Category: Nevin Manimala

Int J Environ Health Res. 2024 Mar 15:1-16. doi: 10.1080/09603123.2024.2328741. Online ahead of print.

ABSTRACT

Climate-induced health hazards are increasingly evident and frequent, with mental health emerging as a critical concern. Our study focuses on assessing mental health challenges related to climate variability in Northeastern Thailand. Using descriptive cross-sectional analysis and the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10), we analyzed mental health morbidity from 2018 to 2022. High average monthly temperatures exceeding 30°C and exposure to floods or droughts elevate the risk of mental health challenges. To address these risks, a holistic approach integrating Sustainable Development Goals and mental health initiatives is essential. This approach should prioritize understanding the impacts of climate change on the environment and human health. Supporting marginalized communities with indigenous knowledge and evidence-based programs can effectively prioritize sustainable mental health support, especially for vulnerable populations, fostering progress in human development and wellbeing.

PMID:38487936 | DOI:10.1080/09603123.2024.2328741

Genet Test Mol Biomarkers. 2024 Mar 15. doi: 10.1089/gtmb.2023.0606. Online ahead of print.

ABSTRACT

Background: Micro RNAs are new diagnostic markers and therapeutic targets in breast cancer research. miR-107 and miR-126 have been reported to be linked with the pathogenesis of breast cancer. The present study investigates the levels of expression of miR-107 and miR-126 in patients with breast cancer to find their correlation with the risk of breast cancer in Amritsar, Punjab, Northwest India. Material and Methods: In total, 200 subjects, 100 patients with breast cancer and 100 controls, were enrolled to screen the expression of miR-107 and miR-126 using quantitative reverse transcription polymerase chain reaction (RT-PCR) technique. The Livak method (2^-ΔΔCt) was used to calculate the fold change of the expression of micro RNAs. Student t-test was used to calculate the significant change in the expression of miRNAs in patients as compared with controls. Spearman rank correlation coefficient and ROC were conducted. The value of p < 0.05 was considered to indicate a statistically significant difference. Results: miR-107 was downregulated in patients with breast cancer as compared with controls (fold change = 0.467; p = 0.114) but not statistically significant. The expression of miR-126 was found to be 5.37 times elevated in patients with breast cancer, specifically in stage I and stage III patients (p = 0.009), compared with controls, which may indicate its oncogenic activity. The ROC analyses revealed that miR-126 could be a potential diagnostic marker. In conclusion oncogenic behavior of miR-126 is suggestive of its role in pathogenesis in patients with breast cancer.

PMID:38487920 | DOI:10.1089/gtmb.2023.0606

Circ Cardiovasc Interv. 2024 Mar 15:e013738. doi: 10.1161/CIRCINTERVENTIONS.123.013738. Online ahead of print.

ABSTRACT

BACKGROUND: Suboptimal coronary reperfusion (no reflow) is common in acute coronary syndrome percutaneous coronary intervention (PCI) and is associated with poor outcomes. We aimed to develop and externally validate a clinical risk score for angiographic no reflow for use following angiography and before PCI.

METHODS: We developed and externally validated a logistic regression model for prediction of no reflow among adult patients undergoing PCI for acute coronary syndrome using data from the Melbourne Interventional Group PCI registry (2005-2020; development cohort) and the British Cardiovascular Interventional Society PCI registry (2006-2020; external validation cohort).

RESULTS: A total of 30 561 patients (mean age, 64.1 years; 24% women) were included in the Melbourne Interventional Group development cohort and 440 256 patients (mean age, 64.9 years; 27% women) in the British Cardiovascular Interventional Society external validation cohort. The primary outcome (no reflow) occurred in 4.1% (1249 patients) and 9.4% (41 222 patients) of the development and validation cohorts, respectively. From 33 candidate predictor variables, 6 final variables were selected by an adaptive least absolute shrinkage and selection operator regression model for inclusion (cardiogenic shock, ST-segment-elevation myocardial infarction with symptom onset >195 minutes pre-PCI, estimated stent length ≥20 mm, vessel diameter <2.5 mm, pre-PCI Thrombolysis in Myocardial Infarction flow <3, and lesion location). Model discrimination was very good (development C statistic, 0.808; validation C statistic, 0.741) with excellent calibration. Patients with a score of ≥8 points had a 22% and 27% risk of no reflow in the development and validation cohorts, respectively.

CONCLUSIONS: The no-reflow prediction in acute coronary syndrome risk score is a simple count-based scoring system based on 6 parameters available before PCI to predict the risk of no reflow. This score could be useful in guiding preventative treatment and future trials.

PMID:38487882 | DOI:10.1161/CIRCINTERVENTIONS.123.013738

Brief Bioinform. 2024 Jan 22;25(2):bbae091. doi: 10.1093/bib/bbae091.

ABSTRACT

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless, challenges arise from prevalent sequencing dropout events and noise effects, impacting subsequent analyses. Here, we introduce a novel algorithm, Single-cell Gene Importance Ranking (scGIR), which utilizes a single-cell gene correlation network to evaluate gene importance. The algorithm transforms single-cell sequencing data into a robust gene correlation network through statistical independence, with correlation edges weighted by gene expression levels. We then constructed a random walk model on the resulting weighted gene correlation network to rank the importance of genes. Our analysis of gene importance using PageRank algorithm across nine authentic scRNA-seq datasets indicates that scGIR can effectively surmount technical noise, enabling the identification of cell types and inference of developmental trajectories. We demonstrated that the edges of gene correlation, weighted by expression, play a critical role in enhancing the algorithm’s performance. Our findings emphasize that scGIR outperforms in enhancing the clustering of cell subtypes, reverse identifying differentially expressed marker genes, and uncovering genes with potential differential importance. Overall, we proposed a promising method capable of extracting more information from single-cell RNA sequencing datasets, potentially shedding new lights on cellular processes and disease mechanisms.

PMID:38487851 | DOI:10.1093/bib/bbae091

Brief Bioinform. 2024 Jan 22;25(2):bbae086. doi: 10.1093/bib/bbae086.

ABSTRACT

Causal discovery is a powerful tool to disclose underlying structures by analyzing purely observational data. Genetic variants can provide useful complementary information for structure learning. Recently, Mendelian randomization (MR) studies have provided abundant marginal causal relationships of traits. Here, we propose a causal network pruning algorithm MRSL (MR-based structure learning algorithm) based on these marginal causal relationships. MRSL combines the graph theory with multivariable MR to learn the conditional causal structure using only genome-wide association analyses (GWAS) summary statistics. Specifically, MRSL utilizes topological sorting to improve the precision of structure learning. It proposes MR-separation instead of d-separation and three candidates of sufficient separating set for MR-separation. The results of simulations revealed that MRSL had up to 2-fold higher F1 score and 100 times faster computing time than other eight competitive methods. Furthermore, we applied MRSL to 26 biomarkers and 44 International Classification of Diseases 10 (ICD10)-defined diseases using GWAS summary data from UK Biobank. The results cover most of the expected causal links that have biological interpretations and several new links supported by clinical case reports or previous observational literatures.

PMID:38487847 | DOI:10.1093/bib/bbae086

Perfusion. 2024 Mar 15:2676591241239823. doi: 10.1177/02676591241239823. Online ahead of print.

ABSTRACT

INTRODUCTION: Postoperative delirium (POD) has a major impact on patient recovery after cardiac surgery. Although its pathophysiology remains unclear, there could be a correlation between cerebral blood flow (CBF) variations during cardio-pulmonary bypass (CPB) and POD. Our study aimed to evaluate whether variations in on-pump CBF, compared to pre-anesthesia and pre-CPB values, are associated with POD following coronary artery bypass grafting (CABG) surgery.

METHODS: This prospective observational cohort study included 95 adult patients undergoing elective on-pump CABG surgery. Right middle cerebral artery blood flow velocity (MCAV) was assessed using Transcranial Doppler before anesthesia induction, before CPB and every fifteen minutes during CPB. Pre-anesthesia and pre-CPB values were chosen as baselines. Individual values, measured during CPB, were converted as percentage changes relative to these baselines and named as %MCAV₀ and %MCAV₁, respectively. POD was assessed using the Confusion Assessment Method for ICU (CAM-ICU) during the first 48 post-operative hours and with the 3-Minute Diagnostic Interview for Confusion Assessment Method (3D-CAM) on the fifth post-surgical day.

RESULTS: Overall POD incidence was 17.9%. At 30 minutes of CPB, %MCAV₀ was higher in POD group than in no-POD group (p = .05). %MCAV₀ at 45 minutes of CPB was significantly higher in POD group (87 (±17) %) than in no-POD group (68 (±24) %), p = .04. %MCAV₁ at 30 and 45 minutes of CPB were higher in POD group than in no-POD group, at the limit of statistical significance. We found %MCAV₁ > 100% in POD group, but not in no-POD group.

CONCLUSIONS: Significant differences in %MCAV₀ became evident after 30 minutes of CPB, whereas differences in %MCAV₁ at 45 minutes of CPB were at limit of statistical significance. In POD group %MCAV₁ was higher than 100% at 30 and 45 minutes of CPB, which is supposed to be a sign of cerebral hyperperfusion. Monitoring CBF during CPB could have prognostic value for POD.

PMID:38487837 | DOI:10.1177/02676591241239823

Cancer Res Treat. 2024 Mar 11. doi: 10.4143/crt.2024.252. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to report the projected cancer incidence and mortality for the year 2024 to estimate Korea’s current cancer burden.

MATERIALS AND METHODS: Cancer incidence data from 1999 to 2021 were obtained from the Korea National Cancer Incidence Database, and cancer mortality data from 1993 to 2022 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and multiplying the projected age-specific rates by the anticipated age-specific population for 2024. A joinpoint regression model was used to determine the year in which the linear trend changed significantly; we only used the data of the latest trend for prediction.

RESULTS: In total, 292,221 new cancer cases and 83,770 cancer deaths are expected to occur in Korea in 2024. The most common cancer site is expected to be the thyroid, followed by the colon and rectum, lung, breast, and stomach. These five cancers are expected to represent 55.7% of the overall burden of cancer in Korea. The most common type of cancer leading to death is expected to be lung cancer, followed by liver, colorectal, pancreatic, and stomach cancers.

CONCLUSION: The age-standardized incidence rates for female breast and prostate cancers are estimated to continue to increase. These up-to-date estimates of the cancer burden in Korea could be an important resource for planning and evaluating cancer-control programs.

PMID:38487833 | DOI:10.4143/crt.2024.252

Cancer Res Treat. 2024 Mar 13. doi: 10.4143/crt.2024.253. Online ahead of print.

ABSTRACT

PURPOSE: The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2021.

MATERIALS AND METHODS: Incidence, survival, and prevalence rates of cancer were calculated using the Korea National Cancer Incidence Database, from 1999 to 2021, with survival follow-up until December 31, 2022. Deaths from cancer were assessed using causes-of-death data obtained from Statistics Korea.

RESULTS: The number of new cancer diagnoses in 2021 increased by 27,002 cases (10.8%) compared to 2020. In 2021, newly diagnosed cancer cases and deaths from cancer were reported as 277,523 (age-standardized rate [ASR], 289.3 per 100,000) and 82,688 (ASR, 67.6 per 100,000), respectively. The overall cancer incidence rates increased by 3.3% annually from 1999 to 2012, and decreased by 5.3% from 2012 to 2015, thereafter, followed by non-significant changes. Cancer mortality rates have been decreasing since 2002, with more rapid decline in recent years (annual decrease of 2.8% from 2002 to 2013; 3.2% from 2013 to 2021). The 5-year relative survival between 2017 and 2021 was 72.1%, which contributed to prevalent cases reaching over 2.4 million in 2021.

CONCLUSION: In 2021, the number of newly diagnosed cancer patients increased as healthcare utilization recovered from the coronavirus disease 2019-related declines of 2020. Revised cancer registration guidelines expanded the registration scope, particularly for stomach and colorectal cancer. Survival rates have improved over the years, leading to a growing population of cancer survivors, necessitating a comprehensive cancer control strategy. The long-term impact of the pandemic on cancer statistics requires future investigation.

PMID:38487832 | DOI:10.4143/crt.2024.253

Pediatrics. 2024 Mar 15:e2023063531. doi: 10.1542/peds.2023-063531. Online ahead of print.

ABSTRACT

BACKGROUND: Approximately 20% of neonates with congenital cytomegalovirus (cCMV) develop long-term sequelae. The ability to accurately predict long-term outcomes as early as the neonatal period would help to provide for appropriate parental counseling and treatment indications. With this study, we aimed to identify neonatal predictive markers of cCMV long-term outcomes.

METHODS: As this study’s subjects, we chose neonates diagnosed with cCMV in 13 hospitals throughout France recruited from 2013 to 2017 and evaluated for at least 2 years with thorough clinical, audiology, and imaging evaluations and psychomotor development tests.

RESULTS: A total of 253 neonates were included, and 3 were later excluded because of the identification of a genetic disorder. A total of 227 were followed up for 2 years: 187/227 (82%) and 34/227 (15%) were infected after a maternal primary or nonprimary infection, respectively, 91/227 (40%) were symptomatic at birth, and 44/227 (19%) had cCMV sequelae. Maternal primary infection in the first trimester was the strongest prognosis factor (odds ratio = 38.34 [95% confidence interval, 5.02-293], P < .001). A predictive model of no risk of sequelae at 2 years of age according to normal hearing loss at birth, normal cerebral ultrasound, and normal platelet count had 98% specificity, 69% sensitivity, and 0.89 area under the curve (95% confidence interval, 0.83-0.96).

CONCLUSIONS: In the studied population, children with normal hearing at birth, normal platelet count at birth, and a normal cranial ultrasound had no risk of neurologic sequelae and a low risk of delayed unilateral sensorineural hearing loss. The use of this model based on readily available neonatal markers should help clinicians establish a personalized care pathway for each cCMV neonate.

PMID:38487823 | DOI:10.1542/peds.2023-063531

J Clin Endocrinol Metab. 2024 Mar 15:dgae172. doi: 10.1210/clinem/dgae172. Online ahead of print.

ABSTRACT

OBJECTIVE: Breastfeeding is associated with a reduced maternal risk for cardiovascular diseases. Since the underlying mechanisms are still poorly understood, we here examined the impact of breastfeeding on the plasmatic coagulation system in women with and without history of gestational diabetes mellitus (GDM).

METHODS: 76 participants of the German Gestational Diabetes Study (PREG; NCT04270578) were examined 14 [interquartile range: 12-26] months after delivery with a 5-point oral glucose tolerance test. Global coagulation tests, prothrombotic coagulation proteins (FII/FVII/FVIII/FIX), antithrombotic proteins (antithrombin, protein C/S) and endothelial markers (von-Willebrand-factor and PAI-1) were determined. The Framingham Risk Score was used to estimate the 10-year cardiovascular risk. The impact of breastfeeding duration on coagulation was analyzed using multivariable linear models.

RESULTS: The mean duration of breastfeeding was 11 [7-14] months. Overall, longer duration of breastfeeding was associated with lower cardiovascular risk (Framingham Risk Score, p=0.05) and was negatively associated with FIX (p=0.018). We detected an interaction between previous GDM and breastfeeding duration for FIX (pInteraction=0.017): only in women with GDM history was the duration of breastfeeding negatively associated with FIX activity (p=0.016). This association persisted in statistical models adjusted for age, body-mass index, insulin sensitivity, and C-reactive protein. The duration of breastfeeding was not associated with anticoagulant proteins and endothelial markers.

CONCLUSION: Longer duration of breastfeeding is associated with lower cardiovascular risk and an improved coagulation profile. Women with GDM history appear to benefit particularly from prolonged breastfeeding.

PMID:38487818 | DOI:10.1210/clinem/dgae172