Systematical explorations of forensic feature and population genetic diversity of the Chinese Mongolian group from northwest China via a self-constructed Multi-InDel panel.

This study aimed to investigate the genetic polymorphisms and population characteristics of Chinese Mongolian group from northwest China (NCM) through a self-developed panel including 43 autosomal insertion/deletion (A-InDel) polymorphism genetic markers. Herein, 288 unrelated healthy individuals from the NCM group were employed to obtain the genetic data of 43 A-InDels through multiplex PCR amplification and InDel genotyping using capillary electrophoresis platform. In addition, multiplex population genetic analyses were performed between the NCM group and 27 reference populations. There were no deviations at 43 loci from Hardy-Weinberg equilibrium in the NCM group. The observed heterozygosity (Ho) values ranged from 0.312 8 to 0.559 2, and the combined power of discrimination (CPD) and cumulative probability of exclusion (CPE) values in the NCM group were 0.999 999 999 999 999 998 77 and 0.999 814, respectively. The forensic parameter values indicated that this panel was polymorphic and informative in the NCM group and could be used as an effective tool for forensic personal identification. Furthermore, the results of pairwise genetic distances, principal component analysis, multidimensional scaling analysis, phylogenetic tree construction, and admixture analysis among the NCM group and 27 reference populations revealed that there were closer genetic relationships between the NCM group and East Asian populations, especially Chinese Hui group (CHH) from the northwest China, which is consistent with the geographical location. These present findings contributed to the ongoing genetic explorations and insights into the genetic architecture of the NCM group.

In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets.

Variability of the gastrointestinal tract is rarely reflected in in vitro test protocols but often turns out to be crucial for the oral dosage form performance. In this study, we present a generation method of dissolution profiles accounting for the variability of fasted gastric conditions. The workflow featured 20 biopredictive tests within the physiological variability. The experimental array was constructed with the use of the design of experiments, based on three parameters: gastric pH and timings of the intragastric stress event and gastric emptying. Then, the resulting dissolution profiles served as a training data set for the dissolution process modeling with the machine learning algorithms. This allowed us to generate individual dissolution profiles under a customizable gastric pH and motility patterns. For the first time ever, we used the method to successfully elucidate dissolution properties of two dosage forms: pellet-filled capsules and bare pellets of the marketed dabigatran etexilate product Pradaxa. We showed that the dissolution of capsules was triggered by mechanical stresses and thus was characterized by higher variability and a longer dissolution onset than observed for pellets. Hence, we proved the applicability of the method for the in vitro and in silico characterization of immediate-release dosage forms and, potentially, for the improvement of in vitro-in vivo extrapolation.

Alterations in self-reported sensory gating and interoception in individuals frequently using cannabis.

Background: Cannabis use is associated with altered processing of external (exteroceptive) and internal (interoceptive) sensory stimuli. However, little research exists on whether subjective experiences of these processes are altered in people who frequently use cannabis. Altered exteroception may influence externally oriented attention, whereas interoceptive differences have implications for intoxication, craving, and withdrawal states.Objectives: The goal of the current study was to investigate subjective experiences of exteroceptive sensory gating and interoception in people frequently using cannabis. We hypothesized subjective impairments in sensory gating and elevations in affect-related interoceptive awareness; furthermore, such deviations would relate to cannabis use patterns.Methods: This cross-sectional study of community adults 18-40 years old included 72 individuals (50% female) who used cannabis at least twice a week (not intoxicated during study) and 78 individuals who did not use cannabis (60% female). Participants completed the Sensory Gating Inventory and the Multidimensional Assessment of Interoceptive Awareness-2 surveys. People using cannabis completed surveys on cannabis use patterns. Analyses tested group differences and associations with cannabis use.Results: People using cannabis reported impaired sensory gating (d = 0.37-0.44; all p values < 0.05) and elevations of interoceptive awareness related to detection and affect (d = 0.21-0.61; all p values < 0.05). Problematic cannabis use was associated with increased sensory gating impairments (r = 0.37, p < .05). Interoceptive awareness was unrelated to cannabis use variables.Conclusion: These findings extend literature on subjective experiences of sensory processing in people using cannabis. Findings may inform inclusion of external attentional tendencies and internal bodily awareness in assessments of risk and novel treatment approaches.

Behavior can be decoded across the cortex when individual differences are considered.

Group-level analyses have typically associated behavioral signatures with a constrained set of brain areas. Here we show that two behavioral metrics - reaction time (RT) and confidence - can be decoded across the cortex when each individual is considered separately. Subjects (N=50) completed a perceptual decision-making task with confidence. We built models decoding trial-level RT and confidence separately for each subject using the activation patterns in one brain area at a time after splitting the entire cortex into 200 regions of interest (ROIs). At the group level, we replicated previous results by showing that both RT and confidence could be decoded from a small number of ROIs (12.0% and 3.5%, respectively). Critically, at the level of the individual, both RT and confidence could be decoded from most brain regions even after Bonferroni correction (90.0% and 72.5%, respectively). Surprisingly, we observed that many brain regions exhibited opposite brain-behavior relationships across individuals, such that, for example, higher activations predicted fast RTs in some subjects but slow RTs in others. These results were further replicated in a second dataset. Lastly, we developed a simple test to determine the robustness of decoding performance, which showed that several hundred trials per subject are required for robust decoding. These results show that behavioral signatures can be decoded from a much broader range of cortical areas than previously recognized and suggest the need to study the brain-behavior relationship at both the group and the individual level.

Response to Difficulty Drives Variation in IQ Test Performance.

In a large (N = 300), pre-registered experiment and data analysis model, we find that individual variation in overall performance on Raven's Progressive Matrices is substantially driven by differential strategizing in the face of difficulty. Some participants choose to spend more time on hard problems while others choose to spend less and these differences explain about 42% of the variance in overall performance. In a data analysis jointly predicting participants' reaction times and accuracy on each item, we find that the Raven's task captures at most half of participants' variation in time-controlled ability (48%) down to almost none (3%), depending on which notion of ability is assumed. Our results highlight the role that confounding factors such as motivation play in explaining individuals' differential performance in IQ testing.

Individual-specific postural discomfort prediction using decision tree models.

The objective of the current study was to explore the utilization of the decision tree (DT) algorithm to model posture-discomfort relationships at the individual level. The DT algorithm has the advantage that it makes no assumptions about the distribution of data, is robust in representing non-linear data with noise, and produces white-box models that are interpretable. Individual-level modelling is essential for examining individual-specific postural discomfort perception processes and understanding the inter-individual variability. It also has practical applications, including the development of individual-specific digital human models and more precise and informative population accommodation analysis. Individual-specific DT models were generated using postural discomfort rating data for various seated upper body postures to predict discomfort based on postural and task variables. The individual-specific DT models accurately predicted postural discomfort and revealed large inter-individual variability in the modelling results. DT modelling is expected to greatly facilitate investigating the human discomfort perception process.

Impacts of active mobility on individual health mediated by physical activities.

Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.

Association of Individual Behaviors With Infection Prevention Measures and COVID-19 Development: A Japanese Cross-Sectional Study.

During the COVID-19 pandemic, people often modified their behaviors and performed individual infection control practices despite the uncertain effectiveness of these in preventing COVID-19. A cross-sectional study using a nationwide internet survey (Japan COVID-19 Society Internet Survey) was conducted from September 2022 through October 2022. The questionnaire consisted of individual-level social distancing behaviors and infection prevention measures, and COVID-19 vaccination status. A multivariate logistic regression was performed to determine factors associated with the diagnosis of COVID-19 in the last 2 months of the survey date. In total, 19,296 respondents were selected for the primary analysis. Of 19,296 respondents, those with COVID-19 diagnosed in the last 2 months were 1,909 (9.9%). Factors independently associated with a recent history of COVID-19 were meeting colleagues in person ≧ 1 per week (adjusted odds ratio [aOR] 1.72, 95% confidence interval [CI] 1.36-2.19, P < .001). The response of "never or rarely" to the question of taking out (ie, dining in) foods was marginally associated with a recent history of COVID-19 (aOR 1.27, 95% CI 0.99-1.63, P = .06). Most individual, infection prevention practices and behavioral modifications during the omicron variant phase of the pandemic did not substantially impact COVID-19 prevention in the community.

Individual peak alpha frequency does not index individual differences in inhibitory cognitive control.

Previous work has indicated that individual differences in cognitive performance can be predicted by characteristics of resting state oscillations, such as individual peak alpha frequency (IAF). Although IAF has previously been correlated with cognitive functions, such as memory, attention, or mental speed, its link to cognitive conflict processing remains unexplored. The current work investigated the relationship between IAF and incl-established conflict tasks, Stroop and Navon task, while also controlling for alpha power, theta power, and the 1/f offset of aperiodic broadband activity. In Bayesian analyses on a large sample of 127 healthy participants, we found substantial evidence against the assumption that IAF predicts individual abilities to spontaneously exert cognitive control. Similarly, our findings yielded substantial evidence against links between cognitive control and resting state power in the alpha and theta bands or between cognitive control and aperiodic 1/f offset. In sum, our results challenge frameworks suggesting that an individual's ability to spontaneously engage attentional control networks may be mirrored in resting state EEG characteristics.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

A home environment-moderated model of the influence of ergonomics on individual work performance among Filipino nurse educators working from home during the COVID-19 pandemic: An interaction moderation analysis using structural equation model.

AIM: To determine the influence of ergonomics on individual work performance of nurse educators working at home during the COVID-19 pandemic and to develop a model of the moderating effect of home environment. DESIGN: Cross-sectional, predictive-correlational design. METHODS: Utilizing interaction moderation and structural equation modeling, 214 consecutively-selected educators from nursing schools in the Greater Manila Area, Philippines completed a four-part online survey. RESULTS: Physical, cognitive, and organizational ergonomics positively influenced individual work performance. Home environment had a linear, positive moderation on the effects of physical and cognitive ergonomics on individual work performance but had a negative moderating effect with organizational ergonomics. CONCLUSION: The moderated model underscored the positive effects of ergonomics and the moderating effect of home environment on the individual work performance of nurse educators working at home during the COVID-19 pandemic, and this knowledge can be used in developing appropriate programs, strategies, and policies. IMPACT: The moderated model highlights the need for policies and programs, training and education, and organizational evaluation geared towards promoting healthy workplace and work-life balance among nurse educators transitioning to remote work and online teaching. PATIENT OR PUBLIC CONTRIBUTION: Eligible participants contributed in the data collection with the survey responses.

Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines.

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

Adjuvant radiotherapy versus observation after gross total resection of WHO grade II ependymoma: a systematic review and individual-participant data meta-analysis.

BACKGROUND: The role of adjuvant radiotherapy (RT) after gross total resection (GTR) of the World Health Organization (WHO) grade II ependymoma is controversial. Therefore, we aimed to compare the outcomes of adjuvant RT against observation after GTR of WHO grade II ependymoma. We also compared the outcomes of adjuvant RT against observation after subtotal resection (STR) of WHO grade II ependymoma and performed further subgroup analysis by age and tumor location. METHODS: PubMed and Embase were systematically reviewed for studies published up till 25 November 2022. Studies that reported individual-participant data on patients who underwent surgery followed by adjuvant RT/observation for WHO grade II ependymoma were included. The exposure was whether adjuvant RT was administered, and the outcomes were recurrence and overall survival (OS). Subgroup analyses were performed by the extent of resection (GTR or STR), tumor location (supratentorial or infratentorial), and age at the first surgery (<18 or ≥18 years old). RESULTS: Of the 4,647 studies screened, three studies reporting a total of 37 patients were included in the analysis. Of these 37 patients, 67.6% (25 patients) underwent GTR, and 51.4% (19 patients) underwent adjuvant RT. Adjuvant RT after GTR was not significantly associated with both recurrence (odds ratio =5.50; 95% confidence interval: 0.64-60.80; P=0.12) and OS (P=0.16). Adjuvant RT was also not significantly associated with both recurrence and OS when the cohort was analyzed as a whole and on subgroup analysis by age and tumor location. However, adjuvant RT was associated with significantly longer OS after STR (P=0.03) with the median OS being 6.33 years, as compared to 0.40 years for patients who underwent STR followed by observation. CONCLUSIONS: Based on our meta-analysis of 37 patients, administration of adjuvant RT after GTR was not significantly associated with improvement in OS or recurrence in patients with WHO grade II ependymoma. However, due to the small number of patients included in the analysis, further prospective controlled studies are warranted.

Advanced Nanoencapsulation-Enabled Ultrasensitive Analysis: Unraveling Tumor Extracellular Vesicle Subpopulations for Differential Diagnosis of Hepatocellular Carcinoma via DNA Cascade Reactions.

Tumor-derived extracellular vesicles (tEVs) hold immense promise as potential biomarkers for the precise diagnosis of hepatocellular carcinoma (HCC). However, their clinical translation is hampered by their inherent characteristics, such as small size and high heterogeneity and complex environment, including non-EV particles and normal cell-derived EVs, which prolong separation procedures and compromise detection accuracy. In this study, we devised a DNA cascade reaction-triggered individual EV nanoencapsulation (DCR-IEVN) strategy to achieve the ultrasensitive and specific detection of tEV subpopulations via routine flow cytometry in a one-pot, one-step fashion. DCR-IEVN enables the direct and selective packaging of multiple tEV subpopulations in clinical serum samples into flower-like particles exceeding 600 nm. This approach bypasses the need for EV isolation, effectively reducing interference from non-EV particles and nontumor EVs. Compared with conventional analytical technologies, DCR-IEVN exhibits superior efficacy in diagnosing HCC owing to its high selectivity for tEVs. Integration of machine learning algorithms with DCR-IEVN resulted in differential diagnosis accuracy of 96.7% for the training cohort (n = 120) and 93.3% for the validation cohort (n = 30), effectively distinguishing HCC, cirrhosis, and healthy donors. This strategy offers a streamlined workflow and rapid assay completion and requires only small-volume serum samples and routine clinical devices, facilitating the clinical translation of tEV-based tumor diagnosis.

Association of symptom severity and cerebrospinal fluid alterations in recent onset psychosis in schizophrenia-spectrum disorders - An individual patient data meta-analysis.

Neuroinflammation and blood-cerebrospinal fluid barrier (BCB) disruption could be key elements in schizophrenia-spectrum disorders(SSDs) etiology and symptom modulation. We present the largest two-stage individual patient data (IPD) meta-analysis, investigating the association of BCB disruption and cerebrospinal fluid (CSF) alterations with symptom severity in first-episode psychosis (FEP) and recent onset psychotic disorder (ROP) individuals, with a focus on sex-related differences. Data was collected from PubMed and EMBASE databases. FEP, ROP and high-risk syndromes for psychosis IPD were included if routine basic CSF-diagnostics were reported. Risk of bias of the included studies was evaluated. Random-effects meta-analyses and mixed-effects linear regression models were employed to assess the impact of BCB alterations on symptom severity. Published (6 studies) and unpublished IPD from n = 531 individuals was included in the analyses. CSF was altered in 38.8 % of individuals. No significant differences in symptom severity were found between individuals with and without CSF alterations (SMD = -0.17, 95 %CI -0.55-0.22, p = 0.341). However, males with elevated CSF/serum albumin ratios or any CSF alteration had significantly higher positive symptom scores than those without alterations (SMD = 0.34, 95 %CI 0.05-0.64, p = 0.037 and SMD = 0.29, 95 %CI 0.17-0.41p = 0.005, respectively). Mixed-effects and simple regression models showed no association (p > 0.1) between CSF parameters and symptomatic outcomes. No interaction between sex and CSF parameters was found (p > 0.1). BCB disruption appears highly prevalent in early psychosis and could be involved in positive symptoms severity in males, indicating potential difficult-to-treat states. This work highlights the need for considering BCB breakdownand sex-related differences in SSDs clinical trials and treatment strategies.

Effect of Performance-Based Nonfinancial Incentives on Data Quality in Individual Medical Records of Institutional Births: Quasi-Experimental Study.

BACKGROUND: Despite the potential of routine health information systems in tackling persistent maternal deaths stemming from poor service quality at health facilities during and around childbirth, research has demonstrated their suboptimal performance, evident from the incomplete and inaccurate data unfit for practical use. There is a consensus that nonfinancial incentives can enhance health care providers' commitment toward achieving the desired health care quality. However, there is limited evidence regarding the effectiveness of nonfinancial incentives in improving the data quality of institutional birth services in Ethiopia. OBJECTIVE: This study aimed to evaluate the effect of performance-based nonfinancial incentives on the completeness and consistency of data in the individual medical records of women who availed institutional birth services in northwest Ethiopia. METHODS: We used a quasi-experimental design with a comparator group in the pre-post period, using a sample of 1969 women's medical records. The study was conducted in the "Wegera" and "Tach-armacheho" districts, which served as the intervention and comparator districts, respectively. The intervention comprised a multicomponent nonfinancial incentive, including smartphones, flash disks, power banks, certificates, and scholarships. Personal records of women who gave birth within 6 months before (April to September 2020) and after (February to July 2021) the intervention were included. Three distinct women's birth records were examined: the integrated card, integrated individual folder, and delivery register. The completeness of the data was determined by examining the presence of data elements, whereas the consistency check involved evaluating the agreement of data elements among women's birth records. The average treatment effect on the treated (ATET), with 95% CIs, was computed using a difference-in-differences model. RESULTS: In the intervention district, data completeness in women's personal records was nearly 4 times higher (ATET 3.8, 95% CI 2.2-5.5; P=.02), and consistency was approximately 12 times more likely (ATET 11.6, 95% CI 4.18-19; P=.03) than in the comparator district. CONCLUSIONS: This study indicates that performance-based nonfinancial incentives enhance data quality in the personal records of institutional births. Health care planners can adapt these incentives to improve the data quality of comparable medical records, particularly pregnancy-related data within health care facilities. Future research is needed to assess the effectiveness of nonfinancial incentives across diverse contexts to support successful scale-up.

Derivative survival analyses: Analysis methods to derive survival outcomes for the remainder patient cohort without individual patient data.

It is not uncommon for industry-sponsored randomized controlled trials to publish survival curves/data for the overall patient cohort("A+B") and for a favorable subgroup ("A") pre-specified or post hoc, but not the survival curves/data for the remainder cohort("B"). Consequently, following regulatory approval of the intervention treatment for the overall patient population if the primary endpoint is met, it is common for cancer patients representing the remainder cohort (B) to be treated as per the results of the overall cohort (A+B). To overcome this important issue in clinical decision-making, this study aimed to identify methods to accurately derive the survival curves and/or hazard ratio (95% confidence interval) for the remainder cohort (B), utilizing published curves and hazard ratios (95% confidence intervals) of the overall (A+B) and favorable subgroup (A) cohorts. The analysis methods (method I and method II) presented here, termed "derivative survival analyses," enable accurate assessment of survival outcomes in the remainder cohort without individual patient data.

A preliminary analysis of the effect of individual differences on cognitive performance in young companion dogs.

Many factors influence cognitive performance in dogs, including breed, temperament, rearing history, and training. Studies in working dog populations have demonstrated age-related improvements in cognitive task performance across the first years of development. However, the effect of certain factors, such as age, sex, and temperament, on cognitive performance in puppies has yet to be evaluated in a more diverse population of companion dogs. In this study, companion dogs under 12 months of age were tested once on two tasks purported to measure aspects of executive function: the delayed-search task (DST) and the detour reversal task (DRT). Owners also filled out the Canine Behavioral Assessment and Research Questionnaire (C-BARQ) to evaluate how temperament influenced task performance. Contrary to prior research, performance did not improve with age on either task. However, the lack of age effects was likely the result of small sample sizes and individual differences across other factors influencing performance. Specifically, temperament differences as measured by the C-BARQ subscales for nonsocial fear and excitability predicted task performance on the DST, but the effect of temperament on task performance differed between males and females. Excitability also predicted performance on the DRT, but the effect depended on the age of the dog. In addition, no correlations were observed between task measures, indicating a lack of construct validity. Overall, these findings provide a preliminary analysis of factors that appear to influence cognitive task performance in young companion dogs and highlight suggestions for future research evaluating the impact of individual differences on cognitive performance.

Chd8 haploinsufficiency impacts rearing experience in C57BL/6 mice.

Mutations in CHD8 are one of the highest genetic risk factors for autism spectrum disorder. Studies in mice that investigate underlying mechanisms have shown Chd8 haploinsufficient mice display some trait disruptions that mimic clinical phenotypes, although inconsistencies have been reported in some traits across different models on the same strain background. One source of variation across studies may be the impact of Chd8 haploinsufficiency on maternal-offspring interactions. While differences in maternal care as a function of Chd8 genotype have not been studied directly, a previous study showed that pup survival was reduced when reared by Chd8 heterozygous dams compared with wild-type (WT) dams, suggesting altered maternal care as a function of Chd8 genotype. Through systematic observation of the C57BL/6 strain, we first determined the impact of Chd8 haploinsufficiency in the offspring on WT maternal care frequencies across preweaning development. We next determined the impact of maternal Chd8 haploinsufficiency on pup care. Compared with litters with all WT offspring, WT dams exhibited less frequent maternal behaviors toward litters consisting of offspring with mixed Chd8 genotypes, particularly during postnatal week 1. Dam Chd8 haploinsufficiency decreased litter survival and increased active maternal care also during postnatal week 1. Determining the impact of Chd8 haploinsufficiency on early life experiences provides an important foundation for interpreting offspring outcomes and determining mechanisms that underlie heterogeneous phenotypes.

Evaluation of the demographic characteristics and general health status of earthquake survivors affected by the 2023 Kahramanmaras earthquake; a section from Gaziantep Nurdagi district.

BACKGROUND: An earthquake with a magnitude of 7.7 occurred in Pazarcik District of Turkey at 04.17 on February 6, 2023 and another earthquake of 7.6 occurred at 13.24 on the same day. This is the second largest earthquake to have occurred in Turkey. The aim of this study is to investigate the earthquake-related level of knowledge, attitudes and behaviours, general health and psychological status of survivors who were affected by the 2023 Kahramanmaras Earthquake and who were living in Nurdagi District of Gaziantep after the earthquake. METHODS: Data of 2317 individuals older than 18 years of age who were living in earthquake neighbourhoods, tents and containers in Nurdagi District of Gaziantep were examined. Variables were evaluated to find out the demographic characteristics and general health status of earthquake victims. General Health Questionnaire (GHQ-12) was used to find out psychological states of earthquake victims. RESULTS: The rate of injuries was 14.2% and leg and foot injuries were the most common with 44.2%. The relationship between injury status; and age, marital status, and being trapped under debris was revealed (p < 0.05). Mean GHQ-12 score of the survivors was 3.81 ± 2.81 and 51.9% experienced psychological distress. In the evaluation with logistic regression, it was found that female gender, being injured in the earthquake, loss of first degree and second degree relatives (with a higher rate in loss of first degree relative), having a severely damaged -to be demolished house and having a completely destroyed house were correlated with higher level of psychological distress (p < 0.05). CONCLUSION: General characteristics, injury prevalence and affecting factors of earthquake survivors were evaluated in the present study. Psychological distress was found in victims. For this reason, providing protective and assistive services to fight the destructive effects of earthquake is vital. Accordingly, increasing the awareness of people residing in earthquake zones regarding earthquakes is exceptionally important.