bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recurrent syncope in long survivors and its association with geriatric syndromes
Authors: Bandhu Kamal , Rao Akshata , Nehra Ashima , Dwivedi Sada Nand , Chakrawarty Avinash , Dey Aparajit Ballav 
Published: January 2023

AbstractObjectiveSyncope is a common clinical condition in the elderly, associated with significant morbidity and risk of recurrence. Recurrent syncope causing a repeated reduction in the cerebral blood flow can predispose to progressive neurodegeneration, a decline in overall health and functionality. Hence, this study was conducted to study the common causes of recurrent syncope and its association with various geriatric syndromes.MethodologyThis case–control study recruited 50 cases of recurrent syncope and 50 controls, aged 75 years and older. A detailed history and sequential evaluation for aetiologies of recurrent syncope were done. Cognition, frailty, activities of daily living, depression, and nutrition were assessed using various scales.ResultsMost (80%, 80/100) of the participants were males and the mean age was 80.04 ± 4.3 years. In the syncope group, 42% (21/50) of patients had arrhythmia, and 30% (15/30) had valvular heart disease. Recurrent syncope was significantly associated with lower scores on Montreal cognitive assessment scale (OR: 6.47 P < 0.001), four or more comorbidities (OR: 6.29 P < 0.001), and hearing impairment (OR: 6.21 P < 0.004) on multivariate logistic regression analysis.ConclusionRecurrent syncope is significantly associated with cognitive impairment, the presence of four or more comorbidities, and hearing impairment. Conduction abnormality was the most common etiology of recurrent cardiovascular syncope. Structured evaluation and appropriate management of recurrent syncope might reduce the decline in physical, cognitive, and psychological reserve. A follow‐up longitudinal study is needed to establish this.
Probing a Hydrogen‐π Interaction Involving a Trapped Water Molecule in the Solid State
Authors: Bartalucci Ettore , Malär Alexander A. , Mehnert Anne , Kleine Büning Julius B. , Günzel Lennart , Icker Maik , Börner Martin , Wiebeler Christian , Meier Beat H. , Grimme Stefan , Kersting Berthold , Wiegand Thomas 
Published: January 2023

AbstractThe detection and characterization of trapped water molecules in chemical entities and biomacromolecules remains a challenging task for solid materials. We herein present proton‐detected solid‐state Nuclear Magnetic Resonance (NMR) experiments at 100 kHz magic‐angle spinning and at high static magnetic‐field strengths (28.2 T) enabling the detection of a single water molecule fixed in the calix[4]arene cavity of a lanthanide complex by a combination of three types of non‐covalent interactions. The water proton resonances are detected at a chemical‐shift value close to zero ppm, which we further confirm by quantum‐chemical calculations. Density Functional Theory calculations pinpoint to the sensitivity of the proton chemical‐shift value for hydrogen‐π interactions. Our study highlights how proton‐detected solid‐state NMR is turning into the method‐of‐choice in probing weak non‐covalent interactions driving a whole branch of molecular‐recognition events in chemistry and biology.
Effects of alkali metal catalysts on the melt fluidity of polycarbonates with different degrees of polymerization
Authors: Zheng Mingfu , Chen Mengdi , Zhang Lu , Peng Wenjun , Zhang Xian‐Ming , Chen Wenxing 
Published: January 2023

AbstractThe melt fluidity of polycarbonate (PC) significantly influences the processing, while the melt viscosity depends on the molecular structure. Specifically, the melt viscosity increases sharply with the increase of polymerization degree. However, the influence mechanism of alkali metal catalysts on the fluidity by affecting the molecular structure remains unclear. Herein, high and low concentrations of NaOH catalysts were used to synthesize PC with different polycondensation degrees. The effect of NaOH catalyst content on the molecular structure and thus melt fluidity of PC were systematically characterized and discussed employing NMR spectroscopy, absolute and relative molecular weight, intrinsic viscosity, melt flow index, and thermal analysis. The results show that a random branched structure of the PC molecular chain caused by excess NaOH improves the melt flowability. However, the residual NaOH promotes the degradation of carbonate bonds during thermal processing, resulting in poor PC stability. Based on the above discussion, empirical fitting equations are proposed to describe the relationship between molecular structure and flow properties, which provides a new way to judge PC performance.
A seesaw‐like mechanism for the neutrino in the presence of a minimal length space–time
Authors: Ferreira Thiago Oliveira , Vasconcellos César A. Z. , Hadjimichef Dimiter 
Published: January 2023

AbstractIn the Standard Model, neutrinos appear as left‐handed massless particles, although experimentally they have a tiny, but non‐vanishing, mass. Inspired by quantum gravity, Moayedi, Setare, Moayeri & Poorakbar (2011) used a Lorentz‐covariant algebra for a quantized space–time to derive a modified Dirac equation due to the presence of a minimal length. In this paper, we study this equation in the massless limit in order to describe neutrino states. We show that the minimal length creates a seesaw‐like mechanism that allows us to describe the observed left‐handed neutrinos with vanishing masses while the unobserved right‐handed neutrinos get extremely heavy.
The laser interferometric gravitational wave detector calibrator suspension: First attempt
Authors: do Prado André Rogerio Cardoso , da Silva Bortoli Fabio , Magalhães Nadja Simao , Frajuca Carlos 
Published: January 2023

AbstractIn 2015 the first detection of gravitational waves (GW) was made; such detection was made by kilometer size interferometer detectors. The calibration of such a detector is still a challenge then a calibrator was proposed. This calibrator is a resonant mass gravitational wave detector that operates at frequencies where the GW have been detected. This work shows part of the challenges of making a suspension for this device. The device has its vibration mode simulated in Finite Element Methods, then the parts of the device which have less movement were chosen to connect the suspension. Other simulations were made with the complete system and the results were analyzed.
Einflüsse auf die Messunsicherheit von SHM‐Systemen und deren Kompensation am Beispiel von Laser‐Distanzmessungen
Authors: Bartels Jan‐Hauke , Gebauer Daniel , Marx Steffen 
Published: January 2023

AbstractStructural Health Monitoring (SHM) wird immer wichtiger für die Überwachung von Ingenieur‐ und Infrastrukturbauwerken, da sie kontinuierlich Informationen generieren und eine Zustandsbewertung in Echtzeit ermöglichen. Eine der wesentlichen Herausforderungen bei der Überwachung ist jedoch, dass die Veränderungen des Zustands aufgrund von Deterioration nur geringfügig sind. Zugleich beeinflussen Umwelteinflüsse wie die Temperatur, oder die Messsystemkomponenten selbst, das Messsignal. Es stellt sich die Frage, wie diese Einflüsse minimiert werden können. Um dies zu untersuchen, werden Laser‐Triangulationssensoren (LTS) getestet und die Messunsicherheit aufgrund von Temperatureinflüssen ermittelt. Es zeigt sich, dass die Messunsicherheit des Messsystems nur geringer als typische Zustandsänderungen an Bauwerken ist, solange eine Temperaturkompensation durchgeführt wird. Außerdem kann festgestellt werden, dass der Sensor – im Vergleich zu Kabel und Messverstärker – den größten Einfluss auf die Messunsicherheit des Messsystems hat und die Kabellänge bei LTS mit Stromausgang keinen Einfluss aufweist.
Evaluation of bottom‐up modeling of the blood–brain barrier to improve brain penetration prediction via physiologically based pharmacokinetic modeling
Authors: Bowman Christine , Ma Fang , Mao Jialin , Plise Emile , Chen Eugene , Liu Liling , Zhang Shu , Chen Yuan 
Published: January 2023

AbstractPredicting the brain penetration of drugs has been notoriously difficult; however, recently, permeability‐limited brain models have been constructed. Lead optimization for central nervous system compounds often focuses on compounds that have low transporter efflux, where passive permeability could be a main driver in determining cerebrospinal fluid (CSF)/brain concentrations. The main objective of this study was to evaluate the translatability of passive permeability data generated from different in vitro systems and its impact on the prediction of human CSF/brain concentrations using physiologically‐based pharmacokinetic (PBPK) modeling. In vitro data were generated using gMDCK and parallel artificial membrane permeability assay‐blood–brain barrier for comparison and predictions using a quantitative structure‐activity relationship model were also evaluated. PBPK modeling was then performed for seven compounds with moderate‐high permeability and a range of efflux in vitro, and the CSF/brain mass concentrations and Kpuu were reasonably predicted. This work provides the first step of a promising approach using bottom‐up PBPK modeling for CSF/brain penetration prediction to support lead optimization and clinical candidate selection.
Safety of prenatal opioid analgesics: Do results differ between public health insurance beneficiary and population‐based cohorts?
Authors: Brogly Susan B. , Bowie Alexa C. , Li Wenbin , Camden Andi , Velez Maria P. , Guttmann Astrid , Werler Martha M. 
Published: January 2023

AbstractBackgroundPregnant patients with particular types of health insurance may have distinct demographic and medical characteristics that have a biologic effect on associations between opioid analgesics and congenital anomalies (CA).MethodsWe followed 199,884 pregnant prescription beneficiaries in Ontario, Canada (1996–2018). Opioid analgesics dispensed in the first trimester and CA were identified from universal‐access administrative health records. We estimated propensity score adjusted risk ratios (RR) between first trimester exposure and CA (any, major, minor, specific). RRs were compared to those published from an Ontario population‐based cohort (N = 599,579, 2013–2018).Results15,724 (7.9%) were exposed to first trimester opioid analgesics, mainly codeine (58.1%) or oxycodone (21.3%); CA prevalence in exposed was 3.1%. RRs in the beneficiary cohort appeared higher than the population‐based cohort for any CA with hydromorphone (RR = 2.34, 95% CI: 1.65, 3.30) and oxycodone (RR = 1.73, 95% CI: 1.46, 2.05) and major CA with hydromorphone (RR = 2.74, 95% CI: 1.91, 3.94) and oxycodone (RR = 1.72, 95% CI: 1.42, 2.08). Other RRs that appeared higher in the beneficiary cohort included cardiovascular (codeine, oxycodone), gastrointestinal (oxycodone), musculoskeletal (any, hydromorphone, oxycodone), CNS (oxycodone), chromosomal (codeine), and neoplasm and tumor (oxycodone) anomalies. The beneficiary cohort had higher opioid doses, was younger, had lower socioeconomic status, and greater comorbidities.ConclusionsIncreased risks of CA after first trimester opioid analgesics were observed in low‐income prescription beneficiaries, and some estimates were higher than a population‐based cohort from the same setting. Biological differences associated with younger age, lower socioeconomic status and greater comorbidity may affect generalizability of results from pregnant low‐income beneficiaries.
An immune, stroma, and epithelial–mesenchymal transition‐related signature for predicting recurrence and chemotherapy benefit in stage II–III colorectal cancer
Authors: Cai Du , Wang Wei , Zhong Min‐Er , Fan Dejun , Liu Xuanhui , Li Cheng‐Hang , Huang Ze‐Ping , Zhu Qiqi , Lv Min‐Yi , Hu Chuling , Duan Xin , Wu Xiao‐Jian , Gao Feng 
Published: January 2023

AbstractBackgroundDebates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage‐based risk stratification system. Epithelial–mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT.MethodsIn total, 2382 CRC patients from seven datasets and one in‐house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial‐mesenchymal transition (ISE)‐related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored.ResultsWe constructed a 26‐gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25–6.01]) and three independent validation cohorts (Validation cohort‐1: p < 0.01, HR [95%CI] = 1.70 [1.15–2.51]; Validation cohort‐2: p < 0.001, HR [95% CI] = 2.30 [1.67–3.16]; Validation cohort‐3: p < 0.01, HR [95% CI] = 2.42 [1.25–4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature's independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04–0.55]). Hypergeometric test and enrichment analysis revealed that low‐risk group was enriched in thr immune pathway while high‐risk group was associated with the EMT pathway and CMS4 subtype.ConclusionWe proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.
The maximum tumor growth rate predicts clinical outcomes of patients with small‐cell lung cancer undergoing first‐line chemotherapy plus immune‐checkpoint inhibitor therapy
Authors: Chen Xiang , Chen Xueyuan , Liu Tingting , Zhou Ting , Chen Gang , Zhou Huaqiang , Huang Yan , Fang Wenfeng , Yang Yunpeng , Zhou Ningning , Chen Likun , Mo Silang , Zhang Li , Zhao Yuanyuan 
Published: January 2023

AbstractBackgroundCurrently, no biomarkers can accurately predict survival outcomes in patients with SCLC undergoing treatment. Tumor growth rate (TGR; percent size change per month [%/m]) is suggested as an imaging predictor of response to anti‐cancer treatment. We aimed to evaluate the predictive role of the maximum TGR (TGRmax) for outcomes of small‐cell lung cancer (SCLC) patients undergoing first‐line chemotherapy plus immune‐checkpoint inhibitor (ICI) treatment.MethodsPatients with SCLC receiving first‐line chemotherapy plus immunotherapy were analyzed within this retrospective study. The X‐tile program was used to identify the cut‐off value of TGRmax based on maximum progression‐free survival (PFS) stratification. The Kaplan–Meier methods and Cox regression models were used to evaluate the effect of the presence of TGRmax on PFS and overall survival (OS).ResultsIn total, 104 patients were evaluated. Median (range) TGRmax was −33.9 (−65.2 to 21.6) %/m and the optimal cut‐off value of TGRmax was −34.3%/m. Multivariate Cox regression analysis revealed that patients with TGRmax > −34.3%/m was associated with shorter PFS (hazard ratio [HR], 2.81; 95% CI, 1.71–4.63; p < 0.001) and OS (HR, 3.17; 95% CI, 1.41–7.08; p = 0.005). In patients who received partial response (PR), Kaplan–Meier survival analyses showed that superior PFS and OS (p = 0.005 and p = 0.009, respectively) benefit was observed when TGRmax ≤−34.3%/m.ConclusionsSCLC patients with TGRmax > −34.3%/m had worse PFS and OS in first‐line ICI plus platin‐based chemotherapy. TGRmax could independently serve as an early biomarker to predict the benefit from chemoimmunotherapy.
A Comprehensive Review of the Phytochemical and Pharmacological Potential of an Evergreen Plant Garcinia cowa
Authors: Chouni Anirban , Paul Santanu 
Published: January 2023

AbstractGarcinia cowa of the Clusiaceae family, native to South‐East Asia used in traditional medicine. It has antipyretic, antimicrobial, and many other biological activities. In this review, a thorough study of this plant's chemical constituents and pharmacological and therapeutic effects was conducted from the research articles from PubMed, Science Direct, Google Scholar, and Scopus from 1977 to 2022. Reported secondary metabolites are enriched with xanthones, phloroglucinols, depsidones, steroids, etc. α‐mangostin, β‐mangostin, cowaxanthone, rubraxanthone, cowanin, norcowanin, etc. represent the major xanthones. This article discusses the relationship between the different functional groups in xanthone compounds and their bioactivity against cancer, diabetes, bacteria, leishmania, malaria, and inflammation. This review is a comprehensive compendium of major bioactive molecules and its implication for human disease.
Investigation of the effect of functionalized carbon nanotube and graphene oxide in guar gum‐based mixed matrix membrane for gas separation application
Authors: Pal Neha , Agarwal Madhu 
Published: January 2023

AbstractThe present study deals with preparing mixed matrix membranes (MMMs), a new polysaccharide‐based natural polymer used as a matrix with functionalized carbon nanotubes (FCNTs) and graphene oxide (GO) used as an inorganic filler. This work identified the effect of the inorganic fillers (FCNTs or GO) with naturally occurring polymer for gas separation. The incorporation of fillers improves the gas separation performance of MMMs. In GG/FCNTs MMMs, the selectivities of CO2/N2 and CO2/H2 were enhanced by 55.24% and 57.89%, respectively. Moreover, in GG/GO MMMs, the selectivities of CO2/N2 and CO2/H2 were improved by 99.50% and 50%, respectively. The membrane was characterized by scanning electron microscopy (SEM) and Fourier‐transform infrared spectroscopy (FTIR). The SEM analysis of GG/GO MMMs reveals layered structure, and GG/FCNTs MMMs create passages to transport gases. The Universal testing machine (UTM) is used to analyze the mechanical properties of pristine and modified membranes.
Ion‐change promoting Co nanoparticles@N‐doped carbon framework on Co2SiO4/rGO support forming “double‐triple‐biscuit” structure boosts oxygen evolution reaction
Authors: Pei Xiaoyu , Mu Yang , Dong Xueying , Ding Chongtao , Xu Lisha , Cui Miao , Meng Changgong , Zhang Yifu 
Published: January 2023

AbstractExploring economic and high‐performance electrocatalysts to decrease the overpotential of oxygen evolution reaction (OER) and facilitate its reaction kinetics is a frontier subject in line with green energy. Herein, metal‐organic framework (MOF)‐derived Co nanoparticles@N‐doped carbon (Co NPs@N,C) is rationally designed on sandwich‐like cobalt silicate/reduced graphene oxide (Co2SiO4/rGO) support to acquire Co NPs@N,C/Co2SiO4/rGO “double‐triple‐biscuit”‐like structure as enhanced OER electrocatalysts. Co NPs@N,C on Co2SiO4/rGO support optimizes its geometric architecture and introduces new active sites. The “double‐triple‐biscuit”‐like Co NPs@N,C/Co2SiO4/rGO structure achieves excellent OER ability compared with the existing materials based on transition metal silicates (TMSs). The overpotential of 278 mV is achieved at the current density of 10 mA cm−2, and it is prominently higher than Co2SiO4/rGO support (390 mV). This excellent OER activity is rooted in its structural peculiarity, enabling efficient ion and electron transport. Co NPs@N,C are highly dispersed on the Co2SiO4/rGO support, increasing the active sites and avoiding self‐aggregation of Co NPs in the OER process. This work combines the advantages of Co2SiO4/rGO support with the triple biscuits' structure and MOF to implement the preparation of boosted Co NPs@N,C/Co2SiO4/rGO, and it opens a new avenue for designing novel architectures to promote the OER activity of TMSs.
AFMC: An alignment framework for multiple computing services and providers
Authors: de Carvalho Leonardo Reboucas , Melo Alba Cristina Alves , Araujo Aleteia 
Published: January 2023

SummaryThe Hirschberg algorithm is commonly used for protein sequence alignment, which is a very important task in bioinformatics. This article presents the AFMC framework for using the Hirschberg method to perform sequence alignment in multiple cloud computing services of different models, such as Infrastructure‐as‐a‐Service and Function‐as‐a‐Service (FaaS). Experiments were carried out in which several instances of AWS EC2, Azure VMs and Google Compute Engine as well as varied configurations of AWS Lambda, Azure Function, and Google Cloud Function were used to pairwise align COVID‐19 spike proteins. The services were submitted to different levels of simultaneity to align the genetic sequences. The findings reveal that there is a tradeoff between predicted execution time and cost for this application, for example, FaaS‐oriented cloud service models generally took less time to process the workloads. On the other hand, it was observed that, as the level of concurrence increased, there was a marked augmentation in cost. In this context, a framework that provides multi cloud solutions for bioinformatics such as AFMC is essential.
Environmental regulation and corporate sustainability: Evidence from green innovation
Authors: Zhuo Weijia 
Published: January 2023

AbstractUsing a difference‐in‐differences (DID) design, this study investigates the effect of environmental regulation on corporate sustainability. The results show that China's low‐carbon city pilot policy has had a positive impact on green innovation. Furthermore, this positive association was especially pronounced for privately owned firms and those in high‐pollution industries. Additional analyses showed that the low‐carbon city pilot policy improved both corporate and environmental performance. This paper thus contributes to the literature on environmental regulation and corporate sustainability and has implications of interest to regulators and managers as well as researchers.