Tag: nevin manimala

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

Curr Eye Res. 2023 Apr 3:1-6. doi: 10.1080/02713683.2023.2192447. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate changes in corneal refractive parameters after implantation of a stromal lenticule of different thickness. We assume that the refractive outcome depends on the optical power of the used lenticule.

METHODS: We conducted an ex-vivo non-human study on 33 normotonic porcine eyeballs divided into two groups, for 4D and 8D human lenticule implantation. Corneal stromal lenticules were obtained as a by-product from a laser procedure ReLEx SMILE. We evaluated corneal refractive parameters measured on Oculus Pentacam© device before and immediately after the intrastromal lenticule implantation.

RESULTS: There was no statistically significant difference in corneal refractive parameters between the eyeball groups before lenticule implantation. In both groups, the intrastromal implantation in the depth of 300um led to a significant increase of central corneal pachymetry and corneal anterior steepening. In the 4D group the average central corneal pachymetry increased from 903 ± 124.59 to 1230 ± 148.99 (p = 0.0022) and in 8D group from 733.35 ± 69.60 to 1109 ± 161.64 (p = 0.0008). Induced changes in other studied parameters were not statistically significant, Kmax changed from 45.57 ± 2.78 to 72.07 ± 16.83 (p = 0.0094) and Km front from 40.72 ± 1.60 to 48.87 ± 5.83 (p = 0.0037) in 4D group and in the 8D group average Kmax increased from 42.22 ± 1.54 to 62.95 ± 12.67 (p = 0.0001) and K2 front 40.46 ± 1.64 to 51.51 ± 9.63 (p = 0.0037). There were no significant differences in refractive changes between the 4D and 8D groups after lenticule implantation.

CONCLUSION: Intrastromal corneal lenticule implantation induces changes in corneal refractive parameters. In both groups, the implantation induced a significant increase of an anterior corneal steepening without any significant influence on posterior corneal flattening. Corneal lenticule implantation did not lead to any significant change of corneal astigmatism. However, in order to have more precise data for future clinical applications we need to continue with the experiments and verify the results on human corneas.

PMID:37009857 | DOI:10.1080/02713683.2023.2192447

J Magn Reson Imaging. 2023 Apr 3. doi: 10.1002/jmri.28705. Online ahead of print.

ABSTRACT

BACKGROUND: Current studies have indicated that tumoral morphologic features are associated with cerebellar mutism syndrome (CMS), but the radiomics application in CMS is scarce.

PURPOSE: To develop a model for CMS discrimination based on multiparametric MRI radiomics in patients with posterior fossa tumors.

STUDY TYPE: Retrospective.

POPULATION: A total of 218 patients (males 132, females 86) with posterior fossa tumors, 169 of which were included in the MRI radiomics analysis. The MRI radiomics study cohort (169) was split into training (119) and testing (50) sets with a ratio of 7:3.

FIELD/SEQUENCE: All the MRI were acquired under 1.5/3.0 T scanners. T2-weighted image (T2W), T1-weighted (T1W), fluid attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI).

ASSESSMENT: Apparent diffusion coefficient (ADC) maps were generated from DWI. Each MRI dataset generated 1561 radiomics characteristics. Feature selection was performed with univariable logistic analysis, correlation analysis, and least absolute shrinkage and selection operator (LASSO) penalized logistic regression. Significant clinical features were selected with multivariable logistic analysis and used to constructed the clinical model. Radiomics models (based on T1W, T2W, FLAIR, DWI, ADC) were constructed with selected radiomics features. The mix model was based on the multiparametric MRI radiomics features.

STATISTICAL TEST: Multivariable logistic analysis was utilized during clinical features selection. Models’ performance was evaluated using the area under the receiver operating characteristic (AUC) curve. Interobserver variability was assessed using Cohen’s kappa. Significant threshold was set as P < 0.05.

RESULTS: Sex (aOR = 3.72), tumor location (aOR = 2.81), hydrocephalus (aOR = 2.14), and tumor texture (aOR = 5.08) were significant features in the multivariable analysis and were used to construct the clinical model (AUC = 0.79); totally, 33 radiomics features were selected to construct radiomics models (AUC = 0.63-0.93). Seven of the 33 radiomics features were selected for the mix model (AUC = 0.93).

DATA CONCLUSION: Multiparametric MRI radiomics may be better at predicting CMS than single-parameter MRI models and clinical model.

EVIDENCE LEVEL: 4.

TECHNICAL EFFICACY: 2.

PMID:37009777 | DOI:10.1002/jmri.28705

Curr Eye Res. 2023 Apr 3:1-9. doi: 10.1080/02713683.2023.2192896. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the correlation between lens density measured by IOL-Master 700 based on swept-source optical coherence tomography (SS-OCT) technology and the phacodynamic parameters of Centurion phacoemulsification in cataract surgery.

METHODS: This prospective study included 66 patients (83 eyes) with age-related cataracts. Using the Lens Opacities Classification System III (LOCS III), the lens nuclear color (NC), lens nuclear opalescence (NO), cortical (C), and posterior subcapsular (P) opacities were obtained. Six meridian orientations of IOL-Master 700 images were captured, and the lens and nuclear regions were analyzed using ImageJ to generate the average lens nucleus density (AND) and average lens density (ALD). Phacodynamic parameters were recorded. The correlation between lens density and the phacodynamic parameters was analyzed. According to the AND, patients were divided into four groups (soft, medium-hard, hard, and extremely hard nucleus), and the phacodynamic parameters were compared among groups.

RESULTS: The correlation between the AND obtained by LOCS III grading and SS-OCT-based cataract quantification system score (NC and NO) was statistically significant (r_NC = 0.795, r_NO=0.794, both p = .000). AND correlated significantly with cumulative dissipated energy (CDE, r = 0.545, p = .000), total ultrasound time (TUST, r = 0.354, p = .001), and total torsional ultrasound time (TTUT, r = 0.314, p = .004). Among the four groups divided by AND, the difference in CDE (P₁₃ = 0.002, P₁₄ < 0.001, P₂₄ = 0.002) was statistically significant.

CONCLUSION: AND measured by IOL-Master 700, SS-OCT correlated significantly with LOCS III classification and phacodynamic parameters of the Centurion system, especially with CDE, TUST, and TTUT. AND can be used as an indicator for quantitative evaluation and help inform the surgical plan.

PMID:37009774 | DOI:10.1080/02713683.2023.2192896

Immunotherapy. 2023 Apr 3. doi: 10.2217/imt-2022-0190. Online ahead of print.

ABSTRACT

There is a critical need for novel therapies to treat patients with advanced biliary tract cancer (BTC). This systematic review summarizes the evidence-based knowledge for the potential role of PD-1 and PD-L1 monoclonal antibodies in the treatment of patients with early-stage and advanced BTC. An Embase database search was conducted, identifying 15 eligible phase II/III clinical trials for review. Results from recent phase III trials show a statistically significant overall survival (OS) benefit from the addition of PD-1/PD-L1 inhibitors to chemotherapy in the first-line management of advanced BTC. Future research should concentrate on the discovery of biomarkers to identify patients who would benefit most from these therapies.

PMID:37009698 | DOI:10.2217/imt-2022-0190

Ann Hum Genet. 2023 Apr 3. doi: 10.1111/ahg.12506. Online ahead of print.

ABSTRACT

INTRODUCTION: Observational studies have shown that body mass index (BMI) and waist-to-hip ratio (WHR) are both inversely associated with lung function, as assessed by forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). However, observational data are susceptible to confounding and reverse causation.

METHODS: We selected genetic instruments based on their relevant large-scale genome-wide association studies. Summary statistics of lung function and asthma came from the UK Biobank and SpiroMeta Consortium meta-analysis (n = 400,102). After examining pleiotropy and removing outliers, we applied inverse-variance weighting to estimate the causal association of BMI and BMI-adjusted WHR (WHRadjBMI) with FVC, FEV1, FEV1/FVC, and asthma. Sensitivity analyses were performed using weighted median, MR-Egger, and MRlap methods.

RESULTS: We found that BMI was inversely associated with FVC (effect estimate, -0.167; 95% confidence interval (CI), -0.203 to -0.130) and FEV1 (effect estimate, -0.111; 95%CI, -0.149 to -0.074). Higher BMI was associated with higher FEV1/FVC (effect estimate, 0.079; 95%CI, 0.049 to 0.110) but was not significantly associated with asthma. WHRadjBMI was inversely associated with FVC (effect estimate, -0.132; 95%CI, -0.180 to -0.084) but has no significant association with FEV1. Higher WHR was associated with higher FEV1/FVC (effect estimate, 0.181; 95%CI, 0.130 to 0.232) and with increased risk of asthma (effect estimate, 0.027; 95%CI, 0.001 to 0.053).

CONCLUSION: We found significant evidence that increased BMI is suggested to be causally related to decreased FVC and FEV1, and increased BMI-adjusted WHR could lead to lower FVC value and higher risk of asthma. Higher BMI and BMI-adjusted WHR were suggested to be causally associated with higher FEV1/FVC.

PMID:37009668 | DOI:10.1111/ahg.12506

Analyst. 2023 Apr 3. doi: 10.1039/d2an02057b. Online ahead of print.

ABSTRACT

Early and accurate diagnosis of gastric cancer is vital for effective and targeted treatment. It is known that glycosylation profiles differ in the cancer tissue development process. This study aimed to profile the N-glycans in gastric cancer tissues to predict gastric cancer using machine learning algorithms. The (glyco-) proteins of formalin-fixed parafilm embedded (FFPE) gastric cancer and adjacent control tissues were extracted by chloroform/methanol extraction after the conventional deparaffinization step. The N-glycans were released and labeled with a 2-amino benzoic (2-AA) tag. The MALDI-MS analysis of the 2-AA labeled N-glycans was performed in negative ionization mode, and fifty-nine N-glycan structures were determined. The relative and analyte areas of the detected N-glycans were extracted from the obtained data. Statistical analyses identified significant expression levels of 14 different N-glycans in gastric cancer tissues. The data were separated based on the physical characteristics of N-glycans and used to test in machine-learning models. It was determined that the multilayer perceptron (MLP) was the most appropriate model with the highest sensitivity, specificity, accuracy, Matthews correlation coefficient, and f1 scores for each dataset. The highest accuracy score (96.0 ± 1.3) was obtained from the whole N-glycans relative area dataset, and the AUC value was determined as 0.98. It was concluded that gastric cancer tissues could be distinguished from adjacent control tissues with high accuracy using mass spectrometry-based N-glycomic data.

PMID:37009642 | DOI:10.1039/d2an02057b