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Reactive astrogliosis is one of the most frequency neuropathological alterations in the hippocampus of animal models and patients with temporal lobe epilepsy (TLE). Valproic acid (VPA), a widely used antiepileptic drug (AED), acts by blocking ion channels and enhancing GABAergic activity. This study investigated the effects of VPA on hippocampal astrogliosis in a rat model of TLE. The results demonstrated that chronic administration of VPA at a dose of 200 mg/kg significantly reduced the severity of astrogliosis and ameliorated neuronal loss in the hippocampus at the early and middle stages post-status epilepticus (SE), while also improving cognitive impairments at the middle and late stages in KA-SE rats. Long-term administration of VPA at 400 mg/kg attenuated astrogliosis in the hippocampus at the middle stage post-SE, but lacked neuroprotective effects and exacerbated cognitive impairments at the late stage. These findings suggest that VPA at an appropriate dose could mitigate hippocampal astrogliosis, potentially offering a new antiepileptic mechanism for its long-term use.

Abstract The early diagnosis of esophageal cancer (EC) is extremely challenging due to a lack of effective diagnostic methods. The study presented herein aims to assess whether serum volatile organic compounds (VOCs) could be utilised as emerging diagnostic biomarkers for EC. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in the serum samples of 55 patients with EC, with samples from 84 healthy controls (HCs) patients analysed as a comparison. All machine learning analyses were based on data from serum VOCs obtained by GC-IMS. A total of 33 substance peak heights were detected in all patient serum samples. The ROC analysis revealed that four machine learning models were effective in facilitating the diagnosis of EC. In addition, the random forests model for 5 VOCs had an AUC of 0.951, with sensitivities and specificities of 94.1 and 96.0%, respectively.

Anaerobic digestion (AD) has been widely used as a promising technology for the treatment of kitchen waste (KW). The effects of several acidification-resisting methods were compared, which included the supplementation of trace elements (TEs) and zero-valent iron (ZVI) / powdered activated carbon (PAC), and the application of the sludge domesticated by acetic acid (HAc) and KW as inoculum. The results showed that the supplementation of TEs and ZVI/PAC at total solid (TS) content of 6% and optimal addition doses resulted in an increase in methane yield to 346 and 366 mL/g VS, respectively. In addition, the methane yields of 327 and 241 mL/g VS were obtained by applying the sludge domesticated with KW and HAc as inoculum, while the methane yield of the control was only 89.2 mL/g VS, representing a relative increase of 288%, 311%, 267%, and 170%. The acidification could be alleviated by applying these methods, and also the methanogenic profile was improved. Furthermore, microbial community analysis revealed that the enrichment of Methanosarcina, which enhanced the substrate utilization capacity and subsequently increased methane production, was achieved through the addition of TEs and ZVI/PAC, along with the application of sludge domesticated by KW.

Owing to the rapid development of the ambient Internet of Things (IoT) industry, Backscatter Communication Systems (BCS) require higher receiver sensitivity for large-scale IoT scenarios than traditional Radio Frequency Identification (RFID) systems. This paper proposes a method of using Multiple-Input Multiple-Output (MIMO) technology to compensate for reflected signals in the 920 MHz backscatter communication systems. The researcher first created a MATLAB model to verify the theoretical feasibility and then built a One-Transmitter Two-Receiver (1T2R) BCS transceiver system compatible with the EPC global protocol for practical verification on LabVIEW. The ITIR and 1T2R tests were conducted using the National Instrument (NI) USRP-2952R device, the directional antennas, and the standard RF electronic tags. Through the process of superimposing and utilizing the phase shift between the two reflected carriers, it has been confirmed that the overall signal strength can be enhanced from 2.2 mV to 4.13 mV and 4.37 mV (nearly reaching 4.70 mV by using two Rx antennas in ideal conditions). After calculation, this advancement increases signal strength from −40.14 dBm (when using a single Rx antenna) to −34.18 dBm (when using two Rx antennas). The improvement in signal strength can provide a gain of 5.96 dB to the backscatter communication systems. Experimental results demonstrate that utilizing MIMO technology to the backscatter communication systems can effectively enhance the sensitivity of the receiver at 920 MHz.

BackgroundLipodystrophy is a rare disease that is poorly diagnosed due to its low prevalence and frequent phenotypic heterogeneity. The main therapeutic measures for patients with clinical lipodystrophy are aimed at improving general metabolic complications such as diabetes mellitus, insulin resistance, and hypertriglyceridemia. Therefore, there is an urgent need to find new biomarkers to aid in the diagnosis and targeted treatment of patients with congenital generalized lipodystrophy (CGL).MethodsDataset GSE159337 was obtained via the Gene Expression Omnibus database. First, differentially expressed genes (DEGs) between CGL and control samples were yielded via differential expression analysis and were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment to explore the functional pathways. Next, protein–protein interaction analysis and the MCC algorithm were implemented to yield candidate genes, which were then subjected to receiver operating characteristic (ROC) analysis to identify biomarkers with an area under the curve value exceeding 0.8. Moreover, random forest (RF), logistic regression, and support vector machine (SVM) analyses were carried out to assess the diagnostic ability of biomarkers for CGL. Finally, the small-molecule drugs targeting biomarkers were predicted, and ibuprofen was further validated in lipodystrophy mice.ResultsA total of 71 DEGs in GSE159337 were sifted out and were involved in immune receptor activity, immune response-regulating signaling pathway, and secretory granule membrane. Moreover, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN were considered as biomarkers by performing ROC analysis on 10 candidate genes. Meanwhile, RF, logistic regression, and SVM analyses further described that those biomarkers had an excellent diagnosis capability for CGL. Eventually, the drug–gene network included ibuprofen–CXCR1, ibuprofen–CXCR1, cenicriviroc–CCR2, fenofibrate–JUN, and other relationship pairs. Ibuprofen treatment was also validated to downregulate CXCR1 and CXCR2 in peripheral blood mononuclear cells (PBMCs) and improve glucose tolerance, hypertriglyceridemia, hepatic steatosis, and liver inflammation in lipodystrophy mice.ConclusionEight biomarkers, namely, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN, were identified through bioinformatic analyses, and ibuprofen targeting CXCR1 and CXCR2 in PBMCs was shown to improve metabolic disturbance in lipodystrophy, contributing to studies related to the diagnosis and treatment of lipodystrophy.

Abstract Background This study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients. Methods This study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy. Results In the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852–0.925), 0.919 (95% CI 0.856–0.983), and 0.811 (95% CI 0.731–0.891), respectively. Conclusions This study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.

Abstract Early diagnosis of esophageal cancer (EC) is extremely challenging. The study presented herein aimed to assess whether urinary volatile organic compounds (VOCs) may be emerging diagnostic biomarkers for EC. Urine samples were collected from EC patients and healthy controls (HCs). Gas chromatography-ion mobility spectrometry (GC-IMS) was next utilised for volatile organic compound detection and predictive models were constructed using machine learning algorithms. ROC curve analysis indicated that an 8-VOCs based machine learning model could aid the diagnosis of EC, with the Random Forests having a maximum AUC of 0.874 and sensitivities and specificities of 84.2% and 90.6%, respectively. Urine VOC analysis aids in the diagnosis of EC.

This paper studies the dynamic behavior of a stochastic SEIRM model of COVID-19 with a standard incidence rate. The existence of global solutions for dynamic system models is proven by integrating stochastic process theory and the concept of stopping times, together with the contradiction method. Moreover, we construct appropriate Lyapunov functions to analyze system stability and apply Dynkin’s formula and Fatou’s lemma to handle stopping times and expectations of stochastic processes. Notably, the extinction study provides mathematical proof that under the given system dynamics, the total population does not grow indefinitely but tends to stabilize over time. The properties of the diffusion matrix are harnessed to guarantee the system’s stationary distribution. Conclusively, numerical simulations confirm the model’s extinction outcomes.

In recent years, the poultry breeding industry has been converted into a large-scale, intensive, and intelligent production mode. The Internet of Things (IoT) is under rapid development, which promotes the development of precision livestock farming. In this study, we developed an intelligent service platform for a facility environment based on the IoT structure, utilizing the capabilities of Platform as a Service (PaaS). The platform consists of four layers, including an information perception layer, network layer, management service layer, and application layer. By using the cloud service model with a distributed network architecture, asynchronous data transmission, and a distributed file system, the platform can centrally manage multiple farm’s data. The intelligent service platform includes the following functions: displaying environmental data, water and electricity consumption, data analysis, and managing production data. Over a 500-day trial period in a live poultry house, the platform demonstrated high data integrity (>87%) and resilience against network disruptions and power outages. The data validity of each environmental element exceeded 94%, among which the validity of the temperature, humidity, and carbon dioxide concentration exceeded 99%. The overall accuracy of the dataset remained relatively high, providing a robust data foundation for further research. Key features included audio analysis, environmental monitoring, and production data management. The platform’s operational status was efficiently communicated via data statistics and email alerts, facilitating timely system recovery. The demonstrated modules included sound recognition, psychrometric charts for visual alerts, and financial analysis tools, offering versatile solutions for integrating PLF models and advanced analytics.

This paper studies the persistence, extinction and practical exponential stability of impulsive stochastic competition models with time-varying delays. The existence of the global positive solutions is investigated by the relationship between the solutions of the original system and the equivalent system, and the sufficient conditions of system persistence and extinction are given. Moreover, our study shows the following facts: (1) The impulsive perturbation does not affect the practical exponential stability under the condition of bounded pulse intensity. (2) In solving the stability of non-Markovian processes, it can be transformed into solving the stability of Markovian processes by applying Razumikhin inequality. (3) In some cases, a non-Markovian process can produce Markovian effects. Finally, numerical simulations obtained the importance and validity of the theoretical results for the existence of practical exponential stability through the relationship between parameters, pulse intensity and noise intensity.

Mesoscale eddies play a significant role in marine energy and matter transportation. Due to their huge impact on the ocean, mesoscale eddy detection has been studied for many years. However, existing methods mainly use single-modal data, such as the sea surface height (SSH), to detect mesoscale eddies, resulting in inaccurate detection results. In this paper, we propose an end-to-end mesoscale eddy detection method based upon multi-modal data fusion. Particularly, we don’t only use SSH, but also add data of other two modals, i.e., the sea surface temperature (SST) and the velocity of flow, which are closely related to mesoscale eddy detection. Moreover, we design a novel network named SymmetricNet, which is able to achieve multi-modal data fusion in mesoscale eddy detection. The proposed SymmetricNet mainly contains a downsampling pathway and an upsampling pathway, where the low-level feature maps from the downsampling pathway and the high-level feature maps from the upsampling pathway are merged through lateral connections. In addition, we apply dilated convolutions to the network structure to increase the receptive field without sacrificing resolution. Experiments on multi-modal mesoscale eddy dataset demonstrate the advantages of the proposed method over previous approaches for mesoscale eddy detection.

Underwater images are generally of low quality, limiting the performance of subsequent perceptual tasks, such as underwater object detection and recognition. However, only a few methods can improve the quality of underwater images by simultaneously restoring and super-resolving underwater images. In this paper, we propose an end-to-end trainable model based on generative adversarial networks (GANs) called Simultaneous Restoration and Super-Resolution GAN (SRSRGAN) to obtain clear super-resolution underwater images automatically. In particular, our model leverages a cascaded architecture with two stages of carefully designed generative adversarial networks to restore and super-resolve corrupted underwater images in a coarse-to-fine manner. The major advantages of SRSRGAN are twofold. First, it is a unified solution that can simultaneously restore and super-resolve images. Second, SRSRGAN is not limited by the prior experience of the types and levels of underwater degraded images but can perform the inference using only observed corrupted images. These two advantages enable SRSRGAN to enjoy better flexibility and higher practicability in realistic underwater scenarios. Extensive experimental results demonstrate the superiority of SRSRGAN in underwater image restoration, super-resolution, and simultaneous restoration and super-resolution.

Prostate cancer (PCa) is one of the most common cancers in men worldwide. Early diagnosis of PCa is extremely challenging due to the lack of effective diagnostic methods. The study presented here aims to evaluate whether urine volatile organic compounds (VOCs) can be used as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in urine samples from 66 patients with PCa and to comparatively analyze samples from 87 patients with non-cancerous controls (NCs). A total of 86 substance peak heights were detected in urine samples from all patients. Analysis using four machine learning algorithms suggested that the diagnosis of PCa could be effectively facilitated. Ultimately, diagnostic models were constructed based on the four VOCs selected. The AUC for the RF and SVM model were 0.955 and 0.981, respectively. Both the NN and DT diagnostic models also achieved an AUC of 0.8 or more, but their sensitivity or specificity was poor compared to the RF and SVM models.

Ultrasound has been proven to enhance the mass transfer process and impact the fabrication of anodic aluminum oxide (AAO). However, the different effects of ultrasound propagating in different media make the specific target and process of ultrasound in AAO remain unclear, and the effects of ultrasound on AAO reported in previous studies are contradictory. These uncertainties have greatly limited the application of ultrasonic-assisted anodization (UAA) in practice. In this study, the bubble desorption and mass transfer enhancement effects were decoupled based on an anodizing system with focused ultrasound, such that the dual effects of ultrasound on different targets were distinguished. The results showed that ultrasound has the dual effects on AAO fabrication. Specifically, ultrasound focused on the anode has a nanopore-expansion effect on AAO, leading to a 12.24 % improvement in fabrication efficiency. This was attributed to the promotion of interfacial ion migration through ultrasonic-induced high-frequency vibrational bubble desorption. However, AAO nanopores were observed to shrink when ultrasound was focused on the electrolyte, accompanied by a 25.85 % reduction in fabrication efficiency. The effects of ultrasound on mass transfer through jet cavitation appeared to be the reason for this phenomenon. This study resolved the paradoxical phenomena of UAA in previous studies and is expected to guide AAO application in electrochemistry and surface treatments.

This study aims to explore the trajectories of health inequalities induced by childhood SES across the life course in China. There are two competing theories on this subject. Cumulative disadvantage theory contends that health gaps induced by childhood SES tend to widen across the life course as adulthood SES compound or multiply the negative effects of early SES disadvantage. Age-neutral theory draws the opposite inference that the physiological decline due to aging offsets the health gaps at older ages. Based on the data of the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018, a two-level mixed-effects model was used to analyze the trajectories of health inequalities induced by childhood SES among Chinese individuals aged 45 and above and further distinguished the age and cohort effects in the overall trajectories. Unlike previous studies that unilaterally supported one of these theories, our findings support both of them. In this study, health gaps induced by childhood SES gradually widened before entering old age, which supports the cumulative disadvantage theory. In contrast, the health gaps in older adults gradually converged with age, thus supporting the age-neutral theory. The age effect shows that in the same birth cohort, health gaps induced by childhood SES first increased and then decreased during the survey time. The cohort effect shows that, at the same age, childhood SES has a greater impact on the health of those with later birth cohorts than on those with earlier birth cohorts. The findings of this study support the importance of policy and practices to reduce health inequalities among adolescents for long-term healthy aging in China.

BackgroundThe medical financial burden has become a key limitation to accessing healthcare in rural areas of China as healthcare expenses continue to rise. To ensure that low-income people have access to basic healthcare services, China has implemented medical financial assistance (MFA) policy, which provides social health insurance and medical cash assistance for low-income people.MethodsUsing data from the 2014 China Family Panel Studies (CFPS), the propensity score matching (PSM) method was applied to estimate the impact of MFA on healthcare expenses and the medical financial burden.ResultsEmpirical results showed that the total annual healthcare expenditure of MFA beneficiaries is significantly higher than that of non-beneficiaries after matching. Although low-income individuals are now covered by MFA, neither the out-of-pocket expenditure to per capita household non-food expenditure ratio nor the likelihood of catastrophic healthcare expenditure (CHE) decrease significantly.ConclusionMedical financial assistance (MFA) has reduced the inequality in healthcare utilization to a certain extent by improving access to healthcare for low-income people. However, people with low income still face a heavy medical financial burden even when they are covered by MFA. Policymakers should pay attention to raising the standards of MFA in rural areas and providing higher subsidies for the reasonable healthcare expenditures of low-income people.

The spread of rumors in online social networks (OSNs) has caused a serious threat to the normal social order. In order to describe the rumor-spreading dynamics in OSNs during emergencies, a novel model with consideration of fans versus ordinary people is proposed in this paper. In contrast to previous studies, we consider the case that two rumors exist simultaneously. It is assumed that one is an entertainment rumor that fans care about, and the other is a common rumor. First, we derive the mean-field equations that describe the dynamics of this dual rumor propagation model and obtain the threshold parameter. Secondly, after finding the necessary and sufficient conditions for the existence of equilibriums, we examine the equilibrium’s local and global stability. Finally, simulations are used to explain how various parameters affect the process of spreading rumors.

This paper investigates the exponential stability of a class of neutral inertial neural networks with multi-proportional delays and leakage delays. By utilizing the Lyapunov stability theory, the approach of parametric variation, and the differential inequality technique, some criteria are acquired that can guarantee that all solutions of the addressed system converge exponentially to the equilibrium point. In particular, the neutral term, multi-proportional delays, and leakage delays are incorporated simultaneously, resulting in a more general model, and the findings are novel and refine the previous works. Finally, one example is provided to indicate that the dynamic behavior is consistent with the theoretical analysis.

This paper is devoted to investigating a class of neutral-type integral differential equations arising in an epidemic model. By using Mawhin’s continuation theorem and the properties of neutral-type operators, we obtain the existence conditions for positive periodic solutions of the considered neutral-type integral differential equation. Compared with previous results, the existence conditions in this paper are less restricted, thus extending the results of the existing literature. Finally, two examples are given to show the effectiveness and merits of the main results of this paper. Our results can be used to obtain the existence of a positive periodic solution to the corresponding non-neutral-type integral differential equation.

Abstract Background Prolonged mechanical ventilation (MV) induces diaphragm dysfunction in patients in the intensive care units (ICUs). Our study aimed to explore the therapeutic efficacy of early rehabilitation therapy in patients with prolonged MV in the ICU. Methods Eighty eligible patients who underwent MV for > 72 h in the ICU from June 2019 to March 2020 were enrolled in this prospective randomised controlled trial. The patients were randomly divided into a rehabilitation group (n = 39) and a control group (n = 41). Rehabilitation therapy included six levels of rehabilitation exercises. Diaphragm function was determined using ultrasound (US). Results Diaphragmatic excursion (DE) and diaphragm thickening fraction (DTF) were significantly decreased in all patients in both groups after prolonged MV (p

Abstract Background With the accelerated ageing of the population in China, the health problems of elderly people have attracted much attention. Although religious belief has been shown to be a key way to improve the health of elderly people in various studies, little is known about the causal relationship between these variables in China. This paper explores the effect of religious belief on the health of elderly people in China, which will provide an important reference for China to achieve healthy ageing. Methods Balanced panel data collected between 2012 and 2016 from the China Family Panel Studies (CFPS) were used. Health was assessed using self-rated health, and religious belief was measured by whether the respondents believed in a religion. The DID+PSM method was employed to solve the endogeneity problem caused by self-selection and omitted variables. In addition, the CESD score (replacing self-rated health) and different matching methods (the method of PSM after DID method) were used to perform the robustness test. Results The results show that religious belief has no significant effect on the health of elderly people. With the application of different matching methods (one-to-one matching, K-nearest neighbour matching, radius matching and kernel matching) and replacing the health indicator (the CESD score) with the above matching methods, the results are still robust. Conclusion In China, religious belief plays a limited role in promoting “healthy ageing”, and it is difficult to improve the health of elderly people only via religious belief. Therefore, except for focusing on the guidance of religion with regard to healthy lifestyles, multiple measures need to be taken to improve the health of elderly people.

This paper studies the practical exponential stability of an impulsive stochastic food chain system with time-varying delays (ISOFCSs). By constructing an auxiliary system equivalent to the original system and comparison theorem, the existence of global positive solutions to the suggested system is discussed. Moreover, we investigate the sufficient conditions for the exponential stability and practical exponential stability of the system, which is given by Razumikhin technique and the Lyapunov method. In addition, when Razumikhin’s condition holds, the exponential stability and practical exponential stability of species are independent of time delay. Finally, numerical simulation finds the validity of the method.

Psychological stress is a negative affective state. The association between physical activity and psychological stress was commonly reported in previous researches. Few published studies with large sample sizes have explored such an association in Chinese population. The current research aims to assess the association between perceived stress and physical activity preferences, as well as the association between risk of high perceived stress and physical activity behaviors (e.g., sports-, transport-, occupational-related physical activity, sedentary activities and time in bed). The data were collected from the China Health and Nutrition Survey (CHNS) in 2015. Generalized linear models and logistic regression models were used to explore the association between perceived stress and physical activity. In total, 11,066 participants were included in the current analysis. For physical activity preferences, we found that “like” preference of all six mentioned domains of activities contributed to lower perceived stress (i.e., lower perceived stress scale −14 score, all β < 0 and p < 0.05). For physical activity behaviors, the results indicated that none/low intensity physical activity behaviors (e.g., sports-, occupational- related, sedentary) were associated with risk of high perceived stress, except that low intensity of transport-related activities seemed to be protective from high stress. However, the association between intensity of physical activity behaviors and perceived stress was not simply the higher the better. High intensity of all these physical activity behaviors was also associated with high perceived stress. Our findings suggest that positive preferences and moderate physical activity behaviors were associated with low perceived stress. The findings herein highlight the effect of regulating physical activity on perceived stress, as well as inform potential strategies to reduce psychological stress.

Wood vinegar wastewater (WVWW) is the main by-product of biomass pyrolysis process, which is more suitable to use anaerobic digestion (AD) to achieve energy recovery due to its large amount of organic matter. In this study, the up-flow anaerobic sludge bed (UASB) reactor was used to investigate the continuous anaerobic transformation of WVWW with gradient concentrations (0.3, 0.675, 1, 2, 3, 4, 5, 6, and 7 g COD/L). Then, the changes of microbial community, diversity index and functional gene were analyzed in detail. The results revealed that WVWW showed good AD performance in continuous fermentation. WVWW of organic loading rate (OLR) of >8.58 g COD/L⋅d showed severe inhibition on biodegradability and methane production, which is mainly due to the toxic substances as compared with the control group. The bacterial communities were dominated by phyla of Chloroflexi, Firmicutes, Proteobacteria, Acidobacteria, Synergistetes, and Actinobacteria. The gene abundances related to energy production, carbohydrate transport and metabolism were relatively high, which are mainly responsible for carbon forms conversion and carbohydrate degradation. This study will provide a basis for the screening and enrichment of functional bacteria and genes.

Depression is considered a widespread neuropsychiatric disease associated with neuronal injury within specific brain regions. Fluoxetine, a selective serotonin reuptake inhibitor, has been widely used in depressed patients. Recently, fluoxetine has demonstrated neuroprotective effects apart from the effect on serotonin. However, the underlying mechanism involved in this neuroprotection remains unclear, in particular, whether fluoxetine exerts antidepressant effects via protecting against neuronal injury. Here, we found that treatment with fluoxetine (10 mg/kg, i.p.) for 2 weeks ameliorated depression-like behaviors in a chronic unpredictable mild stress (CUMS)-induced rat model of depression and was accompanied with an alleviation of glia activation and inhibition of interleukin-1β (IL-1β), interferon gamma (IFN-γ), and tumor necrosis factor-α (TNF-α) expression in the hippocampal dentate gyrus (DG) region. Meanwhile, CUMS rats treated with fluoxetine showed reductions in neuronal apoptosis and a downregulation of the apoptotic protein Bax, cleaved caspase 3, and caspase 9 levels. These effects appear to involve a downregulation of p38 mitogen-activated protein kinase (MAPK) signaling within the DG hippocampus as the specific inhibitor of p38 MAPK, SB203580, significantly suppressed apoptosis, as well as ameliorated depressive behaviors resulting from CUMS exposure. Moreover, fluoxetine could rescue neuronal deterioration and depression-like phenotypes caused by overexpression of p38 in DG. This finding extends our knowledge on the antidepressant-like effects of fluoxetine, which appear to at least partially profit from neuroprotection against inflammation and neuronal apoptosis via downregulation of the p38 MAPK pathway. The neuroprotective mechanisms of fluoxetine may provide some novel therapeutic avenues for stress-related neurological diseases.