Category: Nevin Manimala

Asian Pac J Cancer Prev. 2023 Jun 1;24(6):2083-2088. doi: 10.31557/APJCP.2023.24.6.2083.

ABSTRACT

PURPOSE: This study aimed to determine the difference between the level of sexual satisfaction in breast cancer patients with Modified Radical Mastectomy (MRM) and Breast Conserving Surgery (BCS).

METHODS: This study used a cross-sectional study using a validated Female Sexual Function Index questionnaire. This study was conducted from 2020 until 2021. Data were collected and analyzed using the chi-square test for bivariate variables and logistic regression for multivariate variables.

RESULTS: Patients with BCS were more satisfied with their sexual activity than patients undergoing modified radical mastectomy (p = 0.0001, OR 6.25, CI = 2.78 – 14.01). Other factors having effect on sexual satisfactions were: age that showed a statistically effect on sexual satisfaction (patients <55 years were more satisfied than patients ≥55 years ( p = 0.004, OR = 3.23, CI 1.44 – 7.22), the period after operation (<5 years vs >5 years) showed a statistically significant difference in sexual satisfaction ( p = 0.087, OR=0.53, CI = 0.25-1.10), Having chemotherapy treatment showed statistically significant risk for sexual satisfaction (p = 0.003, OR=7.39, CI= 1.62-33.83). Factors having no statistically significant effect on sexual satisfactions were: Radiotherapy treatment (p = 0.133, OR=1.75 and CI = 0.84 -3.64), length of marriage as defined with <10 years and > 10 years (p = 0.616, OR=1.39 and CI = 0.38-5.09), marital status (p = 0.082, OR =0.39, CI=0,13 – 1.16), educational status (p = 0.778, OR = 1.18, CI = 0.37 – 3.75), and work at home vs outside home (p = 0.117, OR=1.8, and CI = 0.86 – 3.78).

CONCLUSION: BCS as surgical therapy option is the most dominant factor related to sexual satisfaction followed by age group, and chemotherapy group.

PMID:37378939 | DOI:10.31557/APJCP.2023.24.6.2083

Asian Pac J Cancer Prev. 2023 Jun 1;24(6):2061-2072. doi: 10.31557/APJCP.2023.24.6.2061.

ABSTRACT

AIM: To examine computed tomography (CT) radiomic feature stability on various texture patterns during pre-processing utilizing the Credence Cartridge Radiomics (CCR) phantom textures.

MATERIALS AND METHODS: Imaging Biomarker Explorer (IBEX) expansion for the abbreviation IBEX extracted 51 radiomic features of 4 categories from 11 textures image regions of interest (ROI) of the phantom. 19 software pre-processing algorithms processed each CCR phantom ROI. All ROI texture processed image features were retrieved. Pre-processed CT image radiomic features were compared to non-processed features to measure its textural influence. Wilcoxon T-tests measured the pre-processing relevance of CT radiomic features on various textures. Hierarchical cluster analysis (HCA) was performed to cluster processer potency and texture impression likeness.

RESULTS: The pre-processing filter, CT texture Cartridge, and feature category affect the CCR phantom CT image’s radiomic properties. Pre-processing is statistically unaltered by Gray Level Run Length Matrix (GLRLM ) expansion for the abbreviation GLRLM and Neighborhood Intensity Difference matrix (NID) expansion for the abbreviation NID feature categories. The 30%, 40%, and 50% honeycomb are regular directional textures and smooth 3D-printed plaster resin, most of the image pre-processing feature alterations exhibited significant p-values in the histogram feature category. The Laplacian Filter, Log Filter, Resample, and Bit Depth Rescale Range pre-processing algorithms hugely influenced histogram and Gray Level Co-occurrence Matrix (GLCM) image features.

CONCLUSION: We found that homogenous intensity phantom inserts, CT radiomic feature, are less sensitive to feature swaps during pre-processing than normal directed honeycomb and regular projected smooth 3D-printed plaster resin CT image textures. Because they lose fewer information during image enhancement, This feature concentration empowerment of the images also enhances texture pattern recognition.

PMID:37378937 | DOI:10.31557/APJCP.2023.24.6.2061

Asian Pac J Cancer Prev. 2023 Jun 1;24(6):2055-2059. doi: 10.31557/APJCP.2023.24.6.2055.

ABSTRACT

BACKGROUND: MiR27a plays an important role in carcinogenesis, cell proliferation, apoptosis, invasion, migration and angiogenesis. Several studies have identified an important role of pre-miR27a (rs895819) A>G polymorphism in several types of cancer. This research aims to investigate the association of pre-miR27a (rs895819) A>G and breast cancer susceptibility, clinicopathological data and survival. Blood DNA samples of 143 Thai breast cancer patients and 100 healthy Thai women were studied for pre-miR27a (rs895819) A>G polymorphism using polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP).

RESULTS: The results revealed that the frequency of pre-miR27a (rs895819) A>G genotypes was not statistically significant different between breast cancer patient and normal control subjects. The rs895819 A>G genotype was significantly associated with clinicopathological parameter of grade III differentiation (P = 0.006), progesterone receptor (P = 0.011) and triple negative (P = 0.031) in breast cancer patients, but not with breast cancer susceptibility.

CONCLUSION: The pre-miR27a (rs895819) A>G genotype was significantly associated with poorly differentiated, progesterone receptor and triple-negative in breast cancer patients. Therefore, pre-miR27a (rs895819) A>G may be used as a biomarker for poor prognosis.

PMID:37378936 | DOI:10.31557/APJCP.2023.24.6.2055

Asian Pac J Cancer Prev. 2023 Jun 1;24(6):2043-2053. doi: 10.31557/APJCP.2023.24.6.2043.

ABSTRACT

OBJECTIVE: Patients with triple-negative breast cancer (TNBC) frequently develop resistance to chemotherapy. Studies have shown that microRNAs (miRNAs) are often aberrantly expressed in TNBC and are associated with drug resistance. However, a prognostic strategy that correlates miRNAs with chemotherapy resistance remains largely unknown.

METHODS: To identify breast cancer chemoresistance-associated miRNAs, the miRNA microarray dataset GSE71142 was downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE-miRNAs) in chemoresistant groups were identified using the LIMMA package in R. Potential target genes were predicted using the miRTarBase 9. Functional and pathway enrichment analyses was done using WebGestalt. A protein-protein interaction network was visualized using Cytoscape software. The top six hub genes regulated by DE-miRNAs were identified using the random forest model. The chemotherapy resistance index (CRI) in TNBC was defined as sum of the median expression levels of the top six hub genes. The association of CRI with distant relapse risk was evaluated using point-biserial correlation coefficient in the validation cohorts of patients with TNBC. The correlation between CRI and cumulative hazard rate was estimated using the Cox model, and the predicted rate of distant relapse was obtained from the Breslow-type estimator of the survival function. All statistical computations were performed using Origin2019b.

RESULTS: A total of 12 DE-miRNAs were screened, including six upregulated and six downregulated miRNAs in chemoresistant breast cancer tissues compared with chemosensitive tissues. Based on fold changes, miR-214-3p, miR-4758-3p, miR-200c-3p, miR-4254, miR-140-3p, and miR-24-3p were the top six most upregulated miRNAs, whereas miR-142-5p, miR-146-5p, miR-1268b, miR-1275, miR-4447, and miR-4472 were the top six most downregulated miRNAs. The top three hub genes for upregulated miRNAs were RAC1, MYC, and CCND1 and for downregulated miRNAs were IL-6, SOCS1, and PDGFRA. CRI was significantly associated with the risk of distant relapse.

CONCLUSION: CRI predicted survival benefits with reduced hazard rate.

PMID:37378935 | DOI:10.31557/APJCP.2023.24.6.2043

Stroke. 2023 Jun 28. doi: 10.1161/STROKEAHA.123.043547. Online ahead of print.

ABSTRACT

BACKGROUND: We aimed to investigate whether socioeconomic status (SES) was associated with functional outcome in patients with ischemic stroke treated with reperfusion therapy (intravenous thrombolysis and/or thrombectomy).

METHODS: This nationwide cohort study included reperfusion-treated patients with ischemic stroke ≥18 years registered in the Danish Stroke Registry between 2015 and 2018. Functional outcome was determined by the modified Rankin Scale score 90 days after stroke. SES was defined by educational attainment, family income, and employment status before stroke. SES data were available from Statistics Denmark and linked on the individual level with data from the Danish Stroke Registry. Uni- and multivariable ordinal logistic regression was performed for each socioeconomic parameter individually (education, income, and employment) to estimate the common odds ratios (cORs) for lower 90-day modified Rankin Scale scores.

RESULTS: A total of 5666 patients were included. Mean age was 68.7 years (95% CI, 68.3-69.0), and 38.4% were female. Low SES was associated with lower odds for achieving lower 90-day modified Rankin Scale score: Low versus high education, cOR, 0.69 (95% CI, 0.61-0.79), low versus high income, cOR, 0.59 (95% CI, 0.53-0.67), and unemployed versus employed, cOR, 0.70 (95% CI, 0.58-0.83). Inequalities were reduced after adjusting for age, sex, and immigrant status, except for unemployed versus employed patients, adjusted cOR, 0.66 (95% CI, 0.54-0.80). No statistically significant differences remained after adjusting for potentially mediating variables (eg, stroke severity, prestroke modified Rankin Scale, and smoking).

CONCLUSIONS: Socioeconomic inequalities were observed in functional outcome after reperfusion treated ischemic stroke. In particular, prestroke unemployment was negatively associated with good functional outcome. A more adverse prognostic profile among patients with low SES appeared to explain the majority of these inequalities.

PMID:37377030 | DOI:10.1161/STROKEAHA.123.043547

Acta Orthop. 2023 Jun 27;94:300-306. doi: 10.2340/17453674.2023.12359.

ABSTRACT

BACKGROUND AND PURPOSE: Mesenchymal stem cells (MSCs), both endogenous and exogenous, enhance chondrocyte proliferation by stimulating collagen type II. Secretome, an MSC derivate, has shown to also provide this mechanism through a paracrine effect. We aimed to evaluate the use of secretome and MSC in the management of early osteoarthritis (OA).

ANIMALS AND METHODS: 19 (1 control) male sheep (Ovies aries), which were operated on with total lateral meniscectomy to induce knee OA, were divided into 3 groups: the secretome group, hyaluronic acid group, and MSC group. Each group was injected with the respective substances and was evaluated macroscopically and microscopically. The Osteoarthritis Research Society International (OARSI) score was calculated for all subjects and a descriptive and comparative statistical analysis was undertaken.

RESULTS: The macroscopic analysis of the treated groups revealed better OARSI score in the secretome group compared with the other 2 groups. The secretome group showed a significantly better microscopic score compared with the hyaluronic acid group (mean difference [MD] 6.0, 95% confidence interval [CI] 0.15-12), but no significant difference compared with the MSC group (MD 1.0, CI -4.8 to 6.8).

CONCLUSION: Intra-articular injection of secretome is effective in managing early-stage osteoarthritis in the animal model compared with hyaluronic acid and has similar efficacy to MSC injection.

PMID:37377012 | DOI:10.2340/17453674.2023.12359

Phys Chem Chem Phys. 2023 Jun 28. doi: 10.1039/d3cp01428b. Online ahead of print.

ABSTRACT

In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds. Thus, the difference between n-octanol/water and toluene/water partition coefficients has proven to be a valuable descriptor to study the propensity of molecules to form intramolecular hydrogen bonds and exhibit chameleon-like properties that modulate solubility and permeability. In this context, this study reports the experimental toluene/water partition coefficients (log P_tol/w) for a series of 16 drugs that were selected as an external test set in the framework of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind challenge. This external set has been used by the computational community to calibrate their methods in the current edition (SAMPL9) of this contest. Furthermore, the study also investigates the performance of two computational strategies for the prediction of log P_tol/w. The first relies on the development of two machine learning (ML) models, which are built up by combining the selection of 11 molecular descriptors in conjunction with either the multiple linear regression (MLR) or the random forest regression (RFR) model to target a dataset of 252 experimental log P_tol/w values. The second consists of the parametrization of the IEF-PCM/MST continuum solvation model from B3LYP/6-31G(d) calculations to predict the solvation free energies of 163 compounds in toluene and benzene. The performance of the ML and IEF-PCM/MST models has been calibrated against external test sets, including the compounds that define the SAMPL9 log P_tol/w challenge. The results are used to discuss the merits and weaknesses of the two computational approaches.

PMID:37376995 | DOI:10.1039/d3cp01428b

Physiol Meas. 2023 Jun 27. doi: 10.1088/1361-6579/ace241. Online ahead of print.

ABSTRACT

Acute myocardial ischemia in the setting of acute coronary syndrome (ACS) may lead to myocardial infarction. Therefore, timely decisions, already in the pre-hospital phase, are crucial to preserving cardiac function as much as possible. Serial electrocardiography, a comparison of the acute electrocardiogram (AECG) with a previously recorded (reference) ECG (RECG) of the same patient, aids in identifying ischemia-induced electrocardiographic changes by correcting for interindividual ECG variability. Recently, the combination of deep learning and serial electrocardiography provided promising results in detecting emerging cardiac diseases; thus, the aim of our current study is the application of our novel Advanced Repeated Structuring & Learning Procedure (AdvRS&LP), specifically designed for acute myocardial ischemia detection in the pre-hospital phase by using serial ECG features. Data belong to the SUBTRACT study, which includes 1425 ECG pairs, 194 (14%) ACS patients, and 1035 (73%) controls. Each ECG pair was characterized by 28 serial features that, with sex and age, constituted the inputs of the Advanced Repeated Structuring & Learning Procedure (AdvRS&LP), an automatic constructive procedure for creating supervised neural networks (NN). We created 100 NNs to compensate for statistical fluctuations due to random data divisions of a limited dataset. We compared the performance of the obtained NNs to a logistic regression (LR) procedure and the Glasgow program (Uni-G) in terms of area-under-the-curve (AUC) of the receiver-operating-characteristic (ROC) curve, sensitivity (SE), and specificity (SP). NNs (median AUC=83%, median SE=77%, and median SP=89%) presented statistically (P value lower than 0.05) higher testing performance than those presented by LR (median AUC=80%, median SE=67%, and median SP=81%) and by Uni-G algorithm (median SE=72% and median SP=82%). In conclusion, the positive results underscore the value of serial comparison of ECG in ischemia detection and, NNs created by AdvRS&LP seems to be considered as realible tools in terms of generalization and clinical applicability.

PMID:37376978 | DOI:10.1088/1361-6579/ace241

Chin Med Sci J. 2023 Jun 28. doi: 10.24920/004214. Online ahead of print.

ABSTRACT

Objective This study aimed to analyze the medication rules of traditional Chinese medicine (TCM) for malaria treatment. Methods Statistical analysis was conducted on the basic attributes of TCM drugs with regard to property, therapeutic methods, flavor, and meridian tropism. A complex network of TCM drug associations was constructed. Cluster analysis was applied to obtain the core drugs for malaria treatment. The Apriori algorithm was applied to analyze the association rules of these core drugs. Results A total of 357 herbs were used 3,194 times in 461 prescriptions for malaria treatment. Radix Glycyrrhizae (), Rhizoma Pinelliae (), Radix Bupleuri (), and Radix Dichroae () were the frequently used herbs through supplementing, exterior-releasing, heat-clearing, qi-rectifying, and damp-resolving therapeutic methods. Such herbs had warm, natural, and cold herbal properties; pungent, bitter, and sweet flavor; and spleen, lung, and stomach meridian tropism. Cluster analysis showed 61 core drugs, including Radix Glycyrrhizae, Rhizoma Pinelliae, Radix Bupleuri, and Radix Scutellariae (). Apriori association rule analysis yielded 12 binomial rules (herb pairs) and six trinomial rules (herb combinations). Radix Bupleuri plus Radix Scutellariae was the core herbal pair for treating malaria. This pair could be combined with Rhizoma Atractylodis Macrocephalae () for treating warm or cold malaria, combined with Pericarpium Citri Reticulatae () or Radix Dichroae () for treating miasmic malaria, or combined with turtle shells () for treating malaria with splenomegaly. Conclusions TCM can be used to classify and treat malaria in accordance with the different stages of development. As the core herbal pair, Radix Bupleuri plus Radix Scutellariae can be combined with other drugs to treat malaria with different syndrome types.

PMID:37376890 | DOI:10.24920/004214

Stat Methods Med Res. 2023 Jun 28:9622802231181231. doi: 10.1177/09622802231181231. Online ahead of print.

ABSTRACT

Coronary artery disease is one of the most common types of cardiovascular disease. Death from coronary heart disease is influenced by genetic factors in both women and men. In this article, we propose a novel Bayesian variable selection framework for the identification of important genetic variants associated with coronary artery disease disease status. Instead of treating each feature independently as in conventional Bayesian variable selection methods, we propose an innovative prior for the inclusion probabilities of genetic variants that accounts for their ordering structure. We assume that neighboring variants are more likely to be selected together as they tend to be highly correlated and have similar biological functions. Additionally, we propose to group participating subjects based on underlying population structure and fit separate regressions, so that the regression coefficients can better reflect different disease risks in different population groups. Our approach borrows strength across regression models through an innovative prior inspired by the Markov random fields. The proposed framework can improve variable selection and prediction performances as demonstrated in the simulation studies. We also apply the proposed framework to the CATHeterization GENetics data with binary Coronary artery disease disease status.

PMID:37376889 | DOI:10.1177/09622802231181231