Tag: statistics

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

Int J Adolesc Med Health. 2023 Jun 29. doi: 10.1515/ijamh-2022-0070. Online ahead of print.

ABSTRACT

OBJECTIVES: The present study was designed to determine the effect of education based on health belief model (HBM) on high-risk health behaviors in youth.

METHODS: This interventional quasi-experimental study was conducted in 2020-2021 with the participation of 62 students living in the dormitories of University of Mashhad Medical Sciences with available sampling and random allocation in two experimental and control groups. The experimental group received six training sessions. The research instruments included: demographic information, researcher-made questionnaire including HBM constructs, youth high-risk behaviors questionnaire (2019) that were used before, immediately and one month after the educations. The collected data were analyzed using t-test, Mann-Whitney, and ANOVA with SPSS 21.

RESULTS: The mean scores in the field of high-risk behaviors as well as all constructs of HBM were not statistically significant in the two groups before the intervention (p>0.05), but the mean scores immediately and one month after the educational intervention in all constructs of the HBM and the range of high-risk behaviors (other than smoking behavior) in the experimental group compared to the control group was statistically significant (p<0.001).

CONCLUSIONS: Education based on HBM was effective in reducing high-risk health behaviors, so this educational model can be used to reduce high-risk health behaviors in female students.

PMID:37376886 | DOI:10.1515/ijamh-2022-0070

Analyst. 2023 Jun 28. doi: 10.1039/d3an00545c. Online ahead of print.

ABSTRACT

Ion mobility spectrometry (IMS), which can be employed as either a stand-alone instrument or coupled to mass spectrometry, has become an important tool for analytical chemistry. Because of the direct relation between an ion’s mobility and its structure, which is intrinsically related to its collision cross section (CCS), IMS techniques can be used in tandem with computational tools to elucidate ion geometric structure. Here, we present MobCal-MPI 2.0, a software package that demonstrates excellent accuracy (RMSE 2.16%) and efficiency in calculating low-field CCSs via the trajectory method (≤30 minutes on 8 cores for ions with ≤70 atoms). MobCal-MPI 2.0 expands on its predecessor by enabling the calculation of high-field mobilities through the implementation of the 2^nd order approximation to two-temperature theory (2TT). By further introducing an empirical correction to account for deviations between 2TT and experiment, MobCal-MPI 2.0 can compute accurate high-field mobilities that exhibit a mean deviation of <4% from experimentally measured values. Moreover, the velocities used to sample ion-neutral collisions were updated from a weighted to a linear grid, enabling the near-instantaneous evaluation of mobility/CCS at any effective temperature from a single set of N₂ scattering trajectories. Several enhancements made to the code are also discussed, including updates to the statistical analysis of collision event sampling and benchmarking of overall performance.

PMID:37376881 | DOI:10.1039/d3an00545c

Arch Med Sadowej Kryminol. 2021;71(1-2):38-46. doi: 10.5114/amsik.2021.106014.

ABSTRACT

AIM: The study aimed to examine whether volatile substances (ethanol, isopropanol, and acetone) can be detected in costal cartilage and also if concentrations of detected substances reliably reflect their concentrations in the peripheral blood – the standard forensic material for toxicological analyses. Such knowledge can be useful in cases when a cadaver’s blood is unavailable or contaminated.

MATERIAL AND METHODS: Ethanol, isopropanol, and acetone concentrations were determined in samples of unground costal cartilage (UCC), ground costal cartilage (GCC), femoral venous blood, and urine. The samples were analysed by gas chromatography (GC) with a flame ionization detector using headspace analysis.

RESULTS: Volatile substances were detected in 12 out of 100 analysed samples. There was a strong positive correlation between ethanol concentration in the blood and urine (r = 0.899, p < 0.001), UCC (r = 0.809, p < 0.01), and GCC (r = 0.749, p < 0.01). A similar strong correlation was found for isopropanol concentration in the blood and urine (r = 0.979, p < 0.001), UCC (r = 0.866, p < 0.001), and GCC (r = 0.942, p < 0.001). Acetone concentration in the blood strongly correlated only with its concentration in urine (r = 0.960, p < 0.001).

CONCLUSIONS: We demonstrated for the first time the possibility of detecting volatile substances: ethanol, isopropanol and acetone in a human costal cartilage. Also, the study showed that higher volatiles concentrations were better determined in ground samples.

PMID:37376862 | DOI:10.5114/amsik.2021.106014