Prevalence and influencing factors of kinesiophobia after total knee arthroplasty: a systematic review and meta-analysis by Xingbin Du, Yuanwei Shao, Jian Xue, Jianda Kong

“…Two independent researchers used Newcastle-Ottawa Scale (NOS) to evaluate the quality of the included literature. After data extraction, Meta-analysis was performed using Stata17.0. …”
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The Use of Exercise Prescription in Australian Osteopathy Practice: Secondary Analysis of a Nationally Representative Sample of the Profession by Michael Fleischmann, Brett Vaughan, Kylie Fitzgerald

“…This work presents a secondary data analysis of the Australian osteopathy practice-based research network and profiles the characteristics of osteopaths who often use exercise prescription in patient care. …”
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In silico analysis of L- and G-type lectin receptor kinases in tomato: evolution, diversity, and abiotic responses by Makarim Elfadil M. Osman, Rieham Sallah H. Osman, Sara A. A. Elmubarak, Mohanad A. Ibrahim, Hana Badreldin Mohamed Abakar, Amina I. Dirar, Emadeldin Hassan E. Konozy

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Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms by Bowen Zheng, Jianxiong Qiao, Xiaoping Yu, Hanghang Zhou, Anqi Wang, Xuanfen Zhang

“…This study sought to identify biomarkers and potential therapeutic targets for KD through an integrative bioinformatics approach and machine learning analysis of RNA sequencing data. Methods RNA sequencing was performed on skin tissue samples from 13 patients with KD and 14 healthy controls. …”
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Genomic analysis and characterization of lytic bacteriophages that target antimicrobial resistant Escherichia coli in Addis Ababa, Ethiopia by Tamirat Salile Sada, Dawit Hailu Alemayehu, Kalkidan Melaku Tafese, Tesfaye Sisay Tessema

“…In total, 33–218 CDSs (coding sequences) were predicted, with 19–77 % of CDSs encoding functional proteins. All phages lacked tRNA genes in their genomes, except for EI-SP-GF, which possessed five tRNA genes. …”
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Bioinformatics analysis to explore biomarkers and mechanisms of action associated with endoplasmic reticulum stress and ferroptosis in Parkinson's disease. by Hao Wang, Lijuan Feng, Limeng He, Nan Liu, Yan Wan, Wei Zhang

“…Further investigations included functional enrichment analysis, the construction of a protein-protein interaction (PPI) network, and the examination of related genes. …”
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Analysis of mutations in precision oncology using the automated, accurate, and user-friendly web tool PredictONCO by Rayyan Tariq Khan, Petra Pokorna, Jan Stourac, Simeon Borko, Adam Dobias, Joan Planas-Iglesias, Stanislav Mazurenko, Ihor Arefiev, Gaspar Pinto, Veronika Szotkowska, Jaroslav Sterba, Jiri Damborsky, Ondrej Slaby, David Bednar

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Risk factors for pneumonia after radical gastrectomy for gastric cancer: a systematic review and meta-analysis by Siyue Fan, Hongzhan Jiang, Qiuqin Xu, Jiali Shen, Huihui Lin, Liping Yang, Doudou Yu, Nengtong Zheng, Lijuan Chen

“…RevMan 5.4 and R 4.4.2 were the program used to perform the meta-analysis. Results Our study included data from 20,840 individuals across 27 trials. …”
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Analysis of the Influence of Comorbid States on COVID-19 Severity and In-Hospital Mortality for Further Application in an Outpatient Setting by A. Kurakh, I. Chopey, K. Hechko

“…From the register under investigation were excluded articles based on the criteria as follows: patient groups consisting of children under the age of 18 and pregnant women, the lack of cal- culated odds ratios (OR) and patient groups with high risk underlying conditions without multivariable analysis to exclude interference in the results. The data were analyzed based on two main outcomes for each comorbidity - severe disease (including inpatient ICU transfer) and in hospital mortality. …”
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Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease. by Enrique Audain, Anna Wilsdon, Jeroen Breckpot, Jose M G Izarzugaza, Tomas W Fitzgerald, Anne-Karin Kahlert, Alejandro Sifrim, Florian Wünnemann, Yasset Perez-Riverol, Hashim Abdul-Khaliq, Mads Bak, Anne S Bassett, D Woodrow Benson, Felix Berger, Ingo Daehnert, Koenraad Devriendt, Sven Dittrich, Piers Ef Daubeney, Vidu Garg, Karl Hackmann, Kirstin Hoff, Philipp Hofmann, Gregor Dombrowsky, Thomas Pickardt, Ulrike Bauer, Bernard D Keavney, Sabine Klaassen, Hans-Heiner Kramer, Christian R Marshall, Dianna M Milewicz, Scott Lemaire, Joseph S Coselli, Michael E Mitchell, Aoy Tomita-Mitchell, Siddharth K Prakash, Karl Stamm, Alexandre F R Stewart, Candice K Silversides, Reiner Siebert, Brigitte Stiller, Jill A Rosenfeld, Inga Vater, Alex V Postma, Almuth Caliebe, J David Brook, Gregor Andelfinger, Matthew E Hurles, Bernard Thienpont, Lars Allan Larsen, Marc-Phillip Hitz

“…We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. …”
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TRPC6 is a Biomarker for Prognosis and Immunotherapy of Stomach Adenocarcinoma Based on Bioinformatic Analysis and Experimental Validation by Hu X, Wang H, Sun H, Zhang J, Ye Z, Huang Z

“…Although previous studies have implicated TRPC6 in the progression of stomach adenocarcinoma (STAD), its precise functions and mechanisms remain unclear. Understanding TRPC6’s role in STAD may provide insights into its prognostic and therapeutic potential.Methods: Using transcriptional and clinical data from The Cancer Genome Atlas (TCGA) database, we assessed the expression and prognostic value of TRPC6 in STAD through Kaplan-Meier survival curve analysis and correlation studies. …”
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A propensity-matched analysis of cardiac operation in patients with and without cardiac amyloidosisCentral MessagePerspective by Akshay Chauhan, MBBS, Kevin L. Greason, MD, Daniel D. Borgeson, MD, Austin Todd, MS, John M. Stulak, MD, Richard C. Daly, MD, Juan A. Crestanello, MD, Hartzell V. Schaff, MD

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COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT by Thabit Sultan Mohammed, Awni Ismail Sultan, Khattab M. Ali Alheeti, Karim Mohammed Aljebory, Hasan Ismail Sultan, Muzhir Shaban Al-Ani

“…Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. …”
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Kinetic analysis of PODE1–3 combustion mechanisms: towards a general framework for reaction pathways by He Liu, Yajing Yang, Yanju Wei, Abdullah Baig, Yuning Tang, Muhammad Shahid Farooq, Ning Li

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A retrospective analysis of hemodynamic stability in TAVR and TTVR under general anesthesia: implications for sedation in TTVR by Jingsi Wu, Xiaoyu Shang, Yuyu Gu, Yuhang Ying, Jinbao Li, Yun Zou

“…All relevant clinical data were meticulously collected and analyzed using standardized protocols. …”
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Prevalence survey and prognosis analysis of hospitalized patients with acute kidney injury:a single-center study by PAN Xin, NIE Qing-qing, GU Jie, ZHAO Deng-wang, DUAN Yan-ya, ZHAO Dan, ZHANG Chun-jiang, YANG Xiao-ping

“…Objective To investigate the prevalence and the prognosis of acute kidney injury(AKI) in our region and to find out the risk factors associated with the outcome.Methods Between Jan.to Dec.2015,all the hospitalized patients in First Affiliated Hospital of Medical College were screened by Laboratory data retrieval system.Our study cohort was comprised of all the patients with AKI defined by latest clinical guidelines of KDIGO for definition of the renal creatinine.The prevalence was retrospectively analyzed.Logistic regression analysis was used to investigate the risk factors of mortality and renal prognosis.Results Of all the 58 444 hospitalized patients,609 patients suffered from AKI with the prevalence being 1.04%.The ratio of male to female was(2.07:1),and age was(66.3±16.1) years old.by KDIGO criteria,40.9%(n=249) had stage 1,43.2%(n=263) had stage 2 and 15.9%(n=97) had stage 3.The prerenal,intrarenal and postrenal reasons for hospitalized patients with AKI accounted for 70.6%(n=431),21.5%(n=131),and 7.9%(n=48),respectively.On the day 7 after AKI,the mortality rate was 25.5%(155/609).In the final observation,the mortality rate was 29.1%(177/609),complete renal unrecovery rate was 29.9%,partial renal recovery rate was 41.2%,complete renal recovery rate was 18.7%,and the renal function couldn’t be judged in 10.2%patients due to undetermination of creatinine values.Multivariate logistic regression analysis showed that the independent risk factors for mortality were age(OR = 1.598),AKI stage(OR= 1.538),coma(OR= 2.659),and chronic liver disease(OR= 2.134).Organ failure except kidney(P<0.01,OR= 2.548,95%CI:1.717~3.783) was the independent risk factor for renal unrecovery.Conclusions AKI is an increasingly common and potentially catastrophic complication in hospitalized patients.Age,AKI stage,coma,and chronic liver disease were the independent risk factors for mortality.Organ failure except kidney was the independent risk factor for renal unrecovery.AKI should not be viewed as a self-limited disease process from which most patients eventually recover but rather as a significant risk factor for long-term morbidity and mortality following hospital discharge.…”
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Immunohistochemical Analysis of Scarring Trachoma Indicates Infiltration by Natural Killer and Undefined CD45 Negative Cells. by Victor H Hu, Philip J Luthert, Tamsyn Derrick, James Pullin, Helen A Weiss, Patrick Massae, Tara Mtuy, William Makupa, David Essex, David C W Mabey, Robin L Bailey, Martin J Holland, Matthew J Burton

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Machine-learning aided calibration and analysis of porous media CFD models used for rotating packed beds by Ahmed M. Alatyar, Abdallah S. Berrouk

“…The results are validated against the predictions of the analytical sensitivity analysis and the finite difference approximation. After, the Newton – Gauss method that employs the sensitivity pressure drop derivatives, is used to minimize the error (cost function) between the pressure drop obtained from CFD simulations and the available experimental data. …”
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Integrated Co-extraction Protocol for Transcriptomic and 1H NMR Metabolomic Analysis of Multi-species Biofilms by Anaïs Séguéla, Oriane Della-Negra, Roselyne Gautier, Jérôme Hamelin, Kim Milferstedt, Rémi Servien, Marie-Ange Teste, Cécile Canlet

“…The co-extraction will enable a holistic analysis of the metabolomics and metatranscriptomics data generated, minimizing experimental biases, including technical variations and, notably, biological variability. …”
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Efficacy and Safety of Recombinant Human Prourokinase in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis by Abdulaziz A. Alzahrani MBBCh, Ahmed A. Maiz MBBCh, Ahmed A. Ibrahim MBBCh, Mohamed Rifai MBBCh, Suhaiyh Sanad Alotibi MBBCh, Leena Salem MBBCh, Hadeel A. Alzabidi MBBCh, Sarah Mansour Alshehri MBBCh, Yara Fahad Almazyad MBBCh, Zeyad T. Mansour MBBCh, Abubaker Osman Ahmed MD

“…Data were pooled using risk ratio (RR) or mean difference (MD) with 95% confidence intervals (CI) in R version 4.3. …”
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