Universidad Andina del Cusco, Cusco

Corruption is a psychosocial problem that has important implications for different areas of society. In psychology, this problem is usually studied through corrupt behavior. The aim of this study is thus to analyze the tests used to evaluate corrupt behavior from a psychological perspective. A systematic review was conducted following the standards of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 statement of relevant studies published from 2000 to 2023 in Scopus, ScienceDirect and the Web of Science. We have therefore included empirical studies published in Spanish and English, synthesized their information using thematic analysis, and presented these results in a summary table. Specifically, we reviewed 696 articles and 63 relevant full-text articles, and 24 of these studies met the inclusion criteria. Accordingly, we have found that corrupt behavior has been evaluated through three types of tests: surveys, corruption scenarios, and bribery games. The main properties of these tests also vary according to the adopted theoretical framework, domain evaluated, rigor of evaluation, and sample characteristics. These findings can be used to determine the choice of a particular instrument or in the construction of another if the existing instruments are deemed inappropriate.

Epileptic seizures are prevalent in people with brain vascular abnormalities like arteriovenous malformations (AVMs) and cavernous malformations, greatly affecting their quality of life. The connection between intracranial vascular abnormalities and epilepsy is still under debate. Therefore, investigating epilepsy in individuals with AVMs is a crucial and current research area. This review presents a comprehensive examination of recent developments in epilepsy among individuals with brain AVMs. The authors conducted a detailed analysis of the natural progression, epidemiology, diagnostic methods, therapeutic approaches, and post-treatment outcomes for individuals with epilepsy associated with AVMs.

Objective: Musculoskeletal disorders frequently affect postmenopausal women. This study aims to compare muscle disorders between women according to the type of experienced menopause: premature (PM) or normal age of menopause (NAM). Methods: This was a cross-sectional study conducted in nine Latin American countries in which late postmenopausal women (55 to 70 years) were surveyed with a general questionnaire, the Menopause Rating Scale (MRS: item #4 exploring musculoskeletal discomfort), and the trength, assistance with walking, rising from a chair, climbing stairs, and falling questionnaire (risk of sarcopenia). Results: A total of 644 women were included: 468 who had NAM, and 176 who had PM (116 spontaneous and 60 surgical). The overall mean age of the participants was 60.9 ± 4.2 years. Women who had PM experienced more musculoskeletal discomfort (33.5% vs 20.9%, P < 0.001) and a higher likelihood of sarcopenia (35.2% vs 19.9%, P < 0.001) than women who had a NAM. Women who had surgical PM exhibited a higher prevalence of severe musculoskeletal discomfort (46.7% vs 29.3%, P < 0.02) and a higher likelihood of sarcopenia (45.0% vs 27.6%, P < 0.02) than women who had a NAM. After adjusting for covariates (age, body mass index, menopausal hormone therapy use, physical activity, education, cigarette consumption, use of antidepressants, sexual activity, comorbidities, and having a partner), our logistic regression model determined that spontaneous PM was not associated with higher odds of musculoskeletal discomfort and higher odds of sarcopenia. On the other hand, women who had surgical PM were more likely to experience musculoskeletal discomforts (odds ratio: 2.26; 95% confidence interval: 1.22-4.17) and higher odds for sarcopenia (odds ratio: 2.05; 95% confidence interval: 1.16-3.65) as compared to women who experienced a NAM. Conclusions: Women experiencing surgical PM have a higher likelihood of developing muscle disorders. This underscores the potential significance of hormonal levels in influencing musculoskeletal health during postmenopause.

Background Accuracy of molecular tools for the identification of parasites that cause human cutaneous leishmaniasis (CL) could largely depend on the sampling method. Non-invasive or less-invasive sampling methods such as filter paper imprints and cotton swabs are preferred over punch biopsies and lancet scrapings for detection methods of Leishmania based on polymerase chain reaction (PCR) because they are painless, simple, and inexpensive, and of benefit to military and civilian patients to ensure timely treatment. However, different types of samples can generate false negatives and there is a clear need to demonstrate which sample is more proper for molecular assays. Methodology Here, we compared the sensitivity of molecular identification of different Leishmania (Viannia) species from Peru, using three types of sampling: punch biopsy, filter paper imprint and lancet scraping. Different composite reference standards and latent class models allowed to evaluate the accuracy of the molecular tools. Additionally, a quantitative PCR assessed variations in the results and parasite load in each type of sample. Principal findings Different composite reference standards and latent class models determined higher sensitivity when lancet scrapings were used for sampling in the identification and determination of Leishmania (Viannia) species through PCR-based assays. This was consistent for genus identification through kinetoplastid DNA-PCR and for the determination of species using FRET probes-based Nested Real-Time PCR. Lack of species identification in some samples correlated with the low intensity of the PCR electrophoretic band, which reflects the low parasite load in samples. Conclusions The type of clinical sample can directly influence the detection and identification of Leishmania (Viannia) species. Here, we demonstrated that lancet scraping samples consistently allowed the identification of more leishmaniasis cases compared to filter paper imprints or biopsies. This procedure is inexpensive, painless, and easy to implement at the point of care and avoids the need for anesthesia, surgery, and hospitalization and therefore could be used in resource limited settings for both military and civilian populations.

Internal communication is a critical and strategic element in achieving success for any organization. This paper presents a longitudinal study and opinion analysis that utilizes the k-means algorithm to examine the level of usage of digital and traditional channels for internal communication at the Universidad Nacional de San Antonio Abad del Cusco in Peru. The study population consisted of 22,000 employees and students, with three measurements taken at non-probability sampling intervals of 368, 652, and 217 participants in 2014, 2019, and 2022, respectively. The opinion analysis was based on a dataset of 1,300 comments collected between 2014 and 2022. Research findings indicate weak upward communication, a decrease in the use of printed materials, face-to-face meetings, notice boards as primary traditional media, and email and WhatsApp as leading digital media. The k-means algorithm, with three clusters, identified top themes focused on increasing email usage, improving communication within the university, and increasing Internet access speed. In conclusion, the internal communication plan needs to be continuously updated and validated since communication channels change over time and become more potent.

Background Coronavirus disease 2019 (COVID-19) has had a significant impact on dermatology, but to date no bibliometric analysis of this field has been identified. Therefore, the aim of this study was to perform a bibliometric indicator analysis of the worldwide scientific production of COVID-19 in dermatology. Materials and Methods An advanced bibliographic search was performed in the Scopus database to identify articles on COVID-19 and dermatology from 2020 to 2021. The collected information was analysed with SciVal software. Bibliometric data were described through figures and summary tables. Results A total of 1448 documents were collected and analysed. Torello Lotti was the author with the greatest scientific production; however, Esther Freeman had the greatest impact. Harvard University was the institution with the highest number of published articles. Most papers were published in the first quartiles. The United States and Italy were the leading countries in terms of production. Articles with international collaboration had the highest impact. Conclusion Articles related to dermatology and COVID-19 are mostly published with American and Italian affiliations. In addition, there has been an increase in the distribution of articles published in the first quartile, which would reflect a growing interest in the community. Publications with international collaboration reported the highest impact, so future authors should take this into account.

Background: Tridimensional medical knowledge of human anatomy is a key step in the undergraduate and postgraduate medical education, especially in surgical fields. Training simulation before real surgical procedures is necessary to develop clinical competences and to minimize surgical complications. Methods: Latex injection of vascular system in brain and in head-neck segment is made after washing out of the vascular system and fixation of the specimen before and after latex injection. Results: Using this latex injection technique, the vascular system of 90% of brains and 80% of head-neck segments are well-perfused. Latex-injected vessels maintain real appearance compared to silicone, and more flexible vessels compared to resins. Besides, latex makes possible a better perfusion of small vessels. Conclusions: Latex vascular injection technique of the brain and head-neck segment is a simulation model for neurosurgical training based on real experiencing to improve surgical skills and surgical results.

MCH1 is a synthetic macamide that has shown in vitro inhibitory activity on fatty acid amide hydrolase (FAAH), an enzyme responsible for endocannabinoid metabolism. This inhibition can modulate endocannabinoid and dopamine signaling in the nucleus accumbens (NAc), potentially having an antidepressant-like effect. The present study aimed to evaluate the effect of the in vivo administration of MCH1 (3, 10, and 30 mg/kg, ip) in 2-month-old BALB/c male mice (n=97) on forced swimming test (FST), light-dark box (LDB), and open field test (OFT) and on early gene expression changes 2 h after drug injection related to the endocannabinoid system (Cnr1 and Faah) and dopaminergic signaling (Drd1 and Drd2) in the NAc core. We found that the 10 mg/kg MCH1 dose reduced the immobility time compared to the vehicle group in the FST with no effect on anxiety-like behaviors measured in the LDB or OFT. However, a 10 mg/kg MCH1 dose increased locomotor activity in the OFT compared to the vehicle. Moreover, RT-qPCR results showed that the 30 mg/kg MCH1 dose increased Faah gene expression by 2.8-fold, and 10 mg/kg MCH1 increased the Cnr1 gene expression by 4.3-fold compared to the vehicle. No changes were observed in the expression of the Drd1 and Drd2 genes in the NAc at either MCH1 dose. These results indicated that MCH1 might have an antidepressant-like effect without an anxiogenic effect and induces significant changes in endocannabinoid-related genes but not in genes of the dopaminergic signaling system in the NAc of mice.

Objective: There are limited studies on urogenital symptoms in women who experience menopause before the age of 40 years due to primary ovarian insufficiency (POI) or bilateral oophorectomy (surgical POI). This study aimed to compare the urogenital symptoms, including sexuality, of women with POI to those without the condition. Methods: This cross-sectional study conducted was in seven Latin American countries, in which postmenopausal women (with POI and non-POI) were surveyed with a general questionnaire, the Menopause Rating Scale (MRS) and the six-item Female Sexual Function Index (FSFI-6). The association of premature menopause with more urogenital symptoms and lower sexual function was evaluated with logistic regression analysis. Results: Women with POI experience more urogenital symptoms (MRS urogenital score: 3.54 ± 3.16 vs. 3.15 ± 2.89, p < 0.05) and have lower sexual function (total FSFI-6 score: 13.71 ± 7.55 vs. 14.77 ± 7.57 p < 0.05) than women who experience menopause at a normal age range. There were no significant differences in symptoms when comparing women based on the type of POI (idiopathic or surgical). After adjusting for covariates, our logistic regression model determined that POI is associated with more urogenital symptoms (odds ratio [OR]: 1.38, 95% confidence interval [CI] 1.06-1.80) and lower sexual function (OR: 1.67, 95% CI 1.25-2.25). Conclusion: POI, whether idiopathic or secondary to bilateral oophorectomy, is associated with symptoms that affect vaginal and sexual health.

Clinical and epidemiological features of 7 human immunodeficiency virus–negative Peruvian patients coinfected with human T-lymphotropic virus type 1 (HTLV-1) and cryptococcosis (2006–2017) were studied. Most cases had meningeal involvement, were male, and originated from Peru's jungle. Patients with cryptococcosis should be tested for HTLV-1 in endemic areas of this retrovirus.

The 21st century witnesses a pivotal global shift towards Renewable Energy Sources (RES) to combat climate change. Nations are adopting wind, solar, hydro, and other sustainable energy forms. However, a primary concern is the inconsistent nature of these sources. Daily fluctuations, seasonal changes, and weather conditions sometimes make renewables like the sun and wind unreliable. The key to managing this unpredictability is efficient Energy Storage Systems (ESS), ensuring energy is saved during peak periods and used during low production times. However, existing ESSs are not flawless. Energy conversion and storage inefficiencies emerge due to temperature changes, inconsistent charge rates, and voltage fluctuations. These challenges diminish the quality of stored energy, resulting in potential waste. There is a unique chance to address these inefficiencies using the vast data from renewable systems. This research explores Machine Learning (ML), particularly Neural Networks (NN), to improve REES efficiencies. Analyzing data from Palm Springs wind farms, the study employs an Entropy-Based Recursive Feature Elimination (ERFE) coupled with Feed-Forward Neural Networks (FFNN). ERFE utilizes entropy to prioritize essential features, reducing redundant data and computational demands. The tailored FFNN then predicts energy conversion rates, aiming to enhance energy storage conversion and maximize the usability of generated Renewable Energy (RE).

From smart home devices to wearable devices, electronics have become an indispensable part of modern life. Vast volumes of data have been collected by these electronic devices, revealing precise information about device communications, user behaviours, and more. Improvements to device features, insights into the user experience, and the detection of security risks are just some of the many uses for this information. However, advanced analytical methods are required to make sense of this plethora of data successfully. The K-means clustering algorithm is used in the present research to analyse the data sent and received by different types of electronics. The first step of the research is collecting data, intending to create a representative sample of people using various devices and communication methods. After collecting data, preprocessing is necessary to ensure it can be analysed successfully. In the next step, the K-means algorithm classifies the information into subsets that stand for distinct modes of interaction. The primary objective of the research is to gain an improved understanding of these groups by demonstrating how users communicate, device communication, and possibilities for enhancing functionality and security.

The Internet of Things (IoT) has proliferated, transitioning from modest home automation to encompass sectors like healthcare, agriculture, transportation, and manufacturing. This evolution is characterized by devices' ability to autonomously gather, disseminate, and analyze data, leading to improved real-time decision-making, predictive insights, and customized user experiences. The ubiquity of IoT, while promising, introduces significant data security concerns. The vast number of interlinked devices and diverse and often insufficient security features make them vulnerable to cyber threats, emphasizing the need for robust security mechanisms. Intrusion Detection Systems (IDS) have traditionally acted as vital guards against such threats; however, with the ever-increasing data in the IoT, traditional IDS models, such as Naive Bayes, face processing speed and accuracy challenges. This paper introduces a novel model, "FE+NB," which merges advanced Feature Extraction (FE) with the Naive Bayes (NB) classifier. Central to this model is the "Temporal-Structural Synthesis" technique tailored for IoT traffic data, focusing on data compression, temporal and structural analyses, and Feature Selection (FS) using mutual information. Consequently, the model enhances efficiency and accuracy in Intrusion Detection (ID) in complex IoT networks.

Estimadas Editoras:El regreso a la llamada “normalidad” nos induce a pensar a que todo volverá a su estado basal previo al 2020. Sin embargo, la pandemia nos deja una herencia incierta en la salud mental de la población, la predisposición a la vulnerabilidad a diversas patologías psiquiátricas. Dentro de estas, el trauma en etapas tempranas, como los experimentados por los niños y adolescentes en el Perú durante estos años de pandemia, están asociados con la ideación suicida e intento de suicidio (1), ligados al pensamiento rumiante, impulsividad y comportamiento posterior. En el Perú, 10 millones 466 mil personas son menores de 18 años. De estos, en los últimos 3 meses del 2020, se obtuvo que el 54,0% de los hogares del país tiene entre sus miembros al menos una persona menor de 18 años (2). Los individuos afectados por trauma en etapas tempranas e incluso adultos que enfrentaron esta pandemia podrían transmitir multigeneracionalmente la vulnerabilidad en la población, como ya se ha estudiado desde víctimas del holocausto (3), hasta metaanálisis sobre la violencia intrafamiliar (4). Según la OMS, cada año se suicidan cerca de 703000 personas (5), siendo la cuarta causa de muerte entre los jóvenes de 15 a 19 años. Durante la pandemia, encontramos metaanálisis que nos exponen que en 38 estudios que describían a 120 076 participantes, el 12,1% (CI 9,3-15,2) presentaba ideación suicida (6). En otro estudio, de 308 596 participantes en 54 estudios, se observó una ideación suicida en el 10,81 % e intentos de suicidio en el 4,68 % (7).En el Perú, vemos un aumento de los casos de suicidio. Un estudio evaluando la mortalidad por suicidio del 2004 al 2013 nos muestra que en 3162 casos de suicidios (67,2% hombres), el grupo etario con mayor incidencia fue el de 20 a 29 años (28,7%) y el 49,2% ocurrieron por envenenamiento. La tasa de suicidios pasó de 0,46 (IC 95%: 0,38-0,55) a 1,13 (IC 95%: 1,01-1,25) por 100 000 habitantes en el 2004 y 2013 (8). Este aumento en casos de suicidio se ve contrastado en otro estudio de 2017 a 2019, donde observamos 1.666 casos de suicidio, siendo el 52,7% de lo observado entre el 2004 al 2013, pero en un tercio de ese tiempo. Observamos también que el 69,3% fueron varones; el grupo etario con mayor frecuencia fue el de 20 a 29 años de nuevo (27,8%); y que la media de edad al suicidio fue mayor en los varones (37,49 ± 18,96 frente a 27,86 ± 15,42; p < 0,001). Además, la tasa de suicidio aumentó del año 2017 (1,44 muertes/100 000 hab.) al 2019 (1,95 muertes/100 000hab.) (9). En el departamento de Cusco, se vio entre los años 2020 - 2022 un total de 242 casos de suicidio; de los cuales el 22% se dieron en la ciudad del Cusco, 68.5% corresponden a individuos del sexo masculino y el grupo etario más frecuente fue de 18 a 29 años con el 34.2% de los casos. El número de casos de suicidio en Cusco, como los casos a nivel nacional, también tiene una tendencia creciente al pasar de los años (10). Para enfrentar este desarrollo nocivo, obtener métodos de detección de riesgo suicida, que nos permitan una medición cuantificable, objetiva, sensibley específica sería una herramienta valiosa para nuestrapoblación y enfrentar la patología legada por la pandemia en la salud Particularmente, existen pruebas diagnósticas de utilidad en el abordaje de estas patologías. La inflamaciónen procesos de psiconeuroinmunoendocrinología cumple un papel importante en el comportamiento, enel estrés, ansiedad, depresión, ideación suicida, entre otros. Por esto, existe mucha utilidad en la mediciónde interleucinas, biomarcadores como el cortisol, proteína C reactiva, perfil lipídico, entre otros. Sin embargo, debido al alto costo de estos estudios en países en desarrollo como el Perú, podemos enfocarnosen pruebas inmunológicas que prometen tener utilidad como una medición indirecta de estos procesos. Yase ha estudiado otras patologías como la apendicitis, donde la evolución del leucograma y diversos testutilizando los valores leucocitarios son de utilidad para ver la progresión de la enfermedad (11). Estosdiferentes biomarcadores se pueden observar en lafigura 1.

El modelamiento de la dispersión geográfica de PM 10 producida por el sector ladrillero en el distrito de San Jerónimo, utilizando el software AERMOD VIEW10 fue realizado. De acuerdo con el protocolo USEPA, y siguiendo el programa Aermod View se realizó la medición de parámetros y valores in situ, en un horno ladrillero: dimensiones del horno, velocidad de salida del penacho, temperatura de salida de los gases, consumo de combustible, tiempo de cocción y materia prima. Los valores fueron ingresados al programa Aermod View en su versión 9.9.0 determinando el tipo de terreno e identificando las fuentes de emisión. Los resultados se muestran en el mapa de dispersión de PM 10 del sector ladrillero, donde se identificó que el punto de monitoreo CA-SJ-01 presenta una concentración de 133.12 μg/𝑚𝑚3 siendo el punto que sobrepasa los ECA para aire. Se concluye que existe una relación directa entre la dispersión de los contaminantes y los parámetros meteorológicos de velocidad y dirección del viento, validando el monitoreo de calidad de aire realizado por el OEFA.

This article aims to systematize the evidence regarding risk factors associated with COVID-19 reinfection. We conducted a systematic review of all the scientific publications available until August 2022. To ensure the inclusion of the most recent and relevant information, we searched the PubMed and Scopus databases. Thirty studies were reviewed, with a significant proportion being analytical observational case-control and cohort studies. Upon qualitative analysis of the available evidence, it appears that the probability of reinfection is higher for individuals who are not fully immunized when exposed to a new variant, females, those with pre-existing chronic diseases, individuals aged over 60, and those who have previously experienced severe symptoms of the disease or are immunocompromised. In conclusion, further analytical observational case-control studies are necessary to gain a better understanding of the risk factors associated with SARS-CoV-2 (COVID-19) reinfection.

Background The spread of the coronavirus disease 2019 (COVID-19) in Peru has been reported at the regional level, few studies have evaluated its spread at the provincial level, in which the mechanisms could be different. Methods We conducted an analytical, cross-sectional, multistage observational population study to assess the seroprevalence of SARS-COV-2 at the provincial and urban/rural levels in a high-altitude setting. The sampling unit was the household, including a randomly selected family member. Sampling was performed using a data collection sheet on clinical and epidemiological variables. Chemiluminescence tests were used to detect total anti-SARS-COV-2 antibodies (IgG and IgM simultaneously). The percentages were adjusted to the sampling design. Results The overall prevalence in the region of Cusco was 25.9%, with considerably different prevalence between the 13 provinces (from 15.9% in Acomayo to 40.1% in Canchis) and between rural (21.1%) and urban (31.7%) areas. In multivariable model, living in a rural area was a protective factor (adjusted prevalence ratio [aPR], 0.68; 95% confidence interval [CI], 0.61–0.76). Conclusions Geographic diversity and population density determine different prevalence rates, typically lower in rural areas, possibly due to natural social distancing or limited interaction with people at risk.

Major depressive disorder is the most common psychiatric disorder worldwide. To understand mechanisms and search for new approaches to treating depression, animal models are crucial. Chronic mild stress (CMS) is the most used animal model of depression. Although CMS is considered a robust model of depression, conflicting results have been reported for emotion-related behaviors, which the intrinsic characteristics of each rodent strain could explain. To further shed light on the impact of genetic background on the relevant parameters commonly addressed in depression, we examined the effect of 4-weeks CMS on anxiety and depression-related behaviors and body weight gain in three strain mice (BALB/c, C57BL/6, and CD1) of both sexes. CMS reduced body weight gain in C57BL/6NCrl and CD1 male mice. C57BL/6 animals exhibited a more pronounced anxious-like behavior than CD1 and BALB/c mice in the light-dark box (LDB) and the elevated plus maze (EPM) tests, whereas BALB/c animals exhibited the more robust depressive-like phenotype in the splash test (ST), tail suspension test (TST) and forced-swimming test (FST). Under CMS, exposure did not affect anxiety-related behaviors in any strain but induced depression-like behaviors strain-dependently. CMS C57BL/6 and CD1 mice of both sexes showed depression-like behaviors, and CMS BALB/c male mice exhibited reduced depressive behaviors in the FST. These results suggest a differential effect of stress, with the C57BL/6 strain being more vulnerable to stress than the CD1 and BALB/c strain mice. Furthermore, our findings emphasize the need for researchers to consider mouse strains and behavioral tests in their CMS experimental designs. Keywords: Animal model; Anxiety; Behavior; Depression; Sex differences; Stress vulnerability.

Objetivo: Correlacionar la ferritina sérica (FS) con la Hb e IE, y determinar el punto de corte de Hb para predecir DH en lactantes de 6 meses a 3400 m de altitud. Sujetos y Método: Se evaluaron 128 lactantes de 6 meses a 3.400 m de altitud. Se consideró variable independiente a la FS. Los IE y la Hb fueron las variables dependientes. La An en el lactante fue definida con una Hb < 13,4 g/dl. La DH se definió por FS < 12 ug/dL. Los datos se procesaron en el programa SPSS® versión 25. Se usó la correlación Spearman para el análisis bivariado. Se construyó la curva ROC para determinar el punto de corte de Hb para DH. Resultados: La mayor correlación de FS se observó con la hemoglobina corpuscular media (HCM), rho = 0,449 (p < 0,001) y el volumen corpuscular medio (VCM) rho = 0,423 (p < 0,001). El punto de corte de la Hb, según la FS, que define DH fue de 12,15 g/dL (curva ROC: 0,704; IC 95%: 0,597-0,811; p < 0,001). Conclusión: El VCM y la HCM presentaron mejor correlación con la FS. El modelo cúbico y logarítmico son los que representaron mejor estas relaciones respectivamente. La Hb < 12,15 g/dL permite diagnosticar DH en lactantes de 6 meses a 3400 m de altura.