Nevin Manimala

Int Urol Nephrol. 2023 Nov 13. doi: 10.1007/s11255-023-03863-z. Online ahead of print.

ABSTRACT

AIM: To investigate the associations of the weekend warrior and other physical activity (PA) patterns with all-cause, cardiovascular disease (CVD) mortality risk in people with diabetes mellitus (DM) and chronic kidney disease (CKD).

METHODS: This study pooled the data from NHANES 2007-2020. Participants with DM and CKD were included. PA was assessed using a self-reported questionnaire. According to the characteristics of recreational activities, individuals were categorized as inactive (no activities), insufficiently active (total PA duration < 150 min/week), weekend warrior (total PA duration ≥ 150 min/week for 1-2 sessions), and regularly active (total PA duration ≥ 150 min/week for ≥ 3 sessions). Weighted Cox regression models with adjusting sociodemographic, behavioral, and metabolic factors were performed to investigate the relationship of PA patterns with all-cause and CVD mortality risk. Stratification and interaction analyses were further performed.

RESULTS: Among 1702 participants (46.53% female; 64 ± 0.46 years old), 536 died (163 cardiovascular) during the follow-up of 68 (39-104) months. The hazard ratio (HR) of all-cause death was 0.618 (95% CI 0.406-0.942) for insufficiently active PA pattern, 0.338 (95% CI 0.116-0.988) for weekend warrior PA pattern, and 0.536 (95% CI 0.395-0.726) for regularly active PA pattern compared with inactive PA pattern. HR of CVD death was 0.545 (95% CI 0.250-1.189) for the PA pattern of insufficiently active, 0.165 (95% CI 0.020-1.343) for weekend warrior, and 0.393 (95% CI 0.218-0.710) for regularly active compared with the inactive PA pattern. The associations present no difference in subgroups. Moreover, there was no discernible difference between weekend warrior and regularly active PA patterns for all-cause and CVD deaths. The risk of death declined relatively quickly When exercise was initiated and to a total of 450 min or 4 times per week.

CONCLUSION: In a population of DM and CKD, the weekend warrior pattern was similar to regular activity to lower the risk of all-cause mortality, compared with inactivity. The weekend warrior pattern was recommended for people who only have time to exercise on the weekend. However, longer and larger sample cohort studies are needed to validate our findings.

PMID:37955818 | DOI:10.1007/s11255-023-03863-z

Front Med. 2023 Nov 13. doi: 10.1007/s11684-023-1017-7. Online ahead of print.

ABSTRACT

The association of neurogenesis and gliogenesis with glioma remains unclear. By conducting single-cell RNA-seq analyses on 26 gliomas, we reported their classification into primitive oligodendrocyte precursor cell (pri-OPC)-like and radial glia (RG)-like tumors and validated it in a public cohort and TCGA glioma. The RG-like tumors exhibited wild-type isocitrate dehydrogenase and tended to carry EGFR mutations, and the pri-OPC-like ones were prone to carrying TP53 mutations. Tumor subclones only in pri-OPC-like tumors showed substantially down-regulated MHC-I genes, suggesting their distinct immune evasion programs. Furthermore, the two subgroups appeared to extensively modulate glioma-infiltrating lymphocytes in distinct manners. Some specific genes not expressed in normal immune cells were found in glioma-infiltrating lymphocytes. For example, glial/glioma stem cell markers OLIG1/PTPRZ1 and B cell-specific receptors IGLC2/IGKC were expressed in pri-OPC-like and RG-like glioma-infiltrating lymphocytes, respectively. Their expression was positively correlated with those of immune checkpoint genes (e.g., LGALS33) and poor survivals as validated by the increased expression of LGALS3 upon IGKC overexpression in Jurkat cells. This finding indicated a potential inhibitory role in tumor-infiltrating lymphocytes and could provide a new way of cancer immune evasion.

PMID:37955814 | DOI:10.1007/s11684-023-1017-7

Eur J Popul. 2023 Nov 13;39(1):33. doi: 10.1007/s10680-023-09675-2.

ABSTRACT

Demographic forecasters must be realistic about how well they can predict future populations, and it is important that they include estimates of uncertainty in their forecasts. Here we focus on the future development of the immigrant population of Norway and their Norwegian-born children (“second generation”), grouped by three categories of country background: 1. West European countries plus the United States, Canada, Australia, and New Zealand; 2. Central and East European countries that are members of the European Union; 3. other countries. We show how to use a probabilistic forecast to assess the reliability of projections of the immigrant population and their children. We employ the method of random shares using data for immigrants and their children for 2000-2021. We model their age- and sex-specific shares relative to the whole population. Relational models are used for the age patterns in these shares, and time series models to extrapolate the parameters of the age patterns. We compute a probabilistic forecast for six population sub-groups with immigration background, and one for non-immigrants. The probabilistic forecast is calibrated against Statistics Norway’s official population projection. We find that a few population trends are quite certain: strong increases to 2060 in the size of the immigrant population (more specifically those who belong to country group 3) and of Norwegian-born children of immigrants. However, prediction intervals around the forecasts of immigrants and their children by one-year age groups are so wide that these forecasts are not reliable.

PMID:37955802 | DOI:10.1007/s10680-023-09675-2

Lifetime Data Anal. 2023 Nov 13. doi: 10.1007/s10985-023-09612-9. Online ahead of print.

ABSTRACT

In a semi-competing risks model in which a terminal event censors a non-terminal event but not vice versa, the conventional method can predict clinical outcomes by maximizing likelihood estimation. However, this method can produce unreliable or biased estimators when the number of events in the datasets is small. Specifically, parameter estimates may converge to infinity, or their standard errors can be very large. Moreover, terminal and non-terminal event times may be correlated, which can account for the frailty term. Here, we adapt the penalized likelihood with Firth’s correction method for gamma frailty models with semi-competing risks data to reduce the bias caused by rare events. The proposed method is evaluated in terms of relative bias, mean squared error, standard error, and standard deviation compared to the conventional methods through simulation studies. The results of the proposed method are stable and robust even when data contain only a few events with the misspecification of the baseline hazard function. We also illustrate a real example with a multi-centre, patient-based cohort study to identify risk factors for chronic kidney disease progression or adverse clinical outcomes. This study will provide a better understanding of semi-competing risk data in which the number of specific diseases or events of interest is rare.

PMID:37955788 | DOI:10.1007/s10985-023-09612-9

Eur J Pediatr. 2023 Nov 13. doi: 10.1007/s00431-023-05317-1. Online ahead of print.

ABSTRACT

Improved prediction of physical child abuse could aid in developing preventive measures. Parental physical disease has been tested previously as a predictor of documented physical child abuse but in broad categories and with differing results. No prior studies have tested clinically recognizable categories of parental disease in a high-powered dataset. Using Danish registries, data on children and their parents from the years 1997-2018 were used to explore several parental physical disease categories’ associations with documented physical child abuse. For each disease category, survival analysis using pseudovalues was applied. When a parent of a child was diagnosed or received medication that qualified for a category, this family and five comparison families not in this disease category were included, creating separate cohorts for each category of disease. Multiple analyses used samples drawn from 2,705,770 children. Estimates were produced for 32 categories of physical diseases. Using Bonferroni-corrected confidence intervals (CIc), ischemic heart disease showed a relative risk (RR) of 1.44 (CIc 1.13-1.84); peripheral artery occlusive disease, RR 1.39 (CIc 1.01-1.90); stroke, RR 1.19 (1.01-1.41); chronic pulmonary disease, RR 1.33 (CIc 1.18-1.51); ulcer/chronic gastritis, RR 1.27 (CIc 1.08-1.49); painful condition, 1.17 (CIc 1.00-1.37); epilepsy, RR 1.24 (CIc 1.00-1.52); and unspecific somatic symptoms, RR 1.37 (CIc 1.21-1.55). Unspecific somatic symptoms were present in 71.87% of families at some point during the study period.

CONCLUSION: Most parental physical disease categories did not show statistically significant associations, but some showed predictive ability. Further research is needed to explore preventive potential.

WHAT IS KNOWN: • Few and broad categories of parental physical disease have been examined as risk factors for severe physical child abuse; no prior study has used several categories as predictors.

WHAT IS NEW: • Unspecific symptoms, ischemic heart disease, peripheral artery occlusive disease, stroke, chronic pulmonary disease, stomach ulcer/chronic gastritis, painful condition, and epilepsy all showed to be potential predictors, with unspecific symptoms being the most prevalent.

PMID:37955746 | DOI:10.1007/s00431-023-05317-1

Environ Sci Pollut Res Int. 2023 Nov 13. doi: 10.1007/s11356-023-30678-3. Online ahead of print.

ABSTRACT

Maximizing socioeconomic and environmental benefits with minimal investment in urban land resources is a key concern for sustainable urban development. The emission trading system is an important strategy of the Chinese government to control environmental pollution and promote green development, but whether it improves urban land green use efficiency is still unclear. Combining the concept of green development with urban land use efficiency, this paper uses the super-efficiency slack-based measure (SBM) model with undesirable outputs to measure the land green use efficiency of 261 prefecture-level cities in China from 2003 to 2017. In addition, the propensity score matching difference-in-differences (PSM-DID) method and the mediating effect model were used to test the impact of the China’s emission trading system on urban land green use efficiency and behind the mechanism. According to the findings, China’s emission trading system has significantly improved urban land green use efficiency, compared with that in nonpilot cities, urban land green use efficiency in pilot cities has increased by 10.40%. Moreover, the policy effect of the emission trading system is more significant in resource-based cities and cities with a high intensity of environmental regulations. Further mechanism analysis reveals that green technology innovation and industrial structure upgrading are effective transmission mechanisms for China’s emissions trading policy to improve urban land green use efficiency. The findings provide policy implications for promoting the sustainable use of urban land resources and advancing the coordinated development of urban socioeconomic and ecological environments.

PMID:37955732 | DOI:10.1007/s11356-023-30678-3

Environ Sci Pollut Res Int. 2023 Nov 13. doi: 10.1007/s11356-023-30882-1. Online ahead of print.

ABSTRACT

The escalating global greenhouse gas emission crisis necessitates a robust scientific carbon accounting framework and innovative development approaches. Achieving emission peaks remains the primary goal for emission reduction. Guangdong Province, a pivotal region in China, faces pressure to reduce carbon emissions. In this study, data was leveraged from the China Carbon Accounting Database (CEADS) and panel data from the “Guangdong Statistical Yearbook” spanning 1997 to 2022. Factors impacting carbon emissions were selected based on Guangdong Province’s carbon reduction goals, macroeconomic development strategies, and economic-population dynamics. To address multicollinearity, lasso regression identified key factors, including population size, economic development level, energy intensity, and technology factors. A novel STIRPAT extended model, combined with the BP neural network optimized using the TPE algorithm, enhanced carbon emission predictions for Guangdong Province. Employing scenario analysis, five scenarios were generated in alignment with the planning policies of Guangdong Province, to forecast carbon emissions from 2020 to 2050. The results suggest that to achieve a win-win situation for both economic development and environmental protection, Guangdong Province should prioritize the energy-saving scenario (S2), which aligns with the “13th Five-Year Plan’s” ecological and green development directives, to reach a projected carbon peak of 637.05Mt by 2030. In conclusion, recommendations for carbon reduction are proposed in the areas of low-carbon transformation for the population, sustainable economic development, and the development of low-carbon technologies.

PMID:37953421 | DOI:10.1007/s11356-023-30882-1

Pediatr Radiol. 2023 Nov 13. doi: 10.1007/s00247-023-05789-1. Online ahead of print.

ABSTRACT

BACKGROUND: Skeletal dysplasias collectively affect a large number of patients worldwide. Most of these disorders cause growth anomalies. Hence, evaluating skeletal maturity via the determination of bone age (BA) is a useful tool. Moreover, consecutive BA measurements are crucial for monitoring the growth of patients with such disorders, especially for timing hormonal treatment or orthopedic interventions. However, manual BA assessment is time-consuming and suffers from high intra- and inter-rater variability. This is further exacerbated by genetic disorders causing severe skeletal malformations. While numerous approaches to automate BA assessment have been proposed, few are validated for BA assessment on children with skeletal dysplasias.

OBJECTIVE: We present Deeplasia, an open-source prior-free deep-learning approach designed for BA assessment specifically validated on patients with skeletal dysplasias.

MATERIALS AND METHODS: We trained multiple convolutional neural network models under various conditions and selected three to build a precise model ensemble. We utilized the public BA dataset from the Radiological Society of North America (RSNA) consisting of training, validation, and test subsets containing 12,611, 1,425, and 200 hand and wrist radiographs, respectively. For testing the performance of our model ensemble on dysplastic hands, we retrospectively collected 568 radiographs from 189 patients with molecularly confirmed diagnoses of seven different genetic bone disorders including achondroplasia and hypochondroplasia. A subset of the dysplastic cohort (149 images) was used to estimate the test-retest precision of our model ensemble on longitudinal data.

RESULTS: The mean absolute difference of Deeplasia for the RSNA test set (based on the average of six different reference ratings) and dysplastic set (based on the average of two different reference ratings) were 3.87 and 5.84 months, respectively. The test-retest precision of Deeplasia on longitudinal data (2.74 months) is estimated to be similar to a human expert.

CONCLUSION: We demonstrated that Deeplasia is competent in assessing the age and monitoring the development of both normal and dysplastic bones.

PMID:37953411 | DOI:10.1007/s00247-023-05789-1

Immunol Res. 2023 Nov 13. doi: 10.1007/s12026-023-09433-w. Online ahead of print.

ABSTRACT

Behçet disease (BD) is an autoimmune and autoinflammatory disease mainly affecting the Silk Road countries. The interindividual severity of BD depends on differences in the polymorphic profiles of the patients. One of the most prominent markers, HLA-B51 positivity, is also observed in 40-60% of patients with BD on the Silk Road. Inflammatory markers such as interleukin 10 (IL-10) and interleukin 23 receptor (IL-23R) are also widely associated with BD etiology. The polymorphisms on these genes may change the susceptibility to BD. In this case-control study, we assessed the associations of IL-10 rs3024498 and IL-23R rs10889677 single-nucleotide polymorphisms (SNPs) with BD susceptibility, if any. Two hundred eighty HLA-B51-positive patients with BD and 300 healthy controls were genotyped for these SNPs using RFLP-PCR. The chi-square test was used for genotyping. We found that IL-23R rs10889677 CC and IL-10 rs3024498 CT genotype frequencies were higher in the BD group than in the control group (p < 0.0001 and p = 0.0293, respectively). The recessive model (AA + CC vs. AC) and combined genotype (AC + CT) results were also statistically significant (p < 0.0001 and p = 0.0364, respectively). We conclude that IL-23R rs10889677 and IL-10 rs3024498 SNPs may be associated with the susceptibility to BD.

PMID:37953401 | DOI:10.1007/s12026-023-09433-w

Nucleic Acids Res. 2023 Nov 11:gkad1026. doi: 10.1093/nar/gkad1026. Online ahead of print.

ABSTRACT

To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cells in situ. State-of-the-art spatial profiling technologies, such as the Nanostring GeoMx Digital Spatial Profiler (DSP), now allow quantitative spatially resolved measurement of the transcriptome in tissues. However, the bioinformatics pipelines currently used to analyse GeoMx data often fail to successfully account for the technical variability within the data and the complexity of experimental designs, thus limiting the accuracy and reliability of the subsequent analysis. Carefully designed quality control workflows, that include in-depth experiment-specific investigations into technical variation and appropriate adjustment for such variation can address this issue. Here, we present standR, an R/Bioconductor package that enables an end-to-end analysis of GeoMx DSP data. With four case studies from previously published experiments, we demonstrate how the standR workflow can enhance the statistical power of GeoMx DSP data analysis and how the application of standR enables scientists to develop in-depth insights into the biology of interest.

PMID:37953397 | DOI:10.1093/nar/gkad1026