bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports
Authors: Casey Arlene , Davidson Emma , Grover Claire , Tobin Richard , Grivas Andreas , Zhang Huayu , Schrempf Patrick , O’Neil Alison Q. , Lee Liam , Walsh Michael , Pellie Freya , Ferguson Karen , Cvoro Vera , Wu Honghan , Whalley Heather , Mair Grant , Whiteley William , Alex Beatrice 
Published: September 2023

BackgroundNatural language processing (NLP) has the potential to automate the reading of radiology reports, but there is a need to demonstrate that NLP methods are adaptable and reliable for use in real-world clinical applications.MethodsWe tested the F1 score, precision, and recall to compare NLP tools on a cohort from a study on delirium using images and radiology reports from NHS Fife and a population-based cohort (Generation Scotland) that spans multiple National Health Service health boards. We compared four off-the-shelf rule-based and neural NLP tools (namely, EdIE-R, ALARM+, ESPRESSO, and Sem-EHR) and reported on their performance for three cerebrovascular phenotypes, namely, ischaemic stroke, small vessel disease (SVD), and atrophy. Clinical experts from the EdIE-R team defined phenotypes using labelling techniques developed in the development of EdIE-R, in conjunction with an expert researcher who read underlying images.ResultsEdIE-R obtained the highest F1 score in both cohorts for ischaemic stroke, ≥93%, followed by ALARM+, ≥87%. The F1 score of ESPRESSO was ≥74%, whilst that of Sem-EHR is ≥66%, although ESPRESSO had the highest precision in both cohorts, 90% and 98%. For F1 scores for SVD, EdIE-R scored ≥98% and ALARM+ ≥90%. ESPRESSO scored lowest with ≥77% and Sem-EHR ≥81%. In NHS Fife, F1 scores for atrophy by EdIE-R and ALARM+ were 99%, dropping in Generation Scotland to 96% for EdIE-R and 91% for ALARM+. Sem-EHR performed lowest for atrophy at 89% in NHS Fife and 73% in Generation Scotland. When comparing NLP tool output with brain image reads using F1 scores, ALARM+ scored 80%, outperforming EdIE-R at 66% in ischaemic stroke. For SVD, EdIE-R performed best, scoring 84%, with Sem-EHR 82%. For atrophy, EdIE-R and both ALARM+ versions were comparable at 80%.ConclusionsThe four NLP tools show varying F1 (and precision/recall) scores across all three phenotypes, although more apparent for ischaemic stroke. If NLP tools are to be used in clinical settings, this cannot be performed “out of the box.” It is essential to understand the context of their development to assess whether they are suitable for the task at hand or whether further training, re-training, or modification is required to adapt tools to the target task.
Risk of osteoporosis in patients treated with direct oral anticoagulants vs. warfarin: an analysis of observational studies
Authors: Liu Yumeng , Xie Xiaoping , Bi Songqi , Zhang Qiong , Song Qingxu , Sun Yang , Yu Tiecheng 
Published: September 2023

AimsEvidence on the association between the risk of new-onset osteoporosis and oral anticoagulants remains controversial. We aimed to compare the risk of osteoporosis associated with the use of direct oral anticoagulants (DOACs) with that associated with warfarin use.MethodsStudies published up to 15 March 2023 that investigated the association between the use of DOACs and warfarin and the incidence of osteoporosis were identified by online searches in PubMed, Embase, the Cochrane Library, and Web of Science conducted by two independent investigators. Random-effects or fixed-effect models were employed to synthesize hazard ratios (HRs)/relative ratios (RRs) with 95% confidence intervals (CIs) for estimating the risk of osteoporosis correlated with DOAC and warfarin prescriptions (PROSPERO No. CRD42023401199).ResultsOur meta-analysis ultimately included four studies involving 74,338 patients. The results suggested that DOAC use was associated with a significantly lower incidence of new-onset osteoporosis than warfarin use (pooled HR: 0.71, 95% CI: 0.57 to 0.88, p &lt; 0.001, I2: 85.1%). Subanalyses revealed that rivaroxaban was associated with a lower risk of osteoporosis than both warfarin and dabigatran. In addition, DOACs were associated with a lower risk of developing osteoporosis than warfarin in both male and female patients, in patients with atrial fibrillation (AF), and in patients who underwent therapy for &gt; 365 days.ConclusionDOAC users experienced a lower incidence of osteoporosis than warfarin users. This study may give us insight into safe anticoagulation strategies for patients who are at high risk of developing osteoporosis.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42023401199.
Dry matter dynamics and carbon flux along riverine forests of Gori valley, Western Himalaya
Authors: Bisht Soni , Bargali Surendra Singh , Bargali Kiran , Rawat Yashwant Singh , Rawat Gopal Singh 
Published: September 2023

IntroductionRiverine forests in the Himalaya represent a biodiverse, dynamic, and complex ecosystem that offers numerous ecosystem services to local and downstream communities and also contributes to the regional carbon cycle. However, these forests have not been assessed for their contribution to dry matter dynamics and carbon flux. We studied these parameters along three classes of riverine forests in eastern Uttarakhand, dominated by Macaranga, Alnus, and Quercus-Machilus forest.MethodsUsing volume equations, we assessed tree biomass, carbon storage, and sequestration in the study area.ResultsThe total standing tree biomass in Macaranga, Alnus, and Quercus-Machilus forest ranged from 256.6 to 558.1  Mg  ha−1, 460.7 to 485.8 Mg ha−1, and 508.6 to 692.1 Mg ha−1, respectively. A total of 77.6–79.6% of vegetation biomass was stored in the aboveground biomass and 20.4–22.4% in belowground plant parts across the riverine forests. The carbon stock in Macaranga forest ranged from 115.5 to 251.1 Mg ha−1, in Alnus forest from 207.3 to 218.6 Mg ha−1, and in Quercus-Machilus forest from 228.9 to 311.4 Mg ha−1. The mean annual litterfall was accounted maximum for Quercus-Machilus forest (5.94  ±  0.54 Mg ha−1 yr.−1), followed by Alnus (5.57  ±  0.31 Mg ha−1 yr.−1) and Macaranga forest (4.67  ±  0.39 Mg ha−1 yr.−1). The highest value of litterfall was recorded during summer (3.40  ±  0.01 Mg ha−1 yr.−1) and the lowest in winter (0.74  ±  0.01 Mg ha−1 yr.−1). The mean value of net primary productivity and carbon sequestration was estimated to be highest in Quercus-Machilus forest (15.8  ±  0.9 Mg ha−1 yr.−1 and 7.1  ±  0.9 Mg C ha−1 yr.−1, respectively) and lowest in Alnus forest (13.9  ±  0.3 Mg ha−1 yr.−1 and 6.1  ±  0.3 Mg C ha−1 yr.−1, respectively).DiscussionThe results highlight that riverine forests play a critical role in providing a large sink for atmospheric CO2. To improve sustainable ecosystem services and climate change mitigation, riverine forests must be effectively managed and conserved in the region.
A clinical evaluation of an ex vivo organ culture system to predict patient response to cancer therapy
Authors: Golan Shay , Bar Vered , Salpeter Seth J. , Neev Guy , Creiderman German , Kedar Daniel , Aharon Sara , Turovsky Lubov , Zundelevich Adi , Shahar Hamutal , Shapira Hagit , Mallel Giuseppe , Stossel Erez , Gavert Nancy , Straussman Ravid , Dotan Zohar , Berger Raanan , Stossel Chani , Golan Talia , Halperin Sharon , Leibovici Dan , Breuer Shani , Rottenberg Yakir , Applebaum Liat , Hubert Ayala , Nechushtan Hovav , Peretz Tamar , Zick Aviad , Chertin Boris , Koulikov Dmitry , Sonnenblick Amir , Rosenbaum Eli 
Published: September 2023

IntroductionEx vivo organ cultures (EVOC) were recently optimized to sustain cancer tissue for 5 days with its complete microenvironment. We examined the ability of an EVOC platform to predict patient response to cancer therapy.MethodsA multicenter, prospective, single-arm observational trial. Samples were obtained from patients with newly diagnosed bladder cancer who underwent transurethral resection of bladder tumor and from core needle biopsies of patients with metastatic cancer. The tumors were cut into 250 μM slices and cultured within 24 h, then incubated for 96 h with vehicle or intended to treat drug. The cultures were then fixed and stained to analyze their morphology and cell viability. Each EVOC was given a score based on cell viability, level of damage, and Ki67 proliferation, and the scores were correlated with the patients’ clinical response assessed by pathology or Response Evaluation Criteria in Solid Tumors (RECIST).ResultsThe cancer tissue and microenvironment, including endothelial and immune cells, were preserved at high viability with continued cell division for 5 days, demonstrating active cell signaling dynamics. A total of 34 cancer samples were tested by the platform and were correlated with clinical results. A higher EVOC score was correlated with better clinical response. The EVOC system showed a predictive specificity of 77.7% (7/9, 95% CI 0.4–0.97) and a sensitivity of 96% (24/25, 95% CI 0.80–0.99).ConclusionEVOC cultured for 5 days showed high sensitivity and specificity for predicting clinical response to therapy among patients with muscle-invasive bladder cancer and other solid tumors.
Complexity-based graph convolutional neural network for epilepsy diagnosis in normal, acute, and chronic stages
Authors: Zheng Shiming , Zhang Xiaopei , Song Panpan , Hu Yue , Gong Xi , Peng Xiaoling 
Published: September 2023

IntroductionThe automatic precision detection technology based on electroencephalography (EEG) is essential in epilepsy studies. It can provide objective proof for epilepsy diagnosis, treatment, and evaluation, thus helping doctors improve treatment efficiency. At present, the normal and acute phases of epilepsy can be well identified through EEG analysis, but distinguishing between the normal and chronic phases is still tricky.MethodsIn this paper, five popular complexity indicators of EEG signal, including approximate entropy, sample entropy, permutation entropy, fuzzy entropy and Kolmogorov complexity, are computed from rat hippocampi to characterize the normal, acute, and chronic phases during epileptogenesis. Results of one-way ANOVA and principal component analysis both show that utilizing complexity features, we are able to easily identify differences between normal, acute, and chronic phases. We also propose an innovative framework for epilepsy detection based on graph convolutional neural network (GCNN) using multi-channel EEG complexity as input.ResultsCombining information of five complexity measures at eight channels, our GCNN model demonstrate superior ability in recognizing the normal, acute, and chronic phases. Experiments results show that our GCNN model reached the high prediction accuracy above 98% and F1 score above 97% among these three phases for each individual rat.DiscussionOur research practice based on real data shows that EEG complexity characteristics are of great significance for recognizing different stages of epilepsy.
Effects of imipramine on cancer patients over-expressing Fascin1; description of the HITCLIF clinical trial
Authors: Asensi-Cantó Antonio , Rodríguez-Braun Edith , Beltrán-Videla Asunción , Hurtado Ana María , Conesa-Zamora Pablo 
Published: September 2023

BackgroundTumor invasion and metastasis are responsible for the majority of cancer-related deaths. The identification of molecules involved in these processes is crucial to design effective treatments that can halt the progression of cancer. To spread and metastasize, tumor cells must restructure their cytoskeleton and emit protrusions. A key molecule in this process of creating these invading structures is Fascin1, the main protein involved in the formation of actin cytoskeleton bundles and a consistent marker of bad prognosis in several types of cancer. Recent studies have shown that imipramine, an FDA- and EMA-approved antidepressant, can block Fascin1and prevent the formation of actin bundles, making it a promising candidate for the treatment of Fascin1-expressing cancers. As a result, a clinical trial will be conducted to assess the efficacy of imipramine being the first experimental clinical study selecting patients based on Fascin1 expression.MethodsThe HITCLIF trial is a multicenter, double-blind, placebo-controlled, randomized and non-commercial phase II clinical trial conducted in parallel groups to evaluate the effectiveness of the tricyclic antidepressant imipramine as anti-invasive agent in the treatment of localized colon, rectal and triple negative breast cancer patients with overexpression of Fascin1. Eligible patients will be randomly assigned, in a 1:1 ratio, to receive imipramine or placebo. Patients will be stratified into 2 groups according to whether administration of imipramine is concomitant with neoadjuvant chemotherapy regimen. Group A will receive imipramine alone without neoadjuvant chemotherapy, while Group B will receive imipramine treatment along with the standard neoadjuvant chemotherapy regimen. The primary endpoint of the trial is the grade of alteration in the prognostic histopathological features at invasive margins (tumor budding, cytoplasmic pseudo-fragments, tumor growth pattern, and peritumoral lymphocytic infiltration).DiscussionFascin1 is an interesting therapeutical target as it plays a causative role in the invasion and metastasis of cancer cells. Moreover, its expression is virtually absent in normal epithelia but highly expressed in cancer with bad prognosis. In silico, in vitro and in vivo studies by our group have demonstrated that the antidepressant imipramine has Fascin1-dependant anti-invasive and anti-metastatic effects in colorectal cancer cells. Now we are recruiting patients in a clinical trial based on Fascin1 over-expression in which administration of imipramine will be carried out during the period between the diagnosis biopsy and surgical resection to explore the drug effects on tumor invasive front.Clinical trial registrationhttps:///www.clinicaltrialsregister.eu/ctr-search/trial/2021-001328-17/ES, identifier 2021-001328-17.
Construction and validation of a novel prognostic model for intrahepatic cholangiocarcinoma based on a combined scoring system of systemic immune-inflammation index and albumin-bilirubin: a multicenter study
Authors: Zhang Haofeng , Li Qingshan , Huang Guan , Yang Zhenwei , Chen Kunlun , Meng Bo , Yu Haibo 
Published: September 2023

BackgroundThe degree of inflammation and immune status is widely recognized to be associated with intrahepatic cholangiocarcinoma (ICC) and is closely linked to poor postoperative survival. The purpose of this study was to evaluate whether the systemic immune-inflammatory index (SII) and the albumin bilirubin (ALBI) grade together exhibit better predictive strength compared to SII and ALBI separately in patients with ICC undergoing curative surgical resection.MethodsA retrospective analysis was performed on a cohort of 374 patients with histologically confirmed ICC who underwent curative surgical resection from January 2016 to January 2020 at three medical centers. The cohort was divided into a training set comprising 258 patients and a validation set consisting of 116 patients. Subsequently, the prognostic predictive abilities of three indicators, namely SII, ALBI, and SII+ALBI grade, were evaluated. Independent risk factors were identified through univariate and multivariate analyses. The identified independent risk factors were then utilized to construct a nomogram prediction model, and the predictive strength of the nomogram prediction model was assessed through Receiver Operating Characteristic (ROC) survival curves and calibration curves.ResultsUnivariate analysis of the training set, consisting of 258 eligible patients with ICC, revealed that SII, ALBI, and SII+ALBI grade were significant prognostic factors for overall survival (OS) and recurrence-free survival (RFS) (p &lt; 0.05). Multivariate analysis revealed the independent significance of SII+ALBI grade as a risk factor for postoperative OS and RFS (p &lt; 0.05). Furthermore, we conducted an analysis of the correlation between SII, ALBI, SII+ALBI grade, and clinical features, indicating that SII+ALBI grade exhibited stronger associations with clinical and pathological characteristics compared to SII and ALBI. We constructed a predictive model for postoperative survival in ICC based on SII+ALBI grade, as determined by the results of multivariate analysis. Evaluation of the model’s predictive strength was performed through ROC survival curves and calibration curves in the training set and validation set, revealing favorable predictive performance.ConclusionThe SII+ALBI grade, a novel classification based on inflammatory and immune status, serves as a reliable prognostic indicator for postoperative OS and RFS in patients with ICC.
Neonatal sequential organ failure assessment score within 72 h after delivery reliably predicts bronchopulmonary dysplasia in very preterm infants
Authors: Xu Doudou , Dong Ziwei , Yin Xiaoli , Yang Yuanyuan , Wang Yang 
Published: September 2023

BackgroundThe neonatal sequential organ failure assessment (nSOFA) score is an operational definition of organ dysfunction employed to predict sepsis-associated mortality. However, the relationship between the nSOFA score and bronchopulmonary dysplasia (BPD) has not been investigated clearly. This study evaluates whether the nSOFA score within 72 h after delivery could be used to predict the occurrence of BPD in very preterm infants.MethodsIn this retrospective, single-center cohort study, preterm infants born between 2019 and 2021 were investigated, the nSOFA score was calculated from medical records after admission to the neonatal intensive care unit (NICU) within 72 h after delivery, and the peak value was used for calculation. A logistic regression model was used to evaluate the relationship between the nSOFA score and BPD. Propensity score matching and subgroup analysis were performed to verify the reliability of the results.ResultsOf 238 infants meeting the inclusion criteria, 93 infants (39.1%) were diagnosed with BPD. The receiver operating characteristic curve of the nSOFA score in predicting BPD was 0.790 [95% confidence interval (CI): 0.731–0.849]. The logistic regression model showed that an increment of one in the nSOFA score was related to a 2.09-fold increase in the odds of BPD (95% CI: 1.57–2.76) and 6.36-fold increase when the nSOFA score was higher than 1.5 (95% CI: 2.73–14.79).ConclusionsThe nSOFA score within 72 h after delivery is independently related to BPD and can be used to identify high-risk infants and implement early interventions.
Whether and how will using social media induce social anxiety? The correlational and causal evidence from Chinese society
Authors: Yang Feng , Li Minyan , Han Yang 
Published: September 2023

BackgroundPrior literature has well established the relationship between social media use and social anxiety, but little attention has been paid to the underlying mechanisms. Additionally, the causal evidence concerning the effect of social media use on social anxiety is scarce.ObjectiveGiven that, two studies were conducted to examine the effect of social media use on social anxiety and the underlying mechanisms.Methods and resultsIn Study 1, with 470 undergraduates as participants, we applied the questionnaire survey to investigate the relationship between social media use and social anxiety. The results showed that higher social media use intensity was significantly related to higher social anxiety, and social media use was related to social anxiety via two possible mediation paths: (1) social media use → upward social comparison → social anxiety, (2) and social media use → upward social comparison → self-esteem → social anxiety. In Study 2, with 180 undergraduates as participants, we conducted a lab experiment, in which participants were assigned to the experimental (exposed to the content that undergraduates frequently access on social media) or control (exposed to landscape documentaries) condition, and then measured their upward social comparison, self-esteem and social anxiety. The results showed that participants in the experimental condition reported higher social anxiety than those in the control condition, demonstrating the causality between social media exposure and social anxiety. The subsequent mediation analysis basically replicated the findings of Study 1. That is, upward social comparison played the mediating role between social media exposure and social anxiety, and upward social comparison and self-esteem played the chain-mediating role between them.ConclusionThe current research firstly demonstrated the causality between social media use and social anxiety in Chinese society, and also revealed the mediating mechanisms between them, which would deepen our understanding of how social media use will increase social anxiety.
Turnover intention and coping strategies among older nursing assistants in China: a qualitative study
Authors: Tan Yuting , Zhao Qian , Yang Huafeng , Song Shufen , Xie Xiaohua , Yu Zhiying 
Published: September 2023

IntroductionWith the increasing aging population, older nursing assistants have made significant contributions to institutional eldercare. However, there is a high turnover rate among these workers, and it is crucial to address this issue and find ways to stabilize the workforce. This study aimed to explore the factors influencing turnover intention and coping strategies among older nursing assistants, in order to provide targeted assistance and guidance to reduce their intention to resign and ultimately lower the turnover rate.MethodsQualitative research methods were employed to conduct semi-structured interviews with older nursing assistants in Changsha. The data obtained from these interviews were then analyzed using a phenomenological analysis approach and NVIVO (QSR International, Doncaster, Australia) software version 11.0.ResultsIt is found that several factors influence turnover intention among older nursing assistants. Which include work pay, work environment, professional identity, external motivation, and work pressure. Additionally, the coping strategies employed by these individuals in relation to their intention to resign include self-regulation, seeking support, self-improvement, and exploring motivation.DiscussionIt is also evident from our study that reducing the turnover intention of older nursing assistants requires a collaborative effort from older adult care institutions, functional departments, and eldercare nursing assistants themselves. By addressing the factors influencing turnover intention and providing support and resources for coping strategies, we can work towards stabilizing the workforce and improving institutional eldercare.