Major Depressive Disorder Prediction Based on Sleep-Wake Disorders Symptoms in US Adolescents: A Machine Learning Approach from National Sleep Research Resource.

Background: There is substantial evidence from previous studies that abnormalities in sleep parameters associated with depression are demonstrated in almost all stages of sleep architecture. Patients with symptoms of sleep-wake disorders have a much higher risk of developing major depressive disorders (MDD) compared to those without. Objective: The aim of the present study is to establish and compare the performance of different machine learning models based on sleep-wake disorder symptoms data and to select the optimal model to interpret the importance of sleep-wake disorder symptoms to predict MDD occurrence in adolescents. Methods: We derived data for this work from 2020 to 2021 Assessing Nocturnal Sleep/Wake Effects on Risk of Suicide Phase I Study from National Sleep Research Resource. Using demographic and sleep-wake disorder symptoms data as predictors and the occurrence of MDD measured base on the center for epidemiologic studies depression scale as an outcome, the following six machine learning predictive models were developed: eXtreme Gradient Boosting model (XGBoost), Light Gradient Boosting mode, AdaBoost, Gaussian Naïve Bayes, Complement Naïve Bayes, and multilayer perceptron. The models' performance was assessed using the AUC and other metrics, and the final model's predictor importance ranking was explained. Results: XGBoost is the optimal predictive model in comprehensive performance with the AUC of 0.804 in the test set. All sleep-wake disorder symptoms were significantly positively correlated with the occurrence of adolescent MDD. The insomnia severity was the most important predictor compared with the other predictors in this study. Conclusion: This machine learning predictive model based on sleep-wake disorder symptoms can help to raise the awareness of risk of symptoms between sleep-wake disorders and MDD in adolescents and improve primary care and prevention.

Causal associations between digital device use and suicide risk: A bidirectional Mendelian randomization study.

BACKGROUND: The popularity of digital devices seems to provide a new observational variable for early identification and prevention of suicide with the development of the information technology era. Nevertheless, whether it is the use of digital devices that alters suicide risk or suicide risk manifests itself through change digital device use needs to be further explored. METHODS: Bidirectional Mendelian randomization (MR) analysis was used to explore potential causal relationships in the perspective of genetic prediction. We collected publicly available digital device use and suicide risk summary statistics genome-wide association data from UK Biobank, Neale Lab and FinnGen genetic databases. We used inverse variance weighting methods to assess MR estimates. For robustness of the results, we performed further tests of heterogeneity and pleiotropy. RESULTS: In the Phase 1 results, we did not observe any effect of the length of digital device use on the suicide risk, while the results of Phase 2 suggested a significant positive association between suicide risk and the length of mobile phone use (IVW OR, 1.04; 95%CI, 1.01-1.06; P = 0.002), but this significance disappeared after adjusting for confounders of mental and affective disorders. CONCLUSIONS: In this bidirectional MR analysis, we observed that People at high risk of suicide may be more addicted to digital device use, but more detailed GWAS data and research methods to validate this finding are required.

Association between positive youth development and non-suicidal self-injury: A longitudinal survey of children and adolescents in southwest China, 2019-21.

BACKGROUND: Non-suicidal self-injury (NSSI) could lead to serious problems (exp. suicidal attempts) among children and adolescents. Positive youth development (PYD) focuses on comprehensive development instead of a single problem. This study aims to explore the longitudinal relationship between NSSI and PYD among Chinese children and adolescents. METHODS: The longitudinal study used the three-wave dataset from the Chengdu Positive Child Development (CPCD) in southwest China between 2019 and 2021, including 10,370 participants. The parallel process Latent Growth Curve Model (LGCM) was utilized to analyze the relationship between PYD and NSSI across time. RESULTS: The study results demonstrated that the initial level of NSSI is negatively associated with the initial value (ß = -0.730, p < 0.01) and the growth rate (ß = -0.012, p < 0.01) of PYD, and the development rate of the two variables are negatively related to each other(ß = -0.120, p < 0.01). LIMITATIONS: The specific relationships between PYD attributes and NSSI should be explored in the future. And the cultural variation among countries deserves more research. Moreover, the dynamic cohort research leads to a relatively high loss of participants. CONCLUSIONS: PYD and NSSI are closely associated among children and adolescents. Instead of playing a protective role, PYD tends to be predicted by NSSI behaviors over time.

Narcolepsy and cardiovascular disease: A two-sample Mendelian randomization study.

BACKGROUND: Observational findings suggest that patients with narcolepsy are at higher risk for cardiovascular diseases (CVDs), but the potential causal relationship between narcolepsy and CVDs is unclear. Therefore, Mendelian randomization (MR) was used to explore the association between narcolepsy and CVDs. METHODS: Summary statistics related to narcolepsy, coronary artery disease (CAD), myocardial infarction (MI), heart failure (HF), any stroke (AS), and any ischemic stroke (AIS) were extracted from the public database of relevant published genome-wide association studies (GWAS). Independent single nucleotide polymorphisms were selected as instrumental variables under strict quality control criteria. Inverse variance-weighted (IVW) was the main analytical method to assess causal effects. In addition, we conducted MR pleiotropy residual sum and outlier (MR-PRESSO), weighted median, MR-Egger, and leave-one-out sensitivity analysis to verify the robustness and reliability of the results. RESULTS: The results of the MR study revealed that narcolepsy was significantly associated with an increased risk of HF (OR = 1.714; 95%CI [1.031-2.849]; P = 0.037), CAD (OR = 1.702; 95%CI [1.011-2.864]; P = 0.045). There was no statistically significant causal association between narcolepsy and MI, AS, and AIS. In addition, further sensitivity analysis showed robust results. CONCLUSIONS: The results of the two-sample MR study reveal a potential causal relationship between the increased risk of HF and CAD in narcolepsy. These findings emphasize the importance of early monitoring and assessment of cardiovascular risk in patients with narcolepsy.

The role of robot-assisted training on rehabilitation outcomes in Parkinson's disease: a systematic review and meta-analysis.

PURPOSE: The study aims to assess the efficacy of robot-assisted rehabilitation training on upper and lower limb motor function and fatigue in Parkinson's disease (PD), and to explore the best-acting robotic rehabilitation program. METHODS: We searched studies in seven databases and the search period was from the build to 30 June 2023. Two researchers independently screened studies and assessed the quality of the studies for data extraction. RESULTS: A total of 21 studies were included, 18 studies related to lower limbs rehabilitation and 3 studies related to upper limbs rehabilitation, involving a total of 787 participants. The results showed that robot-assisted rehabilitation significantly improved indicators of lower limb motor function UPDRS Part III (WMD = -3.58, 95% CI = -5.91 to -1.25, p = 0.003) and BBS (WMD = 4.24, 95% CI = 2.88 to 5.54, p < 0.001), as well as non-motor symptoms of fatigue (WMD = -13.39, 95% CI = -17.92 to -8.86, p < 0.001) in PD patients. At the level of upper limb function, there was no statistically significant difference in the outcome measures of PFS (WMD = -0.25, 95% CI = -4.44 to 3.93, p = 0.9) and BBT (WMD = 1.73, 95% CI = -2.85 to 6.33, p = 0.458). CONCLUSION: Robot-assisted rehabilitation significantly improved motor function, fatigue, and balance confidence in PD patients, but current evidence doesn't show that intelligent rehabilitation systems improve upper limb function. In particular, robotics combined with virtual reality worked best.

Robot-assisted rehabilitation significantly improves motor symptoms, lower limb motor function, fatigue, and balance confidence in Parkinson's disease (PD) patients.Robotics combined with virtual reality is the most effective application and should be encouraged.In the robotic rehabilitation of PD patients, the focus needs to be on the duration of the training and the long-term benefits it provides.

Global comparison of the effect of non-pharmacological interventions on glycemic control in patients with type 2 diabetes: A network meta-analysis from 107 randomized controlled trials.

OBJECTIVE: To investigate the effectiveness of non-pharmacological interventions (NPIs) on glycemic control in patients with type 2 diabetes (T2D) and to provide guidance for clinical healthcare-giver. DESIGN: Network meta-analysis (NMA). SETTING AND PARTICIPANTS: Randomized controlled trials comparing the effect of NPIs with usual care, waitlist, or other NPIs on glycemic control in patients with T2D. METHODS: This NMA was guided by frequentist framework. PubMed, Embase, the Cochrane Library Central Register of Controlled Trials, Cumulated Index to Nursing and Allied Health Literature, and Web of Science were searched from their inception until January 2023. The primary outcome was HbA1c and secondary outcomes were cardiovascular risk scores and related psychosocial scores. Mean differences and standardized mean differences were pooled using NMA. Study quality was assessed with the Confidence in Network Meta-analysis. RESULTS: A total of 107 studies (10,496 participants) were included. The median sample size of the included studies was 64 (range, 10-563) and the median duration was 3 months (range, 1-24). Compared to usual care, all NPIs except acupuncture (MD: -0.28; 95 % CI: -1.02, 0.26) and psychological therapy (MD: -0.29; 95 % CI: -0.66, 0.08) showed significantly differences in improving glycemic control in patients with T2D. And according to the results of surface under the cumulative ranking analysis and Cluster ranking, meditation therapy was considered to the best choice when balancing the efficacy of glycemic control with self-efficacy and diabetes related problems, while nutrition therapy was considered to the best choice when balancing quality of life with risk of cardiovascular complications. CONCLUSIONS: These findings validate the efficacy of NPIs for glycemic control in patients with T2D and suggest that healthcare-giver should consider both the efficacy of interventions and the psychosocial needs of patients when developing NPIs programs.

Enhanced visible light photocatalytic hydrogen production over poly(dibenzothiophene-S,S-dioxide)-based heterostructures decorated by Earth-abundant layered double hydroxides.

Layered double hydroxides (LDHs) have emerged as one of the promising catalyst substitutes to noble metals in photocatalytic water splitting due to their unique optoelectronic properties. Herein, a series of novel PSO@NiFeLDH composites have been designed and synthesized to investigate photocatalytic performance. Various physicochemical techniques characterized their structural, nanomorphological, and optical properties. These results demonstrated the existence of NiFeLDH particles on the surface of PSO and the strong interaction between NiFeLDH and PSO. The photocatalytic performance was much increased in the case of PSO@NiFeLDH as compared to that of Pt-modified PSO because of the synergistic effect between PSO and NiFeLDH. Remarkably, PSO@NiFeLDH-15 exhibits the highest photocatalytic activity with a rate of 52.8 mmol h-1 g-1 at an optimal content without a Pt cocatalyst under visible light irradiation.

Effectiveness of Wearable Device-based Intervention on Glycemic Control in Patients with Type 2 Diabetes: A System Review and Meta-Analysis.

With the development of flexible electronics and chip technology, the application value of wearable devices in lifelong treatment of chronic diseases is increasing. In view of its rapid development and diversified forms, wearable device-based intervention seems to provide a promising option to solve the problems of long-term glycemic control in type 2 diabetes (T2D). However, to date, it is unclear whether the intervention based on wearable device is effective on glycemic control in patients with T2D. In order to explore whether this choice is effective in glycemic control in patients with T2D, after database search and study screening, 6 studies and 1001 patients were selected from 181studies for this meta-analysis. The results guided that the wearable device-based intervention may be more effective than usual care on glycemic control in patients with T2D. Subgroup analysis showed that when the duration of intervention was equal to or less than 12 weeks, the effect of wearable device-based intervention was significantly different from that of usual care, but when the intervention duration greater than 12 weeks, the effect was not significantly different. The intervention effect of wearable devices with goal-setting or encouragement functions was significantly better than that of usual care, and there was no significant difference between automatic drug delivery wearable devices and usual care. In conclusion, the wearable device-based intervention is effective on glycemic control in patients with T2D. In general, this choice of wearable devices for patients with T2D may be effective to some extent.

Growth factors, as biological macromolecules in bioactivity enhancing of electrospun wound dressings for diabetic wound healing: A review.

Impaired wound healing is of the most conspicuous characteristics of diabetic mellitus. Reduced blood flow, chronic inflammatory reactions, infection, endothelial dysfunction, elevated levels of reactive oxygen species, and metabolic disorders cause wounds to heal more slowly in these patients. Previous studies have reported useful impacts of growth factors in management of such wounds. However, due to their short half-life and low stability, a suitable delivery platform with sustained release profile may boost their healing potential. Controlled and localized delivery of growth factors via electrospun fibers have been extensively explored in previous studies. The electrospinning method; although not new, has turned out to be extremely effective for the preparation of delivery carriers for growth factors. Due to their structural resemblance to native tissues' extracellular matrix, high encapsulation efficacy, tunability, and high surface to volume ratio, electrospun scaffolds have gained significant attention in drug delivery and tissue engineering. In the current review, careful integration of current research regarding the applications of growth factors' delivery through electrospun fibers in diabetic wounds healing has been done. This review will not only give an insight into the current updates, but will also highlights the future perspectives and challenges.

Using Network Pharmacology and Molecular Docking to Explore the Mechanism of Shan Ci Gu (Cremastra appendiculata) Against Non-Small Cell Lung Cancer.

Background: In recent years, the incidence and mortality rates of non-small cell lung cancer (NSCLC) have increased significantly. Shan Ci Gu is commonly used as an anticancer drug in traditional Chinese medicine; however, its specific mechanism against NSCLC has not yet been elucidated. Here, the mechanism was clarified through network pharmacology and molecular docking. Methods: The Traditional Chinese Medicine Systems Pharmacology database was searched for the active ingredients of Shan Ci Gu, and the relevant targets in the Swiss Target Prediction database were obtained according to the structure of the active ingredients. GeneCards were searched for NSCLC-related disease targets. We obtained the cross-target using VENNY to obtain the core targets. The core targets were imported into the Search Tool for the Retrieval of Interacting Genes/Proteins database, and Cytoscape software was used to operate a mesh chart. R software was used to analyze the Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The core targets and active compounds were molecularly docked through Auto-Dock Vina software to predict the detailed molecular mechanism of Shan Ci Gu for NSCLC treatment. We did a simple survival analysis with hub gene to assess the prognosis of NSCLC patients. Results: Three compounds were screened to obtain 143 target genes and 1,226 targets related to NSCLC, of which 56 genes were related to NSCLC treatment. Shan Ci Gu treatment for NSCLC involved many BPs and acted on main targets including epidermal growth factor receptor (EGFR), ESR1, and SRC through signaling pathways including the endocrine resistance, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathways. Shan Ci Gu might be beneficial for treating NSCLC by inhibiting cell proliferation and migration. Molecular docking revealed that the active compounds ß-sitosterol, stigmasterol, and 2-methoxy-9,10-dihydrophenanthrene-4,5-diol had good affinity with the core target genes (EGFR, SRC, and ESR1). Core targets included EGFR, SRC, ESR1, ERBB2, MTOR, MCL1, matrix metalloproteinase 2 (MMP2), MMP9, KDR, and JAK2. Key KEGG pathways included endocrine resistance, EGFR tyrosine kinase inhibitor resistance, ErbB signaling, PI3K-Akt signaling, and Rap1 signaling pathways. These core targets and pathways have an inhibitory effect on the proliferation of NSCLC cells. Conclusion: Shan Ci Gu can treat NSCLC through a multi-target, multi-pathway molecular mechanism and effectively improve NSCLC prognosis. This study could serve as a reference for further mechanistic research on wider application of Shan Ci Gu for NSCLC treatment.

NRT1.1 Regulates Nitrate Allocation and Cadmium Tolerance in Arabidopsis.

Abiotic stress induces nitrate (NO3 -) allocation to roots, which increases stress tolerance in plants. NRT1.1 is broadly involved in abiotic stress tolerance in plants, but the relationship between NRT1.1 and NO3 - allocation under stress conditions is unclear. In this study, we found that Arabidopsis wild-type Col-0 was more cadmium (Cd2+)-tolerant than the nrt1.1 mutant at 20 µM CdCl2. Cd2+ exposure repressed NRT1.5 but upregulated NRT1.8 in roots of Col-0 plants, resulting in increased NO3 - allocation to roots and higher [NO3 -] root-to-shoot (R:S) ratios. Interestingly, NITRATE REGULATORY GENE2 (NRG2) was upregulated by Cd2+ stress in Col-0 but not in nrt1.1. Under Cd2+ stress, nrg2 and nrg2-3chl1-13 mutants exhibited similar phenotypes and NO3 - allocation patterns as observed in the nrt1.1 mutant, but overexpression of NRG2 in Col-0 and nrt1.1 increased the [NO3 -] R:S ratio and restored Cd2+ stress tolerance. Our results indicated that NRT1.1 and NRG2 regulated Cd2+ stress-induced NO3 - allocation to roots and that NRG2 functioned downstream of NRT1.1. Cd2+ uptake did not differ between Col-0 and nrt1.1, but Cd2+ allocation to roots was higher in Col-0 than in nrt1.1. Stressed Col-0 plants increased Cd2+ and NO3 - allocation to root vacuoles, which reduced their cytosolic allocation and transport to the shoots. Our results suggest that NRT1.1 regulates NO3 - allocation to roots by coordinating Cd2+ accumulation in root vacuoles, which facilitates Cd2+ detoxification.

Effect of Nd-doping on the optical properties of yttrium aluminum garnet nanopowders.

Nd-doped and Nd/Si-codoped yttrium aluminum garnet powders were synthesized via a solvothermal method using ethanol as the solvent. The photoluminescence spectra of the powders revealed that the intensity of the emission increased with Nd-doping concentration initially and then decreased with further increase in Nd concentration. The powder containing 3.5 atm% Nd exhibited the highest light emission intensity. The fluorescence lifetime of the yttrium aluminum garnet powders was also measured as a function of Nd-doping concentration. The results were fitted with an empirical equation.