Increased heterogeneity in expression of genes associated with cancer progression and drug resistance.

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

Retrospective analysis of clinico-laboratory parameters, outcome and predictors of scrub typhus co- infection in covid-19 affected children.

The objective of this study was to describe clinico-laboratory parameters, outcome and predictors of scrub typhus co- infection in COVID-19 affected children. Ours was a retrospective analysis done in a tertiary care pediatric COVID facility. COVID-19 positive children in the age group of 1 month to 12 years who were tested for scrub typhus co-infection between May to August 2020 were included in the study. In all positive cases, clinical, laboratory, treatment and outcome data were analyzed. Relevant data were compared between scrub typhus confirmed, and suspected but negative patients. All six patients with co-infection had fever for >5 days and four had features of cerebral involvement. These had lymphocytic pleocytosis in cerebrospinal fluid (CSF) analysis and two had eschar. Screening for scrub typhus in persistently febrile children residing in highly endemic areas is highly recommended.

Impact of intensified control on visceral leishmaniasis in a highly-endemic district of Bihar, India: an interrupted time series analysis.

Visceral leishmaniasis (VL) is declining in India and the World Health Organization's (WHO) 2020 'elimination as a public health problem' target has nearly been achieved. Intensified combined interventions might help reach elimination, but their impact has not been assessed. WHO's Neglected Tropical Diseases 2021-2030 roadmap provides an opportunity to revisit VL control strategies. We estimated the combined effect of a district-wide pilot of intensified interventions in the highly-endemic Vaishali district, where cases fell from 3,598 in 2012-2014 to 762 in 2015-2017. The intensified control approach comprised indoor residual spraying with improved supervision; VL-specific training for accredited social health activists to reduce onset-to-diagnosis time; and increased Information Education & Communication activities in the community. We compared the rate of incidence decrease in Vaishali to other districts in Bihar state via an interrupted time series analysis with a spatiotemporal model informed by previous VL epidemiological estimates. Changes in Vaishali's rank among Bihar's endemic districts in terms of monthly incidence showed a change pre-pilot (3rd highest out of 33 reporting districts) vs. during the pilot (9th) (p<1e-10). The rate of decline in Vaishali's incidence saw no change in rank at 11th highest, both pre-pilot & during the pilot. Counterfactual model simulations suggest an estimated median of 352 cases (IQR 234-477) were averted by the Vaishali pilot between January 2015 and December 2017, which was robust to modest changes in the onset-to-diagnosis distribution. Strengthening control strategies may have precipitated a substantial change in VL incidence in Vaishali and suggests this approach should be piloted in other highly-endemic districts.

Classification of malignant tumors by a non-sequential recurrent ensemble of deep neural network model.

Many significant efforts have so far been made to classify malignant tumors by using various machine learning methods. Most of the studies have considered a particular tumor genre categorized according to its originating organ. This has enriched the domain-specific knowledge of malignant tumor prediction, we are devoid of an efficient model that may predict the stages of tumors irrespective of their origin. Thus, there is ample opportunity to study if a heterogeneous collection of tumor images can be classified according to their respective stages. The present research work has prepared a heterogeneous tumor dataset comprising eight different datasets from The Cancer Imaging Archives and classified them according to their respective stages, as suggested by the American Joint Committee on Cancer. The proposed model has been used for classifying 717 subjects comprising different imaging modalities and varied Tumor-Node-Metastasis stages. A new non-sequential deep hybrid model ensemble has been developed by exploiting branched and re-injected layers, followed by bidirectional recurrent layers to classify tumor images. Results have been compared with standard sequential deep learning models and notable recent studies. The training and validation accuracy along with the ROC-AUC scores have been found satisfactory over the existing models. No model or method in the literature could ever classify such a diversified mix of tumor images with such high accuracy. The proposed model may help radiologists by acting as an auxiliary decision support system and speed up the tumor diagnosis process.

Kala-azar elimination in a highly-endemic district of Bihar, India: A success story.

BACKGROUND: Visceral leishmaniasis (VL) or Kala-azar has been a major public health problem in Bihar, India, for several decades. A few VL infected districts including Vaishali have reported >600 cases annually. Hence, in 2015, the Government of India entrusted ICMR-Rajendra Memorial Research Institute of Medical Sciences, Patna, to implement an integrated control strategy for achieving the VL elimination target (<1 case per 10,000 people at the block level) in the Vaishali District of Bihar. METHODOLOGY: This study was conducted between January 2015 and December 2016. An integrated control strategy including the spatio-temporal mapping of VL-case distribution, active case detection, chemical-based vector control using indoor residual spraying (IRS), community awareness campaigns, the training of IRS members, the training of medical doctors for effective treatment, daily monitoring and the supervision of IRS activities, logistic management, post-IRS quality assurance, epidemiological surveillance, and entomological monitoring was performed. An insecticide quantification test was performed for evaluating the IRS quality on sprayed walls. A modern compression pump was used to maintain spray quality on different wall surfaces. The impact of IRS was assessed through sand fly collection in human dwellings and cattle sheds in pre- and post-IRS. The insecticide susceptibility of local P. argentipes was performed before each IRS round (in February and June) during 2015-2016. Statistical analysis such as the mean, percentage, and 95% CI were used to summarize the results. FINDINGS: All 16 blocks of the Vaishali District achieved the VL elimination target in 2016. The integrated VL control strategy helped reduce the number of VL cases from 664 in 2014 to 163 in 2016 and the number of endemic villages from 282 in 2014 to 142 in 2016. The case reduction rate was increased from 22.6% in 2014 to 58.8% in 2016. On average, 74 VL infected villages became Kala-azar free each year from 2015 to 2016. CONCLUSIONS: The results of this study suggest that the elimination of VL is possible from all endemic blocks of Bihar if the integrated Vaishali VL control strategy is applied under strong monitoring and supervision.

Long Non-coding RNAs in Pulmonary Neuroendocrine Neoplasms.

Pulmonary neuroendocrine neoplasms (NENs) are classified into low-grade neuroendocrine tumors and high-grade neuroendocrine carcinomas (NECs). There are significant differences in therapeutic strategies of the different NEN subtypes, and therefore, precise classification of pulmonary NENs is critical. However, challenges in pulmonary NEN classification include overlap of diagnostic histological features among the subtypes and reduced or negative expression of neuroendocrine markers in poorly differentiated pulmonary NECs. Recently, transcription factor insulinoma-associated protein 1 (INSM1) was identified as a sensitive marker of neuroendocrine and neuroepithelial differentiation. In this study, INSM1 expression was detected by immunohistochemistry in greater than 94% of pulmonary NENs, indicating that it is a highly sensitive marker of pulmonary NENs and is useful to detect poorly differentiated pulmonary NECs. Although there are well-established morphological and immunohistologic criteria to diagnose pulmonary NENs, there is no universal consensus regarding prognostic markers of pulmonary NENs. Studies have shown that non-small cell lung cancers express long non-coding RNAs (lncRNAs), which regulate gene expression, epithelial-to-mesenchymal transition, and carcinogenesis. We characterized expression and function of lncRNAs, including HOX transcript antisense RNA (HOTAIR), maternally expressed 3 (MEG3), and prostate cancer antigen 3 (PCA3) in pulmonary NENs, including typical carcinoid tumors, atypical carcinoid tumors, small cell lung carcinoma (SCLC/NEC), and large cell neuroendocrine carcinoma (LCNEC/NEC). In situ hybridization and real-time polymerase chain reaction studies showed higher expression (p < 0.01) of all lncRNAs in SCLC/NEC. Small interfering RNA studies indicated a role for MEG3 and PCA3 in tumor proliferation. Therefore, these lncRNAs may serve as prognostic indicators of pulmonary NEN aggressiveness and as possible therapeutic targets.

Prediction of Non-small Cell Lung Cancer Histology by a Deep Ensemble of Convolutional and Bidirectional Recurrent Neural Network.

Histology subtype prediction is a major task for grading non-small cell lung cancer (NSCLC) tumors. Invasive methods such as biopsy often lack in tumor sample, and as a result radiologists or oncologists find it difficult to detect proper histology of NSCLC tumors. The non-invasive methods such as machine learning may play a useful role to predict NSCLC histology by using medical image biomarkers. Few attempts have so far been made to predict NSCLC histology by considering all the major subtypes. The present study aimed to develop a more accurate deep learning model by clubbing convolutional and bidirectional recurrent neural networks. The NSCLC Radiogenomics dataset having 211 subjects was used in the study. Ten best models found during experimentation were averaged to form an ensemble. The model ensemble was executed with 10-fold repeated stratified cross-validation, and the results got were tested with metrics like accuracy, recall, precision, F1-score, Cohen's kappa, and ROC-AUC score. The accuracy of the ensemble model showed considerable improvement over the best model found with the single model. The proposed model may help significantly in the automated prognosis of NSCLC and other types of cancers.

Assessing the combined effects of household type and insecticide effectiveness for kala-azar vector control using indoor residual spraying: a case study from North Bihar, India.

BACKGROUND: Indoor residual spraying (IRS) is the mainstay for vector control intervention of visceral leishmaniasis (VL) in India. Little is known on the control effects of IRS on different household types. Here, we assessed if IRS with insecticides has an equal residual and interventional effect on all household types in a village. We also developed a combined spatial-risk map and a sand fly, Phlebotomus argentipes density analytical model based on household characteristics, insecticide susceptibility and IRS-status to explore the spatio-temporal distributions of the vector at a micro-scale level. METHODS: This study was carried out in two villages of Mahnar block in Vaishali district, Bihar. IRS using two insecticides [dichlorodiphenyltrichloroethane (DDT 50%) and synthetic pyrethroid (SP 5%)] was evaluated for VL-vector (P. argentipes) control. Temporal residual efficacy of the insecticides on different wall-surface types was evaluated using the cone-bioassay technique according to WHO guidelines. Insecticide susceptibility of local P. argentipes was explored using the tube-bioassay method. Pre- and post-IRS sand fly densities were monitored in human dwellings and animal shelters using Centers for Disease Control light-traps installed between 18:00-6:00 h. A best-fit model for sand fly density analysis was developed using multiple logistic regression analysis. Geographical information system based spatial analysis techniques were employed to map the household type distribution of insecticide susceptibility of the vector, and IRS-status of the households to interpret the spatio-temporal distributions of P. argentipes. RESULTS: Phlebotomus argentipes was highly susceptible to SP (100%) but showed high resistance to DDT with a 49.1% mortality rate. SP-IRS has been reported as having better community acceptance than DDT-IRS in all household types. Residual efficacies were varied between wall-surfaces; both insecticides failed to achieve the duration of IRS effectiveness recommended by the WHO. Reduction in P. argentipes counts due to SP-IRS was higher than DDT-IRS between household groups (i.e. sprayed and sentinel), in all intervals post-IRS. Combined spatial risk-maps revealed a better control effect of SP-IRS on sand flies than DDT-IRS in all household types risk-zones. The multilevel logistic regression analysis explored five risk-factors that were strongly associated with the density of P. argentipes. CONCLUSIONS: The results contribute to furthering current understanding of IRS-practices for control of visceral leishmaniasis in endemic Bihar, which may help in future actions for improvements.

Automated AJCC (7th edition) staging of non-small cell lung cancer (NSCLC) using deep convolutional neural network (CNN) and recurrent neural network (RNN).

PURPOSE: A large chunk of lung cancers are of the type non-small cell lung cancer (NSCLC). Both the treatment planning and patients' prognosis depend greatly on factors like AJCC staging which is an abstraction over TNM staging. Many significant efforts have so far been made towards automated staging of NSCLC, but the groundbreaking application of a deep neural networks (DNNs) is yet to be observed in this domain of study. DNN is capable of achieving higher level of accuracy than the traditional artificial neural networks (ANNs) as it uses deeper layers of convolutional neural network (CNN). The objective of the present study is to propose a simple yet fast CNN model combined with recurrent neural network (RNN) for automated AJCC staging of NSCLC and to compare the outcome with a few standard machine learning algorithms along with a few similar studies. METHODS: The NSCLC radiogenomics collection from the cancer imaging archive (TCIA) dataset was considered for the study. The tumor images were refined and filtered by resizing, enhancing, de-noising, etc. The initial image processing phase was followed by texture based image segmentation. The segmented images were fed into a hybrid feature detection and extraction model which was comprised of two sequential phases: maximally stable extremal regions (MSER) and the speeded up robust features (SURF). After a prolonged experiment, the desired CNN-RNN model was derived and the extracted features were fed into the model. RESULTS: The proposed CNN-RNN model almost outperformed the other machine learning algorithms under consideration. The accuracy remained steadily higher than the other contemporary studies. CONCLUSION: The proposed CNN-RNN model performed commendably during the study. Further studies may be carried out to refine the model and develop an improved auxiliary decision support system for oncologists and radiologists.

Clinical Profile and Outcome of Patients with Acute Poisoning Admitted in Intensive Care Unit of Tertiary Care Center in Eastern Nepal.

BACKGROUND: Acute poisoning is a common health-care problem requiring admission in the intensive care unit (ICU) in the developing countries. The study was conducted to assess the epidemiological parameters of acute poisoning and factors affecting clinical course and outcome of the patients in ICU in the eastern part of Nepal. METHODOLOGY: This was a prospective observational study conducted at ICU of tertiary care hospital in the eastern part of Nepal for the duration of 2 years. All the acute poisoning cases admitted in the ICU were studied for epidemiological profiles, poisoning characteristics, and various clinical factors affecting the outcome of the patients. RESULTS: Eighty-five patients with acute poisoning were included in the study. Suicidal attempt leading to acute poisoning was seen in majority of the young population. Majority of the poisoning was due to the organophosphorous compounds (43.5%). Patients with organophosphorous poisoning had a significantly longer duration of ICU stay (P = 0.020). The survival of the patients was significantly affected by age, duration of presentation to the hospital, Glasgow Coma Scale, Sequential Organ Failure Assessment score, need for mechanical ventilation, duration of ICU stay, hepatic failure, coagulopathy, and need for vasoactive drugs (P < 0.05). The independent predictors of mortality observed in the study were age, delayed presentation to the hospital, hepatic failure, and need for mechanical ventilation. CONCLUSION: Organophosphorous poisoning was the most common acute poisoning in young population leading to the ICU admission. Older age, delayed initiation of the resuscitative measures, need for mechanical ventilation, and hepatic failure significantly affected the mortality.

Trends in spatio-temporal dynamics of visceral leishmaniasis cases in a highly-endemic focus of Bihar, India: an investigation based on GIS tools.

BACKGROUND: Visceral leishmaniasis (VL) in Bihar State (India) continues to be endemic, despite the existence of effective treatment and a vector control program to control disease morbidity. A clear understanding of spatio-temporal distribution of VL may improve surveillance and control implementation. This study explored the trends in spatio-temporal dynamics of VL endemicity at a meso-scale level in Vaishali District, based on geographical information systems (GIS) tools and spatial statistical analysis. METHODS: A GIS database was used to integrate the VL case data from the study area between 2009 and 2014. All cases were spatially linked at a meso-scale level. Geospatial techniques, such as GIS-layer overlaying and mapping, were employed to visualize and detect the spatio-temporal patterns of a VL endemic outbreak across the district. The spatial statistic Moran's I Index (Moran's I) was used to simultaneously evaluate spatial-correlation between endemic villages and the spatial distribution patterns based on both the village location and the case incidence rate (CIR). Descriptive statistics such as mean, standard error, confidence intervals and percentages were used to summarize the VL case data. RESULTS: There were 624 endemic villages with 2719 (average 906 cases/year) VL cases during 2012-2014. The Moran's I revealed a cluster pattern (P < 0.05) of CIR distribution at the meso-scale level. On average, 68 villages were newly-endemic each year. Of which 93.1% of villages' endemicity were found to have occurred on the peripheries of the previous year endemic villages. The mean CIR of the endemic villages that were peripheral to the following year newly-endemic villages, compared to all endemic villages of the same year, was higher (P < 0.05). CONCLUSION: The results show that the VL endemicity of new villages tends to occur on the periphery of villages endemic in the previous year. High-CIR plays a major role in the spatial dispersion of the VL cases between non-endemic and endemic villages. This information can help achieve VL elimination throughout the Indian subcontinent by improving vector control design and implementation in highly-endemic district.

Analysis of miR-96 and miR-133a Expression in Gastrointestinal Neuroendocrine Neoplasms.

Grading of gastrointestinal neuroendocrine neoplasms (GI-NENs) relies mainly on mitotic activity and Ki-67 proliferation index. It is often difficult to predict metastatic potential of these neoplasms. Recent studies have shown that GI-NENs express a wide spectrum of microRNAs. We examined two microRNAs (miR-96 and miR-133a) that were recently identified in GI-NENs to determine if they could assist in evaluating the biological behavior of these neoplasms. A tissue microarray (TMA) was constructed with 51 primary GI-NENs, mainly from the small intestine and metastatic tumors from the same cases, including liver metastases (N = 20) and lymph node metastases (N = 33). The cases were immunohistochemically stained for chromogranin A, synaptophysin, and Ki-67. In situ hybridization (ISH) was done with probes from Exiqon (Woburn, MA). Quantitative RT-PCR (qRT-PCR) was also performed on all the cases (N = 105). ISH analysis showed that miR-96 expression was significantly higher in the liver metastatic neoplasms compared to the primary NENs (p < 0.05); however, it was not significant for miR-133a expression levels. qRT-PCR showed that miR-96 levels were increased during progression from the primary tumors to metastases in the liver. qRT-PCR showed a decrease in miR-133a in the liver metastases compared to the primary tumors (p < 0.05). Appendiceal carcinoids without metastases (n = 3) had low levels of miR-96 and high levels of miR-133a by qPCR. The study suggests that analysis of these two microRNAs by qRT-PCR may be useful in detecting more aggressive GI-NENs and that ISH analysis may also assist in the evaluation of patients with GI-NENs.

Spatial Distribution of Phlebotomus argentipes (Diptera: Psychodidae) in Eastern India, a Case Study Evaluating Multispatial Resolution Remotely Sensed Environmental Evidence and Microclimatic Data.

Remote sensing, a powerful tool for analyzing landscape factors, is being used to explore the spatial ecology of vectors of several diseases. This study aims to explore the role of buffer size in identification and quantification of geo-environmental factors from multispatial resolution satellite data and its application along with microclimatic data to kala-azar vector abundance modeling.Sand fly abundance and microclimatic data were collected from 210 sample sites during the premonsoon and postmonsoon season of 2014 from Muzaffarpur district of Bihar (India). Linear imaging self-scanning sensor (LISS-III; 23.5 m) and advanced wide field sensor (AWiFS; 56 m) imageries were used for generating environmental variables at 300- and 500-m buffer zones. Four analytical models of sand fly density were developed and evaluated for predictive accuracy.A total of 33 geo-environmental and four microclimatic variables were tested for the prediction of sand fly density, of which the best four were maximum temperature, relative humidity, Euclidean nearest-neighbor distance of settlement area to mixed bush-grass land, and surface water body. Predictive accuracy of the LISS-III models was found to be higher than AWiFS models at all buffer sizes.The results show that geo-environmental parameters and microclimatic data are the best predictors for sand fly density modeling. Buffer sizes play an important role in identifying the explanatory variables. Model parameters may be useful in identifying predisposing factors of sand fly habitat suitability at the micro level.

Chronic Arsenic Exposure and Risk of Post Kala-azar Dermal Leishmaniasis Development in India: A Retrospective Cohort Study.

BACKGROUND: Visceral leishmaniasis (VL), with the squeal of Post-kala-azar dermal leishmaniasis (PKDL), is a global threat for health. Studies have shown sodium stibogluconate (SSG) resistance in VL patients with chronic arsenic exposure. Here, we assessed the association between arsenic exposure and risk of developing PKDL in treated VL patients. METHODS: In this retrospective study, PKDL patients (n = 139), earlier treated with SSG or any other drug during VL, were selected from the study cohort. Trained physicians, unaware of arsenic exposure, interviewed them and collected relevant data in a questionnaire format. All probable water sources were identified around the patient's house and water was collected for evaluation of arsenic concentration. A GIS-based village-level digital database of PKDL cases and arsenic concentration in groundwater was developed and individual point location of PKDL cases were overlaid on an integrated GIS map. We used multivariate logistic regression analysis to assess odds ratios (ORs) for association between arsenic exposure and PKDL development. RESULTS: Out of the 429 water samples tested, 403 had arsenic content of over 10 µg/L, with highest level of 432 µg/L among the seven study villages. Multivariate adjusted ORs for risk of PKDL development in comparison of arsenic concentrations of 10.1-200 µg/L and 200.1-432.0 µg/L were 1.85 (1.13-3.03) and 2.31 (1.39-3.8) respectively. Interestingly, similar results were found for daily dose of arsenic and total arsenic concentration in urine sample of the individual. The multivariate-adjusted OR for comparison of high baseline arsenic exposure to low baseline arsenic exposure of the individuals in the study cohort was 1.66 (95% CI 1.02-2.7; p = 0.04). CONCLUSION: Our findings indicate the need to consider environmental factors, like long time arsenic exposure, as an additional influence on treated VL patients towards risk of PKDL development in Bihar.

IGF-loaded silicon and zinc doped brushite cement: physico-mechanical characterization and in vivo osteogenesis evaluation.

Dopants play critical roles in controlling the physical, mechanical, degradation kinetics, and in vivo properties of calcium phosphates. The aim of the present study was to evaluate the effects of silicon (Si) and zinc (Zn) dopants on the physico-mechanical and in vivo osteogenesis properties of brushite cements (BrCs) alone and in combination with insulin like growth factor 1 (IGF-1). Addition of 0.5 wt% Si did not alter the setting time, ß-TCP content, and compressive strength of BrCs significantly; however, 0.25 wt% Zn incorporation was accompanied by a significant decrease in mechanical strength from 4.78 ± 0.21 MPa for pure BrC to 3.78 ± 0.59 MPa and 3.28 ± 0.22 MPa for Zn-BrC and Si/Zn-BrC, respectively. The in vivo bone regeneration properties of doped BrCs alone and in combination with IGF-1 were assessed and compared using chronological radiography, histology, scanning electron microscopy and fluorochrome labeling at 2 and 4 months post implantation in a rabbit femoral defect model. Based on in vivo characterization focusing on osteogenesis and vasculogenesis, Si-BrC and Si/Zn-BrC showed the best performance followed by Zn-BrC and pure BrCs. Addition of IGF-1 further improved bone regeneration. Our findings confirm that addition of Si and/or Zn alters the physico-mechanical properties of BrCs and promotes the early stage in vivo osseointegration and bone remodeling properties.

Insecticide susceptibility of Phlebotomus argentipes & assessment of vector control in two districts of West Bengal, India.

BACKGROUND & OBJECTIVES: Kala-azar or visceral leishmanisis (VL) is known to be endemic in several States of India including West Bengal (WB). Only meager information is available on the vector dynamics of its vector species, Phlebotomus argentipes particularly in relation to control measure from this State. Hence, a pilot study was undertaken to assess the control strategy and its impact on vector in two endemic districts of WB, India. METHODS: Two villages each from the two districts, Maldah and Burdwan, were selected for the study. Seasonal variation of sandflies was observed during pre-monsoon, post-monsoon and winter seasons. Susceptibility test of P. argentipes against DDT and bioassay on DDT sprayed wall and on long lasting insecticide nets (LN) Perma Net [®] 2.0 were conducted as per the WHO standard methods. RESULTS: P. argentipes density was high during March to October. Susceptibility status of P. argentipes ranged from 40 to 61.54 per cent. Bioassay test showed 57.89 per cent mortality against LN PermaNet [®] -2.0. and 50 per cent against DDT on wall within 30 min of exposure. INTERPRETATION & CONCLUSIONS: Despite the integrated vector management approach, the sandfly population was high in the study area. The reason could be development of resistance in P. argentipes against DDT and low effectiveness of LN PermaNet [®] -2.0. The more pragmatic step will be to conduct large studies to monitor the susceptibility level in P. argentipes against DDT.

Quantitative magnetic resonance imaging of hepatic steatosis: Validation in ex vivo human livers.

UNLABELLED: Emerging magnetic resonance imaging (MRI) biomarkers of hepatic steatosis have demonstrated tremendous promise for accurate quantification of hepatic triglyceride concentration. These methods quantify the proton density fat-fraction (PDFF), which reflects the concentration of triglycerides in tissue. Previous in vivo studies have compared MRI-PDFF with histologic steatosis grading for assessment of hepatic steatosis. However, the correlation of MRI-PDFF with the underlying hepatic triglyceride content remained unknown. The aim of this ex vivo study was to validate the accuracy of MRI-PDFF as an imaging biomarker of hepatic steatosis. Using ex vivo human livers, we compared MRI-PDFF with magnetic resonance spectroscopy-PDFF (MRS-PDFF), biochemical triglyceride extraction, and histology as three independent reference standards. A secondary aim was to compare the precision of MRI-PDFF relative to biopsy for the quantification of hepatic steatosis. MRI-PDFF was prospectively performed at 1.5 Tesla in 13 explanted human livers. We performed colocalized paired evaluation of liver fat content in all nine Couinaud segments using single-voxel MRS-PDFF (n=117) and tissue wedges for biochemical triglyceride extraction (n=117), and five core biopsies performed in each segment for histologic grading (n=585). Accuracy of MRI-PDFF was assessed through linear regression with MRS-PDFF, triglyceride extraction, and histology. Intraobserver agreement, interobserver agreement, and repeatability of MRI-PDFF and histologic grading were assessed through Bland-Altman analyses. MRI-PDFF showed an excellent correlation with MRS-PDFF (r=0.984, confidence interval 0.978-0.989) and strong correlation with histology (r=0.850, confidence interval 0.791-0.894) and triglyceride extraction (r=0.871, confidence interval 0.818-0.909). Intraobserver agreement, interobserver agreement, and repeatability showed a significantly smaller variance for MRI-PDFF than for histologic steatosis grading (all P<0.001). CONCLUSION: MRI-PDFF is an accurate, precise, and reader-independent noninvasive imaging biomarker of liver triglyceride content, capable of steatosis quantification over the entire liver.

Survival trends in metastatic bladder cancer in the United States: a population based study.

BACKGROUND: To evaluate the relative survival rates for patients with metastatic bladder cancer (MBC) over the last two decades in the United States: 1991-2000 and 2001-2010. MATERIALS AND METHODS: We used the Surveillance, Epidemiology, and End Results (SEER*Stat) Program to analyze 6-month and 12-month relative survival rates of American Joint Committee on Cancer (AJCC) Stage IV bladder cancer patients included in the SEER database. We used Z-test in the SEER*Stat Program to compare relative survival rates among cohorts of patients categorized by race, gender, and age groups (<60 and ≥ 60 years). RESULTS: The dataset comprised 4195 and 7629 patients with AJCC Stage IV bladder cancer in the periods 1991-2000 and 2001-2010, respectively. There were statistically significant decreases in relative survival rates for pooled data across all races (67.8 ± 0.7% in 1991-2000 vs. 64.7 ± 0.5% in 2001-2010, P < 0.01), among Caucasian (CC) and other races (Oth) men + women, among CC and Oth men, and several cohorts among men and 60 + Oth-women when categorized by age. African American patients did not show significant changes in survival. CONCLUSIONS: This population-based study shows that decreases in 6-month and 12-month relative survival rates among patients with MBC in 2001-2010 compared to 1991-2000, specifically, more pronounced among CC men and Oth men.

Eosinophilic Coronary Periarteritis with Arterial Dissection: The Mast Cell Hypothesis.

A subset of coronary arterial dissections is associated with eosinophilic coronary periarteritis (ECPA); however, the pathogenesis of the process remains unclear. Mast cells normally reside in coronary arterial adventitia and are known mediators of eosinophilic inflammatory conditions such as type I hypersensitivity reactions. We report two cases in which coronary arterial dissection with ECPA was detected at autopsy. Tryptase, CD68, CD4, CD8, and CD1a immunohistochemical staining was performed to better characterize inflammation. While eosinophils represented a prominent periadventitial inflammatory cell, there were slightly more lymphocytes: CD4/CD8 ratios were within expected reference ranges. There were moderate numbers of macrophages, and few neutrophils or dendritic cells. Numbers of mast cells in dissected versus nondissected sections were compared: adventitial mast cell densities were threefold higher in dissected portions and showed a trend toward increased degranulation. These findings suggest that mast cells may play a role in orchestrating inflammation in cases of ECPA.