bluuebunny/crossref_metadata_2025_split huggingface dataset:
NOTCH3promotes docetaxel resistance of prostate cancer cells through regulatingTUBB3andMAPKsignaling pathway
Authors: Sun Xianchao , Zhang Ying , Xin Shiyong , Jin Liang , Cao Qiong , Wang Hong , Wang Keyi , Liu Xiang , Tang Chaozhi , Li Weiyi , Li Ziyao , Wen Xiaofei , Yang Guosheng , Guo Changcheng , Liu Zhiyu , Ye Lin 
Published: December 2023

AbstractDocetaxel is the preferred chemotherapeutic agent in patients with castrate‐resistant prostate cancer (CRPC). However, patients eventually develop docetaxel resistance and in the absence of effective treatment options. Consequently, it is essential to investigate the mechanisms generating docetaxel resistance and develop novel alternative therapeutic targets. RNA sequencing was undertaken on docetaxel‐sensitive and docetaxel‐resistant prostate cancer (PCa) cells. Subsequently, chemoresistance, cancer stemness, and lipid metabolism were investigated. To obtain insight into the precise activities and action mechanisms of NOTCH3 in docetaxel‐resistant PCa, immunoprecipitation, mass spectrometry, ChIP, luciferase reporter assay, cell metabolism, and animal experiments were performed. Through RNA sequencing analysis, we found that NOTCH3 expression was markedly higher in docetaxel‐resistant cells relative to parental cells, and that this trend was continued in docetaxel‐resistant PCa tissues. Experiments in vitro and in vivo revealed that NOTCH3 enhanced stemness, lipid metabolism, and docetaxel resistance in PCa. Mechanistically, NOTCH3 is bound to TUBB3 and activates the MAPK signaling pathway. Moreover, NOTCH3 was directly regulated by MEF2A in docetaxel‐resistant cells. Notably, targeting NOTCH3 and the MEF2A/TUBB3 signaling axis was related to docetaxel chemoresistance in PCa. Overall, these results demonstrated that NOTCH3 fostered stemness, lipid metabolism, and docetaxel resistance in PCa via the TUBB3 and MAPK signaling pathways. Therefore, NOTCH3 may be employed as a prognostic biomarker in PCa patients. NOTCH3 could be a therapeutic target for PCa patients, particularly those who have developed docetaxel resistance.
The influence of vertical ridge augmentation techniques on peri‐implant bone loss: A systematic review and meta‐analysis
Authors: Cucchi Alessandro , Maiani Francesco , Franceschi Debora , Sassano Michele , Fiorino Antonino , Urban Istvan A. , Corinaldesi Giuseppe 
Published: December 2023

AbstractIntroductionThe primary aim of this systematic review was to investigate and compare the outcomes of different vertical ridge augmentation (VRA) techniques in relation to peri‐implant bone loss (PBL), after at least 12 months of functional loading.Material and methodsThe search was conducted to find all the studies about VRA and measurements of PBL with at least 12 months follow‐up. Three pairwise meta‐analysis (MA) was performed to completely evaluate the outcomes.ResultsA total of 42 studies were included, of which 11 were randomized clinical trials (RCTs). RCTs were available only for guided bone regeneration (GBR), onlay, and inlay techniques. The weighted mean estimate (WME) of PBL value was found to be 1.38 mm (95% confidence interval [95% CI]: 1.10–1.66) after a mean follow‐up of 41.0 ± 27.8 months. GBR, Inlay, Onlay, osteodistraction, and SBB represented in weight 32.9%, 30.6%, 25.0%, 7.6%, and 3.9%, respectively; and their WME (95% CI) were 1.06 (0.87–1.26) mm, 1.72 (1.00–2.43) mm, 1.31 (0.87–1.75) mm, 1.81 (0.87–1.75) mm, and 0.66 (0.55–0.77) mm, respectively. Among the secondary outcomes, the analysis was conducted for vertical bone gain, healing complication rate, surgical complication rate, implant survival, and success rate.ConclusionsThe primary findings of the meta‐analysis, based on the changes between final and baseline values, showed that the peri‐implant bone loss could be influenced by the type of intervention but there is a need to evaluate in RCTs the behavior of the peri‐implant bone levels after long‐term follow‐up for all techniques.
Sentiment analysis on Hindi tweets during COVID‐19 pandemic
Authors: Saroj Anita , Thakur Akash , Pal Sukomal 
Published: December 2023

AbstractA gap among the people has been created due to a lack of social interactions. The physical void has led to an increase in online interaction among users on social media platforms. Sentiment analysis of such interactions can help us analyze the general public psychology during the pandemic. However, the lack of data in non‐English and low‐resource languages like ‘Hindi’ makes it difficult to study it among native and non‐English speaking masses. Here, we create a small collection of ‘Hindi’ tweets on COVID‐19 during the pandemic containing 10,011 tweets for sentiment analysis, which is named as sentiment analysis for Hindi (SAFH). In this article, we describe the process of collecting, creating, annotating the corpus, and sentiment classification. The claims have been verified using different word embedding with a deep learning classifier through the proposed model. The achieved accuracy of the proposed model yields up to a permissible rate of 90.9%.
Harnessing Instagram's “platform vernacular” during the COVID‐19 pandemic: A case study of Philbrook Museum of Art
Authors: Hu Nan , Kidd Jenny 
Published: December 2023

AbstractResearchers have been documenting how museums used social networks during the COVID‐19 global health emergency, however, to date there has been limited assessment of museums' uses of Instagram at that time. This article begins to address that gap with a case study of Philbrook Museum of Art's approach to that platform during the early months of the pandemic. We use a mixed‐method inquiry featuring social media analysis and a series of interviews with staff at the museum to analyze the museum's use of Instagram to maintain a presence within followers' lives during this intensely challenging period. To frame our analysis we introduce Gibbs et al.'s (Information, Communication & Society, 2015, 18, 255) concept of “platform vernacular” to digital heritage studies, trialing its use to critically analyze the combination of affordances, practices, and communicative conventions that Instagram convenes for the museum. We find this approach to be both theoretically and practically insightful, with the potential to inform more meaningful, authentic, and transparent interactions between institutions and users within social networks.
Zoning strategies for human–robot collaborative picking
Authors: Azadeh Kaveh , Roy Debjit , de Koster René , Khalilabadi Seyyed Mahdi Ghorashi 
Published: December 2023

AbstractDuring the last decade, several retailers have started to combine traditional store deliveries with the fulfillment of online sales to consumers from omni‐channel warehouses, which are increasingly being automated. A popular option is to use autonomous mobile robots (AMRs) in collaboration with human pickers. In this approach, the pickers' unproductive walking time can be reduced even further by zoning the storage system, where the pickers stay within their zone periphery and robots transport order totes between the zones. However, the robotic systems' optimal zoning strategy is unclear: few zones are particularly good for large store orders, while many zones are particularly good for small online orders. We study the effect of no zoning (NZ) and progressive zoning strategies on throughput capacity for balanced zone configurations with both fixed and dynamic order profiles. We first develop queuing network models to estimate pick throughput capacity that correspond to a given number of AMRs and picking with a fixed number of zones. We demonstrate that the throughput capacity is dependent on the chosen zoning strategy. However, the magnitude of the gains achieved is influenced by the size of the orders being processed. We also show that using a dynamic switching strategy has little effect on throughput performance. In contrast, a fixed switching strategy benefiting from changes in the order profile has the potential to increase throughput performance by 17% compared to the NZ strategy, albeit at a higher robot cost.
Effect of tirzepatide on albuminuria levels and renal function in patients with type 2 diabetes mellitus: A systematic review and multilevel meta‐analysis
Authors: Karakasis Paschalis , Patoulias Dimitrios , Fragakis Nikolaos , Klisic Aleksandra , Rizzo Manfredi 
Published: December 2023

AbstractAimThe present systematic review aimed to summarize the available evidence from published randomized controlled trials (RCTs) regarding the effect of tirzepatide on albuminuria levels and renal function in patients with type 2 diabetes mellitus.Materials and MethodsMedline (via PubMed), Cochrane Library and Scopus were searched until 20 October 2023. Double‐independent study selection, data extraction and quality assessment were performed. Evidence was pooled with a three‐level mixed‐effects meta‐analysis.ResultsIn total, 9533 participants from eight RCTs were analysed. All RCTs had a low risk of bias, according to the Cochrane Collaboration tool (RoB2). Tirzepatide was associated with a significantly greater reduction in urine albumin‐to‐creatinine ratio compared with controls [mean difference (MD) −26.9%; 95% confidence interval (CI) (−34.76, −19.04); p < .001; level of evidence (LoE) moderate]. This effect remained significant in participants with baseline urine albumin‐to‐creatinine ratio ≥30 mg/g [MD −41.42%; 95% CI (−54.38, −28.45); p < .001; LoE moderate]. Based on subgroup analysis, the comparative effect of tirzepatide was significant against placebo and the insulin regimen, whereas no difference was observed compared with semaglutide. The beneficial effect of tirzepatide on albuminuria levels remained significant across all investigated doses (5, 10 and 15 mg), showing a dose‐response relationship. A neutral effect was observed on the estimated glomerular filtration rate [MD 0.39 ml/min/1.73m2; 95% CI (−0.64, 1.42); p = .46; LoE moderate].ConclusionOur findings suggest that tirzepatide probably leads to a significant reduction in albuminuria across all administered doses, while its use is associated with a neutral effect on creatinine clearance as a measure of renal function.
Impact of the diagnosis of gestational diabetes on maternal physical activity after pregnancy
Authors: Mehmood Sadia , Ye Chang , Hanley Anthony J. , Connelly Philip W. , Sermer Mathew , Zinman Bernard , Retnakaran Ravi 
Published: December 2023

AbstractAimThe diagnosis of gestational diabetes (GDM) identifies women who are at future risk of developing type 2 diabetes. However, it is unclear if diagnosing GDM thus motivates women to increase physical activity after pregnancy or if this medicalization has the opposite effect of decreasing activity, possibly reflecting assumption of a sick role. We thus sought to evaluate the impact of diagnosing GDM on changes in maternal physical activity after pregnancy.MethodsIn this prospective cohort study, physical activity patterns were assessed by the Baecke questionnaire for the year before pregnancy and the first year postpartum in 405 white women comprising the following three gestational glucose tolerance groups: (a) those who did not have GDM (non‐GDM; n = 247), (b) women with undiagnosed GDM (n = 46) and (c) those diagnosed with GDM (n = 112).ResultsIn the year before pregnancy, mean adjusted total physical activity progressively decreased from non‐GDM to undiagnosed GDM to diagnosed GDM (p = .067). Conversely, at 1 year postpartum, total physical activity was highest in those who had been diagnosed with GDM (p = .02). Compared with non‐GDM, diagnosed GDM predicted an increase in total physical activity from pre‐pregnancy to 1 year postpartum (t = 2.3, p = .02) whereas undiagnosed GDM predicted a concurrent decrease in leisure‐time activity (t = −2.74, p = .006). Accordingly, the mean adjusted increase in body mass index from pre‐pregnancy to 1 year postpartum was lowest in those with diagnosed GDM (0.26 ± 0.25 kg/m2), highest in undiagnosed GDM (1.23 ± 0.38 kg/m2) and intermediate in non‐GDM (0.89 ± 0.22 kg/m2) (overall p = .04).ConclusionDiagnosis of GDM leads to increased physical activity after pregnancy that may partially attenuate postpartum weight retention.
Effects of alpha‐tocopherol antioxidant on fracture strength and adhesion of endodontically treated teeth restored after dental bleaching
Authors: Marcomini Natália , Albaricci Maria Carolina da Costa , Costa Joatan Lucas de Sousa Gomes , Besegato João Felipe , Godoy Eduardo Fernández , Dantas Andréa Abi Rached , Kuga Milton Carlos 
Published: December 2023

AbstractThis study evaluated the effect of different concentrations of alpha‐tocopherol in gel form on fracture strength, hybrid layer formation, and microtensile bond strength of endodontically treated teeth bleached with 40% hydrogen peroxide (H2O2). Sixty bovine incisors were randomized into one of six groups (n = 10 incisors per group) defined by the interventions carried out after endodontic treatment. In the control group, no additional intervention was carried out, while all teeth in the five intervention groups were bleached with 40% H2O2 and subsequently treated with alpha‐tocopherol at concentrations of 15% (15AT), 20% (20AT), or 25% (25AT), with 10% sodium ascorbate (10SA), or with nothing (40HP). Fracture strength was evaluated in a mechanical testing machine, hybrid layer formation was assessed using scanning electron microscopy, and bond strength was determined using microtensile bond‐strength testing. Data were analyzed using Kruskal–Wallis and Dunn's tests. No statistically significant difference regarding fracture strength was observed among groups. Hybrid layer formation was greater in the 15AT group than in groups 40HP and 10SA. Teeth in groups 15AT, 20AT, and 25AT demonstrated higher bond strength than teeth in groups 40HP and 10SA. Alpha‐tocopherol, preferably at 15%, effectively reverses the deleterious effects, of bleaching, on hybrid layer formation and bond strength to dentin.
An improved hybrid model for cardiovascular disease detection using machine learning in IoT
Authors: Naseer Arslan , Khan Muhammad Muheet , Arif Fahim , Iqbal Waseem , Ahmad Awais , Ahmad Ijaz 
Published: December 2023

AbstractCardiovascular disease (CVD) believes to be a major cause of transience and indisposition worldwide. Early diagnosis and timely intervention are critical in preventing the progression of CVD and improving patient outcomes. Machine learning (ML) algorithms have emerged as powerful tools in CVD recognition, with the potential to assist physicians in making accurate and efficient diagnoses. This research paper explores the combination of multiple ML algorithms for CVD recognition, utilizing diverse datasets such as the Cleveland, Hungarian, Switzerland, statlog, and VA Long Beach datasets. Additionally, a CVD dataset comprising 12 attributes and 70,000 records is employed, demonstrating improved results through the proposed and trained model compared to previous prediction techniques for CVD. The performance of various ML techniques, including support vector machines (SVM), naive Bayes (NB), K‐nearest neighbour (KNN), random forest (RF), and logistic regression (LR), is evaluated and compared. The impact of feature selection and feature scaling on the models' performance is also examined. An ensemble bagging technique is applied which is being embedded with other classifiers. LR classifier embedded with bagging techniques proved to be our proposed model. The findings reveal that the proposed Hybrid Linear Regression Bagging Model (HLRBM) outperforms other models. Furthermore, the study highlights the significance of data preprocessing techniques, such as data normalization and class balancing, which significantly enhance the performance of all models. To this end, standard scalar and synthetic minority over‐sampling technique (SMOTE) are employed. The study emphasizes the importance of selecting an appropriate ensemble technique in conjunction with various ML algorithms and preprocessing methods for CVD prediction. Overall, the research provides valuable insights into the potential of ML in improving CVD risk assessment.
Deep neural network aided cohesive zone parameter identifications through die shear test in electronic packaging
Authors: Zhao Libo , Dai Yanwei , Wei Jiahui , Qin Fei 
Published: December 2023

AbstractThe die shear test is a feasible and conventional method to characterize the shear strength of die‐attaching layer materials in electronic packaging. A new method for determining cohesive zone model (CZM) parameters using deep neural networks (DNN) and die shear tests is proposed, different from classical fracture framework or lap shear test‐based methods. With the sintered nano‐silver die shear test, the results show that the bilinear CZM inversion results agree well with the experimental results. It is found that the DNN model has high accuracy in predicting and identifying the maximum shear traction strength τmax, separation displacement of the interface δf, and the interface stiffness k1 of CZM parameters for sintered nano‐silver adhesive layer through die shear test load versus displacement curves. The presented DNN‐aided inverse identifying method through the die shear test in this paper could provide an alternative and convenient method for extracting CZM parameters of various kinds of adhesive materials in electronic packaging.
Spindle cell rhabdomyosarcomas: With TFCP2 rearrangements, and novel EWSR1::ZBTB41 and PLOD2::RBM6 gene fusions. A study of five cases and review of the literature
Authors: Bradová Martina , Mosaieby Elaheh , Michal Michael , Vaněček Tomáš , Ing Stanislav Kormunda , Grossmann Petr , Koshyk Olena , Kinkor Zdeněk , Laciok Šimon , Nemcová Antónia , Straka Ľubomír , Farkas Mihaela , Michal Michal , Švajdler Marián 
Published: December 2023

AimsSpindle‐cell/sclerosing rhabdomyosarcomas (SS‐RMS) are clinically and genetically heterogeneous. They include three well‐defined molecular subtypes, of which those with EWSR1/FUS::TFCP2 rearrangements were described only recently. This study aimed to evaluate five new cases of SS‐RMS and to perform a clinicopathological and statistical analysis of all TFCP2‐rearranged SS‐RMS described in the English literature to more comprehensively characterize this rare tumour type.Methods and ResultsCases were retrospectively selected and studied by immunohistochemistry, fluorescence in situ hybridization with EWSR1/FUS and TFCP2 break‐apart probes, next‐generation sequencing (Archer FusionPlex Sarcoma kit and TruSight RNA Pan‐Cancer Panel). The PubMed database was searched for relevant peer‐reviewed English reports. Five cases of SS‐RMS were found. Three cases were TFCP2 rearranged SS‐RMS, having FUSex6::TFCP2ex2 gene fusion in two cases and triple gene fusion EWSR1ex5::TFCP2ex2, VAX2ex2::ALKex2 and VAX2intron2::ALKex2 in one case. Two cases showed rhabdomyoblastic differentiation and spindle‐round cell/sclerosing morphology, but were characterized by novel genetic fusions including EWSR1ex8::ZBTB41ex7 and PLOD2ex8::RBM6ex7, respectively. In the statistical analysis of all published cases, CDKN2A or ALK alterations, the use of standard chemotherapy and age at presentation in the range of 18–24 years were negatively correlated to overall survival.ConclusionEWSR1/FUS::TFCP2‐rearranged SS‐RMS is a rare rhabdomyosarcoma subtype, affecting predominantly young adults with average age at presentation 34 years (median 29.5 years; age range 7–86 years), with a predilection for craniofacial bones, rapid clinical course with frequent bone and lung metastases, and poor prognosis (3‐year overall survival rate 28%).
Individualistic culture and firm default risk: Cross‐country evidence
Authors: Nadarajah Sivathaasan , Liu Benjamin , Atif Muhammad , Richardson Grant 
Published: December 2023

AbstractThis study examines the association between individualistic culture and firm default risk across countries. Using a sample of 15,225 firms across 32 countries over the 2005–2018 period (115,464 firm‐year observations), we find that firms based in countries with high levels of individualism are associated with greater default risk. Our results are robust to a battery of endogeneity and other robustness checks. In additional analyses, we show that risk‐taking behavior is a channel through which individualism impacts firm default risk. We also find that the effect of individualistic culture on firm default risk is weak in countries with stringent bankruptcy laws. Overall, the findings of this study can improve our understanding of the impact of major informal institutions, such as individualistic culture, on manager behavior, which has significant implications for firms operating in global financial markets.
Macroeconomics factor, institutional quality and export performance: Empirical evidence from Pakistan
Authors: Khan Abbas , Khan Muhammad Yar , Ahmad Manzoor 
Published: December 2023

AbstractA country's institutional quality (INS) influences its export performance (EXP) and plays a vital role in international trade. The purpose of this study is to investigate the short‐run and long‐run relationships among these macroeconomic factors in Pakistan. Annual data from the World Development Indicators and the International Country Risk Guide were used from ‘1989 to 2019’. To investigate the short‐run and long‐run linkage between INS and EXP, the non‐linear auto‐regressive distributed lag and error correction model are used after incorporating structural breaks. Additionally, the macroeconomic explanatory variables used are the exchange rate (ER), human capital (HC), gross domestic product (GDP) and foreign direct investment (FDI). In the long run, INS, HC, GDP and FDI have a significant positive relationship with EXP, whereas the ER has a significant negative relationship. In the short run, INS is significant and positive, whereas HC, GDP and FDI with EXP are modest but significantly positive. To improve export performance in Pakistan, strategic reform of governmental institutions is required.
Impact of preoperative chemotherapy on cutaneous wound healing in lung cancer patients: A meta‐analysis
Authors: Zhao Jialai , Cui Hanwen , Qu Mingyue , Xu Zigeng , Zhang Yiling , Ma Chenguang 
Published: December 2023

AbstractAs part of their treatment, lung cancer patients frequently endure thoracic oncological surgery, with preoperative chemotherapeutic interventions being the common approach. However, the potential impact of these chemotherapeutic regimens on cutaneous wound healing outcomes following surgery remains the topic of considerable clinical interest. This meta‐analysis sought to evaluate comprehensively the effect of preoperative chemotherapeutic regimens on cutaneous wound healing in lung cancer patients following thoracic oncological surgery. Extensive literature searches were conducted using the leading databases PubMed, Embase, Cochrane Library and Scopus. Eight studies out of 1342 identified satisfied the inclusion criteria. Consideration was given to both randomized controlled trials (RCTs) and observational studies. Data pertaining to study characteristics, patient demographics, chemotherapeutic regimens and wound healing outcomes were extracted with great attention to detail. The examination of these varied studies provided insights into the fluctuations in rates of recovery following treatment, incidences of wound infections and frequencies of surgical complications. The research studies provided odds ratios for recovery that varied significantly in magnitude from 0.95 to 0.38, with regard to the probability of wound infection. Furthermore, a range of odds ratios for complications were disclosed, with certain odds ratios displaying narrow confidence intervals. The complexity of the effect of preoperative chemotherapy on wound closure subsequent to thoracic oncologic surgery is highlighted by our findings. The results underscore the need for individualized treatment strategies for lung cancer patients undergoing surgical procedures that strike a balance between patient safety and optimal clinical outcomes.