bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tranexamic acid for the prevention and treatment of postpartum hemorrhage in resource-limited settings: a literature review
Authors: Gedeno Gelebo Kanbiro , Mulugeta Hailemariam , Mossie Addisu , Geremu Kuchulo , Darma Bahiru 
Published: November 2023

Introduction:
Postpartum haemorrhage is a major cause of maternal morbidity and mortality worldwide. Early recognition and appropriate treatment are crucial for managing postpartum haemorrhage.

Objectives:
This literature review aimed to evaluate the efficacy of tranexamic acid in the prevention and treatment of postpartum haemorrhage in resource-limited settings.

Search methods:
This literature review was conducted based on the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. A computerized systematic search of the MEDLINE (PubMed), Google Scholar, and Cochrane databases using a combination of the following Medical Subject Headings (MeSH) terms for PubMed: [(obstetric haemorrhage OR postpartum haemorrhage OR massive obstetric haemorrhage) AND (tranexamic acid OR antifibrinolytic drugs) AND (prophylaxis OR prevention) AND (management OR treatment) AND (resource-limited settings OR resource-limited area OR developing countries)] to find articles published in English since 2010.

Selection criteria:
Studies on the obstetric population who underwent vaginal or caesarean delivery, comparing the use of tranexamic acid versus placebo (or no treatment) for treatment (or prevention) of postpartum haemorrhage with the outcome of postpartum haemorrhage rate, blood transfusion requirements, uterotonics requirements, hysterectomy, or mortality were included.

Result:
In total, 5315 articles were identified. Following the elimination of duplicates, the methodological quality of 15 studies was evaluated independently, with eligibility determined based on the inclusion and exclusion criteria, as well as outcome variables. Finally, eight articles were included in the review.

Conclusion:
This review provides evidence that the administration of tranexamic acid has the potential to decrease the need for blood transfusion, incidence of postpartum haemorrhage, demand for supplementary uterotonics, and maternal morbidity and mortality with marginal adverse effects. Healthcare systems must develop and implement interventions that involve the use of tranexamic acid for the treatment of postpartum haemorrhage in resource-limited settings.
CIRC-MARC2 SILENCING PROTECTS HUMAN CARDIOMYOCYTES FROM HYPOXIA/REOXYGENATION–INDUCED INJURY BY MODULATING MIR-335-5P/TRPM7 AXIS
Authors: Deng Huazhao , Cui Meihong , Liu Ling , Yang Fei 
Published: November 2023

ABSTRACT
Myocardial ischemia-reperfusion injury (MIRI) is a vital risk factor for cardiovascular diseases. Some circular RNAs have been identified as modulators of MIRI. However, the effects of circ-mitochondrial amidoxime reducing component 2 (circ-MARC2) in MIRI are unclear. Our results showed that circ-MARC2 was overexpressed in hypoxia/reoxygenation (H/R)–treated AC16 cells. Circ-MARC2 silencing reversed the inhibitory effect of H/R treatment on cell proliferation and promoting effects on lactate dehydrogenase activity, creatine kinase activity, and cell apoptosis in AC16 cells. Moreover, circ-MARC2 served as the sponge for miR-335-5p and ameliorated H/R-induced AC16 cell damage by decoying miR-335-5p. In addition, transient receptor potential cation channel subfamily M member 7 (TRPM7) was identified as the target gene of miR-335-5p. Overexpression of miR-335-5p relieved H/R-induced AC16 cell damage, whereas TRPM7 elevation abolished the effect. Circ-MARC2 knockdown was able to relieve H/R-induced AC16 cell injury through miR-335-5p/TRPM7 axis.
Assessment of abnormal skeletal muscle perfusion by contrast-enhanced ultrasound with parametric imaging in rats after severe injury, hemorrhagic shock, and whole blood resuscitation
Authors: St. John Alexander , Wang Xu , Ringgold Kristyn , Lindner Jonathan , White Nathan , Stern Susan , López José 
Published: November 2023

Abstract

Background
After severe injury, optical measures of microvascular blood flow (MBF) decrease and do not normalize with resuscitation to normal blood pressure. These changes are associated with organ dysfunction, coagulopathy, and death. However, the pathophysiology is not well understood. Several possible pathways could also contribute to the development of trauma-induced coagulopathy (TIC). A small-animal model of trauma-related MBF derangement that persists after resuscitation and includes TIC would facilitate further study. Parametric contrast-enhanced ultrasound (CEUS) is particularly advantageous in this setting, because it noninvasively assesses MBF in large, deep vascular beds. We sought to develop such a model, measuring MBF with CEUS.

Methods
Sixteen male Sprague-Dawley rats were anesthetized, ventilated, and cannulated. Rats were subjected to either no injury (Sham group) or a standardized polytrauma and pressure-targeted arterial catheter hemorrhage with subsequent whole blood resuscitation (Trauma group). At prespecified timepoints, CEUS measurements of uninjured quadriceps muscle, viscoelastic blood clot strength, and complete blood counts were taken.

Results
After resuscitation, blood pressure normalized, but MBF decreased and remained low for the rest of the protocol. This was primarily driven by a decrease in blood volume with a relative sparing of blood velocity. Viscoelastic blood clot strength and platelet count also decreased and remained low throughout the protocol.

Conclusions
We present a rat model of MBF derangement in uninjured skeletal muscle and coagulopathy after polytrauma that persists after resuscitation with whole blood to normal macrohemodynamics. Parametric CEUS analysis shows this change is primarily due to microvascular obstruction. This platform can be used to develop a deeper understanding of this important process.
HYDROGEN PREVENTS LIPOPOLYSACCHARIDE-INDUCED PULMONARY MICROVASCULAR ENDOTHELIAL CELL INJURY BY INHIBITING STORE-OPERATED Ca2+ ENTRY REGULATED BY STIM1/ORAI1
Authors: Li Yuan , Chen Hongguang , Shu Ruichen , Zhang Xuan , Wang Guiyue , Yin Yiqing 
Published: November 2023

ABSTRACTBackground:Sepsis is a type of life-threatening organ dysfunction that is caused by a dysregulated host response to infection. The lung is the most vulnerable target organ under septic conditions. Pulmonary microvascular endothelial cells (PMVECs) play a critical role in acute lung injury (ALI) caused by severe sepsis. The impairment of PMVECs during sepsis is a complex regulatory process involving multiple mechanisms, in which the imbalance of calcium (Ca2+) homeostasis of endothelial cells is a key factor in its functional impairment. Our preliminary results indicated that hydrogen gas (H2) treatment significantly alleviates lung injury in sepsis, protects PMVECs from hyperpermeability, and decreases the expression of plasma membrane stromal interaction molecule 1 (STIM1), but the underlying mechanism by which H2maintains Ca2+homeostasis in endothelial cells in septic models remains unclear. Thus, the purpose of the present study was to investigate the molecular mechanism of STIM1 and Ca2+release–activated Ca2+channel protein1 (Orai1) regulation by H2treatment and explore the effect of H2treatment on Ca2+homeostasis in lipopolysaccharide (LPS)-induced PMVECs and LPS-challenged mice.Methods:We observed the role of H2on LPS-induced ALI of micein vivo. The lung wet/dry weight ratio, total protein in the bronchoalveolar lavage fluid, and Evans blue dye assay were used to evaluate the pulmonary endothelial barrier damage of LPS-challenged mice. The expression of STIM1 and Orai1 was also detected using epifluorescence microscopy. Moreover, we also investigated the role of H2-rich medium in regulating PMVECs under LPS treatment, which induced injury similar to sepsisin vitro. The expression of STIM1 and Orai1 as well as the Ca2+concentration in PMVECs was examined.Results:In vivo, we found that H2alleviated ALI of mice through decreasing lung wet/dry weight ratio, total protein in the bronchoalveolar lavage fluid and permeability of lung. In addition, H2also decreased the expression of STIM1 and Orai1 in pulmonary microvascular endothelium.In vitro, LPS treatment increased the expression levels of STIM1 and Orai1 in PMVECs, while H2reversed these changes. Furthermore, H2ameliorated Ca2+influx under sepsis-mimicking conditions. Treatment with the sarco/endoplasmic reticulum Ca2+adenosine triphosphatase inhibitor, thapsigargin, resulted in a significant reduction in cell viability as well as a reduction in the expression of junctional proteins, including vascular endothelial-cadherin and occludin. Treatment with the store-operated Ca2+entry inhibitor, YM-58483 (BTP2), increased the cell viability and expression of junctional proteins.Conclusions:The present study suggested that H2treatment alleviates LPS-induced PMVEC dysfunction by inhibiting store-operated Ca2+entry mediated by STIM1 and Orai1in vitroandin vivo.
Psychometric Properties of the Chinese Version of the ElectroConvulsive Therapy Cognitive Assessment
Authors: Liu Xinyu , Liang Sixiang , Liu Jun , Sha Sha , Zhang Ling , Jiang Wei , Jiang Changqing , Hermida Adriana P. , Tang Yilang , McDonald William M. , Ren Yanping , Wang Gang 
Published: November 2023

Objectives
Electroconvulsive therapy (ECT) is an effective somatic treatment, but it may be limited by cognitive adverse effects. The existing cognitive screening instruments often lack specificity to ECT-associated cognitive deficits. The ElectroConvulsive Therapy Cognitive Assessment was developed and validated in a clinical setting, but the reliability and validity of the Chinese version of ElectroConvulsive Therapy Cognitive Assessment (ECCA-C) have not been studied in a large clinical sample.

Methods
The ECCA-C and the Montreal Cognitive Assessment (MoCA) were administered to patients with major depressive disorder (MDD) undergoing ECT at 3 time points: pretreatment (baseline), before the fifth treatment, and 1 week posttreatment. The instruments were also administered to a sample of healthy subjects.

Results
Sixty-five patients with MDD and 50 age- and sex-matched healthy controls were recruited in this study. Overall, the patient group had statistically significantly lower MoCA and ECCA-C scores than the control group (both P values <0.001). The Cronbach α of the ECCA-C was 0.88 at baseline. Statistically significant decreases over time were observed in ECCA-C: pre-ECT (23.9 ± 4.0) > mid-ECT (21.3 ± 3.4) > post-ECT (18.7 ± 4.8) (all P values <0.001), whereas no statistically significant changes in MoCA scores were found at these 3 time points (F = 1.86, P = 0.165). A cutoff score of 26.5 on the ECCA-C was found to best differentiate between MDD patients and healthy controls.

Conclusions
The ECCA-C showed satisfactory psychometric properties and may be a more sensitive instrument than the MoCA to assess cognitive impairment associated with ECT.
Language Uncovers Visuospatial Dysfunction in Posterior Cortical Atrophy: A Natural Language Processing Approach
Authors: Rezaii Neguine , Hochberg Daisy , Quimby Megan , Wong Bonnie , McGinnis Scott , Dickerson Bradford C , Putcha Deepti 
Published: November 2023

AbstractIntroductionPosterior Cortical Atrophy (PCA) is a syndrome characterized by a progressive decline in higher-order visuospatial processing, leading to symptoms such as space perception deficit, simultanagnosia, and object perception impairment. While PCA is primarily known for its impact on visuospatial abilities, recent studies have documented language abnormalities in PCA patients. This study aims to delineate the nature and origin of language impairments in PCA, hypothesizing that language deficits reflect the visuospatial processing impairments of the disease.MethodsWe compared the language samples of 25 patients with PCA with age-matched cognitively normal (CN) individuals across two distinct tasks: a visually-dependent picture description and a visually-independent job description task. We extracted word frequency, word utterance latency, and spatial relational words for this comparison. We then conducted an in-depth analysis of the language used in the picture description task to identify specific linguistic indicators that reflect the visuospatial processing deficits of PCA.ResultsPatients with PCA showed significant language deficits in the visually-dependent task, characterized by higher word frequency, prolonged utterance latency, and fewer spatial relational words, but not in the visually-independent task. An in-depth analysis of the picture description task further showed that PCA patients struggled to identify certain visual elements as well as the overall theme of the picture. A predictive model based on these language features distinguished PCA patients from CN individuals with high classification accuracy.DiscussionThe findings indicate that language is a sensitive behavioral construct to detect visuospatial processing abnormalities of PCA. These insights offer theoretical and clinical avenues for understanding and managing PCA, underscoring language as a crucial marker for the visuospatial deficits of this atypical variant of Alzheimer’s disease.
The Impact of Group II Pulmonary Hypertension on Congestive Heart Failure Patients Admitted with ST Elevation Myocardial Infarction, A Nationwide Study
Authors: Labban Mohamad El , Mir Mikael R , Abruzzo Alexandra , Boike Sydney , Niaz Fayreal A , Vo Natasha T , Rauf Ibtisam , Khan Syed Anjum 
Published: November 2023

AbstractObjectiveTo study the impact of group II pulmonary hypertension (PH) on the outcomes of patients admitted with ST-elevation Myocardial Infarction (STEMI), we conducted a nationwide retrospective cohort study.Patients and MethodsUsing the National Inpatient Sample (NIS) Database from 2017 to 2020, a retrospective study of adult patients with a principal diagnosis of STEMI with a secondary diagnosis with or without group II PH according to ICD-10 codes. Several demographics, including age, race, and gender, were analyzed. The primary endpoint was mortality, while the secondary endpoints included cardiogenic shock, mechanical intubation, length of stay in days, and patient charge in dollars. Multivariate logistic regression model analysis was used to adjust for confounders, with a p-value less than 0.05 considered statistically significant.ResultsThe study included 27,020 patients admitted with a STEMI, 95 of whom had group II PH. The mean age for patients with and without PH was 66 and 67, respectively. In the PH group, 37% were females compared to 34% in the non-PH group. The in-hospital mortality rate was higher in the PH group (31.5% vs. 9.5%,P <.001, aOR 3.25,P <.023). The rates and adjusted odds of cardiogenic shock and mechanical ventilation were higher in the PH groups (aOR 1.12 aOR 2.16, respectively) but not statistically significant. Patients with PH had a longer length of stay and a higher total charge.ConclusionGroup II PH was associated with worse clinical and economic outcomes in heart failure patients admitted with STEMI.
Locally low-rank denoising in transform domains
Authors: Moeller Steen , Buko Erick O. , Parvaze Suhail P. , Dowdle Logan , Ugurbil Kamil , Johnson Casey P. , Akcakaya Mehmet 
Published: November 2023

AbstractPurposeTo develop an extension to locally low rank (LLR) denoising techniques based on transform domain processing that reduces the number of images required in the MR image series for high-quality denoising.Theory and MethodsLLR methods with random matrix theory-based thresholds are successfully used in the denoising of MR image series in a number of applications. The performance of these methods depend on how well the LLR assumption is satisfied, which deteriorates with few numbers of images, as is commonly encountered in quantitative MRI applications. We propose a transform-domain approach for denoising of MR image series to represent the underlying signal with higher fidelity when using a locally low rank approximation. The efficacy of the method is demonstrated for fully-sampled k-space, undersampled k-space, DICOM images, and complex-valued SENSE-1 images in quantitative MRI applications with as few as 4 images.ResultsFor both MSK and brain applications, the transform domain denoising preserves local subtle variability, whereas the quantitative maps based on image domain LLR methods tend to be locally more homogeneous.ConclusionA transform domain extension to LLR denoising produces high quality images and is compatible with both raw k-space data and vendor reconstructed data. This allows for improved imaging and more accurate quantitative analyses and parameters obtained therefrom.
A validated heart-specific model for splice-disrupting variants in childhood heart disease
Authors: Lesurf Robert , Breckpot Jeroen , Bouwmeester Jade , Hanafi Nour , Jain Anjali , Liang Yijing , Papaz Tanya , Lougheed Jane , Mondal Tapas , Alsalehi Mahmoud , Altamirano-Diaz Luis , Oechslin Erwin , Audain Enrique , Dombrowsky Gregor , Postma Alex V , Woudstra Odilia I , Bouma Berto J , Hitz Marc-Phillip , Bezzina Connie R , Blue Gillian , Winlaw David S , Mital Seema 
Published: November 2023

ABSTRACTCongenital heart disease (CHD) is the most common congenital anomaly. Non-canonical splice-disrupting variants are not routinely evaluated by clinical tests. Algorithms including SpliceAI predict such variants, but are not specific to cardiac-expressed genes. Whole genome (WGS) (n=1083) and myocardial RNA-Sequencing (RNA-Seq) (n=114) of CHD cases was used to identify splice-disrupting variants. Using features of variants confirmed to affect splicing in myocardial RNA, we trained a machine learning model that outperformed SpliceAI for predicting cardiac-specific splice-disrupting variants (AUC 0.92 vs 0.66), and was independently validated in 43 cardiomyopathy probands (AUC 0.88 vs 0.64). Application of this model to 971 CHD WGS samples identified 9% patients with splice-disrupting variants in CHD genes. Forty-one% of predicted splice-disrupting variants were deeply intronic. The burden of variants in CHD genes was higher in cases compared with 2,570 controls. Our model improved genetic yield by identifying splice-disrupting variants that are not evaluated by routine tests.
Repeat mediated excision of gene drive elements for restoring wild-type populations
Authors: Chennuri Pratima R , Zapletal Josef , Monfardini Raquel D , Ndeffo-Mbah Martial Loth , Adelman Zach N , Myles Kevin M 
Published: November 2023

AbstractWe demonstrate here that single strand annealing (SSA) repair can be co-opted for the precise autocatalytic excision of a drive element. Although SSA is not the predominant form of DNA repair in eukaryotic organisms, we increased the likelihood of its use by engineering direct repeats at sites flanking the drive allele, and then introducing a double-strand DNA break (DSB) at a second endonuclease target site encoded within the drive allele. We have termed this technologyRepeatMediatedExcision of aDriveElement (ReMEDE). Incorporation of ReMEDE into the previously described mutagenic chain reaction (MCR) gene drive, targeting theyellowgene ofDrosophila melanogaster, replaced drive alleles with wild-type alleles demonstrating proof-of-principle. Although the ReMEDE system requires further research and development, the technology has a number of attractive features as a gene drive mitigation strategy, chief among these the potential to restore a wild-type population without releasing additional transgenic organisms or large-scale environmental engineering efforts.
VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction
Authors: Li Jing , Zhao Zhongpeng , Tai ChengZheng , Sun Ting , Tan Lingyun , Li Xinyu , He Wei , Li HongJun , Zhang Jing 
Published: November 2023

AbstractBackgroundThe viruses threats provoke concerns regarding their sustained epidemic transmission, making the development of vaccines particularly important. In the prolonged and costly process of vaccine development, the most important initial step is to identify protective immunogens. Machine learning (ML) approaches are productive in analyzing big data such as microbial proteomes, and can remarkably reduce the cost of experimental work in developing novel vaccine candidates.ResultsWe intensively evaluated the immunogenicity prediction power of eight commonly-used ML methods by random sampling cross validation on a large dataset consisting of known viral immunogens and non-immunogens we manually curated from the public domain. XGBoost, kNN and RF showed the strongest predictive power. We then proposed a novel soft-voting based ensemble approach (VirusImmu), which demonstrated a powerful and stable capability for viral immunogenicity prediction across the test set and external test set irrespective of protein sequence length. VirusImmu was successfully applied to facilitate identifying linear B cell epitopes against African Swine Fever Virus as confirmed by indirect ELISA in vitro.ConclusionsVirusImmu exhibited tremendous potentials in predicting immunogenicity of viral protein segments. It is freely accessible athttps://github.com/zhangjbig/VirusImmu.
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing
Authors: Peng Le , Luo Gaoxiang , Zhou Sicheng , Chen Jiandong , Xu Ziyue , Zhang Rui , Sun Ju 
Published: November 2023

AbstractLanguage models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP). However, the medical field faces challenges in training LMs due to limited data access and privacy constraints imposed by regulations like the Health Insurance Portability and Accountability Act (HIPPA) and the General Data Protection Regulation (GDPR). Federated learning (FL) offers a decentralized solution that enables collaborative learning while ensuring data privacy. In this study, we evaluated FL on 2 biomedical NLP tasks encompassing 8 corpora using 6 LMs. Our results show that: 1) FL models consistently outperformed models trained on individual clients’ data and sometimes performed comparably with models trained with polled data; 2) with the fixed number of total data, FL models training with more clients produced inferior performance but pre-trained transformer-based models exhibited great resilience. 3) FL models significantly outperformed large language models using zero-/one-shot learning and offered lightning inference speed.
Multi-omics features-based machine learning method improve immunotherapy response in clear cell renal cell carcinoma
Authors: Zhang Yiqun , Pei Zhihua 
Published: November 2023

AbstractProgrammed cell death 1 (PD-1) or PD-ligand 1 (PD-L1) blocker-based strategies have improved the survival outcomes of clear cell renal cell carcinomas (ccRCCs) in recent years, but only a small number of patients have benefited from them. In this study, we identified three inflammatory features through over 1900 autoimmune nephropathy patients-related bulk RNA sequencing, single-cell RNA sequencing analysis, and three immunogenic signatures using genomics (TIs), both of which are associated with response to immune checkpoint blocks (ICBs) and the survival of ccRCC patients. Here, we developed a framework with a TIs-based machine learning approach to accurately predict ICB efficacy. We enrolled more than 1000 ccRCC patients with ICB treatment from five cohorts to apply the model and demonstrated its excellent specificity and robustness. Moreover, our model outperforms well-known ICB predictive biomarkers such as tumor mutational burden (TMB), PD-L1 expression, and tumor immune microenvironment (TME). Overall, the TIs-ML model provides a novel method for guiding precise immunotherapy in ccRCC.