Tag: nevin manimala

iScience. 2023 Sep 22;26(10):108007. doi: 10.1016/j.isci.2023.108007. eCollection 2023 Oct 20.

ABSTRACT

The vascular system is a multi-scale network whose functionality depends on its structure, and for which structural alterations can be linked to pathological shifts. Though biologists use multiple 3D imaging techniques to visualize vascular networks, the 3D image processing methodologies remain sources of biases, and the extraction of quantitative morphometric descriptors remains flawed. The article, first, reviews the current 3D image processing methodologies, and morphometric descriptors of vascular network images mainly obtained by light-sheet microscopy on optically cleared organs, found in the literature. Second, it proposes operator-independent segmentation and skeletonization methodologies using the freeware ImageJ. Third, it gives more extractable network-level (density, connectivity, fractal dimension) and segment-level (length, diameter, tortuosity) 3D morphometric descriptors and how to statistically analyze them. Thus, it can serve as a guideline for biologists using 3D imaging techniques of vascular networks, allowing the production of more comparable studies in the future.

PMID:37810224 | PMC:PMC10551892 | DOI:10.1016/j.isci.2023.108007

iScience. 2023 Sep 15;26(10):107934. doi: 10.1016/j.isci.2023.107934. eCollection 2023 Oct 20.

ABSTRACT

Ovarian cancer is the deadliest gynecologic malignancy in women, with a 46% five-year overall survival rate. The objective of the study was to investigate the effects of non-homologous end-joining (NHEJ) genes on clinical outcomes of ovarian cancer patients. To determine if these genes act as prognostic biomarkers of mortality and disease progression, the expression profiles of 48 NHEJ-associated genes were analyzed using an array of statistical and machine learning techniques: logistic regression models, decision trees, naive-Bayes, two sample t-tests, support vector machines, hierarchical clustering, principal component analysis, and neural networks. In this process, the correlation of genes with patient survival and disease progression and recurrence was noted. Also, multiple features from the gene set were found to have significant predictive capabilities. APTX, BRCA1, PAXX, LIG1, and TP53 were identified as most important out of all the candidate genes for predicting clinical outcomes of ovarian cancer patients.

PMID:37810216 | PMC:PMC10558711 | DOI:10.1016/j.isci.2023.107934

IEEE Trans Inf Theory. 2022 Oct;68(10):6631-6662. doi: 10.1109/tit.2022.3175691. Epub 2022 May 17.

ABSTRACT

The recent success of generative adversarial networks and variational learning suggests that training a classification network may work well in addressing the classical two-sample problem, which asks to differentiate two densities given finite samples from each one. Network-based methods have the computational advantage that the algorithm scales to large datasets. This paper considers using the classification logit function, which is provided by a trained classification neural network and evaluated on the testing set split of the two datasets, to compute a two-sample statistic. To analyze the approximation and estimation error of the logit function to differentiate near-manifold densities, we introduce a new result of near-manifold integral approximation by neural networks. We then show that the logit function provably differentiates two sub-exponential densities given that the network is sufficiently parametrized, and for on or near manifold densities, the needed network complexity is reduced to only scale with the intrinsic dimensionality. In experiments, the network logit test demonstrates better performance than previous network-based tests using classification accuracy, and also compares favorably to certain kernel maximum mean discrepancy tests on synthetic datasets and hand-written digit datasets.

PMID:37810208 | PMC:PMC10558099 | DOI:10.1109/tit.2022.3175691

J Comput Graph Stat. 2023;32(3):974-984. doi: 10.1080/10618600.2022.2119986. Epub 2022 Oct 14.

ABSTRACT

The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineering, and other fields. In the reduced-rank regression modelling, a central objective is to estimate the rank of the coefficient matrix that represents the number of effective latent factors in predicting the multivariate response. Although theoretical results such as rank estimation consistency have been established for various methods, in practice rank determination still relies on information criterion based methods such as AIC and BIC or subsampling based methods such as cross validation. Unfortunately, the theoretical properties of these practical methods are largely unknown. In this paper, we present a novel method called StARS-RRR that selects the tuning parameter and then estimates the rank of the coefficient matrix for reduced-rank regression based on the stability approach. We prove that StARS-RRR achieves rank estimation consistency, i.e., the rank estimated with the tuning parameter selected by StARS-RRR is consistent to the true rank. Through a simulation study, we show that StARS-RRR outperforms other tuning parameter selection methods including AIC, BIC, and cross validation as it provides the most accurate estimated rank. In addition, when applied to a breast cancer dataset, StARS-RRR discovers a reasonable number of genetic pathways that affect the DNA copy number variations and results in a smaller prediction error than the other methods with a random-splitting process.

PMID:37810194 | PMC:PMC10554232 | DOI:10.1080/10618600.2022.2119986

J Clin Imaging Sci. 2023 Sep 4;13:25. doi: 10.25259/JCIS_55_2023. eCollection 2023.

ABSTRACT

OBJECTIVES: This study assesses the safety and efficacy of balloon-assisted gastrostomy (BAG) compared to conventional techniques using dilators.

MATERIAL AND METHODS: A single-center retrospective review of all fluoroscopically-guided percutaneous gastrostomy tube insertions from July 2017 to September 2020 was performed. Two hundred and seventy-three patients were included in this study, with 183 patients and 90 patients in the BAG and dilator groups, respectively. Fluoroscopy time, peak radiation dose, pain management, days to interventional radiology (IR) reconsultation, and post-operative complications (major and minor) for each procedure were reviewed to evaluate for statistical differences.

RESULTS: There were shorter fluoroscopy times (5.13 min vs. 7.05 min, P = 0.059) and a significantly lower radiation use (Avg = 102.13 mGy vs. 146.98 mGy, P < 0.05) in the BAG group. The BAG group required significantly lower operating time (41 min vs. 48 min, P < 0.01) and received lower pain management (fentanyl 75 mcg and midazolam 1.5 mg, P < 0.001). The mean days to IR reconsultation for the BAG group was greater (29 days vs. 26 days, P = 0.38). The overall rate of minor complications (grades 1 and 2, according to the CIRSE classification system) was higher in the dilator group (39% vs. 35% in BAG group, P = 0.53). No major complications were reported in either group.

CONCLUSION: BAG is a safe and efficient technique for percutaneous gastrostomy tube placement. BAG patients required significantly lesser radiation, OR time, post-operative pain management, and recorded lower postoperative complications compared to their counterparts in gastrostomies utilizing dilators.

PMID:37810182 | PMC:PMC10559364 | DOI:10.25259/JCIS_55_2023

FASEB Bioadv. 2023 Sep 8;5(10):412-426. doi: 10.1096/fba.2023-00070. eCollection 2023 Oct.

ABSTRACT

Early detection and recurrence prediction are challenging in triple-negative breast cancer (TNBC) patients. We aimed to develop mitochondrial DNA (mtDNA)-based liquid biomarkers to improve TNBC management. Mitochondrial genome (MG) enrichment and next-generation sequencing mapped the entire MG in 73 samples (64 tissues and 9 extracellular vesicles [EV] samples) from 32 metastatic TNBCs. We measured mtDNA and cardiolipin (CL) contents, NDUFB8, and SDHB protein expression in tumors and in corresponding circulating EVs. We identified 168 nonsynonymous mtDNA mutations, with 73% (123/186) coding and 27% (45/168) noncoding in nature. Twenty percent of mutations were nucleotide transversions. Respiratory complex I (RCI) was the key target, which harbored 44% (74/168) of the overall mtDNA mutations. A panel of 11 hotspot mtDNA mutations was identified among 19%-38% TNBCs, which were detectable in the serum-derived EVs with 82% specificity. Overall, 38% of the metastatic tumor-signature mtDNA mutations were traceable in the EVs. An appreciable number of mtDNA mutations were homoplasmic (18%, 31/168), novel (14%, 23/168), and potentially pathogenic (9%, 15/168). The overall and RCI-specific mtDNA mutational load was higher in women with African compared to European ancestry accompanied by an exclusive abundance of respiratory complex (RC) protein NDUFB8 (RCI) and SDHB (RCII) therein. Increased mtDNA (p < 0.0001) content was recorded in both tumors and EVs along with an abundance of CL (p = 0.0001) content in the EVs. Aggressive tumor-signature mtDNA mutation detection and measurement of mtDNA and CL contents in the EVs bear the potential to formulate noninvasive early detection and recurrence prediction strategies.

PMID:37810173 | PMC:PMC10551276 | DOI:10.1096/fba.2023-00070

Heliyon. 2023 Sep 7;9(9):e19848. doi: 10.1016/j.heliyon.2023.e19848. eCollection 2023 Sep.

ABSTRACT

A non-linear system of differential equations was used to explain the spread of the COVID-19 virus and a SEIQR model was developed and tested to provide insights into the spread of the pandemic. This article, which is related to the aforementioned work as well as other work covering variations of SIR models, Hermite Wavelets Transform, and also the Generalized Compartmental COVID-19 model, we develop a mathematical control model and apply it to represent optimal vaccination strategy against COVID-19 using Pontryagin’s Maximum Principle and also factoring in the effect of facemasks on the spread of the virus. As background work, we analyze the mathematical epidemiology model with the facemask effect on both reproduction number and stability, we also analyze the difference between confirmed COVID-19 cases of the Quarantine class and anonymous cases of the Infectious class that is expected to recover. We also apply control theory to mine insights for effective virus spread prevention strategies. Our models are validated using Matlab mathematical model validation tools. Statistical tests against data from Jordan are used to validate our work including the modeling of the relation between the facemask effect and COVID-19 spread. Furthermore, the relation between control measure ξ, cost, and Infected cases is also studied.

PMID:37810168 | PMC:PMC10559238 | DOI:10.1016/j.heliyon.2023.e19848

Heliyon. 2023 Sep 1;9(9):e19729. doi: 10.1016/j.heliyon.2023.e19729. eCollection 2023 Sep.

ABSTRACT

Forecasts for key macroeconomic variables are almost always made simultaneously by the same organizations, presented together, and used together in policy analyses and decision-makings. It is therefore important to know whether the forecasters are skillful enough to forecast the future values of those variables. Here a method for joint evaluation of skill in directional forecasts of multiple variables is introduced. The method is simple to use and does not rely on complicated assumptions required by the conventional statistical methods for measuring accuracy of directional forecast. The data on GDP growth and inflation forecasts of three organizations from Thailand, namely, the Bank of Thailand, the Fiscal Policy Office, and the Office of the National Economic and Social Development Council as well as the actual data on GDP growth and inflation of Thailand between 2001 and 2021 are employed in order to demonstrate how the method could be used to evaluate the skills of forecasters in practice. The overall results indicate that these three organizations are somewhat skillful in forecasting the direction-of-changes of GDP growth and inflation when no band and a band of ± 1 standard deviation of the forecasted outcome are considered. However, when a band of ± 0.5% of the forecasted outcome is introduced, the skills in forecasting the direction-of-changes of GDP growth and inflation of these three organizations are, at best, little better than intelligent guess work.

PMID:37810150 | PMC:PMC10558991 | DOI:10.1016/j.heliyon.2023.e19729

Heliyon. 2023 Aug 25;9(9):e19533. doi: 10.1016/j.heliyon.2023.e19533. eCollection 2023 Sep.

ABSTRACT

The literature on entrepreneurship and technology transfer highlights several factors that impact the creation of university Spin-Offs. However, there is a limited body of research that specifically explores the impact of university-industry collaborations on the performance creation of these spinoffs. This study aims to fill this gap by examining the effects of university-industry collaborations on the creation of Spin-Offs from two perspectives: the number of university collaborations with different companies and the number of previous collaborations between the same university-industry dyad. The research employs joint patents as a source to measure the university-industry collaborations and statistical methods to empirically examine the impact of these collaborations on Spin-Off creation. The study is based on data from 108 universities between the years 2014 and 2017. The findings of this study reveal that both the number of collaborations and specially the presence of previous collaborations between the university and industry have a positive effect on the creation of Spin-Offs. These results suggest that universities and companies should consider these findings when formulating their strategies or policies for technology transfer and innovation management by encouraging university-industry collaborations.

PMID:37810148 | PMC:PMC10558740 | DOI:10.1016/j.heliyon.2023.e19533

Heliyon. 2023 Aug 29;9(9):e19378. doi: 10.1016/j.heliyon.2023.e19378. eCollection 2023 Sep.

ABSTRACT

Empirical observation, controlled experiments, and pedestrian dynamics models are used to research pedestrian movement. These studies rely on single-file fundamental diagrams. Experiments were conducted in Ghana, and African students in China and Germany undertook experiments (Seyfried et al., 2005) [1]. Different groups of pedestrians were tested, and then told the entrance group conducted three corridor rotations. A t-test and z-test were employed to compare all measurement findings statistically. The study found significant spatial and cultural implications on single-file pedestrian travel. African pupils in China have an R² of 0.63 (63%), while Ghanaians have an R² of 0.77 (77%). Both groups are African, suggesting that location influences single-file pedestrian principles. According to a comparable study, Indian and German pedestrian fundamental diagrams [2,3], German and Brazil [4,5] show considerable variances. This research examines whether locations and culture affect single-file pedestrian travel.

PMID:37810143 | PMC:PMC10558330 | DOI:10.1016/j.heliyon.2023.e19378