Category: Nevin Manimala

BMC Oral Health. 2023 Jan 24;23(1):39. doi: 10.1186/s12903-023-02743-3.

ABSTRACT

BACKGROUND: Limited data is available regarding the prevalence of dental caries as a chronic disease among adolescents using different caries assessment indices. The aim of this study was to compare and describe the prevalence of dental caries among group of Egyptian students using two caries assessment indices; DMFS and ICDAS II.

METHODS: This descriptive, cross-sectional epidemiological study included 2760 public secondary school students with age range from 15 to 18 years with permanent dentition and good general health. Presence of; retained teeth, congenital or developmental anomalies in the permanent dentition, orthodontic treatments, systematic conditions, smoking and general health problems were considered the exclusion criteria in this study. Participants were selected randomly from 8 public secondary schools in the Great Cairo, Egypt. The examination was achieved by 6 trained and previously calibrated examiners using sets of diagnostic mirrors, compressed air, a WHO probe and cotton rolls. DMFS index and ICDAS II system were used as caries detection methods. In DMFS index; the number of decayed (D), missing (M) and filled (F) surfaces was recorded, while in the ICDAS II index, the assessment of both cavitated and non-cavitated carious, missed and filled teeth with restorations /sealants was recorded. The examiners performed the oral examination using both scoring systems in an alternating manner. The collected data were explored for normality using Kolmogorov-Smirnov and Shapiro-Wilk tests. Chi square test was used to analyze the frequencies.

RESULTS: There was a statistical significant difference between the DMFS and ICDAS II methods results regarding the recorded number of caries affected teeth and cavitated teeth surfaces. The prevalence of dental caries among the investigated secondary school students was (69.56%) and (78.29%) for DMFS and ICDAS II, respectively.

CONCLUSIONS: The prevalence of dental caries among Egyptian adolescent is high. ICDAS scoring system revealed higher caries prevalence values than DMFS method. ICDAS method is the best choice for the preventive goals, while DMFS is sufficient for clinical purposes.

PMID:36694167 | DOI:10.1186/s12903-023-02743-3

BMC Public Health. 2023 Jan 24;23(1):162. doi: 10.1186/s12889-023-15097-w.

ABSTRACT

BACKGROUND: Alcohol abuse is not only harmful to the consumer but may also negatively impact individuals in the drinker’s social environment. Alcohol’s harm to others is vital to consider when calculating the true societal cost of alcohol use. Children of parents who have alcohol use disorder tend to have an elevated risk of negative outcomes regarding, e.g., health, education, and social relationships. Research on the general youth population has established a link between parental drinking and offspring alcohol use. However, there is a lack of knowledge regarding other outcomes, such as health. The current study aimed to investigate the associations between parental drinking and children’s psychological and somatic complaints, and perceived stress.

METHODS: Data were derived from a nationally representative sample, obtained from the 2010 Swedish Level-of-Living survey (LNU). Parents and adolescents (ages 10-18) living in the same households were interviewed independently. The final study sample included 909 adolescents from 629 households. The three outcomes, psychological and somatic complaints and perceived stress, were derived from adolescents’ self-reports. Parents’ self-reports of alcohol use, both frequency and quantity, were used to categorise adolescents as having abstaining, low-consuming, moderate-drinking, or heavy-drinking parents. Control variables included adolescents’ gender, age, family structure, and household socioeconomic status. Linear and binary logistic regression analyses were performed.

RESULTS: Parental heavy drinking was more common among adolescents living in more socioeconomically advantaged households and among adolescents living with two custodial parents or in reconstituted families. Adolescents with heavy-drinking parents reported higher levels of psychological and somatic complaints and had an increased likelihood of reporting stress, compared with those having moderate-drinking parents. These associations remained statistically significant when adjusting for all control variables.

CONCLUSION: The current study’s results show that parental alcohol consumption is associated with poorer offspring adolescent health. Public health policies that aim to reduce parental drinking or provide support to these adolescents may be beneficial. Further studies investigating the health-related outcomes among young people living with heavy-drinking parents in the general population are needed to gain more knowledge about these individuals and to implement adequate public health measures.

PMID:36694162 | DOI:10.1186/s12889-023-15097-w

BMC Pregnancy Childbirth. 2023 Jan 24;23(1):57. doi: 10.1186/s12884-023-05355-5.

ABSTRACT

BACKGROUND: Congenital heart defects (CHDs) are a major global health problem, yet their crucial environmental risk factors are still unclear. We aimed to explore the associations between maternal periconceptional environmental exposures and all CHDs, isolated and multiple CHDs and CHDs subtypes.

METHOD: A case-control study including 675 infants with CHDs and 1545 healthy controls was conducted. Participating mothers who delivered in Guangzhou from October 2019 to November 2021 were recruited. To examine the independent associations between maternal periconceptional environmental exposure and offspring with CHDs, we calculated odds ratios (ORs) and 95% confidence intervals (CIs) using multivariable logistic regression model.

RESULTS: Maternal exposure to living near main roads [adjusted OR (aOR) = 1.94, 95% CI = 1.06-3.56] and housing renovation (aOR = 1.94, 95% CI = 1.03-3.67) during the periconceptional period were positively related to a greater risk of all CHDs, similar results were also found in isolated CHDs rather than multiple CHDs. Additionally, living near main roads was positively associated with secundum atrial septal defect/patent foramen ovale (aOR = 2.65, 95% CI = 1.03-6.81) and housing renovation was strongly positively associated with ventricular septal defect (aOR = 5.08, 95% CI = 2.05-12.60). However, no association was observed between incense burning and family relationships and all CHDs, isolated and multiple CHDs and CHDs subtypes.

CONCLUSION: Living near main roads and housing renovation during the periconceptional period are significantly associated with the increased risks for all CHDs and isolated CHDs. Further study is needed to extend sample size to explore the effects of time and frequency of burning incense and family relationships on CHDs in offspring.

PMID:36694158 | DOI:10.1186/s12884-023-05355-5

Child Adolesc Psychiatry Ment Health. 2023 Jan 24;17(1):14. doi: 10.1186/s13034-023-00561-7.

ABSTRACT

BACKGROUND: Although studies of adults show that pre-existing mental disorders increase risk for COVID-19 infection and severity, there is limited information about this association among youth. Mental disorders in general as well as specific types of disorders may influence the ability to comply with risk-mitigation strategies to reduce COVID-19 infection and transmission.

METHODS: Youth compliance (rated as “Never,” “Sometimes,” “Often,” or “Very often/Always”) with risk mitigation was reported by parents on the CoRonavIruS Health Impact Survey (CRISIS) in January 2021. The sample comprised 314 female and 514 male participants from the large-scale Child Mind Institute Healthy Brain Network, a transdiagnostic self-referred, community sample of children and adolescents (ages 5-21). Responses were summarized using factor analysis of risk mitigation, and their associations with lifetime mental disorders (assessed via structured diagnostic interviews) were identified with linear regression analyses (adjusted for covariates). All analyses used R Project for Statistical Computing for Mac (v.4.0.5).

RESULTS: A two-factor model was the best-fitting solution. Factor 1 (avoidance behaviors) included avoiding groups, indoor settings, and other peoples’ homes; avoidance scores were higher among youth with any anxiety disorder (p = .01). Factor 2 (hygiene behaviors) included using hand sanitizer, washing hands, and maintaining social distance; hygiene scores were lower among youth with ADHD (combined type) (p = .02). Mask wearing was common (90%), did not load on either factor, and was not associated with any mental health disorder.

CONCLUSION AND RELEVANCE: Although most mental disorders examined were not associated with risk mitigation, youth with ADHD characterized by hyperactivity plus inattention may need additional support to consistently engage in risk-mitigation behaviors. Enhancing risk-mitigation strategies among at-risk groups of youth may help reduce COVID-19 infection and transmission.

PMID:36694157 | DOI:10.1186/s13034-023-00561-7

BMC Public Health. 2023 Jan 24;23(1):159. doi: 10.1186/s12889-023-15078-z.

ABSTRACT

BACKGROUND: Disparities in oral health and distinct patterns in service use related to socio-economic status have been shown to exist in the United Kingdom. A number of studies have used the Andersen behavioural model to better understand the factors that influence utilization and thereby inform policies aimed at improving service uptake. As the nature of need may differ across distinct types of patients, however, so too may the distribution of enabling and pre-disposing factors and observed relationships between need, other factors and service use. In this study we compare samples with distinct self-assessed needs in terms of their characteristics and patterns of service use to compare application of the Andersen model to dental services among respondents to a population based survey.

MATERIALS AND METHODS: Data were taken from the Scottish Health Survey, for 2019. Data on service use, oral hygiene habits, perceived treatment need, and socio-demographic characteristics were extracted. Data were analysed using descriptive statistics, t-tests and ordered logistic regression analyses.

RESULTS: Two thousand one hundred forty-eight usable responses were obtained from the survey, 74.95% of the sample had visited the dentist less than a year ago, 11.82% between 1 year and up to 2 years ago, 7.12% between 2 and 5 years ago and 6.10% more than 5 years. Descriptive statistics, t-tests and ordered logistic regression analyses revealed distinct patterns of service use when the sample was partitioned based on perceived treatment need. Specifically those with self-assessed treatment need were older, more likely to smoke, be male and be less likely to have a degree than those who did not. While service use was positively related to age (predisposing) among those who did not have self-assessed treatment need, it was negatively related for those with perceived treatment need. Distinct patterns were also evident with respect to sugar exposure (need) and ease with which time off work could be organised (enabling).

DISCUSSION: The study shows common and distinct patterns of service use related to enabling and predisposing factors across groups differentiated by self-perceived treatment need. If inequalities in health and healthcare use are to be addressed, it is important to understand their origins. Conflation of distinct types of need that may correlate with predisposing and enabling factors complicates this.

CONCLUSION: In applying the Andersen model, it is important to take account of potential differences in the types of need expressed where possible to understand the role of other variables in service use.

PMID:36694144 | DOI:10.1186/s12889-023-15078-z

BMC Genomics. 2023 Jan 24;24(1):41. doi: 10.1186/s12864-022-09098-z.

ABSTRACT

BACKGROUND: Somatic embryogenesis (SE) is one of the most promising processes for large-scale dissemination of elite varieties. However, for many plant species, optimizing SE protocols still relies on a trial and error approach. We report the first global scale transcriptome profiling performed at all developmental stages of SE in coffee to unravel the mechanisms that regulate cell fate and totipotency.

RESULTS: RNA-seq of 48 samples (12 developmental stages × 4 biological replicates) generated 90 million high quality reads per sample, approximately 74% of which were uniquely mapped to the Arabica genome. First, the statistical analysis of transcript data clearly grouped SE developmental stages into seven important phases (Leaf, Dedifferentiation, Primary callus, Embryogenic callus, Embryogenic cell clusters, Redifferentiation and Embryo) enabling the identification of six key developmental phase switches, which are strategic for the overall biological efficiency of embryo regeneration. Differential gene expression and functional analysis showed that genes encoding transcription factors, stress-related genes, metabolism-related genes and hormone signaling-related genes were significantly enriched. Second, the standard environmental drivers used to control SE, i.e. light, growth regulators and cell density, were clearly perceived at the molecular level at different developmental stages. Third, expression profiles of auxin-related genes, transcription factor-related genes and secondary metabolism-related genes were analyzed during SE. Gene co-expression networks were also inferred. Auxin-related genes were upregulated during dedifferentiation and redifferentiation while transcription factor-related genes were switched on from the embryogenic callus and onward. Secondary metabolism-related genes were switched off during dedifferentiation and switched back on at the onset of redifferentiation. Secondary metabolites and endogenous IAA content were tightly linked with their respective gene expression. Lastly, comparing Arabica embryogenic and non-embryogenic cell transcriptomes enabled the identification of biological processes involved in the acquisition of embryogenic capacity.

CONCLUSIONS: The present analysis showed that transcript fingerprints are discriminating signatures of cell fate and are under the direct influence of environmental drivers. A total of 23 molecular candidates were successfully identified overall the 12 developmental stages and can be tested in many plant species to optimize SE protocols in a rational way.

PMID:36694132 | DOI:10.1186/s12864-022-09098-z

Mol Med. 2023 Jan 24;29(1):12. doi: 10.1186/s10020-023-00603-y.

ABSTRACT

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a rare progressive neurodegenerative disease that affects upper and lower motor neurons. As the molecular basis of the disease is still elusive, the development of high-throughput sequencing technologies, combined with data mining techniques and machine learning methods, could provide remarkable results in identifying pathogenetic mechanisms. High dimensionality is a major problem when applying machine learning techniques in biomedical data analysis, since a huge number of features is available for a limited number of samples. The aim of this study was to develop a methodology for training interpretable machine learning models in the classification of ALS and ALS-subtypes samples, using gene expression datasets.

METHODS: We performed dimensionality reduction in gene expression data using a semi-automated preprocessing systematic gene selection procedure using Statistically Equivalent Signature (SES), a causality-based feature selection algorithm, followed by Boosted Regression Trees (XGBoost) and Random Forest to train the machine learning classifiers. The SHapley Additive exPlanations (SHAP values) were used for interpretation of the machine learning classifiers. The methodology was developed and tested using two distinct publicly available ALS RNA-seq datasets. We evaluated the performance of SES as a dimensionality reduction method against: (a) Least Absolute Shrinkage and Selection Operator (LASSO), and (b) Local Outlier Factor (LOF).

RESULTS: The proposed methodology achieved 85.18% accuracy for the classification of cerebellum or frontal cortex samples as C9orf72-related familial ALS, sporadic ALS or healthy samples. Importantly, the genes identified as the most determinative have also been reported as disease-associated in ALS literature. When tested in the evaluation dataset, the methodology achieved 88.89% accuracy for the classification of sporadic ALS motor neuron samples. When LASSO was used as feature selection method instead of SES, the accuracy of the machine learning classifiers ranged from 74.07 to 96.30%, depending on tissue assessed, while LOF underperformed significantly (77.78% accuracy for the classification of pooled cerebellum and frontal cortex samples).

CONCLUSIONS: Using SES, we addressed the challenge of high dimensionality in gene expression data analysis, and we trained accurate machine learning ALS classifiers, specific for the gene expression patterns of different disease subtypes and tissue samples, while identifying disease-associated genes.

PMID:36694130 | DOI:10.1186/s10020-023-00603-y

BMC Bioinformatics. 2023 Jan 24;24(1):27. doi: 10.1186/s12859-022-05125-8.

ABSTRACT

BACKGROUND: Circular RNAs (circRNAs) are a class of covalenty closed non-coding RNAs that have garnered increased attention from the research community due to their stability, tissue-specific expression and role as transcriptional modulators via sequestration of miRNAs. Currently, multiple quantification tools capable of detecting circRNAs exist, yet none delineate circRNA-miRNA interactions, and only one employs differential expression analysis. Efforts have been made to bridge this gap by way of circRNA workflows, however these workflows are limited by both the types of analyses available and computational skills required to run them.

RESULTS: We present nf-core/circrna, a multi-functional, automated high-throughput pipeline implemented in nextflow that allows users to characterise the role of circRNAs in RNA Sequencing datasets via three analysis modules: (1) circRNA quantification, robust filtering and annotation (2) miRNA target prediction of the mature spliced sequence and (3) differential expression analysis. nf-core/circrna has been developed within the nf-core framework, ensuring robust portability across computing environments via containerisation, parallel deployment on cluster/cloud-based infrastructures, comprehensive documentation and maintenance support.

CONCLUSION: nf-core/circrna reduces the barrier to entry for researchers by providing an easy-to-use, platform-independent and scalable workflow for circRNA analyses. Source code, documentation and installation instructions are freely available at https://nf-co.re/circrna and https://github.com/nf-core/circrna .

PMID:36694127 | DOI:10.1186/s12859-022-05125-8

BMC Pregnancy Childbirth. 2023 Jan 24;23(1):61. doi: 10.1186/s12884-023-05344-8.

ABSTRACT

BACKGROUND: Prenatal alcohol exposure (PAE) can result in a range of adverse neonatal outcomes, including Fetal Alcohol Spectrum Disorder (FASD). This systematic review and meta-analysis sought to investigate the effectiveness of brief interventions (BIs) in eliminating or reducing 1) alcohol consumption during pregnancy; and 2) PAE-related adverse neonatal outcomes; and 3) cost-effectiveness of BIs.

METHOD: We conducted a systematic literature search for original controlled studies (randomized control trials (RCTs); quasi-experimental) in any setting, published from 1987 to 2021. The comparison group was no/minimal intervention, where a measure of alcohol consumption was reported. Studies were critically appraised using the Centre for Evidence-based Medicine Oxford critical appraisal tool for RCTs (1). The certainty in the evidence for each outcome was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) (2). Meta-analysis of continuous and binary estimates of effect-size for similar outcome measures for BIs versus control groups were pooled and reported as mean difference (MD) Hedges’ g and odds ratios (ORs), respectively.

RESULTS: In total, 26 studies, all from high income countries, met inclusion criteria. Alcohol abstinence outcome available in 12 studies (n = 2620) found modest effects in favor of BIs conditions by increasing the odds of abstinence by 56% (OR = 1.56, 95% confidence interval (CI) = 1.15-2.13, I² = 46.75%; p = 0.04). BIs effects for reduction in mean drinks/week (Cohen’s d = – 0.21, 95%CI = – 0.78 to 0.36; p = 0.08) and AUDIT scores (g = 0.10, 95%CI = – 0.06 to 0.26; p = 0.17) were not statistically significant. Among seven studies (n = 740) reporting neonatal outcomes, BI receipt was associated with a modest and significant reduction in preterm birth (OR = 0.67, 95% CI = 0.46-0.98, I² = 0.00%; p = 0.58). No statistically significant differences were observed for mean birthweight or lower likelihood of low birth weight (LBW). Certainty in the evidence was rated as ‘low’. No eligible studies were found on cost-effectiveness of BIs.

CONCLUSION: BIs are moderately effective in increasing abstinence during pregnancy and preventing preterm birth. More studies on the effectiveness of BIs are needed from low- and middle-income countries, as well as with younger mothers and with a broader range of ethnic groups.

PMID:36694121 | DOI:10.1186/s12884-023-05344-8

BMC Med Res Methodol. 2023 Jan 24;23(1):22. doi: 10.1186/s12874-022-01829-w.

ABSTRACT

BACKGROUND: The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both. However, the performance of these survival neural network models compared to each other and to PCEs in ASCVD prediction is unknown.

METHODS: In this study, we used 6 cohorts from the Lifetime Risk Pooling Project (with 5 cohorts as training/internal validation and one cohort as external validation) and compared the performance of the PCEs in 10-year ASCVD risk prediction with an all two-way interactions Cox PH model (Cox PH-TWI) and three state-of-the-art neural network survival models including Nnet-survival, Deepsurv, and Cox-nnet. For all the models, we used the same 7 covariates as used in the PCEs. We fitted each of the aforementioned models in white females, white males, black females, and black males, respectively. We evaluated models’ internal and external discrimination power and calibration.

RESULTS: The training/internal validation sample comprised 23216 individuals. The average age at baseline was 57.8 years old (SD = 9.6); 16% developed ASCVD during average follow-up of 10.50 (SD = 3.02) years. Based on 10 × 10 cross-validation, the method that had the highest C-statistics was Deepsurv (0.7371) for white males, Deepsurv and Cox PH-TWI (0.7972) for white females, PCE (0.6981) for black males, and Deepsurv (0.7886) for black females. In the external validation dataset, Deepsurv (0.7032), Cox-nnet (0.7282), PCE (0.6811), and Deepsurv (0.7316) had the highest C-statistics for white male, white female, black male, and black female population, respectively. Calibration plots showed that in 10 × 10 validation, all models had good calibration in all race and sex groups. In external validation, all models overestimated the risk for 10-year ASCVD.

CONCLUSIONS: We demonstrated the use of the state-of-the-art neural network survival models in ASCVD risk prediction. Neural network survival models had similar if not superior discrimination and calibration compared to PCEs.

PMID:36694118 | DOI:10.1186/s12874-022-01829-w