Northeast Region Research Articles

Responsive feeding patterns during early childhood in urban areas. Argentina, 2018-2019.

Introduction. Dietary quality involves both the quantity and quality of food offered, the way and the setting in which it is offered, and the responses of the person offering it. The objective of this study was to identify behavioral patterns related to responsive feeding in children aged 6 to 23 months in urban areas from Argentina in 2018-2019. Population and methods. Secondary analysis based on data from the second National Survey on Nutrition and Health of 2018-2019 conducted in a multistage probability sample from urban areas of 5000 inhabitants or more in Argentina. A descriptive analysis and a principal component analysis were performed to identify responsive feeding patterns in 4379 children aged 6 to 23 months. Results. Five responsive feeding patterns were identified; the first 2 dimensions explained 71.1% of inertia (p = 0.013). The pattern with a prevailing possibility of experimentation, autonomy, interaction, and the absence of screens, rewards and distractions was associated with children older than 12 months from the central and south regions (Cuyo, Pampa, Greater Buenos Aires, and Patagonia), whereas the pattern related to a lower autonomy, experimentation, and self-regulation corresponded to children aged 6 to 11 months from the Northwest and Northeast regions. Conclusion. There is evidence of responsive feeding practices that correspond to distinguishable patterns, associated with different stages of life and with the region where the children live.

-temporal variability in fire events due to crop residue burning and their impact on atmospheric variables using ground and remote sensingdata in Punjab

We attempted monitoring and mapping of the active fire events in Punjab, during the wheat and rice harvesting period of 2017-2021 from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m aboard. The analysis showed that the highest fire counts were observed in the central region, followed by the south-west and thelowest in the north-east region of Punjab during all the years. Moreover, during the wheat season, highest fire counts were observed in 2019, being 2535, 11062 and 6212 in north-east, central and south-west regions, respectively. However, during rice, highest fire counts were observed in 2020 in the north-east being 2857 and in 2021 the central and south-west regions being 40960 and 30351 respectively. In line with the number of fire counts, the highest concentration of gases and particulate matter obtained from the Central Pollution Control Board (CPCB) was also observed in the central zone. During the wheat harvesting season, central zone experienced the highest concentration of PM2.5 and PM10 in May 2018 and that of SO2 and O3 in May 2019. Similarly, during the rice harvesting season, central zone also experienced the highest concentration of PM2.5 and PM10 during November 2017 and that of SO2 in 2018. However, the highest concentration of NO2 was observed in October 2018 and that of O3 in October 2020 in the central region. Analysis of the concentration of NO2 and SO2 obtained from the Soumi-NPP satellite also had similar results to CPCB. Such a high concentration of gases and particulate matter might be attributed to crop residue burning a significant positive correlation was observed between fire counts and concentration of particulate matter (PM2.5 and PM10). In view of the alarming deterioration of air quality, there is a dire need to check this practice in the region by providing incentives and viable alternatives to the farmers.

State-Level Childhood Lead Poisoning Prevention Policies and Practices in the United States: 2022-2023.

The purpose of this analysis is to better understand laws and practices guiding prevention activities in childhood lead poisoning prevention programs funded by the Centers for Disease Control and Prevention (CDC). In 2022, CDC surveyed 62 funded programs using the Awardee Lead Profile Assessment. Information was collected about childhood lead poisoning-related laws and guidance, surveillance and prevention strategies, and program services including at what blood lead levels (BLLs) various activities are performed. Separately, CDC reviewed state health department websites to obtain information on which states implemented CDC's updated blood lead reference value. Awardee Lead Profile Assessment results are only reported for 47 states, the District of Columbia, and Puerto Rico. Almost all programs (96%) have laws requiring reporting of BLLs, and 51% require BLLs be reported electronically to jurisdictional health departments. Most programs (80%) prioritize areas and populations that are high risk for lead poisoning prevention activities. Approximately half of the programs (51%) have a lead elimination plan or goal. Thirty-nine percent of the programs have already implemented policies, laws, or regulations to achieve lead elimination, and 74% are in the Northeast and Midwest regions of the country. As of March 2023, 71% of the programs have implemented CDC's updated blood lead reference value, and most (65%) did so via guidance for health care providers and laboratories for what BLL should initiate case management and other services for lead-exposed children. Almost all programs have mandatory BLL reporting laws, and about two-thirds of the programs updated their BLLs that trigger public health action.

Rural-urban and regional variations in aspects of caregiving, support services and caregiver health in the USA: evidence from a national survey

ObjectivesDue to substantial regional variability in available caregiving services and supports, culture and health status among informal caregivers in the USA, the study objective was to explore how rural-urban differences...

Climate and Soil Geochemistry Influence the Soil Organic Carbon Content in Drylands of the Songliao Plain, Northeast China

AbstractThe understanding of the spatial distribution of soil organic carbon (SOC) and its influencing factors is crucial for comprehending the global carbon cycle. However, the impact of soil geochemical and climatic conditions on SOC remains limited, particularly in dryland farming areas. In this study, we aimed to enhance the understanding of the factors influencing the distribution of SOC in the drylands of the Songliao Plain, Northeast China. A dataset comprising 35,188 measured soil samples was used to map the SOC distribution in the region. Multiple linear regression (MLR) and random forest models (RFM) were employed to assess the importance of driving indicators for SOC. We also carried out partial correlation and path analyses to further investigate the relationship between climate and geochemistry. The SOC content in dryland soils of the Songliao Plain ranged from 0.05% to 11.63%, with a mean value of 1.47% ± 0.90%. There was a notable increasing trend in SOC content from the southwest to the northeast regions. The results of MLR and RFM revealed that temperature was the most critical factor, demonstrating a significant negative correlation with SOC content. Additionally, iron oxide was the most important soil geochemical indicator affecting SOC variability. Our research further suggested that climate may exert an indirect influence on SOC concentrations through its effect on geochemical properties of soil. These insights highlight the importance of considering both the direct and indirect impact of climate in predicting the SOC under future climate change.

A machine learning-based approach for flash flood susceptibility mapping considering rainfall extremes in the northeast region of Bangladesh

Flash floods are catastrophic global events, especially in northeast Bangladesh, and assessing flash flood susceptibility is crucial for preparedness and mitigation. Traditional geographic system-based flash flood susceptibility mapping struggles to capture flash floods’ non-linear and complex nature. However, machine learning models have recently emerged as an efficient alternative to address these limitations. This study evaluates four machine learning models—Artificial Neural Network (ANN), Recurrent Neural Network (RNN), Random Forest – Gradient Boosting (RFGB) Hybrid, and Categorical Boosting (CatBoost)—for flash flood susceptibility. It categorizes areas into five susceptibility levels: very low, low, moderate, high, and very high. Covering 24,424.25 km2 across eight districts, the study uses 400 points (200 flood and 200 non-flood) for training and validation, based on field investigation, historical flood information, Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar data using Google Earth Engine, and insights from the local people. The models’ predictive performances are evaluated by incorporating topographical attributes and rainfall indices and using accuracy, precision, recall, F1 score, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) score, with 70% of the data for training and 30% for testing. The ANN model performs best with rainfall indices, achieving high accuracy (maximum AUC = 0.802). The RFGB hybrid model shows excellent training accuracy (AUC ≥ 0.971) but suffers from overfitting during validation (AUC ≤ 0.674), requiring careful hyperparameter adjustment. The CatBoost model effectively uses both rainfall indices and terrain features, achieving AUC = 0.701 in training and AUC = 0.667 in validation. The ANN model conservatively includes the largest area (2198.3 km2) under ’very high’ susceptibility. This study’s flash flood susceptibility maps, which include rainfall extremes, are more robust than those without, helping local administrative authorities and national flood practitioners prepare for flash floods.

The Accessibility Levels of the Websites of Federal Higher Education Institutions in Northeast Brazil

The general aim of this study is to make a diagnosis on the accessibility of information made available on the websites of the Federal Higher Education Institutions (IFES) in the Northeast. It is based on the hypothesis that the websites of the IFES in the Northeast Region of Brazil do not have high levels of adequacy, results that do not allow any user, regardless of being a person with disabilities or other limitations, to access the knowledge made available there, either with the help of assistive technologies or autonomously. The methodological procedures will be bibliographical and documentary research with analysis of primary sources on institutional websites and administrative acts made available, or not, on these sources. All the open data portals will be evaluated and simulated to determine their suitability for eMAG. This will be done using the public software ASES, a system for comparing and validating the standards of construction and behaviour of the source code of electronic sites, pointing out the levels of usability, navigability, alternative text, and content markers regarding the eMAG parameters, which are mandatory for public institutional sites in Brazil in terms of digital accessibility. As a result of the research, it was possible to identify that the levels of accessibility on the websites of these institutions were not in line with the parameters of the Digital Government Accessibility Model (eMag) of Brazil. This reveals divergences in the promotion of access to information; while some IFES make information available autonomously, without facing noise, interference, or impediments to the use of information, others do not so much, which has a negative impact on the guarantee of rights such as the exercise of full citizenship.

ESTUDOS SOBRE DESIGUALDADES EDUCACIONAIS NO BRASIL: UMA ANÁLISE SOBRE ALGUNS ESTUDOS DE DESIGUALDADES NA EDUCAÇÃO BÁSICA NO BRASIL

This article presents an analysis of selected studies on educational inequalities in Basic Education in Brazil, addressing the main dimensions of these inequalities, such as socioeconomic, regional, racial, gender factors, and access for people with disabilities. Through a literature review of renowned authors, this work discusses the causes and consequences of educational inequalities and suggests possible solutions to promote more equitable and inclusive education. Socioeconomic inequality is identified as a significant factor, affecting school performance and dropout rates among low-income students. Regional inequalities are also highlighted, emphasizing the disparities between the North and Northeast regions and the more developed Southeast and South regions. Racial analysis reveals ongoing discrimination that hinders black and indigenous students, while gender inequalities, though less pronounced in terms of access, still affect girls' educational and professional choices. Additionally, the inclusion of students with disabilities remains a challenge due to the lack of adequate infrastructure and specific teacher training. The exacerbated impact of the COVID-19 pandemic is addressed, highlighting the digital divide and the need for effective public policies. Programs such as Bolsa Família and the National School Feeding Program (PNAE) are cited as positive measures, although insufficient without equitable resource allocation. The analysis concludes that a multifaceted and inclusive approach is essential to address the various forms of inequality in Basic Education in Brazil, aiming to ensure that all students have access to quality education, regardless of their socioeconomic, regional, racial, gender, or disability status.

Conceptualising climate change vulnerability across the agrarian transition: The example of Egypt

In this study, we explore the relationship between Egypt's agrarian transition and farmers’ perceptions of environmental risks and opportunities for climate change adaptation. Drawing from agrarian studies and rural development pathways in Egypt, we highlight structural challenges in addressing vulnerabilities of households in agrarian communities to environmental change. Our evidence comes from 350 landholders and agricultural labourers in rural Damietta, a governorate in the northeast of the Egyptian Nile Delta Region. We categorize households into three groups based on their reliance on agriculture for income, corresponding to different agrarian transition models. We find that vulnerabilities and capacities for climate change adaptation vary among these groups, with those heavily dependent on agriculture being the most vulnerable, despite having greater awareness of agricultural risks. They exhibit limited capacity to respond effectively – both in and ex situ, indicating a need for targeted support as environmental pressures increase due to climate change.

SOCIAL IMPACT ON PUBLIC ADMINISTRATION: TRAFFIC ACCIDENTS ON BRAZILIAN HIGHWAYS

The aim of this research was to evaluate statistical relationships between variables inherent to accidents and traffic incidents on Brazilian federal highways in 2020. This is an applied study with a quantitative, exploratory, and descriptive approach. The data source was the website of the Brazilian Federal Highway Police, and the locus was the entire Brazilian territory. Data analysis was inferential, given the application of statistical methods via significance hypothesis tests. The Northeast and Southeast regions had the highest number of deaths from traffic accidents (1,571 and 1,371), respectively. On weekends, the majority (21,087) of incidents were recorded during the day (34,397), however, fatal accidents were predominantly recorded at night. The straight track layout had the majority of records (38,336), collisions between vehicles were the most lethal type of accident (2,955), and rural areas recorded twice as many deaths compared to urban areas. In 2020, the COVID-19 pandemic occurred, where restrictive measures on human movement directly influenced traffic accident statistics, especially in the period from March to April 2020, especially in the Southeast and South regions, impacting social relations and public administration due to traffic victimization.

Morphological and biochemical characteristics of wild red-fleshed apples (Malus sieversii f. niedzwetzkyana) in the North and Northeast of Iran

BackgroundRed-flesh apples (Malus sieversii f. niedzwetzkyana) have attracted attention from consumers and researchers due to their pleasant appearance and taste. These exotic apples are rich sources of nutrients and health-promoting polyphenols and phenolics. This study aimed to investigate morphological (40 quantitative and 13 qualitative traits) and biochemical (5 traits) characteristics of four socioeconomically important red-fleshed apple populations in North and Northeast region of Iran, which are understudied and under serious extinction risk.ResultsThe examined characters exhibited wide and statistically significant variations, especially in leaf color (68.86%) and the number of seeds per fruit (61.61%), and more dramatically in the total flavonoids (146.64%) and total phenolics contents (105.81%). There were also strong variations in fresh fruit weight and fruit length, diameter, and flesh thickness. Red, with 34 accessions, was the dominant ripe fruit skin color. All biochemical traits also showed high variations, particularly in total flavonoid content. Red-fleshed Gavramak and Kalateh Khij apples contained the highest biochemical and morphological values, respectively. Principal component analysis (PCA) revealed that the first five principal components together accounted for more than 60.83% variation of the total observed variations. Moreover, the cluster dendrogram analysis based on Ward’s method indicated three different clusters based on the characters measured, indicating high variation among the accessions.Conclusionred-flesh apples can be considered suitable sources of natural antioxidants with great potential as healthy foods and nutraceutical applications. Based on the commercial characters, Red-fleshed Gavramak and Kalateh Khij apples showed the highest fruit quality with proper size and thus can be suggested as superior for cultivation or use in breeding programs due to having higher quality fruits.

Long-period ground motion simulation and pulse probability distribution characteristics of the Kumamoto MW 7.1 earthquake in Japan

The 2016 Kumamoto MW 7.1 earthquake in Japan caused severe structural damage. It produced valuable seismic records that offered an opportunity to investigate the characteristics of long-period ground motion and pulse probability distribution. This study works in three main parts. First, we use the finite difference method (FDM) to reproduce the long-period ground motions of the 2016 Kumamoto MW 7.1 earthquake. That provides a crucial foundation for the subsequent phases. We identify velocity pulses within both synthetic and observed waveforms. By rigorously analyzing these pulses, we unveiled a wealth of insights into the characteristics of velocity pulses, strengthening the influence of the rupture directivity effect. In particular, the northeast region of the rupture exhibited a significant concentration of pulsed attributes. Finally, we further focus on establishing statistical relationships between different pulse parameters. The study revealed that the pulse probability distribution model fit well with the observed pulse distribution in the parallel to the fault (FP) and normal to the fault (FN) directions. However, the model also faced challenges in the FN direction due to the mechanism of velocity pulses and altered rupture propagation direction. Crucially, the study established that velocity pulses primarily cluster within a fault distance of less than 30 km, and the relationship between pulse peak value and fault distance followed an exponential trend. The study underscores the imperative of further refining the probability distribution model of velocity pulses, making it more robust and widely applicable. Furthermore, the correlation between velocity pulses and seismic parameters requires further validation through seismic records. This study sets the stage for a deeper understanding of earthquake-induced ground motion and pulse characteristics, contributing to the ongoing efforts in seismic risk assessment.

PANORAMA DA FISIOTERAPIA OFERTADA A PACIENTES COM SEQUELAS DE QUEIMADURA

Introduction: Burns are thermal, electrical, chemical or radioactive traumas that damage body tissues and can lead to death. Objective: To analyze the data and information collected in the system, referring to the quantity of physiotherapeutic care offered, by the SUS, to patients with burn sequelae, in Brazil, in the last 10 years. Materials and methods: Data were obtained from the DATASUS database. The collected data was organized in an Excel spreadsheet, displayed in graphs and analyzed based on scientific literature. Result: In Brazil, in the last 10 years, 97,685 physiotherapeutic services were offered to medium and large burn patients, through the SUS. The largest number of care for medium and large burn patients was concentrated in the northeast region of Brazil and the smallest number in the Central-West region. Conclusion: The study provided a broad overview of the physiotherapeutic care provided to patients with burns in Brazil over the last ten years.

Quantification of biomass availability for wood harvesting and storage in the continental United States with a carbon cycle model

BackgroundWood Harvesting and Storage (WHS) is a form of Biomass Carbon Removal and Storage (BiCRS) that utilizes a combined natural and engineered process to harvest woody biomass and put it into long term storage, most frequently in the form of subterranean burial. This paper aims to quantify the availability of woody biomass for the purposes of WHS in the continental United States using a carbon cycle modeling approach. Using a regional version of the VEGAS terrestrial carbon cycle model at 10 km resolution, this paper calculates the annual woody net primary production in the continental United States. It then applies a series of constraints to exclude woody biomass that is unavailable for WHS. These constraints include fine woody biomass, current land use, current wood utilization, land conservation, and topographical limitations. These results were then split into state by state and regional totals.ResultsIn total, the model projects the continental United States could produce 1,274 MtCO2e (CO2 equivalent) worth of coarse woody biomass annually in a scenario with no anthropogenic land use or constraints. In a scenario with anthropogenic land use and constraints on wood availability, the model projects that 415 MtCO2e of coarse woody biomass is available for WHS annually. This is enough to offset 8.5% of the United States’ 2020 greenhouse gas emissions. Of this potential, 20 MtCO2e is from the Pacific region, 77 MtCO2e is from the Western Interior, 91 MtCO2e is from the Northeast region, and 228 MtCO2e is from the Southeast region.ConclusionThere is enough coarse woody biomass available in the continental United States to make WHS a viable form of carbon removal and storage in the country. There is coarse woody biomass available across the continental United States. All four primary regions analyzed have enough coarse woody biomass available to justify investment in WHS projects.

Priority areas for the use of solar water disinfection (SODIS) in Brazil: a spatial approach

ABSTRACT This paper presents a methodology for the development of a potential and priority use map for the application of the solar water disinfection (SODIS) method in Brazil. The assessment of solar radiation was conducted, with a particular focus on the annual average global horizontal irradiance (GHI). The water vulnerability index (WVI) and the economic-social-ecosystemic (ESE)-WVI were developed and employed as indicators to define the priority regions for the application of SODIS. The combination of the GHI and WVI maps yielded a SODIS usage potential index (SUPI). The combination of the SUPI map with information pertaining to the human, economic, and ecosystem dimensions of water vulnerability (ESE-WVI) yielded the SODIS usage priority index. The analysis revealed that the country exhibits favorable levels of solar radiation, making the implementation of SODIS a viable option, particularly in the Northeast region. Furthermore, the study identified regions with greater water vulnerability, such as the semi-arid region and some parts of the Amazon, as priorities for the application of SODIS. In conclusion, SODIS represents a viable water treatment technique for various regions in Brazil, particularly those with abundant solar radiation and concerns regarding water security.

Space-time dynamics of the dengue epidemic in Brazil, 2024: an insight for decision making

BackgroundDengue is a vector-borne viral infection caused by the dengue virus transmitted to humans primarily by Aedes aegypti. The year 2024 has been a historic year for dengue in Brazil, with the highest number of probable cases ever registered. Herein, we analyze the temporal trend and spatio-temporal dynamics of dengue cases in Brazil during the first nine epidemiological weeks (EW) of 2024.MethodsThis is an ecological study, including all probable cases of dengue in Brazil during the period, carried out in two steps: time series analysis to assess the temporal trend and spatial analysis to identify high-risk clusters.Results1,345,801 probable cases of dengue were reported. The regions with the highest increasing trend were the Northeast with an average epidemiologic week percent change (AEPC) of 52.4 (95% CI: 45.5–59.7; p < 0.001) and the South with 35.9 (95% CI: 27.7–44.5; p < 0.001). There was a statistically significant increasing trend in all states, except Acre (AEPC = -4.1; 95% CI: -16.3–10; p = 0.55), Amapá (AEPC = 1.3; 95% CI: -16.2–22.3; p = 0.9) and Espírito Santo (AEPC = 8.9; 95% CI: -15.7–40.6; p = 0.5). The retrospective space-time analysis showed a cluster within the Northeast, Central-West and Southeast regions, with a radius of 515.3 km, in which 1,267 municipalities and 525,324 of the cases were concentrated (RR = 6.3; p < 0.001). Regarding the spatial variation of the temporal trend, 21 risk areas were found, all of them located in Southeast or Central-West states. The area with the highest relative risk was Minas Gerais state, where 5,748 cases were concentrated (RR = 8.1; p < 0.001). Finally, a purely spatial analysis revealed 25 clusters, the one with the highest relative risk being composed of two municipalities in Acre (RR = 6.9; p < 0.001).ConclusionsWe described a detailed temporal-spatial analysis of dengue cases in the first EWs of 2024 in Brazil, which were mainly concentrated in the Southeast and Central-West regions. Overall, it is recommended that governments adopt public policies to control the the vector population in high-risk areas, as well as to prevent the spread of dengue fever to other areas of Brazil.

Prenatal Exposure to Herbicide 2,4-Dichlorophenoxyacetic Acid (2,4D) Exacerbates Zika Virus Neurotoxicity In Vitro and In Vivo.

Zika virus (ZIKV) infection during pregnancy can lead to a set of congenital malformations known as Congenital ZIKV syndrome (CZS), whose main feature is microcephaly. The geographic distribution of CZS in Brazil during the 2015-2017 outbreak was asymmetrical, with a higher prevalence in the Northeast and Central-West regions of the country, despite the ubiquitous distribution of the vector Aedes aegypti, indicating that environmental factors could influence ZIKV vertical transmission and/or severity. Here we investigate the involvement of the most used agrochemicals in Brazil with CZS. First, we exposed human neuroblastoma SK-N-AS cells to the 15 frequently used agrochemical molecules or derivative metabolites able to cross the blood-brain barrier. We found that a derived metabolite from a widely used herbicide in the Central-West region, 2,4-dichlorophenoxyacetic acid (2,4D), exacerbates ZIKV neurotoxic effects in vitro. We validate this observation by demonstrating vertical transmission leading to microcephaly in the offspring of immunocompetent C57BL/6J mice exposed to water contaminated with 0.025 mg/L of 2,4D. Newborn mice whose dams were exposed to 2,4D and infected with ZIKV presented a smaller brain area and cortical plate size compared to the control. Also, embryos from animals facing the co-insult of ZIKV and 2,4D exposition presented higher Caspase 3 positive cells in the cortex, fewer CTIP2+ neurons and proliferative cells at the ventricular zone, and a higher viral load. This phenotype is followed by placental alterations, such as vessel congestion, and apoptosis in the labyrinth and decidua. We also observed a mild spatial correlation between CZS prevalence and 2,4D use in Brazil's North and Central-West regions, with R2 = 0.4 and 0.46, respectively. Our results suggest that 2,4D exposition facilitates maternal vertical transmission of ZIKV, exacerbating CZS, possibly contributing to the high prevalence of this syndrome in Brazil's Central-West region compared to other regions.

Pentraxin-3 (PTX-3) as a potential biomarker for predicting death in hospitalized patients with COVID-19

BackgroundPentraxin 3 (PTX3) is an acute-phase protein that belongs to the pentraxin family, which plays an important role in the body’s defense against pathogens. PTX3 levels have been associated with inflammatory processes, and it is a possible biomarker for the diagnosis and prognosis of different infectious diseases, including COVID-19. The objective of this study was to analyze the potential of PTX3 as a plasma biomarker for predicting death in patients hospitalized with COVID-19.MethodsThe study included a total of 312 patients with COVID-19, admitted from July 2020 to August 2021 to hospital ward and intensive care unit beds at two hospitals in the Northeast Region of Brazil. PTX3 was measured using ELISA in samples collected within 24 h after hospital admission. Maximally selected rank statistics were used to determine the PTX3 cutoff point that best distinguished patients who died from those who survived. A receiver operating characteristic (ROC) curve was used to determine the performance of the biomarker. Survival analysis was performed using a Kaplan-Meier curve, and a Cox regression model was used to determine predictors associated with death.ResultsOf the 312 patients included in the study, 233 recovered and 79 died. Patients who died had higher PTX3 levels at the time of admission, when compared to those who recovered (median: 52.84 versus 10.79 ng/mL; p < 0.001). PTX3 showed area under the ROC (AUC) = 0.834, higher than other markers used in clinical practice, such as C-reactive protein (AUC = 0.72) and D-dimer (AUC = 0.77). Furthermore, according to the Kaplan-Meier survival curve, patients with PTX3 concentrations above the cutoff point (27.3 ng/mL) had a lower survival rate (p = 0.014). In multivariate Cox regression, PTX3 > 27.3 ng/mL was an important predictor of death, regardless of other confounding factors (hazard ratio = 1.79; p = 0.027).ConclusionPTX3 can be considered as a potential biomarker for predicting death in patients hospitalized with COVID-19.

Prevalence and genotype distribution of human papillomavirus (HPV) in penile cancer in Brazil

Objective: To estimate the prevalence and genotypic distribution of Human Papillomavirus (HPV) in penile cancer in Brazil. Methods: This is a systematic review and meta-analysis of studies published from 2000 to 2021, that investigated the prevalence and genotypic distribution of HPV in penile cancer in different geographical regions in Brazil, using molecular methods. The review was registered in the International Prospective Register of Systematic Reviews (PROSPERO), conducted in accordance with the Preferred Reporting of Systematic Reviews and Meta-Analysis Statement (PRISMA) and the quality of included studies was assessed by the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data. Results: 15 studies were included, comprising 1,250 cases. The combined prevalence of HPV in penile cancer was 52.0% and the highest prevalence was observed in the Northeast region (79%), followed by the North region (54%), Southeast (44%) and Central-West region (31%). HPV16 was the most prevalent genotype, followed by HPV6, HPV11, HPV18, HPV51, HPV59, HPV74, HPV31, HPV35 and HPV68. Final considerations: Our results confirm the association of HPV with penile cancer and highlight the presence of viral genotypes not covered by the tetravalent prophylactic vaccine distributed by the public health system in Brazil.

Development of Anemometer Based on Inertial Sensor.

The current article elucidates a study centered on the development of an anemometer leveraging an inertial sensor for wind speed measurement in the northeast region of Brazil, focusing on renewable energy generation. The study encompassed a series of experiments aimed at calibrating the anemometer, analyzing the noise generated by the inertial sensor, and scrutinizing the data acquired during wind speed measurement. The calibration process unfolded in three stages: initial noise analysis, subsequent inertial data analysis, and the derivation of calibration curves. The first two stages involved experiments conducted at an average sampling rate of 10 Hz. Simultaneously, the third stage incorporated data collected over a 1 h duration while maintaining the same sampling rate. The outcomes underscore the suitability of the anemometer based on an inertial sensor for wind energy systems and diverse applications. While the wind readings from the prototype exhibit considerable fluctuations, a three-length moving average filter is applied to the prototype's output to mitigate these fluctuations. The calibration surface was established using observational data, and the resultant surface is detailed. Data analysis assumes paramount significance in wind speed measurement, and the K-NN algorithm demonstrated superior efficacy in estimating the correspondence between measured and control data.