bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of postpartum hemorrhage (PPH) using machine learning algorithms in a Kenyan population
Authors: Shah Santosh Yogendra , Saxena Sumant , Rani Satya Pavitra , Nelaturi Naresh , Gill Sheena , Tippett Barr Beth , Were Joyce , Khagayi Sammy , Ouma Gregory , Akelo Victor , Norwitz Errol R. , Ramakrishnan Rama , Onyango Dickens , Teltumbade Manoj 
Published: July 2023

IntroductionPostpartum hemorrhage (PPH) is a significant cause of maternal mortality worldwide, particularly in low- and middle-income countries. It is essential to develop effective prediction models to identify women at risk of PPH and implement appropriate interventions to reduce maternal morbidity and mortality. This study aims to predict the occurrence of postpartum hemorrhage using machine learning models based on antenatal, intrapartum, and postnatal visit data obtained from the Kenya Antenatal and Postnatal Care Research Collective cohort.MethodFour machine learning models – logistic regression, naïve Bayes, decision tree, and random forest – were constructed using 67% training data (1,056/1,576). The training data was further split into 67% for model building and 33% cross validation. Once the models are built, the remaining 33% (520/1,576) independent test data was used for external validation to confirm the models' performance. Models were fine-tuned using feature selection through extra tree classifier technique. Model performance was assessed using accuracy, sensitivity, and area under the curve (AUC) of the receiver operating characteristics (ROC) curve.ResultThe naïve Bayes model performed best with 0.95 accuracy, 0.97 specificity, and 0.76 AUC. Seven factors (anemia, limited prenatal care, hemoglobin concentrations, signs of pallor at intrapartum, intrapartum systolic blood pressure, intrapartum diastolic blood pressure, and intrapartum respiratory rate) were associated with PPH prediction in Kenyan population.DiscussionThis study demonstrates the potential of machine learning models in predicting PPH in the Kenyan population. Future studies with larger datasets and more PPH cases should be conducted to improve prediction performance of machine learning model. Such prediction algorithms would immensely help to construct a personalized obstetric path for each pregnant patient, improve resource allocation, and reduce maternal mortality and morbidity.
Endothelial exosomes work as a functional mediator to activate macrophages
Authors: Lin Wenwen , Huang Feng , Yuan Yin , Li Qiaowei , Lin Zhong , Zhu Wenqing , Lin Binbin , Zhu Pengli 
Published: July 2023

IntroductionIntercellular communication is essential for almost all physiological and pathological processes. Endothelial cell (EC)-derived exosomes, working as mediators for intercellular information exchange, are involved in the pathophysiological mechanisms of atherosclerosis. However, the effect of inflamed endothelial exosomes on the function of macrophages (Mϕ) is poorly defined. This study aims to unravel how exosomes derived from tumor necrosis factor-α (TNF-α)-stimulated ECs (exo-T) affect Mϕ in vitro.Methods and resultsExosomes derived from untreated ECs (exo) and exo-T were identified by using TEM, NTA, and western blot, and we observed that PKH67-labeled exo/exo-T were taken up by Mϕ. Exposure to exo-T for 24 h not only skewed Mϕ to the M1 subtype and exacerbated lipid deposition, but also promoted Mϕ apoptosis, while it did not significantly affect Mϕ migration, as detected by RT-qPCR, Dil-ox-LDL uptake assay, flow cytometry, wound healing assay, and transwell assay, respectively. In addition, exo/exo-T-related microRNA-Seq revealed 104 significantly differentially expressed microRNAs (DE-miRNAs). The target genes of DE-miRNAs were mainly enriched functionally in metabolic pathways, MAPK signaling pathway, etc., as determined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. We further demonstrated by immunoblotting that exo-T intervention improves the phosphorylation of MAPK/NF-κB-related proteins.Discussion and conclusionCollectively, this study reveals that inflamed endothelial exosomes (TNF-α-stimulated EC-derived exosomes) work as a functional mediator to affect Mϕ function and may activate Mϕ through MAPK/NF-κB signaling pathways.
Antibody responses to an inactivated SARS-CoV-2 vaccine in individuals aged from 50 to 102 years
Authors: Zhu Hong-Hong , Sun Guo-Qing , Wu Ji-Yu , Fan Su-Qing , Zhu Ying-Ying , Wang Zhi-Cheng , Liao Xiao-Fang 
Published: July 2023

ObjectivesTo assess antibody responses to an inactivated SARS-CoV-2 vaccine in individuals aged 50 and older.MethodsWe conducted a post-market cross-sectional seroepidemiology study. We recruited 4,632 vaccinated individuals aged 50 and older, measured their total serum SARS-CoV-2-specific antibody (TA), and collected correlates. The primary outcome was the geometric mean titer (GMT) of TA, and the secondary outcome was the decline of TA with age. Univariate, bivariate, and multivariate analyses were used to examine the associations of the TA GMT with age, and trend analyses were used to test whether their associations were significant.ResultsAll participants had a detectable TA, which was generally at a low level across all age groups. The TA GMT (95% CI) in AU/mL was 3.05 (2.93, 3.18); the corresponding arithmetic mean (95% CI) was 17.77 (16.13, 19.42) in all participants and 4.33 (3.88, 4.84), 3.86 (3.49, 4.28), 3.24 (2.92, 3.59), 2.77 (2.60, 2.96), and 2.65 (2.48, 2.83) in the age groups of 50-54, 55-59, 60-64, 65-74, and 75 years or older, respectively. The TA GMT decreased with age with a Ptrend &lt; 0.001. The TA GMT was significantly lower in those with hypertension or diabetes compared to those with neither.ConclusionThe inactivated SARS-CoV-2 vaccine is effective in individuals aged 50 and older. This is the first study that has found an inverse dose-response relationship between ages and the low-level TAs. Older people, especially those with chronic diseases, should get the SARS-CoV-2 vaccine, and their vaccination frequency, dose, and method may need to be different from those of younger people.
Machine learning-based integration develops a neutrophil-derived signature for improving outcomes in hepatocellular carcinoma
Authors: Gong Qiming , Chen Xiaodan , Liu Fahui , Cao Yuhua 
Published: July 2023

IntroductionThe heterogeneity of tumor immune microenvironments is a major factor in poor prognosis among hepatocellular carcinoma (HCC) patients. Neutrophils have been identified as playing a critical role in the immune microenvironment of HCC based on recent single-cell studies. However, there is still a need to stratify HCC patients based on neutrophil heterogeneity. Therefore, developing an approach that efficiently describes "neutrophil characteristics" in HCC patients is crucial to guide clinical decision-making.MethodsWe stratified two cohorts of HCC patients into molecular subtypes associated with neutrophils using bulk-sequencing and single-cell sequencing data. Additionally, we constructed a new risk model by integrating machine learning analysis from 101 prediction models. We compared the biological and molecular features among patient subgroups to assess the model's effectiveness. Furthermore, an essential gene identified in this study was validated through molecular biology experiments.ResultsWe stratified patients with HCC into subtypes that exhibited significant differences in prognosis, clinical pathological characteristics, inflammation-related pathways, levels of immune infiltration, and expression levels of immune genes. Furthermore, A risk model called the "neutrophil-derived signature" (NDS) was constructed using machine learning, consisting of 10 essential genes. The NDS's RiskScore demonstrated superior accuracy to clinical variables and correlated with higher malignancy degrees. RiskScore was an independent prognostic factor for overall survival and showed predictive value for HCC patient prognosis. Additionally, we observed associations between RiskScore and the efficacy of immune therapy and chemotherapy drugs.DiscussionOur study highlights the critical role of neutrophils in the tumor microenvironment of HCC. The developed NDS is a powerful tool for assessing the risk and clinical treatment of HCC. Furthermore, we identified and analyzed the feasibility of the critical gene RTN3 in NDS as a molecular marker for HCC.
Identification of novel clusters of co-expressing cytokines in a diagnostic cytokine multiplex test
Authors: Polley Daniel J. , Latham Penny , Choi May Y. , Buhler Katherine A. , Fritzler Marvin J. , Fritzler Mark L. 
Published: July 2023

IntroductionCytokines are mediators of the immune system that are essential for the maintenance, development and resolution of immune responses. Beneficial immune responses depend on complex, interdependent networks of signaling and regulatory events in which individual cytokines influence the production and release of others. Since disruptions in these signaling networks are associated with a wide spectrum of diseases, cytokines have gained considerable interest as diagnostic, prognostic and precision therapy-relevant biomarkers. However, currently individual cytokines testing has limited value because the wider immune response context is often overlooked. The aim of this study was to identify specific cytokine signaling patterns associated with different diseases.MethodsUnbiased clustering analyses were performed on a clinical cytokine multiplex test using a cohort of human plasma specimens drawn from individuals with known or suspected diseases for which cytokine profiling was considered clinically indicated by the attending physician.Results and discussionSeven clusters of co-expressing cytokines were identified, representing common patterns of immune activation. Common expression profiles of the cytokine clusters and preliminary associations of these profiles with specific diseases or disease categories were also identified. These findings increase our understanding of the immune environments underlying the clinical presentations of patients of inflammatory, autoimmune and neoplastic diseases, which could then improve diagnoses and the identification of evidence-based treatment targets.
Plasma metabolomic signatures of breast cancer
Authors: Xu Yali , Zhao Bin , Xu Zhu , Li Xiaogang , Sun Qiang 
Published: July 2023

BackgroundBreast cancer is a common malignant tumor. A large number of medical evidence shows that breast cancer screening can improve the early diagnosis rate and reduce the mortality rate of breast cancer. In the present study, a wide range of targeted metabolomics profiling was conducted to investigate the plasma signatures of breast cancer.MethodsA total of 86 patients with benign breast abnormalities (L group) and 143 patients with breast cancer (E group) were recruited. We collected their plasma samples and clinical information. Metabolomic analysis, based on the coverage of a wide range of targeted metabolomics was conducted with ultraperformance liquid chromatography- triple quadrupole-linear ion trap mass spectrometer (UPLC-QTRAP-MS).ResultsWe identified 716 metabolites through widely-targeted metabolomics. Serotonergic synapse was the main different metabolic pathway. The fold change of 14 metabolites was considered significantly different (fold change &lt;0.67 or fold change &gt;2; p &lt; 0.05). By combining all the 14 metabolites, we achieved differentiation of L group vs. E group (AUC = 0.792, 95%Cl: 0.662–0.809).ConclusionThis study provided new insights into plasma biomarkers for differential diagnosis of benign abnormalities and breast cancer.
Impact of discontinuing non-pharmacological interventions on cognitive impairment in dementia patients by COVID-19 lockdown. A pilot observational, longitudinal, retrospective study carried out in an adult day center in Spain during the COVID-19 pandemic
Authors: Sánchez-Valdeón Leticia , Bello-Corral Laura , Mayo-Iscar Agustín , Fernández-Lázaro Diego , Seco-Calvo Jesús 
Published: July 2023

BackgroundThe lockdown imposed during the COVID-19 pandemic led to social isolation and prevented patients with dementia from receiving a suite of non-pharmacological interventions (NPIs) that prevent cognitive decline. This discontinuation of NPIs could substantially affect the mental health status of people with dementia in social care settings, such as adult day care centers (ADCs).ProposeThe study aimed to evaluate the effects of the COVID-19 lockdown on mental health and cognitive impairment in patients with dementia who could not attend their usual ADCs and did not receive our NPIs, based on World Health Organization (WHO) Guidelines.MethodsObservational, longitudinal, retrospective study carried out in an adult day center in Spain and reported it in accordance with the Strengthening Reporting of Observational Studies in Epidemiology (STROBE) statement. Cognitive status was assessed using the Mini-Mental State Examination (MMSE) in 80 patients attending the ADC of the “Leonese Association of Dementia Patients” (León, Spain), who had been evaluated with this instrument before the COVID-19 lockdown.ResultsWe observed a 0.4-point decrease in MMSE score/month (IQR = 1.4) during lockdown versus a 0.1-point decrease/month (IQR = 0.3) before this period (p = 0.038). Notably, this translated to &gt;10-point decreases in MMSE score/year in 33.8% of participants during lockdown versus 5.5% earlier (p &lt; 0.001). No statistically significant associations (p &lt; 0.05) were found between the individual characteristics of the caregivers and the occurrence of the event.ConclusionThe reported declines in MMSE scores reveal a significant acceleration of cognitive decline during the period of inactivity. This could suggest that our NPIs, focused on slowing cognitive decline, are beneficial and, therefore, necessary in patients with dementia.
Dissecting contributions of individual systemic inflammatory response syndrome criteria from a prospective algorithm to the prediction and diagnosis of sepsis in a polytrauma cohort
Authors: Schefzik Roman , Hahn Bianka , Schneider-Lindner Verena 
Published: July 2023

BackgroundSepsis is the leading cause of death in intensive care units (ICUs), and its timely detection and treatment improve clinical outcome and survival. Systemic inflammatory response syndrome (SIRS) refers to the concurrent fulfillment of at least two out of the following four clinical criteria: tachycardia, tachypnea, abnormal body temperature, and abnormal leukocyte count. While SIRS was controversially abandoned from the current sepsis definition, a dynamic SIRS representation still has potential for sepsis prediction and diagnosis.ObjectiveWe retrospectively elucidate the individual contributions of the SIRS criteria in a polytrauma cohort from the post-surgical ICU of University Medical Center Mannheim (Germany).MethodsWe used a dynamic and prospective SIRS algorithm tailored to the ICU setting by accounting for catecholamine therapy and mechanical ventilation. Two clinically relevant tasks are considered: (i) sepsis prediction using the first 24 h after admission to our ICU, and (ii) sepsis diagnosis using the last 24 h before sepsis onset and a time point of comparable ICU treatment duration for controls, respectively. We determine the importance of individual SIRS criteria by systematically varying criteria weights when summarizing the SIRS algorithm output with SIRS descriptors and assessing the classification performance of the resulting logistic regression models using a specifically developed ranking score.ResultsOur models perform better for the diagnosis than the prediction task (maximum AUROC 0.816 vs. 0.693). Risk models containing only the SIRS level average mostly show reasonable performance across criteria weights, with prediction and diagnosis AUROCs ranging from 0.455 (weight on leukocyte criterion only) to 0.693 and 0.619 to 0.800, respectively. For sepsis prediction, temperature and tachypnea are the most important SIRS criteria, whereas the leukocytes criterion is least important and potentially even counterproductive. For sepsis diagnosis, all SIRS criteria are relevant, with the temperature criterion being most influential.ConclusionSIRS is relevant for sepsis prediction and diagnosis in polytrauma, and no criterion should a priori be omitted. Hence, the original expert-defined SIRS criteria are valid, capturing important sepsis risk determinants. Our prospective SIRS algorithm provides dynamic determination of SIRS criteria and descriptors, allowing their integration in sepsis risk models also in other settings.
Wilder than intense: higher frequency, variability, and viral flows of porcine circovirus 3 in wild boars and rural farms compared to intensive ones in northern Italy
Authors: Franzo Giovanni , Faustini Giulia , Legnardi Matteo , Berto Giacomo , Dal Maso Mariangela , Genna Viviana , Menandro Maria Luisa , Poletto Francesca , Cecchinato Mattia , Drigo Michele , Tucciarone Claudia Maria 
Published: July 2023

IntroductionPorcine circovirus 3 (PCV-3) was firstly reported in 2017. Although evidence of its pathogenic role has been provided, its clinical relevance seems lower than Porcine circovirus 2 (PCV-2), as well as its evolutionary rate. Different studies have reported a high PCV-3 prevalence in wild boars, sometimes higher than the one observed in commercial pigs. Nevertheless, to date, few studies have objectively investigated the relationships between these populations when inhabiting the same area. Moreover, the role of small-scale, backyard pig production in PCV-3 epidemiology is still obscure.MethodsThe present study investigated PCV-3 occurrence in 216 samples collected from the same area of Northern Italy from commercial and rural pigs, and wild boars. PCV-3 presence was tested by qPCR and complete genome or ORF2 sequences were obtained when possible and analysed using a combination of statistical, phylogenetic and phylodynamic approaches.ResultsA higher infection risk in wild boars and rural pigs compared to the commercial ones was demonstrated. The phylodynamic analysis confirmed a larger viral population size in wild and rural populations and estimated a preferential viral flow from these populations to commercial pigs. A significant flow from wild to rural animals was also proven. The analysis of the Italian sequences and the comparison with a broader international reference dataset highlighted the circulation of a highly divergent clade in Italian rural pigs and wild boars only.DiscussionOverall, the present study results demonstrate the role of non-commercial pig populations in PCV-3 maintenance, epidemiology and evolution, which could represent a threat to intensive farming.
Sport dependent effects on the sensory control of balance during upright posture: a comparison between professional horseback riders, judokas and non-athletes
Authors: Viseu Jean-Philippe , Yiou Eric , Morin Pierre-Olivier , Olivier Agnès 
Published: July 2023

IntroductionCompared to judokas (JU) and non-athletes (NA), horseback riders (HR) may develop specific changes in their sensory control of balance.MethodsThirty-four international-level JU, twenty-seven international-level HR and twenty-one NA participated. Participants stood upright on a plateform (static condition) or on a seesaw device with an instability along the mediolateral (ML) or the anteroposterior (AP) direction (dynamic conditions). These conditions were carried out with eyes opened (EO) or closed (EC), and with (wF) or without a foam (nF). Experimental variables included conventional (linear), non-linear center-of-pressure (COP) parameters, Romberg Quotient (RQ) and Plantar Quotient (PQ).ResultsGroup effects. COP Surface (COPS) and standard deviation of COP along AP (SDY) were lower in HR than in JU in Static. SD Y was lower in HR than in JU in Dynamic AP. COP velocity (COPV) was lower in both HR and JU than in NA in Static and Dynamic. Sample entropy along AP and ML (SampEnY and SampEnX) were higher in HR than in JU in Static. SampEnY was higher in HR than in JU in Dynamic ML. Sensory effects. In EC, COPV was lower in JU than in NA in Dynamic AP, and lower in JU than in both HR and NA in Dynamic ML. In EO, COPV was lower in both JU and HR than in NA in Dynamic ML. RQ applied to COPS was lower in JU than in both HR and NA in Dynamic AP, and lower in JU than in HR in Dynamic ML. RQ applied to COPV was lower in JU than in both HR and NA in Static and Dynamic. PQ applied to COPS was higher in JU than in both HR and NA in Dynamic ML.ConclusionResults showed that the effects of sport expertise on postural control could only be revealed with specific COP variables and were directionally oriented and sport-dependant. HR seem to rely more on vision than JU, thus revealing that the contribution of the sensory inputs to balance control is also sport-dependent. Results open up new knowledge on the specificity of sport practice on multisensory balance information during upright posture.
Development and validation of risk prediction model for sarcopenia in patients with colorectal cancer
Authors: Zhang Ying , Zhu Yongjian 
Published: July 2023

ObjectivesSarcopenia is associated with a poor prognosis in patients with colorectal cancer. However, the clinical factors that lead to colorectal cancer patients with sarcopenia are still unclear. The objective of this study is to develop and validate a nomogram for predicting the occurrence of sarcopenia and to provide healthcare professionals with a reliable tool for early identification of high-risk patients with colorectal cancer associated sarcopenia.MethodsA total of 359 patients diagnosed with colorectal cancer from July 2021 to May 2022 were included. All patients were randomly divided into a training (n = 287) cohort and a validation cohort (n = 72) at the ratio of 80/20. Univariate and multivariate logistic analysis were performed to evaluate the factors associated with sarcopenia. The diagnostic nomogram of sarcopenia in patients with colorectal cancer was constructed in the training cohort and validated in the validation cohort. Various evaluation metrics were employed to assess the performance of the developed nomogram, including the ROC curve, calibration curve, and Hosmer-Lemeshow test.ResultsSmoking history, drinking history, diabetes, TNM stage, nutritional status, and physical activity were included in the nomogram for the prediction of sarcopenia. The diagnostic nomograms demonstrated excellent discrimination, with AUC values of 0.971 and 0.922 in the training and validation cohorts, respectively. Moreover, the calibration performance of the nomogram is also excellent, as evidenced by the Hosmer-Lemeshow test result of 0.886.ConclusionsThe nomogram consisting of preoperative factors was able to successfully predict the occurrence of sarcopenia in colorectal cancer patients, aiding in the early identification of high-risk patients and facilitating timely implementation of appropriate intervention measures.