bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis of 3‐hydroxy‐2‐naphthohydrazide‐based hydrazones and their implications in diabetic management via in vitro and in silico approaches
Authors: Tasleem Mussarat , Ullah Saeed , Halim Sobia Ahsan , Urooj Ifra , Ahmed Nadeem , Munir Rabia , Khan Ajmal , El‐kott Attalla F. , Taslimi Parham , Negm Sally , Al‐Harrasi Ahmed , Shafiq Zahid 
Published: November 2023

AbstractDiabetes mellitus (DM) has prevailed as a chronic health condition and has become a serious global health issue due to its numerous consequences and high prevalence. We have synthesized a series of hydrazone derivatives and tested their antidiabetic potential by inhibiting the essential carbohydrate catabolic enzyme, “α‐glucosidase.” Several approaches including fourier transform infrared, 1H NMR, and 13C NMR were utilized to confirm the structures of all the synthesized derivatives. In vitro analysis of compounds 3a–3p displayed more effective inhibitory activities against α‐glucosidase with IC50 in a range of 2.80–29.66 µM as compared with the commercially available inhibitor, acarbose (IC50 = 873.34 ± 1.67 M). Compound 3h showed the highest inhibitory potential with an IC50 value of 2.80 ± 0.03 µM, followed by 3i (IC50 = 4.13 ± 0.06 µM), 3f (IC50 = 5.18 ± 0.10 µM), 3c (IC50 = 5.42 ± 0.11 µM), 3g (IC50 = 6.17 ± 0.15 µM), 3d (IC50 = 6.76 ± 0.20 µM), 3a (IC50 = 9.59 ± 0.14 µM), and 3n (IC50 = 10.01 ± 0.42 µM). Kinetics analysis of the most potent compound 3h revealed a concentration‐dependent form of inhibition by 3h with Ki value = 4.76 ± 0.0068 µM. Additionally, an in silico docking approach was applied to predict the binding patterns of all the compounds, which indicates that the hydrazide and the naphthalene‐ol groups play a vital role in the binding of the compounds with the essential residues (i.e., Glu277 and Gln279) of the α‐glucosidase enzyme.
Adaptive robust control for unmanned combat platform: Obstacles avoiding and dynamic trajectory tracking
Authors: Sun Qinqin , Chen Yu , Wang Xiuye , Wang Yinlong 
Published: November 2023

AbstractThis paper proposes an adaptive robust control scheme to deal with the uncertainty problem of unmanned combat platform. Under the constraint of the controller, the rescue vehicle aims to follow the trajectory of the reconnaissance vehicle and avoid obstacles (e.g., craters and destroyed tanks), while they eventually reach the defined target location (an accident area). First, for the control objective, the original constraints are innovatively separated into two parts: arrival constraint and tracking‐avoidance constraint. An approximate constraint‐following control substitutes for the triple problem, and the constraint‐following error is subsequently established. Second, for the control strategy, a
‐measure is introduced to measure the constraint‐following error. To ensure the tracking‐avoidance constraint and the arrival constraint can be fully satisfied by the system, an adaptive robust control is designed. Finally, for the fast time‐varying uncertainty with unknown boundary, an adaptive law is introduced to evaluate the triple tracking‐avoidance‐arrival performance. In conclusion, the main contribution of this paper is to achieve triple tracking‐avoidance arrival for unmanned combat platform, and the problem of military detection and rescue on complex battlefields can be eliminated.
Weighted Nash equilibrium of incomplete‐profile networked evolutionary games with multiple payoffs
Authors: Yu Ling , Fu Shihua , Pan Jinfeng , Feng Jun‐e , Wang Ziyun 
Published: November 2023

AbstractThis paper investigates the existence and convergence of weighted Nash equilibrium for incomplete‐profile networked evolutionary games with multiple payoffs. First, the incomplete‐profile networked evolutionary game under probabilistic myopic best response adjustment rule is transformed into an algebraic form based on the semi‐tensor product of matrices. Second, a method for calculating weighted Nash equilibrium is presented, and the relationship between weighted Nash equilibrium and positive‐probability fixed point is derived. Furthermore, a criterion is provided to verify whether the profiles in the feasible profile set can converge to the set of weighted Nash equilibriums with probability one. Finally, an illustrative example is given to support the new results obtained in this paper.
On the limitations of deep learning for statistical downscaling of climate change projections: The transferability and the extrapolation issues
Authors: Hernanz Alfonso , Correa Carlos , Sánchez‐Perrino Juan‐Carlos , Prieto‐Rico Ignacio , Rodríguez‐Guisado Esteban , Domínguez Marta , Rodríguez‐Camino Ernesto 
Published: November 2023

AbstractConvolutional neural networks (CNNs) have become one of the state‐of‐the‐art techniques for downscaling climate projections. They are being applied under Perfect‐Prognosis (trained in a historical period with observations) and hybrid approaches (as Regional Climate Models (RCMs) emulators), with satisfactory results. Nevertheless, two important aspects have not been, to our knowledge, properly assessed yet: (1) their performance as emulators for other Earth System Models (ESMs) different to the one used for training, and (2) their performance under extrapolation, that is, when applied outside of their calibration range. In this study, we use UNET, a popular CNN, to assess these two aspects through two pseudo‐reality experiments, and we compare it with simpler emulators: an interpolation and a linear regression. The RCA4 regional model, with 0.11° resolution over a complex domain centered in the Pyrenees, and driven by the CNRM‐CM5 global model is used to train the emulators. Two frameworks are followed for the training: predictors are taken (1) from the upscaled RCM and (2) from the ESM. In both frameworks, the performance of the UNET when applied for other ESMs different to the one used for training is considerably worse, indicating poor generalization. For the linear method a similar deterioration is seen, so this limitation does not seem method specific but inherent to the task. For the second experiment, the emulators are trained in present and evaluated in future, under extrapolation. While averaged aspects such as the mean values are well simulated in future, significant biases (up to 5°C) appear when assessing warm extremes. These biases are larger by UNET than those produced by the linear method. This limitation suggests that, for variables such as temperature, with a marked signal of change and a strong linear relationship with predictors, simple linear methods might be more appropriate than the sophisticated deep learning techniques.
Evaluation of a novel purified and characterized alkaline protease from the extremophile Exiguobacterium alkaliphilum VLP1 as a detergent additive
Authors: Hemsinli Asiye , Gurkok Sumeyra 
Published: November 2023

AbstractThis study focused on the isolation and identification of a novel alkaline protease‐producing strain from Lake Van, the largest soda lake on Earth. The objective was to purify, characterize, and investigate the potential application of protease in the detergent industry. Through a combination of classical and molecular methods, the most potent protease producer was identified as Exiguobacterium alkaliphilum VLP1. The purification process, involving ammonium sulfate precipitation, ultrafiltration, and anion exchange chromatography, resulted in a 45‐fold purification with a yield of 6.4% and specific activity of 1169 U mg−1 protein. The enzyme exhibited a molecular weight of 69 kDa, a Km value of 0.4 mm, and a maximal velocity (Vmax) value of 2000 U mg−1. The optimum activity was observed at 40°C and potential of hydrogen (pH) 9, while the enzyme also exhibited remarkable stability in the ranges of 30–60°C and pH 9–12. Notably, this study represents the first report of an alkaline protease isolated and characterized from E. alkaliphilum. This study also highlighted the potential of the enzyme as a detergent additive, as it showed compatibility with commercial detergents and effectively removed blood and chocolate stains from fabrics.
An UHPLC–QTOF–MS‐based strategy for systematic profiling of chemical constituents and associated in vivo metabolites of a famous traditional Chinese medicine formula, Yinchenhao decoction
Authors: Wang Jing , Ouyang Bingchen , Cao Rui , Xu Yu 
Published: November 2023

AbstractYinchenhao decoction (YCHD), a famous traditional Chinese medicine formula, has been applied for relieving jaundice in China for more than 1800 years. However, the material basis for YCHD is still unclear, and the chemical composition and metabolism characteristic in vivo are undefined, making the potential effective constituents and mechanism of action unclear. Herein, an ultrahigh‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry (UHPLC–QTOF–MS)‐based strategy was applied for the chemical profiling of YCHD, as well as their in vivo prototypes and global metabolites that defined the metabolome. Our results showed that a total of 139 chemicals were identified in YCHD, including 28 organic acids, 12 monoterpenoids, five diterpenes, three triterpenoids, 17 iridoids, 23 anthraquinones, 26 flavonoids, four coumarins and 21 other types. Moreover, 58 prototypes and 175 metabolites were found in rat biological samples after oral administration of YCHD; those distributed in plasma, liver, intestine and feces were suggested to be potentially effective substances. Oxidation, hydrogenation, decarboxylation and conjugations with methyl, sulfate and glucuronate were considered as the predominant metabolic pathways in vivo. In conclusion, this is a systemic study of chemical constituents and in vivo metabolome profiles of YCHD, contributing to the material basis understanding and further mechanism research.
Gandouling alleviates nerve injury through PI3K/Akt/FoxO1 and Sirt1/FoxO1 signaling pathway to inhibit autophagy in the rats model of Wilson's disease
Authors: Chen Li , Xu Wangyang , Zhang Yuting , Chen Hao , Han Yanquan 
Published: November 2023

AbstractIntroductionPrevious studies have shown that Gandouling (GDL) may alleviate the nerve damage caused by Wilson's disease (WD) by inhibiting the autophagy of nerve cell mitochondria. However, its mechanisms are still unclear. Revealing the therapeutic mechanism of GDL is beneficial for its clinical application and provides theoretical support for the development of new formulations for treating WD.MethodThis time we found that the oxidative stress level in the body of the copper‐overloaded WD rates increased, neurons in the hippocampus were damaged, and autophagy occurred. GDL reversed these situations and significantly improved the learning, memory, and spatial cognitive abilities of the high‐copper‐loaded WD rates. After GDL intervention, the expression of phosphatidylinositol‐3 kinase (PI3K), phosphorylated serine–threonine protein kinase (AKT), and phosphorylated forkhead box protein O1 (FoxO1) significantly increased, whereas FoxO1 in the nucleus decreased and phosphorylated FoxO1 in the cytoplasm also significantly raised. In addition, the expression of Sirt1 significantly declined, and Ac‐FoxO1 in the nucleus also significantly increased.ResultsThese data indicated that GDL may promote the phosphorylation of FoxO1 and promote its nucleation by activating the PI3K/AKT/FoxO1 signaling pathway and inhibit Ac‐FoxO1 hydrolysis in the nucleus through the Sirt1/FoxO1 signaling pathway to suppress the transcriptional activity of FoxO1.ConclusionFurthermore, it inhibited the expression of autophagy genes Atg12 and Gabarapl1. In summary, our work provides new insights into the potential mechanisms of GDL repairing WD neuronal damage through autophagy pathways.
Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients
Authors: Pham Tuan D. , Sun Xiao‐Feng 
Published: November 2023

AbstractBackgroundCancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5‐year survival time of two patient groups: one with preoperative radiotherapy and one without.MethodsThe utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet‐scattering network. Our study combines the strengths of these two convolution‐based approaches to robustly extract image features related to protein expression.ResultsThe efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve.ConclusionThese results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.
Survivorship research in advanced gynecological cancer: A scoping review of cohort studies
Authors: DiSipio Tracey , Pearse Emma , Jordan Susan 
Published: November 2023

AbstractBackgroundRecent calls to action highlight the need to address gaps in our understanding of survivorship for those living with advanced gynecological cancer to support optimal care. To ensure future research fills these knowledge gaps, we need to understand the breadth of existing survivorship research in this patient group, including the outcomes assessed, the populations included and the duration and retention in follow‐up.MethodsWe conducted a systematic scoping review searching PubMed, PsychINFO, and CINAHL during the month of November 2022 to identify prospective cohort studies measuring survivorship outcomes among participants with advanced (stage III–IV) gynecological cancer, or in cohorts in which ≥50% of participants had advanced cancer, or which provide results separately for patients with advanced cancer. Articles were screened, and data extracted using a standard form.ResultsWe assessed 33 articles from 21 unique studies, which overall included 6023 participants with gynecological cancer. Of these, 45% had cervical cancer, 44% ovarian, 10% endometrial/uterine, and 1% vaginal/vulvar cancer. The most frequently measured survivorship outcome was quality of life. Of the 33 articles, most reported on participant age (n = 31), but relatively few reported on comorbidities (n = 10), physical status (n = 6), ethnic background (n = 4), the country of birth (n = 2), or the area of participant residence (n = 2). None included details on indigenous status. Recruitment proportions ranged from 48% to 100%. Retention proportions ranged from 15% to 97%.ConclusionOur findings highlight gaps in survivorship research for advanced gynecological cancers and emphasize the need for future studies to include and describe the experiences of diverse and underrepresented groups.
Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy‐naive men based on multi‐institutional analysis
Authors: Ge Qingyu , Zhang Sicong , Xu Hewei , Zhang Junjie , Fan Zongyao , Li Weilong , Shen Deyun , Xiao Jun , Wei Zhongqing 
Published: November 2023

AbstractBackgroundPrediction of clinically significant prostate cancer (csPCa) is essential to select biopsy‐naive patients for prostate biopsy. This study was to develop and validate a nomogram based on clinicodemographic parameters and exclude csPCa using prostate‐specific antigen density (PSAD) stratification.MethodsIndependent predictors were determined via univariate and multivariate logistic analysis and adopted for developing a predictive nomogram, which was assessed in terms of discrimination, calibration, and net benefit. Different PSAD thresholds were used for deciding immediate biopsies in patients with Prostate Imaging‐Reporting and Data System (PI‐RADS) 3 lesions.ResultsA total of 932 consecutive patients who underwent ultrasound‐guided transperineal cognitive biopsy were enrolled in our study. In the development cohort, age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.036–1.114), PSAD (OR, 6.003; 95% CI, 2.826–12.751), and PI‐RADS (OR, 3.419; 95% CI, 2.453–4.766) were significant predictors for csPCa. On internal and external validation, this nomogram showed high areas under the curve of 0.943, 0.922, and 0.897, and low Brier scores of 0.092, 0.102, and 0.133 and insignificant unreliability tests of 0.713, 0.490, and 0.859, respectively. Decision curve analysis revealed this model could markedly improve clinical net benefit. The probability of excluding csPCa was 98.51% in patients with PI‐RADS 3 lesions and PSAD <0.2 ng/ml2.ConclusionThis novel nomogram including age, PSAD, and PI‐RADS could be applied to accurately predict csPCa, and 44.08% of patients with equivocal imaging findings plus PSAD <0.2 ng/ml2 could safely forgo biopsy.
Exploring the effects of written emotional disclosures (WED) on healthcare workers' (HCWs) mental health symptoms in the UK: A feasibility study
Authors: Kilvington Amy , Allen Sarah , Kyriakopoulos Alex 
Published: November 2023

AbstractBackgroundWritten emotional disclosure (WED) is a creative writing intervention that allows a person to confront emotions and traumatic experiences, which has been shown to produce well‐being benefits and could be used to support healthcare workers (HCWs). Written emotional disclosure is usually delivered as a written intervention, and despite some research exploring the effects of other forms of typing interventions using emotional expression, expressive writing and structured writing, the efficacy of WED as a typing‐based intervention is yet to be examined.AimThe aim of this mixed method feasibility study was to address whether a writing or typing WED intervention would reduce HCW's mental health symptoms. Additionally, to address whether the WED intervention groups were acceptable to HCW as a supportive intervention.FindingsFifty‐five participants (seven males) aged between 22 and 60 took part in this study. The results demonstrate that both the writing and typing WED intervention groups significantly reduce mental health symptoms. Most participants (96.4%) deemed both the WED intervention groups acceptable.ConclusionTherefore, WED interventions could potentially be integrated into existing counselling and therapeutic interventions to support HCW and could be implemented within the existing debrief and clinical supervision frameworks.
Transcript CD81‐215 may be a long noncoding RNA of stromal origin with tumor‐promoting role in colon cancer
Authors: Jovanovic Emilija , Babic Tamara , Dragicevic Sandra , Kmezic Stefan , Nikolic Aleksandra 
Published: November 2023

AbstractThe role of tetraspanin CD81 in malignant transformation is best studied in colorectal cancer, and it appears that other transcripts beside the fully coding mRNA may also be dysregulated in malignant cells. Recent data from a comprehensive pan‐cancer transcriptome analysis demonstrated differential activity of two alternative CD81 gene promoters in malignant versus nonmalignant gut mucosa. The promoter active in gut mucosa gives rise to transcripts CD81‐203 and CD81‐213, while the promoter active in colon and rectal cancer gives rise to transcripts CD81‐205 and CD81‐215. Our study aimed to explore the biomarker potential of the transcripts from the alternative CD81 gene promoters in colon cancer, as well as to investigate their structure and potential function using in silico tools. The analysis of the transcripts' expression in several colon cell lines cultivated in 2D and 3D and a set of colon cancer and healthy gut mucosa samples by qPCR and RNA sequencing suggested their low expression and stromal origin. Expression patterns in tumor and nontumor tissue along with in silico data suppose that the transcript CD81‐215 may be a noncoding RNA of stromal origin with possible involvement in signaling related to malignant transformation.
Regulating the Heme Active Site by Covalent Modifications: Two Case Studies of Myoglobin
Authors: Chen Ze‐Yuan , Yuan Hong , Wang Huamin , Sun Li‐Juan , Yu Lu , Gao Shu‐Qin , Tan Xiangshi , Lin Ying‐Wu 
Published: November 2023

AbstractUsing myoglobin (Mb) as a model protein, we herein developed a facial approach to modifying the heme active site. A cavity was first generated in the heme distal site by F46 C mutation, and the thiol group of Cys46 was then used for covalently linked to exogenous ligands, 1H‐1,2,4‐triazole‐3‐thiol and 1‐(4‐hydroxyphenyl)‐1H‐pyrrole‐2,5‐dione. The engineered proteins, termed F46C‐triazole Mb and F46C‐phenol Mb, respectively, were characterized by X‐ray crystallography, spectroscopic and stopped‐flow kinetic studies. The results showed that both the heme coordination state and the protein function such as H2O2 activation and peroxidase activity could be efficiently regulated, which suggests that this approach might be generally applied to the design of functional heme proteins.
Functional and aesthetical full‐mouth rehabilitation of a patient with severely worn dentition and deep bite using minimally invasive approach in current vertical dimension: A 3‐year follow‐up
Authors: Yaghoobi Negin , Mostafavi Azam , Barati Solmaz 
Published: November 2023

Key Clinical MessageRegaining restorative space for fullmouth reconstruction in a patient with deep bite and worn dentition by conservative approach in current vertical dimension and also using minimally invasive concept is recommended.AbstractFull mouth reconstruction of a deep bite patient with severely worn dentition is a challenging situation for the prosthodontists. This study represents minimally invasive procedures in mentioned condition without increasing vertical dimension. After 3 years of follow up no complication was observed.
Metal‐Free, Hindered, Regioselective Access to Multifunctional Groups Diarylamines via SNAr Substitution of P‐Nitroso Aromatic Methyl Ether by Arylamines
Authors: Zou Shuliang , Zhang Yazhou , Wu Qin , Zhao Tianming , Li Yutao , Liu Bing , Ma Xianguo 
Published: November 2023

AbstractMultifunctional groups diarylamines, an innovative product, efficiently produced from arylamines and p‐nitrosoanisole derivatives by intermolecular SNAr under weak acid conditions. This SNAr proceeds under mild reaction conditions, and more significantly, the substrates involved do not necessarily require strong electron‐withdrawing groups. Moreover, this SNAr is characterized by resistance to space crowding, tolerance to halogen and nitroso functional groups, and high regioselectivity. Mechanistic observations suggest that the SNAr is the result of the transfer of the positive charge center of the protonated nitroso group to the p‐methoxy group.