Impact of the Health Gym Program on hospital admissions for stroke in the state of Pernambuco, Brazil / Impacto do Programa Academia da Saúde nas internações hospitalares por acidente vascular cerebral no Estado de Pernambuco, Brasil / Impacto del Programa Academia de la Salud en los ingresos hospitalarios por accidente cerebrovascular en el estado de Pernambuco, Brasil

This study aimed to evaluate the impact of the Health Gym Program (HGP) on hospital admissions for stroke in the state of Pernambuco, Brazil. This policy impact evaluation used a quasi-experimental approach consisting of a difference-in-differences estimator, weighted by propensity score matching to deal with potential confounding variables. The study comprised socioeconomic, demographic, and epidemiological data from official Brazilian databases from 2010 to 2019. The treatment group was composed of the 134 municipalities that implemented the HGP since 2011. The 51 municipalities that did not were allocated to the comparison group. The nearest neighbor algorithm (N5) was used to pair treatment and comparison group municipalities and create the weights to evaluate the average treatment effect on the treated (ATT) in the difference-in-differences estimator. In 2010, 2,771 people were hospitalized for stroke (0.51% of all hospitalizations) and in 2019, 11,542 (2%). Municipalities that implemented the HGP had 18.37% fewer hospitalizations than their counterparts in the comparison group. The program's impact in reducing hospitalization rates was incrementally greater among men (ATT: -0.1932) and those aged 71 to 80 years (ATT: -0.1911). All results were statistically significant at the 5% level. The HGP reduced hospitalization for stroke in several population groups, but primarily in those whose underlying prevalence of stroke is highest, reinforcing the importance of public investments in health promotion policies designed to encourage lifestyle changes.

O estudo teve como objetivo avaliar o impacto do Programa Academia da Saúde (PAS) nas internações hospitalares por acidente vascular cerebral (AVC) no Estado de Pernambuco, Brasil. Esta avaliação de impacto das políticas utilizou uma abordagem quase-experimental que consiste em um estimador de diferença-em-diferenças, ponderado pelo pareamento por escore de propensão para lidar com possíveis fatores de confusão. O estudo foi composto por dados socioeconômicos, demográficos e epidemiológicos de bases de dados oficiais brasileiras entre os anos de 2010 e 2019. O grupo de tratamento foi composto pelos 134 municípios que implantaram o PAS a partir de 2011, e os 51 municípios que não implantaram foram alocados no grupo de comparação. O algoritmo do vizinho mais próximo (N5) foi utilizado para emparelhar os municípios tratados e comparar aos municípios do grupo controle, criando os pesos que foram utilizados para avaliar o efeito médio do tratamento sobre o tratado (ATT) no estimador de diferença-em-diferenças. Houve 2.771 internações por AVC em 2010 (0,51% de todas as internações) e 11.542 (2%) em 2019. Os municípios que implementaram o PAS tiveram 18,37% menos internações em comparação com seus homólogos no grupo de comparação. O impacto do programa na redução das taxas de internação foi maior entre os homens (ATT: -0,1932) e naqueles com idade entre 71 e 80 anos (ATT: -0,1911). Todos os resultados foram estatisticamente significativos em um nível de 5%. O PAS reduziu a hospitalização por AVC em vários grupos populacionais, mas principalmente naqueles em que a prevalência subjacente de AVC é mais alta, reforçando a importância dos investimentos públicos em políticas de promoção da saúde destinadas a estimular mudanças nos estilos de vida.

El objetivo de este trabajo es evaluar el impacto del Programa Academia de la Salud (PAS) en los ingresos hospitalarios por accidente cerebrovascular (ACV) en el estado de Pernambuco, Brasil. Esta evaluación del impacto de la política utilizó un enfoque cuasi-experimental que consiste en un estimador de diferencias en diferencias, ponderado por el emparejamiento de puntuación de propensión para hacer frente a posibles factores de confusión. El estudio incluyó datos socioeconómicos, demográficos y epidemiológicos de bases de datos oficiales brasileñas de 2010 a 2019. El grupo de tratamiento se compuso de los 134 municipios que implementaron el PAS a partir de 2011 y los 51 municipios que no lo hicieron se asignaron al grupo de comparación. Se utilizó el algoritmo del vecino más próximo (N5) para emparejar los municipios tratados y los del grupo de comparación y crear las ponderaciones que se emplearon para evaluar el efecto medio del tratamiento sobre los tratados (ATT) en el estimador de diferencias en diferencias. Hubo 2.771 hospitalizaciones por ACV en 2010 (0,51% de todas las hospitalizaciones) y 11.542 (2%) en 2019. Los municipios que aplicaron el PAS tuvieron un 18,37% menos de hospitalizaciones en comparación con sus homólogos del grupo de comparación. El impacto del programa en la reducción de las tasas de hospitalización fue gradualmente mayor entre los hombres (ATT: -0,1932) y entre las personas de 71 a 80 años (ATT: -0,1911). Todos los resultados fueron estadísticamente significativos al nivel del 5%. El PAS redujo la hospitalización por ACV en varios grupos de población, pero principalmente en aquellos en los que la prevalencia subyacente de ACV es mayor, lo que refuerza la importancia de las inversiones públicas en políticas de promoción de la salud diseñadas para impulsar cambios en los estilos de vida.

Heart Alert: A heart disease prediction system using machine learning approach and optimization techniques

Background@#Cardiovascular diseases belong to the top three leading causes of mortality in the Philippines with 17.8 % of the total deaths. Lifestyle-related habits such as alcohol consumption, smoking, poor diet and nutrition, high sedentary behavior, overweight, and obesity have been increasingly implicated in the high rates of heart disease among Filipinos leading to a significant burden to the country's healthcare system. The objective of this study was to predict the presence of heart disease using various machine learning algorithms (support vector machine, naïve Bayes, random forest, logistic regression, decision tree, and adaptive boosting) evaluated on an anonymized publicly available cardiovascular disease dataset. @*Methodology@#Various machine learning algorithms were applied on an anonymized publicly available cardiovascular dataset from a machine learning data repository (IEEE Dataport). A web-based application system named Heart Alert was developed based on the best machine learning model that would predict the risk of developing heart disease. An assessment of the effects of different optimization techniques as to the imputation methods (mean, median, mode, and multiple imputation by chained equations) and as to the feature selection method (recursive feature elimination) on the classification performance of the machine learning algorithms was made. All simulation experiments were implemented via Python 3.8 and its machine learning libraries (Scikit-learn, Keras, Tensorflow, Pandas, Matplotlib, Seaborn, NumPy). @*Results@#The support vector machine without imputation and feature selection obtained the highest performance metrics (90.2% accuracy, 87.7% sensitivity, 93.6% specificity, 94.9% precision, 91.2% F1-score and an area under the receiver operating characteristic curve of 0.902 ) and was used to implement the heart disease prediction system (Heart Alert). Following very closely were random forest with mean or median imputation and logistic regression with mode imputation, all having no feature selection which also performed well. @*Conclusion@#The performance of the best four machine learning models suggests that for this dataset, imputation technique for missing values may or may not be done. Likewise, recursive feature elimination for feature selection may not apply as all variables seem to be important in heart disease prediction. An early accurate diagnosis leading to prompt intervention efforts is very crucial as it improves the patient's quality of life and diminishes the risk of developing cardiac events.

Major depressive disorder prediction using data science

Background@#Major depressive disorder is a mood disorder that has affected many people worldwide. It is characterized by persistently low or depressed mood, anhedonia or decreased interest in pleasurable activities, feelings of guilt or worthlessness, lack of energy, poor concentration, appetite changes, psychomotor retardation or agitation, sleep disturbances, or suicidal thoughts. @*Objective@#The objective of the study was to predict the presence of major depressive disorder using a variety of machine learning classification algorithms (logistic regression, Naive Bayes, support vector machine, random forest, adaptive boosting, and extreme gradient boosting) on a publicly available depression dataset. @*Methodology@#After data pre-processing, several experiments were performed to assess the recursive feature elimination with cross validation as a feature selection method and synthetic minority over-sampling technique to address dataset imbalance. Several machine learning algorithms were applied on an anonymized publicly available depression dataset. Feature importance of the top performing models were also generated. All simulation experiments were implemented via Python 3.8 and its machine learning libraries (Scikit-learn, Keras, Tensorflow, Pandas, Matplotlib, Seaborn, NumPy). @*Results@#The top performing model was obtained by logistic regression with excellent performance metrics (91% accuracy, 93% sensitivity, 85% specificity, 93% recall, 93% F1-score, and 0.78 Matthews correlation coefficient). Feature importance scores of the most relevant attribute were also generated for the best model. @*Conclusion@#The findings suggest the utility of data science techniques powered by machine learning models to make a diagnosis of major depressive disorders with acceptable results. The potential deployment of these machine learning models in clinical practice can further enhance the diagnostic acumen of health professionals. Using data analytics and machine learning, data scientists can have a better understanding of mental health illness contributing to prompt and improved diagnosis thereby leading to the institution of early intervention and medical treatments ensuring the best quality of care for our patients.

Thyroid disorder classification using machine learning models

Introduction@#Thyroid hormones are produced by the thyroid gland and are essential for regulating the basal metabolic rate. Abnormalities in the levels of these hormones lead to two classes of thyroid diseases – hyperthyroidism and hypothyroidism. Detection and monitoring of these two general classes of thyroid diseases require accurate measurement and interpretation of thyroid function tests. The clinical utility of machine learning models to predict a class of thyroid disorders has not been fully elucidated. @*Objective@#The objective of this study is to develop machine learning models that classify the type of thyroid disorder on a publicly available thyroid disease dataset extracted from a machine learning data repository. @*Methods@#Several machine learning algorithms for classifying thyroid disorders were utilized after a series of pre-processing steps applied on the dataset. @*Results@#The best performing model was obtained by with XGBoost with a 99% accuracy and showing very good recall, precision, and F1-scores for each of the three thyroid classes. Generally, all models with the exception of Naïve Bayes did well in predicting the negative class generating over 90% in all metrics. For predicting hypothyroidism, XGBoost, decision tree and random forest obtained the most superior performance with metric values ranging from 96-100%. On the other end in predicting hyperthyroidism, all models have lower classification performance as compared to the negative and hypothyroid classes Needless to say, XGBoost and random forest did obtain good metric values ranging from 71-89% in predicting hyperthyroid class. @*Conclusion@#The findings of this study were encouraging and had generated useful insights in the application and development of faster automated models with high reliability which can be of use to clinicians in the assessment of thyroid diseases. The early and prompt clinical assessment coupled with the integration of these machine learning models in practice can be used to determine prompt and precise diagnosis and to formulate personalized treatment options to ensure the best quality of care to our patients.

Melittin-induced metabolic changes on the Madin-Darby Bovine Kidney cell line / [Mudanças metabólicas induzidas por melitina em células da linhagem Madin-Darby Bovine Kidney]

In this study, the toxic effects of melittin on Madin-Darby Bovine Kidney cells (MDBK) were analyzed with respect to mitochondrial functionality by reduction of MTT and flow cytometry, apoptosis potential, necrosis, oxygen reactive species (ROS) production, lipid peroxidation, and DNA fragmentation using flow cytometry and cell membrane destabilization by confocal microscopy. The toxicity presented dose-dependent characteristics and mitochondrial activity was inhibited by up to 78.24 ±3.59% (P<0.01, n = 6) in MDBK cells exposed to melittin (10µg/mL). Flow cytometry analysis revealed that melittin at 2µg/mL had the highest necrosis rate (P<0.05) for the cells. The lipoperoxidation of the membranes was also higher at 2µg/mL of melittin (P<0.05), which was further confirmed by the microphotographs obtained by confocal microscopy. The highest ROS production occurred when the cells were exposed to 2.5µg/mL melittin (P<0.05), and this concentration also increased DNA fragmentation (P<0.05). There was a significative and positive correlation between the lipoperoxidation of membranes with ROS (R=0.4158), mitochondrial functionality (R=0.4149), and apoptosis (R=0.4978). Thus, the oxidative stress generated by melittin culminates in the elevation of intracellular ROS that initiates a cascade of toxic events in MDBK cells.(AU)

Neste estudo, os efeitos tóxicos da melitina em células Madin-Darby Bovine Kidney (MDBK) foram analisados quanto à funcionalidade mitocondrial, por redução de MTT e citometria de fluxo, potencial de apoptose, necrose, produção de espécies reativas de oxigênio (ROS), peroxidação lipídica e fragmentação de DNA, utilizando-se citometria de fluxo e desestabilização da membrana celular, por microscopia confocal. A toxicidade apresentou características dose-dependentes e a atividade mitocondrial foi inibida até 78,24±3,59% (P<0,01, n = 6) em células MDBK expostas à melitina (10µg/mL). Análises por citometria de fluxo revelaram que a melitina a 2µg/mL apresentou o maior índice necrótico celular (P<0,05). A maior lipoperoxidação de membranas também foi na concentração de 2µg/mL de melitina (P<0,05), o que foi posteriormente confirmado por microscopia confocal. A maior produção de ROS aconteceu quando as células foram expostas a 2,5µg/mL de melitina (P<0,05), e essa concentração também aumentou a fragmentação de DNA (P<0,05). Houve uma significativa correlação positiva entre a lipoperoxidação de membranas e a produção de ROS (R=0,4158), funcionalidade mitocondrial (R=0,4149) e apoptose (R=0,4978). Portanto, o estresse oxidativo gerado pela melitina culminou na elevação de ROS intracelular, que inicia uma cascata de eventos tóxicos nas células MDBK.(AU)

Early Cardiac Dysfunction in Biopsy-proven Nonalcoholic Fatty Liver Disease / 대한소화기학회지

Background/Aims@#Nonalcoholic fatty liver disease (NAFLD) encompasses a range of diseases from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) and has been linked to cardiovascular disease and sub-clinical cardiac remodeling. This paper presents a retrospective study of biopsy-proven NAFL and NASH to examine the differences in subclinical cardiac remodeling. @*Methods@#Patients were recruited from an institutional repository of patients with liver-biopsy-confirmed NAFLD. Patients with a transthoracic echocardiogram (TTE) within 12 months of the liver biopsy were included. The parameters of the diastolic dysfunction were reviewed for the differences between NAFL and NASH as well as between the stages and grades of NASH. @*Results@#Thirty-three patients were included in the study, 17 with NAFL and 16 with NASH. The NASH patients were more likely to have lower platelets, higher AST, higher ALT, and higher rates of type 2 diabetes mellitus, coronary artery disease, and hypertension than the NAFL patients. The E/e’ ratio on transthoracic echocardiogram was significantly higher in NASH compared to NAFL, advanced-stage NASH compared to early stage, and high-grade NASH compared to low-grade. The E/e’ ratio was also significantly higher in NASH than NAFL in patients without diabetes mellitus. The presence of diastolic dysfunction trended toward significance. The other markers of diastolic dysfunction were similar. Logistic regression revealed a statistical association with E/e' and NASH. @*Conclusions@#NASH patients had evidence of a higher E/e’ ratio than NAFL, and there was a trend towards a significant diastolic dysfunction. Patients with NASH compared to NAFL should be closely monitored for signs and symptoms of cardiac dysfunction.

Pre-trained convolutional neural networks in the assessment of bone scans for metastasis

Background@#Numerous applications of artificial intelligence have been applied in radiological imaging ranging from computer-aided diagnosis based on machine learning to deep learning using convolutional neural networks. One of the nuclear medicine imaging tests being commonly performed today is bone scan. The use of deep learning methods through convolutional neural networks in bone scintigrams has not been fully explored. Very few studies have been published on its diagnostic capability of convolutional neural networks in assessing osseous metastasis. @*Objective@#The aim of our study is to assess the classification performance of the pre-trained convolutional neural networks in the diagnosis of bone metastasis from whole body bone scintigrams of a local institutional dataset. @*Methods@#Bone scintigrams from all types of cancer were retrospectively reviewed during the period 2019-2020 at the University of Perpetual Help Medical Center in Las Pinas City, Metro Manila. The study was approved by the Institutional Ethical Review Board and Technical Review Board of the medical center. Bone scan studies should be mainly for metastasis screening. The pre-processing techniques consisting of image normalization, image augmentation, data shuffling, and train-test split (testing at 30% and the rest (70%) was split 85% for training and 15% for validation) were applied to image dataset. Three pre-trained architectures (ResNet50, VGG19, DenseNet121) were applied to the processed dataset. Performance metrics such as accuracy, recall (sensitivity), precision (positive predictive value), and F1-scores were obtained.@*Results@#A total of 570 bone scan images with dimension 220 x 646 pixel sizes in .tif file format were included in this study with 40% classified with bone metastasis while 60% were classified as without bone metastasis. DenseNet121 yielded the highest performance metrics with an accuracy rate of 83%, 76% recall, 86% precision, and 81% F1-score. ResNet50 and VGG19 had similar performance with each other across all metrics but generally lower predictive capability as compared to DenseNet121.@*Conclusion@#A bone metastasis machine learning classification study using three pre-trained convolutional neural networks was performed on a local medical center bone scan dataset via transfer learning. DenseNet121 generated the highest performance metrics with 83% accuracy, 76% recall, 86% precision and 81% F1-score. Our simulation experiments generated promising outcomes and potentially could lead to its deployment in the clinical practice of nuclear medicine physicians. The use of deep learning techniques through convolutional neural networks has the potential to improve diagnostic capability of nuclear medicine physicians using bone scans for the assessment of metastasis.

A review of child sexual abuse cases presenting to a paediatric emergency department

INTRODUCTION@#Child sexual abuse (CSA) adversely affects a child's growth and well-being. This study aimed to describe the profile of children presenting to a tertiary paediatric emergency department(ED) with CSA.@*METHODS@#Children 0-16 years old presenting to KK Women's and Children's Hospital ED from June 2016 to August 2020 with sexual abuse were retrospectively reviewed. We performed a secondary analysis on girls and stratified them by age <13 and ≥13 years old.@*RESULTS@#There were 790 patients who made 833 visits for CSA. Victims were predominantly girls (747, 94.8%) and perpetrators were predominantly men (763, 96.6%). The abuse first occurred before the age of 13 years in 315 victims (39.9%). For 468 (59.2%), more than one incident occurred before presentation. Compared to girls ≥13 years old, girls <13 years old were more frequently abused by a family member (47.7% versus 8.0%, @*CONCLUSION@#The findings highlight common characteristics of CSA cases, and can aid the future identification and protection of vulnerable children. The fact that most children presented after more than one incident suggests the need to more closely monitor and protect potentially at-risk children.

Early Cardiac Dysfunction in Biopsy-proven Nonalcoholic Fatty Liver Disease / 대한소화기학회지

Background/Aims@#Nonalcoholic fatty liver disease (NAFLD) encompasses a range of diseases from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) and has been linked to cardiovascular disease and sub-clinical cardiac remodeling. This paper presents a retrospective study of biopsy-proven NAFL and NASH to examine the differences in subclinical cardiac remodeling. @*Methods@#Patients were recruited from an institutional repository of patients with liver-biopsy-confirmed NAFLD. Patients with a transthoracic echocardiogram (TTE) within 12 months of the liver biopsy were included. The parameters of the diastolic dysfunction were reviewed for the differences between NAFL and NASH as well as between the stages and grades of NASH. @*Results@#Thirty-three patients were included in the study, 17 with NAFL and 16 with NASH. The NASH patients were more likely to have lower platelets, higher AST, higher ALT, and higher rates of type 2 diabetes mellitus, coronary artery disease, and hypertension than the NAFL patients. The E/e’ ratio on transthoracic echocardiogram was significantly higher in NASH compared to NAFL, advanced-stage NASH compared to early stage, and high-grade NASH compared to low-grade. The E/e’ ratio was also significantly higher in NASH than NAFL in patients without diabetes mellitus. The presence of diastolic dysfunction trended toward significance. The other markers of diastolic dysfunction were similar. Logistic regression revealed a statistical association with E/e' and NASH. @*Conclusions@#NASH patients had evidence of a higher E/e’ ratio than NAFL, and there was a trend towards a significant diastolic dysfunction. Patients with NASH compared to NAFL should be closely monitored for signs and symptoms of cardiac dysfunction.

Apamin-induced alterations in J774 1. 6 macrophage metabolism / [Alterações induzidas por apamina no metabolismo de macrófagos J774 1. 6]

Among the immune system cells, macrophages have an important role. Apamin, a bee venom constituent, is important in the defense of these insects. Thus, we aimed to evaluate the metabolism of J774 1.6 macrophage cell line when exposed to isolated and purified apamin, using cytotoxicity tests by MTT reduction and analysis by flow cytometry (apoptosis / necrosis, production of reactive oxygen species (ROS), membranous lipoperoxidation (LPO), electrical potential of the mitochondrial membrane (mMP) and DNA fragmentation). None of the tested concentrations (10 to 100µg/mL) were cytotoxic according to MTT reductions. Apoptosis rates decreased at concentrations of 2.5, 5.0, and 10.0µg/mL (P<0.05), while necrosis rates increased (P<0.05). However, rates of healthy cells at the highest tested concentration (10µg/mL) did not differ from control (P>0.05). Apamin did not alter ROS, LPO, or DNA fragmentation. Therefore, all analyzed concentrations (1.25 to 10µg/mL) decreased mMP. Such decrease in apoptosis might be due to a suppression of mitochondrial pro-apoptotic messengers, as this peptide causes no oxidative stress, lipid peroxidation, and DNA damage. Highly sensitive techniques are majorly important for proper interpretation of cellular toxicity mechanisms, combined with routine laboratory methods.(AU)

Das células do sistema imunológico, macrófagos desempenham um papel fundamental. Apamina, constituinte do veneno de abelhas, é importante na defesa destas. Objetivou-se avaliar o metabolismo da linhagem de macrófagos J774 1.6 expostos à apamina isolada e purificada, avaliando-se citotoxicidade por redução de MTT e análise por citometria de fluxo (apoptose / necrose, produção de espécies reativas de oxigênio (EROs), lipoperoxidação membranosa (LPO), potencial elétrico da membrana mitocondrial (MMP) e fragmentação do DNA). Nenhuma concentração testada (10 a 100µg / mL) foi citotóxica. As taxas de apoptose diminuíram nas concentrações 2,5, 5,0 e 10,0µg / mL (P<0,05), enquanto as de necrose aumentaram (P<0,05). Entretanto, as taxas de células saudáveis na maior concentração testada (10µg / mL) não diferiram do controle (P>0,05). A apamina não alterou as ERO, a LPO nem a fragmentação do DNA. Portanto, todas as concentrações analisadas (1,25 a 10µg / mL) diminuíram a mMP. Tal diminuição na apoptose pode ser por uma supressão de mensageiros pró-apoptóticos mitocondriais, já que este peptídeo não causa estresse oxidativo, peroxidação lipídica nem dano ao DNA. Técnicas altamente sensíveis são importantes para adequada interpretação dos mecanismos de citotoxicidade.(AU)

A comparative study of pregnancy outcome among women with preeclampsia and normotensive at the Alex Ekwueme Federal University Teaching Hospital Abakaliki, Nigeria

Background: Preeclampsia is a pregnancy specific multisystem disease and it is associated with increased maternal and perinatal morbidity and mortality. Any factor(s) which could reliably predict the likelihood of serious complications would be very valuable in predicting the associated adverse outcome. Objective of this study compare maternal and fetal outcomes of preeclamptic patients with normotensive control in Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria.Method: This was a 4-year retrospective case-control study of the pregnancy outcomes among preeclamptic and normotensive women managed in our facility between 1st January 2012 and 31st December 2015. Data analysis was done using Epi Info software 7.2.1.Results: During the study period there were 6,585 deliveries among which 92 of the patients were managed for preeclampsia. This gives a prevalence of 1.4% or 14 per 1000 deliveries. There was no difference in the age and parity of the control. Most of the preeclamptic patients managed over the study period were unbooked for antenatal care in the facility (p value <0.0001). Preeclamptic patients were more likely to be delivered preterm (p value was <0.0001), and by caesarean section compared to the control. They were also more likely to have babies with low birth weights and poorer fetal outcomes. There was no difference in maternal mortality between both groups.Conclusion: Preeclampsia is associated with the unbooked status and poorer perinatal outcome compared with normotensive women. There is need to encourage women to book for antenatal care for prompt identification and management of these women.

What is the moral collapse in the Cochrane Collaboration about?

On September 13, 2018, one of the founders of the Cochrane Collaboration was expelled from the organisation, by a narrow vote of 6 to 5. Many see this as a moral collapse in what was once a magnificent grassroots organisation, guided by ethical principles and helping people make better decisions about healthcare interventions. I am that excommunicated person. I review here the essential issues leading to my expulsion, which occurred primarily because, in my capacity as a board member, I had challenged the CEO’s virtually total control over the board, his mismanagement of Cochrane, and the direction in which he was taking the organisation. My criticism of psychiatric drugs and the highly prestigious Cochrane review of HPV vaccines also played a role. Freedom of Information requests revealed that the CEO went well beyond his brief to demand my removal from the Nordic Cochrane Centre, resulting in my sacking.

Chemical and cytotoxic analyses of three varieties of Brazilian propolis (green propolis, jataí propolis and brown propolis) and its anti-Sporothrix brasiliensis in vitro activity / [Análises químicas e citotóxicas de três variedades de própolis brasileiras (própolis verde, própolis jataí e própolis marrom) e sua atividade in vitro anti-Sporothrix brasiliensis]

In this study, we described the antifungal activity of three Brazilian propolis extracts: brown, green and from jataí bees against Sporothrix brasiliensis. The extracts were obtained from ethanolic extraction and their chemical composition was determined by high-performance liquid chromatography coupled to mass spectrometry. The cellular toxicity was measured in MDBK (Madin-Darby Bovine Kidney) cells and quantified by the MTT assay (3- (4,5 dimethylthiazol-2yl -2,5-diphenyl-2H bromine tetrazolato). For antifungal activity, the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined by broth microdilution. The results showed that cell toxicity was not observed at lower concentrations (0.097 to 0.39μg/ml) for all extracts in comparison to cell control. Among the chemical compounds identified, caffeic acid, p-coumaric acid, chlorogenic acid, ferulic acid and rutin were quantified. In antifungal activity, green and jataí did not exhibit activity against the isolates (MIC and MFC greater than 0.78mg/ml). However, all isolates of S. brasiliensis were sensitive to brown propolis (MIC of 0.09 to 0.78mg/ml), including the standard strain (P<0.001). Among the Brazilian propolis studied, the brown propolis showed activity against the S. brasiliensis isolates and more studies should be undertaken in order to evaluate its promising use in the treatment of sporotrichosis.(AU)

Neste estudo, descreveu-se a atividade antifúngica de três extratos de própolis brasileiras: marrom, verde e de abelhas jataí (Tetragonisca angustula), contra Sporothrix brasiliensis. Os extratos foram obtidos de extração etanólica, e a sua composição química foi determinada por cromatografia líquida de alta eficiência, acoplada à espectrometria de massa. A toxicidade celular foi medida em células MDBK (Madin-Darby Bovine Kidney), avaliada por observação microscópica e quantificada pelo ensaio MTT (3- (4,5-dimetiltiazol-2-ilo -2,5-difenil-2H bromo tetrazolato). Para a atividade antifúngica, determinou-se a concentração inibitória mínima (CIM) e a concentração fungicida mínima (CFM) por meio de microdiluição em caldo. Os resultados mostraram que a toxicidade celular não foi observada em concentrações menores (0,097 a 0,39μg/ml). Entre os compostos químicos identificados, foram quantificados o ácido cafeico, ácido p-cumárico, ácido clorogênico, ácido ferúlico e a rutina. Na atividade antifúngica, as própolis verde e jataí não apresentaram atividade contra os isolados (CIM e CFM maior que 0,78mg/ml), porém todos os isolados de S. brasiliensis foram sensíveis à própolis marrom (CIM de 0,09 a 0,78mg/ml), incluindo a cepa padrão (P<0,001). Entre as própolis brasileiras estudadas, a marrom mostrou atividade contra S. brasiliensis, e mais estudos devem ser realizados para avaliar seu uso promissor no tratamento da esporotricose.(AU)

Robotic lower pelvic port placement for optimal upper paraaortic lymph node dissection / 부인종양

OBJECTIVE: Upper paraaortic lymph node dissection (UPALD) to the infrarenal level is one of the most challenging robotic procedures. Because robotic system has the limitation in robotic arm mobility. This surgical video introduces a novel robotic approach, lower pelvic port placement (LP3), to perform optimally and simultaneously both UPALD and pelvic procedures in gynecologic cancer patients using da Vinci Xi system. METHODS: The patient presented with high-grade endometrial cancer. She underwent robotic surgical staging operation. For the setup of the LP3, a line was drown between both anterior superior iliac spines. At 3 cm below this line, another line was drown and four robotic ports were placed on this line. RESULTS: After paraaortic lymph node dissection (PALD) was completed, the boom of robotic system was rotated 180° to retarget for the pelvic lateral displacement. Robotic ports were placed and docked again. The operation was completed robotically without any complication. CONCLUSION: The LP3 was feasible for performing simultaneously optimal PALD as well as procedures in pelvic cavity in gynecologic cancer patients. The advantage of LP3 technique is the robotic port placement that affords for multi-quadrant surgery, abdominal and pelvic dissection. The LP3 is facilitated by utilizing advanced technology of Xi system, including the patient clearance function, the rotating boom, and ‘port hopping’ that allows using every ports for a camera. The LP3 will enable surgeons to extend the surgical indication of robotic surgical system in the gynecologic oncologic field.

Personalized medicine in non-small cell lung cancer: a review from a pharmacogenomics perspective

Non-small cell lung cancer is a prevalent and rapidly-expanding challenge to modern medicine. While generalized medicine with traditional chemotherapy yielded comparatively poor response rates and treatment results, the cornerstone of personalized medicine using genetic profiling to direct treatment has exalted the successes seen in the field and raised the standard for patient treatment in lung and other cancers. Here, we discuss the current state and advances in the field of personalized medicine for lung cancer, reviewing several of the mutation-targeting strategies that are approved for clinical use and how they are guided by patient genetic information. These classes include inhibitors of tyrosine kinase (TKI), anaplastic lymphoma kinase (ALK), and monoclonal antibodies. Selecting from these treatment plans and determining the optimal dosage requires in-depth genetic guidance with consideration towards not only the underlying target genes but also other factors such as individual metabolic capability and presence of resistance-conferring mutations both directly on the target gene and along its cascade(s). Finally, we provide our viewpoints on the future of personalized medicine in lung cancer, including target-based drug combination, mutation-guided drug design and the necessity for data of population genetics, to provide rough guidance on treating patients who are unable to get genetic testing.

Comparison of bone scintigraphy with single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) in the detection of sphenoid bone extension from nasopharyngeal carcinoma (NPCA): A retrospective study

BACKGROUND/OBJECTIVE: Skeletal metastasis is one of the major clinical problems in managing cases of NPCA. Beginning osseous metastasis in the form of sphenoid bone extension is commonly seen in NPCA.Imaging modalities mainly used in detecting sphenoid bone extension are bone scintigraphy with SPECT and MRI. In this paper, the ability of bone scintigraphy with SPECT and MRI in detecting sphenoid bone extension was compared.MATERIALS AND METHODS: Twelve patients with nasopharyngeal carcinoma were studied by bone scintigraphy with SPECT and MRI. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each modality against the gold standard, which is sphenoid bone biopsy, were computed. Statistical analysis was done using the McNemar's Test.RESULTS: The overall performances of bone scintigraphy with SPECT versus MRI were the following: sensitivity 89% vs 78%, specificity 33% vs 67%, positive predictive value 80% vs 88% and negative predictive value 50% vs 50%. There was no significant difference between the two modalities using McNemar's test (p>0.05).CONCLUSION: Bone scintigraphy with SPECT and MRI were both equally effective and were complementary with each other in detecting sphenoid bone extension in patients with NPCA.

Comparison of bone scintigraphy with single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) in the detection of sphenoid bone extension from nasopharyngeal carcinoma (NPCA): A retrospective study

BACKGROUND/OBJECTIVE: Skeletal metastasis is one of the major clinical problems in managing cases of NPCA. Beginning osseous metastasis in the form of sphenoid bone extension is commonly seen in NPCA.Imaging modalities mainly used in detecting sphenoid bone extension are bone scintigraphy with SPECT and MRI. In this paper, the ability of bone scintigraphy with SPECT and MRI in detecting sphenoid bone extension was compared.MATERIALS AND METHODS: Twelve patients with nasopharyngeal carcinoma were studied by bone scintigraphy with SPECT and MRI. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each modality against the gold standard, which is sphenoid bone biopsy, were computed. Statistical analysis was done using the McNemar's Test.RESULTS: The overall performances of bone scintigraphy with SPECT versus MRI were the following: sensitivity 89% vs 78%, specificity 33% vs 67%, positive predictive value 80% vs 88% and negative predictive value 50% vs 50%. There was no significant difference between the two modalities using McNemar's test (p>0.05).CONCLUSION: Bone scintigraphy with SPECT and MRI were both equally effective and were complementary with each other in detecting sphenoid bone extension in patients with NPCA.

Successful therapy of severe pseudomembranous clostridium difficile colitis using a combination of fecal microbiota therapy and fidaxomicin

Objective: The aim of this work was to describe the use of a combination of fidaxomicin and fecal microbiota therapy [FMT] in Clostridium difficile infection [CDI]

Clinical Presentation and Intervention: A 78-year-old female, who was admitted for surgery due to acute diverticulitis caused by postoperative complications and broad antibiotic therapy, developed CDI-induced colitis. Despite the introduction of metronidazole and vancomycin therapy, her clinical condition continued to deteriorate. She was transferred to the intensive care unit where FMT followed by fidaxomicin were performed because her C-reactive protein and leucocyte levels remained elevated. Further clinical improvement and the resolution of colitis was observed

Conclusion: In this case, severe CDI colitis was successfully treated with the combination of FMT and fidaxomicin

Hypertrophic pachymeningitis and the syndrome of inappropriate antidiuretic hormone secretion: coincidence or cause?

Objective: To investigate a potential cause of the syndrome of inappropriate antidiuretic hormone secretion [SIADH]

Clinical Presentation and Intervention: A 70-year-old female patient had nausea and collapsed. Although euvolemic, pathological laboratory findings showed hyponatremia and hypoosmolality, and cerebral magnetic resonance imaging showed hypertrophic pachymeningitis. Secondary hyper-trophic pachymeningitis was excluded. Other nonneurolog-ical reasons for SIADH were also excluded. Moderate fluid restriction restored an almost normal serum osmolality and sodium

Conclusion: This case of SIADH was conservatively treated with moderate fluid restriction that almost restored normal serum osmolality and sodium levels