Infection. 2023 Apr 3. doi: 10.1007/s15010-023-02015-w. Online ahead of print.
NO ABSTRACT
PMID:37010806 | DOI:10.1007/s15010-023-02015-w
Tag: nevin manimala
Qual Life Res. 2023 Apr 3. doi: 10.1007/s11136-023-03398-x. Online ahead of print.
ABSTRACT
PURPOSE: To estimate the health-related quality of life (HRQOL) according to glycemic status, and its relationship with sociodemographic and clinical factors in a population at risk of developing type 2 diabetes (T2D).
METHODS: Cross-sectional study, using cluster sampling. Data were collected from 1135 participants over 30 years of age, at risk of developing T2D from the PREDICOL project. Participants’ glycemic status was defined using an oral glucose tolerance test (OGTT). Participants were divided into normoglycemic subjects (NGT), prediabetes and diabetics do not know they have diabetes (UT2D). HRQOL was assessed using the EQ-5D-3L questionnaire of the EuroQol group. Logistic regression and Tobit models were used to examine factors associated with EQ-5D scores for each glycemic group.
RESULTS: The mean age of participants was 55.6 ± 12.1 years, 76.4% were female, and one in four participants had prediabetes or unknown diabetes. Participants reported problems most frequently on the dimensions of Pain/Discomfort and Anxiety/Depression in the different glycemic groups. The mean EQ-5D score in NGT was 0.80 (95% CI 0.79-0.81), in prediabetes, 0.81 (95% CI 0.79-0.83), and in participants with UT2D of 0.79 (95% CI 0.76-0.82), respectively. Female sex, older age, city of residence, lower education, receiving treatment for hypertension, and marital status were significantly associated with lower levels of HRQOL in the Tobit regression analysis.
CONCLUSIONS: HRQOL of NGT, prediabetes, and UT2D participants was statistically similar. However, factors such as gender, age. and place of residence were found to be significant predictors of HRQOL for each glycemic group.
PMID:37010804 | DOI:10.1007/s11136-023-03398-x
J Am Geriatr Soc. 2023 Apr 3. doi: 10.1111/jgs.18357. Online ahead of print.
ABSTRACT
BACKGROUND: Relatively little is known about how distressing symptoms change among older persons in the setting of major surgery. Our objective was to evaluate changes in distressing symptoms after major surgery and determine whether these changes differ according to the timing of surgery (nonelective vs. elective), sex, multimorbidity, and socioeconomic disadvantage.
METHODS: From a prospective longitudinal study of 754 nondisabled community-living persons, 70 years of age or older, 368 admissions for major surgery were identified from 274 participants who were discharged from the hospital from March 1998 to December 2017. The occurrence of 15 distressing symptoms was ascertained in the month before and 6 months after major surgery. Multimorbidity was defined as more than two chronic conditions. Socioeconomic disadvantage was assessed at the individual level, based on Medicaid eligibility, and neighborhood level, based on an area deprivation index (ADI) score above the 80th state percentile.
RESULTS: In the month before major surgery, the occurrence and mean number of distressing symptoms were 19.6% and 0.75, respectively. In multivariable analyses, the rate ratios, denoting proportional increases in the 6 months after major surgery relative to presurgery values, were 2.56 (95% confidence interval [CI], 1.91-3.44) and 2.90 (95% CI, 2.01-4.18) for the occurrence and number of distressing symptoms, respectively. The corresponding values were 3.54 (95% CI, 2.06-6.08) and 4.51 for nonelective surgery (95% CI, 2.32-8.76) and 2.12 (95% CI, 1.53-2.92) and 2.20 (95% CI, 1.48-3.29) for elective surgery; p-values for interaction were 0.030 and 0.009. None of the other subgroup differences were statistically significant, although men had a greater proportional increase in the occurrence and number of distressing symptoms than women.
CONCLUSIONS: Among community-living older persons, the burden of distressing symptoms increases substantially after major surgery, especially in those having nonelective procedures. Reducing symptom burden has the potential to improve quality of life and enhance functional outcomes after major surgery.
PMID:37010784 | DOI:10.1111/jgs.18357
Appl Biochem Biotechnol. 2023 Apr 3. doi: 10.1007/s12010-023-04433-w. Online ahead of print.
ABSTRACT
The unexpected rise in cancer and diabetes statistics has been a significant global threat, inciting ongoing research into various biomarkers that can act as innovative therapeutic targets for their management. The recent discovery of how EZH2-PPARs’ regulatory function affects the metabolic and signalling pathways contributing to this disease has posed a significant breakthrough, with the synergistic combination of inhibitors like GSK-126 and bezafibrate for treating these diseases. Nonetheless, no findings on other protein biomarkers involved in the associated side effects have been reported. As a result of this virtual study, we identified the gene-disease association, protein interaction networks between EZH2-PPARs and other protein biomarkers regulating pancreatic cancer and diabetes pathology, ADME/Toxicity profiling, docking simulation and density functional theory of some natural products. The results indicated a correlation between obesity and hypertensive disease for the investigated biomarkers. At the same time, the predicted protein network validates the link to cancer and diabetes, and nine natural products were screened to have versatile binding capacity against the targets. Among all natural products, phytocassane A outperforms the standard drugs’ (GSK-126 and bezafibrate) in silico validation for drug-likeness profiles. Hence, these natural products were conclusively proposed for additional experimental screening to complement the results on their utility in drug development for diabetes and cancer therapy against the EZH2-PPARs’ new target.
PMID:37010741 | DOI:10.1007/s12010-023-04433-w
Int Urol Nephrol. 2023 Apr 3. doi: 10.1007/s11255-023-03576-3. Online ahead of print.
ABSTRACT
OBJECTIVES: To investigate the relationship between the number of valvular insufficiency (VI) and emergency hospitalization or mortality in maintenance hemodialysis (HD) patients.
METHODS: The maintenance HD patients with cardiac ultrasonography were included. According to the number of VI ≥ 2 or not, the patients were divided into two groups. The difference of emergency hospitalized for acute heart failure, arrhythmia, acute coronary syndrome (ACS) or stroke, cardiovascular mortality, and all-cause mortality between the two groups were compared.
RESULTS: Among 217 maintenance HD patients, 81.57% had VI. 121 (55.76%) patients had two or more VI, and 96 (44.24%) with one VI or not. The study subjects were followed up for a median of 47 (3-107) months. At the end of the follow up, 95 patients died (43.78%), of whom 47 (21.66%) patients died because of cardiovascular disease. Age (HR 1.033, 95% CI 1.007-1.061, P = 0.013), number of VI ≥ 2 (HR 2.035, 95% CI 1.083-3.821, P = 0.027) and albumin (HR 0.935, 95% CI 0.881-0.992, P = 0.027) were independent risk factors for cardiovascular mortality. The three parameters were also independent risk factors for all-cause mortality. The patients with number of VI ≥ 2 were more likely to be emergency hospitalized for acute heart failure (56 [46.28%] vs 11 [11.46%], P = 0.001). On the contrary, the number of VI was not associated with emergency hospitalized for arrhythmia, ACS or stroke. Survival analysis results showed that probability of survival was statistically different in the two groups (P < 0.05), no matter based on cardiovascular mortality or all-cause mortality. Based on age, number of VI ≥ 2 and albumin, nomogram models for 5-year cardiovascular and all-cause mortality were built.
CONCLUSIONS: In maintenance HD patients, the prevalence of VI is prominently high. The number of VI ≥ 2 is associated with emergency hospitalized for acute heart failure, cardiovascular and all-cause mortality. Combining age, number of VI ≥ 2, and albumin can predict cardiovascular and all-cause mortality.
PMID:37010736 | DOI:10.1007/s11255-023-03576-3
Front Med. 2023 Apr 3. doi: 10.1007/s11684-022-0946-x. Online ahead of print.
ABSTRACT
Anaplastic lymphoma kinase (ALK) is the most common fusion gene involved in non-small cell lung cancer (NSCLC), and remarkable response has been achieved with the use of ALK tyrosine kinase inhibitors (ALK-TKIs). However, the clinical efficacy is highly variable. Pre-existing intratumoral heterogeneity (ITH) has been proven to contribute to the poor treatment response and the resistance to targeted therapies. In this work, we investigated whether the variant allele frequencies (VAFs) of ALK fusions can help assess ITH and predict targeted therapy efficacy. Through the application of next-generation sequencing (NGS), 7.2% (326/4548) of patients were detected to be ALK positive. On the basis of the adjusted VAF (adjVAF, VAF normalization for tumor purity) of four different threshold values (adjVAF < 50%, 40%, 30%, or 20%), the association of ALK subclonality with crizotinib efficacy was assessed. Nonetheless, no statistical association was observed between median progression-free survival (PFS) and ALK subclonality assessed by adjVAF, and a poor correlation of adjVAF with PFS was found among the 85 patients who received first-line crizotinib. Results suggest that the ALK VAF determined by hybrid capture-based NGS is probably unreliable for ITH assessment and targeted therapy efficacy prediction in NSCLC.
PMID:37010729 | DOI:10.1007/s11684-022-0946-x
Biol Trace Elem Res. 2023 Apr 3. doi: 10.1007/s12011-023-03646-8. Online ahead of print.
ABSTRACT
Normalization of the quantitative real-time PCR (RT-qPCR) data to the stably expressed reference genes is critically important for obtaining reliable results. However, all previous studies focused on F– toxicity for brain tissues used a single, non-validated reference gene, what might be a cause of contradictory or false results. The present study was designed to analyze the expression of a series of reference genes to select optimal ones for RT-qPCR analysis in cortex and hippocampus of rats chronically exposed to excessive fluoride (F–) amounts. Six-week-old male Wistar rats randomly assigned to four groups consumed regular tap water with 0.4 (control), 5, 20, and 50 ppm F– (NaF) for 12 months. The expression of six genes (Gapdh, Pgk1, Eef1a1, Ppia, Tbp, Helz) was compared by RT-qPCR in brain tissues from control and F–-exposed animals. The stability of candidate reference genes was evaluated by coefficient of variation (CV) analysis and RefFinder online program summarizing the results of four well-acknowledged statistical methods (Delta-Ct, BestKeeper, NormFinder, and GeNorm). In spite of some discrepancies in gene ranking between these algorisms, Pgk1, Eef1a1, and Ppia were found to be most valid in cortex, while Ppia, Eef1a1, and Helz showed the greatest expression stability in hippocampus. Tbp and Helz were identified as the least stable genes in cortex, whereas Gapdh and Tbp are unsuitable for hippocampus. These data indicate that reliable mRNA quantification in the cortex and hippocampus of F–-poisoned rats is possible using normalization to geometric mean of Pgk1+Eef1a1 or Ppia+Eef1a1 expression, respectively.
PMID:37010724 | DOI:10.1007/s12011-023-03646-8
J Med Syst. 2023 Apr 3;47(1):46. doi: 10.1007/s10916-023-01930-7.
ABSTRACT
Virtual reality is an effective system to train balance and gait in Parkinson’s disease, but attrition of this intervention needs to be further examined. This study aims to review and meta-analyze the dropouts of participants in randomized clinical trials that used virtual reality for balance and gait training in people with Parkinson’s disease. An electronic search was conducted in PubMed, Web of Science, Scopus and CINAHL. The PEDro scale and Revised Cochrane risk-of-bias tool for randomized trials 2.0 were employed to assess methodological quality. Proportions meta-analysis calculated dropout rate. Odds ratio meta-analysis under 1 indicated lower attrition in experimental participants. Meta-regression identified possible dropouts’ moderators. A total of 18 studies were included. The pooled dropout rates were 5.6% (95% CI, 3.3%-9.3%) for all groups, 5.33% (95% CI, 3.03%-9.21%) in virtual reality, and 6.60% (95% CI, 3.84%-26.31%) in comparators. No statistical differences were found in the dropout occurred between the groups (OR 0.83; 95% CI, 0.62-1.12). Number of weeks was the unique moderator (coefficient 0.129, 95% CI 0.018- 0.239; p=0.02). Our overall pooled dropout should be considered in the sample size calculation of future studies. Adequate follow-up of the CONSORT guidelines in the loss report and their reasons could help design suitable retention strategies.
PMID:37010723 | DOI:10.1007/s10916-023-01930-7
Inflammopharmacology. 2023 Apr 3. doi: 10.1007/s10787-023-01198-w. Online ahead of print.
ABSTRACT
Diosmin is a flavonoid with promising anti-inflammatory and antioxidant properties. However, it has difficult physicochemical characteristics since its solubility demands a pH level of 12, which has an impact on the drug’s bioavailability. The aim of this work is the development and characterization of diosmin nanocrystals using anti-solvent precipitation technique to be used for topical treatment of psoriasis. Results revealed that diosmin nanocrystals stabilized with hydroxypropyl methylcellulose (HPMC E15) in ratio (diosmin:polymer; 1:1) reached the desired particle size (276.9 ± 16.49 nm); provided promising colloidal properties and possessed high drug release profile. Additionally, in-vivo assessment was carried out to evaluate and compare the activities of diosmin nanocrystal gel using three different doses and diosmin powder gel in alleviating imiquimod-induced psoriasis in rats and investigating their possible anti-inflammatory mechanisms. Herein, 125 mg of 5% imiquimod cream (IMQ) was applied topically for 5 consecutive days on the shaved backs of rats to induce psoriasis. Diosmin nanocrystal gel especially in the highest dose used offered the best anti-inflammatory effect. This was confirmed by causing the most statistically significant reduction in the psoriasis area severity index (PASI) score and the serum inflammatory cytokines levels. Furthermore, it was capable of maintaining the balance between T helper (Th17) and T regulatory (Treg) cells. Moreover, it tackled TLR7/8/NF-κB, miRNA-31, AKT/mTOR/P70S6K and elevated the TNFAIP3/A20 (a negative regulator of NF-κB) expression in psoriatic skin tissues. This highlights the role of diosmin nanocrystal gel in tackling imiquimod-induced psoriasis in rats, and thus it could be a novel promising therapy for psoriasis.
PMID:37010718 | DOI:10.1007/s10787-023-01198-w
Med Biol Eng Comput. 2023 Apr 3. doi: 10.1007/s11517-023-02802-5. Online ahead of print.
ABSTRACT
Noise and artifacts affect strongly the quality of the electrocardiogram (ECG) in long-term ECG monitoring (LTM), making some of its parts impractical for diagnosis. The clinical severity of noise defines a qualitative quality score according to the manner clinicians make the interpretation of the ECG, in contrast to assess noise from a quantitative standpoint. So clinical noise refers to a scale of different levels of qualitative severity of noise which aims at elucidating which ECG fragments are valid to achieve diagnosis from a clinical point of view, unlike the traditional approach, which assesses noise in terms of quantitative severity. This work proposes the use of machine learning (ML) techniques to categorize different qualitative noise severity using a database annotated according to a clinical noise taxonomy as gold standard. A comparative study is carried out using five representative ML methods, namely, K neareast neighbors, decision trees, support vector machine, single-layer perceptron, and random forest. The models are fed by signal quality indexes characterizing the waveform in time and frequency domains, as well as from a statistical viewpoint, to distinguish between clinically valid ECG segments from invalid ones. A solid methodology to prevent overfitting to both the dataset and the patient is developed, taking into account balance of classes, patient separation, and patient rotation in the test set. All the proposed learning systems have demonstrated good classification performance, attaining a recall, precision, and F1 score up to 0.78, 0.80, and 0.77, respectively, in the test set by a single-layer perceptron approach. These systems provide a classification solution for assessing the clinical quality of the ECG taken from LTM recordings. Graphical Abstract Clinical Noise Severity Classification based on Machine Learning techniques towards Long-Term ECG Monitoring.
PMID:37010711 | DOI:10.1007/s11517-023-02802-5