Non-Association of Driver Alterations in PTEN with Differential Gene Expression and Gene Methylation in IDH1 Wildtype Glioblastomas.

During oncogenesis, alterations in driver genes called driver alterations (DAs) modulate the transcriptome, methylome and proteome through oncogenic signaling pathways. These modulatory effects of any DA may be analyzed by examining differentially expressed mRNAs (DEMs), differentially methylated genes (DMGs) and differentially expressed proteins (DEPs) between tumor samples with and without that DA. We aimed to analyze these modulations with 12 common driver genes in Isocitrate Dehydrogenase 1 wildtype glioblastomas (IDH1-W-GBs). Using Cbioportal, groups of tumor samples with and without DAs in these 12 genes were generated from the IDH1-W-GBs available from "The Cancer Genomics Atlas Firehose Legacy Study Group" (TCGA-FL-SG) on Glioblastomas (GBs). For all 12 genes, samples with and without DAs were compared for DEMs, DMGs and DEPs. We found that DAs in PTEN were unassociated with any DEM or DMG in contrast to DAs in all other drivers, which were associated with several DEMs and DMGs. This contrasting PTEN-related property of being unassociated with differential gene expression or methylation in IDH1-W-GBs was unaffected by concurrent DAs in other common drivers or by the types of DAs affecting PTEN. From the lists of DEMs and DMGs associated with some common drivers other than PTEN, enriched gene ontology terms and insights into the co-regulatory effects of these drivers on the transcriptome were obtained. The findings from this study can improve our understanding of the molecular mechanisms underlying gliomagenesis with potential therapeutic benefits.

Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies.

The shock of Coronavirus Disease 2019 (COVID-19) has disrupted food systems worldwide. Such disruption, affecting multiple systems interfaces in smallholder agriculture, is unprecedented and needs to be understood from multi-stakeholder perspectives. The multiple loops of causality in the pathways of impact renders the system outcomes unpredictable. Understanding the nature of such unpredictable pathways is critical to identify present and future systems intervention strategies. Our study aims to explore the multiple pathways of present and future impact created by the pandemic and "Amphan" cyclonic storm on smallholder agricultural systems. Also, we anticipate the behaviour of the systems elements under different realistic scenarios of intervention. We explored the severity and multi-faceted impacts of the pandemic on vulnerable smallholder agricultural production systems through in-depth interactions with key players at the micro-level. It provided contextual information, and revealed critical insights to understand the cascading effect of the pandemic and the cyclone on farm households. We employed thematic analysis of in-depth interviews with multiple stakeholders in Sundarbans areas in eastern India, to identify the present and future systems outcomes caused by the pandemic, and later compounded by "Amphan". The immediate adaptation strategies of the farmers were engaging family labors, exchanging labors with neighbouring farmers, borrowing money from relatives, accessing free food rations, replacing dead livestock, early harvesting, and reclamation of waterbodies. The thematic analysis identified several systems elements, such as harvesting, marketing, labor accessibility, among others, through which the impacts of the pandemic were expressed. Drawing on these outputs, we employed Mental Modeler, a Fuzzy-Logic Cognitive Mapping tool, to develop multi-stakeholder mental models for the smallholder agricultural systems of the region. Analysis of the mental models indicated the centrality of "Kharif" (monsoon) rice production, current farm income, and investment for the next crop cycle to determine the pathways and degree of the dual impact on farm households. Current household expenditure, livestock, and soil fertility were other central elements in the shared mental model. Scenario analysis with multiple stakeholders suggested enhanced market access and current household income, sustained investment in farming, rapid improvement in affected soil, irrigation water and livestock as the most effective strategies to enhance the resilience of farm families during and after the pandemic. This study may help in formulating short and long-term intervention strategies in the post-pandemic communities, and the methodological approach can be used elsewhere to understand perturbed socioecological systems to formulate anticipatory intervention strategies based on collective wisdom of stakeholders.

Meta-analysis of yield and nitrous oxide outcomes for nitrogen management in agriculture.

Improved nitrogen (N) use is key to future food security and environmental sustainability. While many regions still experience N shortages, agriculture is the leading global emitter of N2 O due to losses exacerbated by N surpluses in other regions. In order to sustainably maintain or increase food production, farmers and their advisors need a comprehensive and actionable understanding of how nutrient management affects both yield and N2 O emissions, particularly in tropical and subtropical agroecosystems. We performed a meta-analysis to determine the effect of N management and other factors on N2 O emissions, plant N uptake, and yield. Our analysis demonstrates that performance indicators-partial N balance and partial factor productivity-predicted N2 O emissions as well as or better than N rate. While we observed consistent production and environmental benefits with enhanced-efficiency fertilizers, we noted potential trade-offs between yield and N2 O emissions for fertilizer placement. Furthermore, we observed confounding effects due to management dynamics that co-vary with nutrient application practices, thus challenging the interpretation of the effect of specific practices such as fertilization frequency. Therefore, rather than providing universally prescriptive management for N2 O emission reduction, our evidence supports mitigation strategies based upon tailored nutrient management approaches that keep N balances within safe limits, so as to minimize N2 O emissions while still achieving high crop yields. The limited evidence available suggests that these relationships hold for temperate, tropical, and subtropical regions, but given the potential for expansion of N use in crop production, further N2 O data collection should be prioritized in under-represented regions such as Sub-Saharan Africa.

Crop nutrient management using Nutrient Expert improves yield, increases farmers' income and reduces greenhouse gas emissions.

Reduction of excess nutrient application and balanced fertilizer use are the key mitigation options in agriculture. We evaluated Nutrient Expert (NE) tool-based site-specific nutrient management (SSNM) in rice and wheat crops by establishing 1594 side-by-side comparison trials with farmers' fertilization practices (FFP) across the Indo-Gangetic Plains (IGP) of India. We found that NE-based fertilizer management can lower global warming potential (GWP) by about 2.5% in rice, and between 12 and 20% in wheat over FFP. More than 80% of the participating farmers increased their crop yield and farm income by applying the NE-based fertilizer recommendation. We also observed that increased crop yield and reduced fertilizer consumption and associated greenhouse gas (GHG) emissions by using NE was significantly influenced by the crop type, agro-ecology, soil properties and farmers' current level of fertilization. Adoption of NE-based fertilizer recommendation practice in all rice and wheat acreage in India would translate into 13.92 million tonnes (Mt) more rice and wheat production with 1.44 Mt less N fertilizer use, and a reduction in GHG of 5.34 Mt CO2e per year over farmers' current practice. Our study establishes the utility of NE to help implement SSNM in smallholder production systems for increasing crop yields and farmers' income while reducing GHG emissions.

Differentiating Biliary Atresia From Idiopathic Neonatal Hepatitis: A Novel Keratin 7 Based Mathematical Approach on Liver Biopsies.

BACKGROUND AND AIMS: Differentiating biliary atresia (BA) from idiopathic neonatal hepatitis (INH) is vital in routine pediatric practice. However, on liver biopsy, few cases offer a diagnostic challenge to discriminate these entities with certainty. Bile ductular reaction (DR), intermediate hepatobiliary cells (IHBC) and extra-portal ductules (EPD) indicate progenitor cell activation, as a response to various hepatic insults. The present study aims to quantify DR, IHBC and EPD by Keratin 7 (CK7) immunohistochemistry (IHC) in BA and INH and to devise a mathematical approach to better differentiate the two, especially in histologically equivocal cases. METHODS: A total of 98 cases were categorized on biopsy as BA, INH or equivocal histology, favoring BA or INH. CK7 DR mean, IHBC mean and EPD mean values were compared between BA and INH. A formula was derived to help distinguish these two entities, the cut-off value, sensitivity and specificity of which were determined by receiver operating characteristic (ROC) curve. This formula was applied and validated on histologically equivocal cases. RESULTS: Univariate logistic regression revealed significant difference between BA and INH with respect to CK7 DR and CK7 EPD mean (p < 0.001 in both); however, CK7 IHBC mean was not significant (p = 0.08). On multivariate logistic regression, only CK7 DR had significant impact on diagnosis (p < 0.001). A formula: (CK7 DR)2 + (CK7 EPD)/(CK7 IHBC) was derived to help distinguish BA from INH. Cut off value of 10.5 and above, determined by ROC curve, favored a diagnosis of BA (sensitivity= 93.4%, specificity= 94.6%). Histologically equivocal and discrepant cases could be correctly categorized using this formula. CONCLUSIONS: Formula using CK7 IHC parameters may aid pathologists better distinguish BA from INH, especially in histologically equivocal cases.

Alveolar soft part sarcoma of the retroperitoneum: A case report.

Alveolar soft part sarcoma is a rare soft tissue tumor with uncertain histogenesis. It is a slow growing tumor with a high rate of metastasis. The tumor is not easily identified as clinical symptoms are not pronounced. The retroperitoneum is a rare location of tumor, with a few cases published in literature. Surgical excision is the mainstay of treatment. Here we describe a rare case of a large retroperitoneal Alveolar soft part sarcoma in a young female with radiological and histopathological findings.

Life After Death.

OBJECTIVES: To test the performance characteristics of 69 primary immunohistochemistry antibodies after expiration and compare with fresh primary antibodies wherever possible. METHODS: A total of 69 expired primary antibodies were evaluated for specificity, background staining, and intensity. An optimal staining result corresponded to a semiquantitatively scored 2+ or 3+ intensity, with intact specificity devoid of moderate or strong background staining. Any deviation from a normal staining pattern was also considered to be a suboptimal result. RESULTS: Nearly half of the antibodies studied showed an optimally positive staining result after expiration (34/69, 49.2%). Overall, 10.1% (7/69) of antibodies could be compared with fresh primary antibodies of the same clone with equivalent results. Eight of 69 (11.6%) expired antibodies showed splotchy or granular staining. CONCLUSIONS: Evidence from this study and previous work point to maintained functionality of a fair number of primary immunohistochemical antibodies after expiration. Decisions about the use of such reagents should be guided by a thorough assessment of functionality by the pathologist rather than a manufacturer-specified deadline. Quality maintenance should imply a sensible balance between histopathologic performance and economics.

Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars.

It is critical to understand nutrient dynamics within different plant parts to correctly fine-tune agronomic advices, and to update breeding programs for increasing nutrient use efficiencies and yields. Farmer's field-based research was conducted to assess the effects of nitrogen (N), phosphorus (P), and potassium (K) levels on dry matter and nutrient accumulation, partitioning, and remobilization dynamics in three popular maize (Zea mays L.) hybrids (P3522, P3396, and Rajkumar) over two years in an alluvial soil of West Bengal, India. Experimental results revealed that NPK rates as well as different cultivars significantly (p ≤ 0.05) influenced the dry matter accumulation (DMA) in different plant parts of maize at both silking and physiological maturity. The post-silking dry matter accumulation (PSDMA) and post-silking N, P, and K accumulations (PSNA, PSPA, PSKA) were highest in cultivar P3396. However, cultivar P3522 recorded the highest nutrient remobilizations and contributions to grain nutrient content. Total P and K accumulation were highest with 125% of the recommended dose of fertilizer (RDF) while total N accumulation increased even after 150% RDF (100% RDF is 200 kg N, 60 kg P2O5, and 60 kg K2O ha-1 for the study region). Application of 125% RDF was optimum for PSDMA. The PSNA continued to increase up to 150% RDF while 125% RDF was optimum for PSPA. Cultivar differences significantly affected both remobilization efficiency (RE) and contribution to grain nutrient content for all tested macronutrients (N, P, and K). In general, RE as well as contribution to grain nutrient content was highest at 125% RDF for N and K, and at 100% RDF for P (either significantly or at par with other rates) for plots receiving nutrients. For all tested cultivars, nutrient remobilization and contribution to grain nutrient content was highest under nutrient-omission plots and absolute control plots. Both year and cultivar effects were non-significant for both grain and stover yields of maize. Application of 75% RDF was sufficient to achieve the attainable yield at the study location. The cultivar P3522 showed higher yield over both P3396 and Rajkumar, irrespective of fertilizer doses, although, the differences were not statistically significant (p ≥ 0.05). The study underscores the importance of maize adaptive responses in terms of nutrients accumulation and remobilization at different levels of nutrient availability for stabilizing yield.

HER-2/neu over expression in gall bladder adenocarcinoma: A quest for potential therapeutic target.

BACKGROUND: Gall bladder carcinoma (GBC) is an aggressive malignancy with high mortality and aggressive course, with palliation as the only available option. OBJECTIVES: To evaluate frequency of HER-2/neu overexpression in GBC and to seek its correlation, if any with conventional clinicopathological parameters and survival. METHODS: Immunohistochemistry (IHC) was performed on 200 cases of GBC, 32 cases of dysplasia, and 100 cases of chronic cholecystitis. Fluorescent in situ hybridization (FISH) was performed on 30 randomly selected cases of GBC to validate IHC. HER-2/neu overexpression (IHC 3+/FISH amplification ≥2.2) was correlated with clinicopathological parameters by Chi-square test.P < 0.05 was considered significant. Survival analysis was done by log-rank test and Kaplan-Meier analysis. RESULTS: HER-2/neu overexpression was seen in 14% (28/200) GBC cases but was not found in dysplasia and chronic cholecystitis. Majority of these cases were ≤grade 2 and in advanced stage, however this was not statistically significant. A lower mean survival in HER-2/neu positive group as compared to HER-2/neu negative group (17.1 ± 2.3 month versus 67.6 ± 8.5 month, respectively) was observed. Concordance between IHC and FISH was seen in 18/19 cases. CONCLUSION: This study delineates a subset of GBC patients with HER-2/neu overexpression, in whom targeted therapy can offer a survival benefit.

Maize yield in smallholder agriculture system-An approach integrating socio-economic and crop management factors.

Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.

Enhanced gamma band mutual information is associated with impaired consciousness during temporal lobe seizures.

BACKGROUND: Epileptic seizures are characterized by aberrant synchronization. We hypothesized that higher synchronization across the seizure onset zone (SOZ) channels during a temporal lobe seizure contributes to impaired consciousness. NEW METHOD: All symmetric bivariate synchronization measures were extended to multivariate measure by a principal component analysis (PCA) based technique. A novel nonparametric method has been proposed to test the statistical significance between increased synchronization across the seizure onset zone (SOZ) channels and reduced consciousness. RESULTS: Increased synchronization in the gamma band towards seizure termination significantly contributes to impaired consciousness (p < 0.1). Synchronization reaches its peak in the extratemporal region (frontal lobe) ahead of the temporal region (p < 0.05). Synchronization is prominent in beta and gamma bands by most methods and it is more in the second half of seizure duration than in the first (p < 0.05). CONCLUSIONS: Mutual information is the only synchronization measure out of the six that we studied, whose increase can be associated with the loss of consciousness in a statistically significant way.

Macronutrients influence yield and oil quality of hybrid maize (Zea mays L.).

In the present two-year study, an attempt was made to estimate the grain yield, grain nutrient uptake, and oil quality of three commonly grown maize (Zea mays L.) hybrids fertilized with varied levels of nitrogen (N), phosphorus (P) and potassium (K). Results obtained from both the experimental years indicated that application of 125% of recommended dose of fertilizer (RDF) recorded maximum grain yield (10.37 t ha-1; 124% higher than control). When compared with 100% RDF, grain yield reduction with nutrient omission was 44% for N omission, 17% for P omission, and 27% for K omission. Nitrogen uptake was increased with increasing NPK levels up to 150% RDF that was statistically at par (p ≥ 0.01) with 125% RDF. Increasing trend in P and K uptake was observed with successive increase in NPK levels up to 125% RDF, above which it declined. The protein content was significantly higher in grains of var. P 3396 with 125% RDF. Nutrient management has significant (p ≤ 0.01) role in the grain oil content. Saturated fatty acids (palmitic, stearic and arachidic acid) content decreased, and unsaturated fatty acid (oleic, linoleic and linolenic acid) increased with increasing NPK levels. The average oleic acid desaturation and linoleic acid desaturation ratios were increased with increasing NPK levels up to 100 and 125% RDF, respectively. However, average monounsaturated fatty acids (MUFA): poly-unsaturated fatty acids (PUFA), saturated: unsaturated as well as linoleic: linolenic acid ratios were increased on receiving 75% RDF, and beyond that it showed decreasing trend. The omission of K had the highest inhibitory effect on corn oil quality followed by N and P omission.

Cytology Microarray on Cell Block Preparation: A Novel Diagnostic Approach in Fluid Cytology.

BACKGROUND: The cytological examination of serous body effusions to diagnose and stage malignancy is well accepted in clinical medicine. Conventional smear (CS) and cell block (CB) study has to be complemented with immunohistochemistry (IHC) for a definitive diagnosis of malignancy and also to differentiate it from reactive mesothelial cells. Cytology microarray (CMA) is a modification of tissue microarray which involves core needle biopsy of multiple cell blocks and embedding it in a single block. AIM: The aim of this study was to assess the effectiveness of IHC technique in CMA for rapid diagnosis of malignancy and to reduce the cost of testing. MATERIALS AND METHODS: In this study, 82 pleural fluids were collected and subjected to CS and CB study followed by IHC in CMA blocks. Six commonly used antibodies were applied to confirm malignancy and diagnose the primary. RESULTS: Nineteen cases were diagnosed as malignancy by CB method. MOC-31 confirmed adenocarcinoma deposit in 67% cases of which 44% were proved to be of lung primary by TTF1. CONCLUSIONS: IHC on CMA blocks of effusion fluids is a very effective technique that can significantly reduce the cost of testing by >70%.

Machine learning identifies "rsfMRI epilepsy networks" in temporal lobe epilepsy.

OBJECTIVES: Experimental models have provided compelling evidence for the existence of neural networks in temporal lobe epilepsy (TLE). To identify and validate the possible existence of resting-state "epilepsy networks," we used machine learning methods on resting-state functional magnetic resonance imaging (rsfMRI) data from 42 individuals with TLE. METHODS: Probabilistic independent component analysis (PICA) was applied to rsfMRI data from 132 subjects (42 TLE patients + 90 healthy controls) and 88 independent components (ICs) were obtained following standard procedures. Elastic net-selected features were used as inputs to support vector machine (SVM). The strengths of the top 10 networks were correlated with clinical features to obtain "rsfMRI epilepsy networks." RESULTS: SVM could classify individuals with epilepsy with 97.5% accuracy (sensitivity = 100%, specificity = 94.4%). Ten networks with the highest ranking were found in the frontal, perisylvian, cingulo-insular, posterior-quadrant, thalamic, cerebello-thalamic, and temporo-thalamic regions. The posterior-quadrant, cerebello-thalamic, thalamic, medial-visual, and perisylvian networks revealed significant correlation (r > 0.40) with age at onset of seizures, the frequency of seizures, duration of illness, and a number of anti-epileptic drugs. CONCLUSIONS: IC-derived rsfMRI networks contain epilepsy-related networks and machine learning methods are useful in identifying these networks in vivo. Increased network strength with disease progression in these "rsfMRI epilepsy networks" could reflect epileptogenesis in TLE. KEY POINTS: • ICA of resting-state fMRI carries disease-specific information about epilepsy. • Machine learning can classify these components with 97.5% accuracy. • "Subject-specific epilepsy networks" could quantify "epileptogenesis" in vivo.

Spectrum of parasitic infections in centrifuged urine sediments from a newly developed tertiary care centre in Central India.

Detection of urinary parasites is relatively rare and incidental finding in routine urine examination. Common urinary parasitic infections as described in literature include Trichomonas, Schistosoma hematobium and Microfilaria. Trichomonas vaginalis is known to cause vaginitis and urethritis, and may be found in urine sediments. In this study, the spectrum of urinary parasitic infections that had been reported in the last one and a half year was evaluated, and point prevalence in this zone was estimated. Microbiologist opinion had been taken in the difficult cases. Out of the total centrifuged urine sediments examined, urinary parasitic infection was found in 33 cases. The calculated point prevalence is 0.39%. Most common parasitic infection reported was flagellates (27 cases: 25 T. vaginalis, 2 commensal flagellate closest to Chylomastix), followed by three cases showing eggs of Enterobius vermicularis, one case showing larvae of Strongyloides stercoralis and two cases of ciliate protozoa. One of the ciliate protozoa was Balantidium coli and the other one was Balantidium like ciliate morphologically closest to Chilodonella spp. Pyuria was found in 22 out of the 33 cases and hematuria in 17 out of 33 cases. A fairly wide morphological spectrum of parasites may be diagnosed through microscopic examination of centrifuged urine sediment. They may cause pyuria and haematuria, and morphological awareness helps in prompt and effective management in most cases.

Incidentally detected asymptomatic hepatitis C virus infection with significant fibrosis: Possible impacts on management.

BACKGROUND AND AIMS: Liver biopsy may be considered in patients with hepatitis C virus (HCV) infection to assess the severity of liver injury and stage of fibrosis, thereby guiding therapeutic decisions. In addition, advanced stage also necessitates surveillance for hepatocellular carcinoma. The aim of this study was to assess whether transaminase (alanine transaminase [ALT]) levels and RNA titers correlate with the histological activity index (HAI) and fibrosis (F) stage in asymptomatic patients with incidentally detected HCV (IDHCV). PATIENTS AND METHODS: Retrospective evaluation of liver biopsies was done in 113 patients with IDHCV, diagnosed during routine screening. Decision of liver biopsy was made on the basis of age, genotype, acceptable clinical, hematological, and biochemical profiles, and willingness of the patients to undergo treatment. Serum ALT levels, HCV RNA titers, and genotypes were correlated with HAI and F stage. RESULTS: Genotyping was done in 77 of the 113 patients, of which genotype 3 was seen in 43 and genotype 1 in 25 patients. A higher fibrosis stage (Ishak's >F2) was noted in 23.8% of the biopsies. Serum ALT showed a significant correlation with the HAI score on liver biopsy (P = 0.01) but not with the stage of fibrosis (P = 0.52). HCV RNA titers did not reveal any correlation with HAI score or fibrosis stage. CONCLUSION: Serum transaminases and HCV RNA titers are poor predictors of disease severity and fibrosis. Since HCV shows a slow disease progression, higher stage may predict a worse prognosis irrespective of the low viral RNA load. Liver biopsy may help guide therapeutic decisions in IDHCV infection.

Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients with Temporal Lobe Epilepsy (TLE) in the absence of an interictal discharge (IED). METHOD: 4 Classes of microstates were computed from 2 min artefact free EEG epochs in 42 subjects (21 TLE and 21 controls). The percentage of time coverage, frequency of occurrence and duration for each of these microstates were computed and redundancy reduced using feature selection methods. Subsequently, Fishers Linear Discriminant Analysis (FLDA) and logistic regression were used for classification. RESULT: FLDA distinguished TLE with 76.1% accuracy (85.0% sensitivity, 66.6% specificity) considering frequency of occurrence and percentage of time coverage of microstate C as features. CONCLUSION: Microstate alterations are present in patients with TLE. This feature might be useful in the diagnosis of epilepsy even in the absence of an IED.