Prevalence and target attainment of traditional cardiovascular risk factors in patients with systemic lupus erythematosus: a cross-sectional study including 3401 individuals from 24 countries.

BACKGROUND: Systemic lupus erythematosus (SLE) is characterised by increased cardiovascular morbidity and mortality risk. We aimed to examine the prevalence of traditional cardiovascular risk factors and their control in an international survey of patients with systemic lupus erythematosus. METHODS: In this multicentre, cross-sectional study, cardiovascular risk factor data from medical files of adult patients (aged ≥18) with SLE followed between Jan 1, 2015, and Jan 1, 2020, were collected from 24 countries, across five continents. We assessed the prevalence and target attainment of cardiovascular risk factors and examined potential differences by country income level and antiphospholipid syndrome coexistence. We used the Systemic Coronary Risk Evaluation algorithm for cardiovascular risk estimation, and the European Society of Cardiology guidelines for assessing cardiovascular risk factor target attainment. People with lived experience were not involved in the research or writing process. FINDINGS: 3401 patients with SLE were included in the study. The median age was 43·0 years (IQR 33-54), 3047 (89·7%) of 3396 patients were women, 349 (10.3%) were men, and 1629 (48·1%) of 3390 were White. 556 (20·7%) of 2681 patients had concomitant antiphospholipid syndrome. We found a high cardiovascular risk factor prevalence (hypertension 1210 [35·6%] of 3398 patients, obesity 751 [23·7%] of 3169 patients, and hyperlipidaemia 650 [19·8%] of 3279 patients), and suboptimal control of modifiable cardiovascular risk factors (blood pressure [target of <130/80 mm Hg], BMI, and lipids) in the entire SLE group. Higher prevalence of cardiovascular risk factors but a better blood pressure (target of <130/80 mm Hg; 54·9% [1170 of 2132 patients] vs 46·8% [519 of 1109 patients]; p<0·0001), and lipid control (75·0% [895 of 1194 patients] vs 51·4% [386 of 751 patients], p<0·0001 for high-density lipoprotein [HDL]; 66·4% [769 of 1158 patients] vs 60·8% [453 of 745 patients], p=0·013 for non-HDL; 80·9% [1017 of 1257 patients] vs 61·4% [486 of 792 patients], p<0·0001 for triglycerides]) was observed in patients from high-income versus those from middle-income countries. Patients with SLE with antiphospholipid syndrome had a higher prevalence of modifiable cardiovascular risk factors, and significantly lower attainment of BMI and lipid targets (for low-density lipoprotein and non-HDL) than patients with SLE without antiphospholipid syndrome. INTERPRETATION: High prevalence and inadequate cardiovascular risk factor control were observed in a large multicentre and multiethnic SLE cohort, especially among patients from middle-income compared with high-income countries and among those with coexistent antiphospholipid syndrome. Increased awareness of cardiovascular disease risk in SLE, especially in the above subgroups, is urgently warranted. FUNDING: None.

Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach.

BACKGROUND: Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases. METHODS: The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level. RESULTS: Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses. CONCLUSIONS: Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Microbiome in the nasopharynx: Insights into the impact of COVID-19 severity.

Background: The respiratory tract harbors a variety of microbiota, whose composition and abundance depend on specific site factors, interaction with external factors, and disease. The aim of this study was to investigate the relationship between COVID-19 severity and the nasopharyngeal microbiome. Methods: We conducted a prospective cohort study in Mexico City, collecting nasopharyngeal swabs from 30 COVID-19 patients and 14 healthy volunteers. Microbiome profiling was performed using 16S rRNA gene analysis. Taxonomic assignment, classification, diversity analysis, core microbiome analysis, and statistical analysis were conducted using R packages. Results: The microbiome data analysis revealed taxonomic shifts within the nasopharyngeal microbiome in severe COVID-19. Particularly, we observed a significant reduction in the relative abundance of Lawsonella and Cutibacterium genera in critically ill COVID-19 patients (p < 0.001). In contrast, these patients exhibited a marked enrichment of Streptococcus, Actinomyces, Peptostreptococcus, Atopobium, Granulicatella, Mogibacterium, Veillonella, Prevotella_7, Rothia, Gemella, Alloprevotella, and Solobacterium genera (p < 0.01). Analysis of the core microbiome across all samples consistently identified the presence of Staphylococcus, Corynebacterium, and Streptococcus. Conclusions: Our study suggests that the disruption of physicochemical conditions and barriers resulting from inflammatory processes and the intubation procedure in critically ill COVID-19 patients may facilitate the colonization and invasion of the nasopharynx by oral microorganisms.

The rs11684747 and rs55790676 SNPs of ADAM17 influence tuberculosis susceptibility and plasma levels of TNF, TNFR1, and TNFR2.

Introduction: The proteolytic activity of A Disintegrin and Metalloproteinase 17 (ADAM17) regulates the release of tumor necrosis factor (TNF) and TNF receptors (TNFRs) from cell surfaces. These molecules play important roles in tuberculosis (TB) shaping innate immune reactions and granuloma formation. Methods: Here, we investigated whether single nucleotide polymorphisms (SNPs) of ADAM17 influence TNF and TNFRs levels in 224 patients with active TB (ATB) and 118 healthy close contacts. Also, we looked for significant associations between SNPs of ADAM17 and ATB status. TNF, TNFR1, and TNFR2 levels were measured in plasma samples by ELISA. Four SNPs of ADAM17 (rs12692386, rs1524668, rs11684747, and rs55790676) were analyzed in DNA isolated from peripheral blood leucocytes. The association between ATB status, genotype, and cytokines was analyzed by multiple regression models. Results: Our results showed a higher frequency of rs11684747 and rs55790676 in close contacts than ATB patients. Coincidentally, heterozygous to these SNPs of ADAM17 showed higher plasma levels of TNF compared to homozygous to their respective ancestral alleles. Strikingly, the levels of TNF and TNFRs distinguished participant groups, with ATB patients displaying lower TNF and higher TNFR1/TNFR2 levels compared to their close contacts. Conclusion: These findings suggest a role for SNPs of ADAM17 in genetic susceptibility to ATB.

Complete Genome Sequencing, Annotation, and Mutational Profiling of the Novel Clade I Human Mpox Virus, Kamituga Strain.

INTRODUCTION: Human Mpox (formerly monkeypox) infection is an emerging zoonotic disease caused by the Mpox virus (MPXV). We describe the complete genome annotation, phylogeny, and mutational profile of a novel, sustained Clade I Mpox outbreak in the city of Kamituga in Eastern Democratic Republic of the Congo (DRC). METHODOLOGY: A cross-sectional, observational, cohort study was performed among patients of all ages admitted to the Kamituga Hospital with Mpox infection symptoms between late September 2023 and late January 2024. DNA was isolated from Mpox swabbed lesions and sequenced followed by phylogenetic analysis, genome annotation, and mutational profiling. RESULTS: We describe an ongoing Clade I Mpox outbreak in the city of Kamituga, South Kivu Province, Democratic Republic of Congo. Whole-genome sequencing of the viral RNA samples revealed, on average, 201.5 snps, 28 insertions, 81 deletions, 2 indels, 312.5 total variants, 158.3 amino acid changes, 81.66 intergenic variants, 72.16 synonymous mutations, 106 missense variants, 41.16 frameshift variants, and 3.33 inframe deletions across six samples. By assigning mutations at the proteome level for Kamituga MPXV sequences, we observed that seven proteins, namely, C9L (OPG047), I4L (OPG080), L6R (OPG105), A17L (OPG143), A25R (OPG151), A28L (OPG153), and B21R (OPG210) have emerged as hot spot mutations based on the consensuses inframe deletions, frameshift variants, synonymous variants, and amino acids substitutions. Based on the outcome of the annotation, we found a deletion of the D14L (OPG032) gene in all six samples. Following phylogenetic analysis and whole genome assembly, we determined that this cluster of Mpox infections is genetically distinct from previously reported Clade I outbreaks, and thus propose that the Kamituga Mpox outbreak represents a novel subgroup (subgroup VI) of Clade I MPXV. CONCLUSIONS: Here we report the complete viral genome for the ongoing Clade I Mpox Kamituga outbreak for the first time. This outbreak presents a distinct mutational profile from previously sequenced Clade I MPXV oubtreaks, suggesting that this cluster of infections is a novel subgroup (we term this subgroup VI). These findings underscore the need for ongoing vigilance and continued sequencing of novel Mpox threats in endemic regions.

PASC (Post Acute Sequelae of COVID-19) is associated with decreased neutralizing antibody titers in both biological sexes and increased ANG-2 and GM-CSF in females.

Post-acute sequelae of COVID-19 (PASC) or the continuation of COVID-19 (Coronavirus disease 2019) symptoms past 12 weeks may affect as many as 30% of people recovering from a SARS-CoV-2 (severe acute respiratory coronavirus 2) infection. The mechanisms regulating the development of PASC are currently not known; however, hypotheses include virus reservoirs, pre-existing conditions, microblood clots, immune dysregulation, as well as poor antibody responses. Importantly, virus neutralizing antibodies are essential for COVID-19 recovery and protection from reinfection but there is currently limited information on these immune regulators and associated cytokines in PASC patients. Understanding the key drivers of general and specific symptoms associated with Long COVID and the presence of virus neutralizing antibodies in PASC will aid in the development of therapeutics, diagnostics, and vaccines which currently do not exist. We designed a cross-sectional study to investigate systemic antibody and cytokine responses during COVID-19 recovery and PASC. In total, 195 participants were recruited in one of four groups: (1) Those who never had COVID-19 (No COVID); (2) Those in acute COVID-19 recovery (Acute Recovery) (4-12 weeks post infection); (3) Those who recovered from COVID-19 (Recovered) (+ 12 weeks from infection); and (4) those who had PASC (PASC) (+ 12 weeks from infection). Participants completed a questionnaire on health history, sex, gender, demographics, experiences with COVID-19 acute and COVID-19 recovery/continuing symptoms. Serum samples collected were evaluated for antibody binding to viral proteins, virus neutralizing antibody titers, and serum cytokine levels using Ella SimplePlex Immunoassay™ panels. We found participants with PASC reported more pre-existing conditions (e.g. such as hypertension, asthma, and obesity), and PASC symptoms (e.g. fatigue, brain fog, headaches, and shortness of breath) following COVID-19 than COVID-19 Recovered individuals. Importantly, we found PASC individuals to have significantly decreased levels of neutralizing antibodies toward both SARS-CoV-2 and the Omicron BA.1 variant. Sex analysis indicated that female PASC study participants had sustained antibody levels as well as levels of the inflammatory cytokines GM-CSF and ANG-2 over time following COVID-19. Our study reports people experiencing PASC had lower levels of virus neutralizing antibodies; however, the results are limited by the collection time post-COVID-19 and post-vaccination. Moreover, we found females experiencing PASC had sustained levels of GM-CSF and ANG-2. With lower levels of virus neutralizing antibodies, this data suggests that PASC individuals not only have had a suboptimal antibody response during acute SARS-CoV-2 infection but may also have increased susceptibility to subsequent infections which may exacerbate or prolong current PASC illnesses. We also provide evidence suggesting GM-CSF and ANG-2 to play a role in the sex-bias of PASC. Taken together, our findings maybe important for understanding immune molecular drivers of PASC and PASC subgroups.

Mortality Rate and Acute Kidney Injury Prevalence Reduction in COVID-19 Critical Patients Treated with Hemoperfusion.

Introduction: Coronavirus disease 2019 (COVID-19) induces organic damage mainly through the patient's immune overreaction. Hemoperfusion (HPF) can remove inflammatory cytokines and can reduce the negative effects of cytokine storm in COVID-19. We compared the mortality rate, inflammatory response, and acute kidney injury (AKI) prevalence among patients suffering from respiratory insufficiency secondary to COVID-19 treated with and without HPF with HA330 cartridge. Methods: Mortality rate, serum creatinine, and ferritin values were compared between patients suffering from respiratory insufficiency secondary to COVID-19 who received conventional treatment and another group of patients who additionally received four sessions of HPF with HA330. Results: Of 116 patients suffering from acute respiratory insufficiency secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), one group (n: 84) received support treatment and the other group (n: 32) additionally received HPF with HA330 cartridge. Both groups had no renal disease and similar age and comorbidities at admission, except for obesity and mechanical ventilation requirement, which were significantly higher in the HPF group. Mortality rate (61% vs. 31%, P: 0.008), serum creatinine (1.4 vs. 0.5 mg/dl, P < 0.001), and post-HPF serum ferritin (2868 vs. 1675, P < 0.001) were significantly lower in the HPF group. Conclusion: Mortality rate, serum ferritin, and AKI were significantly reduced in critical COVID-19 patients who received HPF with HA330 cartridge than in those who did not receive it. These results were obtained despite the HPF group risk factors, such as obesity and mechanical ventilation, worsening its prognosis.

Urinary metabolomic profiling of a cohort of Colombian patients with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune and multisystem disease with a high public health impact. Lupus nephritis (LN), commonly known as renal involvement in SLE, is associated with a poorer prognosis and increased rates of morbidity and mortality in patients with SLE. Identifying new urinary biomarkers that can be used for LN prognosis or diagnosis is essential and is part of current active research. In this study, we applied an untargeted metabolomics approach involving liquid and gas chromatography coupled with mass spectrometry to urine samples collected from 17 individuals with SLE and no kidney damage, 23 individuals with LN, and 10 clinically healthy controls (HCs) to identify differential metabolic profiles for SLE and LN. The data analysis revealed a differentially abundant metabolite expression profile for each study group, and those metabolites may act as potential differential biomarkers of SLE and LN. The differential metabolic pathways found between the LN and SLE patients with no kidney involvement included primary bile acid biosynthesis, branched-chain amino acid synthesis and degradation, pantothenate and coenzyme A biosynthesis, lysine degradation, and tryptophan metabolism. Receiver operating characteristic curve analysis revealed that monopalmitin, glycolic acid, and glutamic acid allowed for the differentiation of individuals with SLE and no kidney involvement and individuals with LN considering high confidence levels. While the results offer promise, it is important to recognize the significant influence of medications and other external factors on metabolomics studies. This impact has the potential to obscure differences in metabolic profiles, presenting a considerable challenge in the identification of disease biomarkers. Therefore, experimental validation should be conducted with a larger sample size to explore the diagnostic potential of the metabolites found as well as to examine how treatment and disease activity influence the identified chemical compounds. This will be crucial for refining the accuracy and effectiveness of using urine metabolomics for diagnosing and monitoring lupus and lupus nephritis.

The impact of public transportation on the transmission of COVID-19 in Rwanda.

Introduction: The onset of the COVID-19 pandemic has placed a significant burden on healthcare systems worldwide, particularly in sub-Saharan regions where healthcare resources are limited. The transmission of SARS-CoV-2 is facilitated by the movement of people from place to place. Therefore, implementing measures that restrict movement of people and contacts is crucial in controlling the spread of the disease. Following the identification of the first COVID-19 case in Rwanda, the government implemented stringent measures, including a complete nationwide lockdown, border closures, curfews, reduced capacity in public transportation and businesses, and mandatory testing. This study aims to assess epidemiological trends in COVID-19 cases in relation to changes in population mobility within the public transportation system. Methods: A descriptive analysis using publicly available data on COVID-19 epidemiological indicators (cases, deaths, vaccinations, and stringency index) and mobility data was conducted. Results: The results reveal a strong correlation between mobility in public transportation and other activities, underscoring Rwanda's reliance on its public transportation system. The study also identifies a pattern where increases in transit station mobility preceded spikes in COVID-19 cases, suggesting that the subsequent rise in public transportation usage may contribute to higher infection rates. Discussion: Therefore, this study emphasizes the importance of ongoing vigilance and regulatory measures regarding public transportation during infectious disease outbreaks.

Surface-enhanced Raman Spectroscopy in urinalysis of hypertension patients with kidney disease.

Arterial hypertension (AH) is a multifactorial and asymptomatic disease that affects vital organs such as the kidneys and heart. Considering its prevalence and the associated severe health repercussions, hypertension has become a disease of great relevance for public health across the globe. Conventionally, the classification of an individual as hypertensive or non-hypertensive is conducted through ambulatory blood pressure monitoring over a 24-h period. Although this method provides a reliable diagnosis, it has notable limitations, such as additional costs, intolerance experienced by some patients, and interferences derived from physical activities. Moreover, some patients with significant renal impairment may not present proteinuria. Accordingly, alternative methodologies are applied for the classification of individuals as hypertensive or non-hypertensive, such as the detection of metabolites in urine samples through liquid chromatography or mass spectrometry. However, the high cost of these techniques limits their applicability for clinical use. Consequently, an alternative methodology was developed for the detection of molecular patterns in urine collected from hypertension patients. This study generated a direct discrimination model for hypertensive and non-hypertensive individuals through the amplification of Raman signals in urine samples based on gold nanoparticles and supported by chemometric techniques such as partial least squares-discriminant analysis (PLS-DA). Specifically, 162 patient urine samples were used to create a PLS-DA model. These samples included 87 urine samples from patients diagnosed with hypertension and 75 samples from non-hypertensive volunteers. In the AH group, 35 patients were diagnosed with kidney damage and were further classified into a subgroup termed (RAH). The PLS-DA model with 4 latent variables (LV) was used to classify the hypertensive patients with external validation prediction (P) sensitivity of 86.4%, P specificity of 77.8%, and P accuracy of 82.5%. This study demonstrates the ability of surface-enhanced Raman spectroscopy to differentiate between hypertensive and non-hypertensive patients through urine samples, representing a significant advance in the detection and management of AH. Additionally, the same model was then used to discriminate only patients diagnosed with renal damage and controls with a P sensitivity of 100%, P specificity of 77.8%, and P accuracy of 82.5%.

Alactic base excess (ABE): a novel internal milieu parameter-its concept and clinical importance.

Inspired by the Stewart-Figge acid-base approach, Gattinoni et al. recently introduced a new internal milieu parameter known as alactic base excess (ABE). The authors defined ABE as the sum of lactate and standard base excess. In the context of sepsis, ABE has been proposed as a valuable marker to discern between metabolic acidosis resulting from the accumulation of lactate and the retention of fixed acids, which can occur in cases of renal failure. Multiple studies have demonstrated that a negative ABE value (<-3 mmol/L) represents an early marker of renal dysfunction, and significantly correlates with higher mortality rates in septic patients. In conclusion, ABE is a simple and useful parameter that can be used to better interpret a patient's acid-base status, assess renal function, and general prognosis in sepsis. By incorporating ABE into clinical practice, healthcare professionals can enhance their understanding of the complex acid-base imbalances in their patients and tailor more individualized, effective treatment plans.

Atypical Hemolytic Uremic Syndrome: A Nationwide Colombian Pediatric Series.

Objectives. Atypical hemolytic uremic syndrome (aHUS) is a rare complement-mediated kidney disease with genetic predisposition and represents up to 10% of pediatric hemolytic uremic syndrome (HUS) cases. Few studies have evaluated aHUS in Latin American population. We studied a Colombian pediatric cohort to delineate disease presentation and outcomes. Methods. A multicenter cohort of 27 Colombian children with aHUS were included. Patients were grouped by age at onset. Clinical features were compared using analysis of variance (ANOVA) and Fisher exact tests. Renal biopsy was performed on 6 patients who were suspected of having other renal diseases before aHUS diagnosis. Results. Most patients were male (70%). The onset of aHUS occurred frequently before age 4 years (60%) and followed gastroenteritis as the main triggering event (52%). Age groups showed comparable clinical presentation, disease severity, treatment, and outcomes. Pulmonary involvement (67%) was the main extrarenal manifestation, particularly in the 1 to 7 age group (P = .01). Renal biopsies were as follows: 3 had membranoproliferative glomerulonephritis (MPGN) type I, one MPGN type III, one C3-glomerulonephritis, and one rapidly progressive GN. Genetic screening was available in 6 patients and identified 2xCFHR5, 2xMCP, 1xADAMTS13/THBD, and 1xDGKE mutations. A total of 15 relapses were seen, of which 8 (72%) occurred in the 1 to 7 age group. The renal outcome was not significantly different regardless of age group. Conclusion. In our cohort, we observed a relatively high frequency of extrarenal involvement at first presentation represented by pulmonary manifestations. The renal prognosis at initial presentation was worse than in previous reports.

Pregnancy-Associated Atypical Hemolytic Uremic Syndrome: A Case Report with MCP Gene Mutation and Successful Eculizumab Treatment.

Pregnancy-associated atypical hemolytic uremic syndrome (P-aHUS) is a rare condition characterized by microangiopathic hemolytic anemia and kidney injury from thrombotic microangiopathy. P-aHUS occurs in approximately 1 in 25,000 pregnancies and is strongly related to complement dysregulation and pregnancy-related disorders, such as preeclampsia, eclampsia, and hemolysis, elevated liver enzymes, low platelet (HELLP) syndrome, resulting in adverse perinatal and fetal outcomes. Complement dysregulation in P-aHUS is commonly attributed to genetic mutations or autoantibodies affecting complement factors, including CFH , CFI , and MCP. We present a case of a 25-year-old primigravida who experienced severe preeclampsia and HELLP syndrome followed by the development of complicated P-aHUS during the early postpartum period. The patient exhibited severe clinical manifestations, including hypertensive emergency, central nervous system involvement, renal impairment, and microangiopathic hemolytic anemia. Timely initiation of eculizumab therapy resulted in successful disease remission. Further genetic analysis revealed a likely rare pathogenic MCP gene variant.

CDBProm: the Comprehensive Directory of Bacterial Promoters.

The decreasing cost of whole genome sequencing has produced high volumes of genomic information that require annotation. The experimental identification of promoter sequences, pivotal for regulating gene expression, is a laborious and cost-prohibitive task. To expedite this, we introduce the Comprehensive Directory of Bacterial Promoters (CDBProm), a directory of in-silico predicted bacterial promoter sequences. We first identified that an Extreme Gradient Boosting (XGBoost) algorithm would distinguish promoters from random downstream regions with an accuracy of 87%. To capture distinctive promoter signals, we generated a second XGBoost classifier trained on the instances misclassified in our first classifier. The predictor of CDBProm is then fed with over 55 million upstream regions from more than 6000 bacterial genomes. Upon finding potential promoter sequences in upstream regions, each promoter is mapped to the genomic data of the organism, linking the predicted promoter with its coding DNA sequence, and identifying the function of the gene regulated by the promoter. The collection of bacterial promoters available in CDBProm enables the quantitative analysis of a plethora of bacterial promoters. Our collection with over 24 million promoters is publicly available at https://aw.iimas.unam.mx/cdbprom/.

PoxiPred: An Artificial-Intelligence-Based Method for the Prediction of Potential Antigens and Epitopes to Accelerate Vaccine Development Efforts against Poxviruses.

Poxviridae is a family of large, complex, enveloped, and double-stranded DNA viruses. The members of this family are ubiquitous and well known to cause contagious diseases in humans and other types of animals as well. Taxonomically, the poxviridae family is classified into two subfamilies, namely Chordopoxvirinae (affecting vertebrates) and Entomopoxvirinae (affecting insects). The members of the Chordopoxvirinae subfamily are further divided into 18 genera based on the genome architecture and evolutionary relationship. Of these 18 genera, four genera, namely Molluscipoxvirus, Orthopoxvirus, Parapoxvirus, and Yatapoxvirus, are known for infecting humans. Some of the popular members of poxviridae are variola virus, vaccine virus, Mpox (formerly known as monkeypox), cowpox, etc. There is still a pressing demand for the development of effective vaccines against poxviruses. Integrated immunoinformatics and artificial-intelligence (AI)-based methods have emerged as important approaches to design multi-epitope vaccines against contagious emerging infectious diseases. Despite significant progress in immunoinformatics and AI-based techniques, limited methods are available to predict the epitopes. In this study, we have proposed a unique method to predict the potential antigens and T-cell epitopes for multiple poxviruses. With PoxiPred, we developed an AI-based tool that was trained and tested with the antigens and epitopes of poxviruses. Our tool was able to locate 3191 antigen proteins from 25 distinct poxviruses. From these antigenic proteins, PoxiPred redundantly located up to five epitopes per protein, resulting in 16,817 potential T-cell epitopes which were mostly (i.e., 92%) predicted as being reactive to CD8+ T-cells. PoxiPred is able to, on a single run, identify antigens and T-cell epitopes for poxviruses with one single input, i.e., the proteome file of any poxvirus.

MLDSPP: Bacterial Promoter Prediction Tool Using DNA Structural Properties with Machine Learning and Explainable AI.

Bacterial promoters play a crucial role in gene expression by serving as docking sites for the transcription initiation machinery. However, accurately identifying promoter regions in bacterial genomes remains a challenge due to their diverse architecture and variations. In this study, we propose MLDSPP (Machine Learning and Duplex Stability based Promoter prediction in Prokaryotes), a machine learning-based promoter prediction tool, to comprehensively screen bacterial promoter regions in 12 diverse genomes. We leveraged biologically relevant and informative DNA structural properties, such as DNA duplex stability and base stacking, and state-of-the-art machine learning (ML) strategies to gain insights into promoter characteristics. We evaluated several machine learning models, including Support Vector Machines, Random Forests, and XGBoost, and assessed their performance using accuracy, precision, recall, specificity, F1 score, and MCC metrics. Our findings reveal that XGBoost outperformed other models and current state-of-the-art promoter prediction tools, namely Sigma70pred and iPromoter2L, achieving F1-scores >95% in most systems. Significantly, the use of one-hot encoding for representing nucleotide sequences complements these structural features, enhancing our XGBoost model's predictive capabilities. To address the challenge of model interpretability, we incorporated explainable AI techniques using Shapley values. This enhancement allows for a better understanding and interpretation of the predictions of our model. In conclusion, our study presents MLDSPP as a novel, generic tool for predicting promoter regions in bacteria, utilizing original downstream sequences as nonpromoter controls. This tool has the potential to significantly advance the field of bacterial genomics and contribute to our understanding of gene regulation in diverse bacterial systems.

Hyponatremia and malnutrition: a comprehensive review.

BACKGROUND: Hyponatremia (serum sodium lower than 135 mmol/L) is the most frequent electrolyte alteration diagnosed in medical practice. It has deleterious clinical effects, being an independent predictor of mortality. Malnutrition encompasses pathological states caused by both nutrients excess and deficiency, being frequently documented in chronic kidney disease patients. In addition, chronic hyponatremia promotes adiposity loss and sarcopenia, while malnutrition can induce hyponatremia. This pathological interaction is mediated by four main mechanisms: altered electrolyte body composition (low sodium, low potassium, low phosphorus, or high-water body content), systemic inflammation (cytokines increase), hormonal mechanisms (renin-angiotensin-aldosterone system activation, vasopressin release), and anorexia (primary or secondary). CONCLUSION: Malnutrition can induce hyponatremia through hydro-electrolytic, hormonal, inflammatory, or nutritional behavior changes; while hyponatremia per se can induce malnutrition, so there is a pathophysiological feedback between both conditions.

Obesity and glomerular filtration rate.

Obesity has received considerable attention in general medicine and nephrology over the last few years. This condition increases the risk of metabolic syndrome, diabetes mellitus, hypertension, and dyslipidemia, which are the main risk factors for developing chronic kidney disease (CKD). Kidney damage caused by obesity can be explained by many mechanisms, such as sympathetic nervous and renin-angiotensin-aldosterone systems activation, mechanical stress, hormonal unbalance, as well as inflammatory cytokines production. Even though creatinine-based glomerular filtration rate (GFR) equations in obese individuals have been validated (Salazar-Corcoran and CKD-MCQ), changes in body weight after bariatric surgery (BS) leads to changes in creatininemia, affecting its reliability. Thus, an average between creatine and cystatin-based GFR equations would be more appropriate in this setting. Bariatric surgery can reverse diabetes mellitus and improve hypertension, which are the main causes of CKD. Conclusion: GFR can be affected by obesity and BS, and its value should be cautiously evaluated in this setting.