Does rAj-Tspin, a novel peptide from A. japonicus, exert antihepatocellular carcinoma effects via the ITGB1/ZYX/FAK/AKT signaling pathway?

rAj-Tspin, a soluble recombinant peptide from Apostichopus japonicus, can inhibit the integrin ß1 (ITGB1)/FAK/AKT signaling pathway in hepatocellular carcinoma (HCC) via cell epithelial-mesenchymal transition (EMT) and apoptosis. Zyxin (ZYX) is a focal adhesion protein that is considered a novel mediator of EMT and apoptosis. However, the inhibitory mechanisms of rAj-Tspin in HCC and whether it is related to ZYX are unclear. We examined the antitumor effect of rAj-Tspin on the Huh7 human HCC cell line and on a nude mouse model generated via subcutaneous injection or orthotopic intrahepatic transplantation of Huh7 cells. Our results revealed that rAj-Tspin strikingly reduced the viability and promoted the apoptosis of Huh7 cells and inhibited HCC tumor growth in nude mice. rAj-Tspin inhibited ITGB1 and ZYX protein expression in vivo and in vitro in a dose-dependent manner. Mechanistically, the FAK/AKT signaling pathway and the proliferation and invasion of HCC cells were suppressed upon ITGB1 and ZYX knockdown. Moreover, the effect of ITGB1 overexpression on the growth of HCC cells was inhibited by rAj-Tspin. In contrast, the promoting effect of ITGB1 overexpression could be inhibited by ZYX knockdown. ZYX knockdown had no effect on ITGB1 expression. These findings suggest that ZYX is required for the indispensable role of ITGB1 in rAj-Tspin-alleviated HCC and provide an important therapeutic target for HCC. In summary, the anti-HCC effect of rAj-Tspin potentially involves the regulation of the ITGB1/ZYX/FAK/AKT pathway, which in turn impacts EMT and apoptosis.

Interleukin-18 in chronic pain: Focus on pathogenic mechanisms and potential therapeutic targets.

Chronic pain has been proven to be an independent disease, other than an accompanying symptom of certain diseases. Interleukin-18 (IL-18), a pro-inflammatory cytokine with pleiotropic biological effects, participates in immune modulation, inflammatory response, tumor growth, as well as the process of chronic pain. Compelling evidence suggests that IL-18 is upregulated in the occurrence of chronic pain. Antagonism or inhibition of IL-18 expression can alleviate the occurrence and development of chronic pain. And IL-18 is located in microglia, while IL-18R is mostly located in astrocytes in the spinal cord. This indicates that the interaction between microglia and astrocytes mediated by the IL-18/IL-18R axis is involved in the occurrence of chronic pain. In this review, we described the role and mechanism of IL-18 in different types of chronic pain. This review provides strong evidence that IL-18 is a potential therapeutic target in pain management.

Enhanced chromium and nitrogen removal by constructing a biofilm reaction system based on denitrifying bacteria preferential colonization theory.

Understanding the developmental characteristics of microbial communities in biofilms is crucial for designing targeted functional microbial enhancements for the remediation of complex contamination scenarios. The strong prioritization effect of microorganisms confers the ability to colonize strains that arrive first dominantly. In this study, the auto-aggregating denitrifying bacterial Pseudomonas stutzeri strain YC-34, which has both nitrogen and chromium removal characteristics, was used as a biological material to form a stable biofilm system based on the principle of dominant colonization and biofortification. The effect of the biofilm system on nitrogen and chromium removal was characterized by measuring the changes in the quality of influent and effluent water. The pattern of biofilm changes was analyzed by measuring biofilm content and thickness and characterizing extracellular polymer substances (EPS). Further analysis of the biofilm microbiota characteristics and potential functions revealed the mechanism of strain YC-34 biofortified biofilm. The results revealed that the biofilm system formed could achieve 90.56% nitrate-nitrogen removal with an average initial nitrate-nitrogen concentration of 51.9 mg/L and 40% chromium removal with an average initial hexavalent chromium Cr(VI) concentration of 7.12 mg/L. The biofilm properties of the system were comparatively analyzed during the biofilm formation period, the fluctuation period of Cr(VI)-stressed water quality, and the stabilization period of Cr(VI)-stressed water quality. The biofilm system may be able to increase the structure of hydrogen bonds, the type of protein secondary structure, and the abundance of amino acid-like components in the EPS, which may confer biofilm tolerance to Cr(VI) stress and allow the system to maintain a stable biofilm structure. Furthermore, microbial characterization indicated an increase in microbial diversity in the face of chromium stress, with an increase in the abundance of nitrogen removal-associated functional microbiota and an increasing trend in the abundance of nitrogen transfer pathways. These results demonstrate that the biofilm system is stable in nitrogen and chromium removal. This bioaugmentation method may provide a new way for the remediation of heavy metal-polluted water bodies and also provides theoretical and application parameters for the popularization and application of biofilm systems.

Light-Boosting Highly Sensitive and Ultrafast Piezoelectric Sensor Based on Composite Membrane of Copper Phthalocyanine and Graphene Oxide.

Self-powered wearable pressure sensors based on flexible electronics have emerged as a new trend due to the increasing demand for intelligent and portable devices. Improvements in pressure-sensing performance, including in the output voltage, sensitivity and response time, can greatly expand their related applications; however, this remains challenging. Here, we report on a highly sensitive piezoelectric sensor with novel light-boosting pressure-sensing performance, based on a composite membrane of copper phthalocyanine (CuPC) and graphene oxide (GO) (CuPC@GO). Under light illumination, the CuPC@GO piezoelectric sensor demonstrates a remarkable increase in output voltage (381.17 mV, 50 kPa) and sensitivity (116.80 mV/kPa, <5 kPa), which are approximately twice and three times of that the sensor without light illumination, respectively. Furthermore, light exposure significantly improves the response speed of the sensor with a response time of 38.04 µs and recovery time of 58.48 µs, while maintaining excellent mechanical stability even after 2000 cycles. Density functional theory calculations reveal that increased electron transfer from graphene to CuPC can occur when the CuPC is in the excited state, which indicates that the light illumination promotes the electron excitation of CuPC, and thus brings about the high polarization of the sensor. Importantly, these sensors exhibit universal spatial non-contact adjustability, highlighting their versatility and applicability in various settings.

Regulating Microstructure and Macroscopic Properties in Saturated Salt Solutions Containing Disordered Anions and Cations by Magnetic Field.

Saturated aqueous salt solutions have diverse applications in food production, mineral processing, pharmaceuticals, and environmental monitoring. However, the random and disordered arrangement of ions in these solutions poses limitations across different fields. In this study, we employ magnetic fields to regulate the disordered arrangement by a comprehensive methodology combining contact angle measurement, Raman spectroscopy, X-ray diffraction, and molecular dynamics simulations on saturated KCl solutions. Our findings reveal that weak magnetic fields impede the formation of K-Cl contact pairs and disrupt hydrogen bond networks, particularly DDAA and free OH types. However, they facilitate the interaction between water molecules and ions, leading to an increase in the number of K-O and Cl-H contact pairs, along with an expansion in ion hydration radius. These changes affect macroscopic properties, including the interaction with solid substrates and potential solubility increases. Our experimental and simulation results mutually validate each other, contributing to a theoretical framework for studying magnetic field-material interactions.

Biodegradation of atrazine and nicosulfuron by Streptomyces nigra LM01: Performance, degradative pathway, and possible genes involved.

Microbial herbicide degradation is an efficient bioremediation method. In this study, a strain of Streptomyces nigra, LM01, which efficiently degrades atrazine and nicosulfuron, was isolated from a corn field using a direct isolation method. The degradation effects of the identified strain on two herbicides were investigated and optimized using an artificial neural network. The maximum degradation rates of S. nigra LM01 were 58.09 % and 42.97 % for atrazine and nicosulfuron, respectively. The degradation rate of atrazine in the soil reached 67.94 % when the concentration was 108 CFU/g after 5 d and was less effective than that of nicosulfuron. Whole genome sequencing of strain LM01 helped elucidate the possible degradation pathways of atrazine and nicosulfuron. The protein sequences of strain LM01 were aligned with the sequences of the degraded proteins of the two herbicides by using the National Center for Biotechnology Information platform. The sequence (GE005358, GE001556, GE004212, GE005218, GE004846, GE002487) with the highest query cover was retained and docked with the small-molecule ligands of the herbicides. The results revealed a binding energy of - 6.23 kcal/mol between GE005358 and the atrazine ligand and - 6.66 kcal/mol between GE002487 and the nicosulfuron ligand.

Multi-hop clustering routing protocol design based on simultaneous wireless information and power transfer technology and imperfect spectrum sensing for EH-CRSNs.

Existing clustering routing protocols for multi-hop energy harvesting-cognitive radio sensor networks (EH-CRSNs) generally assume perfect spectrum sensing, which is not aligned with the practical spectrum sensing capabilities of nodes in real networks. Additionally, the severe imbalance in residual energy among cluster heads (CHs) negatively affects the successful data delivery. To resolve these problems, this paper introduces a simultaneous wireless information and power transfer (SWIPT)- and imperfect spectrum sensing-based multi-hop clustering routing protocol (ES-ISSMCRP). ES-ISSMCRP makes full use of downlink EH and intra-cluster SWIPT technologies to replenish and equalize the remaining energy among nodes, further extending network lifespan while maintaining network surveillance capabilities. Specifically, to reduce the adverse impact of imperfect spectrum sensing on network performance and improve energy utilization, this paper proposes an EH-based energy level function and associated selection criteria for CHs and relays, facilitating distributed cluster formation and multi-hop routing selection between clusters. To equalize the residual energy among nodes within a cluster, ES-ISSMCRP protocol enables cluster members (CMs) to decide whether employ SWIPT technology with a power splitting (PS) receiver architecture to transmit energy to their CH while sending data. The actual energy value transmitted by CMs using SWIPT technology is deduced by calculating the PS ratio and the expected energy expenditure of nodes for data transmission. Simulation results show that ES-ISSMCRP protocol offers significant improvements over other comparative protocols in terms of extending network lifespan and enhancing network surveillance capabilities.

Early Endonasal Dacryocystorhinostomy for Acute Dacryocystitis: A Systematic Review and Meta-Analysis.

OBJECTIVE: The aim of this meta-analysis is to compare the outcomes of early endonasal dacryocystorhinostomy (DCR) with delayed DCR in the treatment of acute dacryocystitis (AD). METHODS: A comprehensive electronic search of PubMed, Embase, Web of Science, and the Cochrane Library databases was conducted up to November 11, 2023. Data synthesis was performed using Review Manager 5.4, and forest plots were generated for each outcome measure. Potential publication bias was assessed using funnel plots and Egger's test. RESULTS: Six studies involving 288 patients were included in the meta-analysis. Overall, the success rate of early endonasal DCR was comparable to that in the delayed DCR group (odds ratio [OR] = 1.52, 95% confidence interval [CI]: 0.81-2.85, P = .19). Furthermore, in comparison with the delayed DCR group, early endonasal DCR significantly reduced the time for medial canthus swelling resolution (mean differences [MD] = -4.92, 95% CI: -5.46 to 4-.37, P < .00001) and complete resolution of symptoms (MD = -17.70, 95% CI: -23.88 to -11.52, P < .00001). CONCLUSION: Primary early endonasal DCR seems to be a promising and favorable approach for managing AD with comparable efficacy and faster relief of symptoms compared to conventional delayed DCR.

Inhibition of spinal BRD4 alleviates pyroptosis and M1 microglia polarization via STING-IRF3 pathway in morphine-tolerant rats.

BACKGROUND: Morphine tolerance has been a challenging medical issue. Neuroinflammation is considered as a critical mechanism for the development of morphine tolerance. Bromodomain-containing protein 4 (BRD4), a key regulator in cell damage and inflammation, participates in the development of chronic pain. However, whether BRD4 is involved in morphine tolerance and the underlying mechanisms remain unknown. METHODS: The morphine-tolerant rat model was established by intrathecal administration of morphine twice daily for 7 days. Behavior test was assessed by a tail-flick latency test. The roles of BRD4, pyroptosis, microglia polarization and related signaling pathways in morphine tolerance were elucidated by Western blot, real-time quantitative polymerase chain reaction, and immunofluorescence. RESULTS: Repeated morphine administration upregulated BRD4 level, induced pyroptosis, and promoted microglia M1-polarization in spinal cord, accompanied by the release of proinflammatory cytokines, such as TNF-α and IL-1ß. JQ-1, a BRD4 antagonist, alleviated the development of morphine tolerance, diminished pyroptosis and induced the switch of microglia from M1 to M2 phenotype. Mechanistically, stimulator of interferon gene (STING)- interferon regulatory factor 3 (IRF3) pathway was activated and the protective effect of JQ-1 against morphine tolerance was at least partially mediated by inhibition of STING-IRF3 pathway. CONCLUSION: This study demonstrated for the first time that spinal BRD4 contributes to pyroptosis and switch of microglia polarization via STING-IRF3 signaling pathway during the development of morphine tolerance, which extend the understanding of the neuroinflammation mechanism of morphine tolerance and provide an alternative strategy for the precaution against of this medical condition.

Hyperspectral upgrade solution for biomicroscope combined with Transformer network to classify infectious bacteria.

Infectious diseases caused by bacterial pathogens pose a significant public health threat, emphasizing the need for swift and accurate bacterial species detection methods. Hyperspectral microscopic imaging (HMI) offers nondestructive, rapid, and data-rich advantages, making it a promising tool for microbial detection. In this research, we present a highly compatible and cost-effective approach to extend a standard biomicroscope system into a hyperspectral biomicroscope using a prism-grating-prism configuration. Using this prototype, we generate 600 hyperspectral data cubes for Listeria, Bacillus typhi, Bacillus pestis, and Bacillus anthracis. Additionally, we propose a Transformer-based classification network that achieves a 99.44% accuracy in classifying these infectious pathogens, outperforming traditional methods. Our results suggest that the successful combination of HMI and the optimized Transformer-based classification network highlights the potential for rapid and precise detection of infectious disease pathogens .

A Sinh-Cosh-Enhanced DBO Algorithm Applied to Global Optimization Problems.

The Dung beetle optimization (DBO) algorithm, devised by Jiankai Xue in 2022, is known for its strong optimization capabilities and fast convergence. However, it does have certain limitations, including insufficiently random population initialization, slow search speed, and inadequate global search capabilities. Drawing inspiration from the mathematical properties of the Sinh and Cosh functions, we proposed a new metaheuristic algorithm, Sinh-Cosh Dung Beetle Optimization (SCDBO). By leveraging the Sinh and Cosh functions to disrupt the initial distribution of DBO and balance the development of rollerball dung beetles, SCDBO enhances the search efficiency and global exploration capabilities of DBO through nonlinear enhancements. These improvements collectively enhance the performance of the dung beetle optimization algorithm, making it more adept at solving complex real-world problems. To evaluate the performance of the SCDBO algorithm, we compared it with seven typical algorithms using the CEC2017 test functions. Additionally, by successfully applying it to three engineering problems, robot arm design, pressure vessel problem, and unmanned aerial vehicle (UAV) path planning, we further demonstrate the superiority of the SCDBO algorithm.

A diagonal masking self-attention-based multi-scale network for motor imagery classification.

Objective. Electroencephalography (EEG)-based motor imagery (MI) is a promising paradigm for brain-computer interface (BCI), but the non-stationarity and low signal-to-noise ratio of EEG signals make it a challenging task.Approach. To achieve high-precision MI classification, we propose a Diagonal Masking Self-Attention-based Multi-Scale Network (DMSA-MSNet) to fully develop, extract, and emphasize features from different scales. First, for local features, a multi-scale temporal-spatial block is proposed to extract features from different receptive fields. Second, an adaptive branch fusion block is specifically designed to bridge the semantic gap between these coded features from different scales. Finally, in order to analyze global information over long ranges, a diagonal masking self-attention block is introduced, which highlights the most valuable features in the data.Main results. The proposed DMSA-MSNet outperforms state-of-the-art models on the BCI Competition IV 2a and the BCI Competition IV 2b datasets.Significance. Our study achieves rich information extraction from EEG signals and provides an effective solution for MI classification.

The effect of modifier and a water-soluble fertilizer on two forages grown in saline-alkaline soil.

Saline-alkali soil significantly impairs crop growth. This research employs the impacts of the modifier and water-soluble fertilizer, as well as their interaction, on the root systems of alfalfa and leymus chinensis in saline-alkali soil. The results exhibit that the hydrochar source modifier effectively enhances the root growth of both forage species. There are certain improvements in the root growth indicators of both crops at a dosage of 20 g/kg. Root enzyme activity and rhizosphere soil enzyme activity are enhanced in alfalfa, showing significant improvements in the first planting compared to the second planting. The application of water-soluble fertilizers also promotes root growth and root dehydrogenase activity. The root dehydrogenase activity of alfalfa and leymus chinensis are enhanced 62.18% and 10.15% in first planting than that of blank, respectively. Additionally, the two-factor variance analysis revealed a correlation between rhizosphere soil enzyme activity and changes in root traits. Higher rhizosphere soil enzyme activity is observed in conjunction with better root growth. The combined application of a modifier and water-soluble fertilizer has demonstrated a significant interaction effect on various aspects of the first planting of alfalfa and leymus chinensis. Moreover, the combined application of the modifier and water-soluble fertilizer has yielded superior results when compared to the individual application of either the modifier or the water-soluble fertilizer alone. This combined approach has proven effective in improving saline-alkali soil conditions and promoting crop growth in such challenging environments.

Disentangled Generation With Information Bottleneck for Enhanced Few-Shot Learning.

Few-shot learning (FSL) poses a significant challenge in classifying unseen classes with limited samples, primarily stemming from the scarcity of data. Although numerous generative approaches have been investigated for FSL, their generation process often results in entangled outputs, exacerbating the distribution shift inherent in FSL. Consequently, this considerably hampers the overall quality of the generated samples. Addressing this concern, we present a pioneering framework called DisGenIB, which leverages an Information Bottleneck (IB) approach for Disentangled Generation. Our framework ensures both discrimination and diversity in the generated samples, simultaneously. Specifically, we introduce a groundbreaking Information Theoretic objective that unifies disentangled representation learning and sample generation within a novel framework. In contrast to previous IB-based methods that struggle to leverage priors, our proposed DisGenIB effectively incorporates priors as invariant domain knowledge of sub-features, thereby enhancing disentanglement. This innovative approach enables us to exploit priors to their full potential and facilitates the overall disentanglement process. Moreover, we establish the theoretical foundation that reveals certain prior generative and disentanglement methods as special instances of our DisGenIB, underscoring the versatility of our proposed framework. To solidify our claims, we conduct comprehensive experiments on demanding FSL benchmarks, affirming the remarkable efficacy and superiority of DisGenIB. Furthermore, the validity of our theoretical analyses is substantiated by the experimental results. Our code is available at https://github.com/eric-hang/DisGenIB.

P62-autophagic pathway degrades SLC7A11 to regulate ferroptosis in doxorubicin-induced cardiotoxicity.

Doxorubicin-induced cardiotoxicity (DIC) poses a significant challenge, impeding its widespread application. Emerging evidence suggests the involvement of ferroptosis in the DIC. While the downregulation of SLC7A11 expression has been linked to the promotion of ferroptosis, the precise regulatory mechanism remains unclear. Recent studies, including our own, have highlighted abnormal levels of autophagy adapter protein P62 and autophagy in DIC development. Thus, our study aimed to further investigate the role of autophagy and ferroptosis in DIC, elucidating underlying molecular mechanisms across molecular, cellular, and whole-organ levels utilizing gene knockdown, immunoprecipitation, and mass spectrometry techniques. The results of our findings unveiled cardiomyocyte damage, heightened autophagy levels, and ferroptosis in DOX-treated mouse hearts. Notably, inhibition of autophagy levels attenuated DOX-induced ferroptosis. Mechanistically, we discovered that the autophagy adaptor protein P62 mediates the entry of SLC7A11 into the autophagic pathway for degradation. Furthermore, the addition of autophagy inhibitors (CQ or BAF) could elevate SLC7A11 and GPX4 protein expression, reduce the accumulation of Fe2+ and ROS in cardiomyocytes, and thus mitigate DOX-induced ferroptosis. In summary, our findings underscore the pivotal role of the P62-autophagy pathway in SLC7A11 degradation, modulating ferroptosis to exacerbate DIC. This finding offers significant insights into the underlying molecular mechanisms of DOX-induced ferroptosis and identifies new targets for reversing DIC.

TiO2 nanofilms for surface-enhanced Raman scattering analysis of urea.

In this study, titanium dioxide (TiO2) nanofilms with nanoparticle structure were grown in situ on metallic aluminum (Al) sheets using a simple sol-hydrothermal method. Al sheets were chosen because they can form Schottky junctions with TiO2 during the calcination process, thus achieving a tight bonding between the nanoparticles and the solid substrate, which cannot be achieved with conventional glass substrates. The substrates synthesized with different contents of titanium butoxide [Ti(OBu)4] were investigated using 4-mercaptobenzoic acid as a probe molecule, and the results showed that the substrate with 9 % of the total volume of Ti(OBu)4 had the highest surface-enhanced Raman scattering (SERS) performance. As a low-cost SERS substrate that is simple to synthesize, it has excellent signal reproducibility, with a relative standard deviation of 4.51 % for the same substrate and 6.43 % for different batches of synthesized substrates. Meanwhile, the same batch of substrate can be stored at room temperature for at least 20 weeks and still maintain stable SERS signals. In addition, the synthetic substrate was used to quantitatively detect urea with a detection limit of 4.23 × 10-3 mol/L, which is comparable to the application of noble metal substrates. The feasibility of this method was verified in human urine, and the results were consistent with the clinical results, indicating that this method has great potential for clinical application.

Enhanced humification via lignocellulosic pretreatment in remediation of agricultural solid waste.

Stover and manure are the main solid waste in agricultural industry. The generation of stover and manure could lead to serious environmental pollution if not handled properly. Composting is the potential greener solution to remediate and reduce agricultural solid waste, through which stover and manure could be remediated and converted into organic fertilizer, but the long composting period and low efficiency of humic substance production are the key constraints in such remediation approach. In this study, we explore the effect of lignocellulose selective removal on composting by performing chemical pretreatment on agricultural waste followed by utilization of biochar to assist in the remediation by co-composting treatment and reveal the impacts of different lignocellulose component on organic fertilizer production. Aiming to discover the key factors that influence humification during composting process and improve the composting quality as well as comprehensive utilization of agricultural solid waste. The results demonstrated that the removal of selective lignin or hemicellulose led to the shift of abundances lignocellulose-degrading bacteria, which in turn accelerated the degradation of lignocellulose by almost 51.2%. The process also facilitated the remediation of organic waste via humification and increased the humic acid level and HA/FA ratio in just 22 days. The richness of media relies on their lignocellulose content, which is negatively correlated with total nitrogen content, humic acid (HA) content, germination index (GI), and pH, but positively correlated with fulvic acid (FA) and total organic carbon (TOC). The work provides a potential cost effective and efficient framework for agricultural solid waste remediation and reduction.

A look-up-table development to facilitate CT simulation of MR-Linac treatment.

While current MR-Linac (MRL) treatment workflows utilize a large table overlay during CT simulation to convert indexing between the two machines, we developed a look-up-table (LUT) as an alternative approach. After populating the LUT, index conversion factors were verified at three separate table locations. The resultant root-mean-square isocenter shifts on the MRL were 0.04/0.08 cm, 0.08/0.07 cm, and 0.09/0.08 cm with/without using the table overlay during simulation in the lateral, longitudinal, and vertical directions, respectively, which is within registration tolerance. Clinical implementation of the LUT has resulted in a more efficient MRL treatment workflow while maintaining accurate patient setup.

Transition and trend analysis of the burden of depression in China and different income countries: Based on GBD database and joinpoint regression model.

BACKGROUND: Depression is a leading cause of disability and poor health worldwide and is expected to rank first worldwide by 2030. The aim of this study is to analyze the transition and trend of depression burden in China and various income-level countries by utilizing the Global Burden of Disease (GBD) database and the Joinpoint regression model. This analysis seeks to comprehend the variations in the burden of depression across different income regions and evaluate their developmental patterns. METHODS: Based on the GBD 2019 open dataset, this study extracted data on YLD (Years Lived with Disability), DALY (Disability-Adjusted Life Years), and incidence related to depression. The analysis focused on the period between 1990 and 2019, covering global data and distinguishing between high-income, upper-middle-income, lower-middle-income, low-income countries, and China. We utilized the Joinpoint regression model to fit the spatiotemporal trend changes among different income-level countries. Pairwise comparisons were conducted to examine the parallelism and to determine if the differences in trend changes among various regions were statistically significant. RESULTS: From 1990 to 2019, the age-standardized YLD and DALY for depression female were higher than that in male. The YLD total change rate of depression men was higher than that of women. China exhibited the largest disparity in total YLD change rates between genders, reaching 0.08. During 1990 to 2019, the incidence of depression in 2005-2019 increased among females in middle to high-income countries, low-income countries, and China as compare to that of 1990-2005. Notably, China shown the most increase the incidence rate of females (from -0.4 % to 0.84 %). China experienced the most significant change in the YLD of depression during this period (AAPC = 0.45, 95 % CI = 0.41, 0.48, P < 0.01). China's YLD/Incidence rate was higher compared to the global, HICs, UMCs, LMCs, and LICs. In China, the YLD/incidence rate of depression began to rise in 1994, peaking around 2010, and then gradually declining. Since 2010, the growth rate of depression DALYs in China has been higher than the global average, high-income countries, upper-middle-income countries, lower-middle-income countries, and low-income countries. The DALY's AAPC value for the HLCs was the highest (AAPC = 0.24, 95 % CI = 0.22, 0.25, P < 0.01). The UMCs, in comparison to other regions, incidence rate had the highest AAPC value (AAPC = 0.48, 95 % CI = 0.46, 0.50, P < 0.01). CONCLUSIONS: Given the significant variations in the burden of depression across countries with different income levels, future strategies aimed at reducing the burden of depression should adopt tailored and differentiated approaches according to each country's specific needs and developmental stages.

Practice of distributed machine learning in clinical modeling for chronic obstructive pulmonary disease.

Background: The high prevalence, morbidity and mortality, and disease heterogeneity of chronic obstructive pulmonary disease (COPD) result in the scattered data derived from patient visits in different medical units. The huge cost of integrating the scattered data for analysis and modeling, as well as the legal demand for patient privacy protection lead to the emergence of data island. Objectives: On the premise of protecting patient privacy, integrating scattered data of patients from different medical units for high-quality modeling is beneficial to promoting the development of digital health. Based on this, we develop a distributed COPD disease diagnosis system termed COPD average federated learning (COPD_AVG_FL) using FedAvg. Methods: First, to build the COPD_AVG_FL, the clinical data of COPD patients from the real world is collected and the data pre-processing is performed to clean the incorrect data, outlier samples and missing values. Then, a classical federated learning architecture is designed as COPD_AVG_FL. Finally, to evaluate the established COPD_AVG_FL system, we develop Centralized Machine Learning (CML). Conclusions: Our results suggest that, with the assistance of COPD_AVG_FL, the absolute improvement rates are 13.4% (accuracy), 13.3% (precision), 12.8% (recall), 13.1% (F1-Score) and 12.9% (AUC) on the test data, respectively. The decoupling between model training and raw training data protects the patients' privacy, and helps to securely integrate more COPD data from different medical units to generate a more comprehensive model COPD_AVG_FL. This approach promotes the landing of wise information technology of medicine for COPD in the real clinical world. Code for our model will be made available at https://github.com/Cczhh/COPD_AVG_FL/tree/master.