Maize is one of the most important crops for human and animal consumption and contains a chemical arsenal essential for survival: flavonoids. Moreover, flavonoids are well known for their beneficial effects on human health. In this review, we decided to organize the information about maize flavonoids into three sections. In the first section, we include updated information about the enzymatic pathway of maize flavonoids. We describe a total of twenty-one genes for the flavonoid pathway of maize. The first three genes participate in the general phenylpropanoid pathway. Four genes are common biosynthetic early genes for flavonoids, and fourteen are specific genes for the flavonoid subgroups, the anthocyanins, and flavone C-glycosides. The second section explains the tissue accumulation and regulation of flavonoids by environmental factors affecting the expression of the MYB-bHLH-WD40 (MBW) transcriptional complex. The study of transcription factors of the MBW complex is fundamental for understanding how the flavonoid profiles generate a palette of colors in the plant tissues. Finally, we also include an update of the biological activities of C3G, the major maize anthocyanin, including anticancer, antidiabetic, and antioxidant effects, among others. This review intends to disclose and integrate the existing knowledge regarding maize flavonoid pigmentation and its relevance in the human health sector.

Different maize ( Zea mays L.) varieties have been used for thousands of years as a healthy food source in Mesoamerica including pigmented maize. Maize ingestion could contribute to the reduction in the rate of non-communicable diseases and, in turn, to its function as an adjuvant in their...

HNF1A gene regulates liver‐specific genes, and genes that have a role in glucose metabolism, transport, and secretion of insulin. HNF1A gene mutations are frequently associated with type 2 diabetes. HNF1A protein has three domains: the dimerization domain, the DNA‐binding domain, and the trans‐activation domain. Some mutations in the dimerization or DNA‐binding domains have no influence on the normal allele, while others have dominant negative effects. The I27L, A98V, and S487N polymorphisms are common variants of the HNF1A gene; they have been found in T2D and non‐diabetic subjects. We searched for mutations in the first three exons of the HNF1A gen in an Amerindian population of 71 diabetic patients. DNA sequencing revealed the previously reported I27L polymorphism (c.79A>C) in 53% of diabetic patients and in 67% of the control group. Thus, the I27L/L27L polymorphism might be a marker of Amerindians. In addition, we found the c.422_423InsT mutation in the HNF1A gene of one patient, which had not been previously reported. This mutation resulted in a frame shift of the open reading frame and a new translation stop in codon 187, leading to a truncated polypeptide of 186 amino acids (Q141Hfs*47). This novel mutation affects the DNA‐binding capacity of the mutant HNF1A protein by EMSA; its intracellular localization by fluorescence and confocal microscopy, and a dominant‐negative effect affecting the DNA‐binding capacity of the normal HNF1A by EMSA. We also studied the homology modeling structure to understand the effect of this mutation on its DNA‐binding capacity and its dominant negative effect. The HNF1A Q141Hfs*47 mutant polypeptide has no DNA‐binding capacity and exerts a dominant negative effect on the HNF1A protein. Therefore, it might produce severe phenotypic effects on the expression levels of a set of β‐cell genes. Consequently, its screening should be included in the genetic analysis of diabetic patients after more functional studies are performed.

Background: Since December 2019, the SARS-CoV-2 virus has been highly contagious and pathogenic, causing mild to severe respiratory failure. The most investigated biomarkers can help to predict disease progression and guide treatment decisions. Expert clinicians suggested that the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) represent rapid, easy, widely available, and relatively inexpensive tools. Objectives: We aimed to explore the NLR and PLR in predicting the poor prognosis of COVID-19 patients in the Mexican Southeast. Methods: In this retrospective study, we included hospitalized adults with COVID-19 from Dr. Juan Graham Casasús Hospital who had survived or non-survived between June 2020 and January 2022. Demographic and laboratory data were acquired from electronic medical records. We calculated NLR, PLR, and SII. The continuous variables were expressed as average and were compared with the Student t-test, as well as with the categorical variables. These were expressed as numbers and percentages and were compared with the χ2 test between the survivor group and the non-survivor group. The sensitivity and specificity in the prediction of death according to the cutoff values of the NLR, PLR, and the SII by ROC curve. P values less than 0.05 were considered significant. Results: We admitted 189 patients. The average age was 61.8 ± 17.3 years, 59.8% (n = 113) were men, and 55.6% (n = 105) were non - survivors. We showed differences among survivors and non - survivors, age (65.6 vs. 56.9 P = 0.001), white blood cell count (14.1 vs. 10.2 P = 0.001), neutrophil (12.4 vs. 8.5 P = 0.002), CRP (213.7 vs. 158.5 P = 0.003), IL - 6 (192.3 vs. 81.0 P = 0.005), NLR (23.5 vs. 11.4 P = 0.000), PLR (524.8 vs. 287.6 P = 0.010), SII (6982.0 vs. 3003.1 P = 0.004). The optimal cutoff for the NLR was 8.6 with a sensitivity of 70.4% and a specificity of 51.8 (AUC 0.678, CI 95% 0.6024 - 0.7541, P < 0.0001), for the PLR where it shows 252.6 with a sensitivity of a 60.0% and a specificity of 50.6 (AUC 0.6096, CI 95% 0.5297 - 0.6895, P < 0.0099), for the SII that 1815 with a sensitivity of 70.4%, and a specificity of 51.8 (AUC 0.6566, CI 95% 0.5788 - 0.7344, P < 0.0002). Conclusions: We propose that NLR, PLR, and SII should be considered an inexpensive, accessible, and effective biomarker in the management of patients with COVID-19. In conclusion, the high NLR, PLR, and SII were related to poor prognosis in COVID-19 patients.

We conducted a retrospective study using a population of patients who were hospitalized at Dr. Juan Graham Casasus Hospital in Villahermosa (Tabasco, Mexico) and had a positive RT-PCR test for SARS-CoV-2 between June 2020 and January 2022. We analyzed all medical records, including demographic data, SARS-CoV-2 exposure history, underlying comorbidities, symptoms, signs at admission, laboratory findings during the hospital stay, outcome, and whole-genome sequencing data. Finally, the data were analyzed in different sub-groups according to distribution during waves of the COVID-19 pandemic regarding Mexican reports from June 2020 to January 2022. Of the 200 patients who tested positive via PCR for SARS-CoV-2, only 197 had samples that could be sequenced. Of the samples, 58.9% (n = 116) were males and 41.1% (n = 81) females, with a median age of 61.7 ± 17.0 years. Comparisons between the waves of the pandemic revealed there were significant differences in the fourth wave: the age of patients was higher (p = 0.002); comorbidities such as obesity were lower (p = 0.000), while CKD was higher (p = 0.011); and hospital stays were shorter (p = 0.003). The SARS-CoV-2 sequences revealed the presence of 11 clades in the study population. Overall, we found that adult patients admitted to a third-level Mexican hospital had a wide range of clinical presentations. The current study provides evidence for the simultaneous circulation of SARS-CoV-2 variants during the four pandemic waves.