Tag: nevin manimala
Schizophr Bull. 2023 Jun 15:sbad082. doi: 10.1093/schbul/sbad082. Online ahead of print.
ABSTRACT
BACKGROUND: Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ.
STUDY DESIGN: GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects.
STUDY RESULTS: The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms.
CONCLUSIONS: Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.
PMID:37319439 | DOI:10.1093/schbul/sbad082
J Occup Environ Hyg. 2023 Jun 15:1-10. doi: 10.1080/15459624.2023.2226180. Online ahead of print.
ABSTRACT
Widespread disease outbreaks can result in prolonged wear times of National Institute for Occupational Safety and Health Approved N95 filtering facepiece respirators by healthcare personnel. Prolonged wear times of these devices can cause the development of various adverse facial skin conditions. Healthcare personnel have been reported to apply “skin protectants” to the face to reduce pressure and friction of respirators. Because tight-fitting respirators rely on a good face seal to protect the wearer, it is important to understand if fit is affected when skin protectants are used. This laboratory pilot study included 10 volunteers who performed quantitative fit tests to evaluate respirator fit while wearing skin protectants. Three N95 filtering facepiece respirator models and three skin protectants were evaluated. Three replicate fit tests were performed for each combination of subject, skin protectant (including a control condition of no protectant), and respirator model. Fit Factor (FF) was affected differently by the combination of protectant type and respirator model. The main effects of protectant type and respirator model were both significant (p <0.001); additionally, their interaction was significant (p = 0.02), indicating FF is affected by the combined effects of protectant type and respirator model. Compared to the control condition, using a bandage-type or surgical tape skin protectant decreased the odds of passing the fit test. Using a barrier cream skin protectant also decreased the odds of passing the fit test across all models compared to the control condition; however, the probability of passing a fit test was not statistically significantly different from the control condition (p = 0.174). These results imply that all three skin protectants reduced mean fit factors for all N95 filtering facepiece respirator models tested. The bandage-type and surgical tape skin protectants both reduced fit factors and passing rates to a greater degree than the barrier cream. Respirator users should follow respirator manufacturers’ guidance on the use of skin protectants. If a skin protectant is to be worn with a tight-fitting respirator, the fit of the respirator should be evaluated with the skin protectant applied before use in the workplace.
PMID:37319423 | DOI:10.1080/15459624.2023.2226180
Issues Ment Health Nurs. 2023 Jun 15:1-15. doi: 10.1080/01612840.2023.2212780. Online ahead of print.
ABSTRACT
The purpose of this convergent mixed methods interprofessional education (IPE) pilot project was to help health profession students gain valuable insight about the experiences of people living with mental illness, to help them have a better understanding of person-centered care and have greater knowledge about the importance of interprofessional collaboration. A developmental workgroup which consisted of mental health consumers, four interdisciplinary students, and our team developed and implemented a virtual Mental Health World Café IPE event. Twelve other students attended the World Café event. A paired sample t-test was used to examine group differences between pre- and post-test scores for the Interprofessional Socialization and Valuing Scale and the Texas AHEC Survey measures among the four student leaders and the 12 student participants of the virtual Mental Health World Cafe. We conducted individual interviews with the four student leaders and collected reflective journals from the 12 students who attended the World Café event. We examined to what extent the statistically significant quantitative results supported the qualitative results separately for the student leaders and for the student participants of the virtual World Café. We also examined how both the quantitative and qualitative findings aligned with the key components of the Patient-Centered Care in Interprofessional Collaborative Practice Model. While the project allowed the students to reflect upon how they may apply the principles of person-centered care and interprofessional collaboration, the impact of the consumers on the student’s experiences was profound and resulted in widespread engagement of the students who attended the event.
PMID:37319417 | DOI:10.1080/01612840.2023.2212780
Acta Odontol Scand. 2023 Jun 15:1-6. doi: 10.1080/00016357.2023.2223715. Online ahead of print.
ABSTRACT
OBJECTIVE: The aim of this in-vitro study was to investigate the tactile assessment ability at the implant impression-taking stage.
METHODS: Thirty clinicians (18 novices, 12 experts) were included for a tactile fit assessment by using a used/new probe (tip diameter 100 µm/20 µm). Six implant replicas and related impression copings of two internal connection implant systems were used, each with a perfect fit (0 µm) and defined vertical micro gaps of 8, 24, 55, 110 and 220 µm at the interface. Statistical analysis was performed using descriptive methods and non-parametric tests with a focus on specificity (ability to detect perfect fit), sensitivity (ability to detect misfit), and predictive values. P-values <5% were considered statistically significant.
RESULTS: The tactile assessment showed a mean total sensitivity for the Straumann and Nobel Biocare systems of 83% and 80% with a used probe, and 91% and 92% with a new probe, respectively. The mean total specificities were 33% and 20% with a used probe and 17% and 3% with a new probe, respectively. No statistical significance was observed between novice and expert clinicians concerning their tactile assessment ability.
CONCLUSIONS: The ability to detect a perfect fit (specificity) with a probe was very poor for both implant systems and impaired with the use of a new probe. The use of a new probe improved the gap detection ability (sensitivity) significantly at the expense of the specificity. A combination of additional chairside techniques with training and calibration could improve clinicians’ ability to correctly assess the fit/misfit at the implant-abutment interface.
PMID:37319413 | DOI:10.1080/00016357.2023.2223715
Int J Adolesc Med Health. 2023 Jun 16. doi: 10.1515/ijamh-2023-0011. Online ahead of print.
ABSTRACT
OBJECTIVES: To evaluate the association of health-related quality of life (HRQOL) with physical activity, food consumption, sleep duration and screen time in children and adolescents.
METHODS: Cross-sectional study with 268 students aged 10-17 years from a public school in Brazil. The outcome variable was HRQOL score, evaluated by the Pediatric Quality of Life Inventory™ (PedsQL™). Exposure variables were habitual physical activity, food consumption, sleep duration, and screen time. A general linear model was used to estimate age-adjusted means and 95 % confidence interval (95 % CI) of HRQOL scores, and a multivariable analysis of variance to identify factors associated with lower/higher HRQOL scores. The study was approved by the Human Research Ethics Committee of the Pontifical Catholic University of Campinas.
RESULTS: Overall HRQOL score was 70.3 (95 % CI: 68.0-72.6). Multivariable analyses showed lower HRQOL scores for those adolescents who: 1-were physically inactive (67.3; p=0.014); 2-sleep less than 6 h per night (66.8; p=0.003); 3-eat fruits and vegetables less than five days/week (68.9; p=0.027); and 4-eat fast food twice/week or more (68.6; p=0.036) when compared to their opposite groups. Screen time was not statistically significantly associated with total HRQOL.
CONCLUSIONS: The joint association found in our study suggests that at least three habits must change to improve the HRQOL of children and adolescents (physical activity, food consumption, and sleep duration). Therefore, interventions in schools to promote a healthy lifestyle to achieve a better HRQOL should include a multidisciplinary team to properly guide children and adolescents about these habits simultaneously.
PMID:37319352 | DOI:10.1515/ijamh-2023-0011
J Perinat Neonatal Nurs. 2023 Jun 15. doi: 10.1097/JPN.0000000000000742. Online ahead of print.
ABSTRACT
BACKGROUND: Nursing and midwifery students do not feel adequately prepared during their clinical training to support women who breastfeed, demanding more effective communication skills and knowledge.
AIM: The aim was to evaluate changes in students’ breastfeeding knowledge.
METHODS: This was a mixed-methods quasi-experimental design. Forty students voluntarily participated. Using a 1:1 ratio, 2 groups were randomly created and completed the validated questionnaire ECoLaE (pre-post). The educational program consisted of focus groups, a clinical simulation, and a visit to the local breastfeeding association.
FINDINGS: The control group’s posttest scores ranged from 6 to 20 (mean = 13.1, standard deviation [SD] = 3.0). The intervention group ranged from 12 to 20 (mean = 17.3, SD = 2.3). A Student’s t test for independence samples was calculated (P < .005, t = 4.5, median = 4.2). The intervention group had a mean difference of 10 points in improvement (mean =10.53, SD = 2.20, min = 7, max = 14), whereas the control group had a mean of 6 points (mean = 6.80, SD = 3.03, min = 3, max = 13). The multiple linear regression explained the intervention’s effect. The regression model had statistical significance (F = 4.87, P = 0.004), with an adjusted R2 = 0.31. The linear regression between the posttest scores and group variables after adjusting by age showed an increment of 4.1 points in the intervention posttest scores (P < .005, 95% confidence interval [CI] = 2.1-6.1).
CONCLUSIONS: The educational program “Engage in breaking the barriers to breastfeeding” improved nursing students’ knowledge.
PMID:37319350 | DOI:10.1097/JPN.0000000000000742
J Chem Inf Model. 2023 Jun 15. doi: 10.1021/acs.jcim.3c00557. Online ahead of print.
ABSTRACT
The initial phases of drug discovery – in silico drug design – could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines – so far an unmet and crucial goal – will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.
PMID:37319347 | DOI:10.1021/acs.jcim.3c00557
Environ Sci Technol. 2023 Jun 15. doi: 10.1021/acs.est.3c01256. Online ahead of print.
ABSTRACT
Disposal of industrial and hazardous waste in the ocean was a pervasive global practice in the 20th century. Uncertainty in the quantity, location, and contents of dumped materials underscores ongoing risks to marine ecosystems and human health. This study presents an analysis of a wide-area side-scan sonar survey conducted with autonomous underwater vehicles (AUVs) at a dump site in the San Pedro Basin, California. Previous camera surveys located 60 barrels and other debris. Sediment analysis in the region showed varying concentrations of the insecticidal chemical dichlorodiphenyltrichloroethane (DDT), of which an estimated 350-700 t were discarded in the San Pedro Basin between 1947 and 1961. A lack of primary historical documents specifying DDT acid waste disposal methods has contributed to the ambiguity surrounding whether dumping occurred via bulk discharge or containerized units. Barrels and debris observed during previous surveys were used for ground truth classification algorithms based on size and acoustic intensity characteristics. Image and signal processing techniques identified over 74,000 debris targets within the survey region. Statistical, spectral, and machine learning methods characterize seabed variability and classify bottom-type. These analytical techniques combined with AUV capabilities provide a framework for efficient mapping and characterization of uncharted deep-water disposal sites.
PMID:37319331 | DOI:10.1021/acs.est.3c01256