bluuebunny/crossref_metadata_2025 huggingface dataset:
Explore the shared molecular mechanism between dermatomyositis and nasopharyngeal cancer by bioinformatic analysis
Authors: Zhong Xiuqin , Shang Jingjing , Zhang Rongwei , Zhang Xiuling , Yu Le , Niu Haitao , Duan Xinwang
Published: May 2024

Background

Dermatomyositis (DM) is prone to nasopharyngeal carcinoma (NPC), but the mechanism is unclear. This study aimed to explore the potential pathogenesis of DM and NPC.

Methods

The datasets GSE46239, GSE142807, GSE12452, and GSE53819 were downloaded from the GEO dataset. The disease co-expression module was obtained by R-package WGCNA. We built PPI networks for the key modules. ClueGO was used to analyze functional enrichment for the key modules. DEG analysis was performed with the R-package "limma". R-package “pROC” was applied to assess the diagnostic performance of hub genes. MiRNA-mRNA networks were constructed using MiRTarBase and miRWalk databases.

Results

The key modules that positively correlated with NPC and DM were found. Its intersecting genes were enriched in the negative regulation of viral gene replication pathway. Similarly, overlapping down-regulated DEGs in DM and NPC were also enriched in negatively regulated viral gene replication. Finally, we identified 10 hub genes that primarily regulate viral biological processes and type I interferon responses. Four key genes (GBP1, IFIH1, IFIT3, BST2) showed strong diagnostic performance, with AUC>0.8. In both DM and NPC, the expression of key genes was correlated with macrophage infiltration level. Based on hub genes’ miRNA-mRNA network, hsa-miR-146a plays a vital role in DM-associated NPC.

Conclusions

Our research discovered pivot genes between DM and NPC. Viral gene replication and response to type I interferon may be the crucial bridge between DM and NPC. By regulating hub genes, MiR-146a will provide new strategies for diagnosis and treatment in DM complicated by NPC patients. For individuals with persistent viral replication in DM, screening for nasopharyngeal cancer is necessary.
Bayesian and non-bayesian inference for logistic-exponential distribution using improved adaptive type-II progressively censored data
Authors: Dutta Subhankar , Alqifari Hana N. , Almohaimeed Amani
Published: May 2024

Improved adaptive type-II progressive censoring schemes (IAT-II PCS) are increasingly being used to estimate parameters and reliability characteristics of lifetime distributions, leading to more accurate and reliable estimates. The logistic exponential distribution (LED), a flexible distribution with five hazard rate forms, is employed in several fields, including lifetime, financial, and environmental data. This research aims to enhance the accuracy and reliability estimation capabilities for the logistic exponential distribution under IAT-II PCS. By developing novel statistical inference methods, we can better understand the behavior of failure times, allow for more accurate decision-making, and improve the overall reliability of the model. In this research, we consider both classical and Bayesian techniques. The classical technique involves constructing maximum likelihood estimators of the model parameters and their asymptotic covariance matrix, followed by estimating the distribution’s reliability using survival and hazard functions. The delta approach is used to create estimated confidence intervals for the model parameters. In the Bayesian technique, prior information about the LED parameters is used to estimate the posterior distribution of the parameters, which is derived using Bayes’ theorem. The model’s reliability is determined by computing the posterior predictive distribution of the survival or hazard functions. Extensive simulation studies and real-data applications assess the effectiveness of the proposed methods and evaluate their performance against existing methods.
Predicting malaria outbreak in The Gambia using machine learning techniques
Authors: Khan Ousman , Ajadi Jimoh Olawale , Hossain M. Pear
Published: May 2024

Malaria is the most common cause of death among the parasitic diseases. Malaria continues to pose a growing threat to the public health and economic growth of nations in the tropical and subtropical parts of the world. This study aims to address this challenge by developing a predictive model for malaria outbreaks in each district of The Gambia, leveraging historical meteorological data. To achieve this objective, we employ and compare the performance of eight machine learning algorithms, including C5.0 decision trees, artificial neural networks, k-nearest neighbors, support vector machines with linear and radial kernels, logistic regression, extreme gradient boosting, and random forests. The models are evaluated using 10-fold cross-validation during the training phase, repeated five times to ensure robust validation. Our findings reveal that extreme gradient boosting and decision trees exhibit the highest prediction accuracy on the testing set, achieving 93.3% accuracy, followed closely by random forests with 91.5% accuracy. In contrast, the support vector machine with a linear kernel performs less favorably, showing a prediction accuracy of 84.8% and underperforming in specificity analysis. Notably, the integration of both climatic and non-climatic features proves to be a crucial factor in accurately predicting malaria outbreaks in The Gambia.
DB-EAC and LSTR: DBnet based seal text detection and Lightweight Seal Text Recognition
Authors: Huang Baohua , Bai Aokun , Wu Yuqiong , Yang Chanjuan , Sun Han
Published: May 2024

Recognition of the key text of the Chinese seal can speed up the approval of documents, and improve the office efficiency of enterprises or government administrative departments. Due to image blurring and occlusion, the accuracy of Chinese seal recognition is low. In addition, the real dataset is very limited. In order to solve these problems, we improve the differentiable binarization detection algorithm (DBnet) to construct a model DB-ECA for text region detection, and propose a model named LSTR (Lightweight Seal Text Recognition) for text recognition. The efficient channel attention module is added to the differentiable binarization network to solve the feature pyramid conflict, and the convolutional layer network structure is improved to delay downsampling for reducing semantic feature loss. LSTR uses a lightweight CNN more suitable for small-sample generalization, and dynamically fuses positional and visual information through a self-attention-based inference layer to predict the label distribution of feature sequences in parallel. The inference layer not only solves the weak discriminative power of CNN in the shallow layer, but also facilitates CTC (Connectionist Temporal Classification) to accurately align the feature region with the target character. Experiments on the homemade dataset in this paper, DB-ECA compared with the other five commonly used detection models, the precision, recall, F-measure are the best effect of 90.29, 85.17, 87.65, respectively. LSTR compared with the other five kinds of recognition models in the last three years, to achieve the highest effect of accuracy 91.29%, and has the advantages of a small number of parameters and fast inference. The experimental results fully prove the innovation and effectiveness of our model.
Hepatitis B and C viral coinfection and associated factors among HIV-positive patients attending ART clinics of Afar regional state, northeast Ethiopia
Authors: Hagos Yemane Mengsteab , Yalew Gebrehiwet Tesfay , Meles Hadush Negash , Tsegay Ephrem , Lemelem Mulu , Wasihun Araya Gebreyesus
Published: May 2024

Background

Hepatitis B (HBV) and C virus (HCV) coinfection are the major causes of liver-related morbidity and mortality among people living with Human Immunodeficiency Virus (HIV). The burden of hepatitis among HIV-positive individuals has not been studied in the Afar region. Therefore, this study aimed to determine the prevalence of HBV and HCV coinfection and associated factors among HIV-positive patients in Afar Regional State, northeast Ethiopia.

Methods

A cross-sectional study was conducted on 477 HIV-positive patients between February 2019 and May 2019. A structured and pretested questionnaire was used to collect socio-demographic data and associated factors. Five milliliters of blood was collected, and Hepatitis B surface antigen (HBsAg) and HCV antibodies were detected using rapid test kits. Positive samples were confirmed using enzyme-linked immunosorbent assay (ELISA). Binary and multivariable logistic regression analyses were performed to identify associated factors. Statistical significance was set atP<0.05.

Results

Among the 477 study participants, 320/477(67.1%) of them were females and 157(32.9%) males. The overall prevalence of HIV-HBV and HIV-HCV coinfection was 25(5.2%) and 7(1.5%), respectively. Multi-sexual practice was significantly associated with HIV-HBV coinfection (AOR = 5.3; 95% CI: 1.2–24.4,P= 0.032).

Conclusion

The prevalence of both HIV-HBV and HIV-HCV coinfection was intermediate. Multi-sexual practice was significantly associated with HIV-HBV coinfection. Screening of all HIV-positive patients for HBV and HCV and health education regarding the transmission modes should be considered.
Norms for gender stereotypically congruent, stereotypically incongruent, semantically correct, and semantically incorrect sentences in Polish and English
Authors: Jankowiak Katarzyna , Naranowicz Marcin , Skałba Anna , Drążkowski Dariusz , Pawelczyk Joanna
Published: May 2024

The present contribution provides ratings for a database of gender stereotypically congruent, stereotypically incongruent, semantically correct, and semantically incorrect sentences in Polish and English. A total of 942 volunteers rated 480 sentences (120 per condition) in each language in terms of their meaningfulness, probability of use, and stereotypicality. The stimuli were highly controlled for their length and critical words, which were shared across the conditions. The results of the ratings revealed that stereotypically incongruent sentences were consciously evaluated as both less meaningful and probable to use relative to sentences that adhere to stereotype-driven expectations regarding males and females, indicating that stereotype violations communicated through language exert influence on language perception. Furthermore, the results yielded a stronger internalization of gender stereotypes among sex-typed individuals, thus pointing to the crucial role of gender schema in the sensitivity to gender stereotypical attributes. The ratings reported in the present article aim to broaden researchers’ stimulus choices and allow for consistency across different laboratories and research projects on gender stereotype processing. The adaptation of this database to other languages or cultures could also enable a cross-cultural comparison of empirical findings on stereotype processing.
Attention pyramid pooling network for artificial diagnosis on pulmonary nodules
Authors: Wang Hongfeng , Zhu Hai , Ding Lihua , Yang Kaili
Published: May 2024

The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. However, lung nodules can be difficult to detect and classify, from CT images since different imaging modalities may provide varying levels of detail and clarity. Besides, the existing convolutional neural network may struggle to detect nodules that are small or located in difficult-to-detect regions of the lung. Therefore, the attention pyramid pooling network (APPN) is proposed to identify and classify lung nodules. First, a strong feature extractor, named vgg16, is used to obtain features from CT images. Then, the attention primary pyramid module is proposed by combining the attention mechanism and pyramid pooling module, which allows for the fusion of features at different scales and focuses on the most important features for nodule classification. Finally, we use the gated spatial memory technique to decode the general features, which is able to extract more accurate features for classifying lung nodules. The experimental results on the LIDC-IDRI dataset show that the APPN can achieve highly accurate and effective for classifying lung nodules, with sensitivity of 87.59%, specificity of 90.46%, accuracy of 88.47%, positive predictive value of 95.41%, negative predictive value of 76.29% and area under receiver operating characteristic curve of 0.914.
Potential model of Scalesia pedunculata carbon sequestration through restoration efforts in agricultural fields of Galapagos
Authors: Velasco Nicolás , Diaz Patricia Jaramillo
Published: May 2024

Scalesia pendunculata Hook.f. is the dominant tree in several highlands’ areas of the Galapagos Archipelago, yet in inhabited islands the conversion to agricultural fields has reduced its cover. The transition to agroforestry systems including the species shows promising scenarios to restore its cover and to provide ecosystem services such as carbon sequestration. Here, based on field gathered data, we model the potential contribution of S. pedunculata stands in the carbon sequestration of Galapagos. Between 2013–2021, 426 S. pedunculata seedlings were planted in the highlands of Santa Cruz and Floreana islands using several restoration technologies, and their height and survival were monitored every three months. A sub-sample of 276 trees alive since 2020 was used to estimate the DBH based on plant age and height. Based on scientific literature, biomass and carbon content were estimated across time. The final modelling included the density of plants in the restoration sites, estimated DBH, potential survival by restoration treatment, and a Brownian noise to add stochastic events. Overall, survival of S. pedunculata was high in control and slightly increased by most restoration treatments. A stand of 530 trees/ha was projected to sequester ~21 Mg C/ha in 10 years. If this is replicated over all Galapagos coffee production would contribute to the reduction of -1.062% of the Galapagos carbon footprint for the same period. This study adds to compiling benefits of restoring Galapagos flora.
Introducing the trier univalence neutrality ambivalence (TUNA) database: A picture database differentiating complex attitudes
Authors: Hahn Lena , Buttlar Benjamin , Künne Ria , Walther Eva
Published: May 2024

Using validated stimulus material is crucial for ensuring research comparability and replicability. However, many databases rely solely on bidimensional valence ratings, ranging from negative to positive. While this material might be appropriate for certain studies, it does not reflect the complexity of attitudes and therefore might hamper the unambiguous interpretation of some study results. In fact, most databases cannot differentiate between neutral (i.e., neither positive nor negative) and ambivalent (i.e., simultaneously positive and negative) attitudes. Consequently, even presumably univalent (only positive or negative) stimuli cannot be clearly distinguished from ambivalent ones when selected via bipolar rating scales. In the present research, we introduce the Trier Univalence Neutrality Ambivalence (TUNA) database, a database containing 304,262 validation ratings from heterogeneous samples of 3,232 participants and at least 20 (M = 27.3, SD = 4.84) ratings per self-report scale per picture for a variety of attitude objects on split semantic differential scales. As these scales measure positive and negative evaluations independently, the TUNA database allows to distinguish univalence, neutrality, and ambivalence (i.e., potential ambivalence). TUNA also goes beyond previous databases by validating the stimulus materials on affective outcomes such as experiences of conflict (i.e., felt ambivalence), arousal, anger, disgust, and empathy. The TUNA database consists of 796 pictures and is compatible with other popular databases. It sets a focus on food pictures in various forms (e.g., raw vs. cooked, non-processed vs. highly processed), but includes pictures of other objects that are typically used in research to study univalent (e.g., flowers) and ambivalent (e.g., money, cars) attitudes for comparison. Furthermore, to facilitate the stimulus selection the TUNA database has an accompanying desktop app that allows easy stimulus selection via a multitude of filter options.
Research on the spatial and temporal patterns of ozone concentration and population health effects in the Central Plains Urban Agglomeration from 2017 to 2020
Authors: Yan Jun , Wang Xinying , Zhang Jiyuan , Qin Zeyu , Wang Ting , Tian Qingzhi , Zhong Shizhen
Published: May 2024

Fine particulate matter (PM2.5) and near-surface ozone (O3) are the main atmospheric pollutants in China. Long-term exposure to high ozone concentrations adversely affects human health. It is of great significance to systematically analyze the spatiotemporal evolution mechanism and health effects of ozone pollution. Based on the ozone data of 91 monitoring stations in the Central Plains Urban Agglomeration from 2017 to 2020, the research used Kriging method and spatial autocorrelation analysis to investigate the spatiotemporal variations of ozone concentration. Additionally, the study assessed the health effects of ozone on the population using the population exposure risk model and exposure-response relationship model. The results indicated that: (1) The number of premature deaths caused by ozone pollution in the warm season were 37,053 at 95% confidence interval (95% CI: 28,190–45,930) in 2017, 37,685 (95% CI: 28,669–46,713) in 2018, and 37,655 (95% CI: 28,647–46,676) in 2019. (2) The ozone concentration of the Central Plains urban agglomeration showed a decreasing trend throughout the year and during the warm season from 2017 to 2020, there are two peaks monthly, one is June, and the other is September. (3) In the warm season, the high-risk areas of population exposure to ozone in the Central Plains Urban Agglomeration were mainly concentrated in urban areas. In general, the population exposure risk of the south is lower than that of the north. The number of premature deaths attributed to ozone concentration during the warm season has decreased, but some southern cities such as Xinyang and Zhumadian have also seen an increase in premature deaths. China has achieved significant results in air pollution control, but in areas with high ozone concentrations and high population density, the health burden caused by air pollution remains heavy, and stricter air pollution control policies need to be implemented.
A qualitative exploration of the challenges providers experience during peripartum management of patients with a body mass index ≥ 50 kg/m2 and recommendations for improvement
Authors: Kominiarek Michelle A. , Lyleroehr Madison , Torres Jissell
Published: May 2024

Background

The objective of this research was to conduct a qualitative study among a diverse group of providers to identify their clinical needs, barriers, and adverse safety events in the peripartum care of people with a body mass index (BMI) ≥ 50 kg/m2.

Methods

Obstetricians, anesthesiologists, certified nurse midwives, nurse practitioners, and nurses were invited to participate in focus group discussions if they were employed at the hospital for >6 months. Key concepts in the focus group guide included: (1) Discussion of challenging situations, (2) Current peripartum management approaches, (3) Patient and family knowledge and counseling, (4) Design and implementation of a guideline (e.g., checklist or toolkit) for peripartum care. The audiotaped focus groups were transcribed verbatim, uploaded to a qualitative analysis software program, and analyzed using inductive and constant comparative approaches. Emerging themes were summarized along with representative quotes.

Results

Five focus groups of 27 providers were completed in 2023. The themes included staffing (level of experience, nursing-patient ratios, safety concerns), equipment (limitations of transfer mats, need for larger sizes, location for blood pressure cuff, patient embarrassment), titrating oxytocin (lack of guidelines, range of uses), monitoring fetal heart rate and contractions, patient positioning, and communication (lack of patient feedback, need for bias training, need for interdisciplinary relationships). Providers gave examples of items to include in a “BMI cart” and suggestions for a guideline including designated rooms for patients with a BMI ≥ 50 kg/m2, defining nursing ratios and oxytocin titration plans, postpartum incentive spirometer, and touch points with providers (nursing, physicians) at every shift change.

Conclusions

Providers discussed a range of challenges and described how current approaches to care may negatively affect the peripartum experience and pose threats to safety for patients with a BMI ≥ 50 kg/m2 and their providers. We gathered information on improving equipment and communication among providers.
Echinatin attenuates acute lung injury and inflammatory responses via TAK1-MAPK/NF-κB and Keap1-Nrf2-HO-1 signaling pathways in macrophages
Authors: Luo Liuling , Wang Huan , Xiong Jinrui , Chen Xiaorui , Shen Xiaofei , Zhang Hai
Published: May 2024

Echinatin is an active ingredient in licorice, a traditional Chinese medicine used in the treatment of inflammatory disorders. However, the protective effect and underlying mechanism of echinatin against acute lung injury (ALI) is still unclear. Herein, we aimed to explore echinatin-mediated anti-inflammatory effects on lipopolysaccharide (LPS)-stimulated ALI and its molecular mechanisms in macrophages. In vitro, echinatin markedly decreased the levels of nitric oxide (NO) and prostaglandin E2 (PGE2) in LPS-stimulated murine MH-S alveolar macrophages and RAW264.7 macrophages by suppressing inducible nitric oxide synthase and cyclooxygenase-2 (COX-2) expression. Furthermore, echinatin reduced LPS-induced mRNA expression and release of interleukin-1β (IL-1β) and IL-6 in RAW264.7 cells. Western blotting and CETSA showed that echinatin repressed LPS-induced activation of mitogen-activated protein kinase (MAPK) and nuclear factor-kappa B (NF-κB) pathways through targeting transforming growth factor-beta-activated kinase 1 (TAK1). Furthermore, echinatin directly interacted with Kelch-like ECH-associated protein 1 (Keap1) and activated the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway to enhance heme oxygenase-1 (HO-1) expression. In vivo, echinatin ameliorated LPS-induced lung inflammatory injury, and reduced production of IL-1β and IL-6. These findings demonstrated that echinatin exerted anti-inflammatory effects in vitro and in vivo, via blocking the TAK1-MAPK/NF-κB pathway and activating the Keap1-Nrf2-HO-1 pathway.
Machine learning for the detection and diagnosis of cognitive impairment in Parkinson’s Disease: A systematic review
Authors: Altham Callum , Zhang Huaizhong , Pereira Ella
Published: May 2024

Background

Parkinson’s Disease is the second most common neurological disease in over 60s. Cognitive impairment is a major clinical symptom, with risk of severe dysfunction up to 20 years post-diagnosis. Processes for detection and diagnosis of cognitive impairments are not sufficient to predict decline at an early stage for significant impact. Ageing populations, neurologist shortages and subjective interpretations reduce the effectiveness of decisions and diagnoses. Researchers are now utilising machine learning for detection and diagnosis of cognitive impairment based on symptom presentation and clinical investigation. This work aims to provide an overview of published studies applying machine learning to detecting and diagnosing cognitive impairment, evaluate the feasibility of implemented methods, their impacts, and provide suitable recommendations for methods, modalities and outcomes.

Methods

To provide an overview of the machine learning techniques, data sources and modalities used for detection and diagnosis of cognitive impairment in Parkinson’s Disease, we conducted a review of studies published on the PubMed, IEEE Xplore, Scopus and ScienceDirect databases. 70 studies were included in this review, with the most relevant information extracted from each. From each study, strategy, modalities, sources, methods and outcomes were extracted.

Results

Literatures demonstrate that machine learning techniques have potential to provide considerable insight into investigation of cognitive impairment in Parkinson’s Disease. Our review demonstrates the versatility of machine learning in analysing a wide range of different modalities for the detection and diagnosis of cognitive impairment in Parkinson’s Disease, including imaging, EEG, speech and more, yielding notable diagnostic accuracy.

Conclusions

Machine learning based interventions have the potential to glean meaningful insight from data, and may offer non-invasive means of enhancing cognitive impairment assessment, providing clear and formidable potential for implementation of machine learning into clinical practice.
Acute strength exercise training impacts differently the HERV-W expression and inflammatory biomarkers in resistance exercise training individuals
Authors: Morais Lucas Vinicius , dos Santos Samuel Nascimento , Gomes Tabatah Hellen , Malta Romano Camila , Colombo-Souza Patricia , Amaral Jonatas Bussador , Shio Marina Tiemi , Neves Lucas Melo , Bachi André Luis Lacerda , França Carolina Nunes , Nali Luiz Henrique da Silva
Published: May 2024

Background

Human Endogenous Retroviruses (HERVs) are fossil viruses that composes 8% of the human genome and plays several important roles in human physiology, including muscle repair/myogenesis. It is believed that inflammation may also regulate HERV expression, and therefore may contribute in the muscle repair, especially after training exercise. Hence, this study aimed to assess the level of HERVs expression and inflammation profile in practitioners’ resistance exercises after an acute strength training session.

Methods

Healthy volunteers were separated in regular practitioners of resistance exercise training group (REG, n = 27) and non-trained individuals (Control Group, n = 20). All individuals performed a strength exercise section. Blood samples were collected before the exercise (T0) and 45 minutes after the training session (T1). HERV-K (HML1-10) and W were relatively quantified, cytokine concentration and circulating microparticles were assessed.

Results

REG presented higher level of HERV-W expression (~2.5 fold change) than CG at T1 (p<0.01). No difference was observed in the levels of HERV-K expression between the groups as well as the time points. Higher serum TNF-α and IL-10 levels were verified post-training session in REG and CG (p<0.01), and in REG was found a positive correlation between the levels of TNF-α at T1 and IL-10 at T0 (p = 0.01). Finally, a lower endothelial microparticle percentage was observed in REG at T1 than in T0 (p = 0.04).

Conclusion

REG individuals exhibited a significant upregulation of HERV-W and modulation of inflammatory markers when compared to CG. This combined effect could potentially support the process of skeletal muscle repair in the exercised individuals.
Reflexión sobre la Relevancia de la Investigación Cualitativa y/o Fenomenológica en la Diabetes
Authors: Marrero González Cristo Manuel , García Hernández Alfonso Miguel
Published: May 2024

Objeto del presente ensayo reflexivo: Mostrar y reflexionar sobre la utilidad que tiene la investigación cualitativa y/o fenomenológica en la atención del paciente que presenta diabetes. Desarrollo: la atención integral de una forma biopsicosocial, cultural y espiritual tanto al paciente como a la familia del mismo por parte del profesional sanitario, juega un papel importante a la hora de tener calidad de vida en el nuevo estilo de vida. Conclusiones y reflexiones finales: La investigación cualitativa en enfermería, ayuda a interpretar el sufrimiento del paciente, su relación con su entorno social y cultural y sus sentimientos e inquietudes dentro de la diabetes.
Violencia en pareja en personas seropositivas: una revisión sistemática
Authors: Rodríguez Otero Luis Manuel , Mancinas Espinoza Sandra Elizabeth
Published: May 2024

El presente trabajo tiene como objetivo, caracterizar la violencia en pareja en personas con seropositividad (prevalencia, tipos de acciones violentas, variables de riesgo/ protectoras y consecuencias), para lo cual se realizó una revisión sistemática a través del protocolo PRISMA. La búsqueda de artículos se realizó en Scopus, Web of Science, Eric, Scielo y Pubmed publicados hasta 2021. Se encontraron 113 artículos, de los cuales 22 cumplieron con los criterios de elegibilidad. Los resultados indican que la violencia en pareja en personas seropositivas, además de manifestarse de manera física, psicológica, patrimonial, sexual y verbal, se puede presentar a través del uso del VIH para ejercer la violencia. La prevalencia varía en función del contexto geográfico en un intervalo del 19,6% al 43,1%; la cual es superior en población migrante y en hombres que tienen sexo con hombres (HSH) mujeres seropositivas, parejas no heterosexuales y en parejas en la que ambos miembros son seropositivos. Las variables de riesgo/ protectoras identificadas se asociaron con las dimensiones: informativas, motivacionales, de habilidades conductuales, sociodemográficas, culturales, de salud, sociofamiliares y políticas. Asimismo, se evidenciaron consecuencias sociales, económicas y de salud.
Salud Mental en enfermeras al cuidado de pacientes en área COVID: estudio de caso
Authors: Jiménez-Macías Iván Ulianov , Medina Mendoza Eudes Jairo , Silva Magaña Guillermo
Published: May 2024

La enfermería es la labor que abarca la atención autónoma a personas de todas las edades, familias, grupos y comunidades, la principal característica y esencia es el cuidado, implica establecer una relación de comprensión y acompañamiento de manera integral, convirtiéndolos en los principales cuidadores formales en la asistencia, lo que pone de manifiesto la necesidad de mirar su salud mental y bienestar del personal de enfermería. El objetivo fue describir el impacto en la salud mental de un profesional de la enfermería en la atención a pacientes del área COVID en tiempos de pandemia, en el periodo 2022-2023. Se realizó un estudio cualitativo, primero mediante el análisis documental y posteriormente mediante el método fenomenológico, descriptivo con base en el estudio de caso, considerando la temporalidad en tres momentos, antes, durante y después de la pandemia por COVID. Los hallazgos dan constancia, de cambios e impactos a nivel biológico, psicológico, social y espiritual que derivan en afectaciones en salud mental que se experimentaron, y, por otro lado, de la escasez acciones para dotar a los profesionales de la salud de un acompañamiento, capacitación y sensibilización en salud mental para la mejora de su labor y bienestar personal.
La labor del Protomedicato en la salud pública en el virreinato del Perú
Authors: Rivasplata Varillas Paula Ermila
Published: May 2024

El objetivo de la presente investigación es conocer el papel que cumplió el Protomedicato en la salud publica en el virreinato del Perú. La metodología utilizada fue la narración histórica siguiendo el método heurístico y hermenéutico, utilizando fuentes primarias documentales de archivos históricos peruanos y españoles. El resultado obtenido fue confirmar que el Protomedicato veló por la salud de los vecinos y que tenía carácter administrativo judicial y sus funciones principales fueron regularizar la labor de los que ejercieran cualquier tipo de atención sanitaria, otorgando licencias, fijando aranceles y vigilando el trabajo realizado en las boticas y la calidad de los medicamentos, a través de visitas periódicas. La conclusión determina que hubo mejoras sanitarias como consecuencia de la gestión del Protomedicato en el virreinato del Perú, proponiendo medidas salubres e, incluso, disponía la movilización de personal médico a través del virreinato y participaba ante cualquier consulta de otras entidades coloniales, como el cabildo, referentes a salud pública, como eliminación de acequias, declaración de pestes, y otros.
Cuerpos desgener[iz]ados: rescatando las experiencias de personas intersex como usuarias del sistema de salud público Chileno
Authors: Gacitúa Casanova Camila , Pavez Lizarraga Amaya
Published: May 2024

Introducción: La intersexualidad comprende condiciones infrecuentes donde una persona nace con una anatomía sexual diferente del binario hombre-mujer; esto supone habitar un cuerpo fuera de lo inteligible y estigmatizado. Históricamente, desde la heteronorma, el modelo biomédico ha buscado normalizarles quirúrgicamente para asignar precoz y arbitrariamente un sexo-género armónico con la genitalidad. Desde los Derechos Humanos, estas prácticas son cuestionadas por colectivos Intersex. Materiales y método: Estudio de caso, entre años 2019 y 2020; técnica de entrevista en profundidad a dos usuarios adultos de los Policlínicos de Urología y Endocrinología de un hospital público en Santiago, Chile; se utilizó la fenomenología de Husserl para comprender la experiencia en el sistema de salud de las personas intersex. El análisis de la información se basó en la propuesta de Colaizzi. Resultados: Se reconocieron unidades de significado principales e imbricadas, cuyas esencias permitieron describir el fenómeno de: ser niño y habitar el espacio hospitalario, vivir con la condición actualmente, y la experiencia de utilizar el sistema de salud siendo adulto. Conclusiones: Se identificaron diversas estrategias de agencia tanto en el espacio hospitalario como el cotidiano, mediante un proceso personal y silencioso de aprendizajes sobre las implicancias de ser intersexual.
Circuits for anesthesia, unawareness, OIRD, sleep and memory replay:

MHb→IPN→PAG + DRN + MRN→claustrum→cortex.
Authors: Vadovičová Karin
Published: May 2024

Opiates are fast pain relievers that can cause respiratory arrest. I show new mechanisms how mu-opioids and high prenatal nicotine cause respiratory slowdown linked to slow wave sleep. Mu-opioids activate the medial habenula which activates the interpeduncular nucleus. The MHb-IPN system decreases respiration and alarm/arousal response to hypercapnia by projections to PAG, DRN, MRN and MRN→LPO→RMTg→vPAG. The same MHb-IPN circuit that causes respiratory slowdown, likely causes ventilatory deficits in mammalian neonates, known as sudden infant death syndrome (SIDS), linked to high fetal nicotine intake. Natural slowdown of respiration and heart rate is caused by slow wave sleep, when body is not moving. The MHb and rostromedial tegmental nucleus are known for high amount of mu-opioid receptors. Both were claimed to be activated by the MHb→IPN→MRN circuit that activates serotonin release, promotes slow SWS, rest, immune defense, recovery, sharp wave ripples, cortical spindles, replay of temporaly, spatialy and relationally bound memories, synaptogenesis, BDNF linked growth and DG neurogenesis, but inhibits theta states, arousal, alert wakefulness, awareness and REM sleep linked circuits (Vadovičová, 2015).This updated circuit model explains role of the MHb→IPN→MRN→hippocampus + claustrum→cortical slow wave activity (SWA) in anesthesia, memory replay, loss of awareness, SWS and in theta states suppression. I proposed new mechanisms for anesthetic ketamine effect: activation of the IPN→MRN→claustrum→cortical SWA circuit by the 5-HT2a IPN and claustrum receptors. I show why are ketamine and hallucinogens anxiolytic and antidepressant, andhow activation of 5-HT2a receptors in vACC/infralimbic cortex increases the safety, well-beingsignal, and cognitive flexibility.
Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data—A Systematic Review and Assessment
Authors: Mishra Anup Kumar , Chong Bradford , Arunachalam Shivaram P. , Oberg Ann L. , Majumder Shounak
Published: May 2024

INTRODUCTION:

Accurate risk prediction can facilitate screening and early detection of pancreatic cancer (PC). We conducted a systematic review to critically evaluate effectiveness of machine learning (ML) and artificial intelligence (AI) techniques applied to electronic health records (EHR) for PC risk prediction.

METHODS:

Ovid MEDLINE(R), Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Scopus, and Web of Science were searched for articles that utilized ML/AI techniques to predict PC, published between January 1, 2012, and February 1, 2024. Study selection and data extraction were conducted by 2 independent reviewers. Critical appraisal and data extraction were performed using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Risk of bias and applicability were examined using prediction model risk of bias assessment tool.

RESULTS:

Thirty studies including 169,149 PC cases were identified. Logistic regression was the most frequent modeling method. Twenty studies utilized a curated set of known PC risk predictors or those identified by clinical experts. ML model discrimination performance (C-index) ranged from 0.57 to 1.0. Missing data were underreported, and most studies did not implement explainable-AI techniques or report exclusion time intervals.

DISCUSSION:

AI/ML models for PC risk prediction using known risk factors perform reasonably well and may have near-term applications in identifying cohorts for targeted PC screening if validated in real-world data sets. The combined use of structured and unstructured EHR data using emerging AI models while incorporating explainable-AI techniques has the potential to identify novel PC risk factors, and this approach merits further study.
The Construction and Concept Validation of Indian Financial Market Composite Risk Index (IFM: CRI): A Vibrant Risk Indicator to Retail Investors
Authors: Subba Susmita , Muthu Pandian B , Shekhar Vishal Ravi
Published: May 2024

The financial market volatility has been a major interest to all the stakeholders of the market especially to the retail investors post 2020. In this backdrop, the study is focused on constructing a Composite Risk Index (CRI) for the Indian Financial Market and examining the various methods of weighting as well as types of volatility capture in the construction of the Financial Market Composite Risk Index. The study intends on giving its contribution on the methodological portion of the derivation of appropriate weights to each segment of financial market. The study is based on the daily price series from 1st January 2020 to 31st March 2023. The research develops nine (09) different Composite Risk Index based on the types of volatility capture [Standard Deviation (SD), Autoregressive Conditional Heteroskedastic (ARCH), Generalised Autoregressive Conditional Heteroskedastic (GARCH)] and method of deriving the weights [Principal Component Analysis (PCA), Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA)] of various sub markets [ Equity, Commodity and Forex] and its segments [Spot and Derivatives]. The inter and intra evaluation of nine CRI are carried out with the help of nonparametric statistical tool Kruskal Wallis Test, further the pairwise comparation is also preformed to analyze the homogeneity between the types of volatility capture and method of deriving the weights. The results reveal that, GARCH based DEA Composite Risk Index is better exhibiting the volatility of the Indian Financial Markets compared to their counterpart CRI and also having a high co-movement with India VIX.
Risk-Adjusted Portfolio Optimization: Monte Carlo Simulation and Rebalancing
Authors: Meher Premananda , Kumar Mishra Rohita
Published: May 2024

This study evaluates the risk-adjusted performance of a diversified portfolio in the Indian financial market from 2011 to 2021, incorporating Nifty 50 stocks and new-age assets. Leveraging Monte Carlo simulations and mathematical optimization, the research identifies an optimal portfolio on the efficient frontier. Integration of the Black-Litterman model provides a comparative analysis, emphasizing the impact of investor views. Despite transaction costs, optimized portfolios outperform the Nifty 50 index, with the rebalanced portfolio demonstrating higher cumulative returns. Key findings include TCS. NS is a leader in share price, HDFCBANK.NS showcasing stability and alternative assets exhibit higher volatility but have the potential for amplified returns. This research offers valuable insights for investors seeking resilient strategies in the Indian financial landscape.
IPOs as Catalysts for Retail Investor Wealth Creation: Evidence from the Indian Stock Market
Authors: Ali Mohammed Mujahed , Masood Shaik
Published: May 2024

The study delves into the dynamics of wealth creation for retail investors in the context of Initial Public Offerings (IPOs) within the Indian equity markets. Against the backdrop of a burgeoning retail investor base, the research offers a comprehensive analysis spanning April 2012 to December 2022, evaluating short-term and long-term IPO performance metrics. The study reveals nuanced insights into wealth creation dynamics by scrutinizing listing day returns, first-week to third-year returns, and market-adjusted returns vis-à-vis the Nifty50 Index. Notably, the research suggests that while IPOs exhibit promise with positive listing day returns, sustaining growth over extended horizons poses challenges. The hypothesis of inflation serving as a pragmatic hurdle rate for retail investors is explored, offering a novel perspective on wealth preservation. It also sheds light on the significant variability in the Real Rate of Returns (RRRs) among IPOs, with some contributing to wealth generation while others result in wealth erosion. This underscores the importance of retail investors carefully assessing and managing risks, emphasizing the need for prudent portfolio diversification and effective risk mitigation strategies, particularly over longer investment horizons.
Problems of Myanmar Women of Reproductive Age in Accessing Health Services as Migrant Workers in Thailand: A Qualitative Study
Authors: Sitkulanan Piyaporn , Chaisitsanguan Kunnikar , Winaiprasert Prakaipetch , Wong-arsa Wilailuck
Published: May 2024

Background: The largest portion of migrant labor in Thailand originates from Myanmar, with almost half consisting of female workers. Most female migrant workers (MWs) are of reproductive age and often experience physical illnesses, including pregnancy and childbirth. Although access to prenatal care and delivery services for Myanmar MWs has been previously studied, their challenges in accessing other reproductive health services (HSs) have not yet been explored.Purpose: This study aimed to explore problems in accessing health services experienced by women of reproductive age (WRA) who were members of the Myanmar migrant workforce in Thailand.Methods: The present study employed a qualitative research design. The samples consisted of 20 informants aged 18-49 years old, who were Myanmar WRA working as migrant laborers for more than one year. They were subdivided into two groups: 10 participants provided information through in-depth interviews, and the other 10 participated in focus group discussions, with each group comprising 5 individuals. The researchers selected informants using criterion sampling. Data analysis utilized the Diekelmann and Allen method.Results: The findings revealed two general themes, including care ineligibility and problems in accessing health services. The six major issues among Myanmar WRA include inability to purchase or renew health insurance cards (HICs), HIC or social security wage deduction avoidance, communication issues, hospital inexperience, the transit fare, and admission refusal.Conclusion: Despite available health services, migrant women from Myanmar encounter barriers such as inability to purchase health insurance cards, wage deduction concerns, communication issues, hospital unfamiliarity, transportation expenses, and admission refusal. Addressing these barriers through policy interventions and support mechanisms is crucial for enhancing healthcare access.
Socio-Demographic and Clinical Profiles Associated with Sodium Consumption Behaviors in Patients with Non-Dialysis Chronic Kidney Disease: A Study in Myanmar
Authors: Hlaing Kay Thi , Sriyuktasuth Aurawamon , Phligbua Warunee
Published: May 2024

Background: Sodium consumption behaviors (SCB) play a significant role in the development of kidney failure and associated comorbidities in patients with chronic kidney disease (CKD). Despite the widespread harmful effects of excessive salt consumption, factors influencing SCB in patients with non-dialysis CKD are still little known in Myanmar. No previous study was carried out among Myanmar populations with non-dialysis CKD.Purpose: This study aimed to identify the association between socio-demographic and clinical profiles and SCB in patients with non-dialysis CKD in Myanmar.Methods: Cross-sectional data of 123 patients with non-dialysis CKD, gathered from a tertiary hospital-based study in Myanmar, were analyzed. Non-dialysis CKD patients who had been diagnosed with CKD for more than 3 months were recruited via convenience sampling. Data were collected using demographic and clinical characteristics data form, and Sodium Consumption Behaviors Questionnaire (SCBQ). Descriptive and inferential statistics were employed for data analysis.Results: The mean score of SCB was 31.5 (SD=5.1), indicating quite good behaviors. Participants who had high education (b= -.233, p= .006) and old age (b= -.169, p= .048) were more likely to have good SCB, whereas participants who took antihypertensive medication (b= .304, p= .001) and had comorbidities (b= .232, p= .006) were more likely to have poor SCB.Conclusion: The participants in this study displayed quite favorable SCB. Educational level, age, taking antihypertensive medication, and comorbidity significantly contributed to SCB. Hence, nurses and other healthcare providers should screen patients with these characteristics and provide health education to promote good SCB and prevent the progression of CKD in non-dialysis CKD patients in Myanmar.
"Menelusuri Pergolakan Emosional pada Puisi “Tentang Mahasiswa yang Mati, 1996”
Authors: Mukafi Muhammad Hamdan , Putra Wahyu Kartika
Published: May 2024

The poem "About Students Who Died in 1996" was included in Sapardi Djoko Damono's poetry anthology Ayat-Ayat Api. The anthology illustrates the atmosphere of the new order environment in Indonesia so that the poems contained therein carry an emotional message in the struggle for democracy. This research will focus on tracing the creation of emotional turmoil created in the poems. Thus, the purpose of this research is to (1) present a review of the development of empathetic emotions in poetry to create an aesthetic understanding, and (2) present a review of the relevance of poetry to its visualization (image 1). As the basis of analysis, the method used is descriptive qualitative method, with critical discourse analysis technique supported by empathy theory by Titchener and cognitive & affective empathy theory by Hoffman. The theory of empathy is used to determine the construction of cognitive empathy knowledge narratives that later lead to affective empathy and finally lead to intact knowledge about the aesthetics of the poems and images analyzed. The theory attempts to answer the mobilization and development of cognitive and affective empathy for the poem based on the events of Kudatuli 1996. The reader is also directed to know about the event in order to bring out the aesthetic understanding. With the visualization of images taken in the 20s, this research tries to construct the emotion of the poem's content.