found between groups, although there was a striking enrichment of markers of autophagic mitochondria and autophagic vesicles within Lewy bodies. Evaluation of diffuse α-synuclein aggregates, thought to precede Lewy body formation, suggested only autophagic mitochondria were present in early aggregates, perhaps suggesting sequestration of dysfunctional mitochondria is an early step in Lewy body formation. To characterise the composition of Lewy bodies, discovery proteomics was performed on isolated insoluble proteins from frozen cingulate gyrus, which identified up-regulation of markers of aggresomes, a regulated cellular response that occurs when protein degradative pathways become overwhelmed, a mechanism of spatial protein quality control (sPQC). Taken together, these findings are consistent with impairment of cellular waste handling pathways in Lewy body-bearing neurons, and that the formation of a Lewy body could be a deliberate cellular response to compartmentalise such waste.
A conserved role of hnRNPL in regulating alternative splicing of transcriptional regulators necessary for B cell activation
Authors: Subramani Poorani Ganesh , Fraszczak Jennifer , Helness Anne , Estall Jennifer L. , Möröy Tarik , Noia Javier M Di 
Published: September 2023

ABSTRACTThe multifunctional RNA-binding protein hnRNPL has been implicated in antibody class switching but its broader function in B cells is unknown. Here, we show that hnRNPL is essential for B cell activation, and thereby germinal center and antibody responses. Upon activation, hnRNPL-deficient B cells show proliferation defects and increased apoptosis. Comparative analysis of RNA-seq data from activated B cells and another 8 hnRNPL-depleted cell types reveals a common function in the MYC and E2F transcriptional programs required for proliferation, likely borne out of alternative splicing changes affecting multiple transcription regulators. Notably, while individual gene expression changes were cell type specific, several alternative splicing events affecting histone modifiers like, KDM6A, NSD2, and SIRT1, were conserved across cell types, which could contribute to gene expression changes and other phenotypes upon hnRNPL loss. In line with reduced SIRT1, hnRNPL-deficient B cells had dysfunctional mitochondria and ROS overproduction, which could contribute to defects in B cell activation. Thus, hnRNPL is essential for the resting-to-activated B cell transition by regulating transcriptional programs and metabolism, most likely through the alternative splicing of several histone modifiers.
The effects of queen mandibular pheromone on nurse-aged honey bee (Apis mellifera) hypopharyngeal gland size and lipid metabolism
Authors: Oreshkova Angela , Scofield Sebastian , Amdam Gro V. 
Published: September 2023

AbstractQueen honey bees (Apis mellifera) release Queen Mandibular Pheromone (QMP) to regulate traits in the caste of female helpers called workers. QMP signals the queen’s presence and suppresses worker reproduction. In the absence of reproduction, young workers take care of the queen and her larvae (nurse tasks), while older workers forage. In nurses, QMP increases lipid stores in abdominal fat tissue (fat body) and protein content in hypopharyngeal glands (HPG). HPG are worker-specific head glands that can synthesize royal jelly used in colony nourishment. Larger HPG signifies ability to secrete royal jelly, while shrunken glands characterize foragers that do not make jelly. While it is known that QMP increases abdominal lipid stores, the mechanism is unclear: Does QMP make workers consume more pollen which provides lipids, or does QMP increase lipogenic capacity? Here, we measure abdominal lipogenic capacity as fatty acid synthase (FAS) activity while monitoring abdominal protein content and HPG size in caged workers. Cages allow us to rigorously control worker age, pheromone exposure, and diet. In our 2-factorial design, 3-vs. 8-day-old workers (age factor) were exposed to synthetic QMP or not (pheromone factor) while consuming a lipid deficient diet. We found that QMP did not influence abdominal FAS activity or protein content, but QMP still increased HPG size in the absence of dietary lipids. Our data revealed a positive correlation between abdominal protein content and HPG size. Our findings show that QMP is not a strong modulator of lipogenic capacity in caged worker bees. However, our data may reflect that QMP mobilizes abdominal protein for production of jelly, in line with previous findings on effects of honey bee Brood Pheromone. Overall, our study expands the understanding of how QMP can affect honey bee workers. Such insights are important beyond regulatory biology, as QMP is used in various aspects of beekeeping.
Determination of phylogenetic relationships in the genusMangiferabased on whole chloroplast genome and nuclear genome sequences
Authors: Kumari Wijesundara WWM Upendra , Furtado Agnelo , Dillon Natalie L. , Masouleh Ardashir Kharabian , Henry Robert J 
Published: September 2023

AbstractThe genusMangifera(Anacardiaceae) includes 69 species of whichMangifera indica L. is the most important and primarily cultivated species for commercial mango production. Although the species are classified based on morphological descriptors, molecular evidence has proposed the hybrid origin of two species suggesting the possibility that more of the species may be of hybrid origin. To analyze evolutionary relationships within the genus, 13 samples representing 11Mangiferaspecies were sequenced and whole chloroplast (Cp) genomes and 47 common single-copy nuclear gene sequences were assembled and used for phylogenetic analysis using concatenation and coalescence-based methods. The Cp genome size varied from 151,752 to 158,965 bp withM. caesiaandM. laurinahaving the smallest and largest genomes, respectively. Genome annotation revealed 80 protein-coding genes, 31 tRNA and four rRNA genes across all the species. Comparative analysis of whole Cp genome sequence and nuclear gene-based phylogenies revealed topological conflicts suggesting chloroplast capture or cross hybridization. The Cp genomes ofM. altissima,M. applanata,M. caloneuraandM. lalijiwawere similar to those ofM. indica(99.9% sequence similarity). Their close sequence relationship suggests a common ancestry and likely cross-hybridization between wild relatives andM. indica. This study provides improved knowledge of phylogenetic relationships inMangifera,indicating extensive gene flow among the different species, suggesting that hybrids may be common within the genus.