Background: Wildfires are increasingly common with wildfire smoke affecting millions globally, yet its impact on immune responses is poorly understood. Natural Killer (NK) cells play a role in mediating air pollutant effects and regulating vaccine immunity. Objective: This real-world study, conducted on participants in the Pfizer BNT162b2 COVID-19 vaccine trial, studied the effects of wildfire smoke exposure on long-term vaccine effects. Methods: We collected blood samples from 52 healthy, non-smoking participants (ages 26-83) before and 1 month after placebo or vaccine injections during heavy wildfire smoke events in Sacramento. The study included 28 vaccinated (Group 1) and 24 placebo-injected (Group 2) individuals, the latter vaccinated several months later, outside wildfire season. Blood samples from both Group 1 and 2 were also investigated 6 months after the second dose of vaccine. We analyzed intracellular cytokines, B and NK cell markers by flow cytometry, and serum immunoglobulin levels against common coronaviruses using multiplex assays. Results: A robust S-RBD-specific IgG response observed 1 month post booster, declined variably 6 months later. Wildfire smoke acutely increased IL-13 expression by CD56bright NK cells. IL-13+CD56bright NK cells at the time of vaccination negatively correlated with anti-S-RBD IgG (r=-0.41, p<0.05) one month later. Total IgG levels on the other hand, positively correlated with the air quality index (AQI) measured during vaccination (r=0.96, p<0.01). Similarly to age (but not sex, BMI or race/ethnicity), the two-week AQI averages during vaccination showed a significant negative correlation with anti-S-RBD IgG levels 6 months later (r=-0.41, p<0.05). Conclusion: Wildfire smoke may lead to inappropriate immunoglobulin production and diminished vaccine immunity. Our novel findings highlight a previously unrecognized pathway involving NK-cell derived IL-13 and non-specific B-cell activation and underscore the significance of environmental exposures in shaping immunity.

Wildfires are increasing in intensity, duration, and frequency with smoke plums affecting the lives of millions over large geographic areas. The immune modulatory effects of wildfire smoke are unclear. We previously showed that a major wildfire smoke component, ozone, inhibited dendritic cell lymph node homing (an essential process in vaccine immunity) by suppressing NK cell-derived IFN-γ expression in mice.

Drug discovery is the mainstay of the pharmaceutical industry. Despite the advent of technologies that enable a deep understanding of diseases at the molecular and biochemical levels, drug target identification remains a bottle neck in the drug discovery process. The number of targets with which approved drugs interact represents only a tiny fraction of the human proteome. In addition, most of the newly identified targets fall into certain privileged protein families, and the discovery of a new class of drug targets is a rare event. While there could be a lot more of druggable proteins encoded by the genome, technologies enabling their discovery are limited. Furthermore, the multifactorial genesis of diseases makes target discovery less straight forward. The target identification strategy is dependent upon the mode of drug discovery. Whereas the forward pharmacology approach relies on identifying drug leads first and then deconvoluting the targets, reverse pharmacology utilizes hypothetical or validated targets as the starting point for lead identification. The unravelling of the human genome and the subsequent revolution in high-throughput omics technologies and data-driven discovery paradigms in biology is impacting the drug discovery enterprise, as any other domain. High-throughput genome editing technologies such as CRISPR-Cas9, transcriptomics tools like RNA-seq, and advancements in mass spectrometry are expected to accelerate target identification. Furthermore, the surge in omics data has provided a better scope for computational and machine-learning interventions in drug discovery. The present chapter reviews the contemporary methods used in drug target identification.

BACKGROUND:Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological analysis, combined with clinical, microbiological, and immunological data, by machine learning (ML), can help achieve it. METHODS:Six rhesus macaques were experimentally inoculated with pathogenic Mycobacterium tuberculosis in the lung. Data, including Computed Tomography (CT), were collected at 0, 2, 4, 8, 12, 16, and 20 weeks. RESULTS:Our ML-based CT analysis (TB-Net) efficiently and accurately analyzed disease progression, performing better than standard deep learning model (LLM OpenAI's CLIP Vi4). TB-Net based results were more consistent than, and confirmed independently by, blinded manual disease scoring by two radiologists and exhibited strong correlations with blood biomarkers, TB-lesion volumes, and disease-signs during disease pathogenesis. CONCLUSION:The proposed approach is valuable in early disease detection, monitoring efficacy of therapy, and clinical decision making.

Complementary and alternative medicines (CAM) include conventional medical treatments. Patients worldwide use CAM at alarming rates; thus, reports of CAM-related DILI have been on the rise. The clinical presentations include asymptomatic liver test abnormalities, acute hepatitis with or without jaundice, acute cholestatic liver disease (bland or with hepatitis), acute liver failure, severe hepatitis with features of portal hypertension, and acute decompensation of known or unknown cirrhosis that can lead to acute-on-chronic liver failure. Acute hepatitis with or without necrosis, hepatocellular and canalicular cholestasis, herb-induced or CAM-triggered autoimmune hepatitis, granulomatous hepatitis, severe steatohepatitis, and vanishing bile duct syndrome are common liver biopsy findings in CAM-DILI. The presence of preexisting liver disease predicts severe liver injury, risk of progression to liver failure, and decreased transplant-free survival in patients with CAM-DILI. This review discusses global epidemiology and trends in CAM-DILI, clinical presentation, assessment and outcomes, commonly emerging threats in the context of hepatotoxic herbs, pragmatic assessment of “liver beneficial” herbs and health care myths, patient communication, regulatory framework, and future directions on research in CAM.

Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases.

This study investigates Bacillus Calmette-Guérin (BCG) as a potential treatment for hepatocellular carcinoma (HCC), a condition often associated with unfavorable treatment outcomes. Exploiting BCG's recognized immune-boosting properties, preclinical trials are conducted using HCC mice, with a single subcutaneous dose of BCG administered post-tumor formation. Results indicate that BCG treatment effectively diminishes tumor burden and extends survival in both male and female HCC mice. Positive influences on hepatic fibrosis and metabolism are observed, leading to a reduction in lipid levels. Spatial analysis underscores BCG's tumor-specific effects, inducing the enrichment of metabolic pathways and inhibiting various cancer-related pathways. Furthermore, BCG promotes immune cell infiltration, including CD4+, CD8+ T cells, and M1 macrophages, in both v-akt murine thymoma viral oncogene homolog 1(AKT)/neutoblastoma RAS viral oncogene homolog (RAS) and β-catenin positive HCC models. Interestingly, blocking T cells, trained immunity, and Interferon-γ (IFN-γ) function reverses BCG's anti-HCC effects. In conclusion, BCG emerges as a promising treatment option for HCC, characterized by a favorable safety profile and efficacy in inhibiting fibrosis, improving metabolism, and engaging both trained immunity and T cells in therapeutic mechanisms.

Protein powders, including those containing herbal and dietary supplements such as vitamins, minerals, and other natural or synthetic ingredients, can be associated with hepatotoxicity. Protein supplements are often mislabeled and deceptive in their contents. In this self-funded transparent study, we extensively analyzed popular protein supplements in India to identify potential hepatotoxic substances based on industrial standards. All products underwent extensive analysis, including total protein content, fungal aflatoxin detection, pesticide residue estimation, heavy metal quantification, steroid detection, and complete organic and inorganic profiling, according to industry standards. Most protein supplements did not meet the labeled and advertised protein content, while certain brands surpassed the stated levels, raising concerns about potential “protein/amino-spiking.” In addition, the major brands contained detectable fungal toxins and pesticide residues. Furthermore, many major formulations contained harmful heavy metals such as lead and arsenic, and some featured hepatoxic herbal extracts, particularly green tea extract, turmeric, Garcinia cambogia, and Ashwagandha. Indian-made products were inferior to those manufactured by multinational companies. The presence of various potentially toxic compounds, such as cycloheptatriene, benzene derivatives, toluene, and isopropyl alcohol, within a nonstandardized and unregulated diverse ingredient mix added to the overall concern. We demonstrate that the protein-based herbal and dietary supplement industry requires stringent scrutiny, regulation, and basic safety studies before being marketed. Manufacturers must consider reducing “ingredient complexities” of their protein powders to prevent adverse interactions between herbal and nonherbal components in consumers. Manufacturers must avoid using known toxic ingredients to reduce the avoidable disease burden within the public community.

The greatest loss to the world’s economy has resulted from the multidrug resistance (MDR) strains and other prevalent infectious diseases like leishmania, diarrheal diseases, malaria, tuberculosis, parasitic infections, pneumonia, and trypanosomiasis. Antibiotics have played the core role of wonder drugs in treating a variety of diseases. However, the irregular, unsuitable, and irrational uses of antibiotics have led to the emergence of antibiotic resistance. This has paved the way to an increased usage of medicinal plants as currently, many nutraceuticals and pharmaceuticals are plant derived. This chapter describes the huge repositories of secondary metabolites present in medicinal plants that may provide novel antibiotics to tackle all the infectious disease-causing pathogens and other prevalent diseases and reclaim the currently used antibiotics. The wide spectrum of phytochemicals in medicinal plants is to be explored as potential therapeutics for the sustainable use of plant resources. This chapter focuses on the diverse efficacy and effects of plant-derived multiple compounds for the development of bioactive therapeutics to identify novel antibiotics in controlling many infectious pathogens and finding a cure for the most common prevalent diseases. More research into unexplored plants is the need of the hour for global health benefits to identify novel antibiotics.

Host immune responses play a key role in COVID-19 pathogenesis. The underlying phenomena are orchestrated by signaling molecules such as cytokines/chemokines and lipid mediators. These immune molecules, including anti-SARS-CoV-2 antibodies, interact with immune cells and regulate host responses, contributing to inflammation that drives the disease. We investigated 48 plasma cytokines/chemokines, 21 lipid mediators, and anti-S protein (RBD) antibodies in COVID-19 patients (n = 56) and non-COVID-19 respiratory disease controls (n = 49), to identify immune-biomarker profiles. Cytokines/chemokines (IL-6, CXCL-10 (IP-10), HGF, MIG, MCP-1, and G-CSF) and lipid mediators (TxB2, 11-HETE, 9-HODE, 13-HODE, 5-HETE, 12-HETE, 15-HETE, 14S-HDHA, 17S-HDHA, and 5-oxo ETE) were significantly elevated in COVID-19 patients compared to controls. In patients exhibiting severe disease, pro-inflammatory cytokines/chemokines (IL-6, CXCL-10, and HGF) and anti-SARS-CoV-2 antibodies were significantly elevated. In contrast, lipid mediators involved in the reduction/resolution of inflammation, in particular, 5-HETE, 11-HETE, and 5-oxoETE, were significantly elevated in mild/moderate disease. Taken together, these immune-biomarker profiles provide insight into immune responses related to COVID-19 pathogenesis. Importantly, our findings suggest that elevation in plasma concentrations of IL-6, CXCL-10, HGF, and anti-SARS-CoV-2 antibodies can predict severe disease, whereas elevation in lipid mediators peaks early (compared to cytokines) and includes induction of mechanisms leading to reduction of inflammation, associated complications, and maintenance of homeostasis.

We assessed the humoral immune responses to a COVID-19 vaccine in a well-controlled rhesus macaque model compared to humans immunized with two mRNA vaccines over several months post-second dose. The plasma IgG levels against seven coronaviruses (including SARS-CoV-2) and antibody subtypes (IgG 1-4 and IgM) against SARS-CoV-2 were evaluated using multiplex assays. The neutralization capacity of plasma antibodies against the original SAR-CoV-2 isolate and nine variants was evaluated in vaccinated humans and non-human primates. Immunization of macaques and humans with SARS-CoV-2 vaccines induced a robust neutralizing antibody response. In non-SIV-infected adult macaques immunized with an adenoviral vector expressing S-RBD (n = 7) or N protein (n = 3), elevated levels of IgG and neutralizing antibodies were detected 2 weeks post-second dose. Immune responses to the S-RBD vaccine in SIV-infected adult macaques (n = 2) were similar to the non-SIV-infected animals. Adult humans immunized with Pfizer (n = 35) or Moderna (n = 18) vaccines developed IgG and neutralizing antibodies at 4 weeks post-second dose. In both vaccine groups, IgG 1 was the predominant subtype, followed by IgG 3. The IgG levels, including total and IgG 1,2,3 elicited by the Moderna vaccine, were significantly higher than the corresponding levels elicited by the Pfizer vaccine at 4 weeks post-second dose. A significant correlation was observed between the plasma total IgG antibody levels and neutralization titers in both macaques and humans. Furthermore, broad-spectrum neutralization antibodies against several variants of SARS-CoV-2 were detected in the plasma of both macaques and humans after two vaccinations.

Background: Ashwagandha herb is commonly used in Ayurveda and a "fad" dietary supplement for a host of indications based on low levels of evidence. Recently, ashwagandha was implicated in multiple reports of herb-induced liver injury (HILI), mainly from the United States. We present the first, and currently largest, series of ashwagandha-HILI from multiple centers in India. Methods: We retrospectively analyzed the respective institutional electronic medical records for ashwagandha-HILI. Patients consuming ashwagandha as part of multiherbal formulations or along with other known hepatotoxic supplements or medicines were excluded. All patients underwent a detailed diagnostic workup to exclude competing causes reasonably. Where possible, the implicated herbal formulation was retrieved and subjected to chemical analysis. Results: Out of 23 patients with liver injury from ashwagandha (January 2019 to December 2022), we report 8 patients with single-ingredient formulation-related HILI. Study cohort was male predominant, and cholestatic hepatitis was the commonest presentation. Five patients had underlying chronic liver disease; 3 presented with acute-on-chronic liver failure, and all 3 died on follow-up. In others, the liver injury was prolonged, nonetheless self-limiting. Liver biopsy revealed cholestatic features predominantly with hepatocellular necrosis and lymphocyte/eosinophil predominant portal-based inflammation. One patient progressed to chronic HILI. Chemical analysis revealed only natural phytochemicals without adulteration or contamination. Conclusions: Ashwagandha-HILI presents with cholestatic hepatitis and can lead to the syndrome of acute-on-chronic liver failure with high mortality in those with pre-existing liver disease. Educating the public on avoiding the use of potentially toxic and unrecommended herbal supplements can help mitigate the avoidable liver disease burden in the community.

Hepatitis-associated aplastic anaemia (HAAA) is a rare condition characterised by onset of acute hepatitis which is followed by development of severe pancytopenia due to bone marrow failure within 6 months. This syndrome can be precipitated by acute viral infections, but the aetiology remains unknown in the majority. Drug-induced HAAA is extremely rare and has been reported with nutritional and dietary supplements in current literature. We report the first cases of ayurvedic herbal and homeopathic remedies-associated HAAA in two patients which proved fatal in both. Evaluation of patients with acute hepatitis and severe pancytopenia must include a detailed evaluation for complementary and alternative medicine use.

OBJECTIVE:This study was undertaken to identify the mechanistic role of γδ T cells in the pathogenesis of experimental psoriatic arthritis (PsA).METHODS:In this study, we performed interleukin-23 (IL-23) gene transfer in wild-type (WT) and T cell receptor δ-deficient (TCRδ-/- ) mice and conducted tissue phenotyping in the joint, skin, and nails to characterize the inflammatory infiltrate. We further performed detailed flow cytometry, immunofluorescence staining, RNA sequencing, T cell repertoire analysis, and in vitro T cell polarization assays to identify regulatory mechanisms of γδ T cells.RESULTS:We demonstrated that γδ T cells support systemic granulopoiesis, which is critical for murine PsA-like pathology. Briefly, γδ T cell ablation inhibited the expression of neutrophil chemokines CXCL1 and CXCL2 and neutrophil CD11b+Ly6G+ accumulation in the aforementioned PsA-related tissues. Although significantly reduced expression of granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-17A was detected systemically in TCRδ-/- mice, no GM-CSF+/IL-17A+ γδ T cells were detected locally in the inflamed skin or bone marrow in WT mice. Our data showed that nonresident γδ T cells regulate the expansion of an CD11b+Ly6G+ neutrophil population and their recruitment to joint and skin tissues, where they develop hallmark pathologic features of human PsA.CONCLUSION:Our findings do not support the notion that tissue-resident γδ T cells initiate the disease but demonstrate a novel role of γδ T cells in neutrophil regulation that can be exploited therapeutically in PsA patients.

Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time consuming and tedious undertaking addressed by the automated machine learning platform MILO (Machine Intelligence Learning Optimizer). MILO seamlessly integrates data processing, feature selection, model training, and model validation to simultaneously generate and evaluate thousands of models. These models were then further tested for generalizability on out-of-sample secondary and tertiary datasets. Out of 31 antigens evaluated, a 23-antigen model was the most robust on both the secondary dataset (TB vs healthy) and the tertiary dataset (TB vs COPD) with sensitivity of 90.5% and respective specificities of 100.0% and 74.6%. MILO represents a user-friendly, end-to-end solution for automated generation and deployment of optimized models, ideal for applications where rapid clinical implementation is critical such as emerging infectious diseases.

Polyunsaturated fatty acids are metabolized into regulatory lipids important for initiating inflammatory responses in the event of disease or injury and for signaling the resolution of inflammation and return to homeostasis. The epoxides of linoleic acid (leukotoxins) regulate skin barrier function, perivascular and alveolar permeability and have been associated with poor outcomes in burn patients and in sepsis. It was later reported that blocking metabolism of leukotoxins into the vicinal diols ameliorated the deleterious effects of leukotoxins, suggesting that the leukotoxin diols are contributing to the toxicity. During quantitative profiling of fatty acid chemical mediators (eicosanoids) in COVID-19 patients, we found increases in the regioisomeric leukotoxin diols in plasma samples of hospitalized patients suffering from severe pulmonary involvement. In rodents these leukotoxin diols cause dramatic vascular permeability and are associated with acute adult respiratory like symptoms. Thus, pathways involved in the biosynthesis and degradation of these regulatory lipids should be investigated in larger biomarker studies to determine their significance in COVID-19 disease. In addition, incorporating diols in plasma multi-omics of patients could illuminate the COVID-19 pathological signature along with other lipid mediators and blood chemistry.

Tuberculosis (TB) is the largest infectious disease with 10 million new active-TB patients and1.7 million deaths per year. Active-TB is an inflammatory disease and is increasingly viewed as an imbalance of immune responses to M. tb. infection. The mechanisms of a switch from latent infection to active disease is not well worked out but a shift in the immune responses is thought to be responsible. Increasingly, the role of gut microbiota has been described as a major influencer of the immune system. And because the gut is the largest immune organ, we aimed to analyze the gut microbiome in active-TB patients in a TB-endemic country, Pakistan. The study revealed that Ruminococcacea, Enetrobactericeae, Erysipelotrichaceae, Bifidobacterium, etc. were the major genera associated with active-TB, also associated with chronic inflammatory disease. Plasma antibody profiles against several M. tb. antigens, as specific biomarkers for active-TB, correlated closely with the patient gut microbial profiles. Besides, bcoA gene copy number, indicative of the level of butyrate production by the gut microbiome was five-fold lower in TB patients compared to healthy individuals. These findings suggest that gut health in TB patients is compromised, with implications for disease morbidity (e.g., severe weight loss) as well as immune impairment.

Rationale: Surfactant protein D (SP-D) is a major immune protective molecule produced in the respiratory epithelium. SP-D binds to specific pathogen surfaces through its carbohydrate recognition (lectin) domain, that helps in their neutralization and clearance by phagocytes. SP-D also acts as an anti-inflammatory molecule. We hypothesized that SP-D plays a protective role in COVID-19. Methods: Polar+, a novel quantum computing algorithm for molecular pruning, and classical in silico modeling were used to investigate potential binding sites between SP-D and SARS CoV2. Electronegativity and topologically oriented molecular pruning, calculation of electronic force-fields and electrostatic binding combined with protein-protein docking, geometric fitting and assessment of protein glycosylation sites were employed. SP-D-/- mouse lung was used to study expression of the SARS-CoV-2 viral entry molecules TMPRSS2 and ACE2. Plasma from COVID-19 patients was studied for SP-D leakage, cytokine levels and lipid mediators. Results: We found that SP-D potentially binds to the same SARS CoV-2 glycoprotein (S protein) that it utilizes to bind the cellular receptor, ACE2, with high affinity. However, SP-D binds to subunit 2, instead of subunit 1 (that ACE2 utilizes). Additional studies will need to determine if SP-D binding affects S protein and ACE2 interactions. We also found that SP-D-/- mice had increased expression of the TMRSS2 gene in the lung and that both TMPRSS2 and ACE2 mRNA levels were increased during lung injury, amplified by the lack of SP-D. SP-D leakage from the lung to the circulation was significantly increased in COVID- 19 patients and correlated with expression of pro-neutrophilic inflammatory markers. Conclusions: We speculate that SP-D aids in the protection from SARS CoV2 infection by both acting as a potential natural decoy to prevent coronavirus entry into airway epithelial cells and by attenuating the expression of the viral entry receptor TMPRSS2. Oxidative lung injury results in SP-D leak into the circulation denoting disease severity in COVID-19 patients. (AH) .

COVID-19 serological test must have high sensitivity as well as specificity to rule out cross-reactivity with common coronaviruses (HCoVs). We have developed a quantitative multiplex test, measuring antibodies against spike (S) proteins of SARS-CoV-2, SARS-CoV, MERS-CoV, and common human coronavirus strains (229E, NL63, OC43, HKU1), and nucleocapsid (N) protein of SARS-CoV viruses. Receptor binding domain of S protein of SARS-CoV-2 (S-RBD), and N protein, demonstrated sensitivity (94% and 92.5%, respectively) in COVID-19 patients (n = 53), with 98% specificity in non-COVID-19 respiratory-disease (n = 98), and healthy-controls (n = 129). Anti S-RBD and N antibodies appeared five to ten days post-onset of symptoms, peaking at approximately four weeks. The appearance of IgG and IgM coincided while IgG subtypes, IgG1 and IgG3 appeared soon after the total IgG; IgG2 and IgG4 remained undetectable. Several inflammatory cytokines/chemokines were found to be elevated in many COVID-19 patients (e.g., Eotaxin, Gro-α, CXCL-10 (IP-10), RANTES (CCL5), IL-2Rα, MCP-1, and SCGF-b); CXCL-10 was elevated in all. In contrast to antibody titers, levels of CXCL-10 decreased with the improvement in patient health suggesting it as a candidate for disease resolution. Importantly, anti-N antibodies appear before S-RBD and differentiate between vaccinated and infected people—current vaccines (and several in the pipeline) are S protein-based.