Natural Killer T Cell Diversity and Immunotherapy.

Invariant natural killer T cells (iNKTs), a type of unconventional T cells, share features with NK cells and have an invariant T cell receptor (TCR), which recognizes lipid antigens loaded on CD1d molecules, a major histocompatibility complex class I (MHC-I)-like protein. This interaction produces the secretion of a wide array of cytokines by these cells, including interferon gamma (IFN-γ) and interleukin 4 (IL-4), allowing iNKTs to link innate with adaptive responses. Interestingly, molecules that bind CD1d have been identified that enable the modulation of these cells, highlighting their potential pro-inflammatory and immunosuppressive capacities, as required in different clinical settings. In this review, we summarize key features of iNKTs and current understandings of modulatory α-galactosylceramide (α-GalCer) variants, a model iNKT cell activator that can shift the outcome of adaptive immune responses. Furthermore, we discuss advances in the development of strategies that modulate these cells to target pathologies that are considerable healthcare burdens. Finally, we recapitulate findings supporting a role for iNKTs in infectious diseases and tumor immunotherapy.

Bifactor SEM and MIRT Structure of a 12-Item Human Immunodeficiency Virus Stigma Scale in Peruvian Adults.

BACKGROUND: The stigma associated with human immunodeficiency virus (HIV) can lead to prejudice and discrimination against people who have been infected by this virus, consequently, it is important to have a validated tool to measure this phenomenon. However, there is only 1 national precedent that has validated the scores of this instrument in its 21-item version. Therefore, this study examined the bifactor structural equation method (SEM) and multidimensional item response theory (MIRT) structure of a 12-item human immunodeficiency virus stigma scale in Peruvian adults. METHODS: We evaluated 342 patients (57.6% female and 42.45% male) diagnosed with HIV receiving highly active antiretroviral therapy (HAART) from a hospital located in East Lima, aged 18 to 45 years (M = 31.4, SD = 9.79). A SEM was used to test 2 measurement models, a 4-factor correlated oblique model and a bifactor model due to high interfactor relationships. RESULTS: Acceptable fit indices were identified for the oblique model (χ2/df = 1.26, SRMR = 0.044, RMSEA [90% CI] = 0.028 [0.000-0.047], CFI = 0.996, TLI = 0.994). In the same way, similar results were evident for the bifactor model (χ2/df = 1.14, SRMR = 0.039, RMSEA [90% CI] = 0.020 [0.000-0.044], CFI = 0.998, TLI = 0.997), however, in the latter it showed a greater explanation for the unidimensional model (H = 0.87, PUC = 0.82, LCA = 0.70), which was also evidenced by the bifactor MIRT analysis. CONCLUSION: It is concluded that the 12-item HIV Stigma Scale meets the psychometric properties of internal structure and unifactorial reliability.

Psychometric Properties of the Peruvian Version of the MOS Scale for Social Support in Cancer Patients and Convergent Network with Quality of Life.

Introduction: One of the key psychosocial factors that impact mental and emotional health is social support. While much research has been conducted on the role of social support in the lives of cancer patients, there is a lack of studies that consider populations who need specific tools to assess this concept. Purpose: The aim of this study was to evaluate the psychometric properties of the MOS Social Support Scale (1991) in 499 Peruvian cancer patients between the ages of 18 and 87 (M= 46.30, SD = 15.747). Methods: In this study, three models of the MOS were analyzed based on 19-item versions (four factor, second order and bifactor model). Results: The results showed a better psychometric fit in the 19-item bifactor model with optimal fit indices through the structural equation method (SB-χ2/df = 1.94, CFI = 0.966, TLI= 0.955, SRMR = 0.038 and RMSEA = 0.058). Additionally, there was evidence of configural, metric and scalar invariance with this instrument according to the gender of the surveyed cancer patients. Convergent validity using a network analysis approach revealed positive associations between social support dimensions and quality of life. Conclusion: Emotional support and positive interactions dimensions were found to be important interconnections in the overall network, as indicated by their greater centralities. Therefore, this instrument could be suggested as a reliable way to evaluate cancer patients and their perceived support.

Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System.

Background: People with depression are at increased risk for comorbidities; however, the clustering of comorbidity patterns in these patients is still unclear. Objective: The aim of the study was to identify latent comorbidity patterns and explore the comorbidity network structure that included 12 chronic conditions in adults diagnosed with depressive disorder. Methods: A cross-sectional study was conducted based on secondary data from the 2017 behavioral risk factor surveillance system (BRFSS) covering all 50 American states. A sample of 89,209 U.S. participants, 29,079 men and 60,063 women aged 18 years or older, was considered using exploratory graphical analysis (EGA), a statistical graphical model that includes algorithms for grouping and factoring variables in a multivariate system of network relationships. Results: The EGA findings show that the network presents 3 latent comorbidity patterns, i.e., that comorbidities are grouped into 3 factors. The first group was composed of 7 comorbidities (obesity, cancer, high blood pressure, high blood cholesterol, arthritis, kidney disease, and diabetes). The second pattern of latent comorbidity included the diagnosis of asthma and respiratory diseases. The last factor grouped 3 conditions (heart attack, coronary heart disease, and stroke). Hypertension reported higher measures of network centrality. Conclusion: Associations between chronic conditions were reported; furthermore, they were grouped into 3 latent dimensions of comorbidity and reported network factor loadings. The implementation of care and treatment guidelines and protocols for patients with depressive symptomatology and multimorbidity is suggested.

Association Between Emotional Eating, Sociodemographic Characteristics, Physical Activity, Sleep Duration, and Mental and Physical Health in Young Adults.

Background: Emotional eating (EmE) is one of the most common eating behaviors maladaptive among young adults, however, in the Peruvian context, it remains unexplored. Objective: The aim of the study was to determine the association between negative EmE, sociodemographic characteristics, physical activity, sleep duration, and mental and physical health in young adults. Methods: A cross-sectional study was conducted in 400 young Peruvian adults living in three regions of Peru (coast, jungle, and highlands). An online survey was used to collect information on sociodemographic characteristics, physical activity, sleep duration, depressive symptoms, anxiety, hypertension, and negative EmE. In addition, self-reported anthropometric data were collected to calculate body mass index (BMI). Results: Approximately 55.8% of women presented negative EmE. Logistic regression analysis revealed that participants aged 30-39 years were less likely to have negative EmE in both female and male gender, OR; 0.24, 95% CI; 0.08-0.66, p<0.01 and OR; 0.40, 95% CI; 0.16-0.97, p<0.05, respectively. Perform physical activity 3 to 4 times 5.22 (95% CI: 1.31-20.78), 1 to 2 times a week 5.77 (95% CI: 1.91-17.44), and never 15.18 (95% CI: 3.90-59.00) were associated with negative EmE. Moreover, sleeping less than 7 hours per day (OR; 2.26, 95% CI; 1.04-4.90), depressive symptoms (OR = 6.29, 95% CI: 1.27-31.19), anxiety (OR = 14.13, 95% CI: 2.46-80. 97, p<0.01), hypertension (OR = 7.58, 95% CI: 1.24-46.17), and BMI ≥25 (overweight/obese) (OR = 1.51, 95% CI: 1.66-3.41) were associated with negative EmE. Conclusion: The findings show that there is an association between negative EmE, sociodemographic characteristics, physical activity, sleep duration, and mental and physical health in young adults.

Representación de sistemas asociativos de red: el caso del miedo y la ansiedad por COVID-19 / Representation of associative network systems: the case of fear and anxiety by COVID-19

Un estudio de revisión de la presente revista refiere que la rápida propagación de la COVID- 19 por todo el mundo y las medidas para contener el impacto sin precedentes de esta pandemia, devenida en emergencia sanitaria internacional,1 han generado también problemas de salud mental como el estrés, la ansiedad, los síntomas depresivos, el insomnio, la negación, la ira y el miedo.2 Para atender la demanda de atención psicológica a los afectados,3 las herramientas empíricas, como las escalas validadas y los cuestionarios, son esenciales entre las medidas que ayudarían en el ejercicio de los profesionales de las ciencias clínicas en este dramático contexto sanitario.4 Entre las medidas psicológicas de mayor uso es la Fear of COVID-19 Scale (FCV-19S; 7 items), de Ahorsu y otros.5 y The Coronavirus Anxiety Scale (CAS; 5 ítems).6 En un estudio metanalítico integrado por 23 estudios y 19 978 participantes, se escogieron estos instrumentos debido a que el miedo y la ansiedad han sido reportados como las reacciones psicológicas más frecuentes,7 con una relación fuerte (r = 0,55) entre ambas, y cuyas magnitudes fueron mayores en comparación a otras variables de sintomatología psiquiátrica.7 Entre los factores externos prevalentes en relación con ambas variables destaca el sexo femenino, atribuible a las diferencias conocidas en los sistemas de respuesta al estrés en relación con los varones. En el sexo femenino se reporta un aumento mayor a las respuestas endocrinas, afectivas y de excitación al estrés que genera una mayor vulnerabilidad a la angustia psicológica,8 en especial en el personal sanitario, sector donde además predomina. Según una investigación...(AU)

Una alternativa de análisis de redes en la exploración de los estados de salud mental, condiciones crónicas y COVID-19 / An alternative network analysis in the exploration of mental health states, chronic conditions and COVID-19

El análisis de redes es una técnica estadística gráfica que permite visualizar e interpretar intuitivamente asociaciones entre síntomas y múltiples variables vinculadas al funcionamiento y espectro de diversas condiciones de salud. Siendo de relevancia clínica en el contexto actual de la pandemia de COVID-19, y ante su poca difusión en Sudamérica, se tuvo como objetivo un análisis narrativo de este modelo de red durante la pandemia. Se realizó una revisión narrativa de los estudios empíricos publicados desde mayo de 2020 a julio de 2021 en la base de datos de PubMed y ScienceDirect. Se seleccionaron las investigaciones que utilizaron redes psicométricas de correlación parcial en participantes evaluados durante la pandemia de COVID-19. Esta revisión reporta 13 estudios de red que utilizaron mayormente síntomas relacionados a la ansiedad (7 estudios), depresión (6 estudios) y estrés (6 estudios). La información resultante se agrupa en 3 grupos (publicaciones en revistas de psiquiatría, ciencias psicológicas, medicina y afines). La revisión presentada refiere que este análisis de red permite una nueva forma de identificar aspectos clínicos importantes como la comorbilidad, concurrencia de los síntomas y medidas no sintomatológicas, agrupaciones de síntomas con otras variables de naturaleza latente u observable que comparten una causa común, la exploración de nuevas hipótesis clínicas holísticas con variables epidemiológicas, psicológicas, biomédicas y contextuales de mayor interés, como la comparación de sistemas de asociación causal de variables de múltiples niveles en el proceso psicobiológico y sus factores de riesgo y protección en varios periodos de tiempo.

Summary Network analysis is a graphical statistical technique that allows visualizing and intuitively interpreting the spectrum of various health conditions, being of clinical relevance in the current context of the COVID-19 pandemic. Given its limited dissemination in South America, we aimed at a narrative analysis of this network model during the pandemic. A narrative review of empirical studies published from May 2020 to July 2021 in the PubMed and ScienceDirect database was performed. We selected research that used partial correlation psychometric networks in participants assessed during the COVID-19 pandemic. This review reports 13 network studies that used mostly symptoms related to anxiety (7 studies), depression (6 studies) and stress (6 studies). The resulting information is grouped into 3 clusters (publications in psychiatry, psychological sciences, medicine and related journals). The presented review refers that this network analysis allows a new way of identifying important clinical aspects such as comorbidity, concurrence of symptoms and nonsymptomatologic measures, groupings of symptoms with other variables of latent or observable nature that share a major common cause, the exploration of new holistic clinical hypotheses with epidemiological, psychological, biomedical and contextual variables of major current interest such as the comparison of causal association systems of multilevel variables in the psychobiological process, and their risk and protective factors in various time periods.

Etiology and the challenge of diagnostic testing of community-acquired pneumonia in children and adolescents.

BACKGROUND: Pneumonia is the leading cause of mortality in pediatric population. The etiology of pneumonia in this population is variable and changes according to age and disease severity and where the study is conducted. Our aim was to determine the etiology of community-acquired pneumonia (CAP) in children aged 1 month to 17 years admitted to 13 Colombian hospitals. METHODS: Prospective cohort study. Hospitalized children with radiologically confirmed CAP and ≤ 15 days of symptoms were included and followed together with a control group. Induced sputum (IS) was submitted for stains and cultures for pyogenic bacteria and Mycobacterium tuberculosis, and multiplex PCR (mPCR) for bacteria and viruses; urinary antigens for pneumococcus and Legionella pneumophila; nasopharyngeal swabs for viruses, and paired serology for atypical bacteria and viruses. Additional cultures were taken at the discretion of primary care pediatricians. RESULTS: Among 525 children with CAP, 71.6% had non-severe pneumonia; 24.8% severe and 3.6% very severe pneumonia, and no fatal cases. At least one microorganism was identified in 84% of children and 61% were of mixed etiology; 72% had at least one respiratory virus, 28% pyogenic bacteria and 21% atypical bacteria. Respiratory syncytial virus, Parainfluenza, Rhinovirus, Influenza, Mycoplasma pneumoniae, Adenovirus and Streptococcus pneumoniae were the most common etiologies of CAP. Respiratory syncytial virus was more frequent in children under 2 years and in severe pneumonia. Tuberculosis was diagnosed in 2.3% of children. IS was the most useful specimen to identify the etiology (33.6%), and blood cultures were positive in 3.6%. The concordance between all available diagnostic tests was low. A high percentage of healthy children were colonized by S. pneumoniae and Haemophilus influenzae, or were infected by Parainfluenza, Rhinovirus, Influenza and Adenovirus. CONCLUSIONS: Respiratory viruses are the most frequent etiology of CAP in children and adolescents, in particular in those under 5 years. This study shows the challenges in making an etiologic diagnosis of CAP in pediatric population because of the poor concordance between tests and the high percentage of multiple microorganisms in healthy children. IS is useful for CAP diagnosis in pediatric population.

Consumption of Alcoholic Beverages Associated With Physical Health Status in Adults: Secondary Analysis of the Health Information National Trends Survey Data.

INTRODUCTION: Alcohol consumption constitutes one of the main modifiable risk factors that contribute to the increase in the global burden of non-communicable diseases (NCDs). The objective of this study was to determine the effects of the consumption of alcoholic beverages on the state of physical health and its equivalence according to gender. METHODS: Cross-sectional data from the Health Information National Trends Survey (HINTS) of the National Cancer Institute (NCI) (n = 3865), collected during 2020 were used. Structural equation modeling was applied to assess the fit of the model, which included the prediction of measures of alcohol consumption in physical health and the equivalence of measurements of the proposed structural model in men and women. RESULTS: The proposed structural model reported adequate goodness-of-fit indices (SBχ²/gl = 3.817, CFI = 0.984, TLI = 0.968, RMSEA [90% CI] = 0.027 [0.016-0.039]; SRMR = 0.016). Frequent alcohol consumption had a negative effect on physical health (b = -0.13, P < .01). Similarly, occasional alcohol consumption negatively predicted elevated BMI and chronic conditions such as, diabetes, hypertension, CVD, and cancer (b = -0.09, P < .01). In addition, drinking patterns of alcoholic beverages affect physical health in equal ways for men and women. CONCLUSION: The findings highlight that frequent and occasional alcohol consumption significantly affected physical health in a negative way. Future interventions could address ways to encourage the adoption of a healthy lifestyle to reduce the risks of chronic conditions derived from excessive alcohol consumption.

Is It Possible to Differentiate Pneumocystis jirovecii Pneumonia and Colonization in the Immunocompromised Patients with Pneumonia?

Respiratory sample staining is a standard tool used to diagnose Pneumocystis jirovecii pneumonia (PjP). Although molecular tests are more sensitive, their interpretation can be difficult due to the potential of colonization. We aimed to validate a Pneumocystis jirovecii (Pj) real-time PCR (qPCR) assay in bronchoscopic bronchoalveolar lavage (BAL) and oropharyngeal washes (OW). We included 158 immunosuppressed patients with pneumonia, 35 lung cancer patients who underwent BAL, and 20 healthy individuals. We used a SYBR green qPCR assay to look for a 103 bp fragment of the Pj mtLSU rRNA gene in BAL and OW. We calculated the qPCR cut-off as well as the analytical and diagnostic characteristics. The qPCR was positive in 67.8% of BAL samples from the immunocompromised patients. The established cut-off for discriminating between disease and colonization was Ct 24.53 for BAL samples. In the immunosuppressed group, qPCR detected all 25 microscopy-positive PjP cases, plus three additional cases. Pj colonization in the immunocompromised group was 66.2%, while in the cancer group, colonization rates were 48%. qPCR was ineffective at diagnosing PjP in the OW samples. This new qPCR allowed for reliable diagnosis of PjP, and differentiation between PjP disease and colonization in BAL of immunocompromised patients with pneumonia.