Prevalence of DNA-Repair Gene mutations in Mexican men with prostate cancer.

INTRODUCTION AND OBJECTIVE: Mexico reported 26,742 new cases of prostate cancer in 2020. Different risk factors have been identified in the pathogenesis of prostate cancer. Among them, genetic factors and alterations or mutations in specific genes have been described in different ethnic groups worldwide. The aim of our study is to report the prevalence of germline DNA-repair gene mutations in Mexican patients with prostate cancer. MATERIAL AND METHOD: We performed germline genetic testing in 50 patients with localized prostate cancer and 50 patients with metastatic prostate cancer. Demographic, clinical, and histopathological data were collected. RESULTS: Thirty-seven germline mutations were identified in 32 patients. The most commonly affected genes were ATM in 6%, followed by FANCA (5%), and ATR (4%). BRCA2 mutations were identified in 3%. The frequency of mutations was higher in the metastatic group. DISCUSSION AND CONCLUSION: The results of our study show different mutations from those reported in different populations or regions. The use of PARP inhibitors is indicated in patients with germline mutations, specifically BRCA2, showing improvement in overall survival and progression free survival. To our knowledge, this is the first study reporting the prevalence of mutations in DNA-repair genes in Mexican patients with prostate cancer.

A new flexible regression model with application to recovery probability Covid-19 patients.

The aim of this study is to propose a generalized odd log-logistic Maxwell mixture model to analyze the effect of gender and age groups on lifetimes and on the recovery probabilities of Chinese individuals with COVID-19. We add new properties of the generalized Maxwell model. The coefficients of the regression and the recovered fraction are estimated by maximum likelihood and Bayesian methods. Further, some simulation studies are done to compare the regressions for different scenarios. Model-checking techniques based on the quantile residuals are addressed. The estimated survival functions for the patients are reported by age range and sex. The simulation study showed that mean squared errors decay toward zero and the average estimates converge to the true parameters when sample size increases. According to the fitted model, there is a significant difference only in the age group on the lifetime of individuals with COVID-19. Women have higher probability of recovering than men and individuals aged ≥60 years have lower recovered probabilities than those who aged <60 years. The findings suggest that the proposed model could be a good alternative to analyze censored lifetime of individuals with COVID-19.

What kind of sheets does the fat sleeper fish prefer? Effect of pond bottom color on the growth and health of Dormitator latifrons (Richardson 1844).

A little-studied characteristic of the Mexican native fish Dormitator latifrons is the effect that the color of the bottom or lining of ponds or tubs can have on their growth and blood parameters under controlled conditions. After a quarantine period in prophylactic treatment, an initial assay was performed. The organisms were grouped into four treatments (white, yellow, blue, and black) in triplicate, with 30 individuals with an average weight of 34.7± 2.5 g and average size of 12.5 ± 1.5 cm per tank. The trial lasted 60 days, after which a final biometry to all specimens and blood extractions to six random organisms per tank were performed. The following hematological and blood chemistry parameters were evaluated: erythrocytes, cell counts, and differential counts, as well as glucose, albumin, a/g ratio, and total proteins. Final weight, weight gain, and specific growth rate presented statistical differences between treatments (p<0.05), with dark bottoms (blue and black) above 80% of WG and above 1.0 of SGR. No statistically differences were found in hematological blood chemistry parameters (p>0.05). The growth results suggest that dark pond bottoms promote the adaptation of Dormitator latifrons by allowing it to avoid detection by predators through the adoption of a cryptic coloration. However, the species shows a great capacity for crypsis, being able to change its pigmentation to adapt to different bottom colors.

Posttransplantation diabetes mellitus after liver transplant and the impact of family history of diabetes in a Mexican cohort.

INTRODUCTION AND AIMS: Posttransplantation diabetes mellitus (PTDM) is a serious long-term complication that has a negative impact on graft and patient survival. The purpose of the present study was to describe the incidence of PTDM in a Mexican cohort and evaluate its association with a previous family history of diabetes (FHD). METHODS: A retrospective single-center cohort study was conducted on patients undergoing liver transplantation (LT). The primary outcome was time from LT to PTDM. The diagnosis of PTDM was established using the ADA criteria. A mediation analysis that used adjusted Cox regression models and considered pretransplant prediabetes a mediator was performed, to determine the total effect and direct effect of FHD on PTDM. RESULTS: A total of 152 patients were included, with a median follow-up time of 41 months; 19.2% (n = 29) had pretransplant diabetes. During the follow-up time, 15% of patients developed PTDM (n = 23), with an incidence rate of 4.71 cases/100 person-years. PTDM was significantly higher in patients with FHD, compared with those with no FHD (8.72 cases/100 person-years vs 2.04 cases/100 person-years, respectively; p = 0.001). The adjusted hazard ratio of PTDM for FHD was 4.14 (95% CI 1.60-10.7), p = 0.005) and 3.48 (95% CI 1.35-9.01, p = 0.010), when further controlled for pretransplant prediabetes. CONCLUSION: The occurrence of PTDM was similar to that reported in most international studies. As with type 2 diabetes, family history plays an important role in the development of PTDM, even after accounting for pretransplant prediabetes. Patients with FHD should undergo a stricter metabolic program.

The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil.

Among the models applied to analyze survival data, a standout is the inverse Gaussian distribution, which belongs to the class of models to analyze positive asymmetric data. However, the variance of this distribution depends on two parameters, which prevents establishing a functional relation with a linear predictor when the assumption of constant variance does not hold. In this context, the aim of this paper is to re-parameterize the inverse Gaussian distribution to enable establishing an association between a linear predictor and the variance. We propose deviance residuals to verify the model assumptions. Some simulations indicate that the distribution of these residuals approaches the standard normal distribution and the mean squared errors of the estimators are small for large samples. Further, we fit the new model to hospitalization times of COVID-19 patients in Piracicaba (Brazil) which indicates that men spend more time hospitalized than women, and this pattern is more pronounced for individuals older than 60 years. The re-parameterized inverse Gaussian model proved to be a good alternative to analyze censored data with non-constant variance.

A random effect regression based on the odd log-logistic generalized inverse Gaussian distribution.

In recent decades, the use of regression models with random effects has made great progress. Among these models' attractions is the flexibility to analyze correlated data. In various situations, the distribution of the response variable presents asymmetry or bimodality. In these cases, it is possible to use the normal regression with random effect at the intercept. In light of these contexts, i.e. the desire to analyze correlated data in the presence of bimodality or asymmetry, in this paper we propose a regression model with random effect at the intercept based onthe generalized inverse Gaussian distribution model with correlated data. The maximum likelihood is adopted to estimate the parameters and various simulations are performed for correlated data. A type of residuals for the new regression is proposed whose empirical distribution is close to normal. The versatility of the new regression is demonstrated by estimating the average price per hectare of bare land in 10 municipalities in the state of São Paulo (Brazil). In this context, various databases are constantly emerging, requiring flexible modeling. Thus, it is likely to be of interest to data analysts, and can make a good contribution to the statistical literature.

Contribution of halloysite as nanotubular clay mineral on mechanism and adsorption rate of Cd(II) onto nanocomposites alginate-halloysite.

In this work nanocomposites based on alginate (Alg) and halloysite as a nanotubular clay (Hy) were developed. Characterization techniques reveal that Hy/Alg nanocomposites are cation exchangers with predominantly negative charge density and good thermal stability. The adsorption equilibrium of Cd(II) in aqueous solution onto Hy/Alg nanocomposites revealed that by increasing the mass of halloysite in the nanocomposite, the adsorption capacity diminished significantly due to the halloysite-alginate interactions. Maximum adsorption capacities of 8, 65, 88, and 132 mg/g of Cd(II) were obtained for samples Hy, Hy/Alg 50%, Hy/Alg 95%, and Alg, respectively. In addition, the adsorption equilibrium of Cd(II) on the Hy/Alg bionanocomposites was affected by the pH and temperature of the solution, demonstrating the presence of electrostatic interactions during adsorption and that this is an exothermic process. The controlling mechanism of adsorption was cation exchange influenced by electrostatic forces. The Cd(II) adsorption rate studies were interpreted by the diffusion-permeation model and reveal that the presence of Hy in the structure of the nanocomposites enhances the permeation coefficient, that is, the adsorption rate was increased. The values of the permeation coefficient varied from 1.95 × 10-7 to 8.50 × 10-7 cm2/s for Hy/Alg 50% and from 1.70 × 10-7 to 3.55 × 10-7 cm2/s for Hy/Alg 95%.

Capacitors Based on Polypyrrole Nanowire Electrodeposits.

The electrochemical polymerization of polypyrrole nanowires is carried out using potentiodynamic and galvanostatic methods in order to enhance the performance of the modified electrodes as capacitor devices. The electrochemical, spectroscopic, and morphological properties are determined through cyclic voltammetry, Raman spectroscopy and scanning electron microscopy, respectively, corroborating the presence of PPy-nw in dimensions of 30 nm in diameter. Characterization as a capacitor revealed that the nanowire structure enhances key parameters such as specific capacitance with 60 times greater value than bulk polymer modification, in addition to a significant increase in stability. In this way, it is verified that electrodes modified with polypyrrole nanowires obtained in situ by electrochemical methods constitute an excellent candidate for the development of capacitors.

A new regression model for rates and proportions data with applications.

We propose a new continuous distribution in the interval ( 0 , 1 ) based on the generalized odd log-logistic-G family, whose density function can be symmetrical, asymmetric, unimodal and bimodal. The new model is implemented using the gamlss packages in R. We propose an extended regression based on this distribution which includes as sub-models some important regressions. We employ a frequentist and Bayesian analysis to estimate the parameters and adopt the non-parametric and parametric bootstrap methods to obtain better efficiency of the estimators. Some simulations are conducted to verify the empirical distribution of the maximum likelihood estimators. We compare the empirical distribution of the quantile residuals with the standard normal distribution. The extended regression can give more realistic fits than other regressions in the analysis of proportional data.

The semiparametric regression model for bimodal data with different penalized smoothers applied to climatology, ethanol and air quality data.

Semiparametric regressions can be used to model data when covariables and the response variable have a nonlinear relationship. In this work, we propose three flexible regression models for bimodal data called the additive, additive partial and semiparametric regressions, basing on the odd log-logistic generalized inverse Gaussian distribution under three types of penalized smoothers, where the main idea is not to confront the three forms of smoothings but to show the versatility of the distribution with three types of penalized smoothers. We present several Monte Carlo simulations carried out for different configurations of the parameters and some sample sizes to verify the precision of the penalized maximum-likelihood estimators. The usefulness of the proposed regressions is proved empirically through three applications to climatology, ethanol and air quality data.

Joint regression modeling of location and scale parameters of the skew t distribution with application in soil chemistry data.

In regression model applications, the errors may frequently present a symmetric shape. In such cases, the normal and Student t distributions are commonly used. In this paper, we shall be concerned only to model heavy-tailed, skewed errors and absence of variance homogeneity with two regression structures based on the skew t distribution. We consider a classic analysis for the parameters of the proposed model. We perform a diagnostic analysis based on global influence and quantile residuals. For different parameter settings and sample sizes, various simulation results are obtained and compared to evaluate the performance of the skew t regression. Further, we illustrate the usefulness of the new regression by means of a real data set (amount of potassium in different soil areas) from a study carried out at the Department of Soil Science of the Luiz de Queiroz School of Agriculture, University of São Paulo.

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil.

A heteroscedastic regression based on the odd log-logistic Marshall-Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.

Factores asociados a malestar psicológico durante la pandemia de COVID-19 en personal de salud de un hospital público de Ecuador

Fundamento: La pandemia por el coronavirus SARS-CoV-2, genera afectaciones en las esferas social, económica y sanitariade un país, y de manera particular, consecuencias psicológicas negativas en el personal sanitario de hospitales públicos,considerados como la primera línea de atención a pacientes con esta enfermedad.Objetivo: Describir factores asociados a la presencia de malestar psicológico en el personal sanitario de un hospital generalpúblico en Ecuador, durante la pandemia de COVID-19.Metodología: Estudio no experimental, de corte transversal, con alcance descriptivo-correlacional. Los datos correspondierona 276 funcionarios de la salud que respondieron un instrumento online, con un módulo de datos sociodemográficos y una escalade tamizaje de malestar psicológico, estos se aplicaron después de una intervención en salud dirigida al personal de saludrealizada al inicio de la pandemia, en mayo del año 2020. Se realizaron análisis descriptivos y de asociación, mediante elsoftware SPSS 25.0.Resultados: La muestra estuvo compuesta por 76.1 porciento de mujeres, 23.9 porciento de hombres, con una media de edad de 36 años,en mayor cantidad con profesionales de Enfermería (33.7 porciento), seguido de Medicina (24.3 porciento). El 70.7 porciento del personal de saludpresentó malestar psicológico, de estos, el 26.1 porciento con indicativo de trastorno mental. Se encontraron tres variables asociadasa la presencia de malestar psicológico: clima laboral, teletrabajo y convivir con grupos de riesgo.Conclusiones: El personal de Salud ha presentado afectación en su salud mental asociado a las condiciones sociolaboralesdurante la pandemia. [AU]

Socio-academic Factors Influencing Knowledge About Organ Donation among Medical Students in Paraguay, 2018.

Organ donation currently is an extremely important issue in public health. Proper information about the details of this topic is extremely important, but is not yet widespread among the public. This study was carried out with the aim to determine the level of knowledge about organ donation among medical students in Paraguay and associated socio-academic factors influencing their level of knowledge. This was an analytical cross-sectional study, based on a multicenter survey among university medical students. About 68.7% (235) of the respondents were preclinical students doing basic sciences. Two aspects were evaluated, the knowledge regarding the donation of the organs and the socio-academic factors, then both the aspects were evaluated through bivariate and multivariate analyses. There were 342 respondents with a median age of 22 years (interquartile range: 20-23 years) of which 263 (77%) were women. One hundred and eighty-eight (55%) reported not knowing the law that protects and regulates the activities of organ and tissue donation in Paraguay. In the multivariate analysis, the highest frequency of a good level of knowledge of organ donation occurred in those who were older [RPA: 1.07, 95% confidence interval (CI): 1.02-1.12, P = 0.007] and in two of the universities evaluated (both with values P <0.012). On the contrary, those who were preclinical students, in general, had a lower level of knowledge of organ donation (RPa: 0.61, 95% CI: 0.46-0.79; value P <0.001). Our findings denote relatively a poor knowledge of organ donation in some socio-academic subsets. Therefore, it is important to develop strategies to increase the knowledge about the subject, by creating opportunities by way of discussions and debates among the students at all academic levels and also by conducting academic conferences on the subject.

Use of anterolateral thigh free flap for reconstruction and salvage of thoracic limb caused by an arteriovenous malformation.

Vascular arteriovenous malformations originate during the early stages of embryonic development and generally grow progressively, especially during adolescence and pregnancy. Limb salvage using microsurgery is presented, in a patient with an arteriovenous malformation who was initially a candidate for limb amputation. En bloc resection of the arteriovenous malformation of all segments with extended brachial approach and the cutaneous component was performed, with an anterolateral thigh free flap for the lateral reconstruction of the hand.

The multinomial logistic regression model for predicting the discharge status after liver transplantation: estimation and diagnostics analysis.

The multinomial logistic regression model (MLRM) can be interpreted as a natural extension of the binomial model with logit link function to situations where the response variable can have three or more possible outcomes. In addition, when the categories of the response variable are nominal, the MLRM can be expressed in terms of two or more logistic models and analyzed in both frequentist and Bayesian approaches. However, few discussions about post modeling in categorical data models are found in the literature, and they mainly use Bayesian inference. The objective of this work is to present classic and Bayesian diagnostic measures for categorical data models. These measures are applied to a dataset (status) of patients undergoing kidney transplantation.

Relationship between photo-physical and electrochemical properties of D-π-A compounds regarding solar cell applications. 1. Substituent type effect in photovoltaic performance.

Studying the electrochemical characteristics is an important step for determining interactions between molecules and the chemical environment. Moreover, the electrochemical evaluation of dyes is highly needed to establish the behavior of electro-active chemical species inside dye-sensitized solar cells (DSSCs). Four compounds, M8-1, M8-2, M8-O1, and M8-O2 (with a common organic structure (E)-2-cyano-3-(5-((E)-2-(9,9-diethyl-7-(phenylamino)-9H-fluoren-2-yl)vinyl)thiophen-2-yl)acrylic acid), are studied in two solvents, tetrahydrofuran (THF) and dimethylsulfoxide (DMSO). Among the studied compounds, M8-1 has highlighted characteristics compared with the others: its ground and excited states oxidation potential are the highest (1.14 and -1.22 V, respectively). Also, it shows the lowest energy gap between the excited state oxidation potential and the TiO2 conduction band. Relating to the substituent effect, the shorter the length, the higher the energetic difference in the electronic transition (M8-1 and 2). Comparing characteristics through quantum chemistry, the values obtained in DMSO are the most predictable. The injection energies signal that M8-1 is the best injector. The performances in solar cells are measured in three TiO2 materials: Degussa (D-TiO2), active opaque (A-TiO2), and transparent (T-TiO2). The IPCE results show the A > T > D average tendency, and the family of substituted alkyl has higher values than the alcoxyl one. Furthermore, in the first family the methyl substituent has a higher value than the ethyl one. M8-1 has the highest IPCE value, on average. In terms of efficiency, the alkyl substituted family again has higher values than the alcoxyl family. On average, the methyl substituent has a higher value than the ethyl one in both families. M8-1 has the highest efficiency value.

Anticancer activity of two novel ruthenium compounds in gastric cancer cells.

AIMS: Ruthenium (II) complexes are promising anticancer molecules due its pharmacological properties and selectivity to cells tumor. The aim of this work was to study the cytotoxic activity, and apoptosis induction of two new ruthenium complexes on a human gastric cancer cell line. MAIN METHODS: Two ruthenium(II) complexes were synthesized: [(H2pbbzim)Ru(tpy-Ph-COOCH3)](Cl)2 (Ru-UCN1), and [(tpy)Ru(tpy-Ph-bzH)](Cl)2 (Ru-UCN3), and their anticancer capacity determined by cytotoxic assays, gene expression analysis, caspase activation and confocal microscopy. KEY FINDINGS: Ru-UCN3 is more notably cytotoxic than cisplatin in human gastric cancer cells AGS at 24 h, while Ru-UCN1 is more active against gastric cancer cells than cisplatin at 48 h. The complexes induce apoptosis as shown by RT-qPCR, protease activity, and confocal microscopy. Ru-UCN1 induces the overexpression of pro-apoptotic genes at 3 and 6 h, whereas Ru-UCN3 induces overexpression of these genes at 12 and 24 h. Ru-UCN1 treatment shows a strong activation of caspases 3/7 at 24 h, which was not observed for Ru-UCN3 treatment in the same timeframe. SIGNIFICANCE: Taken together, this data suggests that Ru-UCN1 and to a lesser extent, Ru-UCN3, may be interesting anticancer agents for gastric cancer.