[Vitamin D and polymorphisms of VDR and GC genes in the severity and mortality from COVID-19. A systematic review]. / Vitamina D y polimorfismos de los genes VDR y GC en la severidad y mortalidad por COVID-19. Una revisión sistemática.

Previous studies have pointed to a possible relationship between vitamin D deficiency and the severity of the disease promoted by SARS-CoV-2, reducing respiratory and cardiovascular complications caused by a hyperreaction of the immune system known as "cytokine storm". This vitamin exerts multiple functions that depend on the presence and levels of different proteins, such as the vitamin D receptor (VDR) and the vitamin D binding protein (DBP), and the existence of single nucleotide polymorphisms (SNPs) of the genes that encode these proteins. The objective of this review is to assess whether some VDR and GC SNPs are risk factors for the most severe forms of COVID-19 disease and whether they condition the response to vitamin D supplementation. A search was performed in PubMed, Google Scholar and Scielo, finding that genotypes in patients affected by COVID-19, were rarely performed, although some studies find a relationship between different alleles and the severity of the disease. The ApaI polymorphism of the VDR gene stands out, as the minor allele "a" increases the risk of mortality from COVID-19 (OR = 11.828, CI: 2,493-56,104, p = 0.002). Results divergency in the efficacy of vitamin D supplementation suggest the need for a larger number of studies. In conclusion, the study of VDR and GC polymorphisms seems essential to effectively treat vitamin D deficiency and particularly to protect against COVID-19. Well-designed studies are needed to elucidate whether plasma vitamin D levels play a role of casuality or causality.

Government strategies in confronting COVID-19 in the republic of Cuba.

BACKGROUND: In Cuba, the first cases of coronavirus 2019 (COVID-19) were confirmed on March 11, 2020, when the World Health Organization (WHO) officially declared the pandemic and the Ministry of Public Health of Cuba (MINSAP) began to execute the COVID-19 Prevention and Control Plan. This plan was prepared two months earlier by MINSAP working together with the National Civil Defense and the government approved it at the end of January. OBJECTIVE: The aim of this research is to assess the effectiveness of the government strategies to deal with COVID-19, by analyzing the role of the different agencies involved in the pandemic management. METHODS: A bibliographical review of the following documents was conducted: information issued by MINSAP and other ministries, archives of the Pedro Kouri Institute (IPK) and Cuban journals regarding the high impact in the field of medicine. The data were processed with different tools (diagrams, bar graphs, analysis and synthesis, etc.) that allowed measuring the effectiveness of the strategies implemented. RESULTS: The government's strategies focused on: the integration of all state agencies and some private institutions to confront COVID-19; the collaboration between MINSAP specialists, country's research centers and universities for the creation of vaccines to contain the pandemic; the production of medical equipment and instruments; the design of the organization processes of the services, such as planning techniques and distribution of ambulances, allocation of hospitals and isolation centers for sufferers and direct contacts respectively. CONCLUSION: The analysis carried out showed that the interrelations between the different organizations involved had positive influences on the treatment of the pandemic.

Preoperative risk assessment and spirometry is a cost-effective strategy to reduce post-operative complications and mortality in Mexico.

AIM: Combining preoperative spirometry with the Assess Respiratory Risk in Surgical Patients in Catalunia (ARISCAT) risk scale can reduce post-operative complications and improve patient survival. This study aimed to assess the cost-effectiveness of performing spirometry or not in conjunction with the ARISCAT scale, to reduce post-operative complications and improve survival among adult patients undergoing elective surgery in Mexico. METHODS: A cost-effectiveness analysis (CEA) was performed to compare the specific cost and health outcomes associated with the combined use of the ARISCAT scale and preoperative spirometry (Group 1), and the use of the ARISCAT scale without preoperative spirometry (Group 2). The health outcomes evaluated were post-operative complications and survival. The perspective was from the health care provider (Hospital General de México) and direct medical costs were reported in 2019 US dollars. A decision tree with a time horizon of eight months was used for each health outcome and ARISCAT risk level. RESULTS: The combined use of the ARISCAT scale and spirometry is more cost-effective for reducing post-operative complications in the low and moderate-risk levels and is cost-saving in the high-risk level, than use of the ARISCAT scale without spirometry. To improve patient survival, ARISCAT and spirometry are also more cost-effective at the moderate risk level, and cost-saving for high-risk patients, than using the ARISCAT scale alone. CONCLUSIONS: The use of preoperative spirometry among patients with a high ARISCAT risk level was cost-saving, reduced post-operative complications, and improved survival. Our findings indicate an urgent need to implement spirometry as part of preoperative care in Mexico, which is already the standard of care in other countries.

Two short low complexity regions (LCRs) are hallmark sequences of the Delta SARS-CoV-2 variant spike protein.

Low complexity regions (LCRs) are protein sequences formed by a set of compositionally biased residues. LCRs are extremely abundant in cellular proteins and have also been reported in viruses, where they may partake in evasion of the host immune system. Analyses of 28,231 SARS-CoV-2 whole proteomes and of 261,051 spike protein sequences revealed the presence of four extremely conserved LCRs in the spike protein of several SARS-CoV-2 variants. With the exception of Iota, where it is absent, the Spike LCR-1 is present in the signal peptide of 80.57% of the Delta variant sequences, and in other variants of concern and interest. The Spike LCR-2 is highly prevalent (79.87%) in Iota. Two distinctive LCRs are present in the Delta spike protein. The Delta Spike LCR-3 is present in 99.19% of the analyzed sequences, and the Delta Spike LCR-4 in 98.3% of the same set of proteins. These two LCRs are located in the furin cleavage site and HR1 domain, respectively, and may be considered hallmark traits of the Delta variant. The presence of the medically-important point mutations P681R and D950N in these LCRs, combined with the ubiquity of these regions in the highly contagious Delta variant opens the possibility that they may play a role in its rapid spread.

Bacteremia caused by Anaerococcus SPP: Is this an underdiagnosed infection?

The objectives of this study were to report 10 episodes of clinically significant bacteremia caused by species of the genus Anaerococcus isolated between July 2018 and February 2021 from the microbiology laboratory of a tertiary hospital in Granada (Spain). None of the isolates were identified by MALDI-TOF MS, and the definitive species identification was performed by 16 S rRNA gene sequencing. No reference spectra of the Anaerococcus species were present in the MALDI-TOF MS database. Eight isolates were finally identified as A. octavius, one isolate as A. tetradius and the other as A. urinomassiliensis. The majority of these infections were seen in patients aged >70 years. Risk factors for anaerobic infection were observed in eight patients, especially diabetes mellitus, surgery, and the presence of cancer. Fever was present in all patients. Three patients died, but only one death was attributed to the infection. Mean detection time of positive blood cultures was 47.5 h (range 24-92 h). Antimicrobial susceptibility to penicillin, amoxicillin-clavulanate, imipenem, moxifloxacin, clindamycin, metronidazole, and piperacillin-tazobactam was tested using the gradient diffusion technique and EUCAST breakpoints (except for moxifloxacin). No resistance to amoxicillin-clavulanate, metronidazole, imipenem, or piperacillin-tazobactam was detected; however, the majority of isolates were resistant to clindamycin. When MALDI-TOF MS does not provide a correct identification at genus or species level, as in some isolates of Gram-positive anaerobic cocci, microbiologists should perform an additional confirmatory technique, such as gene sequencing analysis, to obtain a definitive diagnosis.

Structural analysis of viral ExoN domains reveals polyphyletic hijacking events.

Nidoviruses and arenaviruses are the only known RNA viruses encoding a 3'-5' exonuclease domain (ExoN). The proofreading activity of the ExoN domain has played a key role in the growth of nidoviral genomes, while in arenaviruses this domain partakes in the suppression of the host innate immune signaling. Sequence and structural homology analyses suggest that these proteins have been hijacked from cellular hosts many times. Analysis of the available nidoviral ExoN sequences reveals a high conservation level comparable to that of the viral RNA-dependent RNA polymerases (RdRp), which are the most conserved viral proteins. Two highly preserved zinc fingers are present in all nidoviral exonucleases, while in the arenaviral protein only one zinc finger can be identified. This is in sharp contrast with the reported lack of zinc fingers in cellular ExoNs, and opens the possibility of therapeutic strategies in the struggle against COVID-19.

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients.

The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach.