analysis

Introduction: The spread of SARS-CoV-2 cases grew exponentially. In Mexico, it focused mainly on containing the disease and adopting activities and actions to mitigate it. Hospital reconversion was a fundamental strategy in the management of care for patients with COVID-19.Objective: To know the clinical characteristics of patients admitted with respiratory disease and probable COVID-19 in the Zacatecas General Hospital “Luz González Cosío” México.Material and methods: Descriptive, cross-sectional, and analytical study, at the General Hospital, from March 2019 to September 2021; using data from the Respiratory Disease Surveillance System. Data from patients admitted with a diagnosis of some pathology of respiratory disease and probable COVID-19 were analyzed.Results: We included 2,678 diagnosed with respiratory disease and a mean age; of 47.6 ± 21.6 gender distribution was almost equal; women 1,344 (51.0%). positive result to COVID-19 by PCR; 1,654 negatives; 900 and 124 without result. 193 (7.0%) required mechanical ventilation. The presence of comorbidities was evaluated; type 2 diabetes mellitus, systemic arterial hypertension, obesity, alone and together. Also the association of the age factor, as well as the lethality index; was 531 (19.6%).Discussion: What has been published in other studies about comorbidities and their influence on the severity of COVID-19 is confirmed, disagreeing on the case fatality rate; 20.7% against what was reported; 17.6% in other countries for COVID-19 hospitalized. An age variable was used as a risk factor with a cut-off point > 45 years; (FRE), obtaining; RR 3.42 (95% CI 2.79 to 4.19) and an odds ratio of 4.015 in binary logistic regression analysis. Reported male mortality (OR = 1.45; 95% CI: 1.41–1.51) according to our OR results; 1,45.Conclusion: The present study shows how certain chronic diseases influenced respiratory disease to present a serious state, regardless of the positive or negative result of COVID-19.

Introduction: Patients with aortic stenosis often develop hypertrophy and fibrosis, regardless of symptoms. Cardiac Magnetic Resonance (CMR) represents the gold standard for the evaluation of fibrosis despite numerous limitations: cost, availability, atrial fibrillation, claustrophobia, kidney failure or inability to apnea.Purpose: The aim is to validate the role of echocardiographic parameters, such as Global Longitudinal Strain (GLS), as early markers of fibrosis. Clinical and laboratory data, particularly B-type Natriuretic Peptide (BNP), were also analyzed.Material and methods: In our study we recruited 33 patients with severe aortic stenosis, correlating echocardiographic values of GLS with the qualitative analysis of Late Gadolinium Enhancement (LGE) and the quantitative analysis of T1 mapping of CMR.Results: 70% of patients with an alteration of GLS had LGE+. Univariate logistic regression shows that the factors associated with the presence of LGE on CMR are hypertension (p = 0.043), GLS (p = 0.032), and elevated BNP values (p = 0.021); for GLS, Odds Ratio (OR) is 5 so the chance of finding fibrosis on CMR increases 5 times in presence of an altered GLS. The multivariate analysis confirms the association with impaired GLS values (p = 0.033) and hypertension (p = 0.025), but not with elevated Pro-BNP values.Conclusion: In patients with severe aortic stenosis, the association between GLS, LGE, and T1 mapping can help identify earlier those patients with structural changes caused by the disease, who could benefit from early intervention. It remains to be established how the presence of these alterations has a role in determining the intervention time and the outcome of these patients.

Coronavirus disease (COVID-19) is a viral pneumonia that is found in China and has spread globally. Early diagnosis is important for effective and timely treatment. Thus, many ongoing studies attempt to solve key COVID-19 problems such as workload classification, detection, and differentiation from other pneumonia and healthy lungs using different imaging modalities. Researchers have identified some limitations in the deployment of deep learning methods to detect COVID-19, but there are still unmet challenges to be addressed. The use of binary classifiers or building classifiers based on only a few classes is some of the limitations that most of the existing research on the COVID-19 classification problem suffers from. Additionally, most prior studies have focused on model or ensemble models that depend on a flat single-feature imaging modality without using any clinical information or benefiting from the hierarchical structure of pneumonia, which leads to clinical challenges, and evaluated their systems using a small public dataset. Additionally, reliance on diagnostic processes based on CT as the main imaging modality, ignoring chest X-rays. Radiologists, computer scientists, and physicians all need to come to an understanding of these interdisciplinary issues. This article first highlights the challenges of deep learning deployment for COVID-19 detection using a literature review and document analysis. Second, it provides six key recommendations that could assist future researchers in this field in improving the diagnostic process for COVID-19. However, there is a need for a collective effort from all of them to consider the provided recommendations to effectively solve these issues.

This paper is a study of the nuclear Equation of State (EOS) of cold nuclear matter with the B3Y-Fetal effective interaction in its CDM3Y density-dependent version within the framework of Hartree-Fock approximation. The well-known saturation properties of both symmetric and asymmetric nuclear matter are well-reproduced in this work. Using the CDM3Y-K approach, this study has evolved a new set of user interactions, some of which are CDB3Y1-, CDB3Y2-, CDB3Y3-, CDB3Y4-, CDB3Y5-, CDB3Y6-Fetal interactions with corresponding incompressibilities K0 = 188, 204, 217,228, 241 and 252 MeV respectively, in excellent agreement with those of the M3Y-Paris and M3Y-Reid effective interactions. For asymmetric nuclear matter, the new set of interactions has produced the symmetry energy Esym = 32.00 MeV with an associated slope parameter L = 55 MeV at a saturation density ρ = 0.17fm−3 and asymmetry parameter δ = 1.00 (pure neutron matter) in good agreement with the standard values obtained from coupled channel analysis of charge exchange reactions, statistical multifragmentation model and terrestrial Nuclear Physics experimental analyses. Furthermore, the new set of interactions has been found to have bright prospects in a nuclear reaction as the real folded potential computed with the CDB3Y6-Fetal interaction within the framework of double folding potential has been found to be good and similar to that of CDB3Y6-Paris whose optical potential has a repulsive direct component.

Sclerotinia sclerotiorum is a necrotrophic plant pathogen causing more than 60 different disease symptoms in approximately 400 plants globally. Hence, due to this distinctive characteristic, S. sclerotiorum has been the subject of various research to comprehend its pathogenicity mechanism, including virulent genes, proteins, and metabolites. Likewise, the genomic annotation of S. sclerotiorum uncovered its remarkable potential for producing secondary metabolites, of which genome mining has additionally prompted the disclosure of these uncharacterized metabolic pathways, which might aid the pathogenicity process. To comprehend the secondary metabolites secreted by S. sclerotiorum that might be involved in its pathogenicity, a secondary metabolite-level investigation of this plant pathogen was performed. Profiling and characterizing these secondary metabolites produced during in vitro germination would increase the current knowledge of this pathogen. In this study, S. sclerotiorum secondary metabolites profile examination was conducted, utilizing the Ultra-High Resolution Qq-Time-Of-Flight mass spectrometer (UHR-QqTOF). Proficient data analysis and verification with the genomic pathways of S. sclerotiorum gave an unequivocal metabolome profile of this pathogen. Two hundred and thirty secondary metabolites were identified in all three biological replicates, and their bodily functions were identified.

Background: In light of the COVID-19 pandemic and the health crisis left in its wake, our goal is to develop extensive machine-learning techniques to provide a clear picture of the treatment, and possible mistreatment, of specific patient demographics during hospital triaging.Objective: We aim to reveal whether a patient’s treatment and hospital disposition is related to the following attributes - Emergency Severity Index (ESI), gender, employment status, insurance status, race, or ethnicity which our 100 MB dataset included.Materials and methods: Our work is separated into two parts - the classification task and data analysis. As part of the classification task, we used the k-Nearest-Neighbor classifier, the F1-score, and a random forest. We then analyze the data using SHapley Additive exPlanations (SHAP) values to determine the importance of each attribute.Results: Our findings show that significance varies for each attribute. Notably, we found that patients with private insurance programs receive better treatment compared to patients with federal-run healthcare programs (e.g. Medicaid, Medicare). Furthermore, a patient’s ethnicity has a greater impact on treatment for patients under 40 years of age for any given ESI level. Surprisingly, our findings show language is not a barrier during treatment.Discussion and conclusion: We, therefore, conclude that although hospitals may not be doing so intentionally, there is a systemic bias in hospital triaging for specific patient demographics. For future works, we hope to aggregate additional patient data from hospitals to find whether specific demographics of patients receive better healthcare in different parts of the United States.

Background: 800 women die and 2.6 million stillbirths occur worldwide related to pregnancy complications. Racial/ethnic disparities in pregnancy-related mortality have continued to be significantly higher among black than whites due to various factors. We sought to investigate complications among pregnant women of different race/ethnicity.Methods: Cross-sectional observational study of 2030 obstetric cases randomly selected for the period January 1 to December 31, 2021. Data was collected from the hard copy and electronic inpatients’ records. Analysis was performed using SPSS version 23. Descriptive statistics analyzed the pregnancy complication frequencies, standard deviations, range, minimum and maximum values. Maternal characteristics were analyzed using an independent samples t-test. Maternal characteristics were evaluated using the two samples t-test. The odds ratios and confidence intervals were calculated as measures of association between ethnicity/race and pregnancy complications using a binary logistic regression model. Confidence interval was set at 95% and p < 0.05 (2-tailed) was considered statistically significant.Results: 76.25% of Chinese and 67.86% of Zambians were affected by one or more complications. The mean ± standard deviation for MGH [age (26.69 ± 7.33), gravidity (3.35 ± 2.08), and parity (2.07 ± 1.68)] and for 2nd affiliated hospital was [age (30.04 ± 4.29), gravidity (2.19 ± 1.38) and parity (0.45 ± 0.55)]. Prevalence of top five pregnancy complications in the Chinese group was gestational diabetes mellitus at 18.41%, hypothyroidism at 15.91%, oligohydramnios at 14.39%, premature rupture of membranes at 12.17%, and anemia at 5.73%. The prevalence of the top five pregnancy complications in the Zambian group was preeclampsia at 13.80%, PIH at 12.74%, PROM at 12.45%, eclampsia at 7.53%, and placenta abruption at 7.43%. Statistical significance findings were noted as follows: Oligohydramnios [OR 0.02, CI (0.01 - 0.05), p = 0.000], placenta praevia [OR 0.08, CI (0.01 - 0.61), p = 0.015], preeclampsia [OR 13.10, CI (7.22 - 23.78), p = 0.000], placenta abruptio [OR 79.73, CI (11.07 - 574.38), p = 0.000], PIH [OR 11.95, CI (6.57 - 21.73), p = 0.005], eclampsia [OR 162.90, CI (10.08 - 2631, p = 0.000), PPROM [OR 0.03, CI (0.00 - 0.45), p = 0.012], GDM [OR 0.11, CI (0.07 - 0.17), p = 0.000], hypothyroidism [OR 0.01(0.00-0.03), p = 0.000], anemia [OR 0.18, CI (0.92-0.34), p = 0.000], ICP [OR 0.03, CI (0.00 - 0.48), p = 0.013], syphilis [OR 7.17, CI (2.14 - 24.02), p = 0.001], UTI [OR 22.55, CI (3.04 - 17.26), p = 0.002], HBV [OR 0.05, CI (0.00 - 0.86), p = 0.039] and GBS [OR 0.06, CI (0.00 - 1.11), p = 0.059].Conclusion: Highest odds for obstetrical and infection-related pregnancy complications were associated with Zambian cases. The highest odds for medical complications were associated with Chinese cases.

Tissue Doppler Imaging and Speckle Tracking Echocardiography are newer echo-cardiographic modalities, that assess myocardial and valvular function in congenital and acquired heart diseases in childhood. In addition, cross-sectional imaging including Cardiac Magnetic Resonance (CMR) and Cardiac Computed Tomography has been widely used over the last decade in paediatric cardiology, in order to evaluate intra-cardiac and extra-cardiac anatomy. Cardiac Magnetic Resonance particularly allows detailed analysis of myocardial function, and shunt quantification and has applications even in fetal life. This mini-review summarizes the basic principles of the above-advanced modalities and highlights their main indications and clinical applications in childhood.

Neurointerventional Radiology (NIR), encompassing neuroendovascular surgery, endovascular neurosurgery, and interventional neurology, is an innovative and rapidly evolving multidisciplinary specialty focused on minimally invasive therapies for a wide range of neurological disorders. This review provides a comprehensive overview of NIR, discussing the three routes into the field, highlighting their distinct training paradigms, and emphasizing the importance of unified approaches through organizations like the Society of Neurointerventional Surgery (SNIS).The paper explores the benefits of co-managed care and its potential to improve patient outcomes, as well as the role of interdisciplinary collaboration and cross-disciplinary integration in advancing the field. We discuss the various contributions of neurosurgery, radiology, and neurology to cerebrovascular surgery, aiming to inform and educate those interested in pursuing a career in neurointervention. Additionally, the review examines the adoption of innovative technologies such as robotic-assisted techniques and artificial intelligence in NIR, and their implications for patient care and the future of the specialty. By presenting a comprehensive analysis of the field of neurointervention, we hope to inspire those considering a career in this exciting and rapidly advancing specialty, and underscore the importance of interdisciplinary collaboration in shaping its future.

Purpose: Stereotactic body radiation therapy (SBRT) has emerged as an alternative to surgery for patients with inoperable early-stage non-small cell lung cancer (NSCLC). The majority of inoperable NSCLC patients are elderly and frequently have comorbidities including cardiovascular diseases for which they frequently receive angiotensin receptor blockers (ARBs) or angiotensin-converting enzyme inhibitors (ACEIs). The interactions of these medications with SBRT are not clear. The objective of the current study is to investigate the interaction of ARBs and ACEIs with SBRT for the outcomes of early-stage NSCLC. Methods and Materials: A retrospective chart review of patients treated with SBRT for Stage I and II NSCLC (AJCC 7th edition) at a single institution between 2006 and 2017 was conducted. Information on the use of ARBs, ACEIs, demographics, and tumor-related factors was collected. Kaplan-Meier and Cox proportional hazard analyses were performed to assess the impact of ARBs and ACEIs combined with SBRT respectively on the treatment outcomes of these patients. Results: In total, 116 patients were included in the study, among whom 38/116 (32.76%) received ACEIs, and 20/116 (17.24%) received ARBs. In the multivariable analysis, the use of ARBs, but not ACEIs, with SBRT, was significantly associated with the increased risk of dissemination (Hazard Ratio (HR): 2.97; CI: 1.40-6.27; p < 0.004) compared to SBRT without ARBs. The tumor size of > = 3 cm was associated with significantly decreased time to local failure and OS compared to tumor size <3cm. Conclusion: In the current retrospective study, the use of ARBs, in combination with SBRT, was associated with a significantly increased risk of disease dissemination in early-stage NSCLC compared to SBRT alone. The findings warrant further investigations on the concurrent use of ARBs, ACEIs, and other medicines used for chronic diseases with SBRT for early-stage NSCLC.

Depression is a mental, psychiatric medical condition or disorder in which individuals manifest some clinical syndrome characterized by sadness, mood swings, societal withdrawal, lack of interest, family issues, and education problems which affect the daily student life in which the individual does not participate in daily activities. Sometimes individual commits suicide due to exam stress and that swings the mood upon the condition of the individual. The cost of brand-name medications prescribed in such circumstances exacerbates the disease burden and may even result in noncompliance with therapy. IDR (Indian Depository Receipt) was used to calculate the cost of various antidepressant drug brands. Using the percentage cost ratio, one can ascertain the price of each brand’s 10 tablets in INR (Indian Rupees), the cost ratio, and the percentage cost variance. The difference between the greatest and lowest prices of the same drug produced by Indian pharmaceutical industries was calculated. There is a greater price disparity between agents on the market. The greatest expense variance was found to be amitriptyline 25 mg (195%), fluoxetine 50 mg (95%), sertraline 50 mg (83%) and the lowest % cost variation was of fluvoxamine 20 mg (13.8 mg), duloxetine 20 mg (16%) and escitalopram 10 mg (38%). On the Indian market, the average price disparity between antidepressant medications of various brands is quite high. If a pricey brand is prescribed, patients will incur additional costs.

Introduction: The bone marrow aspirate examination is defined as a quantitative and qualitative study of bone marrow cells obtained by puncture and aspiration. Aim: Our objective was to evaluate the practice of this exam at Andrainjato Fianarantsoa University Hospital in order to improve its diagnostic relevance.Method: This is a prospective and descriptive cross-sectional study of all bone marrow aspirates performed at the Andrainjato Fianarantsoa University Hospital Madagascar, during 18 months, from January 2021 to June 2022.Results: Forty-two bone marrow aspirate examinations were performed during the study period, among the 338 requests for hematological analysis received, representing a percentage of 1.26%. The average age of the patients was 32.17 years, with a sex ratio of 2.5. The prescription was of hospital origin in 83.3% of patients, motivated by the disturbance of the blood count in 78.6% of cases. Thirty-three requests were evaluated as relevant prescriptions. Coupled with the realization of the bone marrow examination, the haemograms were pathological in 78.6% of cases. The result of the bone marrow aspirate showed normal marrow cytology (16.7%), reactive marrow (23.8%), pathological marrow (50.0%), and hemodiluted marrow (9.5%). Dysmyelopoiesis (33.3%), multiple myeloma (23.8%), and acute leukemia (19.0%) were the main pathologies found. The difficulties encountered were related to the poor quality of the equipment and the non-availability of other complementary explorations.Conclusion: The bone marrow aspirate examination is technically feasible at Andrainjato Fianarantsoa University Hospital despite the existence of difficulties. The commitment to the process of continuous improvement of quality would impose the improvement of the technical platform.

Pre-eclampsia is a pregnancy-associated condition, which is characterized by the onset of hypertension and proteinuria. It is one of the leading causes of maternal and neonatal mortality and this affliction has been recorded in around 8% of all pregnancies in the world. In addition to this, the etiopathology of this condition is very less understood and the resources available to diagnose and treat it are limited. Prior studies suggest more than a hundred possible diagnostic biomarkers that could be used to detect this disease early on. However, most of them are not feasible due to several reasons including stability, cost, safety, etc. Here two biomarkers HtrA3 (high-temperature requirement A3) and NGAL (Neutrophil Gelatinase Associated Lipocalin) are selected for the detection of pre-eclampsia, and we compare their efficacy in the detection of pre-eclampsia based on their specificity, ease of use, speed, stage of detection and source (invasiveness). We found that these two biomarkers are efficient under some parameters, and inefficient under others. The scoring system used in the current study suggests that NGAL is a superior biomarker. The results of this study help to develop a stronger understanding of both these biomarkers in the short and long term to classify the biomarkers more efficiently and understand the complicated pathologies of pre-eclampsia.

Continuous noninvasive cuffless blood pressure (BP) monitoring is essential for early detection and treatment of hypertension. In this paper, we provide an overview of the recent advancements in cuffless BP sensors. These include contact wearable sensors such as electrocardiography (ECG), photoplethysmography (PPG), contact non-wearable sensors such as ballistocardiography (BCG), and contactless sensors such as video plethysmography (VPG). These sensors employ different measuring mechanisms such as pulse arrival time (PAT), pulse transit time (PTT), and pulse wave analysis (PWA) to estimate BP. However, challenges exist in the effective use and interpretation of signal features to obtain clinically reliable BP measurements. The correlations between signal features and BP are obtained by mechanism-driven models which use physiological principles to identify mathematical correlations, and data-driven models which use machine learning algorithms to analyze observational data to identify multidimensional correlations. On the one hand, applying mechanism-driven models to non-linear scenarios and incomplete or noisy data is challenging On the other hand, data-driven models require a large amount of data in order to prevent physically inconsistent predictions, resulting in poor generalization. From this perspective, this paper proposes to combine the strengths of mechanism-driven and data-driven approaches to obtain a more comprehensive approach, the physiology-informed machine-learning approach, with the goal of enhancing the accuracy, interpretability, and scalability of continuous cuffless BP monitoring. This holds promise for personalized clinical applications and the advancement of hypertension management.

Internet addiction is a growing addictive behavior and a major public health problem worldwide. Several psychological factors can contribute to the problematic use of the Internet. This study aimed to determine the prevalence of Internet Addiction (IA) in a sample of university students and to examine the relationship between IA, self-esteem, and attachment styles.The present study was a cross-sectional study, involving 135 students from the Faculty of Medicine of Monastir. The participants completed a questionnaire, which contained the socio-demographic data, the reasons for Internet use, the Young Cyberaddiction scale to seek IA, the Relationships-style-questionnaire-RSQ to assess attachment style, and the Rosenberg Self-Esteem Scale (RSES).The mean age of the students was 21.5 ± 1.9 years old. They were 112 (83%) females. The prevalence of Internet addiction was 23.7%. The average connection time was 3.5 ± 1.8 hours/day. The most frequent online activities were chat (online discussion, forums ...) in 94.8% of cases followed by download activities (78.5%), scientific research (75.6%), online games (23.7%), and online shopping (13.3%). IA was associated with school failure, alcohol use, online gaming, and low self-esteem. The majority of the participants (84.4%) in this study reported an insecure attachment style. Logistic regression analysis showed a strong association between IA and fearful attachment style.IA was frequent among students. Fearful attachment style was found to be a risk factor for IA. This study highlights the impact of relationships between child and their caregivers on the development of addiction.

Objective: The study evaluated the hyperglycaemia-lowering effects, safety, and phytochemical profile of Celtis zenkeri leaf extract in order to justify its antidiabetic folkloric usage. Methods:  Modified OECD test guidelines were used to assess its acute and sub-acute toxicity while its effect on blood parameters such as blood glucose, and haematological and biochemical levels were evaluated using appropriate assays. Both in vitro and in vivo antihyperglycaemic assays were used for the antidiabetic studies while histology of the pancreas, liver, and kidney of the rats was examined after treatment with the extract at 250, 500, and 1000 mg/kg for 21 days.  GC-MS analysis was used to determine the chemical constituents of the extract. Results: The results obtained showed that the leaf extract of C. zenkeri was not toxic in rats at 5000 mg/kg. It elicited a significant decrease in the blood glucose levels of the animals but did not affect the haematological and biochemical components of normal rats. It significantly inhibited α-amylase and α-glucosidase actions and gave comparable activity to glibenclamide (5 mg/kg) at all time points at 200 and 400 mg/kg. The extract comparably reduced blood glucose levels with glibenclamide at 100 and 200 mg/kg on days 10 and 14 in drug-induced diabetic rats and maintained the histoarchitecture of the liver, kidney, and pancreas at 250 and 500 mg/kg.Conclusion: The study justified the ethnomedicinal use of C. zenkeri in diabetes management.

Forensic handwriting analysis is a specialized field within forensic science that aims to identify and compare handwriting samples for investigative purposes. This scientific note provides an overview of the fundamental principles, methodologies, and techniques involved in the examination of handwriting evidence. The note explores the importance of handwriting analysis in criminal investigations, discusses the underlying scientific principles, and highlights the challenges faced by forensic experts in this field. Additionally, it explores the advancements in technology that have aided the analysis of handwriting and conclude with the potential future directions of research in forensic handwriting analysis. This study focuses on the natural variation that occurs due to the unusual surfaces of tables and bricks, the variation occurs mostly in the class characteristics of the person like slant, speed, line quality, alignment, etc. Samples are collected on two different surfaces; a table and a wall (smooth and rough surfaces). And on the basis of these two surfaces, the variations in the characteristics of the individual are observed. The significance of the research is to find out the range of natural variation that occurs in the individual handwriting whenever there is a change in the writing surface.

Introduction: Aluminum Phosphide (AlP) poisoning is a life-threatening condition that commonly occurs in developing countries, often resulting in cardiac, respiratory, and metabolic complications, leading to multi-organ failure and mortality. Extracorporeal Membrane Oxygenation (ECMO) has been proposed as a potential therapy for severe AlP poisoning cases refractory to conventional management, though its use remains controversial. Methodology: for this literature review, we conducted a comprehensive analysis of existing literature concerning the utilization of ECMO in patients with severe AlP poisoning. We meticulously examined available publications to explore the relationship between ECMO initiation and patient outcomes. Discussion: The review reveals that early ECMO initiation within 6 hours of presentation is associated with better outcomes and higher survival rates in severe AlP poisoning cases. However, uncertainties persist regarding the optimal timing and duration of ECMO support, and potential complications, including bleeding, acute renal injury, and ventilator-associated pneumonia, need careful consideration. Conclusion: Despite promising results in certain cases, the risks and benefits of ECMO in AlP poisoning require meticulous evaluation. Ethical considerations, encompassing resource allocation and implications for other patients, necessitate appropriate patient selection criteria.

Chronic infectious, granulomatous and suppurative dermatosis, classified among the subcutaneous mycoses, prevalent in tropical and subtropical regions and caused by the traumatic implantation of dematiaceous fungal species, where the presence of muriform bodies is an expression of the causal agent in the grafted tissue, are characteristic of chromoblastomycosis. Considered the second implantation mycosis in the world, it manifests itself with slow and progressive growth lesions of exophytic and verrucous plaques and black dots on the surface.The disease is considered a neglected and occupational disease, which occurs mainly among agricultural workers, coconut and babassu harvesters, lumberjacks, and traders of agricultural products. It is important to highlight that people at risk of contracting chromoblastomycosis work in tropical countries, where the temperature can be above 40 °C in summer, and generally refuse to wear protective equipment during the day (shoes, gloves, clothes, etc.), although they know that this type of prophylactic measure can prevent different types of diseases. These vulnerable people often live in low-income countries and sometimes live far from medical services and, once infected, do not seek medical attention. We report below an exuberant and unusual case due to multiple simultaneous inoculations on the back after the patient suffered an accidental fall while working on his farm. The diagnosis was established by direct mycological examination, histopathological examination, culture, microculture, and MALDI-TOF MS analysis that identified the agent of the Fonsecaea pedrosoi.

Introduction: Nursing theories are critical as they drive nursing education, practice, and research. Neuman Systems Model (NSM) considers a person a complete system with integrated psychological, physiological, spiritual, social, and developmental components. Nurses give their patients physical, emotional, and psychological assistance and are subjected to mental and physical pressure due to these responsibilities, impacting their health, psychological well-being, and interpersonal relationships. This paper aims to perform a concept analysis of stressors proposed in NSM about lines of defense and the level of preventive interventions that can affect a person’s well-being. Further, this paper discusses knowledge generation through NSM’s applicability to preventing exhaustion and burnout among nurses. Methodology: This theoretical attempt is carried out using the theory analysis approach suggested by Walker and Avant (2019).Discussion: Nursing is a career that requires a great deal of dedication and personal engagement. Nurses are subjected to recurrent stresses due to technological advances and rising demands. Burnout occurs when nurses get discouraged and have less compassion for the patients due to recurrent burdens. Stress and burnout are two of the most common reasons for nurses to quit hospitals. The NSM is concerned with stresses that may affect a person’s health and well-being (prediction). Nurses assist patients at the most vulnerable and challenging times, such as surgical procedures, traumas and personal and physical losses.Conclusion: The NSM enables the investigation of preventative and protective treatments. Because of the model’s flexibility, it may be used in a wide range of nursing situations. Administrative, hospitals, clinics, and other nurses can benefit from this paradigm. Evaluating the many distinct elements contributing to burnout is also feasible. The model’s client factors of physiological, sociocultural, developmental, and spiritual characteristics are used to achieve this. Viewing the individual as an open system that responds to environmental stimuli encourages the existence of stressors that might lead to burnout.