Category: Nevin Manimala

Biol Sport. 2023 Jul;40(3):699-706. doi: 10.5114/biolsport.2023.119287. Epub 2022 Sep 22.

ABSTRACT

This study aimed to investigate the effect of a combined jump and sprint training program, two sessions a week for 6 weeks, on sprinting, change of directions (COD) and jumping performance in semi-professional soccer players. Twenty soccer players were enrolled in this randomized controlled trial (age 20 ± 2 years, body mass 74.3 ± 5.9 kg). Players were randomized into two groups such as training group (TG, n = 10 players) or control group (CG, n = 10 players). Physical tests were performed before and after 6 weeks of training such as sprint 10 m, sprint 30 m, 505-COD test and standing long jump (LJ). The two groups performed the same training except for the combined jump and sprint training performed twice a week by TG. After 6 weeks of training, between-group analysis reported statistical difference in favor of the TG in sprint 10 m (p = 0.015, η² = 0.295, large), sprint 30 m (p < 0.001, η² = 0.599, large), in 505-COD (p = 0.026, η² = 0.154, large), and LJ (p = 0.025, η² = 0.027, small). These data indicate that combined sprint and jump training, when performed twice a week, for the duration of 6 weeks, in addition to the regular team training, can improve specific physical performance in male soccer players. This study has shown that a volume increment of 10% after 3 weeks of training can be a suitable training dose progression and that a combination of 64-70 jumps and 675-738 m of sprinting training per session can yield benefits in sprint, COD and jump performance.

PMID:37398964 | PMC:PMC10286599 | DOI:10.5114/biolsport.2023.119287

Biol Sport. 2023 Jul;40(3):835-855. doi: 10.5114/biolsport.2023.121322. Epub 2022 Nov 22.

ABSTRACT

The purpose of this investigation is to estimate the global disease burden attributable to low physical activity (PA) in 204 countries and territories from 1990 to 2019 by age, sex, and Socio-Demographic Index (SDI). Detailed information on global deaths and disability-adjusted life years (DALYs) attributable to low PA were collected from the Global Burden of Disease Study 2019. The ideal exposure scenario of PA was defined as 3000-4500 metabolic equivalent minutes per week and low PA was considered to be less than this threshold. Age-standardization was used to improve the comparison of rates across locations or between time periods. In 2019, low PA seems to contribute to 0.83 million [95% uncertainty interval (UI) 0.43 to 1.47] deaths and 15.75 million (95% UI 8.52 to 28.62) DALYs globally, an increase of 83.9% (95% UI 69.3 to 105.7) and 82.9% (95% UI 65.5 to 112.1) since 1990, respectively. The age-standardized rates of low-PA-related deaths and DALYs per 100,000 people in 2019 were 11.1 (95% UI 5.7 to 19.5) and 198.4 (95% UI 108.2 to 360.3), respectively. Of all age-standardized DALYs globally in 2019, 0.6% (95% UI 0.3 to 1.1) may be attributable to low PA. The association between SDI and the proportion of age-standardized DALYs attributable to low PA suggests that regions with the highest SDI largely decreased their proportions of age-standardized DALYs attributable to low PA during 1990-2019, while other regions tended to have increased proportions in the same timeframe. In 2019, the rates of low-PA-related deaths and DALYs tended to rise with increasing age in both sexes, with no differences between males and females in the age-standardized rates. An insufficient accumulation of PA across the globe occurs together with a considerable public health burden. Health initiatives to promote PA within different age groups and countries are urgently needed.

PMID:37398951 | PMC:PMC10286621 | DOI:10.5114/biolsport.2023.121322

Biol Sport. 2023 Jul;40(3):899-918. doi: 10.5114/biolsport.2023.122479. Epub 2023 Feb 1.

ABSTRACT

Ice-hockey requires high acceleration and speed sprint abilities, but it is unclear what the distance characteristic is for measuring these capabilities. Therefore, this systematic meta-analysis aims to summarize the sprint reference values for different sprint distances and suggest the appropriate use of ice-hockey straight sprint testing protocols. A total of 60 studies with a pooled sample of 2254 males and 398 females aged 11-37 years were included. However, the pooled data for women was not large enough to permit statistical analysis. The sprint distance used for measuring the reported acceleration and speed was between 4-48 m. Increased test distance was positively associated with increased speed (r = 0.70) and negatively with average acceleration (r = -0.87). Forward skating sprint speed increases with the measured distance up to 26 m and do not differ much from longer distance tests, while acceleration decreases with a drop below 3 m/s at distances 15 m and longer. The highest acceleration (5.89 m/s² peak, 3.31 m/s² average) was achieved in the shortest distances up to 7 m which significantly differs from 8-14 m tests. The highest speed (8.1 m/s peak, 6.76 m/s average) has been recorded between 26-39 m; therefore, distances over 39 m are not necessary to achieve maximum speed. Considering match demands and most reported test distances, 6.1 m is the recommended distance for peak acceleration and 30 m for peak speed. The sprint time, acceleration, and speed of each individual and the number of skating strides should be reported in future studies.

PMID:37398950 | PMC:PMC10286618 | DOI:10.5114/biolsport.2023.122479

J Open Source Softw. 2023;8(82):4181. doi: 10.21105/joss.04181. Epub 2023 Feb 21.

ABSTRACT

Statistical causal inference of mixed exposures has been limited by reliance on parametric models and, until recently, by researchers considering only one exposure at a time, usually estimated as a beta coefficient in a generalized linear regression model (GLM). This independent assessment of exposures poorly estimates the joint impact of a collection of the same exposures in a realistic exposure setting. Marginal methods for mixture variable selection such as ridge/lasso regression are biased by linear assumptions and the interactions modeled are chosen by the user. Clustering methods such as principal component regression lose both interpretability and valid inference. Newer mixture methods such as quantile g-computation (Keil et al., 2020) are biased by linear/additive assumptions. More flexible methods such as Bayesian kernel machine regression (BKMR)(Bobb et al., 2014) are sensitive to the choice of tuning parameters, are computationally taxing and lack an interpretable and robust summary statistic of dose-response relationships. No methods currently exist which finds the best flexible model to adjust for covariates while applying a non-parametric model that targets for interactions in a mixture and delivers valid inference for a target parameter. Non-parametric methods such as decision trees are a useful tool to evaluate combined exposures by finding partitions in the joint-exposure (mixture) space that best explain the variance in an outcome. However, current methods using decision trees to assess statistical inference for interactions are biased and are prone to overfitting by using the full data to both identify nodes in the tree and make statistical inference given these nodes. Other methods have used an independent test set to derive inference which does not use the full data. The CVtreeMLE R package provides researchers in (bio)statistics, epidemiology, and environmental health sciences with access to state-of-the-art statistical methodology for evaluating the causal effects of a data-adaptively determined mixed exposure using decision trees. Our target audience are those analysts who would normally use a potentially biased GLM based model for a mixed exposure. Instead, we hope to provide users with a non-parametric statistical machine where users simply specify the exposures, covariates and outcome, CVtreeMLE then determines if a best fitting decision tree exists and delivers interpretable results.

PMID:37398941 | PMC:PMC10312067 | DOI:10.21105/joss.04181

J Migr Health. 2023 Jan 24;7:100164. doi: 10.1016/j.jmh.2023.100164. eCollection 2023.

ABSTRACT

BACKGROUND: Adolescent substance use is a significant issue which occurs during a critical period of life of youth. Perceived stress is a risk factor for adolescent substance use, and life events such as low family support, and community and familial turmoil often lead to ongoing feelings of stress and uncertainty. Similarly, structural factors such as poverty, local neighborhood disinvestment and disrepair, and exposure to racism and discrimination are linked to feelings of stress. The US-Mexico border region is favorable for drug smuggling. Such a context exacerbates stressful life events during adolescence and increases the risk of adolescent substance use. This study aims to investigate the impact family support has on substance use in adolescents living on either side of the U.S./Mexico border who self-reported high perceptions of disordered neighborhood stress, border community and immigration stress, or normalization of drug trafficking.

METHODS: This study used data from the cross-sectional BASUS survey. Logistic regression was used to study the association between family support and past 30-day use of alcohol, tobacco, marijuana, and any substance in a sample restricted to students who self-reported high perceptions of disordered neighborhood stress, border community and immigration stress, or normalization of drug trafficking.

RESULTS: Participants with low family support were at higher risk of using any substance compared to participants with high family support (aOR= 1.58, 95% CI: 1.02; 2.45). Similar results were found for alcohol (aOR= 1.79, 95% CI: 1.13, 2.83). While the odds of using tobacco were higher for those with low social support as compared to participants with higher social support, this association was not statistically significant (aOR = 1.74, 95% CI: 0.93, 3.27).

CONCLUSION: Prevention programs tailored to the U.S.-Mexico border region should emphasize strengthening family support as a preventive factor against adolescent substance use. Family support should be considered in school counseling assessments, healthcare screenings and other social services.

PMID:37398939 | PMC:PMC10313897 | DOI:10.1016/j.jmh.2023.100164

J Struct Biol X. 2023 Jun 2;7:100089. doi: 10.1016/j.yjsbx.2023.100089. eCollection 2023.

ABSTRACT

Correlation functions play an important role in the theoretical underpinnings of many disparate areas of the physical sciences: in particular, scattering theory. More recently, they have become useful in the classification of objects in areas such as computer vision and our area of cryoEM. Our primary classification scheme in the cryoEM image processing system, EMAN2, is now based on third order invariants formulated in Fourier space. This allows a factor of 8 speed up in the two classification procedures inherent in our software pipeline, because it allows for classification without the need for computationally costly alignment procedures. In this work, we address several formal and practical aspects of such multispectral invariants. We show that we can formulate such invariants in the representation in which the original signal is most compact. We explicitly construct transformations between invariants in different orientations for arbitrary order of correlation functions and dimension. We demonstrate that third order invariants distinguish 2D mirrored patterns (unlike the radial power spectrum), which is a fundamental aspects of its classification efficacy. We show the limitations of 3rd order invariants also, by giving an example of a wide family of patterns with identical (vanishing) set of 3rd order invariants. For sufficiently rich patterns, the third order invariants should distinguish typical images, textures and patterns.

PMID:37398937 | PMC:PMC10314203 | DOI:10.1016/j.yjsbx.2023.100089

Front Comput Neurosci. 2023 Jun 15;17:1189949. doi: 10.3389/fncom.2023.1189949. eCollection 2023.

ABSTRACT

The property of covariance, also referred to as equivariance, means that an image operator is well-behaved under image transformations, in the sense that the result of applying the image operator to a transformed input image gives essentially a similar result as applying the same image transformation to the output of applying the image operator to the original image. This paper presents a theory of geometric covariance properties in vision, developed for a generalised Gaussian derivative model of receptive fields in the primary visual cortex and the lateral geniculate nucleus, which, in turn, enable geometric invariance properties at higher levels in the visual hierarchy. It is shown how the studied generalised Gaussian derivative model for visual receptive fields obeys true covariance properties under spatial scaling transformations, spatial affine transformations, Galilean transformations and temporal scaling transformations. These covariance properties imply that a vision system, based on image and video measurements in terms of the receptive fields according to the generalised Gaussian derivative model, can, to first order of approximation, handle the image and video deformations between multiple views of objects delimited by smooth surfaces, as well as between multiple views of spatio-temporal events, under varying relative motions between the objects and events in the world and the observer. We conclude by describing implications of the presented theory for biological vision, regarding connections between the variabilities of the shapes of biological visual receptive fields and the variabilities of spatial and spatio-temporal image structures under natural image transformations. Specifically, we formulate experimentally testable biological hypotheses as well as needs for measuring population statistics of receptive field characteristics, originating from predictions from the presented theory, concerning the extent to which the shapes of the biological receptive fields in the primary visual cortex span the variabilities of spatial and spatio-temporal image structures induced by natural image transformations, based on geometric covariance properties.

PMID:37398936 | PMC:PMC10311448 | DOI:10.3389/fncom.2023.1189949

Gastroenterol Rep (Oxf). 2023 Jun 30;11:goad036. doi: 10.1093/gastro/goad036. eCollection 2023.

ABSTRACT

BACKGROUND: Compared with conventional laparoscopic surgery, natural orifice specimen extraction surgery (NOSES) has many advantages. Laparoscopic right colectomy with transvaginal specimen extraction has been reported, but the safety and feasibility of transrectal specimen extraction in male patients with ascending colon cancer remain to be verified. This study aimed to preliminarily evaluate the feasibility and safety of laparoscopic right hemicolectomy with transrectal specimen extraction.

METHODS: The study was conducted at a single tertiary medical center in China. A total of 494 consecutive patients who underwent laparoscopic right colectomy between September 2018 and September 2020 were included. Transrectal specimen extraction was performed in 40 male patients (the NOSES group). Patients in the NOSES group were matched to the conventional laparoscopic group using propensity score matching at a 1:2 ratio. Short-term and long-term outcomes between the two groups were compared and evaluated.

RESULTS: Forty patients in the NOSES group and 80 patients in the conventional laparoscopic group were matched for analysis. Baseline characteristics were balanced after propensity matching. The operative features, including operating time, intraoperative bleeding, and the number of harvested lymph nodes, were statistically comparable in both groups. In terms of post-operative recovery, patients in the NOSES group showed preferable outcomes, as evidenced by less post-operative pain and faster return to flatus, defecation, and discharge. The post-operative complications rate, according to the Clavien-Dindo classification system, was similar in both groups. No differences in overall survival or disease-free survival were observed between the two groups.

CONCLUSIONS: Laparoscopic right colectomy with transrectal specimen extraction is oncologically safe. Compared with conventional laparoscopic right colectomy, it can reduce post-operative pain, accelerate post-operative recovery, shorten the hospital stay, and achieve better cosmetic effect.

PMID:37398927 | PMC:PMC10313420 | DOI:10.1093/gastro/goad036

Open Med (Wars). 2023 Jun 29;18(1):20230712. doi: 10.1515/med-2023-0712. eCollection 2023.

ABSTRACT

The objective was to explore the efficacy of Tongdu Tuina manipulation in the treatment of primary single-symptom enuresis in children. A total of 102 children aged 5-16 with primary single-symptom enuresis were included in this study and randomly assigned to the Tuina group, the medication group and the control group, with 34 children in each group. The Tongdu Tuina group included manipulation of the Guanyuan, Qihai, Zhongji, Mingmen, kidney, Baihui, Sishencong and bladder acupoints, five times a week, the medication group was treated with 0.1 mg desmopressin acetate every night, and in the control group, the patients were given foods with high water content and underwent water deprivation 2 h before bedtime every night. The intervention time of each group was 1 month. The participants were followed up on Day 1 following treatment, as well as half a month, 1 month and 3 months after the implementation of the intervention measures, and the effective rate, the incidence of enuresis per week and the recurrence rate were calculated. As a result baseline demographic characteristics were comparable among 102 patients. Overall, 32 patients in the Tongdu Tuina group, 30 patients in the medication group and 34 patients in the control group completed the intervention. After half a month of treatment, there was no significant difference in the therapeutic efficacy among the three groups (P = 0.158), but each treatment could effectively reduce the frequency of weekly enuresis. The frequency of weekly enuresis in the Tongdu Tuina group was 3.8 ± 1.1 times, while that in the medication group was 4.0 ± 2.0 times. The frequency of weekly enuresis in the control group was 4.7 ± 1.8 times, and the difference was statistically significant (P = 0.016). After 1 month of treatment, the effective rates of the Tongdu Tuina group and the medication group were significantly increased (87.5% vs 83.33%, P < 0.0001), which was not the case with the control group. The frequency of enuresis was 1.9 ± 2.1 times per week in the Tongdu Tuina group, 2.4 ± 1.8 times per week in the medication group and 4.0 ± 0.9 times per week in the control group after 1 month of treatment. The difference between the three groups was statistically significant (P = 0.021), and there was a difference between the Tongdu Tuina group and the medication group (P < 0.0001). There was no significant difference between recurrence rate and the incidence of adverse events (P = 0.837, P = 0.856). In conclusion, both Tuina manipulation and desmopressin treatment can effectively improve children’s primary single-symptom enuresis with safety. However, Tongdu Tuina therapy may be superior to desmopressin treatment.

PMID:37398900 | PMC:PMC10314128 | DOI:10.1515/med-2023-0712

Ann Appl Stat. 2020 Mar;14(1):433-451. doi: 10.1214/19-aoas1312. Epub 2020 Apr 16.

ABSTRACT

Principal component analysis (PCA) is a popular method for dimension reduction in unsupervised multivariate analysis. However, existing ad hoc uses of PCA in both multivariate regression (multiple outcomes) and multiple regression (multiple predictors) lack theoretical justification. The differences in the statistical properties of PCAs in these two regression settings are not well understood. In this paper we provide theoretical results on the power of PCA in genetic association testings in both multiple phenotype and SNP-set settings. The multiple phenotype setting refers to the case when one is interested in studying the association between a single SNP and multiple phenotypes as outcomes. The SNP-set setting refers to the case when one is interested in studying the association between multiple SNPs in a SNP set and a single phenotype as the outcome. We demonstrate analytically that the properties of the PC-based analysis in these two regression settings are substantially different. We show that the lower order PCs, that is, PCs with large eigenvalues, are generally preferred and lead to a higher power in the SNP-set setting, while the higher-order PCs, that is, PCs with small eigenvalues, are generally preferred in the multiple phenotype setting. We also investigate the power of three other popular statistical methods, the Wald test, the variance component test and the minimum $p$-value test, in both multiple phenotype and SNP-set settings. We use theoretical power, simulation studies, and two real data analyses to validate our findings.

PMID:37398898 | PMC:PMC10313330 | DOI:10.1214/19-aoas1312