Paired immunoglobulin-like receptor B (PirB) has been identified as a new receptor for myelin-associated inhibitory (MAI) proteins, which may play important role in axonal regeneration and corticospinal tract (CST) projection associated with neurobehavioral function recovery after stroke. Here, we found that the expression of PirB was increased in the cortical penumbra from 1 to 28 days after transient focal cerebral ischemic reperfusion of rats. Then, transactivator of transcription-PirB extracellular peptide (TAT-PEP) was generated that might block the interactions between MAIs and PirB. The results showed that TAT-PEP displayed high affinity for MAIs and ameliorated their inhibitory effect on neurite growth. Furthermore, TAT-PEP can widely distribute in the penumbra after intraperitoneal injection. Then, we found that TAT-PEP enhanced neurite growth and alleviated growth cone collapse after oxygen glucose deprivation (OGD) injury. In addition, TAT-PEP promoted long-term neurobehavioral functional recovery through enhancing axonal regeneration and CST projection. Finally, the observations demonstrated that POSH/RhoA/growth-associated protein 43 (GAP43) as PirB-associated downstream signaling molecules played important role in neurobehavioral functional recovery after stroke. Moreover, the underlying mechanism associated with TAT-PEP-mediated promoting axonal regeneration and CST projection was by intervening in the expression of POSH, RhoA, and GAP43. These studies suggest that TAT-PEP may represent an attractive therapeutic strategy against stroke.

ObjectivesThis study aimed to investigate the impact of meteorological factors on the incidence and multi-route transmission dynamics of hepatitis E virus (HEV) in Jiangsu Province, China, during the pre-COVID-19 era (2005–2018), and to develop predictive models for informing public health interventions.Study designA dual-model study integrating the Multi-Host and Multi-Route Transmission Dynamic Model (MHMRTDM) and Generalized Additive Model (GAM) was employed to quantify meteorological impacts on multi-route HEV transmission.MethodsHEV incidence data (2005–2018) and meteorological variables from provincial and national agencies were analyzed. The MHMRTDM quantified transmission rate coefficients (β, βw and βp′). GAMs linked the transmission coefficients and incidence to meteorological factors, validated using 2017–2018 data.ResultsThe optimal GAM integrated with the MHMRTDM was established (lowest GCV = 1.705 × 10−21, R2 = 0.980, lowest RMSE = 3.682 × 10−11, lowest MAE = 2.987 × 10−11). Analysis of four dependent variables (incidence, β, βw and βp′) revealed distinct climate-driven patterns: (1) Incidence exhibited dual seasonal peaks linked to atmospheric pressure, sunshine duration, and humidity; (2) Host-to-person transmission (βp′) was most sensitive to climatic conditions, peaking at 1013 hPa and declining sharply above 75% humidity, while susceptible person-to-infected person (β) and environment-to-person (βw) transmission were primarily modulated by humidity and wind speed; (3) The GAM validation confirmed robust performance for transmission coefficients (p < 0.001). Predictions for 2019–2021 highlighted persistent seasonal bimodality, reinforcing the model’s utility for outbreak forecasting.ConclusionMeteorological factors drive HEV transmission through distinct pathways, with host-to-person interactions being particularly climate-sensitive. While the GAM provided valuable insights, future research incorporating behavioral and land-use factors, as well as causal inference models, will be critical for improving the understanding and predictive accuracy of HEV transmission dynamics.

Background: Sleep loss and its associated conditions (e.g. cognitive deficits) represent a large societal burden, but the underlying mechanisms of these cognitive deficits remain unknown. This study assessed the effect of dexmedetomidine (DEX) on cognitive decline induced by sleep loss. Methods: C57BL/6 mice were subjected to chronic sleep restriction (CSR) for 20 h (5 pm-1 pm the next day) daily for 7 days, and cognitive tests were subsequently carried out. The neuromolecular and cellular changes that occurred in the presence and absence of DEX (100 mu g kg(-1), i.v., at 1 pm and 3 pm every day) were also investigated. Results: CSR mice displayed a decline in learning and memory by 12% (P<0.05) in the Y-maze and by 18% (P<0.01) in the novel object recognition test; these changes were associated with increases in microglial activation, CD68+ microglial phagosome counts, astrocyte-derived complement C3 secretion, and microglial C3a receptor expression (all P<0.05). Synapse elimination, as indicated by a 66% decrease in synaptophysin expression (P=0.0004) and a 45% decrease in postsynaptic density protein-95 expression (P=0.0003), was associated with the occurrence of cognitive deficits. DEX activated astrocytic alpha(2A) adrenoceptors and inhibited astrocytic complement C3 release to attenuate synapse elimination through microglial phagocytosis. DEX restored synaptic connections and reversed cognitive deficits induced by CSR. Conclusions: The results demonstrate that complement pathway activation associated with synapse elimination contributes to sleep loss-related cognitive deficits and that dexmedetomidine protects against sleep deprivation-induced complement activation. Dexmedetomidine holds potential for preventing cognitive deficits associated with sleep loss, which warrants further study.

Type 2 diabetes mellitus (T2DM) induced diabetes-associated cognitive dysfunction (DACD) that seriously affects the self-management of T2DM patients, is currently one of the most severe T2DM-associated complications, but the mechanistic basis remains unclear. Mitochondria are highly dynamic organelles, whose function refers to a broad spectrum of features such as mitochondrial dynamics, mitophagy and so on. Mitochondrial abnormalities have emerged as key determinants for cognitive function, the relationship between DACD and mitochondria is not well understood. Here, we explored the underlying mechanism of mitochondrial dysfunction of T2DM mice and HT22 cells treated with high glucose/palmitic acid (HG/Pal) focusing on the mitochondrial fission-mitophagy axis with drug injection, western blotting, Immunofluorescence, and electron microscopy. We further explored the potential role of caveolin-1 (cav-1) in T2DM induced mitochondrial dysfunction and synaptic alteration through viral transduction. As previously reported, T2DM condition significantly prompted hippocampal mitochondrial fission, whereas mitophagy was blocked rather than increasing, which was accompanied by dysfunctional mitochondria and impaired neuronal function. By contrast, Mdivi-1 (mitochondrial division inhibitor) and urolithin A (mitophagy activator) ameliorated mitochondrial and neuronal function and thereafter lead to cognitive improvement by inhibiting excessive mitochondrial fission and giving rise to mitophagy, respectively. We have previously shown that cav-1 can significantly improve DACD by inhibiting ferroptosis. Here, we further demonstrated that cav-1 could not only inhibit mitochondrial fission via the interaction with GSK3β to modulate Drp1 pathway, but also rescue mitophagy through interacting with AMPK to activate PINK1/Parkin and ULK1-dependent signlings. Overall, our data for the first time point to a mitochondrial fission-mitophagy axis as a driver of neuronal dysfunction in a phenotype that was exaggerated by T2DM, and the protective role of cav-1 in DACD. Graphic Summary Illustration. In T2DM, excessive mitochondrial fission and impaired mitophagy conspire to an altered mitochondrial morphology and mitochondrial dysfunction, with a consequent neuronal damage, overall suggesting an unbalanced mitochondrial fission-mitophagy axis. Upon cav-1 overexpression, GSK3β and AMPK are phosphorylated respectively to activate Drp1 and mitophagy-related pathways (PINK1 and ULKI), ultimately inhibits mitochondrial fission and enhances mitophagy. In the meantime, the mitochondrial morphology and neuronal function are rescued, indicating the protective role of cav-1 on mitochondrial fission-mitophagy axis.

Paired immunoglobulin-like receptor B (PirB) was identified as a myelin-associated inhibitory protein (MAIP) receptor that plays a critical role in axonal regeneration, synaptic plasticity and neuronal survival after stroke. In our previous study, a transactivator of transcription-PirB extracellular peptide (TAT-PEP) was generated that can block the interactions between MAIs and PirB. We found that TAT-PEP treatment improved axonal regeneration, CST projection and long-term neurobehavioural recovery after stroke through its effects on PirB-mediated downstream signalling. However, the effect of TAT-PEP on the recovery of cognitive function and the survival of neurons also needs to be investigated. In this study, we investigated whether pirb RNAi could alleviate neuronal injury by inhibiting the expression of PirB following exposure to oxygen-glucose deprivation (OGD) in vitro. In addition, TAT-PEP treatment attenuated the volume of the brain infarct and promoted the recovery of neurobehavioural function and cognitive function. This study also found that TAT-PEP exerts neuroprotection by reducing neuronal degeneration and apoptosis after ischemia-reperfusion injury. In addition, TAT-PEP improved neuron survival and reduced lactate dehydrogenase (LDH) release in vitro. Results also showed that TAT-PEP reduced malondialdehyde (MDA) levels, increased superoxide dismutase (SOD) activity and reduced reactive oxygen species (ROS) accumulation in OGD-injured neurons. The possible mechanism was that TAT-PEP could contribute to the damage of neuronal mitochondria and affect the expression of cleaved caspase 3, Bax and Bcl-2. Our results suggest that PirB overexpression in neurons after ischaemic-reperfusion injury induces neuronal mitochondrial damage, oxidative stress and apoptosis. This study also suggests that TAT-PEP may be a potent neuroprotectant with therapeutic potential for stroke by reducing neuronal oxidative stress, mitochondrial damage, degeneration and apoptosis in ischemic stroke.

(1) Background: Sleep deprivation (SD) triggers a range of neuroinflammatory responses. Dexmedetomidine can improve sleep deprivation-induced anxiety by reducing neuroinflammatory response but the mechanism is unclear; (2) Methods: The sleep deprivation model was established by using an interference rod device. An open field test and an elevated plus maze test were used to detect the emotional behavior of mice. Mouse cortical tissues were subjected to RNA sequence (RNA-seq) analysis. Western blotting and immunofluorescence were used to detect the expression of p38/p-p38, MSK1/p-MSK1, and NFκBp65/p- NFκBp65. Inflammatory cytokines were detected using enzyme-linked immunosorbent assay (ELISA); (3) Results: SD triggered anxiety-like behaviors in mice and was closely associated with inflammatory responses and the MAPK pathway (as demonstrated by transcriptome analysis). SD led to increased expression levels of p-p38, p-MSK1, and p-NFκB. P38 inhibitor SB203580 was used to confirm the important role of the p38/MSK1/NFκB pathway in SD-induced neuroinflammation. Dexmedetomidine (Dex) effectively improves emotional behavior in sleep-deprived mice by attenuating SD-induced inflammatory responses and oxidative stress in the cerebral cortex, mainly by inhibiting the activation of the p38/MSK1/NFκB pathway; (4) Conclusions: Dex inhibits the activation of the p38/MSK1/NFκB pathway, thus attenuating SD-induced inflammatory responses and oxidative stress in the cerebral cortex of mice.

Background:Quantitative assessment of the risk of local transmission from imported dengue cases makes a great challenge to the development of public health in China. The purpose of this study is to observe the risk of mosquito-borne transmission in Xiamen City through ecological and insecticide resistance monitoring. Quantitative evaluation of mosquito insecticide resistance, community population and the number of imported cases affecting the transmission of dengue fever (DF) in Xiamen was carried out based on transmission dynamics model, so as to reveal the correlation between key risk factors and DF transmission.Methods:Based on the dynamics model and combined with the epidemiological characteristics of DF in Xiamen City, a transmission dynamics model was built to simulate the secondary cases caused by imported cases to evaluate the transmission risk of DF, and to explore the influence of mosquito insecticide resistance, community population and imported cases on the epidemic situation of DF in Xiamen City.Results:For the transmission model of DF, when the community population is between 10,000 and 25,000, changing the number of imported DF cases and the mortality rate of mosquitoes will have an impact on the spread of indigenous DF cases, however, changing the birth rate of mosquitoes did not gain more effect on the spread of local DF transmission.Conclusions:Through the quantitative evaluation of the model, this study determined that the mosquito resistance index has an important influence on the local transmission of dengue fever caused by imported cases in Xiamen, and the Brayton index can also affect the local transmission of the disease.

Post-stroke anxiety (PSA) is a kind of affective disorder occurring after a stroke, with anxiety as the primary clinical manifestation. PSA's mechanism is unclear, and there are few prevention and treatment measures. Our previous study found that HDAC3 could activate NF-κB signaling through mediated p65 deacetylation, which further influenced microglia activation. That implies HDAC3 may be the key mediator in ischemic stroke mice and modulates anxiety susceptibility to stress. This study established a PSA model in male C57BL/6 mice through photothrombotic stroke combined with chronic restrain stress. We focused on exploring whether esketamine administration can alleviate anxiety-like behavior and neuroinflammation, which may be associated with inhibiting HDAC3 expression and NF-κB pathway activation. The results showed that esketamine administration alleviated anxiety-like behavior in PSA mice. And the results showed that esketamine alleviated cortical microglial activation, altered microglial number, and kept morphology features. Furthermore, the results showed that the expression of HDAC3, phosphor-p65/p65, and COX1 significantly decreased in esketamine-treated PSA mice. Besides, we also found that esketamine reduced PGE2 expression, one of the primary regulators of negative emotions. Interestingly, our results indicate that esketamine reduced the perineuronal net (PNN) number in the pathological process of PSA. In conclusion, this study suggests esketamine could alleviate microglial activation, reduces inflammatory cytokine, and inhibits the expression of HDAC3 and NF-κB in the cortex of PSA mice to attenuate anxiety-like behavior. Our results provided a new potential therapeutic target for applying esketamine to PSA.

Background In September 2021, there was an outbreak of coronavirus disease 2019 (COVID-19) in Xiamen, China. Various non-pharmacological interventions (NPIs) and pharmacological interventions (PIs) have been implemented to prevent and control the spread of the disease. This study aimed to evaluate the effectiveness of various interventions and to identify priorities for the implementation of prevention and control measures. Methods The data of patients with COVID-19 were collected from 8 to 30 September 2021. A Susceptible-Exposed-Infectious-Recovered (SEIR) dynamics model was developed to fit the data and simulate the effectiveness of interventions (medical treatment, isolation, social distancing, masking, and vaccination) under different scenarios. The effective reproductive number (Reff) was used to assess the transmissibility and transmission risk. Results A total of 236 cases of COVID-19 were reported in Xiamen. The epidemic curve was divided into three phases (Reff = 6.8, 1.5, and 0). Notably, the cumulative number of cases was reduced by 99.67% due to the preventive and control measures implemented by the local government. In the effective containment stage, the number of cases could be reduced to 115 by intensifying the implementation of interventions. The total number of cases (TN) could be reduced by 29.66–95.34% when patients voluntarily visit fever clinics. When only two or three of these measures are implemented, the simulated TN may be greater than the actual number. As four measures were taken simultaneously, the TN may be <100, which is 57.63% less than the actual number. The simultaneous implementation of five interventions could rapidly control the transmission and reduce the number of cases to fewer than 25. Conclusion With the joint efforts of the government and the public, the outbreak was controlled quickly and effectively. Authorities could promptly cut the transmission chain and control the spread of the disease when patients with fever voluntarily went to the hospital. The ultimate effect of controlling the outbreak through only one intervention was not obvious. The combined community control and mask wearing, along with other interventions, could lead to rapid control of the outbreak and ultimately lower the total number of cases. More importantly, this would mitigate the impact of the outbreak on society and socioeconomics.

Mathematical models have played an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic. The aim of this review is to describe the use of COVID-19 mathematical models, their classification, and the advantages and disadvantages of different types of models. We conducted subject heading searches of PubMed and China National Knowledge Infrastructure with the terms "COVID-19," "Mathematical Statistical Model," "Model," "Modeling," "Agent-based Model," and "Ordinary Differential Equation Model" and classified and analyzed the scientific literature retrieved in the search. We categorized the models as data-driven or mechanism-driven. Data-driven models are mainly used for predicting epidemics, and have the advantage of rapid assessment of disease instances. However, their ability to determine transmission mechanisms is limited. Mechanism-driven models include ordinary differential equation (ODE) and agent-based models. ODE models are used to estimate transmissibility and evaluate impact of interventions. Although ODE models are good at determining pathogen transmission characteristics, they are less suitable for simulation of early epidemic stages and rely heavily on availability of first-hand field data. Agent-based models consider influences of individual differences, but they require large amounts of data and can take a long time to develop fully. Many COVID-19 mathematical modeling studies have been conducted, and these have been used for predicting trends, evaluating interventions, and calculating pathogen transmissibility. Successful infectious disease modeling requires comprehensive considerations of data, applications, and purposes.

Abstract Objective: This study elaborated the natural history parameters of Delta variant, explored the differences in detection cycle thresholds (Ct) among cases.Method: Natural history parameters were calculated based on the different onset times and exposure times of the cases. Intergenerational relationships between generations of cases were calculated. Differences in Ct values of cases by gender, age, and mode of detection were analyzed statistically to assess the detoxification capacity of cases.Result: The median incubation period was 4 days; the detection time for cases decreased from 25 to 7 hours as the outbreak continued. The mean intergenerational, intergenerational infectiousness and intergenerational symptomatology were 3.6, 1.67 and 1.7 days. Among the Ct values, we found little differences in testing across companies, but there were some differences in the gender of detected genes. The Ct values continuous to decreased with age, but increased when the age was greater than 60.Conclusion: This epidemic was caused by the aggregation of factories. The effective reproduction number and real-time reproduction number were calculated using symptom intergenerational relationship (SI). And the analysis of Ct values can improve the positive detection rate and improve prevention and control measures.

Background There is still a relatively serious disease burden of infectious diseases and the warning time for different infectious diseases before implementation of interventions is important. The logistic differential equation models can be used for predicting early warning of infectious diseases. The aim of this study is to compare the disease fitting effects of the logistic differential equation (LDE) model and the generalized logistic differential equation (GLDE) model for the first time using data on multiple infectious diseases in Jilin Province and to calculate the early warning signals for different types of infectious diseases using these two models in Jilin Province to solve the disease early warning schedule for Jilin Province throughout the year. Methods Collecting the incidence of 22 infectious diseases in Jilin Province, China. The LDE and GLDE models were used to calculate the recommended warning week (RWW), the epidemic acceleration week (EAW) and warning removed week (WRW) for acute infectious diseases with seasonality, respectively. Results Five diseases were selected for analysis based on screening principles: hemorrhagic fever with renal syndrome (HFRS), shigellosis, mumps, Hand, foot and mouth disease (HFMD), and scarlet fever. The GLDE model fitted the above diseases better (0.80 ≤ R 2 ≤ 0.94, P < 0. 005) than the LDE model. The estimated warning durations (per year) of the LDE model for the above diseases were: weeks 12–23 and 40–50; weeks 20–36; weeks 15–24 and 43–52; weeks 26–34; and weeks 16–25 and 41–50. While the durations of early warning (per year) estimated by the GLDE model were: weeks 7–24 and 36–51; weeks 13–37; weeks 11–26 and 39–54; weeks 23–35; and weeks 12–26 and 40–50. Conclusions Compared to the LDE model, the GLDE model provides a better fit to the actual disease incidence data. The RWW appeared to be earlier when estimated with the GLDE model than the LDE model. In addition, the WRW estimated with the GLDE model were more lagged and had a longer warning time.

Sleep loss is often associated with cognitive dysfunction. Alterations in the structure and function of synapses in the hippocampus are thought to underlie memory storage. Paired immunoglobulin-like receptor B (PirB) plays a negative role in various neurological diseases by inhibiting axon regeneration and synaptic plasticity. However, the contributions of PirB to the mechanisms underlying the changes in synaptic plasticity after sleep loss that ultimately promote deficits in cognitive function have not been well elucidated. Here, we showed that chronic sleep restriction (CSR) mice displayed cognitive impairment and synaptic deficits accompanied by upregulation of PirB expression in the hippocampus. Mechanistically, PirB caused the dysregulation of actin through the RhoA/ROCK2/LIMK1/cofilin signalling pathway, leading to abnormal structural and functional plasticity, which in turn resulted in cognitive dysfunction. PirB knockdown alleviated synaptic deficits and cognitive impairment after CSR by inhibiting the RhoA/ROCK2/LIMK1/cofilin signalling pathway. Moreover, we found that fasudil, a widely used ROCK2 inhibitor, could mimic the beneficial effect of PirB knockdown and ameliorate synaptic deficits and cognitive impairment, further demonstrating that PirB induced cognitive dysfunction after CSR via the RhoA/ROCK2/LIMK1/cofilin signalling pathway. Our study sheds new light on the role of PirB as an important mediator in modulating the dysfunction of synaptic plasticity and cognitive function via the RhoA/ROCK2/LIMK1/cofilin signalling pathway, which indicated that hippocampal PirB is a promising therapeutic target for counteracting cognitive impairment after CSR. This illustration depicts the signalling pathway by PirB in mediating cognitive impairment and synaptic deficits in CSR mice. In the hippocampus of CSR mice, the expression level of PirB was significantly increased. In addition, CSR increases RhoA and ROCK2 levels and reduces levels of both LIMK1 and cofilin phosphorylation. PirB knockdown reverses cognitive impairment and synaptic plasticity disorders caused by CSR through the RhoA/ROCK2/LIMK1/cofilin signalling pathway.

Background Meteorological factors have been proven to affect pathogens; both the transmission routes and other intermediate. Many studies have worked on assessing how those meteorological factors would influence the transmissibility of COVID-19. In this study, we used generalized estimating equations to evaluate the impact of meteorological factors on Coronavirus disease 2019 (COVID-19) by using three outcome variables, which are transmissibility, incidence rate, and the number of reported cases. Methods In this study, the data on the daily number of new cases and deaths of COVID-19 in 30 provinces and cities nationwide were obtained from the provincial and municipal health committees, while the data from 682 conventional weather stations in the selected provinces and cities were obtained from the website of the China Meteorological Administration. We built a Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model to fit the data, then we calculated the transmissibility of COVID-19 using an indicator of the effective reproduction number (Reff). To quantify the different impacts of meteorological factors on several outcome variables including transmissibility, incidence rate, and the number of reported cases of COVID-19, we collected panel data and used generalized estimating equations. We also explored whether there is a lag effect and the different times of meteorological factors on the three outcome variables. Results Precipitation and wind speed had a negative effect on transmissibility, incidence rate, and the number of reported cases, while humidity had a positive effect on them. The higher the temperature, the lower the transmissibility. The temperature had a lag effect on the incidence rate, while the remaining five meteorological factors had immediate and lag effects on the incidence rate and the number of reported cases. Conclusion Meteorological factors had similar effects on incidence rate and number of reported cases, but different effects on transmissibility. Temperature, relative humidity, precipitation, sunshine hours, and wind speed had immediate and lag effects on transmissibility, but with different lag times. An increase in temperature may first cause a decrease in virus transmissibility and then lead to a decrease in incidence rate. Also, the mechanism of the role of meteorological factors in the process of transmissibility to incidence rate needs to be further explored.

BackgroundTo date, there is a lack of sufficient evidence on the type of clusters in which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is most likely to spread. Notably, the differences between cluster-level and population-level outbreaks in epidemiological characteristics and transmissibility remain unclear. Identifying the characteristics of these two levels, including epidemiology and transmission dynamics, allows us to develop better surveillance and control strategies following the current removal of suppression measures in China.MethodsWe described the epidemiological characteristics of SARS-CoV-2 and calculated its transmissibility by taking a Chinese city as an example. We used descriptive analysis to characterize epidemiological features for coronavirus disease 2019 (COVID-19) incidence database from 1 Jan 2020 to 2 March 2020 in Chaoyang District, Beijing City, China. The susceptible-exposed-infected-asymptomatic-recovered (SEIAR) model was fitted with the dataset, and the effective reproduction number (Reff) was calculated as the transmissibility of a single population. Also, the basic reproduction number (R0) was calculated by definition for three clusters, such as household, factory and community, as the transmissibility of subgroups.ResultsThe epidemic curve in Chaoyang District was divided into three stages. We included nine clusters (subgroups), which comprised of seven household-level and one factory-level and one community-level cluster, with sizes ranging from 2 to 17 cases. For the nine clusters, the median incubation period was 17.0 days [Interquartile range (IQR): 8.4–24.0 days (d)], and the average interval between date of onset (report date) and diagnosis date was 1.9 d (IQR: 1.7 to 6.4 d). At the population level, the transmissibility of the virus was high in the early stage of the epidemic (Reff = 4.81). The transmissibility was higher in factory-level clusters (R0 = 16) than in community-level clusters (R0 = 3), and household-level clusters (R0 = 1).ConclusionsIn Chaoyang District, the epidemiological features of SARS-CoV-2 showed multi-stage pattern. Many clusters were reported to occur indoors, mostly from households and factories, and few from the community. The risk of transmission varies by setting, with indoor settings being more severe than outdoor settings. Reported household clusters were the predominant type, but the population size of the different types of clusters limited transmission. The transmissibility of SARS-CoV-2 was different between a single population and its subgroups, with cluster-level transmissibility higher than population-level transmissibility.

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS), one kind of tick-borne acute infectious disease, is caused by a novel bunyavirus. The relationship between meteorological factors and infectious diseases is a hot topic of current research. Liaoning Province has reported a high incidence of SFTS in recent years. However, the epidemiological characteristics of SFTS and its relationship with meteorological factors in the province remain largely unexplored. Methods Data on reported SFTS cases were collected from 2011 to 2019. Epidemiological characteristics of SFTS were analyzed. Spearman’s correlation test and generalized linear models (GLM) were used to identify the relationship between meteorological factors and the number of SFTS cases. Results From 2011 to 2019, the incidence showed an overall upward trend in Liaoning Province, with the highest incidence in 2019 (0.35/100,000). The incidence was slightly higher in males (55.9%, 438/783), and there were more SFTS patients in the 60–69 age group (31.29%, 245/783). Dalian City and Dandong City had the largest number of cases of SFTS (87.99%, 689/783). The median duration from the date of illness onset to the date of diagnosis was 8 days [interquartile range (IQR): 4–13 days]. Spearman correlation analysis and GLM showed that the number of SFTS cases was positively correlated with monthly average rainfall (r s = 0.750, P < 0.001; β = 0.285, P < 0.001), monthly average relative humidity (r s = 0.683, P < 0.001; β = 0.096, P < 0.001), monthly average temperature (r s = 0.822, P < 0.001; β = 0.154, P < 0.001), and monthly average ground temperature (r s = 0.810, P < 0.001; β = 0.134, P < 0.001), while negatively correlated with monthly average air pressure (r s = −0.728, P < 0.001; β = −0.145, P < 0.001), and monthly average wind speed (r s = −0.272, P < 0.05; β = −1.048, P < 0.001). By comparing both correlation coefficients and regression coefficients between the number of SFTS cases (dependent variable) and meteorological factors (independent variables), no significant differences were observed when considering immediate cases and cases with lags of 1 to 5 weeks for dependent variables. Based on the forward and backward stepwise GLM regression, the monthly average air pressure, monthly average temperature, monthly average wind speed, and time sequence were selected as relevant influences on the number of SFTS cases. Conclusion The annual incidence of SFTS increased year on year in Liaoning Province. Incidence of SFTS was affected by several meteorological factors, including monthly average air pressure, monthly average temperature, and monthly average wind speed. Graphical Abstract

Systemic inflammatory response syndrome (SIRS) is a sepsis-associated inflammatory state and a self-defense mechanism against specific and nonspecific stimuli. Ketamine influences many key processes that are altered during sepsis. However, the underlying mechanisms remain incompletely understood. In this study, TNF-α-treated mice, as well as HT-29 and L929 cell models, were applied to characterize TNF-α-induced systemic and local cecal tissue inflammatory responses. Behavioral, biochemical, histological, and molecular biological approaches were applied to illustrate the related processes. Mice with TNF-α-induced SIRS showed systemic and local cecal tissue inflammatory responses, as indicated by increased levels of high mobility group box 1 protein (HMGB1), chemokines (C-X-C motif) ligand 10 (CXCL10), interleukin-6 (IL-6), and IL-10, as well as high mortality. Ketamine pretreatment alleviated death rates, symptoms, and the production of inflammatory cytokines induced by TNF-α in mice. Moreover, ketamine also protected the mice from TNF-α-induced cecal damage by suppressing the phosphorylation of receptor-interacting serine/threonine-protein kinase 3 (RIP3) and mixed lineage kinase domain-like protein (MLKL). In addition, our results showed that ketamine efficiently inhibited TNF-α-induced necroptosis in HT-29 and L929 cells. Furthermore, we explored the mechanism using different L929 cell lines. The results displayed that ketamine inhibited TNF-α-induced necroptosis by enhancing RIP1 ubiquitination and reducing the RIP1-RIP3 and RIP3-MLKL interactions, as well as the formation of necrosomes. Thus, our study may provide a new theoretical and experimental basis for treating diseases characterized by SIRS-associated inflammatory factor storms. Moreover, our exploration may provide potential molecular mechanisms and targets for therapeutic intervention and clinical application of ketamine.

Introduction: Modeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and prediction of optimal early warning timing: the logistic differential equation (LDE) model and the more complex generalized logistic differential equation (GLDE) model. This study aimed to compare and analyze these two models. Methods: We collected data on (coronavirus disease 2019) COVID-19 and four other infectious diseases and classified the data into four categories: different transmission routes, different epidemic intensities, different time scales, and different regions, using R-2 to compare and analyze the goodness-of-fit of LDE and GLDE models. Results: Both models fitted the epidemic curves well, and all results were statistically significant. The R-2 test value of COVID-19 was 0.924 (p < 0.001) fitted by the GLDE model and 0.916 (p < 0.001) fitted by the LDE model. The R-2 test value varied between 0.793 and 0.966 fitted by the GLDE model and varied between 0.594 and 0.922 fitted by the LDE model for diseases with different transmission routes. The R-2 test values varied between 0.853 and 0.939 fitted by the GLDE model and varied from 0.687 to 0.769 fitted by the LDE model for diseases with different prevalence intensities. The R-2 test value varied between 0.706 and 0.917 fitted by the GLDE model and varied between 0.410 and 0.898 fitted by the LDE model for diseases with different time scales. The GLDE model also performed better with nation-level data with the R-2 test values between 0.897 and 0.970 vs. 0.731 and 0.953 that fitted by the LDE model. Both models could characterize the patterns of the epidemics well and calculate the acceleration weeks. Conclusion: The GLDE model provides more accurate goodness-of-fit to the data than the LDE model. The GLDE model is able to handle asymmetric data by introducing shape parameters that allow it to fit data with various distributions. The LDE model provides an earlier epidemic acceleration week than the GLDE model. We conclude that the GLDE model is more advantageous in asymmetric infectious disease data simulation.

Depression is accompanied by excessive neuroinflammation. Liver X receptor beta (LXR beta) has been reported as a newly emerging target that exerts systemic and organic inflammation modulation. However, the modulatory mechanism in alleviating neuroinflammation are far from being revealed. In the current study, depression-related behaviors in mice were induced by chronic unpredictable mild stress (CUMS) and corticosterone (CORT) drinking. Mice received either TO901317, PLX-5622 and intra-bilateral basolateral amygdale (BLA) injection of rAAV9-hSyn-hM3D(Gq)-eGFP to activate LXR beta, eliminate microglia and pharmacogenetic activate neurons in BLA, respectively, followed by behavioral tests. Microglial pro-inflammatory and pro-phagocytic activation, as well as nuclear factor-kappa B (NF-kappa B) signaling pathway, NLRP3 inflammasome activation and inter-leukin-1 beta (IL-1 beta) release in BLA were investigated. Moreover, pro-inflammatory activation of BV2 cells-induced by CORT with or without TO901317 was detected. Neuroinflammation indicated by IL-1 beta release was measured in a co-culture system of HT22-primary microglia with or without TO901317. Our results indicated that chronic stress induced depression-related behaviors, which were accompanied with microglial pro-inflammatory and pro-phagocytic activation, as well as NF-kappa B signaling pathway and NLRP3 inflammasome activation in BLA. Accordingly, pharmacological activation of LXR beta inhibited microglial pro-inflammatory and pro-phagocytic activation, as well as NF-kappa B signaling pathway and NLRP3 inflammasome activation, and IL-1 beta release both in vivo and in vitro. Finally, both elimination of microglia and pharmacogenetic activation of neurons in BLA protected mice from chronic stress-induced depression-related behavior. Collectively, pharmacological activa-tion of neuronal-microglial LXR beta alleviates depression-related behavior by modulating excessive neuro -inflammation via inhibiting NF-kappa B signaling pathway and NLRP3 inflammasome activation.

Objective: Mumps is a seasonal infectious disease, always occurring in winter and spring. In this study, we aim to analyze its epidemiological characteristics, transmissibility, and its correlation with meteorological variables. Method: A seasonal Susceptible-Exposed-Infectious/Asymptomatic-Recovered model and a next-generation matrix method were applied to estimate the time-dependent reproduction number (R-t). Results: The seasonal double peak of annual incidence was mainly in May to July and November to December. There was high transmission at the median of R-t = 1.091 (ranged: 0 to 4.393). R-t was seasonally distributed mainly from February to April and from September to November. Correlations were found between temperature (Pearson correlation coefficient [r] ranged: from 0.101 to 0.115), average relative humidity (r = 0.070), average local pressure (r = -0.066), and the number of new cases. In addition, average local pressure (r = 0.188), average wind speed (r = 0.111), air temperature (r ranged: -0.128 to -0.150), average relative humidity (r = -0.203) and sunshine duration (r = -0.075) were all correlated with R-t. Conclusion: A relatively high level of transmissibility has been found in Xiamen City, leading to a continuous epidemic of mumps. Meteorological factors, especially air temperature and relative humidity, may be more closely associated with mumps than other factors. (C) 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.