Advances in AI for Protein Structure Prediction: Implications for Cancer Drug Discovery and Development.

Recent advancements in AI-driven technologies, particularly in protein structure prediction, are significantly reshaping the landscape of drug discovery and development. This review focuses on the question of how these technological breakthroughs, exemplified by AlphaFold2, are revolutionizing our understanding of protein structure and function changes underlying cancer and improve our approaches to counter them. By enhancing the precision and speed at which drug targets are identified and drug candidates can be designed and optimized, these technologies are streamlining the entire drug development process. We explore the use of AlphaFold2 in cancer drug development, scrutinizing its efficacy, limitations, and potential challenges. We also compare AlphaFold2 with other algorithms like ESMFold, explaining the diverse methodologies employed in this field and the practical effects of these differences for the application of specific algorithms. Additionally, we discuss the broader applications of these technologies, including the prediction of protein complex structures and the generative AI-driven design of novel proteins.

Group 1 metabotropic glutamate receptor expression defines a T cell memory population during chronic Toxoplasma infection that enhances IFN-gamma and perforin production in the CNS.

Within the brain, a pro-inflammatory response is essential to prevent clinical disease due to Toxoplasma gondii reactivation. Infection in the immunocompromised leads to lethal Toxoplasmic encephalitis while in the immunocompetent, there is persistent low-grade inflammation which is devoid of clinical symptoms. This signifies that there is a well-balanced and regulated inflammatory response to T. gondii in the brain. T cells are the dominant immune cells that prevent clinical disease, and this is mediated through the secretion of effector molecules such as perforins and IFN-γ. The presence of cognate antigen, the expression of survival cytokines, and the alteration of the epigenetic landscape drive the development of memory T cells. However, specific extrinsic signals that promote the formation and maintenance of memory T cells within tissue are poorly understood. During chronic infection, there is an increase in extracellular glutamate that, due to its function as an excitatory neurotransmitter, is normally tightly controlled in the CNS. Here we demonstrate that CD8+ T cells from the T. gondii-infected brain parenchyma are enriched for metabotropic glutamate receptors (mGluR's). Characterization studies determined that mGluR+ expression by CD8+ T cells defines a distinct memory population at the transcriptional and protein level. Finally, using receptor antagonists and agonists we demonstrate mGluR signaling is required for optimal CD8+ T cell production of the effector cytokine IFNγ. This work suggests that glutamate is an important environmental signal of inflammation that promotes T cell function. Understanding glutamate's influence on T cells in the brain can provide insights into the mechanisms that govern protective immunity against CNS-infiltrating pathogens and neuroinflammation.

Unusual structural and functional features of TpLRR/BspA-like LRR proteins.

Leucine Rich Repeat (LRR) domains, are present in hundreds of thousands of proteins across all kingdoms of life and are typically involved in protein-protein interactions and ligand recognition. LRR domains are classified into eight classes and when examined in three dimensions seven, of them form curved solenoid-like super-helices, also described as toruses, with a beta sheet on the concave (inside) and stacked alpha-helices on the convex (outside) of the torus. Here we present an overview of the least characterized 8th class of LRR proteins, the TpLRR-like LRRs, named after the Treponema pallidum protein Tp0225. Proteins from the TpLRR class differ from the proteins in all other known LRR classes by having a flipped curvature, with the beta sheet on the convex side of the torus and irregular secondary structure instead of helices on the opposite, now concave site. TpLRR proteins also present highly divergent sequence pattern of individual repeats and can associate with specific types of additional domains. Several of the characterized proteins from this class, specifically the BspA-like proteins, were found in human bacterial and protozoan pathogens, playing an important role in the interactions between the pathogens and the host immune system. In this paper we surveyed all existing experimental structures and selected AlphaFold models of the best-known proteins containing this class of LRR repeats, analyzing the relation between the pattern of conserved residues, specific structural features and functions of these proteins.

Health disparities in COVID-19: immune and vascular changes are linked to disease severity and persist in a high-risk population in Riverside County, California.

BACKGROUND: Health disparities in underserved communities, such as inadequate healthcare access, impact COVID-19 disease outcomes. These disparities are evident in Hispanic populations nationwide, with disproportionately high infection and mortality rates. Furthermore, infected individuals can develop long COVID with sustained impacts on quality of life. The goal of this study was to identify immune and endothelial factors that are associated with COVID-19 outcomes in Riverside County, a high-risk and predominantly Hispanic community, and investigate the long-term impacts of COVID-19 infection. METHODS: 112 participants in Riverside County, California, were recruited according to the following criteria: healthy control (n = 23), outpatients with moderate infection (outpatient, n = 33), ICU patients with severe infection (hospitalized, n = 33), and individuals recovered from moderate infection (n = 23). Differences in outcomes between Hispanic and non-Hispanic individuals and presence/absence of co-morbidities were evaluated. Circulating immune and vascular biomarkers were measured by ELISA, multiplex analyte assays, and flow cytometry. Follow-up assessments for long COVID, lung health, and immune and vascular changes were conducted after recovery (n = 23) including paired analyses of the same participants. RESULTS: Compared to uninfected controls, the severe infection group had a higher proportion of Hispanic individuals (n = 23, p = 0.012) than moderate infection (n = 8, p = 0.550). Disease severity was associated with changes in innate monocytes and neutrophils, lymphopenia, disrupted cytokine production (increased IL-8 and IP-10/CXCL10 but reduced IFNλ2/3 and IFNγ), and increased endothelial injury (myoglobin, VCAM-1). In the severe infection group, a machine learning model identified LCN2/NGAL, IL-6, and monocyte activation as parameters associated with fatality while anti-coagulant therapy was associated with survival. Recovery from moderate COVID infection resulted in long-term immune changes including increased monocytes/lymphocytes and decreased neutrophils and endothelial markers. This group had a lower proportion of co-morbidities (n = 8, p = 1.0) but still reported symptoms associated with long COVID despite recovered pulmonary function. CONCLUSION: This study indicates increased severity of COVID-19 infection in Hispanic individuals of Riverside County, California. Infection resulted in immunological and vascular changes and long COVID symptoms that were sustained for up to 11 months, however, lung volume and airflow resistance was recovered. Given the immune and behavioral impacts of long COVID, the potential for increased susceptibility to infections and decreased quality of life in high-risk populations warrants further investigation.

Sexual dimorphism in obesity is governed by RELMα regulation of adipose macrophages and eosinophils.

Obesity incidence is increasing worldwide with the urgent need to identify new therapeutics. Sex differences in immune cell activation drive obesity-mediated pathologies where males are more susceptible to obesity comorbidities and exacerbated inflammation. Here, we demonstrate that the macrophage-secreted protein RELMα critically protects females against high-fat diet (HFD)-induced obesity. Compared to male mice, serum RELMα levels were higher in both control and HFD-fed females and correlated with frequency of adipose macrophages and eosinophils. RELMα-deficient females gained more weight and had proinflammatory macrophage accumulation and eosinophil loss in the adipose stromal vascular fraction (SVF), while RELMα treatment or eosinophil transfer rescued this phenotype. Single-cell RNA-sequencing of the adipose SVF was performed and identified sex and RELMα-dependent changes. Genes involved in oxygen sensing and iron homeostasis, including hemoglobin and lncRNA Gm47283/Gm21887, correlated with increased obesity, while eosinophil chemotaxis and response to amyloid-beta were protective. Monocyte-to-macrophage transition was also dysregulated in RELMα-deficient animals. Collectively, these studies implicate a RELMα-macrophage-eosinophil axis in sex-specific protection against obesity and uncover new therapeutic targets for obesity.

Gender differences in smoking-induced changes in the tumor immune microenvironment.

Both gender and smoking are correlated with prevalence and outcomes in many types of cancers. Tobacco smoke is a known carcinogen through its genotoxicity but can also affect cancer progression through its effect on the immune system. In this study, we aim to evaluate the hypothesis that the effects of smoking on the tumor immune microenvironment will be influenced differently by gender using large-scale analysis of publicly available cancer datasets. We used The Cancer Genomic Atlas (TCGA) datasets (n = 2724) to analyze effects of smoking on different cancer immune subtypes and the relative abundance of immune cell types between male and female cancer patients. We further validated our results by analyzing additional datasets, including Expression Project for Oncology (expO) bulk RNA-seq dataset (n = 1118) and single-cell RNA-seq dataset (n = 14). Results of our study indicate that in female patients, two immune subtypes, C1 and C2, are respectively over and under abundant in smokers vs. never smokers. In males, the only significant difference is underabundance of the C6 subtype in smokers. We identified gender-specific differences in the population of immune cell types between smokers and never smokers in all TCGA and expO cancer types. Increased plasma cell population was identified as the most consistent feature distinguishing smokers and never smokers, especially in current female smokers based on both TCGA and expO data. Our analysis of existing single-cell RNA-seq data further revealed that smoking differentially affects the gene expression profile of cancer patients based on the immune cell type and gender. In our analysis, female and male smokers show different smoking-induced patterns of immune cells in tumor microenvironment. Besides, our results suggest cancer tissues directly exposed to tobacco smoke undergo the most significant changes, but all other tissue types are affected as well. Findings of current study also indicate that changes in the populations of plasma cells and their correlations to survival outcomes are stronger in female current smokers, with implications for cancer immunotherapy of women smokers. In conclusion, results of this study can be used to develop personalized treatment plans for cancer patients who smoke, particularly women smokers, taking into account the unique immune cell profile of their tumors.

Sexual dimorphism in obesity is governed by RELMα regulation of adipose macrophages and eosinophils.

Obesity incidence is increasing worldwide with the urgent need to identify new therapeutics. Sex differences in immune cell activation drive obesity-mediated pathologies where males are more susceptible to obesity co-morbidities and exacerbated inflammation. Here, we demonstrate that the macrophage-secreted protein RELMα critically protects females against high fat diet-induced obesity. Compared to male mice, RELMα levels were elevated in both control and high fat dietfed females and correlated with adipose macrophages and eosinophils. RELMα-deficient females gained more weight and had pro-inflammatory macrophage accumulation and eosinophil loss, while both RELMα treatment and eosinophil transfer rescued this phenotype. Single cell RNA-sequencing of the adipose stromal vascular fraction was performed and identified sex and RELMα-dependent changes. Genes involved in oxygen sensing and iron homeostasis, including hemoglobin and lncRNA Gm47283, correlated with increased obesity, while eosinophil chemotaxis and response to amyloid-beta were protective. Monocyte-to-macrophage transition was also dysregulated in RELMα-deficient animals. Collectively, these studies implicate a RELMα-macrophage-eosinophil axis in sex-specific protection against obesity and uncover new therapeutic targets for obesity.

Resistin Concentration in Early Sepsis and All-Cause Mortality at a Safety-Net Hospital in Riverside County.

Background: Sepsis mortality has remained unchanged for greater than a decade, and early recognition continues to be the most important factor in mortality outcome. Plasma resistin concentration is increased in sepsis, but its mechanism and clinical relevance is unclear. As one function, resistin interacts with toll-like receptor 4 in competition with lipopolysaccharide, a main component of the gram-negative bacterial cell wall. It is not known if the type of infection leading to sepsis influences resistin production. The objective of this study was to investigate whether 1) early plasma resistin concentration can predict mortality, 2) elevated plasma resistin concentration is associated with clinical disease severity scores, such as SOFA, mSOFA and APACHE II, and 3) plasma resistin concentrations differ between gram negative versus other etiologies of sepsis. Methods: This was an exploratory study in the framework of a prospective observational design. Peripheral venous blood samples were obtained from subjects admitted to the intensive care unit at clinical recognition of sepsis (0 hour) and at 6 and 24 hours. Vasopressor utilization was not a requirement for inclusion. Plasma was analyzed for resistin concentration by ELISA. Cytokine concentrations including IL-6, IL-8, and IL-10 were determined by cytokine bead array. Cytokine data were evaluated against publicly available sepsis RNA expression datasets to compare protein versus RNA expression levels in predicting clinical disease state. Clinical data were collected from electronic health records for clinical severity index calculations and context for interpretation of resistin and cytokine concentrations. Subjects were followed up to 60 days, or until death, whichever came first. Statistical analysis was completed with R package and SPSS software. Results: Resistin levels were elevated in subjects admitted to the intensive care unit with sepsis. Four-hundred subjects were screened with 45 subjects included in the final analysis. Thirteen of 45 patients were non-survivors. Mortality within 60 days correlated with significantly higher resistin concentrations than in survivors. A resistin concentration of >126 ng/mL at clinical recognition of sepsis and >197 ng/mL within the first 24 hours were associated with mortality within 60 days with an area under the curve of 0.82 and 0.88, respectively. Most subjects with resistin concentration greater than these threshold values were deceased prior to 30 days. Resistin concentrations correlated with SOFA, mSOFA, and APACHE II scores in addition to having association with increases in inflammatory and sepsis biomarkers. These associations were validated with analysis of RNA expression datasets. Conclusion: Plasma resistin concentrations of >126 ng/mL at clinical recognition of sepsis and >197 ng/mL within the first 24 hours of clinical sepsis recognition are associated with all-cause mortality. Resistin concentration within this timeframe also has comparable mortality association to well-validated clinical severity indices of SOFA, mSOFA, and APACHE II scores.

Dynamic changes in human single-cell transcriptional signatures during fatal sepsis.

Systemic infections, especially in patients with chronic diseases, may result in sepsis: an explosive, uncoordinated immune response that can lead to multisystem organ failure with a high mortality rate. Patients with similar clinical phenotypes or sepsis biomarker expression upon diagnosis may have different outcomes, suggesting that the dynamics of sepsis is critical in disease progression. A within-subject study of patients with Gram-negative bacterial sepsis with surviving and fatal outcomes was designed and single-cell transcriptomic analyses of peripheral blood mononuclear cells (PBMC) collected during the critical period between sepsis diagnosis and 6 h were performed. The single-cell observations in the study are consistent with trends from public datasets but also identify dynamic effects in individual cell subsets that change within hours. It is shown that platelet and erythroid precursor responses are drivers of fatal sepsis, with transcriptional signatures that are shared with severe COVID-19 disease. It is also shown that hypoxic stress is a driving factor in immune and metabolic dysfunction of monocytes and erythroid precursors. Last, the data support CD52 as a prognostic biomarker and therapeutic target for sepsis as its expression dynamically increases in lymphocytes and correlates with improved sepsis outcomes. In conclusion, this study describes the first single-cell study that analyzed short-term temporal changes in the immune cell populations and their characteristics in surviving or fatal sepsis. Tracking temporal expression changes in specific cell types could lead to more accurate predictions of sepsis outcomes and identify molecular biomarkers and pathways that could be therapeutically controlled to improve the sepsis trajectory toward better outcomes.

Protocol and Guidelines for Point-of-Care Lung Ultrasound in Diagnosing Neonatal Pulmonary Diseases Based on International Expert Consensus.

Ultrasound is a safe bedside imaging tool that obviates the use of ionizing radiation diagnostic procedures. Due to its convenience, the lung ultrasound has received increasing attention from neonatal physicians. Nevertheless, clear reference standards and guideline limits are needed for accurate application of this diagnostic modality. This document aims to summarize expert opinions and to provide precise guidance to help facilitate the use of the lung ultrasound in the diagnosis of neonatal lung diseases.