Sexual Maturation, Attitudes towards Sexual Maturity, and Body Esteem in Elementary-School Children

PURPOSE: The purpose of this study is to evaluate sexual maturation, attitudes toward sexual maturity, and body esteem in the sexual development of Korean elementary-school boys and girls. METHODS: A descriptive cross-sectional study was conducted with 399 fifth and sixth graders (192 boys and 207 girls). The data were analysed with a χ2 test, t-test, and Pearson correlation coefficients. RESULTS: Among the 207 girls, 70.5% had pubic hair growth, 68.1% had breast development, and 56.0% had a menstrual period. In boys, 59.4% of the 192 subjects experienced the development of external genitalia and 52.6% had pubic hair growth. Sexual maturation was related to grade (boys, t=7.07, p=.008; girls, t=12.76, p < .001), age (t=−2.20, p=.030; t=−4.11, p < .001), height (t=−5.16, p < .001; t=−7.52, p < .001), and weight (t=−2.89, p=.004; t=−5.19, p < .001) in both boys and girls. Girls were more likely to have sexual maturity than boys (χ2=22.29, p < .001). Boys showed more positive attitudes toward sexual maturity (t=2.10, p=.036) and higher body esteem (t=2.12, p=.035) than girls. CONCLUSION: This study shows that sexual maturation, attitude toward sexual maturity, and body esteem in sexual development differ between boys and girls. The findings indicate that it is necessary to develop a tailored sex-education program according to the sex of elementary-school children

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design setting and participants: Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. Main outcomes and measures: For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z1.96) scores. Results: CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADS SA showed significant but weak associations (|β|<0.09; P FDR <0.05) with positive symptoms and IQ. Conclusions and relevance: The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk. Key points: Question: Is the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation?Findings: In this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder.Meaning: The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.</p

Normative modeling of brain morphometry in clinical high risk for psychosis

Importance The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design, Setting, and Participants This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)–derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. Main Outcomes and Measures For each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z &lt; −1.96) or supranormal (z &gt; 1.96) scores. Results Among 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the mean (SD) age was 22.32 (4.95) years. Individuals with CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z scores, and all ADS values. For any given region, the proportion of individuals with CHR-P who had infranormal or supranormal values was low (up to 153 individuals [&lt;11.42%]) and similar to that of healthy individuals (&lt;115 individuals [&lt;9.30%]). Individuals with CHR-P who converted to a psychotic disorder had a higher percentage of infranormal values in temporal regions compared with those who did not convert (7.01% vs 1.38%) and healthy individuals (5.10% vs 0.89%). In the CHR-P group, only the ADS SA was associated with positive symptoms (β = −0.08; 95% CI, −0.13 to −0.02; P = .02 for false discovery rate) and IQ (β = 0.09; 95% CI, 0.02-0.15; P = .02 for false discovery rate). Conclusions and Relevance In this case-control study, findings suggest that macroscale neuromorphometric measures may not provide an adequate explanation of psychosis risk

Chemical vapor deposition of edge-on oriented 2D conductive metal-organic framework thin films

2

The prognostic value of a combined immune score in tumor and immune cells assessed by immunohistochemistry in triple-negative breast cancer

Abstract Background This study aimed to develop a novel combined immune score (CIS)-based model assessing prognosis in triple-negative breast cancer (TNBC). Methods The expression of eight immune markers (PD-1, PD-L1, PD-L2, IDO, TIM3, OX40, OX40L, and H7-H2) was assessed with immunohistochemistry on the tumor cells (TCs) and immune cells (ICs) of 227 TNBC cases, respectively, and subsequently associated with selected clinicopathological parameters and survival. Data retrieved from The Cancer Genome Atlas (TCGA) were further examined to validate our findings. Results All immune markers were often expressed in TCs and ICs, except for PD-1 which was not expressed in TCs. In ICs, the expression of all immune markers was positively correlated between one another, except between PD-L1 and OX40, also TIM3 and OX40. In ICs, PD-1, PD-L1, and OX40L positive expression was associated with a longer progression-free survival (PFS; p = 0.040, p = 0.020, and p = 0.020, respectively). In TCs, OX40 positive expression was associated with a shorter PFS (p = 0.025). Subsequently, the TNBC patients were classified into high and low combined immune score groups (CIS-H and CIS-L), based on the expression levels of a selection of biomarkers in TCs (TCIS-H or TCIS-L) and ICs (ICIS-H or ICIS-L). The TCIS-H group was significantly associated with a longer PFS (p < 0.001). Furthermore, the ICIS-H group was additionally associated with a longer PFS (p < 0.001) and overall survival (OS; p = 0.001), at significant levels. In the multivariate analysis, both TCIS-H and ICIS-H groups were identified as independent predictors of favorable PFS (p = 0.012 and p = 0.001, respectively). ICIS-H was also shown to be an independent predictor of favorable OS (p = 0.003). The analysis of the mRNA expression data from TCGA also validated our findings regarding TNBC. Conclusion Our novel TCIS and ICIS exhibited a significant prognostic value in TNBC. Additional research would be needed to strengthen our findings and identify the most efficient prognostic and predictive biomarkers for TNBC patients

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings

Remote heteroepitaxy of GaN microrod heterostructures for deformable light-emitting diodes and wafer recycle

There have been rapidly increasing demands for flexible lighting apparatus, and micrometer-scale light-emitting diodes (LEDs) are regarded as one of the promising lighting sources for deformable device applications. Herein, we demonstrate a method of creating a deformable LED, based on remote heteroepitaxy of GaN microrod (MR) p-n junction arrays on c-Al2O3 wafer across graphene. The use of graphene allows the transfer of MR LED arrays onto a copper plate, and spatially separate MR arrays offer ideal device geometry suitable for deformable LED in various shapes without serious device performance degradation. Moreover, remote heteroepitaxy also allows the wafer to be reused, allowing reproducible production of MR LEDs using a single substrate without noticeable device degradation. The remote heteroepitaxial relation is determined by high-resolution scanning transmission electron microscopy, and the density functional theory simulations clarify how the remote heteroepitaxy is made possible through graphene.11Ysciescopu

Anti-inflammatory and Antibacterial Effects of Covalently Attached Biomembrane-Mimic Polymer Grafts on Gore-Tex Implants

Expanded polytetrafluoroethylene (ePTFE), also known as Gore-Tex, is widely used as an implantable biomaterial in biomedical applications because of its favorable mechanical properties and biochemical inertness. However, infection and inflammation are two major complications with ePTFE implantations, because pathogenic bacteria can inhabit the microsized pores, without clearance by host immune cells, and the limited biocompatibility can induce foreign body reactions. To minimize these complications, we covalently grafted a biomembrane-mimic polymer, poly­(2-methacryloyloxylethyl phosphorylcholine) (PMPC), by partial defluorination followed by UV-induced polymerization with cross-linkers on the ePTFE surface. PMPC grafting greatly reduced serum protein adsorption as well as fibroblast adhesion on the ePTFE surface. Moreover, the PMPC-grafted ePTFE surface exhibited a dramatic inhibition of the adhesion and growth of <i>Staphylococcus aureus</i>, a typical pathogenic bacterium in ePTFE implants, in the porous network. On the basis of an analysis of immune cells and inflammation-related factors, i.e., transforming growth factor-β (TGF-β) and myeloperoxidase (MPO), we confirmed that inflammation was efficiently alleviated in tissues around PMPC-grafted ePTFE plates implanted in the backs of rats. Covalent PMPC may be an effective strategy for promoting anti-inflammatory and antibacterial functions in ePTFE implants and to reduce side effects in biomedical applications of ePTFE