bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing Diagnostic Accuracy of Fresh Vertebral Compression Fractures with Deep Learning Models
Authors: Li Kai-Yu , Ye Hao-Bo , Zhang Yu-Long , Huang Jia-Wei , Li Hua-Lin , Tian Nai-Feng 
Published: October 2024

Study Design:
Retrospective study.

Objectives:
The study aimed to develop and authenticated a deep learning model based on X-ray images to accurately diagnose fresh thoracolumbar vertebral compression fractures.

Summary of Background Data:
In clinical practice, diagnosing fresh vertebral compression fractures often requires MRI. However, due to the scarcity of MRI resources and the high time and economic costs involved, some patients may not receive timely diagnosis and treatment. Using a deep learning model combined with X-rays for diagnostic assistance could potentially serve as an alternative to MRI.

Methods:
In this study, the main collection included X-ray images suspected of thoracolumbar vertebral compression fractures from the municipal shared database between December 2012 and February 2024. Deep learning models were constructed using frameworks of EfficientNet, MobileNet, and MnasNet respectively. We conducted a preliminary evaluation of the deep learning model using the validation set. The diagnostic performance of the models was evaluated using metrics such as AUC value, accuracy, sensitivity, specificity, F1 score, precision, and ROC curve. Finally, the deep learning models were compared with evaluations from two spine surgeons of different experience levels on the control set.

Results:
This study included a total of 3025 lateral X-ray images from 2224 patients. The dataset was divided into a training set of 2388 cases, a validation set of 482 cases, and a control set of 155 cases. In the validation set, the three groups of DL models had accuracies of 83.0%, 82.4%, and 82.2%, respectively. The AUC values were 0.861, 0.852, and 0.865, respectively. In the control set, the accuracies of the three groups of DL models were 78.1%, 78.1%, and 80.7%, respectively, all higher than spinal surgeons and significantly higher than junior spine surgeon.

Conclusion:
This study developed deep learning models for detecting fresh vertebral compression fractures, demonstrating high accuracy.
Lip Augmentation with Soft Tissue Fillers: Social Media, Perceptual Adaptation, and Shifting Beauty Trends beyond Golden Standard Ideals
Authors: Atiyeh Bishara S. , Beaineh Paul T. , Hakim Christopher R. A. , Makkawi Kareem W. , Habr Natasha T. , Zeineddine Jana H. , Emsieh Saif E. , Issa Oussama B. , Gnaedinger Anika G. , Ibrahim Amir E. 
Published: October 2024

Background:
Unfortunately, current beauty trends greatly advertised by social media are trespassing recognized cannons of beauty. Of particular interest are patients’ expectations of soft tissue volume augmentation of the face, specifically of the lips.

Methods:
An artificial intelligence picture of a White female face was generated. With the fixed standard golden upper-to-lower (U/L) lip ratio, a first set of pictures was generated with varying lip fullness. A second set of pictures was generated with various U/L ratios and lip fullness. In a survey format, the 2 sets of pictures were rated for attractiveness from the most to the least attractive by adult men and women.

Results:
Rating the first set of pictures clearly demonstrates that overinflation of lips with upper lip height in excess of 30% of hemi-lip width is highly regarded as unaesthetic and unattractive, with a net preference of 20%–25%. For the second set, U/L ratios between 0.618:1 and 1:1 are still regarded to be most aesthetic.

Conclusions:
Though social media have an influence on perception of beauty, data provided by the survey confirm that golden standards of aesthetics remain constant and that exaggerated requests of some patients may not be attributed solely to social media influence but probably to social media in combination with additional personal predisposing factors. Patients must be made aware that how they are perceived by others is essential for them to be satisfied with their appearance.
Efficacy of Liposuction of the Posterior Arm Fat Pad in Axillobrachioplasty after Massive Weigh Loss: A Pilot Study
Authors: Gunnarsson Gudjon Leifur , Gudjonsdottir Linda Regina , Koidil Amelia , Haukeland Lars , Berg Erik , Thomsen Jorn Bo 
Published: October 2024

Background:
The topographic anatomical changes of the upper arms and axilla after massive weight loss (MWL) seem ill-described in the literature. The importance of the axilla in MWL brachioplasty and how the procedure differs from the postmenopausal “batwing” deformity of the upper arms is also unclear. Consideration of the underlying pathology seems imperative for a successful reconstruction. We aim to test a procedure specifically designed to mend the underlying pathology of obesity and MWL, liposuction-assisted axillobrachioplasty (LAAB).

Methods:
A prospective pilot study was designed to test the effect of LAAB on the axilla and evaluate the results comparative to patient’s preoperative complaints and well-being and allow for adjustments for future trials. We measured the diameter of the arm and axilla at three specific points, A, B and C, and applied the arm module of BODY-Q regarding body perception and psychosocial well-being.

Results:
Fifteen women, for a total of 30 arms, were included. Age average was 48 years (29–59) and showed a significant improvement in all measurements A–C, most significantly at point A in the axilla, where the reduction was associated with relief of preoperative ailments and great improvement on BODY-Q ratings. The procedure was uncomplicated, with high patient satisfaction.

Conclusions:
LAAB significantly improves the axilla and upper arm contour after MWL and correlates strongly with improvement of preoperative ailments. The study furthermore supports the clinical relevance of a posterior arm fat pad. The presented procedure seems to be uncomplicated and reproducible with a high patient satisfaction warranting a long-term clinical trial
The co-location of MARCO+ tumor-associated macrophages and CTSE+ tumor cells determined the poor prognosis in intrahepatic cholangiocarcinoma
Authors: Fan Guangyu , Tao Changcheng , Li Lin , Xie Tongji , Tang Le , Han Xiaohong , Shi Yuankai 
Published: October 2024

Background and Aims:
Intratumor immune infiltration plays a crucial role in interacting with tumor cells in intrahepatic cholangiocarcinoma (ICC). However, the specific phenotypes of immune cells and their spatial distribution within the tumor microenvironment remain unclear. This study aimed to address these limitations by providing a detailed analysis of immune infiltration patterns in ICC using combined spatial and single-cell transcriptomic data.

Approach and Results:
We analyzed 29,632 spots from 6 spatial transcriptomic samples and 21,158 cells from 35 single-cell samples of ICC. Two distinct immune infiltration patterns were identified: macrophage+ (characterized by CD68 and macrophage receptor with collagenous structure [MARCO]) and plasma cell+ (characterized by IGHG1 and JCHAIN). These patterns showed contrasting impacts on patient survival, with macrophage+ infiltration associated with poorer outcomes and plasma cell+ infiltration linked to better survival. MARCO+ tumor-associated macrophages (TAMs) were the predominant cell type in macrophage+ samples, indicative of an immune-resistant microenvironment. In MARCO+ TAMs, elevated epithelial-mesenchymal transition activity, angiogenesis, and hypoxia were observed. Spatial transcriptomics and bulk data also revealed co-location of MARCO+ TAMs with cathepsin E (CTSE+) tumor cells, a finding validated by multiplex immunofluorescence in 20 ICC samples. The co-location area was enriched with protumorigenic pathways and suppressed immune responses, and CTSE expression was associated with intrahepatic metastasis and vascular invasion. High infiltration of both MARCO+ TAMs and CTSE+ tumor cells correlated with the poorest survival outcomes. Within the co-location area, the galectin signaling pathway, particularly the LGALS9-CD44 ligand-receptor pair, was highly active in cell-cell communication.

Conclusions:
This study identifies 2 intratumor immune infiltration patterns, macrophage+ and plasma cell+, in ICC. Furthermore, the co-location of MARCO+ TAMs and CTSE+ tumor cells contributes to an immune-resistant microenvironment, highlighting potential targets for therapeutic intervention in ICC.
Narrative Thinking of Healthcare Providers in Medical Cases and Its Implications for Modern Medical Education
Authors: YANG Xiaolin , HUANG Qing 
Published: October 2024

Abstract
In the realm of Chinese narrative medicine, narrative thinking holds equal significance to evidence-based thinking within clinical practice, making substantial contributions to patient safety and medical quality. Ancient Chinese medical theories advocate forging a narrative bond with patients, urging healthcare practitioners to utilize Dao Shu Jie He (道术结合 integration of Dao and techniques) and Yi Dao Yu Shu (以道驭术 guiding techniques with Dao) during diagnosis, treatment, and rehabilitation. In this context, Dao (道) in traditional Chinese medicine (TCM) corresponds to narrative thinking (叙事思维) while Shu (术) aligns with scientific thinking (科学思维) in evidence-based medicine. This study adopts “narrative Chinese medicine” within the “discourse system of Chinese narrative medicine” as its framework, centering on medical stories that exemplify the application of narrative thinking in ancient Chinese diagnosis and treatment. It delves into the narrative thinking encapsulated in Chinese medicine, such as Guan Wu Qu Xiang (观物取象 observing things and extracting information), Can He Er Xing (参合而行 final examination and decision by integrating the four diagnoses), Xing Shen Bing Zhi (形神并治 body-spirit treatment), Xin Shen Jian Li (心身兼理 mind-body balance) and Bian Zheng Lun Zhi (辨证论治 treatment based on pattern differentiation). The study endeavors to inspire contemporary medical educators and clinicians to acknowledge the value of narrative thinking in TCM and fully incorporate it into daily medical practice.
Diagnostic accuracy of NT-proBNP to predict the incidence of CSA-AKI: A systematic review and meta-analysis
Authors: Zhang Jiaying , Li Xin , Yu Xiaofeng 
Published: October 2024

Background:
Cardiac surgery–associated acute kidney injury (CSA-AKI) is a severe complication following cardiac surgery. Early identification and diagnosis are critical. In this study, we aim to systematically assess the diagnostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) for CSA-AKI.

Methods:
The PubMed, Embase, Web of Science, and Cochrane Library databases were searched from January 1971 to October 2023 to identify prospective observational and retrospective observational studies. Data extraction and study screening were carried out independently by 2 authors. The methodological quality of the included studies was evaluated by the Quality Assessment of Diagnostic Accuracy Studies 2 standards, and all statistical analyses were conducted by Stata 15.0.

Results:
Seven studies including 37,200 patients were identified. The pooled sensitivity of 0.67 (95% credible interval [CI] = 0.56–0.77), specificity of 0.55 (95% CI = 0.45–0.64), area under the summary receiver operating characteristic curve of 0.65 (95% CI = 0.60–0.69), positive likelihood ratio of 1.5 (95% CI = 1.2–1.8), negative likelihood ratio of 0.60 (95% CI = 0.46–0.79), and diagnostic odds ratio of 2 (95% CI = 2–4) suggested that patients with higher preoperative NT-proBNP levels (pg/mL) are at higher risk of developing acute kidney injury after cardiac surgery. However, NT-proBNP lacks sufficient sensitivity and specificity to reliably predict CSA-AKI.

Conclusion:
Our findings suggest that the diagnostic accuracy of NT-proBNP to predict the incidence of CSA-AKI is limited. However, we provide novel perspectives on the early detection of CSA-AKI biomarkers, and it is urgent to identify more precise and practical biomarkers for the early diagnosis of CSA-AKI.
Polymyalgia rheumatica following COVID-19 vaccination: Case series of 3 patients and literature review on polymyalgia rheumatica induced by various vaccines
Authors: Irani Laure , Bou Karroum Mira , Chehab Yara , Abi Saad Nesrine , Al Dailaty Ali , Husni Roula 
Published: October 2024

Rationale:
Since the onset of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic in 2019, considerable resources have been devoted to developing vaccines to reduce related deaths and the burden of disease. Various vaccine formulations eventually became available and were approved for clinical use. In this article, we have conducted a review of polymyalgia rheumatica (PMR) cases induced by different COVID-19 vaccines [Pfizer: BNT162b2, AstraZeneca: ChAdOx1-S, Moderna: mRNA-1273, and Janssen: Ad26.COV2.S)], as well as non-COVID-19 vaccines, such as influenza, zoster, hepatitis B, and tetanus vaccines. Additionally, this article investigates 3 cases with clinical presentations suggestive of PMR following COVID-19 mRNA vaccination. This study aims to offer valuable insights through sharing diagnostic and therapeutic experiences.

Patient concerns:
Three patients presented with severe pain and stiffness in both shoulder and pelvic girdle muscles, following COVID-19 mRNA vaccination.

Diagnoses:
Clinical presentations, laboratory parameters, and echographic findings confirmed the diagnosis of PMR following COVID-19 mRNA vaccination.

Interventions:
Patients received Prednisone and/or Methotrexate adjusted to body weight.

Outcomes:
Polymyalgia rheumatica resolved successfully without any adverse events.

Lessons:
Although direct causality was not definitively established in this article, the BNT162b2 COVID-19 mRNA vaccine, similar to other vaccines, might be considered a potential trigger for PMR. This raises the need for further research into this issue and potentially other immunological outcomes.
Internalized Phobia, Community Connectedness, Outness, and Mental Health Risk and Protection in LGBTQ Persons
Authors: Graziano Teresa A. , Fitzgerald Holly N. , Ortiz José , Owen Christopher K. , Shook Natalie J. 
Published: October 2024

Background
Community connectedness, outness, and internalized phobia are potential protective and risk factors for mental health in lesbian, gay, bisexual, transgender, and queer (LGBTQ) individuals. However, these interrelated factors have generally been examined in isolation and for the LGBTQ community in aggregate. As such, there may be undetected effects of factors on mental health for each LGBTQ group.

Objectives
We examined the associations between mental health (i.e., depression and anxiety) and risk/protective factors (i.e., internalized phobia, community connectedness, outness) in each LGBTQ subgroup separately.

Method
A large national U.S. sample (N = 1,030) of individuals who identified as LGBTQ completed an anonymous Internet survey during fall 2019. Participants answered questionnaires about community connectedness, outness, internalized homophobia or transphobia, anxiety, and depression.

Results
On average, most subgroups reported symptoms of depression and anxiety above clinical cutoffs. Less outness and greater internalized phobia were associated with more severe depression and anxiety, but this pattern was not consistent across LGBTQ subgroups. Greater community connectedness was generally associated with more severe anxiety and depression.

Discussion
LGBTQ subgroups vary in how risk and protective factors relate to mental health outcomes. Our findings highlight the importance of examining LGBTQ subgroups separately and examining risk/protective factors simultaneously to identify the unique contribution of each factor. More research is needed to understand potential LGBTQ mental health risks and protective factors, and future researchers should examine the unique roles of risk and protective factors in separate LGBTQ subgroups.
Emerging integrase resistance in an international perinatal virtual clinic
Authors: Eni-Olotu Ayolola , Mackie Nicola E. , Glenn Jessica , Bailey Angela , Bamford Alasdair , Kenny Julia , Levin Leon , Lyall Hermione , Milheiro Silva Tiago , Simon Katie , Tickner Neil , Turkova Anna , Welch Steven , Foster Caroline 
Published: October 2024

Objective:
The aim of this study was to identify the prevalence of emergent integrase drug resistance mutations (INSTI-DRMs) in international referrals to a perinatal virtual clinic (PVC).

Design:
A retrospective cohort study.

Setting:
Monthly multidisciplinary PVC reviewing complex case management for children and adolescents with perinatally acquired HIV (CAWHIV).

Participants:
One hundred fourteen cases referred for virological failure between October 2018 and January 2024.

Main outcome measures:
Data collected included age, sex, weight, country of residence, antiretroviral therapy (ART) history, HIV viral load, CD4+ cell count, and comorbidities. Resistance mutations were interpreted using the Stanford HIV Drug Resistance database with emergent major INSTI-DRMs described.

Results:
Of 114 referrals, 103 (90%) had resistance sequences available. Prior INSTI exposure was documented in 61/103 (59%) with 19/61 (31%) having INSTI-DRMs. For these 19, median (IQR) age was 11 years (6–14), weight 25 kg (17–50), CD4+ cell count 485 cells/μl (153–805), and viral load 84 000 copies/ml (2380–137 000). Twelve of 19 (65%) were from low/middle-income countries (LMIC), 6/19 (32%) had current AIDS diagnoses with 14/19 (74%) referred from 2022 onwards. There were a median three prior regimens with 13/19 (68%) having at least 3 class resistance. Two developed INSTI-DRMs on first-line dolutegravir (DTG)-based ART, 17 on second+ line therapy. PVC recommendations were for tenofovir+ lamivudine/emtricitabine (six split adult tablets) with boosted darunavir [19; six twice daily (b.i.d.)], with b.i.d. DTG (6), plus fostemsavir (1) and ibalizumab (1).

Conclusion:
Although uncommon, INSTI resistance is emerging, mainly in highly treatment experienced CAWHIV from LMIC, highlighting the global need for access to boosted protease inhibitors and novel classes, including formulations for children less than 35 kg.
Loss of IVNS1ABP, a gigaxonin paralogue, leads to a progeroid neuropathy due to impaired proteostasis
Authors: Bonnard Carine , Ali Ain Nur , Yuan Fang , Tan Kiat Y. , Lim Yan T. , Chan Puck W. , Ramanathan Nanthini , Kamsani Nur A.B.M. , Chaganty Vindhya , Xiong Ding , Tan Ye S. , Chou Shu-Min , Chourabi Marwa , Narayanan Gunaseelan , Ng Alvin Y.J. , Tohari Sumanty , Yang Meah W. , Karaman Birsen , Turgut Gözde T. , Szenker-Ravi Emmanuelle , Sobota Radoslaw M. , Chen Zhuoyao , Bullock Alex N. , Fathallah Rajaa , Altunoglu Umut , Byrappa Venkatesh , Mathuru Ajay S. , Shboul Mohammad , Zhang Su-Chun , Reversade Bruno 
Published: October 2024

SummaryImpaired proteostasis can induce protein aggregation which is toxic to neuronal cells, contributing to neurodegeneration and other signs of aging. In this study, we delineate an early-onset progressive neuropathy evoking Giant Axonal Neuropathy 1. The causative geneIVNS1ABPencodes a E3-ubiquitin ligase adaptor which is a close gigaxonin paralogue. Patient-derived fibroblasts, iPSCs, and neural progenitors exhibited hallmarks of protein accumulation and lysosomal dysfunction. Ubiquitome analysis revealed overlapping targets with gigaxonin, including Vimentin and MAP1B. The biallelic correction to the isogenic wildtype state in disease- relevant motor neurons partly rescued cellular vulnerabilities. A newly generatedivns1abpa/bknockout zebrafish model partially recapitulated the human peripheral neuropathy, exhibiting aberrant primary motor neuron axon pathfinding, leading to impaired locomotion. Our findings indicate that IVNS1ABP functions in the same pathway as gigaxonin, ensuring appropriate cellular turnover of critical protein substrates, whose accumulation leads to accelerated aging in discrete cellular lineages.
Genular: An Integrated Platform for Defining Cellular Identity and Function through Single-Cell Gene Expression and Multi-Domain Biological Data
Authors: Tomic Ivan , Hao Stephanie P , Tomic Adriana 
Published: October 2024

AbstractAccurately defining cellular identity and function is essential for advancing immunology, understanding disease mechanisms, and developing targeted therapies. However, current bioinformatics tools are limited in their ability to integrate and analyze the vast and diverse single-cell RNA sequencing (scRNA-seq) datasets available, hindering the comprehensive capture of cellular heterogeneity and the identification of subtle genetic changes across immune states, differentiation pathways, and tissue contexts. To overcome these challenges, we introducegenular, an open-source platform that unifies gene expression data analysis across diverse cell types by integrating scRNA-seq data with extensive genomic and proteomic information from 16 databases, including NCBI Gene, Human Protein Atlas, STRING, and UniProt.genularaggregates data from more than 2,893 scRNA-seq experiments, encompassing over 74.5 million unique cells across various tissues and conditions. A key feature ofgenularis calculating a cell marker score for each gene, enabling the quantification of gene expression across cells to derive unique profiles specific to cell types, states, and lineages. Usinggenular, we differentiate T cell memory states, map differentiation profiles by tracking gene expression changes as monocytes mature into macrophages and lymphoid progenitor cells develop into T cells, and capture tissue-specific reprogramming of macrophages, revealing distinct gene expression profiles that enable specialized functions in different tissues. By integrating scRNA-seq data with multi-domain biological information and employing advanced statistical methodologies,genularprovides a scalable platform that accurately defines cellular identities, functional states, and differentiation pathways. This comprehensive approach facilitates breakthroughs in immunology, gene regulation, cellular differentiation, and disease research, enabling a deeper understanding of immune cell functions and their roles in health and disease.
Tricked by Edge Cases: Can Current Approaches Lead to Accurate Prediction of T-Cell Specificity with Machine Learning?
Authors: Culka Martin , Orlova Darya 
Published: October 2024

AbstractThe ability to predict T-cell receptor (TCR) specificity computationally could revolutionize personalized immunotherapies, vaccine development, and the understanding of immunology and autoimmune diseases. While progress depends on obtaining training data that represent the vast range of possible TCR-ligand pairs, systematic assessment of modeling assumptions is equally important and can begin with existing data. We illustrate this by evaluating two ideas currently present in the field1,2: treating TCR specificity and T cell activation as distinct modeling tasks, and using unsupervised models based on sequence similarity for TCR specificity prediction. Although presented as general strategies, we argue these are exceptions rather than universally applicable principles.