Lipopolysaccharide induces acute lung injury and alveolar haemorrhage in association with the cytokine storm, coagulopathy and AT1R/JAK/STAT augmentation in a rat model that mimics moderate and severe Covid-19 pathology.

Progress in the study of Covid-19 disease in rodents has been hampered by the lack of angiotensin-converting enzyme 2 (ACE2; virus entry route to the target cell) affinities for the virus spike proteins across species. Therefore, we sought to determine whether a modified protocol of lipopolysaccharide (LPS)-induced acute respiratory distress syndrome in rats can mimic both cell signalling pathways as well as severe disease phenotypes of Covid-19 disease. Rats were injected via intratracheal (IT) instillation with either 15 mg/kg of LPS (model group) or saline (control group) before being killed after 3 days. A severe acute respiratory syndrome (SARS)-like effect was observed in the model group as demonstrated by the development of a "cytokine storm" (>2.7 fold increase in blood levels of IL-6, IL-17A, GM-CSF, and TNF-α), high blood ferritin, demonstrable coagulopathy, including elevated D-dimer (approximately 10-fold increase), PAI-1, PT, and APTT (p < 0.0001). In addition, LPS increased the expression of lung angiotensin II type I receptor (AT1R)-JAK-STAT axis (>4 fold increase). Chest imaging revealed bilateral small patchy opacities of the lungs. Severe lung injury was noted by the presence of both, alveolar collapse and haemorrhage, desquamation of epithelial cells in the airway lumen, infiltration of inflammatory cells (CD45+ leukocytes), widespread thickening of the interalveolar septa, and ultrastructural alterations similar to Covid-19. Thus, these findings demonstrate that IT injection of 15 mg/kg LPS into rats, induced an AT1R/JAK/STAT-mediated cytokine storm with resultant pneumonia and coagulopathy that was commensurate with moderate and severe Covid-19 disease noted in humans.

Multiplex gyrB PCR Assay for Identification of Acinetobacter baumannii Is Validated by Whole Genome Sequence-Based Assays.

OBJECTIVE: A multiplex gyrB PCR assay has been used to diagnose Acinetobacter baumannii. However, this assay has not been validated against the gold standard DNA-DNA hybridization assay, which is a laborious method. DNA-DNA hybridization assay is now replaced by whole genome sequence (WGS)-based methods. Two such methods are a k-mer-based search of sequence reads using the Kraken 2 program and average nucleotide identity (ANI). The objective was to validate the gyrB PCR assay with WGS-based methods. SUBJECTS AND METHODS: We cultured 270 sequential A. baumannii isolates from the rectal swabs of 32 adult patients. The identity of the isolates was determined by gyrB PCR. The sequences of 269 isolates were determined by Illumina sequencing and the taxonomy was inferred by the Kraken 2 program and ANI. RESULTS: All the 269 isolates were confirmed as A. baumannii by Kraken 2 and ANI. CONCLUSION: The gyrB PCR assay is now validated for easy identification of A. baumannii in comparison with gold standard WGS-based assays.

Expanding the phenotype, genotype and biochemical knowledge of ALG3-CDG.

Congenital disorders of glycosylation (CDGs) are a continuously expanding group of monogenic disorders of glycoprotein and glycolipid biosynthesis that cause multisystem diseases. Individuals with ALG3-CDG frequently exhibit severe neurological involvement (epilepsy, microcephaly, and hypotonia), ocular anomalies, dysmorphic features, skeletal anomalies, and feeding difficulties. We present 10 unreported individuals diagnosed with ALG3-CDG based on molecular and biochemical testing with 11 novel variants in ALG3, bringing the total to 40 reported individuals. In addition to the typical multisystem disease seen in ALG3-CDG, we expand the symptomatology of ALG3-CDG to now include endocrine abnormalities, neural tube defects, mild aortic root dilatation, immunodeficiency, and renal anomalies. N-glycan analyses of these individuals showed combined deficiencies of hybrid glycans and glycan extension beyond Man5 GlcNAc2 consistent with their truncated lipid-linked precursor oligosaccharides. This spectrum of N-glycan changes is unique to ALG3-CDG. These expanded features of ALG3-CDG facilitate diagnosis and suggest that optimal management should include baseline endocrine, renal, cardiac, and immunological evaluation at the time of diagnosis and with ongoing monitoring.

Cancer Management in Saudi Arabia: Recommendations by the Saudi Oncology HeAlth Economics ExpeRt GrouP (SHARP).

Cancer is widely recognized as a major global health problem and is estimated to rank as one of the leading causes of death worldwide. Saudi Arabia has undergone remarkable socioeconomic development in the past 40 years which has contributed to the increase in cancer incidence. The high costs of new oncology medications in combination with uncertainty of long-term effectiveness and safety outcomes highlight the importance of considering value, in terms of clinical outcomes, relative to cost. We convened a group of experts to discuss key factors impacting the current state of cancer management in Saudi Arabia and to agree on a list of recommendations, with a focus on value-based care, considering evidence, patients, and costs.

Resveratrol Pretreatment Ameliorates p53-Bax Axis and Augments the Survival Biomarker B-Cell Lymphoma 2 Modulated by Paracetamol Overdose in a Rat Model of Acute Liver Injury.

BACKGROUND: The potential protective effects of resveratrol (RES) on the modulation of hepatic biomarkers of apoptosis and survival, p53-Bax axis, and B-cell lymphoma 2 (Bcl-2) in an animal model of paracetamol-induced acute liver injury have not been investigated before. METHODS: The model group of rats received a single dose of paracetamol (2 g/kg, orally), whereas the protective group of rats were pretreated for 7 days with RES (30 mg/kg, i.p.) before they were given a single dose of paracetamol. All rats were then sacrificed 24-h post paracetamol ingestion. RESULTS: Histology images showed that paracetamol overdose induced acute liver injury, which was substantially protected by RES. Paracetamol significantly (p < 0.05) modulated p53, apoptosis regulator Bax, Bcl-2, tumor necrosis factor-alpha, interleukin-6, inducible nitric oxide synthase, malondialdehyde, superoxide dismutase, glutathione peroxidase, alanine aminotransferase, and aspartate aminotransferase, which were significantly protected by RES. We further demonstrated a significant (p< 0.01) correlation between either p53 or Bcl-2 scoring and the levels of inflammatory, nitrosative stress, and liver injury biomarkers. CONCLUSION: We demonstrate a substantial protection by RES pretreatment against paracetamol-induced modulation of p53-Bax axis, Bcl-2, and other acute liver injury biomarkers in rats.

Leishmaniasis in Saudi Arabia: Current situation and future perspectives.

BACKGROUND AND OBJECTIVE: Leishmaniasis is endemic in Saudi Arabia with cases reported in many regions. This review refers to publications on leishmaniasis in Saudi Arabia and discusses issues related to parasite species, clinical manifestation and diagnosis. METHODS: This research was done at Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia by systematic literature search on PubMed and Google Scholar databases from 1989 to 2018. Selection criteria included original articles reporting on visceral leishmaniasis (VL) or cutaneous leishmaniasis (CL) in Saudi Arabia. RESULTS: The search identified 16 eligible articles, six for VL and 10 for CL. VL was reported in areas known to be non-endemic. Leishmania donovani was the main cause for human VL while Leishmania infantum seemed to cause the disease in animals. Dogs were considered the main reservoir hosts and black rats (Rattus rattus) were potential hosts. VL mainly affected infants and young children. It is important to note that VL diagnosis was based on either invasive parasite detection procedures or serologically using indirect hemagglutination test. CL represented the most frequent clinical form with the main endemic foci reported in the South-West and Eastern regions. CL appeared to have no demographic or socioeconomic restriction; it affected both rural and urban citizens, with the majority occurring among farmers. Travelling was recognized as an important risk factor. Leishmania tropica and Leishmania major were recognized as the main causes for CL. CONCLUSION: This report summarizes the potential risks for VL and CL in Saudi Arabia in areas known to be non-endemic. There are substantial gaps in knowledge and practices in regard to leishmaniasis in Saudi Arabia, highlighting the need for more research and medical surveillance targeting the disease in humans and animals.

Metformin inhibits mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers in thioacetamide-induced hepatic tissue alterations.

The potential inhibitory effect of the antidiabetic and anti-inflammatory drug, metformin on thioacetamide (TAA)-induced hepatotoxicity associated with the inhibition of mammalian target of rapamycin (mTOR)-hypoxia-inducible factor-1α (HIF-1α) axis has not been investigated before. Therefore, we tested whether metformin can protect against liver injuries including fibrosis induced by TAA possibly via the downregulation of mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers. Rats either injected with TAA (200 mg/kg; twice a week for 8 weeks) before being killed after 10 weeks (model group) or were pretreated with metformin (200 mg/kg) daily for 2 weeks before TAA injections and continued receiving both agents until the end of the experiment, at Week 10 (protective group). Using light and electron microscopy examinations, we observed in the model group substantial damage to the hepatocytes and liver tissue such as collagen deposition, infiltration of inflammatory cells, and degenerative cellular changes with ballooned mitochondria that were substantially ameliorated by metformin. Metformin also significantly ( p < 0.05) inhibited TAA-induced HIF-1α, mTOR, the profibrogenic biomarker α-smooth muscle actin, tissue inhibitor of metalloproteinases-1, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), alanine aminotransferase (ALT) and aspartate aminotransferase in harvested liver homogenates and blood samples. In addition, a significant ( p < 0.01) positive correlation between hypoxia scoring (HIF-1α) and the serum levels of TNF-α ( r = 0.797), IL-6 ( r = 0.859), and ALT ( r = 0.760) was observed. We conclude that metformin protects against TAA-induced hepatic injuries in rats, which is associated with the inhibition of mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers; thus, may offer therapeutic potential in humans.

Truncating ARL6IP1 variant as the genetic cause of fatal complicated hereditary spastic paraplegia.

BACKGROUND: Mutations in ARL6IP1, which encodes a tetraspan membrane protein localized to the endoplasmic reticulum (ER), have been recently described in a large family with a complicated form of hereditary spastic paraplegia (HSP). CASE PRESENTATION: We sought to expand the HSP phenotype associated with ARL6IP1 variants by examining a Saudi kindred with a clinically more severe presentation, which resulted in spontaneous neonatal death of both affected siblings. Clinical features encompassed not only spastic paraplegia but also developmental delay, microcephaly, cerebral atrophy, periventricular leukoencephalopathy, hypotonia, seizures, spasticity, jejunal stricture, gastrointestinal reflux, neuropathy, dysmorphism and respiratory distress. We performed clinical assessment and radiological studies of this family, in addition to homozygosity mapping and whole exome sequencing (WES) to identify the disease-associated variant. Homozygosity mapping localized the causative gene to a region on chromosome 16 harboring ARL6IP1. WES of the index case identified the homoallelic nonsense variant, c.112C > T in ARL6IP1 that segregated with the phenotype and was predicted to result in loss of the protein. Allelic expression analysis of the parents demonstrated downward pressure on the mutant allele, suggestive of nonsense-mediated decay. CONCLUSIONS: Our report shows that the phenotype associated with ARL6IP1 variants may be broader and more acute than so far reported and identifies fatal HSP as the severe end of the phenotypic spectrum of ARL6IP1 variants.

Cardioprotective effect of ghrelin against myocardial infarction-induced left ventricular injury via inhibition of SOCS3 and activation of JAK2/STAT3 signaling.

The molecular mechanisms through which ghrelin exerts its cardioprotective effects during cardiac remodeling post-myocardial infarction (MI) are poorly understood. The aim of this study was to investigate whether the cardioprotection mechanisms are mediated by modulation of JAK/STAT signaling and what triggers this modulation. Rats were divided into six groups (n = 12/group): control, sham, sham + ghrelin (100 µg/kg, s.c., daily, starting 1 day post-MI), MI, MI+ ghrelin, and MI+ ghrelin+ AG490, a potent JAK2 inhibitor (5 mg/kg, i.p., daily). All treatments were administered for 3 weeks. Administration of ghrelin to MI rats improved left ventricle (LV) architecture and restored cardiac contraction. In remote non-infarcted areas of MI rats, ghrelin reduced cardiac inflammation and lipid peroxidation and enhanced antioxidant enzymatic activity. In addition, independent of the growth factor/insulin growth factor-1 (GF/IGF-1) axis, ghrelin significantly increased the phosphorylation of JAK2 and Tyr702 and Ser727 residues of STAT3 and inhibited the phosphorylation of JAK1 and Tyr701 and Ser727 residues of STAT1, simultaneously increasing the expression of BCL-2 and decreasing in the expression of BAX, cleaved CASP3, and FAS. This effect coincided with decreased expression of SOCS3. All these beneficial effects of ghrelin, except its inhibitory action on IL-6 expression, were partially and significantly abolished by the co-administration of AG490. In conclusion, the cardioprotective effect of ghrelin against MI-induced LV injury is exerted via activation of JAK2/STAT3 signaling and inhibition of STAT1 signaling. These effects were independent of the GF/IGF-1 axis and could be partially mediated via inhibition of cardiac IL-6.

Acylated ghrelin protects aorta damage post-MI via activation of eNOS and inhibition of angiotensin-converting enzyme induced activation of NAD(P)H-dependent oxidase.

NAD(P)H dependent oxidase derived-reactive oxygen species (ROS) due to activation of the renin-angiotensin-aldosterone system (RAAS) in blood vessels postmyocardial infarction MI or during the HF leads to endothelium dysfunction and enhanced apoptosis. Acylated ghrelin (AG) is a well-reported cardioprotective and antiapoptotic agent for the heart. AG receptors are widely distributed in most of blood vessels, suggesting a role in the regulation of endothelial function and survival. This study investigated if AG can protect aorta of rats' postmyocardial infarction (MI)-induced damage and endothelial dysfunction. Adult male rats were divided into four groups of (1) Sham, (2) Sham + AG, (3) MI, and (4) MI + AG. Vehicle (normal saline) or AG (100 µ/kg) was administered to rats for 21 consecutive days, after which, numerous biochemical markers were detected by blot. Both histological and electron microscope studies were carried on aortic samples from MI-induced rats. AG increased protein levels of both total and phosphorylated forms of endothelial nitric oxide synthase (eNOS and p-eNOS, respectively). Only in MI-treated rats, AG prevented the decreases in the levels of reduced glutathione (GSH) and superoxide dismutase (SOD) and lowered levels of malondialdehyde (MDA) and glutathione disulfide (GSSG). Concomitantly, it lowered the increased protein levels of angiotensin-converting enzyme (ACE), p22phox and cleaved caspase-3 and prevented the aorta histological and ultrustructural abnormalities induced by MI.

Exercise protects against insulin-dependent diabetes-induced osteoarthritis in rats: A scanning electron microscopy study.

We tested the hypothesis that swim exercise can protect the articular cartilage from damages induced secondary to insulin-dependent diabetes mellitus in rats using the scanning electron microscopy and to monitor the blood levels of oxidative and antioxidative stress biomarkers that are known to be modulated in osteoarthritis (OA). A profound damage to the cartilage was observed in the diabetic rats. Our findings also show that swim exercise protects the knee joints from damage induced by diabetes as well as significantly inhibiting OA-induced upregulation of thiobarbituric acid reactive substances (TBARS) and tumor necrosis factor alpha (TNF-α) and augmented superoxide dismutase (SOD) inhibition by OA. Thus, we demonstrated an effective protection by swim exercise against diabetes-induced OA in a rat model of the disease.

Effect of multifocality and multicentricity on outcome in early stage breast cancer: a systematic review and meta-analysis.

Women with multifocal or multicentric breast tumors (multifocality henceforth) have been reported to have greater probability of nodal metastasis and relapse and worse survival than women with unifocal tumors. However, these associations have been inconsistent and multifocality is not taken into account by staging guidelines and prognostic models. A systematic review of electronic databases identified publications exploring the association between multifocality and overall survival (OS), disease-free survival (DFS), disease-specific survival (DSS), and loco-regional relapse (LRR). The hazard ratios (HRs) for OS and DFS for multifocal compared to unifocal tumors were extracted from multivariable analyses and included in a meta-analysis. For studies not reporting multivariable analyses, odds ratios (OR) were estimated from Kaplan-Meier curves for all endpoints at 5 and 10 years. Twenty-two studies comprising 67,557 women were included. Multifocality was reported in 9.5 % of patients. Classical prognostic factors were well balanced between unifocal and multifocal populations. In multivariable analyses, multifocality was associated with significantly worse OS (HR 1.65; P = 0.02), and a non-significant association with worse DFS (HR 1.96; P = 0.07). In univariable analyses, multifocality was associated with worse OS, DFS, DSS, and LRR at 5 years (OR 1.39, P = 0.02; OR 1.52, P = 0.02; OR 1.56, P = 0.03; and OR 3.23, P = 0.02, respectively). Similar estimates were observed at 10 years, but statistical significance was only reached for DSS and LRR. Mutifocality appears to be associated with a worse prognosis, however, substantial inter-study heterogeneity limits the precise determination of increased risk. Further validation of the independent prognostic impact of multifocality is warranted.

The impact of human EGFR kinase domain mutations on lung tumorigenesis and in vivo sensitivity to EGFR-targeted therapies.

To understand the role of human epidermal growth factor receptor (hEGFR) kinase domain mutations in lung tumorigenesis and response to EGFR-targeted therapies, we generated bitransgenic mice with inducible expression in type II pneumocytes of two common hEGFR mutants seen in human lung cancer. Both bitransgenic lines developed lung adenocarcinoma after sustained hEGFR mutant expression, confirming their oncogenic potential. Maintenance of these lung tumors was dependent on continued expression of the EGFR mutants. Treatment with small molecule inhibitors (erlotinib or HKI-272) as well as prolonged treatment with a humanized anti-hEGFR antibody (cetuximab) led to dramatic tumor regression. These data suggest that persistent EGFR signaling is required for tumor maintenance in human lung adenocarcinomas expressing EGFR mutants.

Preventive roles of swimming exercise and pioglitazone treatment on hepatic dysfunction in a rat model of metabolic syndrome.

Pioglitazone (Pio) and swimming exercise (SE) are insulin sensitisers. This investigation was suggested because of the significant side effects associated with Pio treatment in metabolic syndrome (MetS). This study was, therefore, designed to investigate the preventive role of Pio treatment and SE in terms of efficiency and pathological changes in MetS in a rat model. Sixty male Sprague-Dawley rats were distributed equally among 6 groups: (i) control group (C), (ii) exercised control group (C+E), (iii) Pio-treated control group (C+Pio), (iv) group with MetS, (v) group with MetS treated with Pio (MetS+Pio), and (vi) exercised MetS group (MetS+E). Systolic blood pressure and heart rate were measured at the end of the experiments (16 weeks). Retro-orbital blood samples were used to determine the serum levels of glucose, insulin, lipids, gamma glutamyl transferase, alanine transaminase, aspartate transaminase, alkaline phosphatase, fetuin-A, and adiponectin. Semiquantitative reverse transcriptase - PCR insulin gene expression assays and hepatic histopathological examination were conducted. Swimming exercise significantly improved all of the aforementioned parameters, more so than the Pio treatment. In particular, the serum hepatic enzyme levels and hepatic histopathological changes were improved compared with the MetS group. These results suggested that swimming exercise might be an alternative physiological preventive tool against hepatic dysfunction to avoid the side effects associated with Pio treatment, and this could be demonstrated in a rat model of metabolic syndrome.

Investigating the impact of smoking habits through photoplethysmography analysis.

Smoking is widely recognized as a significant risk factor in the progression of arterial stiffness and cardiovascular diseases. Valuable information related to cardiac arrhythmias and heart function can be obtained by analyzing biosignals such as the electrocardiogram (ECG) and the photoplethysmogram (PPG). The PPG signal is a non-invasive optical technique that can be used to evaluate the changes in blood volume, and thus it can be linked to the health of the vascular system.Objective. In this study, the impact of three smoking habits-cigarettes, shisha, and electronic cigarettes (e-cigarettes)-on the features of the PPG signal were investigated.Approach. The PPG signals are measured for 45 healthy smokers before, during, and after the smoking session and then processed to extract the morphological features. Quantitative statistical techniques were used to analyze the PPG features and provide the most significant features of the three smoking habits. The impact of smoking is observed through significant changes in the features of the PPG signal, indicating blood volume instability.Main results. The results revealed that the three smoking habits influence the characteristics of the PPG signal significantly, which presentseven after 15 min of smoking. Among them, shisha has the greatest impact on PPG features, particularly on heart rate, systolic time, augmentation index, and peak pulse interval change. In contrast, e-cigarettes have the least effect on PPG features. Interestingly, smoking electronic cigarettes, which many participants use as a substitute for traditional cigarettes when attempting to quit smoking, has nearly a comparable effect to regular smoking.Significance. The findings suggest that individuals who smoke shisha are more likely to develop cardiovascular diseases at an earlier age compared to those who have other smoking habits. Understanding the variations in the PPG signal caused by smoking can aid in the early detection of cardiovascular disorders and provide insight into cardiac conditions. This ultimately contributes to the prevention of the development of cardiovascular diseases and the development of a health screening system.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

BACKGROUND: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques. METHODS: Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D. RESULTS: As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures. CONCLUSIONS: ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.

Platelet Metabolites as Candidate Biomarkers in Sepsis Diagnosis and Management Using the Proposed Explainable Artificial Intelligence Approach.

Background: Sepsis is characterized by an atypical immune response to infection and is a dangerous health problem leading to significant mortality. Current diagnostic methods exhibit insufficient sensitivity and specificity and require the discovery of precise biomarkers for the early diagnosis and treatment of sepsis. Platelets, known for their hemostatic abilities, also play an important role in immunological responses. This study aims to develop a model integrating machine learning and explainable artificial intelligence (XAI) to identify novel platelet metabolomics markers of sepsis. Methods: A total of 39 participants, 25 diagnosed with sepsis and 14 control subjects, were included in the study. The profiles of platelet metabolites were analyzed using quantitative 1H-nuclear magnetic resonance (NMR) technology. Data were processed using the synthetic minority oversampling method (SMOTE)-Tomek to address the issue of class imbalance. In addition, missing data were filled using a technique based on random forests. Three machine learning models, namely extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and kernel tree boosting (KTBoost), were used for sepsis prediction. The models were validated using cross-validation. Clinical annotations of the optimal sepsis prediction model were analyzed using SHapley Additive exPlanations (SHAP), an XAI technique. Results: The results showed that the KTBoost model (0.900 accuracy and 0.943 AUC) achieved better performance than the other models in sepsis diagnosis. SHAP results revealed that metabolites such as carnitine, glutamate, and myo-inositol are important biomarkers in sepsis prediction and intuitively explained the prediction decisions of the model. Conclusion: Platelet metabolites identified by the KTBoost model and XAI have significant potential for the early diagnosis and monitoring of sepsis and improving patient outcomes.

Combining the Strengths of the Explainable Boosting Machine and Metabolomics Approaches for Biomarker Discovery in Acute Myocardial Infarction.

Acute Myocardial Infarction (AMI), a common disease that can have serious consequences, occurs when myocardial blood flow stops due to occlusion of the coronary artery. Early and accurate prediction of AMI is critical for rapid prognosis and improved patient outcomes. Metabolomics, the study of small molecules within biological systems, is an effective tool used to discover biomarkers associated with many diseases. This study intended to construct a predictive model for AMI utilizing metabolomics data and an explainable machine learning approach called Explainable Boosting Machines (EBM). The EBM model was trained on a dataset of 102 prognostic metabolites gathered from 99 individuals, including 34 healthy controls and 65 AMI patients. After a comprehensive data preprocessing, 21 metabolites were determined as the candidate predictors to predict AMI. The EBM model displayed satisfactory performance in predicting AMI, with various classification performance metrics. The model's predictions were based on the combined effects of individual metabolites and their interactions. In this context, the results obtained in two different EBM modeling, including both only individual metabolite features and their interaction effects, were discussed. The most important predictors included creatinine, nicotinamide, and isocitrate. These metabolites are involved in different biological activities, such as energy metabolism, DNA repair, and cellular signaling. The results demonstrate the potential of the combination of metabolomics and the EBM model in constructing reliable and interpretable prediction outputs for AMI. The discussed metabolite biomarkers may assist in early diagnosis, risk assessment, and personalized treatment methods for AMI patients. This study successfully developed a pipeline incorporating extensive data preprocessing and the EBM model to identify potential metabolite biomarkers for predicting AMI. The EBM model, with its ability to incorporate interaction terms, demonstrated satisfactory classification performance and revealed significant metabolite interactions that could be valuable in assessing AMI risk. However, the results obtained from this study should be validated with studies to be carried out in larger and well-defined samples.

Metabolomics Biomarker Discovery to Optimize Hepatocellular Carcinoma Diagnosis: Methodology Integrating AutoML and Explainable Artificial Intelligence.

Background: This study aims to assess the efficacy of combining automated machine learning (AutoML) and explainable artificial intelligence (XAI) in identifying metabolomic biomarkers that can differentiate between hepatocellular carcinoma (HCC) and liver cirrhosis in patients with hepatitis C virus (HCV) infection. Methods: We investigated publicly accessible data encompassing HCC patients and cirrhotic controls. The TPOT tool, which is an AutoML tool, was used to optimize the preparation of features and data, as well as to select the most suitable machine learning model. The TreeSHAP approach, which is a type of XAI, was used to interpret the model by assessing each metabolite's individual contribution to the categorization process. Results: TPOT had superior performance in distinguishing between HCC and cirrhosis compared to other AutoML approaches AutoSKlearn and H2O AutoML, in addition to traditional machine learning models such as random forest, support vector machine, and k-nearest neighbor. The TPOT technique attained an AUC value of 0.81, showcasing superior accuracy, sensitivity, and specificity in comparison to the other models. Key metabolites, including L-valine, glycine, and DL-isoleucine, were identified as essential by TPOT and subsequently verified by TreeSHAP analysis. TreeSHAP provided a comprehensive explanation of the contribution of these metabolites to the model's predictions, thereby increasing the interpretability and dependability of the results. This thorough assessment highlights the strength and reliability of the AutoML framework in the development of clinical biomarkers. Conclusions: This study shows that AutoML and XAI can be used together to create metabolomic biomarkers that are specific to HCC. The exceptional performance of TPOT in comparison to traditional models highlights its capacity to identify biomarkers. Furthermore, TreeSHAP boosted model transparency by highlighting the relevance of certain metabolites. This comprehensive method has the potential to enhance the identification of biomarkers and generate precise, easily understandable, AI-driven solutions for diagnosing HCC.

Vanillylacetone attenuates cadmium chloride-induced hippocampal damage and memory loss through up-regulation of nuclear factor erythroid 2-related factor 2 gene and protein expression.

JOURNAL/nrgr/04.03/01300535-202412000-00030/figure1/v/2024-04-08T165401Z/r/image-tiff Memory loss and dementia are major public health concerns with a substantial economic burden. Oxidative stress has been shown to play a crucial role in the pathophysiology of hippocampal damage-induced memory impairment. To investigate whether the antioxidant and anti-inflammatory compound vanillylacetone (zingerone) can protect against hippocampal damage and memory loss induced by cadmium chloride (CdCl2) administration in rats, we explored the potential involvement of the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway, which is known to modulate oxidative stress and inflammation. Sixty healthy male Wistar rats were divided into five groups: vehicle-treated (control), vanillylacetone, CdCl2, vanillylacetone + CdCl2, vanillylacetone + CdCl2 + brusatol (a selective pharmacological Nrf2 inhibitor) groups. Vanillylacetone effectively attenuated CdCl2-induced damage in the dental gyrus of the hippocampus and improved the memory function assessed by the Morris Water Maze test. Additionally, vanillylacetone markedly decreased the hippocampal tissue levels of inflammatory biomarkers (interleukin-6, tumor necrosis factor-α, intracellular cell adhesive molecules) and apoptosis biomarkers (Bax and cleaved caspase-3). The control and CdCl2-treated groups treated with vanillylacetone showed reduced generation of reactive oxygen species, decreased malondialdehyde levels, and increased superoxide dismutase and glutathione activities, along with significant elevation of nuclear Nrf2 mRNA and protein expression in hippocampal tissue. All the protective effects of vanillylacetone were substantially blocked by the co-administration of brusatol (a selective Nrf2 inhibitor). Vanillylacetone mitigated hippocampal damage and memory loss induced by CdCl2, at least in part, by activating the nuclear transcription factor Nrf2. Additionally, vanillylacetone exerted its potent antioxidant and anti-inflammatory actions.