Discovering the Symptom Patterns of COVID-19 from Recovered and Deceased Patients Using Apriori Association Rule Mining

The COVID-19 pandemic has a devastating impact globally, claiming millions of lives and causing significant social and economic disruptions. In order to optimize decision-making and allocate limited resources, it is essential to identify COVID-19 symptoms and determine the severity of each case. Machine learning algorithms offer a potent tool in the medical field, particularly in mining clinical datasets for useful information and guiding scientific decisions. Association rule mining is a machine learning technique for extracting hidden patterns from data. This paper presents an application of association rule mining based Apriori algorithm to discover symptom patterns from COVID-19 patients. The study, using 2875 records of patient, identified the most common symptoms as apnea (72%), cough (64%), fever (59%), weakness (18%), myalgia (14.5%), and sore throat (12%). The proposed method provides clinicians with valuable insight into disease that can assist them in managing and treating it effectively

Long-Term Effects of Low-Dose Naltrexone on Immunomodulatory Properties of Human Adipose-Derived Mesenchymal Stem Cells

Background: Low-dose naltrexone (LDN) is involved in the treatment of inflammatory and immune system diseases and can affect immune cells. Mesenchymal stem cells (MSCs) are known for their immunomodulatory effects and the potential for the treatment of certain types of autoimmune diseases.Objective: To investigate the long-term effects of LDN on human adipose-derived mesenchymal stem cells (ASCs) to see how their immunomodulatory properties are affected and also how LDN-treated ASCs interact with other immune cells present in peripheral blood mononuclear cells (PBMCs).Methods: After 14 days of treatment, the ability of LDN-treated ASCs to modulate PBMC proliferation in a two-way mixed lymphocyte reaction (MLR) model was assessed using XTT. The relative expression of IDO, PD-L1, COX-2, HGF genes, and the level of IL-6 and TGF-β cytokines were measured in IFN-γ stimulated and unstimulated ASCs (treated and not treated cells) using real-time PCR and ELISA respectively.Results: Unstimulated ASCs treated with 10-8 M Naltrexone (10-8 M NTX) showed higher levels of TGF-β, compared with the controls (P<0.05). Stimulated ASCs treated with 10-6 M NTX showed elevated expression of IDO, PD-L1 genes, and IL-6 level (P<0.05).Conclusion: Our results demonstrated that various LDN concentrations have dissimilar effects on ASCs’ immunomodulatory properties. A higher LDN concentration induced an alteration in the immunomodulatory features of ASCs

Kinetic simulation of flameless burners with methane/hydrogen blended fuel: Effects of molecular diffusion and Schmidt number

The newly developed concept of MILD combustion has paved the way through achievement of high thermal efficiencies with low levels of pollutants and greenhouse gases. High fidelity numerical models play key role in design and optimization of these burners. The present research aims to assess the effect of molecular diffusion and deviations in the amount of different species Schmidt number on the precision of the model. To this end, a previously investigated MILD burner is opted as case-study. From the results it is evident that in contrast to conventional combustion regimes problems, the impact of the often-neglected laminar diffusion is comparable to turbulent diffusion. On the other hand, consideration of molecular diffusion in the species transport equation significantly improves the model accuracy only if proper Schmidt number for species are considered. Suitable Sutherland coefficients and Schmidt numbers for each species are found based on relevant data in the literature and reported

Impaired immunomodulatory ability of type 2 diabetic adipose-derived mesenchymal stem cells in regulation of inflammatory condition in mixed leukocyte reaction

The immunomodulatory properties of type 2 diabetic patients’ adipose-derived mesenchymal stem cells (D-ASCs) has not been extensively studied. In this study, we compared the immunomodulatory properties of D-ASCs and non-diabetic subjects mesenchymal stem cells (ND-ASCs) in co-culture with mixed leukocyte reaction (MLR). ASCs were isolated from adipose tissue samples of type 2 diabetic and non-diabetic subjects (age: 40-55). D-ASCs and ND-ASCs were co-cultured with two-way MLR. Peri pheral blood mononuclear ce lls (PBMCs) proliferation ratio, protein levels of IFN- γ and IL-10, mRNA expression of COX-2 , TNF- α , TGF- β 1 and IL-6 genes in MLR, D-ASCs and ND-ASCs co-cultures were assessed using XTT, ELISA and Real-time qRT-PCR, respectively. PBMCs proliferation on days 2 and 4 of D-ASCs co-culture was higher than ND-ASCs co-culture of the same days ( p < 0.001). IFN- γ level decreased on day 4 compared to day 2 of ND-ASCs co-culture, but its level had not changed in D-ASCs co-culture. COX-2 expression on days 2 and 4 of D-ASCs co-culture was lower than ND- ASCs co-culture of the same days ( p < 0.05). The expression of TNF- α and IL-6 on days 2 and 4 of D-ASCs co- culture were higher than ND-ASCs co-culture of the same days ( p < 0.001). TGF- β 1 on day 4 of ND-ASCs co- culture showed a slightly higher expression than D-ASCs co-culture of the same day. Lower suppression of PBMCs proliferation, declined expre ssion of anti-inflammatory and upregulated expression of pro-inflammatory factors in D-ASCs co-culture, indicated an impairment of these cells in modulation of the inflammatory condition

The value of predictive instruments in the screening of acute stroke: an umbrella review on previous systematic reviews

Objective: Although various predictive instruments have been introduced for early stroke diagnosis, there is no consensus on their performance. Therefore, we decided to assess the value of predictive instruments in the detection of stroke by conducting an umbrella review. Method: A search was performed in the Medline, Embase, Scopus and Web of Science databases by the end of August 2021 for systematic reviews and meta-analyses. Original articles included in the systematic reviews were retrieved, summarized and pooled sensitivity, specificity and diagnostic odds ratio were calculated. The level of evidence was divided into five groups: convincing (class I), highly suggestive (class II), suggestive (class III), weak (class IV) and non-significant. Results: The value of 33 predictive instruments was evaluated. The sample size included in these scoring systems’ assessments varied between 182 and 47072 patients. The level of evidence was class I in one tool, class II in 18 tools, class III in 2 tools, class IV in 11 tools, and non-significant in one tool. Apart from Med PACS, which had a low diagnostic value, other tools appeared to be able to detect a stroke. The optimum performance for diagnosis of stroke was for ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS. Conclusion: Convincing to suggestive evidence shows that ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS have the optimum performance in identifying stroke. Since ROSIER’s calculation is simple and has the highest sensitivity and specificity among those predictive instruments, it is recommended for stroke diagnosis in pre-hospital and in-hospital settings

Association between SGLT2 (sodium-glucose cotransporter-2) inhibitors and bladder cancer in individuals with type 2 diabetes; a systematic review and meta-analysis

Introduction: Sodium-glucose cotransporter-2 (SGLT2) inhibitors are the most recent pharmaceutical group for type 2 diabetes (T2D) treatment. Evidence indicates contradictory relationships between sodium-glucose cotransporter-2 inhibitors and bladder cancer (BC). Hence, this study aims to investigate the relationship between SGLT2 inhibitors and BC in patients with T2D. Materials and Methods: This study is a systematic review and meta-analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). International databases including Cochrane, Web of Science, Scopus, PubMed, and Google Scholar were conducted for searching with keywords and without time and language limitations. The reference searching stage continued upgrading until November, 2022. Data analysis was performed with STATA 14 software. The tests with P values lower than 0.05 were considered statistically significant. Results: The four reviewed studies with a sample size comprising 497 755 individuals indicated the impact of SGLT2 inhibitors on BC of patients with T2D (OR: 0.68; 95% CI: 0.37, 1.2). The effect of dapagliflozin, canagliflozin and empagliflozin administration on the incidence of BC among the T2D patients were (OR: 0.72; 95% CI: 0.39, 1.30), (OR: 0.53; 95% CI: 0.23, 1.20), and (OR: 0.51; 95% CI: 0.20, 1.28), respectively. Conclusion: The general conclusion of this study revealed that SGLT2 inhibitors did not increase the risk of BC in T2D patients. The analysis of subgroups also indicated that the administration of dapagliflozin, canagliflozin, and empagliflozin also did not increase the risk of BC in T2D patients. Registration: This study has been compiled based on the PRISMA checklist, and its protocol was registered on the PROSPERO website (ID=CRD42023389014)

Effect of hydrogen enrichment on pollutant and greenhouse gases formation and exergy efficiency of methane MILD combustion

The present study aims to investigate the effect of hydrogen enrichment of the methane jet fuel on the formation of pollutants and greenhouse gases and exergy efficiency of a burner working on flameless MILD combustion mode for different amounts of oxygen present in the hot air co-flow stream using computational fluid dynamics coupled with detailed chemistry. OpenFOAM v. 3.0 is employed for the simulations. The results indicate considerable the pivotal role of the amount of hydrogen present in the fuel stream. It is also evident that hydrogen enrichment could be considered as a promising strategy for further increasing the exergy efficiency of burners working in MILD combustion mode

Low volume polyethylene glycol combined with senna versus high volume polyethylene glycol, which regimen is better for bowel preparation for colonoscopy? A randomized, controlled, and single‐blinded trial

Abstract Background and Aims Bowel preparation affects the quality of colonoscopy. Reaching the optimal preparation has been a challenge for years. Polyethylene glycol (PEG) is the sole FDA‐approved substance for this purpose. However, patients find it unpleasant and often complain about its adverse effects. In this study, we aimed to reduce these complaints by lowering the amount of PEG and adding senna which is an herbal stimulant laxative. Methods Four hundred and eighty‐six patients were admitted for colonoscopy. Finally, 382 patients were enrolled in the study and we divided them into two groups; 186 patients were placed in which conventional high volume PEG‐alone regimen was consumed and 196 patients in which low volume PEG plus senna regimen was offered. The quality of colon preparation was compared between the two groups by independent two samples t‐test (or its corresponding nonparametric test), Fisher's exact, or χ2 test in SPSS software version 22. Results The colon preparation quality was equally efficient in the two groups as 69.36% in the high volume PEG group and 71.94% in PEG plus senna group had adequate bowel preparation (p = 0.58). Adverse effects, like nausea, bloating, headache, and sleeplessness were significantly less in the low volume PEG plus senna group. Conclusion Besides the fact that bowel preparation by low volume PEG plus senna combination was noninferior to the conventional high volume PEG‐alone regimen, the side effects were much less common with the low volume PEG plus senna regimen