JOURNAL OF WATER AND HEALTH
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2025
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IF 2.4
Yuan Shuai,Xiao Yue,Luo Ruxin,Wang Xin,Xiang Ping
View large Download slide View large Download slide Close modal In recent years, mental disorders have become serious health problems. Monitoring the usage of psychotropic drugs can reflect the prevalence of mental disorders in the population, and wastewater analysis is an effective method for monitoring the use of psychoactive pharmaceuticals. In our study, we collected 58 samples from 12 wastewater treatment plants (WWTPs) in a southern city in China. We then analyzed the concentrations and loads of 18 frequently used psychoactive drugs and corresponding metabolites. The most abundant compounds in wastewater were diazepam, sulpiride, clozapine, venlafaxine, and quetiapine, with a detection frequency close to 100%. Sulpiride had the highest average load, followed by venlafaxine, clozapine, quetiapine, and diazepam. The higher load of diazepam in suburban WWTPs than in urban WWTPs reflects the large numbers of older people living in suburban areas in most of China. The lower loads of most target compounds in suburban WWTPs than in urban WWTPs indicate a greater likelihood of mental disorders in urban people than in suburban people. A correlation analysis of the target compounds revealed a correlation between the occurrence of venlafaxine, sulpiride, and clozapine. Overall, wastewater analysis is expected to be a significant tool for monitoring the consumption of psychoactive pharmaceuticals. Timing and regional distribution of 18 psychoactive drugs and metabolites in a Chinese city. The loads of most target compounds were lower in suburban WWTPs than in urban WWTPs. Schools showed high loads of diazepam, indicating that diazepam may be abused among students. Correlation was observed between venlafaxine, sulpiride, and clozapine loads.
研究领域:
环境科学
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公共卫生
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药理学
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DOI
PubMed
高影响因子
ELECTROCHIMICA ACTA
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2025
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IF 5.6
Chengchen Tang,Chenhao Wang,Wei Wei,Kexin Chen,Zhenjie Zhang,Xiaoyan Wang,Hui Kong
Dynamic monitoring of psychological and physiological states is important for supporting mental health assessment. However, most existing sensors are invasive and lack real-time capabilities, limiting their practical application. Here, we present a wearable biosensing platform for non-invasive assessment of mental health—related biomarkers through sweat analysis. The device integrates a flexible skin interface with molecularly imprinted polymers for high molecular specificity and sweat-stimulation electrodes that induce perspiration under resting conditions. A spiral-shaped sweat collection system enables directional transport to sensing zones, allowing real-time quantification of tyrosine and tryptophan—two biomarkers associated with psychological states. A dopamine sensor was also incorporated, showing excellent electrochemical performance with a detection limit of 0.1 μM L⁻¹ in artificial sweat. Preliminary testing with collected sweat samples confirmed the feasibility of dopamine detection in real sweat. Given the low endogenous dopamine levels and individual variability, these results serve as proof-of-concept. The detection limits for tryptophan and tyrosine were both 1 μM L⁻¹, supporting the sensor’s sensitivity and applicability. Overall, this wearable platform demonstrates strong potential as an auxiliary tool for multi-biomarker monitoring to support mental health management in daily life.
研究领域:
生物医学工程
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可穿戴传感器
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心理健康技术
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电化学传感
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生理监测
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DOI
高影响因子
JOURNAL OF NANOBIOTECHNOLOGY
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2023
·Vol. 21
·期 1
·1-24
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IF 10.2
Liu Ziyao,Chen Bei,Xiang Shijun,Hu Shuo
Background Pharmacotherapy constitutes the first-line treatment for depression. However, its clinical use is hindered by several limitations, such as time lag, side effects, and narrow therapeutic windows. Nanotechnology can be employed to shorten the onset time by ensuring permeation across the blood brain barrier (BBB) to precisely deliver more therapeutic agents; unfortunately, formidable challenges owing to the intrinsic shortcomings of commercial drugs remain.Results Based on the extraordinary capability of monoamines to regulate the neuronal environment, we engineer a network nanocapsule for delivering serotonin (5-hydroxytryptamine, 5-HT) and catalase (CAT) to the brain parenchyma for synergistic antidepression therapy. The nanoantidepressants are fabricated by the formation of 5-HT polymerization and simultaneous payload CAT, following by surface modifications using human serum albumin and rabies virus glycoprotein. The virus-inspired nanocapsules benefit from the surface-modifying strategies and exhibit pronounced BBB penetration. Once nanocapsules reach the brain parenchyma, the mildly acidic conditions trigger the release of 5-HT from the sacrificial nanocapsule. Releasing 5-HT further positively regulate moods, relieving depressive symptoms. Meanwhile, cargo CAT alleviates neuroinflammation and enhances therapeutic efficacy of 5-HT.Conclusion Altogether, the results offer detailed information encouraging the rational designing of nanoantidepressants and highlighting the potential of nanotechnology in mental health disorder therapies.Graphical abstract
研究领域:
药理学
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纳米医学
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神经科学
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心理健康
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DOI
PubMed
高影响因子
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
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2021
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IF 3.575
Xinyi Zhou,Qian Xiao,Jie Tu
It is very important to maintain normal levels of risk avoidance in daily life. We found that DISC1-N TM mice, which are a model for mental disorders, had a phenotype marked by a risk-avoidance impairment as measured in an open-field test (OFT). We used optogenetic methods to modulate glutamatergic neurons in the basolateral amygdala (BLA) in an attempt to rescue this risk-avoidance impairment. We found that photostimulation of BLA neurons at 20 Hz modified DISC1-N TM mouse behavior from low risk avoidance to high risk avoidance. We observed following photostimulation that, compared to controls, the number of entries to the center of the open field was lower and less time was spent in the central area. We also found that the time spent immobile was higher during photostimulation compared with WT mice. We also used a lower photostimulation frequency of 5 Hz, which activated BLA glutamatergic neurons and rescued the risk-avoidance impairment in DISC1-N TM mice. Our findings confirm that the BLA participates in diverse risk-avoidance behavior. Our results are also a reminder that differences in neuronal firing patterns within the same pathway may lead to different physiological functions.
研究领域:
神经科学
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行为科学
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心理健康
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DOI
PubMed
高影响因子
ACS Nano
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2025
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IF 16
Jing-Hui Mao,Zhong-Hui Shen,Jian Wang,Run-Lin Liu,Xiao-Fei Liu,Ying Lan,Mengjun Zhou,Jian-Yong Jiang,Yang Shen,Ce-Wen Nan
Emotion monitoring plays a crucial role in mental health management. However, traditional methods of emotion recognition predominantly rely on subjective questionnaires or facial expression analyses, which are often inadequate for continuous and highly accurate monitoring. In this study, we propose a high-precision, fine-grained emotion recognition system based on multisource throat physiological signals. The system collects signals through optimized flexible multiporous skin sensors and analyzes them using machine learning models capable of efficiently capturing complex feature interactions. First, we adopt a two-step cross-linking strategy to modulate the porous structure of the sensitive layer to enable accurate detection of the diverse and weak physiological signals in the throat. By extracting four-dimensional features from the input of 7025 samples, the platform based on the Light Gradient Boosting Machine (LightGBM) efficiently captures their nonlinear interactions, ultimately achieving precise classification of five emotional states (relaxation, surprise, disgust, fear, and neutral) with an accuracy of 98.9%. Further validation on an independent data set reveals an average emotion recognition accuracy of 99.3%, demonstrating the system’s robustness and reliability in real-world applications. This work provides a viable technological solution for real-time and continuous emotion monitoring, offering significant potential in mental health management and related fields.
研究领域:
生物医学工程
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人工智能
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心理健康
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF NURSING SCHOLARSHIP
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2022
·Vol. 55
·期 1
·291-303
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IF 3.928
Ita Daryanti Saragih,Chun-Wang Wei,Sakti Oktaria Batubara,Ice Septriani Saragih,Bih-O Lee
Purpose The use of technology-assisted interventions in dementia care contributes to increased communication, reduced burden on the caregivers, improved health outcomes, and improved expense management. Technology-assisted interventions can be provided remotely to monitor, improve, and enable home care, benefiting the health of both patients and caregivers. Despite increasing use, the effectiveness of technology-assisted interventions for dementia care remains uncertain, with studies reporting inconclusive findings subject to interpretation. Therefore, the current study investigated the available evidence to explore the efficacy of technology-assisted interventions for people with dementia. Design Systematic review and meta-analysis. Methods The study was preregistered with the PROSPERO international prospective register of systematic reviews using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided protocol. The primary search was conducted in eight databases from database inception to January 29, 2022. Using a random-effects model, the standardized mean differences (SMDs) with 95% confidence intervals (CIs) were synthesized to obtain pooled effect sizes (using Stata 16.0). The updated Cochrane Risk of Bias 2 tool (RoB-2) was used to evaluate the methodological quality of the studies. Findings A pooled analysis of 12 trials, including 584 people with dementia, showed more improvement associated with technology-assisted interventions compared with standard care, including in the domains of cognitive function (SMD = 0.39; 95% CI: 0.14 to 0.64; p < 0.001) and depression (SMD = −0.75; 95% CI: −1.33 to −0.17; p = 0.01). However, no significant effects were observed for activities of daily living (ADL) or quality of life. Conclusion Technology-assisted interventions appear to improve cognitive function and reduce depression in people with dementia compared with standard care. Clinical relevance This study may be used to demonstrate that interventions incorporating many modalities or technologies can be used to enhance dementia care, which may improve favorable outcomes when using technology-assisted interventions to remotely initiate appropriate activities for people with dementia. Because technology allows for simultaneous communication and access to shared multimedia, it removes environmental constraints and allows treatment to be administered remotely.
研究领域:
老年医学
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神经病学
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数字健康
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心理健康
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远程医疗
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DOI
高影响因子
Frontiers in Public Health
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2022
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IF 6.461
Xiaowu Hu,Caiyi Tang,Dongmei Wang
Introduction: Psychological injuries in social work are on the rise in complex modern society. Some individuals are incurring both physical and psychological injuries. Often, psychological injuries are more miserable than physical injuries. To combat the psychological injury suffered by individuals involved in social work, authorities should mobilize support via social media and raise funds by this and other feasible means to cover the cost of care for these individuals. This study focuses on social media support and funding assistance that could play useful roles in helping to treat psychological injuries among social workers and their clients in China.Methods: A scoping review of academic and gray literature was undertaken to identify the different injuries involved in social work. Semi-structured interviews were carried out with 7 experts, including social workers, social media professionals, and social fund directors. Empirical studies on psychological injuries in social work provided examples in support of the policy advocacy reported in this paper.Results: The scoping review found diverse literature on the subject of psychological injury in social work over the past decade in China. Semi-structured interviews with experts indicate that social media support can alleviate psychological suffering and that funding assistance has a positive influence on assisting individuals coping with psychological injuries. The empirical cases support the plan to encourage more support from social media and funding sources.Conclusion: Psychological injury is greatly influenced by social bias and discrimination. According to cases and actions are taken to mitigate the harm done, supportive social media strategies could greatly diminish the psychological injuries to social workers and their clients and help them avoid much suffering. This study finds that funding organizations could provide a new treatment mechanism—social media marketing strategies and functional activities—to help a large number of individuals with psychological injuries out of the disease trap in China.
研究领域:
社会工作
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心理健康
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公共卫生
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数字媒体
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卫生政策
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DOI
高影响因子
ARCHIVES OF GERONTOLOGY AND GERIATRICS
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2016
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IF 1.971
David Jackson,Gail Roberts,Min Lin Wu,Rosemary Ford,Colleen Doyle
Background The objective of this review was to assess the effectiveness of interventions delivered by telephone, internet or combined formats to support carers of community dwelling people living with Alzheimer’s Disease, vascular dementia or mixed dementia. Method English language literature published up to 2016 was searched. The initial search included: MEDLINE, Cumulative Index to Nursing and Allied Health (CINAHL), and PsycINFO. A second search was conducted using Medical Subject Headings (MeSH) and
研究领域:
老年学
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心理健康
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远程医疗
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痴呆照护
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公共卫生
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DOI
高影响因子
ACS Nano
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2025
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IF 16
Hongwei Chu,Wooyoung Park,Yue Hu,Zhenhe Huang,Rui Shi,Jiyu Li,Zhiyuan Li,Mengge Wu,Yuyu Gao,Guangyao Zhao,Xingcan Huang,Chun Ki Yiu,Binbin Zhang,Dengfeng Li,Kuanming Yao,Jian Li,Yuan Guo,Ya Huang,Qiuqian Ou,Guoqiang Xu,Pengcheng Wu,Jiao Yang,Yingchun Li,Xinge Yu
Mental stress has been a paramount concern worldwide, serving as a critical element for the optimal functioning and thriving of families, communities, and societies. However, the evaluation of the mental stress state in current clinical practice relies on symptom criteria associated with self-reported psychometric tools and behavioral manifestations, which raises the concerns of both accuracy issue and difficulty in identifying classifications. Continuous and quantitative assessments of mental stress-related physical/biomarkers based on wearable technologies is a very feasible way to solve the hurdle, while the implementation of such technology at clinical scales remains quite challenging and has yet to be documented. Herein, we report the collection of advances in sensing strategies, system integration, and model construction for mental health monitoring and management. A set of physical/biomarkers (cortisol, glucose, body temperature, and heart rate) are selected based on the systematic studies on the stress-correlated physiological pathways to form the marker panel. Corresponding stable and sustainable sensing systems are established upon the optimization of nanomaterials and nanostructure design. Comprehensive indicators are further generated based on algorithm bonuses for acute and chronic stress assessment. The fully integrated reusable wearable biosystem demonstrates its effectiveness in identifying, quantifying, and tracking the prognosis of stress in paradigmatic stress scenarios and clinical applications of social anxiety disorder/depression. The technology reported here presents a promising solution for customized mental stress management to facilitate the development of healthcare in psychological well-being.
研究领域:
生物医学工程
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可穿戴技术
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心理健康
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生理监测
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纳米技术
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临床心理学
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数字健康
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DOI
PubMed
高影响因子
BIOSENSORS & BIOELECTRONICS
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2018
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IF 8.173
Bolu Sun,Jinying Cai,Wuyan Li,Xiaodan Gou,Yuqiang Gou,Dai Li,Fangdi Hu
In this study, a novel electrochemical immunosensor for early screening of depression markers-heat shock protein 70 (HSP70) was successfully developed based on the porous graphene (PG) with huge specific surface area and excellent structure. Benefiting from the strong adsorption and good bioactivity of PG which was initially prepared via a simple pyrolysis process, a variety of heat shock protein70 (HSP70) can be firmly loaded on the PG to construct the basic electrode (HSP70/PG/GCE)，which was characterized by the cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), respectively. Due to the HSP70 fixed on the surface of basic electrode and the HSP70 in the samples can competitively combine with the horseradish peroxidase labeled human HSP 70 antibody (HRP-Strept-Biotin-Ab). As a result, it presented a negative correlation between the concentration of HSP70 in samples and the detection signal of the proposed electrochemical immunosensor (HRP-Strept-Biotin-Ab-HSP70/PG/GCE) in the test liquid. The application of PG with excellent electrical conductivity in construction of immunosensor remarkably improved the sensitivity of the immunosensor for detection of HSP70. The proposed immunosensor demonstrated a wide linear range of 0.0448 ~ 100 ng/mL with a low detection limit of 0.02 ng/mL at 3σ. Moreover, the proposed immunosensor could be applied for the sensitive and efficient detection of HSP70 in real samples with good precision, acceptable stability, reproducibility and satisfactory results. Therefore, the HSP70 immunosensor provides a novel and convenient method for early clinical screening of depression markers-heat shock protein 70.
研究领域:
电化学
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生物传感器
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纳米材料
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临床诊断
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心理健康
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
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2022
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IF 3.571
Dongyuan Lu,Zhipeng Wang,Shouhong Gao,Yuehao Han,Hongsen Wang,Hanglin Li,Hongxia Yan,Bosu Meng,Yuhui Mu,Yi Jiang,Xia Tao,Wansheng Chen
Depression is a mental health disorder characterized by chronic negative mood, and depression has become a major threat to human health and quality of life. Anyupeibo capsule , a fifth-class new Chinese medicine, was prepared with extracts of Piper laetispicum C.DC. (Piperaceae), and the alkaloid K6 (5′-methoxy-3′,4′-methyl-enedioxycinnamic-acidisob-utylamide-isobutylamide) was found to be the main active component. Using high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (LC-MS/MS), we developed a method to quantify the concentration of K6 in serum samples from patients with depression. Pretreatment of samples was completed based on solid-phase extraction, and the mobile phase for subsequent LC analysis consisted of aqueous ammonium acetate (0.1 mmol/L, phase A) and acetonitrile (phase B) with isocratic elution at 60% B. Chromatographic separation of K6 was achieved within 3 min with an Agilent ZORBAX SB-C 18 column (2.1 × 150 mm, 3.5 µm) at a flow rate of 0.3 mL/min. A linear regression equation for K6 yielded correlation coefficients of r 2 > 0.99 within a linear range 0.0503–100.5000 ng/mL. Extraction recovery ranged from 85.33% to 101.18%, and the matrix effect ranged from 87.15% to 100.28%. The inter-day and intra-day precision values—expressed as relative standard deviation—were less than 15%, and the corresponding accuracy values were within ±15%. All validation results for stability, specificity, and carry-over met the requirements of Pharmacopoeia. The LC-MS/MS method was applied to determine the K6 concentration in serum samples from patients with depression in a phase III clinical trial of Anyupeibo capsule.
研究领域:
药理学
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分析化学
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临床试验
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心理健康
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产品关联
DOI
PubMed
高影响因子
Frontiers in Psychiatry
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2023
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IF 4.7
Zhang Yanjie,Sun Yajun,Miao Qin,Guo Shilong,Wang Qi,Shi Tianyuan,Guo Xinsheng,Liu Shuai,Cheng Guiding,Wang Chuansheng,Zhang Ruiling
Objective: Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.Methods: Liquid chromatography-mass spectrometry (LC–MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.Results: The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.Conclusion: The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.
研究领域:
心理健康
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代谢组学
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药理学
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临床化学
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产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）