Neuro-immune communication at the core of craving-associated brain structural network reconfiguration in methamphetamine users.

Methamphetamine (MA) use disorder is a chronic neurotoxic brain disease characterized by a high risk of relapse driven by intense cravings. However, the neurobiological signatures of cravings remain unclear, limiting the effectiveness of various treatment methods. Diffusion MRI (dMRI) scans from 62 MA users and 57 healthy controls (HC) were used in this study. The MA users were longitudinally followed up during their period of long-term abstinence (duration of long-term abstinence: 347.52±99.25 days). We systematically quantified the control ability of each brain region for craving-associated state transitions using network control theory from a causal perspective. Craving-associated structural alterations (CSA) were investigated through multivariate group comparisons and biological relevance analysis. The neural mechanisms underlying CSA were elucidated using transcriptomic and neurochemical analyses. We observed that long-term abstinence-induced structural alterations significantly influenced the state transition energy involved in the cognitive control response to external information, which correlated with changes in craving scores (r ∼ 0.35, P <0.01). Our causal network analysis further supported the crucial role of the prefrontal cortex (PFC) in craving mechanisms. Notably, while the PFC is central to the craving, the CSAs were distributed widely across multiple brain regions (PFDR<0.05), with strong alterations in somatomotor regions (PFDR<0.05) and moderate alterations in high-level association networks (PFDR<0.05). Additionally, transcriptomic, chemical compounds, cell-type analyses, and molecular imaging collectively highlight the influence of neuro-immune communication on human craving modulation. Our results offer an integrative, multi-scale perspective on unraveling the neural underpinnings of craving and suggest that neuro-immune signaling may be a promising target for future human addiction therapeutics.

Prevalence of Tourette syndrome among children and adolescents in the United States, 2016-2022.

BACKGROUND: Tourette syndrome (TS) is a neurodevelopmental disorder. The prevalence of TS in 2016-2017 has been reported; however, little is known about the current prevalence and trend in children and adolescents with TS. This study aimed to estimate the prevalence and trend of Tourette syndrome (TS) among US children and adolescents aged 0-17 years from 2016 to 2022. METHODS: We analyzed data from a nationally representative sample of 278,472 children and adolescents aged 0-17 years who participated in the 2016-2022 National Survey of Children's Health (NSCH), a nationwide, population-based, cross-sectional survey of US children and adolescents. TS was defined as the affirmative response in the questionnaire completed by a parent or guardian. RESULTS: Among the 278,472 children and adolescents enrolled, 754 had been diagnosed with TS, with an overall prevalence of 0.23% in all children and adolescents aged 0-17 years. The weighted prevalence by age group was lower than 0.01% in children aged 0-2 years, 0.05% in children aged 3-5 years, 0.28% in children aged 6-11 years, and 0.38% in adolescents aged 12-17 years. There were significant sex and racial/ethnic differences in the overall prevalence of diagnosed TS (i.e., 0.35% in boys and 0.11% in girls, 0.22% in Hispanics, 0.28% in non-Hispanic whites and 0.16% in non-Hispanic blacks). There was no significant change in the estimated prevalence of TS from 2016 to 2022. CONCLUSION: Based on nationally representative data, this study found that the national prevalence of TS among the US children and adolescents differed by sex and race/ethnicity but remained stable from 2016 to 2022.

Prognostic and predictive factors in advanced upper gastrointestinal cancer treated with immune checkpoint inhibitors: a systematic review and meta-analysis of the current evidence.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown encouraging treatment efficacy for upper gastrointestinal cancers (UGICs). However, durable clinical responses only existed in a minority of patients. We evaluated evidence predicting survival benefits to identify the optimal population followed by ICI-based therapy. METHODS: A comprehensive search was performed using PubMed, Embase, Cochrane Library, and Web of Science to identify clinical trials for UGICs with ICI-based therapy. The outcomes were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The quality of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation System (GRADE). RESULTS: Thirty-six studies comprising 12,440 patients were included for quantitative synthesis. Patients with PD-L1-positive (OR = 2.08, p < 0.00001), EBV+ (OR = 8.47, p = 0.003) tumors were more likely to respond to ICI treatment. Moreover, OS was significantly improved with the statistical subgroup difference concerning sex (p = 0.02) and region (p = 0.02). An exploratory subgroup analysis showed significantly improved OS with ICI plus chemotherapy in patients with CPS ≥ 10 (HR = 0.66, p = 0.001) and CPS ≥ 1 (HR = 0.75, p < 0.00001). CONCLUSION: UGIC patients with PD-L1-positive, EBV + status are associated with a better therapeutic response to ICI-based therapy. The male patients and Asian patients could derive more survival benefits following ICI treatment than female and non-Asian ones. A combination of prognostic and predictive factors was suggested to help guide immunotherapy decision-making in UGIC patients.

Toward Real-World Super Resolution With Adaptive Self-Similarity Mining.

Despite efforts to construct super-resolution (SR) training datasets with a wide range of degradation scenarios, existing supervised methods based on these datasets still struggle to consistently offer promising results due to the diversity of real-world degradation scenarios and the inherent complexity of model learning. Our work explores a new route: integrating the sample-adaptive property learned through image intrinsic self-similarity and the universal knowledge acquired from large-scale data. We achieve this by uniting internal learning and external learning by an unrolled optimization process. With the merits of both, the tuned fully-supervised SR models can be augmented to broadly handle the real-world degradation in a plug-and-play style. Furthermore, to promote the efficiency of combining internal/external learning, we apply an attention-based weight-updating method to guide the mining of self-similarity, and various data augmentations are adopted while applying the exponential moving average strategy. We conduct extensive experiments on real-world degraded images and our approach outperforms other methods in both qualitative and quantitative comparisons. Our project is available at: https://github.com/ZahraFan/AdaSSR/.

M2Trans: Multi-Modal Regularized Coarse-to-Fine Transformer for Ultrasound Image Super-Resolution.

Ultrasound image super-resolution (SR) aims to transform low-resolution images into high-resolution ones, thereby restoring intricate details crucial for improved diagnostic accuracy. However, prevailing methods relying solely on image modality guidance and pixel-wise loss functions struggle to capture the distinct characteristics of medical images, such as unique texture patterns and specific colors harboring critical diagnostic information. To overcome these challenges, this paper introduces the Multi-Modal Regularized Coarse-to-fine Transformer (M2Trans) for Ultrasound Image SR. By integrating the text modality, we establish joint image-text guidance during training, leveraging the medical CLIP model to incorporate richer priors from text descriptions into the SR optimization process, enhancing detail, structure, and semantic recovery. Furthermore, we propose a novel coarse-to-fine transformer comprising multiple branches infused with self-attention and frequency transforms to efficiently capture signal dependencies across different scales. Extensive experimental results demonstrate significant improvements over state-of-the-art methods on benchmark datasets, including CCA-US, US-CASE, and our newly created dataset MMUS1K, with a minimum improvement of 0.17dB, 0.30dB, and 0.28dB in terms of PSNR. Our code and dataset will be available at: https://github.com/eezkni/M2Trans.

Unveiling causal relationships between addiction phenotypes and inflammatory cytokines: insights from bidirectional mendelian randomization and bibliometric analysis.

Observational studies have suggested associations between multiple inflammatory factors and tobacco and alcohol use, but establishing causation is challenging in epidemiological investigations. We employed genetic association data about the circulating levels of 41 cytokines obtained from the genome-wide association study (GWAS), which contained 8293 Finnish participants. Genetic data on 5 substance use phenotypes were obtained from the GWAS dataset containing 1.2 million European subjects. Then, we conducted a bidirectional mendelian randomization (MR) study. The forward results indicated that smoking cessation was positively correlated with hepatocyte growth factor (HGF), interleukin-10 (IL-10), and stem cell factor (SCF); cigarettes per day was a risk factor associated with high expression in stromal cell-derived factor 1α (SDF-1 A), interferon-γ (IFN-G), IL-4, and granulocyte colony-stimulating factor (G-CSF); drinks per week and smoking initiation were risk factors respectively correlated with reduced HGF and IL-2RA levels. During inverse MR analysis, the findings revealed that both IL-16 and IL-18 increased the risk of cigarettes per day; macrophage inflammatory protein-1ß (MIP-1B) and tumor necrosis factor-ß (TNF-B) inhibited and promoted smoking cessation, respectively; macrophage colony-stimulating factor (M-CSF) elevated the risk of drinks per week, while interferon inducible protein 10 (IP-10) had a contrary role; IL-7 and M-CSF respectively prolonged and shortened age of initiation of regular smoking. This study provides genetic proof supporting a causal relationship between various inflammatory factors and addiction phenotypes. Further comprehensive investigations are required to uncover underlying biological mechanisms. In addition, bibliometric studies have shown that oxidative stress is one of the most important orientations in alcohol and tobacco addiction research, where an in-depth investigation of its pro-inflammatory mechanisms would facilitate the development of potential therapeutic biological targets and drugs.

Differences in the prevalence of allergy and asthma among US children and adolescents during and before the COVID-19 pandemic.

BACKGROUND: The increasing prevalence of allergies and asthma has led to a growing global socioeconomic burden. Since the outbreak of the COVID-19 pandemic, the health and lifestyles of children and adolescents have changed dramatically. It's unclear how this shift impacted allergy and asthma, with limited studies addressing this question. We aim to explore the difference of the prevalence of allergies and asthma among US children and adolescents during and before the COVID-19 pandemic using a nationally representative sample of US children and adolescents. METHODS: This cross-sectional study included 31,503 participants in the National Health Interview Survey (NHIS) between 2018 and 2021. Allergies and asthma were defined on an affirmative response in the questionnaire by a parent or guardian. Chi-square tests were used to compare baseline characteristics with allergies and asthma for categorical variables. Differences in prevalence during and before the COVID-19 pandemic were estimated with weighted logistic regression, adjusting for demographic factors. Interaction analyses explored variations across strata. RESULTS: In US children and adolescents aged 0 to 17, prevalence of any allergy was 26.1% (95% CI, 24.8%- 27.4%) in 2018 and 27.1% (95% CI, 25.9%- 28.2%) in 2021. Thereinto, in 2018, prevalence of respiratory allergies, food allergies and skin allergies were 14.0% (95% CI, 13.1%- 15.0%), 6.5% (95% CI, 5.8%- 7.1%) and 12.6% (95% CI, 11.6%- 13.5%), respectively, and in 2021, 18.8% (95% CI, 17.8%- 19.9%), 5.8% (95% CI, 5.2%- 6.4%) and 10.7% (95% CI, 9.9%- 11.5%), respectively. And prevalence of asthma was 11.1% (95% CI, 10.5%- 11.7%) in 2018-2019 and 9.8% (95% CI, 9.2%- 10.4%) in 2020-2021. Prevalence of respiratory allergies, skin allergies and asthma during and before the COVID-19 pandemic in children and adolescents had statistically significant differences. The differences persisted after adjusting for demographic and socioeconomic variables. CONCLUSION: Prevalence of respiratory allergies increased and the prevalence of both skin allergies and asthma decreased among US children and adolescents during the COVID-19 pandemic compared with the pre-COVID-19 pandemic. Further research is required to explore the association between allergic diseases and the pandemic, with a particular emphasis on the impact of lifestyle changes resulting from measures to prevent COVID-19 infection.

An Interpretable System for Screening the Severity Level of Retinopathy in Premature Infants Using Deep Learning.

Accurate evaluation of retinopathy of prematurity (ROP) severity is vital for screening and proper treatment. Current deep-learning-based automated AI systems for assessing ROP severity do not follow clinical guidelines and are opaque. The aim of this study is to develop an interpretable AI system by mimicking the clinical screening process to determine ROP severity level. A total of 6100 RetCam Ⅲ wide-field digital retinal images were collected from Guangdong Women and Children Hospital at Panyu (PY) and Zhongshan Ophthalmic Center (ZOC). A total of 3330 images of 520 pediatric patients from PY were annotated to train an object detection model to detect lesion type and location. A total of 2770 images of 81 pediatric patients from ZOC were annotated for stage, zone, and the presence of plus disease. Integrating stage, zone, and the presence of plus disease according to clinical guidelines yields ROP severity such that an interpretable AI system was developed to provide the stage from the lesion type, the zone from the lesion location, and the presence of plus disease from a plus disease classification model. The ROP severity was calculated accordingly and compared with the assessment of a human expert. Our method achieved an area under the curve (AUC) of 0.95 (95% confidence interval [CI] 0.90-0.98) in assessing the severity level of ROP. Compared with clinical doctors, our method achieved the highest F1 score value of 0.76 in assessing the severity level of ROP. In conclusion, we developed an interpretable AI system for assessing the severity level of ROP that shows significant potential for use in clinical practice for ROP severity level screening.

Synthesis of Multifunctional Organic Molecules via Michael Addition Reaction to Manage Perovskite Crystallization and Defect.

Additive engineering plays a pivotal role in achieving high-quality light-absorbing layers for high-performance and stable perovskite solar cells (PSCs). Various functional groups within the additives exert distinct regulatory effects on the perovskite layer. However, few additive molecules can synergistically fulfill the dual functions of regulating crystallization and passivating defects. Here, we custom-synthesized 2-ureido-4-pyrimidone (UPy) organic small molecules with diverse functional groups as additives to modulate crystallization and defects in perovskite films via the Michael addition reaction. Theoretical and experimental investigations demonstrate that the -OH groups in UPy exhibit significant effects in fixing uncoordinated Pb2+ ions, passivation of lead-iodide antisite defects, alleviating hysteresis, and reducing non-radiative recombination. Furthermore, the enhanced C=O and -NH2 motifs interact with the A-site cation via hydrogen bonding, which relieves residual strain and adjusts crystal orientation. This strategy effectively controls perovskite crystallization and passivates defects, ultimately enhancing the quality of perovskite films. Consequently, the open-circuit voltage of the UPy-based p-i-n PSCs reaches 1.20 V, and the fill factor surpasses 84 %. The champion device delivers a power conversion efficiency of 25.75 %. Remarkably, the unencapsulated device maintained 96.9 % and 94.5 % of its initial efficiency following 3,360 hours of dark storage and 1,866 hours of 1-sun illumination, respectively.

Downregulation of tRF-Cys-GCA-029 by hyperglycemia promotes tumorigenesis and glycolysis of diabetic breast cancer through upregulating PRKCG translation.

BACKGROUND: Diabetes mellitus (DM) affects up to one-third of breast cancer (BC) patients. Patients with co-existing BC and DM (BC-DM) have worsened BC prognosis. Nevertheless, the molecular mechanisms orchestrating BC-DM prognosis remain poorly understood. tRNA-derived fragments (tRFs) have been shown to regulate cancer progression. However, the biological role of tRFs in BC-DM has not been explored. METHODS: tRF levels in tumor tissues and cells were detected by tRF sequencing and qRT-PCR. The effects of tRF on BC cell malignancy were assessed under euglycemic and hyperglycemic conditions in vitro. Metabolic changes were assessed by lactate, pyruvate, and extracellular acidification rate (ECAR) assays. Diabetic animal model was used to evaluate the impacts of tRF on BC tumor growth. RNA-sequencing (RNA-seq), qRT-PCR, Western blot, polysome profiling, luciferase reporter assay, and rescue experiments were performed to explore the regulatory mechanisms of tRF in BC-DM. RESULTS: We identified that tRF-Cys-GCA-029 was downregulated in BC-DM tissues and under hyperglycemia conditions in BC cells. Functionally, downregulation of tRF-Cys-GCA-029 promoted BC cell proliferation and migration in a glucose level-dependent manner. tRF-Cys-GCA-029 knockdown also enhanced glycolysis metabolism in BC cells, indicated by increasing lactate/pyruvate production and ECAR levels. Notably, injection of tRF-Cys-GCA-029 mimic significantly suppressed BC tumor growth in diabetic-mice. Mechanistically, tRF-Cys-GCA-029 regulated BC cell malignancy and glycolysis via interacting with PRKCG in two ways: binding to the coding sequence (CDS) of PRKCG mRNA to regulate its transcription and altering polysomal PRKCG mRNA expression to modify its translation. CONCLUSIONS: Hyperglycemia-downregulated tRF-Cys-GCA-029 enhances the malignancy and glycolysis of BC cells. tRF-Cys-GCA-029-PRKCG-glycolysis axis may be a potential therapeutic target against BC-DM.

Tailoring component incorporation for homogenized perovskite solar cells.

Deep-level traps at the buried interface of perovskite and energy mismatch problems between the perovskite layer and heterogeneous interfaces restrict the development of ideal homogenized films and efficient perovskite solar cells (PSCs) using the one-step spin-coating method. Here, we strategically employed sparingly soluble germanium iodide as a homogenized bulk in-situ reconstruction inducing material preferentially aggregated at the perovskite buried interface with gradient doping, markedly reducing deep-level traps and withstanding local lattice strain, while minimizing non-radiative recombination losses and enhancing the charge carrier lifetime over 9 µs. Furthermore, this gradient doping assisted in modifying the band diagram at the buried interface into a desirable flattened alignment, substantially mitigating the energy loss of charge carriers within perovskite films and improving the carrier extraction equilibrium. As a result, the optimized device achieved a champion power conversion efficiency of 25.24% with a fill factor of up to 84.65%, and the unencapsulated device also demonstrated excellent light stability and humidity stability. This work provides a straightforward and reliable homogenization strategy of perovskite components for obtaining efficient and stable PSCs.

Multimodal frontal neuroimaging markers predict longitudinal craving reduction in abstinent individuals with heroin use disorder.

The variation in improvement among individuals with addiction after abstinence is a critical issue. Here, we aimed to identify robust multimodal markers associated with high response to 8-month abstinence in the individuals with heroin use disorder (HUD) and explore whether the identified markers could be generalized to the individuals with methamphetamine use disorder (MUD). According to the median of craving changes, 53 individuals with HUD with 8-month abstinence were divided into two groups: higher craving reduction and lower craving reduction. At baseline, clinical variables, cortical thickness and subcortical volume, fractional anisotropy (FA) of fibers and resting-state functional connectivity (RSFC) were extracted. Different strategies (single metric, multimodal neuroimaging fusion and multimodal neuroimaging-clinical data fusion) were used to identify reliable features for discriminating the individuals with HUD with higher craving reduction from those with lower reduction. The generalization ability of the identified features was validated in the 21 individuals with MUD. Multimodal neuroimaging-clinical fusion features with best performance was achieved an 87.1 ± 3.89% average accuracy in individuals with HUD, with a moderate accuracy of 66.7% when generalizing to individuals with MUD. The multimodal neuroimaging features, primarily converging in frontal regions (e.g., the left superior frontal (LSF) thickness, FA of the LSF-occipital tract, and RSFC of left middle frontal-right superior temporal lobe), collectively contributed to prediction alongside dosage and attention impulsiveness. In this study, we identified the validated multimodal frontal neuroimaging markers associated with higher response to long-term abstinence and revealed insights for the neural mechanisms of addiction abstinence, contributing to clinical strategies and treatment for addiction.

A multi-source heterogeneous medical data enhancement framework based on lakehouse.

Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of data is in need of quality improvement before being used to analyze the health condition of patients. There have been many researches in data extraction, data cleaning and data imputation, respectively. However, there are seldom frameworks integrating with these three techniques, making the dataset suffer in accuracy, consistency and integrity. In this paper, a multi-source heterogeneous data enhancement framework based on a lakehouse MHDP is proposed, which includes three steps of data extraction, data cleaning and data imputation. In the data extraction step, a data fusion technique is offered to handle multi-modal and multi-source heterogeneous data. In the data cleaning step, we propose HoloCleanX, which provides a convenient interactive procedure. In the data imputation step, multiple imputation (MI) and the SOTA algorithm SAITS, are applied for different situations. We evaluate our framework via three tasks: clustering, classification and strategy prediction. The experimental results prove the effectiveness of our data enhancement framework.

RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images.

Retinal diseases stand as a primary cause of childhood blindness. Analyzing the progression of these diseases requires close attention to lesion morphology and spatial information. Standard image registration methods fail to accurately reconstruct pediatric fundus images containing significant distortion and blurring. To address this challenge, we proposed a robust deep learning-based image registration method (RDLR). The method consisted of two modules: registration module (RM) and panoramic view module (PVM). RM effectively integrated global and local feature information and learned prior information related to the orientation of images. PVM was capable of reconstructing spatial information in panoramic images. Furthermore, as the registration model was trained on over 280,000 pediatric fundus images, we introduced a registration annotation automatic generation process coupled with a quality control module to ensure the reliability of training data. We compared the performance of RDLR to the other methods, including conventional registration pipeline (CRP), voxel morph (WM), generalizable image matcher (GIM), and self-supervised techniques (SS). RDLR achieved significantly higher registration accuracy (average Dice score of 0.948) than the other methods (ranging from 0.491 to 0.802). The resulting panoramic retinal maps reconstructed by RDLR also demonstrated substantially higher fidelity (average Dice score of 0.960) compared to the other methods (ranging from 0.720 to 0.783). Overall, the proposed method addressed key challenges in pediatric retinal imaging, providing an effective solution to enhance disease diagnosis. Our source code is available at https://github.com/wuwusky/RobustDeepLeraningRegistration .

Neurofunctional changes related to methamphetamine and sexual cues in methamphetamine dependence from short- to long-term abstinence.

AIMS: Abuse of methamphetamine has aroused concern worldwide. Stimulant use and sexual behaviours have been linked in behavioural and epidemiological studies. Although methamphetamine-related neurofunctional differences are reported in previous studies, only few studies have examined neurofunctional changes related to methamphetamine and sexual cues in methamphetamine dependence from short- to long-term abstinence. METHODS: Neurofunctional changes were measured using a cue-reactivity task involving methamphetamine, sexual, and neutral cues in 20 methamphetamine abusers who were evaluated after a short- (1 week to 3 months) and long-term (10-15 months) abstinence. RESULTS: Five brain regions mainly involved in the occipital lobe and the parietal lobe were found with the group-by-condition interaction. Region-of-interest analyses found higher sexual-cue-related activation than other two activations in all five brain regions in the long-term methamphetamine abstinence group while no group differences were found. Negative relationships between motor impulsivity and methamphetamine- or sexual-cue-related activations in the left middle occipital gyrus, the superior parietal gyrus and the right angular gyrus were found. CONCLUSIONS: The findings suggested that methamphetamine abstinence may change the neural response of methamphetamine abusers to methamphetamine and sexual cues, and the neurofunction of the five brain regions reported in this study may partly recover with long-term methamphetamine abstinence. Given the use and relapse of methamphetamine for sexual purposes, the findings of this study may have particular clinical relevance.

Transparent Recombination Layers Design and Rational Characterizations for Efficient Two-Terminal Perovskite-Based Tandem Solar Cells.

Two-terminal (2T) perovskite-based tandem solar cells (TSCs) arouse burgeoning interest in breaking the Shockley-Queisser (S-Q) limit of single-junction solar cells by combining two subcells with different bandgaps. However, the highest certified efficiency of 2T perovskite-based TSCs (33.9%) lags behind the theoretical limit (42-43%). A vital challenge limiting the development of 2T perovskite-based TSCs is the transparent recombination layers/interconnecting layers (RLs) design between two subcells. To improve the performance of 2T perovskite-based TSCs, RLs simultaneously fulfill the optical loss, contact resistance, carrier mobility, stress management, and conformal coverage requirements. In this review, the definition, functions, and requirements of RLs in 2T perovskite-based TSCs are presented. The insightful characterization methods applicable to RLs, which are inspiring for further research on the RLs both in 2T perovskite-based two-junction and multi-junction TSCs, are also highlighted. Finally, the key factors that currently limit the performance enhancement of RLs and the future directions that should be continuously focused on are summarized.

Prevalence of Autism Spectrum Disorder Among Children and Adolescents in the United States from 2021 to 2022.

PURPOSE: The prevalence of autism spectrum disorder (ASD) among children and adolescents seem to be high in countries around the world, and it's worth understanding the latest prevalence and trends of ASD in children and adolescents. The purpose of this study was to examine the latest prevalence and decade trend of ASD among individuals aged 3-17 years in the United States. METHODS: A total of 13,198 individuals aged 3-17 years were included. Annual data were examined from the National Health Interview Survey (2021-2022). Weighted prevalence for each of the selected developmental disabilities were calculated. RESULTS: This cross-sectional study estimated the weighted prevalence of autism spectrum disorder were 3.05, 3.79, and 3.42% among individuals aged 3-17 years in the US in 2021, 2022, and the 2-year overall, respectively. We also observed a decade-long upward trend even after adjusting for demographic characteristics (P for trend < .05). CONCLUSION: The results of this study showed that the prevalence of ASD among children and adolescents aged 3-17 years in the United States remained high and has increased over the past decade. The further investigation is necessary to evaluate potential modifiable risk factors and causes of ASD.

Nonlinear dose-response association of moderate-to-vigorous physical activity with hyperuricemia in US adults: NHANES 2007-2018.

BACKGROUND: The relationship between physical activity and hyperuricemia (HUA) remains inconsistent, and the dose-response association between moderate-to- vigorous physical activity (MVPA) level and HUA still unclear. In this study, we aimed to investigate the dose-response association of MVPA with HUA, and to explore an appropriate range of MVPA level for preventing HUA. METHODS: Data from the US National Health and Nutrition Examination Survey (NHANES) 2007-2018 were used, including 28740 non-gout adult Americans. MVPA level was self-reported using the Global Physical Activity Questionnaire and serum uric acid was measured using timed endpoint method. The dose-response relationship between MVPA level and HUA was modeled with restricted cubic spline analysis. Logistic regression analysis were applied to estimate odd ratios (ORs) and 95% confidence intervals (CIs) of the relationships between MVPA level and HUA. RESULTS: A total of 28740 adults were included in the study (weighted mean age, 47.3 years; 46.5% men), with a prevalence rate of HUA was 17.6%. The restricted cubic spline functions depicted a general U-shaped relationship between MVPA level and HUA. The MVPA level of 933 and 3423 metabolic equivalent (MET) -min/wk were the cut-off discriminating for the risk of HUA. Participants with MVPA levels in the range of 933-3423 MET-min/wk had lower risk of HUA and they had the lowest risk when MVPA levels at around 1556 MET-min/wk. Compared with the moderate-activity group (600-2999 Met-min/wk), the low-activity group (< 600 Met-min/wk) had a greater risk of HUA (OR, 1.13 [95%CI, 1.02-1.26]) after fully adjusting for potential confounders. CONCLUSIONS: Compared with the moderate MVPA level, the low MVPA level was associated with the higher risk of HUA. And there may be a U-shaped dose-response relationship between MVPA level and HUA. When MVPA level was approximately 933-3423 MET-min/wk, the risk of HUA may at a lower level and the risk reached the lowest when MVPA level at around 1556 MET-min/wk.

Trends in prevalence of hearing loss in adults in the USA 1999-2018: a cross-sectional study.

BACKGROUND: A better understanding of how the prevalence of hearing loss and its associated factors change over time could help in developing an appropriate program to prevent the development of hearing loss. METHODS: Population-representative cross-sectional data from the United States National Health and Nutrition Examination Survey (NHANES) were used to estimate the trends in the prevalence of hearing loss among adults in the USA over the period 1999-2018. A total of 15,498 adult participants aged 20 years or older had complete audiometric examination data. Logistic regression was employed to evaluate the trend in hearing loss; weighted Rao-Scott χ2 tests and univariate logistic regression analyses were used to examine the association between hearing loss and relevant factors. RESULTS: The overall hearing loss prevalence in 1999-2018 was 19.1% 19.1 (95% CI, 18.0-20.2%). The prevalence of hearing loss decreased in cycles (P for trend < 0.001). For participants aged 20-69 years, the prevalence decreased from 15.6% (95% CI, 12.9-18.4%) in 1999-2000 to 14.9% (95% CI, 13.2- 16.6%) in 2015-2016; for participants aged > 70 years the prevalence decreased from 79.9% (95% CI, 76.1-83.8%) in 2005-2006 to 64.5% (95% CI, 58.8-70.2%) in 2017-2018. Participants with hearing loss were likely to be older, male, non-Hispanic white, and to have not completed high school. Mild hearing loss was more prevalent among those aged 20-79 years; in those aged over 80 years the prevalence of moderate hearing loss exceeded that of mild loss. Among all otologically normal participants, hearing thresholds increased with age across the entire frequency range. CONCLUSIONS: The prevalence of hearing loss in USA adults changed over the period 1999-2018. The trends observed provide valuable insight for making public health plans and allocating resources to hearing care. Further investigation is necessary to monitor hearing loss and its potential risk factors.

Hereditary and cortical morphological biomarker of sensitivity to reward in short-term withdrawal methamphetamine abusers.

Higher sensitivity to reward (SR) and weaker sensitivity to punishment (SP) construct the fundamental craving characteristics of methamphetamine abuse. However, few studies have appraised relationships between SR/SP (SR or SP) and cortical morphological alterations in methamphetamine abusers and whether hereditary factors take effects on SR/SP is unclear. Based on surface-based morphometric analysis, cortical discrepancy was investigated between 38 methamphetamine abusers and 37 healthy controls. Within methamphetamine abusers, correlation profiling was performed to discover associations among aberrant neuroimaging substrates, SR, SP, and craving. According to nine single nucleotide polymorphism sites of dopamine-related genes, we conducted univariate general linear model to find different effects of genotypes on cortical alterations and SR/SP/craving (SR, SP, or craving). Ultimately, mediation analyses were conducted among single nucleotide polymorphism sites, SR/SP/craving, and cortical morphological alterations to discover their association pathways. Compared to healthy controls, thinner cortices in inferior temporal gyrus, lateral orbitofrontal cortex, medial orbitofrontal cortex, inferior parietal lobule, and lateral occipital cortex in the left hemisphere were found in methamphetamine abusers (P < 0.05, family-wise error corrected). Cortical thickness in the inferior temporal gyrus was negatively correlated with SR scores. We found that rs1800497 A-containing genotypes had lower cortical thickness in the left inferior parietal lobule than the GG genotype. The rs5751876 had effects on SR scores. This study would provide convincing biomarkers for SR in methamphetamine abusers and offer potential genetic targets for personalizing relapse prevention.