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BACKGROUND: The inflammatory response in patients with traumatic brain injury (TBI) offers opportunities for stratification and intervention. Previous unselected approaches to immunomodulation in patients with TBI have not improved patient outcomes. METHODS: Serum and plasma samples from two prospective, multi-centre observational studies of patients with TBI were used to discover (Collaborative European NeuroTrauma Effectiveness Research [CENTER-TBI], Europe) and validate (Transforming Research and Clinical Knowledge in Traumatic Brain Injury [TRACK-TBI] Pilot, USA) individual variations in the immune response using a multiplex panel of 30 inflammatory mediators. Mediators that were associated with unfavourable outcomes (Glasgow outcome score-extended [GOS-E] ≤ 4) were used for hierarchical clustering to identify patients with similar signatures. FINDINGS: Two clusters were identified in both the discovery and validation cohorts, termed early-inflammatory and pauci-inflammatory. The early-inflammatory phenotype had higher concentrations of interleukin-6 (IL-6), IL-15, and monocyte chemoattractant protein 1 (MCP1). Patients with the early-inflammatory phenotype were older and more likely to have an unfavourable GOS-E at 6 months. There were no differences in the baseline injury severity scores between patients in each phenotype. A combined IL-15 and MCP1 signature identified patients with the early-inflammatory phenotype in both cohorts. Inflammatory processes mediated outcomes in older patients with moderate-severe TBI. INTERPRETATION: Our findings offer a precision medicine approach for future clinical trials of immunomodulation in patients with TBI, by using inflammatory signatures to stratify patients. FUNDING: CENTER-TBI study was supported by the European Union 7th Framework Programme. TRACK-TBI is supported by the National Institute of Neurological Disorders and Stroke.

The relationship between systemic inflammation and secondary injury in traumatic brain injury (TBI) is complex. We investigated associations between inflammatory markers and clinical confirmation of TBI diagnosis and prognosis. The prospective TRACK-TBI Pilot (Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot) study enrolled TBI patients triaged to head computed tomography (CT) and received blood draw within 24 h of injury. Healthy controls (HCs) and orthopedic controls (OCs) were included. Thirty-one inflammatory markers were analyzed from plasma. Area under the receiver operating characteristic curve (AUC) was used to evaluate discriminatory ability. AUC >0.7 was considered acceptable. Criteria included: TBI diagnosis (vs. OC/HC); moderate/severe vs. mild TBI (Glasgow Coma Scale; GCS); radiographic TBI (CT positive vs. CT negative); 3- and 6-month Glasgow Outcome Scale-Extended (GOSE) dichotomized to death/greater relative disability versus less relative disability (GOSE 1-4/5-8); and incomplete versus full recovery (GOSE

Following recent advances in post-thrombectomy stroke care, the role of neuroinflammation and neuroprotective strategies in mitigating secondary injury has gained prominence. Yet, while neuroprotection and anti-inflammatory agents have re-emerged in clinical trials, their success has been limited. The neuroinflammatory response in cerebral ischemia is robust and multifactorial, complicating therapeutic approaches targeting single pathways. In this study, we aimed to characterize early inflammatory gene dysregulation following ischemic stroke using translational in-silico and in-vivo approaches. Using an in vivo ischemic stroke model, transcriptomic analysis revealed significant dysregulation of inflammatory genes. Graph theory analysis then showed a rich-club organization among stroke-related genes, with highly connected core nodes. The expression levels of the core genes identified within this network significantly explained radiological outcomes, including T2-signal hyperintensity (R2 = 0.57, P < 0.001), mean diffusivity (R2 = 0.52, P < 0.001), and mean kurtosis (R2 = 0.65, P < 0.001), correlating more strongly than non-core genes. Similar findings were observed with functional and cognitive outcomes, showing R2 values of 0.58, 0.7, 0.54, and 0.7 for neurological severity scores, corner tasks, passive avoidance, and novel object recognition tasks, respectively (P < 0.001). Using in-silico analysis, we identified a set of upstream regulators directly interacting with core network nodes, leading to simulations that highlighted C3-targeted therapy as a potential treatment. This hypothesis was then confirmed in vivo using a targeted C3 inhibitor (CR2-fH), which reversed gene dysregulation in the neuroinflammatory network and improved radiological and functional outcomes. Our findings underscore the significance of neuroinflammation in stroke pathology, supporting network-based therapeutic targeting and demonstrating the benefits of targeted complement inhibition in enhancing outcomes through modulation of the neuroinflammatory network core. This study's approach, combining graph theory analysis along with in-silico modeling, offers a promising translational pipeline applicable to stroke and other complex diseases. [ABSTRACT FROM AUTHOR]

Summary: Childhood obesity represents a significant public health concern, imposing a substantial burden on the healthcare system. Furthermore, weight‐loss programs often exhibit reduced effectiveness in adults who have a history of childhood obesity. Therefore, early intervention against childhood obesity is imperative. Presently, the primary method for diagnosing childhood obesity relies on body mass index (BMI), yet this approach has inherent limitations. Leptin, a satiety hormone produced by adipocytes, holds promise as a superior tool for predicting both childhood and subsequent adulthood obesity. In this review, we elucidate the tools employed for assessing obesity in children, delve into the biological functions of leptin, and examine the factors governing its expression. Additionally, we discuss maternal and infantile leptin levels as predictors of childhood obesity. By exploring the relationship between leptin levels and weight loss, we present leptin as a potential indicator of the effectiveness of obesity interventions. [ABSTRACT FROM AUTHOR]

The editorial published in Frontiers in Cellular Neuroscience on October 17, 2024, focuses on revisiting mouse models of traumatic brain injuries, specifically looking at intracellular mechanisms. The article discusses the importance of mouse models in TBI research due to limitations in human clinical studies. It highlights the relevance and shortcomings of existing TBI mouse models and investigates dysregulated intracellular mechanisms in the injured brain. The research aims to improve understanding and potential treatments for TBI, emphasizing the need for further studies on translational outcomes. [Extracted from the article]

Simple Summary: Multi-omics has become a crucial tool in cancer biomarker discovery over the last decade, including for prostate cancer. This approach integrates data from various biological layers, enhancing our understanding of complex, heterogeneous cancers. Multi-omics accelerates precision medicine by identifying new biomarkers and therapeutic targets, potentially improving treatment options for advanced prostate cancer patients. This review discusses traditional prostate cancer biomarkers and highlights recent single-omics and multi-omics advances that have improved clinical diagnostic and prognostic capabilities. Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Delirium is a common and acute neuropsychiatric syndrome that requires timely intervention to prevent its associated morbidity and mortality. Yet, its diagnosis and symptoms are often overlooked due to its variable clinical presentation and fluctuating nature. Thus, in this study, we address the barriers to delirium diagnosis by utilizing a machine learning-based predictive algorithm for incident delirium that relies on archived electronic health records (EHRs) data. Methods: We used the Medical Information Mart for Intensive Care (MIMIC) database to create a detailed dataset for identifying delirium in intensive care unit (ICU) patients. Our approach involved training machine learning models on this dataset to pinpoint critical clinical features for delirium detection. These features were then refined and applied to non-ICU patients using EHRs from the American University of Beirut Medical Center (AUBMC). Results: Our study assessed machine learning models like Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Classification and Regression Trees (CART), Random Forest (RF), Neural Oblivious Decision Ensembles (NODE), and Logistic Regression (LR), highlighting superior delirium detection in diverse clinical settings. The CatBoost model excelled in ICU environments with an F1 Score of 89.2%, while XGBoost performed best in general hospital settings with a 75.4% F1 Score. Interpretations using Tabular Local Interpretable Model-agnostic Explanations (LIME) revealed critical indicators such as prothrombin time and hematocrit levels, enhancing model transparency and clinical applicability. These clinical insights help differentiate the delirium predictors between ICU patients, who are often sensitive to various factors. Conclusion: The proposed predictive algorithm improves delirium detection rates and streamlines efficiency in hospital electronic systems, thereby enabling prompt interventions to prevent delirium progression and associated complications. The clinical indicators for delirium that we identified in general hospital settings and ICU can greatly help healthcare professionals identify potential causes of delirium and reduce misdiagnosis. [ABSTRACT FROM AUTHOR]

Simple Summary: HER2 is a well-known driver of worse outcomes for many types of cancer, including prostate cancer. While HER2 has been previously evaluated in prostate cancer bench studies and clinical trials, there has been a lack of diversity in the experimental designs and protocols. For this reason, it has only recently been reported that Black men with prostate cancer may have a higher prevalence of HER2 overexpression. To thoroughly address health inequities that exist for Black men with prostate cancer, it is critical to utilize diverse biospecimens and enroll diverse study participants into studies that evaluate genetic and molecular contributors to worse prognosis for high-risk populations. In this review, we reconsider the role of HER2 in prostate cancer with an approach that incorporates the effects of race and genetic ancestry. Human epidermal growth factor receptor 2 (HER2) is a major driver of disease progression, treatment resistance, and worse survival for patients with various types of cancers, including prostate cancer. However, key bench studies and clinical trials have failed to evaluate the role of HER2 in prostate cancer using racially diverse experimental designs and protocols. This lack of diversity represents what has been the status quo of cancer research in the United States for decades. In the case of prostate cancer, homogenic study designs are problematic as Black men are much more likely to be diagnosed and die from aggressive and incurable forms of the disease. Therefore, the strategic inclusion of biospecimens collected from Black patients as well as the recruitment and enrollment of Black men into prostate cancer clinical trials is necessary to comprehensively evaluate genetic and molecular factors that contribute to variable outcomes in this high-risk population. Additionally, a higher prevalence of HER2 expression in Black men was recently reported in a small cohort of prostate cancer patients and may contribute to worsened prognosis. In this review, we carefully consider the role of HER2 in prostate cancer while, for the first time, taking into account the influences of race and genetic ancestry. [ABSTRACT FROM AUTHOR]

Vitamin D deficiency is a global problem. Vitamin D, the vitamin D receptor, and its enzymes are found throughout neuronal, ependymal, and glial cells in the brain and are implicated in certain processes and mechanisms in the brain. To investigate the processes affected by vitamin D deficiency in adults, we studied vitamin D deficient, control, and supplemented diets over 6 weeks in male and female C57Bl/6 mice. The effect of the vitamin D diets on proliferation in the neurogenic niches, changes in glial cells, as well as on memory, locomotion, and anxiety-like behavior, was investigated. Six weeks on a deficient diet was adequate time to reach deficiency. However, vitamin D deficiency and supplementation did not affect proliferation, neurogenesis, or astrocyte changes, and this was reflected on behavioral measures. Supplementation only affected microglia in the dentate gyrus of female mice. Indicating that vitamin D deficiency and supplementation do not affect these processes over a 6-week period. [ABSTRACT FROM AUTHOR]