bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of botanical extract on controlling damping off disease of cauliflower
Authors:   Pankaj Kumar Yadav1, Bhujel Prabina , Adhikari Pratishtha , Pokhrel Sarad , Shrestha Samir , Amine Kouadri Mohamed El 
Published: October 2023

Abstract

An experiment was conducted with five treatments in pot culture at Chitwan, in Completely Randomized Design (CRD) with six replications to study the efficacy of botanicals in controlling damping off disease of cauliflower. Analysis of variance for each variable showed significant differences among treatments. The aqueous extracts of Neem leaf, Garlic clove and Bauhinia leaf were prepared for application. The positive control, Captan showed the highest efficiency in controlling pre - and post-emergence damping off and it was followed by Neem and Garlic, whereas both Neem and Garlic were statistically at par. Captan showed the highest germination percentage of seedlings 95.6% and least by Control (49.83%). The highest incidence of damping off was recorded in Control (80.49%). Neem and Garlic showed satisfactory results in controlling damping off disease and Bauhinia was insignificant with negative control. This suggested that, Neem and Garlic can be used to manage this nursery problem and more research is needed to be done in this regard.
Current scenario and challenges of clinical pharmacists to implement pharmaceutical care in DRG/DIP payment hospitals in China: a qualitative interview study
Authors: Gao Suyu , Wang Xuanxuan , Lu Yun , Liu Yunkun , Jiang Qiaoli , Feng Jiajia , Kong Weihua , Lin Likai , Cheng Hong 
Published: October 2023

Abstract
Purpose
The Diagnosis-Related Group (DRG) or Diagnosis-Intervention Packet (DIP)payment system, now introduced in China, intends to streamline healthcare billing practices. However, its implications for clinical pharmacists, pivotal stakeholders in the healthcare system, remains inadequately explored.This study sought to assess the perceptions, challenges, and roles of clinical pharmacists in China following the introduction of the DRG or DIP payment system.
Methods
Qualitative interviews were conducted among a sample of clinical pharmacists. Ten semi-structured interviews were conducted, either online or face to face. Thematic analysis was employed to identify key insights and concerns related to their professional landscape under the DRG or DIP system.
Results
Clinical pharmacists exhibited variable awareness levels about the DRG or DIP system. Their roles have undergone shifts, creating a balance between traditional responsibilities and new obligations dictated by the DRG or DIP system. Professional development, particularly concerning health economics and DRG-based or DIP-based patient care, was highlighted as a key need. There were calls for policy support at both healthcare and national levels and a revised, holistic performance assessment system. The demand for more resources, be it in training platforms or personnel, was a recurrent theme.
Conclusion
The DRG or DIP system's introduction in China poses both opportunities and challenges for clinical pharmacists. Addressing awareness gaps, offering robust policy support, ensuring adequate resource allocation, and recognizing the evolving role of pharmacists are crucial for harmoniously integrating the DRG or DIP system into the Chinese healthcare paradigm.
Discovery of N-Substituted Pyrazoline derivatives as novel 3-Benzo[b]thiophene and 2- Mercaptobenzimidazole inhibitor for the treatment of breast cancer
Authors: Jeyanthi S. , Muniyappan N. 
Published: October 2023

Abstract
A new series of pyrazoline derivatives 4(a-g) bearing 3-Benzo[b]thiophene and Benz imidazole thioether moiety were synthesised from substituted benzaldehyde and 2-acetyl benzo thiophene through Chalcones, followed by the cyclisation with hydrazine hydrate, acylation using chloroacetyl chloride and finally substituted with 1H-benzo[d]imidazole thiol. All synthesized compounds 4(a-g) were characterized by 1H NMR, 13C NMR and Mass spectra. The major scope behind the synthesis of these compounds is the immense biological activities associated to these heterocyclic derivatives against bacteria and fungi, anti-oxidant,anti-inflammatory and anti-cancer activity. Most of the compounds showed a fair degree of potent antimicrobial, anti-oxidant, anti-inflammatory and anticancer activity.
Automated Pain Assessment Increases Nurses’ Working Efficiency in elderly with hip fractures
Authors: Yang Shuang , Gong Liangbo , Zhao Huiwen , Liu Jing , Chen Xiaoying , Shen Siyi , Zhu Xiaoya , Luo Wen 
Published: October 2023

Abstract
The aim of this study was to design a modified ResNet 50 algorithm to achieve automatic classification model for pain expressions by elderly patients with hip fractures. We built a dataset by combining the advantages of deep learning in image recognition, using a hybrid of the Multi-Task Cascaded Convolutional Neural Networks (MTCNN). ResNet 50-based network framework utilized transfer learning to implement model function. We performed Bayesian optimization on the hyperparameters in the learning process. We calculated intraclass correlation between visual analog scale scores provided by nurses independently and those provided by pain expression evaluation assistant.The automatic pain expression recognition model for elderly patients with hip fractures, constructed using the algorithm, achieved an accuracy of 99.6% on the training set, 98.7% on the validation set, and 98.2% on the test set. The substantial kappa coefficient of 0.683 confirmed the PEEA's efficacy in pain assessment.This study demonstrates that the modified ResNet 50 algorithm with Bayesian optimization can be used to construct an automatic pain expression recognition model for elderly patients with hip fractures with higher accuracy.
Alkaloids and Quinolones as potential MtbTopI inhibitors: An in-silico discovery using ADME studies and molecular dynamics simulation
Authors: Cardoza Jyothsna Volisha , Ali Zeeshan , Singh Vijay Pratap , Issac Samuel Paul , Contini Alessandro , George Sudhan S. 
Published: October 2023

Abstract
Mycobacterium tuberculosis (M.tb), the causative agent of Tuberculosis, threats human lives more than any other infectious diseases worldwide. Despite of various developed drugs against M.tb, lack of an efficient therapeutic has led to continuous formulation of new drugs against the disease. The bacteria's specific adaptations to achieve drug resistance operate as a defensive mechanism, thereby making the development of anti-mycobacterial drugs particularly complicated. Therefore, targeting new receptors in the bacteria to develop a potential drug is recommended. In this study, a pool of alkaloid and quinolone compounds have been screened against the M.tb Topoisomerase I receptor. The prime function of MtbTopI in mycobacterium is to maintain DNA topology and regulate the torsional stress during DNA replication. Targeting MtbTopI can not only disrupt DNA structure, but also lead to restricted growth and ultimately death of the pathogen. A total of 257 alkaloids and 1515 quinolones were screened in silico against the receptor to find compounds able to inhibit the growth of Mycobacterium tuberculosis. One alkaloid and two quinolones were eventually found as potential inhibitors of MtbTopI.
Diagnostic model for radiographic instability of L4-5 degenerative lumbar spondylolisthesis based on propensity score matching and LASSO regression Author’s List
Authors: zhang Jing , Huang Zhongyichen , Wang Yi , Zhang Yao , Wen Donglin , Ran Jun , Wu Gang , Li Xiaoming 
Published: October 2023

Abstract

Background: This study aims to establish a diagnostic model for radiographic instability of L4-5 degenerative lumbar spondylolisthesis (DLS) based on propensity score matching (PSM) and least absolute shrinkage and selection operator (LASSO) regression.
Method: This retrospective study included 163 patients diagnosed with DLS at the L4-5 level. Radiographic instability was defined as a relative translation of >8% and an intervertebral angulation > 10° on standing lateral flexion-extension radiographs. 62 pairs of individuals with stable and unstable DLS were matched by PSM to minimize the influence of confounding baseline characteristics. LASSO regression was performed to select the optimal combination of features. Finally, a diagnostic model for radiographic instability was constructed using multifactor binary logistic regression. The model's efficiency was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve (ROC).
Result: Patients in unstable group had a higher fat fraction (FF) of multifidus (MF) and erector spinae (ES) muscles and a thicker ligamentum flavum (LF). There was no significant difference between the two groups for MF and ES relative cross-sectional areas, total endplate scores and modified Pfirrmann grades. As for T2 histogram features of paraspinal muscle (PM), significant differences between the two groups were found for mean, variance, skewness, kurtosis, 10th, 50th and 90th percentiles. There was a linear correlation between relative translation and MF FF (r=0.517), ES FF (r=0.456). 58 features were extracted from MRI images and T2 histograms of PM, and five features including MF FF, sum ES variance, left MF kurtosis, left MF skewness and left MF variance were selected by LASSO regression. MF fat fraction (OR=1.394, P<0.001), ES variance sum (OR=1.001, P<0.05) and thickened LF(Y/N) (OR=4.892, P<0.05) were potential risk factors for unstable DLS, whereas left MF variance (OR=0.998, P<0.01) was protective feature for stable DLS. The AUC, sensitivity and specificity of the diagnostic model were 0.972, 86.46% (95%IC 81.72%-91.20%) and 95.19% (95%IC 92.23%-98.16%) respectively.
Conclusion: FF and T2 histogram features of PM and LF morphology are valuable for lumbar dynamic instability. A diagnostic model based on these features in conventional MRI images and T2 histograms can evaluate radiological segmental stability of DLS.
Longitudinal association between household air pollution from biomass fuel use and depression in middle-aged and older adults in China: a national cohort study
Authors: Che xinyao , Quan Peiqin , Yang Yinan , Hu Xiaobin 
Published: October 2023

Abstract
Background
Incomplete combustion of biomass fuels significantly contributed to household air pollution (HAP). Evidence related to HAP and mental health from biomass fuel use remains limited. Therefore, we aimed to explore the longitudinal association between indoor biomass fuel consumption and depression.
Method
Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). Cox proportional hazards regression and linear mixed effects models were used to investigate the longitudinal association between indoor biomass fuel use and depression. We also investigated the effect of switching primary fuels on depression risk.
Result
A total of 4745 participants were included. Users of biomass fuel for heating and cooking had a higher risk of depression than those who used clean fuels, with hazard ratios (HRs) of 1.22 (95% confidence interval (CI): 1.09–1.36) and 1.33 (95% CI: 1.16–1.52), respectively. Furthermore, compared to clean fuel users, we found that biomass fuel users had elevated depression scores (β: 0.30, 95% CI: 0.11–0.49, P < 0.05 for cooking; β: 0.37, 95% CI: 0.15–0.59, P < 0.001 for heating), and higher growth rates of scores (β: 0.14, 95% CI: 0.05–0.22, P < 0.001 for cooking; β: 0.10, 95% CI: 0.01–0.19, P < 0.05 for heating). Compared to using clean fuels for both cooking and heating, utilizing biomass fuels for both cooking and heating increased the risk of depression (HR: 1.43, 95% CI: 1.23–1.67), along with a higher depression score (β: 0.50, 95% CI: 0.25–0.75, P < 0.001) and a higher growth rate of the score (β: 0.15, 95% CI: 0.05–0.25, P < 0.05). Additionally, individuals who changed their primary sources of heating and cooking from clean to biomass fuels had elevated risk of depression than those who always used clean fuels, with odds ratios (ORs) of 1.35 (95% CI: 1.05–1.76) and 1.43 (95% CI: 1.01–2.02), respectively.
Conclusion
Our research points to HAP as a potential contributor to depression risk in middle-aged and older adults. The usage of clean fuels should be encouraged since it may have a positive impact on mental health.
Multiple Graphs Structure of Intra-class Representation with Semantic Information for Image Annotation
Authors: liu baodi , Liu Yan , Shao Qianqian , Liu Weifeng 
Published: October 2023

Abstract
Automatic image annotation has absorbed a few research interests in recent decades quietly. Nevertheless, most methods leave graph structure out of consideration or utilize merely the graph without semantic information to capture manifold information of samples. Furthermore, it is inaccurate to consider the label matrix of a dataset as the feature matrix of tags during the computing label graph. To overcome these shortcomings, we propose a method, called Multiple Graphs Structure of Intra-class Representation with Semantic Information for Image Annotation. Our method proposes a superior multiple graphs structure called multiple graphs structure of intra-class representation as combining the semantic information with sample graph structure. Then, the probability Laplacian graph is presented to obtain the relationship between tags according to prior knowledge instead of exploiting tag features. Afterward, some experiments have been implemented to certify the effectiveness of the proposed graph structures on Corel5K, ESPGame, IAPRTC12, and NUS-WIDE datasets.
GANACHE: A Robust Framework for Efficient and Secure Storage of Data on Private Ethereum Blockchains
Authors: Mathur Garima 
Published: October 2023

Abstract
Blockchain technology has gained significant attention in recent years due to its decentralized and secure nature. Ethereum a popular blockchain platform supports the execution of smart contracts and enables the storage of data on the blockchain. However Ethereum's public nature may not be suitable for scenarios where sensitive or private data needs to be stored and accessed securely. In this paper we present GANACHE an efficient private Ethereum blockchain tool that addresses the confidentiality and security concerns associated with data storage. GANACHE leverages various cryptographic techniques such as encryption and zero-knowledge proofs to ensure the privacy of stored data while maintaining the benefits of blockchain technology.
The development and evidence of psychometric properties of the Self-Care Activities Scale focusing on the Daily Life Advanced Activities
Authors: Silva José Vitor , Maeda Marcos Toyotoshi , Orlandi Fabiana de Souza 
Published: October 2023

Abstract

Objective: To develop the Self-Care Activities Scale focusing on the Daily Life Advanced Activities (SCCAS-DLAAs) and to analyze its psychometric properties.
Method: This was a methodological, descriptive, and analytical study. The sample consisted of 1200 interviewees of both sexes, aged 70 years or older, residents in cities in southern Minas Gerais state, Brazil. The instruments used were as follows: an instrument to classify the baseline conditioning factors of elderly people, the SCCAS-DLAAs, and the Self-Care Skills Assessment Scale.
Results: The SCCAS-DLAAs consisted of 20 items and four domains, namely: Social (α Cronbach = 0.768), Leisure (α Cronbach = 0.643), Intellectual (α Cronbach = 0.708), and Religious (α Cronbach = 0.704). Convergent validity was satisfactory as it showed a positive and significant correlation (p≤0.001). For discriminant validation, the comparative analyses of the sociodemographic variables with the SCCAS-DLAAs were used, presenting a significance level between them, which demonstrated discriminative power.
Conclusion: The developed scale showed adequate reliability and validity for the Brazilian context.
Computational Profiling of Inflammatory and Coagulation Responses in COVID-19 via RNA-Seq
Authors: Chhabra Varun 
Published: October 2023

Abstract
The COVID-19 pandemic, driven by the SARS-CoV-2 virus, has emerged as an unparalleled global public health crisis. Despite extensive research efforts, the precise etiology of this disease remains enigmatic. In this study, we employ in-silico methods to analyze publicly available gene expression datasets from the Gene Expression Omnibus (GEO), aiming to uncover the underlying molecular mechanisms. Gene expression datasets were retrieved from GEO, and differential gene expression patterns were identified using the GEO2R pipeline. Subsequent analyses included the generation of heatmaps, principal component analysis (PCA), construction of protein-protein interaction networks (PPIs), and KEGG pathway predictions through NetworkAnalyst and DAVID. We also examined key hub genes, microRNA targets, and potential drug targets to elucidate the molecular intricacies involved. Our analysis revealed pivotal hub genes, such as VWF, TNF, E2F1, IL1B, IL10, IL-12A, ITGB-5, ELANE, and PLK1, alongside significant microRNAs like hsa-mir193b-3p, hsa-mir-92a-3p, hsa-mir-16-5p, hsa-mir-1925p, hsa-let-7b-5p, hsa-mir26a-5p, hsa-mir1865p, hsa-mir243a-5p, and hsa-mir-34a-5p. Pathways linked to inflammation, including neutrophil extracellular trap formation, systemic lupus erythematous, complement and coagulation cascades, and the coronavirus disease-COVID-19 pathway, played crucial roles in COVID-19 pathogenesis. Additionally, these identified genes and microRNAs hold promise as potential drug targets and biomarkers. In summary, this research offers valuable insights into the pathways, biomarkers, including gene targets and microRNA targets, as well as potential drug targets associated with the inflammatory and coagulation aspects of COVID-19. These discoveries enhance our understanding of the disease's molecular intricacies and open doors to the development of precisely targeted therapeutic interventions.
Building National Patient Registries in Mexico: Insights from the MexOMICS Consortium.
Authors: Reyes-Pérez Paula , Hernández-Ledesma Ana Laura , Román-López Talía V. , García-Vilchis Brisa , Ramírez-González Diego , Lázaro-Figueroa Alejandra , Martínez Domingo , Flores-Ocampo Victor , Espinosa-Méndez Ian M. , Tinajero-Nieto Lizbet , Peña-Ayala Angélica , Morelos-Figaredo Eugenia , Guerra-Galicia Carlos M. , Torres-Valdez Estefania , Gordillo-Huerta María Vanessa , Gandarilla-Martínez Nadia A. , Salinas-Barboza Karla , Félix-Rodríguez Guillermo , Frontana-Vázquez Gabriel , Matuk-Pérez Yamil , Estrada-Bellmann Ingrid , Alpízar-Rodríguez Deshiré , Rodríguez-Violante Mayela , Rentería Miguel E. , Ruíz-Contreras Alejandra E. , Alcauter Sarael , Medina-Rivera Alejandra 
Published: October 2023

Abstract

OBJECTIVE
To introduce MexOMICS, a Mexican Consortium focused on establishing electronic databases to collect, cross-reference, and share health-related and omics data on the Mexican population.
METHODS
The Mexican Twin Registry (TwinsMX), Mexican Lupus Registry (LupusRGMX) and the Mexican Parkinson’s Research Network (Mex-PD) were designed and implemented using Research Electronic Data Capture web-based application. Registries were compiled through voluntary participation and on-site engagement with medical specialists. In some instances, DNA samples and Magnetic Resonance Imaging images were also acquired.
RESULTS
Since 2019, the MexOMICS Consortium has successfully established three electronic-based registries: TwinsMX (n = 2915), LupusRGMX (n = 1761) and Mex-PD (n = 750). In addition to sociodemographic, psychosocial, and clinical data, MexOMICS has collected samples for genetic determinations across the three registries. Cognitive function assessments, conducted using the Montreal Cognitive Assessment, have been administered to a subsample of 376 Mex-PD participants. Furthermore, a subset of 267 twins underwent measurements of structural, functional, and spectroscopy brain images; comparable evaluations are projected for LupusRGMX and Mex-PD.
CONCLUSIONS
The MexOMICS registries offer a valuable repository of information concerning the potential interplay of genetic and environmental factors in health conditions among the Mexican population.
Using Torsional Wave Elastography to Evaluate Spring Pot Parameters In Skin Tumor Mimicking Phantoms
Authors: Almashakbeh Yousef saleh , Shamimi Hirad , Callejas Antonio , Rus Guillermo 
Published: October 2023

Abstract
Estimating the tissue parameters of skin tumors is crucial for diagnosis and effective therapy in dermatology and related fields. However, identifying the most sensitive biomarkers require an optimal rheological model for simulating skin behavior this remains an ongoing research endeavor. Additionally, the multi-layered structure of the skin introduces further complexity to this task. In order to surmount these challenges, an inverse problem methodology, in conjunction with signal analysis techniques, is being employed. In this study, a fractional rheological model is presented to enhance the precision of skin tissue parameter estimation from the acquired signal from torsional wave elastography technique (TWE) on skin tumor-mimicking phantoms for lab validation and the estimation of the thickness of the cancerous layer. An exhaustive analysis of the spring-pot model (SP) solved by the finite difference time domain (FDTD) is conducted. The results of experiments performed using a TWE probe designed and prototyped in the laboratory were validated against ultrafast imaging carried out by the Verasonics Research System. Twelve tissue-mimicking phantoms, which precisely simulated the characteristics of skin tissue, were prepared for our experimental setting. The experimental data from these bi-layer phantoms were measured using a TWE probe, and the parameters of the skin tissue were estimated using inverse problem-solving. The agreement between the two datasets was evaluated by comparing the experimental data obtained from the TWE technique with simulated data from the spring-pot FDTD model using Pearson correlation, dynamic time warping (DTW), and time-frequency representation. Our findings show that the spring-pot FDTD model and TWE are capable of determining the mechanical properties of both layers in a bilayer phantom, using a single signal and an inverse problem approach. The ultrafast imaging and the validation of TWE results further demonstrate the robustness and reliability of our technology for a realistic range of phantoms. This fusion of the spring-pot FDTD model and TWE, as well as inverse problem-solving methods has the potential to have a considerable impact on diagnoses and treatments in dermatology and related fields.