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Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986–0.995), with sensitivity of 0.978 (0.963–0.992) and specificity of 0.920 (0.890–0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952–0.977), with sensitivity of 0.993(0.984–1.000) and specificity of 0.851 (0.815–0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800–0.858), with sensitivity of 0.738 (0.695–0.781) and specificity of 0.781 (0.735–0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788–0.874), with sensitivity of 0.765 (0.697–0.832) and specificity of 0.817 (0.770–0.865).

Several epidemiological studies in diabetic patients have demonstrated a protective effect of metformin to the development of several types of cancer. The underlying mechanisms of such phenomenon is related to the effect of metformin on cell proliferation among which, mTOR, AMPK and other targets have been identified. However, little is known about the role that metformin treatment have on other cell types such as keratinocytes and whether exposure to metformin of these cells might have serious repercussions in wound healing delay and in the development of complications in diabetic patients with foot ulcers or in their exacerbation. HaCaT Cells were exposed to various concentrations of metformin and cell viability was evaluated by a Resazurin assay; Proliferation was also evaluated with a colony formation assay and with CFSE dilution assay by flow cytometry. Cell cycle was also evaluated by flow cytometry by PI staining. An animal model of wound healing was used to evaluate the effect of metformin in wound closure. Also, an analysis of patients receiving metformin treatment was performed to determine the effect of metformin treatment on the outcome and wound area. Statistical analysis was performed on SPSS v. 18 and GraphPad software v.5. Metformin treatment significantly reduces cell proliferation; colony formation and alterations of the cell cycle are observed also in the metformin treated cells, particularly in the S phase. There is a significant increase in the area of the wound of the metformin treated animals at different time points (P<0.05). There is also a significant increase in the size and wound area of the patients with diabetic foot ulcers at the time of hospitalization. A protective effect of metformin was observed for amputation, probably associated with the anti inflammatory effects reported of metformin. Metformin treatment reduces cell proliferation and reduces wound healing in an animal model and affects clinical outcomes in diabetic foot ulcer patients. Chronic use of this drug should be further investigated to provide evidence of their security in association with DFU.

Tuberculosis is an ongoing threat to global health, especially with the emergence of multi drug-resistant (MDR) and extremely drug-resistant strains that are motivating the search for new treatment strategies. One potential strategy is immunotherapy using Innate Defence Regulator (IDR) peptides that selectively modulate innate immunity, enhancing chemokine induction and cell recruitment while suppressing potentially harmful inflammatory responses. IDR peptides possess only modest antimicrobial activity but have profound immunomodulatory functions that appear to be influential in resolving animal model infections. The IDR peptides HH2, 1018 and 1002 were tested for their activity against two M. tuberculosis strains, one drug-sensitive and the other MDR in both in vitro and in vivo models. All peptides showed no cytotoxic activity and only modest direct antimicrobial activity versus M. tuberculosis (MIC of 15-30 µg/ml). Nevertheless peptides HH2 and 1018 reduced bacillary loads in animal models with both the virulent drug susceptible H37Rv strain and an MDR isolate and, especially 1018 led to a considerable reduction in lung inflammation as revealed by decreased pneumonia. These results indicate that IDR peptides have potential as a novel immunotherapy against TB.

Understanding and monitoring the demographics of SARS-CoV-2 infection can inform strategies for prevention. Surveillance monitoring has suggested that the age distribution of people infected with SARS-CoV-2 has changed since the pandemic began, but no formal analysis has been performed. Retrospective review of SARS-CoV-2 molecular testing results from a national reference laboratory was performed. Result distributions by age and positivity were compared between early period (March-April 2020) and late periods (June-July 2020) of the COVID-19 pandemic. Additionally, a sub-analysis compared changing age distributions between inpatients and outpatients. There were 277,601 test results of which 19320 (7.0%) were positive. The median age of infected people declined over time (p < 0.0005). In March-April, the median age of positive people was 40.8 years (Interquartile range (IQR): 29.0-54.1). In June-July, the median age of positive people was 35.8 years (IQR: 24.0-50.2). The positivity rate of patients under 50 increased from 6.0 to 10.6 percent and the positivity rate for those over 50 decreased from 6.3 to 5.0 percent between the early and late periods. The trend was only observed for outpatient populations. We confirm that there is a trend toward decreasing age among persons with laboratory-confirmed SARS-CoV-2 infection, but that these trends seem to be specific to the outpatient population. Overall, this suggests that observed age-related trends are driven by changes in testing patterns rather than true changes in the epidemiology of SARS-CoV-2 infection. This calls for caution in interpretation of routine surveillance data until testing patterns stabilize.

The MERS-CoV, SARS-CoV, and SARS-CoV-2 are highly pathogenic viruses that can cause severe pneumonic diseases in humans. Unfortunately, there is a non-available effective treatment to combat these viruses. Domain-motif interactions (DMIs) are an essential means by which viruses mimic and hijack the biological processes of host cells. To disentangle how viruses achieve this process can help to develop new rational therapies. Data mining was performed to obtain DMIs stored as regular expressions (regexp) in 3DID and ELM databases. The mined regexp information was mapped on the coronaviruses’ proteomes. Most motifs on viral protein that could interact with human proteins are shared across the coronavirus species, indicating that molecular mimicry is a common strategy for coronavirus infection. Enrichment ontology analysis for protein domains showed a shared biological process and molecular function terms related to carbon source utilization and potassium channel regulation. Some of the mapped motifs were nested on B, and T cell epitopes, suggesting that it could be as an alternative way for reverse vaccinology. The information obtained in this study could be used for further theoretic and experimental explorations on coronavirus infection mechanism and development of medicines for treatment.

Adoptive cell therapy has emerged as a promising approach for treating advanced solid malignancies. Genetic engineering techniques represent an exciting area of research for the development of cellular products with enhanced cytotoxicity, phenotype, and metabolism.

Genomics has significantly revolutionized pathogen surveillance, particularly in epidemiological studies, the detection of drug-resistant strains, and disease control. Despite its potential, the representation of Latin American countries in the genomic catalogues of Mycobacterium tuberculosis (Mtb) , the bacteria responsible for Tuberculosis (TB), remains limited. In this study, we present a whole genome sequencing (WGS)-based analysis of 85 Mtb clinical strains from 17 Mexican states, providing insights into local adaptations and drug resistance signatures in the region. Our results reveal that the Euro-American lineage (L4) accounts for 94% of our dataset, showing 4.1.2.1 (Haarlem, n = 32), and 4.1.1.3 (X-type, n = 34) sublineages as the most prevalent. We report the presence of the 4.1.1.3 sublineage, which is endemic to Mexico, in six additional locations beyond previous reports. Phenotypic drug resistance tests showed that 34 out of 85 Mtb samples were resistant, exhibiting a variety of resistance profiles to the first-line antibiotics tested. We observed high levels of discrepancy between phenotype and genotype associated with drug resistance in our dataset, including pyrazinamide-monoresistant Mtb strains lacking canonical variants of drug resistance. Expanding the Latin American Mtb genome databases will enhance our understanding of TB epidemiology and potentially provide new avenues for controlling the disease in the region.

This research was funded by the project (Proyecto de Invercion) “Mejoramiento de los servicios de investigación y transferencia tecnológica agraria en cultivos frutícolas en los 24 departamentos del Perú” of the Ministry of Agrarian Development and Irrigation (MIDAGRI) of the Peruvian Government with grant number CUI 2532404.

Cancers are caused by genomic alterations known as drivers. Hundreds of drivers in coding genes are known but, to date, only a handful of noncoding drivers have been discovered—despite intensive searching 1 , 2 . Attention has recently shifted to the role of altered RNA splicing in cancer; driver mutations that lead to transcriptome-wide aberrant splicing have been identified in multiple types of cancer, although these mutations have only been found in protein-coding splicing factors such as splicing factor 3b subunit 1 ( SF3B1 ) 3 – 6 . By contrast, cancer-related alterations in the noncoding component of the spliceosome—a series of small nuclear RNAs (snRNAs)—have barely been studied, owing to the combined challenges of characterizing noncoding cancer drivers and the repetitive nature of snRNA genes 1 , 7 , 8 . Here we report a highly recurrent A>C somatic mutation at the third base of U1 snRNA in several types of tumour. The primary function of U1 snRNA is to recognize the 5′ splice site via base-pairing. This mutation changes the preferential A–U base-pairing between U1 snRNA and the 5′ splice site to C–G base-pairing, and thus creates novel splice junctions and alters the splicing pattern of multiple genes—including known drivers of cancer. Clinically, the A>C mutation is associated with heavy alcohol use in patients with hepatocellular carcinoma, and with the aggressive subtype of chronic lymphocytic leukaemia with unmutated immunoglobulin heavy-chain variable regions. The mutation in U1 snRNA also independently confers an adverse prognosis to patients with chronic lymphocytic leukaemia. Our study demonstrates a noncoding driver in spliceosomal RNAs, reveals a mechanism of aberrant splicing in cancer and may represent a new target for treatment. Our findings also suggest that driver discovery should be extended to a wider range of genomic regions. A highly recurrent A>C somatic mutation in U1 small nuclear RNA, which alters the splicing pattern of genes that include known drivers of cancer, is identified in several types of tumour.

Research exploring the development and outcome of COVID-19 infections has led to the need to find better diagnostic and prognostic biomarkers. This cross-sectional study used targeted metabolomics to identify potential COVID-19 biomarkers that predicted the course of the illness by assessing 110 endogenous plasma metabolites from individuals admitted to a local hospital for diagnosis/treatment. Patients were classified into four groups (≈ 40 each) according to standard polymerase chain reaction (PCR) COVID-19 testing and disease course: PCR−/controls (i.e., non-COVID controls), PCR+/not-hospitalized, PCR+/hospitalized, and PCR+/intubated. Blood samples were collected within 2 days of admission/PCR testing. Metabolite concentration data, demographic data and clinical data were used to propose biomarkers and develop optimal regression models for the diagnosis and prognosis of COVID-19. The area under the receiver operating characteristic curve (AUC; 95% CI) was used to assess each models’ predictive value. A panel that included the kynurenine: tryptophan ratio, lysoPC a C26:0, and pyruvic acid discriminated non-COVID controls from PCR+/not-hospitalized (AUC = 0.947; 95% CI 0.931–0.962). A second panel consisting of C10:2, butyric acid, and pyruvic acid distinguished PCR+/not-hospitalized from PCR+/hospitalized and PCR+/intubated (AUC = 0.975; 95% CI 0.968–0.983). Only lysoPC a C28:0 differentiated PCR+/hospitalized from PCR+/intubated patients (AUC = 0.770; 95% CI 0.736–0.803). If additional studies with targeted metabolomics confirm the diagnostic value of these plasma biomarkers, such panels could eventually be of clinical use in medical practice.