bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spread of Staphylococcus aureus resistant genes to antibiotics: Clones and genetic elements (toxin genes)
Authors: Vittorakis Eftychios , Vica Mihaela Laura , Zervaki Calina-Oana , Vittorakis Evangelos , Maraki Sofia , Mavromanolaki Viktoria Eirini , Schürger Michael Ewald , Neculicioiu Vlad Sever , Papadomanolaki Evangelia , Maragoudakis Spyridon , Junie Lia Monica 
Published: April 2023

Abstract
Antibiotic overuse has led to the emergence of resistant strains of bacteria, such as Methicillin-resistant Staphylococcus aureus (MRSA), which has become a global public health concern. The aim of this study was to investigate the genetic and microbiological characteristics of MRSA in hospitals in Crete, located in the southeastern Balkan region. S. Aureus samples were collected from hospitalized patients and tested for antibiotic susceptibility using the Kirby-Bauer disk diffusion method. The presence of mecA, enterotoxin genes (sem gene or seg genes), agr genes, and PVL genes was detected using PCR. Of the 141 S. Aureus strains tested, 102 (72.34%) were found to have the genes of interest, with 69 MRSA (48.9%) mecA+ strains and 33 methicillin-susceptible S. Aureus (MSSA) mecA negative strains. The most prevalent gene detected was the agr gene (48.93%), followed by the enterotoxin gene (44.68%). Four agr groups (I – IV) were detected in 69 MRSA isolates (48.9%). This study highlights the prevalence of MRSA in hospitals in Crete and emphasizes the importance of appropriate antibiotic use and infection control measures to prevent the spread of antibiotic-resistant bacteria. Although a correlation between the presence of the detected genes and certain resistance phenotypes was not observed, the findings indicate the necessity to trace these genes using PCR and involve them in clinical diseases. The circulation of sensitive strains to antibiotics and resistant strains to some antibiotics with different resistance phenotypes was also noted in the hospital. Overall, this study provides important insights into the genetic and microbiological characteristics of MRSA in the southeastern Balkan region, and the results can inform future efforts to control the spread of antibiotic-resistant bacteria.
Combining geophysical and geological datasets to improve a conceptual aquifer model of the Oak Openings Region in northwest Ohio, USA
Authors: Ogunkoya Akinwale O. , Martin-Hayden James M. , Fisher Timothy G. , Doro Kennedy O. 
Published: April 2023

Abstract
In this study, geophysical and geologic data were combined to develop a 3D conceptual hydrogeological model of a section of the Oak Openings Region (OOR) in northwest Ohio with a globally rare ecosystem of oak savanna and grassland prairie. The presence of a rhythmically laminated silt and clay unit underlying the study area is now widely realized. Assessing the influence of this unit on the interaction between shallow unconfined, sandy, and confined carbonate bedrock aquifers requires an appropriate groundwater model. A first step to this is to update the current conceptual hydrogeological model of the region, which either neglects the rhythmites or combines it with the till as a single hydrogeological unit. To do this, twenty electrical resistivity soundings and eleven 166 m long 2D transects of electrical resistivity data were combined with refraction seismic data acquired along a 96 m long transect. The geophysics results were validated with lithological data from a public database and two wells drilled during the study. A digital elevation model and stratigraphic layers extracted from the geophysics result were used to create a 3D site model. The model shows four layers consisting of a carbonate bedrock aquifer, confining till layer, rhythmically laminated silt and clay, and a sandy aquifer in a bottom-up sequence. The rhythmites consist of horizontal laminae that are more permeable than the underlying till. Combining geophysics with geologic data distinguished the till from rhythmites and defines the hydrostratigraphic layers used to refine the aquifer conceptual model across sections of the OOR.
Exploration of urban sustainability of India through the lens of sustainable development goals
Authors: Roy Ajishnu , Garai Nandini , Biswas Jayanta Kumar 
Published: April 2023

Abstract
Sustainable Development Goal (SDG) index is a recognized metric for measuring progress in the UN SDGs. However, national or multinational-level analyses are more prevalent than sub-national types. We analysed the performance of 14 SDGs for 56 Indian cities (grouped into 6 regions) with available 77 indicators (2020–2021). Pearson’s correlation, hierarchical clustering, data envelopment analysis etc. were used to infer existing status, interactions, efficiency, and interrelationships. Finally, we offer policy suggestions coupled with limitations to mitigate the drawbacks of the Indian city SDG framework. The findings reveal the asynchronous nature of SDGs. 18% of Indian cities register a poor track record of converting environmental performance into socioeconomic prosperity while 55% of cities are lagging in performance than respective states. A significant degree of inequality reigns among cities of various regions towards achieving SDGs. In a race to be economically powerful, the environment is being adversely affected. So, mainstreaming the environment into development planning is urgently warranted.
SH2 Superbinder Inhibits Autophagy of Pancreatic Cancer Cells by Blocking DDR1-Mediated Signaling
Authors: Liu An-Dong , Hou Guo-Qing , Sang Ya-Zhou , Lin Li , Gan Xiao-Cai , Xu Hui , Cao Xuan 
Published: April 2023

AbstractBackgroundPancreatic cancer is highly lethal, of which 90% is pancreatic ductal adenocarcinoma (PDAC), with a 5-year survival rate of less than 12%, lacking effective treatment options and late diagnosis. Furthermore, the tumors show an intense resistance to cytotoxic chemotherapies. As autophagy is elevated in PDAC, targeting the autophagic pathway is regarded as a promising strategy for cancer treatment.MethodsImmunofluorescence and transmission electron microscopy were utilized to assess the autophagic flux. Label-free quantitative phosphoproteomics was used to figure out critically altered tyrosine phosphorylation of the proteins. Tumor-bearing mice were used to validate that SH2 TrM-(Arg)9 restrained the growth of tumor cells.ResultsSH2 TrM-(Arg)9 inhibited collagen-induced autophagy via blocking the DDR1/PYK2/ERK signaling cascades. SH2 TrM-(Arg)9 improved the sensitivity of PANC-1/GEM cells to gemcitabine (GEM). Inhibition of autophagy by SH2 TrM-(Arg)9 may synergized with chemotherapy and robusted tumor suppression in pancreatic cancer xenografts.ConclusionsSH2 TrM-(Arg)9 could enter into PDAC cells and blockade autophagy through inhibiting DDR1/PYK2/ERK signaling and may be a new treatment strategy for targeted therapy of PDAC.
Description of Sporanaerobium hydrogeniformans gen. nov., sp. nov., an obligately anaerobic, hydrogen producing bacterium of Lachnospiraceae family isolated from Aravali hot spring in India
Authors: Hivarkar Sai Suresh , Vasudevan Gowdaman , Dhakephalkar Prashant K. , Dagar Sumit Singh 
Published: April 2023

Abstract
An obligately anaerobic bacterium XHS1971T, capable of degrading cellulose and xylan, was isolated from the sediment sample of a hot spring located in Aravali, Ratnagiri, India. Cells of strain XHS1971T were Gram-stain-negative, spore-forming, motile, long rods. Growth of strain XHS1971T was observed at temperatures 30–50°C (optimum 40–45°C), pH 5.0–10.0 (optimum pH 8.0) and NaCl concentrations 0–0.5% (optimum 0%). The generation time of strain XHS1971T was 5 h under the optimized growth conditions. The strain XHS1971T showed the ability to metabolize different complex and simple sugars constituting lignocellulosic biomass. The strain fermented glucose, majorly into hydrogen, formic acid, acetic acid, and ethanol, whereas carbon dioxide, butyric acid, lactic acid and succinic acid were produced in traces. The major cellular fatty acids (> 5%) were C14:0, C16:0, C18:0, and C16:1 ω7c. The 16S rRNA gene analysis of the strain XHS1971T revealed the highest homology of < 94.5% with Cellulosilyticum lentocellum DSM 5427T followed by Cellulosilyticum ruminicola JCM 14822T, identifying it as a distinct member of family Lachnospiraceae. The genome size of the strain was 3.74 Mb with a G + C content of 35.3 mol% and predicted to have 3828 protein-coding genes. Of these, 357 genes were annotated to carbohydrate metabolism, including genes involved in the degradation of cellulose and xylan and the production of hydrogen, ethanol and acetate. The results indicate the potential use of strain XHS1971T in biomass-derived biofuel production. The uniqueness of our strain was further validated by digital DNA-DNA hybridization (dDDH), Average Nucleotide Identity (ANI), and Average Amino Acid Identity (AAI) values of 22%, 80%, and 63%, respectively, with nearest phylogenetic affiliates. Based on the detailed analyses, we propose a new genus and species, Sporanaerobium hydrogeniformans gen. nov., sp. nov., for strain XHS1971T (= MCC 3498T = KCTC 15729T = JCM 32657T) within the family Lachnospiraceae.
Feasibility of a reconfigured domestic violence and abuse training and support intervention responding to affected women, men, children and young people through primary care
Authors: Szilassy Eszter , Coope Caroline , Emsley Elizabeth , Williamson Emma , Barbosa Estela Capelas , Johnson Medina , Dowrick Anna , Feder Gene 
Published: April 2023

Abstract

Background
Identification in UK general practice of women affected by domestic violence and abuse (DVA) is increasing, but men and children/young people (CYP) are rarely identified and referred for specialist support. To address this gap, we collaborated with IRISi (UK social enterprise) to strengthen elements of the IRIS+ intervention which included the identification of men, direct engagement with CYP, and improved guidance on responding to information received from other agencies. IRIS+ was an adaptation of the national IRIS (Identification and Referral to Improve Safety) model focused on the needs of female victim-survivorsof DVA. Without diminishing the responses to women, IRIS+ also responded to the needs of men experiencing or perpetrating DVA, and CYP living with DVA and/or experiencing it in their own relationships. Our study tested the feasibility of the adapted IRIS+ intervention in England and Wales between 2019-21.
Methods
We used mixed method analysis to triangulate data from various sources (pre/post intervention questionnaires with primary care clinicians; data extracted from medical records and DVA agencies; semi-structured interviews with clinicians, service providers and referred adults and children) to assess the feasibility and acceptability of the IRIS+ intervention.
Results
The rate of referral for women doubled (21.6/year/practice) from the rate (9.29/year/practice) in the original IRIS trial. The intervention also enabled identification and direct referral of CYP (15% of total referrals) and men (mostly survivors, 11% of total referrals). Despite an increase in self-reported clinician preparedness to respond to all patient groups, the intervention generated a low number of male perpetrator referrals (2% of all referrals). GPs were the principal patient referrers. Over two-thirds of referred women and CYP and almost half of all referred men were directly supported by the service. Many CYP also received IRIS+ support indirectly, via the referred parents. Men and CYP supported by IRIS+ reported improved physical and mental health, wellbeing, and confidence.
Conclusions
Although the study showed acceptability and feasibility, there remains uncertainty about the effectiveness, cost-effectiveness, and scalability of IRIS+. Building on the success of this feasibility study, the next step should be trialling the effectiveness of IRIS+ implementation to inform service implementation decisions.
Analysis of prognostic value of lactate metabolism-related genes in ovarian cancer based on bioinformatics
Authors: Sun Jinrui , Xu Yingying , Liu Ping , Wu Yumei 
Published: April 2023

Abstract
Background Recent studies have provided evidence supporting the functional role and mechanism of lactate in suppressing anticancer immunity. However, there is no systematic analysis of lactate metabolism-related genes (LMRGs) and ovarian cancer (OV) prognosis.Results Six genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) were selected as prognostic genes and a prognostic model was utilized. Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) analyses were further performed and indicated that the prognostic model was effective. Subsequently, the neoplasm_cancer_status and RiskScore were determined as independent prognostic factors, and a nomogram was established with relatively accurate forecasting ability. Additionally, 2 types of immune cells (Central memory CD8 T cell and Immature B cell), 4 types of immune functions (APC co inhibition, DCs, Tfh and Th1 cells), 9 immune checkpoints (BTLA, CTLA4, IDO1, LAG3, VTCN1, CXCL10, CXCL9, IFNG, CD27) and tumor immune dysfunction and exclusion (TIDE) scores were significantly different between risk groups. The expression of 6 genes were verified by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and the expression of 6 genes were higher in the high-grade serous carcinoma (HGSC) samples.Conclusion A prognostic model related to lactate metabolism was established for OV based on six genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) that could provide new insights into therapy.
Prognostic factors and construction of a nomogram prediction model for ductal adenocarcinoma of the prostate based on the SEER database
Authors: Li Cheng , Wan Zhengqiang , Wang Yinglei , Shan Gaungming , Yang Baoquan 
Published: April 2023

Abstract
Background: The aim of this study was to determine the prognostic factors associated with survival in patients with ductal carcinoma of the prostate (DAC) and to develop a nomogram model for them that can be individually predicted.
Methods: We explored prognostic factors affecting patients with ductal adenocarcinoma of the prostate using univariate and multifactorial COX regression analyses, Kaplan-Meier method, using clinical data from DAC patients collected between 2003-2017 from the Surveillance, Epidemiology and End Results (SEER) database. Nomogram models predicting overall survival in DAC patients were drawn based on the results of the multifactorial analysis, and the discriminatory power and ability of the prediction models were assessed by prediction curves, the area under the curve(AUC) and decision curve analysis (DCA).
Results: A total of 834 patients were included in this study and were randomized in a 7:3 ratio into a training cohor (n = 585) and a validation cohor (n = 249). After univariate and multivariate Cox regression analyses, we identified that eight independent risk factors (age, T-stage, N-stage, M-stage, surgery, lymph node dissection, Gleason score, PSA) were identified for patients with DAC, and subsequently the first static and online nomogram for predicting overall survival for patients with DAC were created, respectively. Calibration curves were plotted and found that predicted survival closely matched actual survival, with AUC for the training cohort at 1-, 3-, 5-year being 0.807, 0.841 and 0.850 respectively. Further internal validation was performed and the AUC for the internal Validation cohort were 0.887, 0.848 and 0.817 respectively. The AUC and DCA were better than the TNM system. In addition, our study also found that patients with non-metastatic DAC who underwent the RP surgical approach or surgery combined with lymph node dissection had a better prognosis.Finally patients in the training and validation cohort were divided into high and low risk groups based on nomogram scores.
Conclusion:We constructed and validated the first static and online nomogram for predicting patients with DAC. The high predictive accuracy and reliability of this study will help physicians to analyse the prognosis of patients and individualise treatment.
Multidrug-resistant gram-negative bacterial infections and associated factors in a Kenyan intensive care unit: A cross-sectional study
Authors: Maina Jane Wairimu , Onyambu Frank Gekara , Shikuku Peter Kibet , Musyoki Abednego Moki 
Published: April 2023

Abstract
Background: Patients admitted to intensive care units (ICU) are at risk of Gram-negative bacteria (GNB) infections, especially those caused by multidrug-resistant (MDR) isolates, increasing morbidity, mortality, and increased healthcare costs. However, epidemiological surveillance data on MDR bacteria to inform infection prevention and control (IPCs) interventions is limited in our study setting. Here we assessed the prevalence and factors associated with GNB infections in ICU- patients admitted in our study setting.
Methods: This was a hospital-based cross-sectional study among patients admitted to the ICU at the Nairobi West Hospital, Kenya, between January and October 2022. A total of 162 patients were recruited, excluding those hospitalized for less than 48 hours and declining consent. We collected the participants' demographics and clinical data by case report form. Samples were collected and transported to the hospital microbiology laboratory in a cool box and processed, within 2 hours, by standard bacteriological and automated methods.
Results: The prevalence of GNB infections was 55.6%, predominated by urinary tract infections (UTIs). We recovered 13 GNB types, with Escherichia coli (33.3%) and Klebsiella pneumoniae (31.1%) as the most common isolates. Factors associated with GNB infections were a history of antibiotic use (aOR = 4.23, p =0.001), nasogastric tube use (NGT, aOR = 3.04, p = 0.013), respiratory tract (RT, aOR = 5.3, p= 0.005) and cardiovascular (CV, aOR = 5.7, p = 0.024 conditions. About 92% of the GNB isolates were MDR, predominately Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa.
Conclusion: We report a high prevalence of MDR-GNB infections, predominated by UTI, in ICU, where patients with a history of antibiotic use, using the NGT, and having RT and CV conditions were at increased risk. In our study setting, improving ICU patient management warrants strict adherence to IPC policies and implementation of antimicrobial stewardship programs in line with the global and national antimicrobial action plans.
Water Body Change Detection and Estimation From Landsat Satellite Images Using Deep Learning
Authors: Devaki M. , Jayanthi K. B. 
Published: April 2023

Abstract
Identification of urban water bodies from satellite images has been extensively explored in the recent past. Different types of mechanisms have been developed to delineate water bodies from distinct satellite images differing in spatial and temporal aspects. The problem of identifying urban water body with abundant sureness materializes in several applications. Amongst them, natural resource mapping like forest and urban water bodies utilizing satellite image has received much significance over the past few years. This is owing to the reason than both forest and water resources are dependent on each other to enormous exploitation and hence monitoring them at regular time intervals is highly essential for their sustainable management. At the same time, different methods have been adopted to select the pertinent features from satellite images using machine learning and each method has its own advantages and disadvantages. In this work, a method called, Nonlinear Recursive Filter used to preprocessing the satellite image and Convolution neural network (Deep learning method) used for urban water body identification from satellite images is proposed. The proposed CNN method is split into three parts. First, with the satellite images of water bodies taken as input, significant amount of noise are removed and also preserving the edges for future reference with the aid of Nonlinear Recursive Filter-based Preprocessing model. Second with the noise minimized preprocessed water body images, relevant features are selected in Convolution neural network Deep learning model. Finally, appropriate classification between the water bodies and non-water bodies are made by utilizing CNN Model. Experiments are conducted using water body images and simulations are performed to analyze PSNR, water body identification justify that accuracy, Spatial and Temporal analysis.
Perceived Disrespectful Treatment in Low Income Healthcare Settings Through the Lens of Intersectionality
Authors: Sntiselaar Sara , Carr Deborah 
Published: April 2023

Abstract
Race and gender differences in the quality of one’s health care encounters are widely documented, but few studies explore the multiplicative impacts of race and gender. Drawing on intersectionality frameworks, we contrast white, Black, Hispanic, Asian, and Native American men’s and women’s perceptions of disrespectful treatment from health care providers and staff (e.g., receptionists, clerks) in low-income health settings. Data are from the 2014 Health Center Patient Survey (N=5,385), a nationally representative survey of community-dwelling patients receiving care at health centers funded through Section 330 of the Public Health Service Act. Our results show race and sex differences in the study outcomes, yet weaker support for intersectional effects. Asian men and women report significantly more disrespectful treatment from providers and staff, relative to other ethnic groups. Across race and ethnic groups, women are more likely than men to report disrespectful treatment from staff. Health care providers and staff may require training focused on the distinctive needs of Asian patients, for whom “saving face” is a salient goal. Structural changes to reduce wait times and employ medical interpreters, and staff training focused on verbal and nonverbal communication may mitigate against actions perceived as disrespectful in low-income health settings.
Kinetic and Mechanistic Studies of Forskolin Oxidation By hexavalent Chromium, N-halosuccinimides, Ceric Ammonium Nitrate In Perchloric and Nitric acid Media.
Authors: Bibballi Sridhar Swamy 
Published: April 2023

Abstract
This study is dealing with the natural product forskolin (ROH) oxidation, by using various oxidants such as hexavalent chromium, N-halosuccinimides, ceric ammonium nitarte in solvent 'DMF-Perchloric acid' and 'methanol- nitric acid' medium. The pseudo firstorder kineticks followed for the oxidation process to investigate the linear energy solvent relation ship for better scope of thermodynamic properties change, nature of reactive species involved (anoinic, cationic, radical or complex) in transition state. The reaction theme is is to compare the efficiency and selectivity of the different oxidants and discuss the factors influencing in favor of oxidation, finally the most suaitable oxidants are figured out and substantiated with the reaction mechanism.