Regulatory T cells, a subset of CD4+ T cells, play a critical role in maintaining immune tolerance and tissue homeostasis due to their potent immunosuppressive properties. Recent advances in research have highlighted the important therapeutic potential of Tregs in neurological diseases and tissue repair, emphasizing their multifaceted roles in immune regulation. This review aims to summarize and analyze the mechanisms of action and therapeutic potential of Tregs in relation to neurological diseases and neural regeneration. Beyond their classical immune-regulatory functions, emerging evidence points to non-immune mechanisms of regulatory T cells, particularly their interactions with stem cells and other non-immune cells. These interactions contribute to optimizing the repair microenvironment and promoting tissue repair and nerve regeneration, positioning non-immune pathways as a promising direction for future research. By modulating immune and non-immune cells, including neurons and glia within neural tissues, Tregs have demonstrated remarkable efficacy in enhancing regeneration in the central and peripheral nervous systems. Preclinical studies have revealed that Treg cells interact with neurons, glial cells, and other neural components to mitigate inflammatory damage and support functional recovery. Current mechanistic studies show that Tregs can significantly promote neural repair and functional recovery by regulating inflammatory responses and the local immune microenvironment. However, research on the mechanistic roles of regulatory T cells in other diseases remains limited, highlighting substantial gaps and opportunities for exploration in this field. Laboratory and clinical studies have further advanced the application of regulatory T cells. Technical advances have enabled efficient isolation, ex vivo expansion and functionalization, and adoptive transfer of regulatory T cells, with efficacy validated in animal models. Innovative strategies, including gene editing, cell-free technologies, biomaterial-based recruitment, and in situ delivery have expanded the therapeutic potential of regulatory T cells. Gene editing enables precise functional optimization, while biomaterial and in situ delivery technologies enhance their accumulation and efficacy at target sites. These advancements not only improve the immune-regulatory capacity of regulatory T cells but also significantly enhance their role in tissue repair. By leveraging the pivotal and diverse functions of Tregs in immune modulation and tissue repair, regulatory T cells–based therapies may lead to transformative breakthroughs in the treatment of neurological diseases.
Garazi Retegui, María Dolores Ugarte, Jaione Etxeberria
et al.
To date, we have seen the emergence of a large literature on multivariate disease mapping. That is, incidence of (or mortality from) multiple diseases is recorded at the scale of areal units where incidence (mortality) across the diseases is expected to manifest dependence. The modeling involves a hierarchical structure: a Poisson model for disease counts (conditioning on the rates) at the first stage, and a specification of a function of the rates using spatial random effects at the second stage. These random effects are specified as a prior and introduce spatial smoothing to the rate (or risk) estimates. What we see in the literature is the amount of smoothing induced under a given prior across areal units compared with the observed/empirical risks. Our contribution here extends previous research on smoothing in univariate areal data models. Specifically, for three different choices of multivariate prior, we investigate both within prior smoothing according to hyperparameters and across prior smoothing. Its benefit to the user is to illuminate the expected nature of departure from perfect fit associated with these priors since model performance is not a question of goodness of fit. We propose both theoretical and empirical metrics for our investigation and illustrate with both simulated and real data.
Joemer C. Maravilla, Shoshanna L. Fine, Astha Ramaiya
et al.
Abstract Background There is a lack of country-level evidence for the association between social support and adolescent mental health while existing studies vary greatly in how they account for the interplay of multiple sources of social support. Methods This study utilised data from the National Adolescent Mental Health Surveys, nationally representative surveys of adolescents aged 10–17 years and their primary caregiver in Kenya, Indonesia, and Vietnam. Patterns of social support among adolescents in each country were assessed using a latent class analysis. The association between the identified social support classes and any mental disorder, suicidal ideation, and self-harm in the past 12 months was assessed using the Bolck–Croon–Hagenaars method, adjusted for demographic characteristics and caregiver mental health. All estimates were weighted to the respective country’s population and presented with 95% confidence intervals (CIs). Results Three latent social support classes were consistently identified in Kenya, Indonesia, and Vietnam: Caregiver-focussed support, Other support, and Limited support. The Caregiver-focussed support class had the highest proportion of adolescents in all three countries (Kenya: 65.3%, 95% CI: 63.0–67.5; Indonesia: 54.0%, 95% CI: 50.4–57.6; Vietnam: 81.6%, 95% CI: 79.0–84.1), although the proportions varied significantly by country. Adolescents in the Caregiver-focussed support class had significantly lower odds of any mental disorder (Kenya: adjusted odds ratio [aOR]: 0.31, 95% CI: 0.25–0.38; Indonesia: aOR: 0.23, 95% CI: 0.17–0.31; Vietnam: aOR: 0.39, 95 CI%: 0.26–0.57), suicidal ideation (Kenya: aOR: 0.14, 95% CI: 0.10–0.19; Indonesia: aOR: 0.17, 95% CI: 0.10–0.29; Vietnam: aOR: 0.42, 95% CI: 0.24–0.76) and self-harm (Kenya aOR: 0.07, 95% CI: 0.04–0.13; Indonesia aOR: 0.23, 95% CI: 0.11–0.47 and Vietnam aOR: 0.16, 95% CI: 0.09–0.27) compared to the Limited support class. Adolescents belonging to the Other support class also demonstrated lower odds of these outcomes than those in the Limited support class. Conclusions The association between social support and poor mental health indicates the critical role of primary caregivers, other family members, and peers in adolescent mental health. These findings highlight the need to develop interventions that leverage an adolescent’s existing support networks.
Objectives: To investigate the effect of IRE1α/TRAF2/NF-κB pathway on early brain injury. Methods: An endovascular puncture model of subarachnoid hemorrhage (SAH) was developed and SAH grading was performed. The following groups of experimental animals were randomly assigned: Blank group, Sham group, SAH+ DMSO group, SAH+STF-083010(IRE1α inhibitor) group, and SAH+BAY11‐7082(NF-κB inhibitor) group. Neurological deficits were assessed in the animal models using a modified Garcia score. The expression of IRE1α, GRP78, TRAF2, NF-κB, and caspase3 was measured using western blot analysis. The concentrations of TNF-α, IL-1β and IL-6 were evaluated with ELISA kits. An analysis of neuronal apoptosis was performed using TUNEL staining. Results: The neurological deficits, expression of IRE1α/TRAF2/NF-κB axis and its related proteins, inflammatory cytokines and apoptosis were increased after SAH, whereas their expressions were suppressed since the inhibition of the IRE1α/TRAF2/NF-κB signal pathway. Moreover, correlation analysis showed that TNF-α, IL-1β and IL-6 were positively correlated with apoptosis. Conclusions: The IRE1α/TRAF2/NF-κB signal pathway was activated and promoted apoptosis by promoting the expression of inflammatory cytokines after SAH.
Coraima Beatriz Anaya Linan, Antônio Furlanetto Corte, João Renato Garcia e Silva
et al.
RESUMO Introdução: Depressão Resistente ao Tratamento (DTR) é a falta de resposta a ≥2 tratamentos consecutivos com medicação antidepressiva em dosagem e duração adequada. Neste contexto, a Escetamina Intranasal surgiu como uma nova alternativa de tratamento. Relato de caso: Paciente masculino de 28 anos, com risco agudo de suicídio em uso de diferentes medicações, sem alívio dos sintomas. Diagnosticado com Depressão Resistente ao Tratamento e tratado com Escetamina Intranasal em associação aos fármacos que o paciente já utilizava. Após 4 semanas de utilização da Escetamina, apresentou remissão dos sintomas clínicos e teve alta hospitalar, permanecendo sem novas internações. Discussão: o paciente do relato apresentava diversos transtornos comórbidos, bem como uma história de vida traumática, fatores que atuam como preditores de má resposta ao tratamento com antidepressivos convencionais. Além disso, as terapias convencionais apresentam um tempo prolongado de resposta ao tratamento, o que gera dificuldade de manejo de pacientes com risco agudo de suicídio. A escetamina intranasal atua com uma maior rapidez no sistema nervoso central, diminuindo o risco de suicídio em algumas horas após a primeira aplicação. Conclusão: a aplicação precoce do Cloridrato de Escetamina Intranasal muda a trajetória de vida dos pacientes refratários ao tratamento convencional, reduzindo a recorrência de novas tentativas de suicídio.
Chronic Wasting Disease (CWD) is a neurological disease impacting deer, elk, moose, and other cervid populations and is caused by a misfolded protein known as a prion. CWD is difficult to control due to the persistence of prions in the environment. Prions can remain infectious for more than a decade and have been found in soil as well as other environmental vectors, such as ticks and plants. Here, we provide a bifurcation analysis of a mathematical model of CWD spread in a cervid population, and use a modification of the Gillespie algorithm to explore if wolves can be used as an ecological control strategy to limit the spread of the disease in several relevant scenarios. We then analytically compute the probability that the disease spreads given one infected member enters a fully healthy population and the probability of elimination, given a fully susceptible population and remaining prions in the environment. From our analysis, we conclude that wolves can be used as an effective control strategy to limit the spread of CWD in cervid populations, and hunting or other means of lowering the susceptible population are beneficial to controlling the spread of CWD, although it is important to note that inferring biologically relevant parameters from the existing data is an ongoing challenge for this system.
Jueqi Wang, Zachary Jacokes, John Darrell Van Horn
et al.
While imaging-genetics holds great promise for unraveling the complex interplay between brain structure and genetic variation in neurological disorders, traditional methods are limited to simplistic linear models or to black-box techniques that lack interpretability. In this paper, we present NeuroPathX, an explainable deep learning framework that uses an early fusion strategy powered by cross-attention mechanisms to capture meaningful interactions between structural variations in the brain derived from MRI and established biological pathways derived from genetics data. To enhance interpretability and robustness, we introduce two loss functions over the attention matrix - a sparsity loss that focuses on the most salient interactions and a pathway similarity loss that enforces consistent representations across the cohort. We validate NeuroPathX on both autism spectrum disorder and Alzheimer's disease. Our results demonstrate that NeuroPathX outperforms competing baseline approaches and reveals biologically plausible associations linked to the disorder. These findings underscore the potential of NeuroPathX to advance our understanding of complex brain disorders. Code is available at https://github.com/jueqiw/NeuroPathX .
ObjectiveTo determine the efficacy of mechanical thrombectomy combined with prolonged mild hypothermia compared with conventional treatment in managing acute middle cerebral artery occlusion, and to explore whether extending the duration of hypothermia can improve neurological function.MethodFrom 2018 to June 2023, a retrospective analysis was conducted on 45 patients with acute middle cerebral artery occlusion treated at the NICU of Suzhou Kowloon Hospital, affiliated with Shanghai Jiao Tong University School of Medicine. After thrombectomy, patients were admitted to the neurological intensive care unit (NICU) for targeted temperature management. Patients were divided into two groups: the mild hypothermia group (34.5–35.9°C) receiving 5–7 days of treatment, and the normothermia group (control group) whose body temperature was kept between 36 and 37.5°C using pharmacological and physical cooling methods. Baseline characteristics and temperature changes were compared between the two groups of patients. The primary outcome was the modified Rankin Scale (mRS) score at 3 month after surgery, and the secondary outcomes were related complications and mortality rate. Prognostic risk factors were investigated using both univariate and multivariate logistic regression analyses.ResultsAmong 45 patients, 21 underwent prolonged mild hypothermia, and 24 received normothermia, with no significant differences in baseline characteristics between the two groups. The duration of mild hypothermia ranged from 5 to 7 days. The incidence of chills (33.3% vs. 8.3%, p = 0.031) and constipation (57.1% vs. 20.8%, p = 0.028) was significantly higher in the mild hypothermia group compared with the control group. There was no significant difference in mortality rates between the mild hypothermia and the control group (4.76% vs. 8.33%, p = 1.000, OR = 1.75, 95% CI, 0.171–17.949). At 3 month, there was no significant difference in the modified mRS (0–3) score between the mild hypothermia and control groups (52.4% vs. 25%, p = 0.114, OR = 0.477, 95% CI, 0.214–1.066). Infarct core volume was an independent risk factor for adverse neurological outcomes.ConclusionProlonged mild hypothermia following mechanical thrombectomy had no severe complications and shows a trend to improve the prognosis of neurological function. The Infarct core volume on CTP was an independent risk factor for predicting neurological function.
Chandni Gajperia, Jennifer McBride, Janet Treasure
et al.
Abstract Background The ability to recognize one’s own emotions is associated with one’s ability to recognize others’ emotions. Beyond the domain of emotion, however, the relationship between recognition of one’s own internal states (interoception) and others’ interoceptive states has not been investigated, either in the typical population or clinical groups with interoceptive difficulties (e.g. eating disorders; EDs). Method This study investigated recognition of one’s own and others’ internal states in adults with and without eating disorders, using a high frequency visual noise paradigm. Participants completed self-report measures of interoception, alexithymia (difficulties recognising one’s own emotional internal states) and ED symptomatology, and the Heartbeat Counting Task measure of cardiac interoceptive accuracy. Results Alexithymia was significantly negatively correlated with recognition of others’ interoceptive states. EDs were not associated with difficulties recognising others’ interoceptive states. Conclusions The ability to recognise one’s own emotional internal states is associated with the recognition of others’ interoceptive states, which may contribute to social skills and the ability to care for others.
Saeid Safiri, Saeid Safiri, Amir Ghaffari Jolfayi
et al.
BackgroundMultiple sclerosis (MS) is a progressively debilitating disorder that has seen a notable rise in prevalence in recent years. This study examines the burden of MS from 1990 to 2019, providing a detailed analysis by age, sex, and sociodemographic index (SDI) across 204 countries and territories.MethodsData on the prevalence, death and disability-adjusted life years (DALYs) attributable to MS were obtained from the publically available Global Burden of Disease 2019 project. The estimates are reported as numbers, percentages, and age-standardized rates per 100,000, accompanied by 95% uncertainty intervals.ResultsIn 2019, MS accounted for 1.8 million prevalent cases, 22.4 thousand deaths and 1.2 million DALYs worldwide. There were significant declines in the global age-standardized prevalence, mortality and DALY rates of MS over the period 1990–2019. In 2019, females exhibited a higher global point prevalence and a greater total number of prevalent MS cases than males across all age groups. At the regional level, a non-linear relationship was observed between the age-standardized DALY rate of MS and SDI.ConclusionAlthough the global age-standardized DALY rate of MS decreased between 1990 and 2019, MS continues to account for a considerable number of DALYs and prevalent cases. Integrating MS and its associated risk factors into healthcare planning is vital, especially in areas with high levels of socioeconomic development.
Early detection of chronic diseases is beneficial to healthcare by providing a golden opportunity for timely interventions. Although numerous prior studies have successfully used machine learning (ML) models for disease diagnoses, they highly rely on medical data, which are scarce for most patients in the early stage of the chronic diseases. In this paper, we aim to diagnose hyperglycemia (diabetes), hyperlipidemia, and hypertension (collectively known as 3H) using own collected behavioral data, thus, enable the early detection of 3H without using medical data collected in clinical settings. Specifically, we collected daily behavioral data from 629 participants over a 3-month study period, and trained various ML models after data preprocessing. Experimental results show that only using the participants' uploaded behavioral data, we can achieve accurate 3H diagnoses: 80.2\%, 71.3\%, and 81.2\% for diabetes, hyperlipidemia, and hypertension, respectively. Furthermore, we conduct Shapley analysis on the trained models to identify the most influential features for each type of diseases. The identified influential features are consistent with those reported in the literature.
Lemons and oranges, both are the most economically significant citrus fruits globally. The production of lemons and oranges is severely affected due to diseases in its growth stages. Fruit quality has degraded due to the presence of flaws. Thus, it is necessary to diagnose the disease accurately so that we can avoid major loss of lemons and oranges. To improve citrus farming, we proposed a disease classification approach for lemons and oranges. This approach would enable early disease detection and intervention, reduce yield losses, and optimize resource allocation. For the initial modeling of disease classification, the research uses innovative deep learning architectures such as VGG16, VGG19 and ResNet50. In addition, for achieving better accuracy, the basic machine learning algorithms used for classification problems include Random Forest, Naive Bayes, K-Nearest Neighbors (KNN) and Logistic Regression. The lemon and orange fruits diseases are classified more accurately (95.0% for lemon and 99.69% for orange) by the model. The model's base features were extracted from the ResNet50 pre-trained model and the diseases are classified by the Logistic Regression which beats the performance given by VGG16 and VGG19 for other classifiers. Experimental outcomes show that the proposed model also outperforms existing models in which most of them classified the diseases using the Softmax classifier without using any individual classifiers.
We analyze a disease transmission model that allows individuals to acquire fear and change their behaviour to reduce transmission. Fear is acquired through contact with infected individuals and through the influence of fearful individuals. We analyze the model in two limits: First, an Established Disease Limit (EDL), where the spread of the disease is much faster than the spread of fear, and second, a Novel Disease Limit (NDL), where the spread of the disease is comparable to that of fear. For the EDL, we show that the relative rate of fear acquisition to disease transmission controls the size of the fearful population at the end of a disease outbreak, and that the fear-induced contact reduction behaviour has very little impact on disease burden. Conversely, we show that in the NDL, disease burden can be controlled by fear-induced behaviour depending on the rate of fear loss. Specifically, fear-induced behaviour introduces a contact parameter $p$, which if too large prevents the contact reduction from effectively managing the epidemic. We analytically identify a critical prophylactic behaviour parameter $p=p_c$ where this happens leading to a discontinuity in epidemic prevalence. We show that this change in disease burden introduces delayed epidemic waves.
It was observed that the number of cases and deaths for infectious diseases were associated with heavy-tailed power law distributions such as the Pareto distribution. While Pareto distribution was widely used to model the cases and deaths of infectious diseases, a major limitation of Pareto distribution is that it can only fit a given data set beyond a certain threshold. Thus, it can only model part of the data set. Thus, we proposed some novel discrete composite distributions with Pareto tails to fit the real infectious disease data. To provide necessary statistical inference for the tail behavior of the data, we developed a hypothesis testing procedure to test the tail index parameter. COVID-19 reported cases in Singapore and monkeypox reported cases in France were analyzed to evaluate the performance of the newly created distributions. The results from the analysis suggested that the discrete composite distributions could demonstrate competitive performance compared to the commonly used discrete distributions. Furthermore, the analysis of the tail index parameter can provide great insights into preventing and controlling infectious diseases.
Austin M. Jeffries, Alexander J. Suptela, Ian Marriott
Abstract Background The mechanisms by which glia respond to viral central nervous system (CNS) pathogens are now becoming apparent with the demonstration that microglia and astrocytes express an array of pattern recognition receptors that include intracellular RNA and DNA sensors. We have previously demonstrated that glia express Z-DNA binding protein 1 (ZBP1) and showed that this cytosolic nucleic acid sensor contributes to the inflammatory/neurotoxic responses of these cells to herpes simplex virus-1 (HSV-1). However, the relative contribution made by ZBP1- to HSV-1-mediated cell death in glia has not been determined. Methods We have investigated the relative contribution made by ZBP1- to HSV-1-mediated cell death in primary astrocytes derived from mice genetically deficient in this sensor. We have used capture ELISAs and immunoblot analysis to assess inflammatory cytokine production and ZBP1 and phosphorylated mixed lineage kinase domain-like protein (MLKL) expression levels, respectively, following HSV-1 challenge. Furthermore, we have used a commercially available cell viability assay to determine the proportion and rate of cell death in cells following infection with laboratory and neuroinvasive clinical strains of HSV-1, and pharmacological inhibitors of necroptotic and apoptotic pathway components to assess the relative role of each. Results We show that the loss of ZBP1 in astrocytes results in an increase in the number of viral particles released following HSV-1 infection. Importantly, we have confirmed that HSV-1 induces necroptosis in astrocytes and have established the ability of ZBP1 to mediate this cell death pathway. Interestingly, while ZBP1 is best known for its role in necroptotic signaling, our findings indicate that this sensor can also contribute to virally induced apoptosis in these glia. Conclusions Our findings indicate that ZBP1 serves as a restriction factor for HSV-1 infection and is associated with the induction of both necroptotic and apoptotic cell death pathways in primary murine astrocytes. While it remains to be seen whether ZBP1-mediated activation of cell death in astrocytes contributes significantly to host protection or, rather, exacerbates HSV-1 encephalitis pathology, the identification of such a role in resident CNS cells may represent a novel target for therapeutic intervention to reduce HSV encephalitis-associated morbidity and mortality.
Christine Sundgot-Borgen, Lise Katrine Jepsen Trangsrud, Tobias Otterbring
et al.
Plain English summary Physical activity helps us feel good about ourselves and appreciate our bodies. However, less is known about the extent to which different arenas for physical activity are related to body appreciation. Therefore, 360 adults from Norway completed a survey with questions about their physical activity level, use of nature, fitness centers, and organized sports as arenas for physical activity, and measures linked to connectedness with nature, self-compassion, and body appreciation. We found an association between body appreciation and performing physical activity at fitness centers and in nature. Physical activity at these two arenas together with self-compassion and connectedness with nature explained body appreciation in these adults. Future studies should focus on the adolescent population, where the level of body appreciation tend to be lower and where organized sports, in addition to fitness centers, constitute an even more commonly used physical activity arena.
Varghese Kurian, Navid Ghadipasha, Michelle Gee
et al.
Chronic Obstructive Pulmonary Disease (COPD) is a progressive lung disease characterized by airflow limitation. This study develops a systems engineering framework for representing important mechanistic details of COPD in a model of the cardio-respiratory system. In this model, we present the cardio-respiratory system as an integrated biological control system responsible for regulating breathing. Four engineering control system components are considered: sensor, controller, actuator, and the process itself. Knowledge of human anatomy and physiology is used to develop appropriate mechanistic mathematical models for each component. Following a systematic analysis of the computational model, we identify three physiological parameters associated with reproducing clinical manifestations of COPD - changes in the forced expiratory volume (FEV), lung volumes, and pulmonary hypertension. We quantify the changes in these parameters (airway resistance, lung elastance, and pulmonary resistance) as the ones that result in a systemic response that is diagnostic of COPD. A multivariate analysis reveals that the changes in airway resistance have a broad impact on the human cardio-respiratory system, and that the pulmonary circuit is stressed beyond normal under hypoxic environments in most COPD patients.