Can site-specific nutrient management improve the productivity and resource use efficiency of climate-resilient finger millet in calcareous soils in India?

Finger millet, an important 'Nutri-Cereal' and climate-resilient crop, is cultivated as a marginal crop in calcareous soils. Calcareous soils have low organic carbon content, high pH levels, and poor structure. Such a situation leads to poor productivity of the crop. Site-specific nutrient management (SSNM), which focuses on supplying optimum nutrients when a crop is needed, can ensure optimum production and improve the nutrient and energy use efficiency of crops. Moreover, developing an appropriate SSNM technique for this crop could offer new insights into nutrient management practices, particularly for calcareous soils. A field experiment was conducted during the rainy seasons of 2020 and 2021 in calcareous soil at Dr. Rajendra Prasad Central Agricultural University, Pusa, India. The experiment consisted of 8 treatments, viz. control, nitrogen (N)/phosphorus (P)/potassium (K)-omission, 75 %, 100 %, and 125 % recommended fertilizer dose (RFD), and 100 % recommended P and K + 30 kg ha-1 N as basal + rest N as per GreenSeeker readings. From this study, it was observed that the GreenSeeker-based SSNM resulted in the maximum grain yield (2873 kg ha-1), net output energy (96.3 GJ ha-1), and agronomic efficiency of N (30.6 kg kg-1), P (68.9 kg kg-1), and K (68.9 kg kg-1). The application of 125 % RFD resulted in ∼7 % lower yield than that under GreenSeeker-based nutrient management. Approximately 12 % greater energy use efficiency and 21-36 % greater nutrient use efficiency were recorded under GreenSeeker-based nutrient management than under 125 % RDF. The indigenous supplies of N, P, and K were found to be 14.31, 3.00, and 18.51 kg ha-1, respectively. Thus, 100 % of the recommended P and K + 30 kg ha-1 N as basal + rest N according to GreenSeeker readings can improve the yield, nutrient use efficiency, and energy balance of finger millet in calcareous soils.

Optimized preparation route for polyamide top-coated forward osmosis membrane for enhanced water flux using industrial wastewater as feed.

The forward osmosis (FO) process has recently gained significant interest in treating wastewater, brackish/seawater and concentrating feedstocks for various operations, including desalination. The study investigates the effect of different synthesis conditions of the polyamide-based thin-film composite (TFC) FO membranes on the membranes' final performance. Taguchi statistical analyses were used to fabricate and optimize the polyamide TFC FO membrane. The process parameters as factors were the amount of polyethersulfone (PES), polyethylene glycol 400 (PEG-400), polyvinyl pyrrolidone (PVP), m-phenylenediamine (MPD), and trimesoyl chloride (TMC), and TMC reaction-time (RT). The Taguchi method was adopted to investigate the optimal conditions and the significance of individual factors using an L16 (45) orthogonal array. Another Taguchi analysis (Taguchi 2) was adopted to investigate the influence of other important parameters like optimal conditions for MPD, TMC, and TMC reaction-time factors using an L9 (33) orthogonal array. Confirmation tests validated a maximum water flux of 46.4 ± 2.32 L/m2·h with a specific combination of control factors for membrane synthesis: PES/PEG/PVP/MPD/TMC/TMC RT-16/7/0.5/1/0.05/30. These tests demonstrated a high-water flux of 7.05 ± 0.35 L/m2·h when exposed to industrial wastewater (secondary effluent) as the feed solution (FS) and fertilizer as the draw solution (DS) in the FO process. The R2 values were more than 90%. The experimental validation confirmed the models' predictive ability with different FSs, including industrial wastewater.

Exploration of culturable bacterial associates of aphids and their interactions with entomopathogens.

Aphids shelter several bacteria that benefit them in various ways. The associates having an obligatory relationship are non-culturable, while a few of facultative associates are culturable in insect cell lines, axenic media or standard microbiology media. In the present investigation, isolation, and characterization of the culturable bacterial associates of various aphid species, viz., Rhopalosiphum maidis, Rhopalosiphum padi, Sitobion avenae, Schizaphis graminum, and Lipaphis erysimi pseudobrassicae were carried out. A total of 42 isolates were isolated using different growth media, followed by their morphological, biochemical, and molecular characterization. The isolated culturable bacterial associates were found to belong to the genera Acinetobacter, Bacillus, Brevundimonas, Cytobacillus, Fictibacillus, Planococcus, Priestia, Pseudomonas, Staphylococcus, Sutcliffiella, and Tumebacillus which were grouped under seven families of four different orders of phyla Bacillota (Firmicutes) and Pseudomonata (Proteobacteria). Symbiont-entomopathogen interaction study was also conducted, in which the quantification of colony forming units of culturable bacterial associates of entomopathogenic fungal-treated aphids led us to the assumption that the bacterial load in aphid body can be altered by the application of entomopathogens. Whereas, the mycelial growth of entomopathogens Akanthomyces lecanii and Metarhizium anisopliae was found uninhibited by the bacterial associates obtained from Sitobion avenae and Rhopalosiphum padi. Analyzing persistent aphid microflora and their interactions with entomopathogens enhances our understanding of aphid resistance. It also fosters the development of innovative solutions for agricultural pest management, highlighting the intricate dynamics of symbiotic relationships in pest management strategies.

Lanthanum Cerate Microspheres for Efficient Fluoride Removal from Wastewater.

The performance of lanthanum cerate microspheres (LCM) at removing fluoride was analyzed in batch experiments after they were synthesized via the hydrothermal strategy. The ball-shaped microsphere morphology of LCM is confirmed by SEM and TEM. The synthesized LCM adsorbent showed excellent adsorption capacity in the pH range 3.0-7.0, with the optimal pH range being 3.5-4.5. The Langmuir adsorption model was more appropriate than the Freundlich model for describing the adsorption isotherm. The LCM adsorbent exhibited a significantly higher Langmuir adsorption capacity of 104.83 mg/g at pH 4.0, surpassing that of any other reported adsorbent. We investigated the adsorption of fluoride under a variety of conditions, including the presence of distinct anions. Furthermore, testing the adsorbent in actual groundwater demonstrated its high effectiveness in removing fluoride. Different useful analytical techniques were used for measurements and to learn and deduce the adsorption mechanism.

Emergency Department Point-of-Care Tests during Cardiopulmonary Resuscitation to Predict Cardiac Arrest Outcomes.

Introduction: This study evaluated the role of point-of-care tests (POCT) such as blood lactate, anion gap (AG), base deficit, pH, N-terminal pro B-type natriuretic peptide (NT-proBNP), and troponin as the predictors of cardiac arrest outcomes in the emergency department (ED). Methods: We conducted a prospective, observational study in the ED of a tertiary care hospital in India. All the adult patients who received cardiopulmonary resuscitation (CPR) in the ED were included in the study. Blood samples were collected within 10 min of initiation of CPR for assay of POCTs. Outcomes assessed were the return of spontaneous circulation (ROSC), 24-h survival, survival to hospital discharge (STHD), survival at 7 days, and favorable neurological outcome (FNO) at day 7 of admission. Results: One hundred and fifty-one patients were included in the study (median age: 50 years, 65% males). Out of 151 cases, ROSC, survival at 7 days, STHD, and FNO was observed in 86 patients, six patients, five patients, and two patients, respectively. "No-ROSC" could be significantly predicted by raised lactate (odds ratio [OR]: 1.14, 95% confidence interval: 1.07-1.22) and NT-proBNP (OR: 1.05, 1.01-1.09) values at the time of cardiac arrest. "24-h mortality" could be significantly predicted by the raised lactate (OR: 1.14, 1.01-1.28), low arterial pH (OR: 0.05, 0.01-0.52), raised AG (OR: 1.08, 1.01-1.15), and lower base deficit (<-15) (OR: 1.07, 1.01-1.14). None of the other POCTs was found to be a predictor of other cardiac arrest outcomes. Conclusion: Among various POCTs, raised lactate assayed within 10 min of cardiac arrest can predict poor outcomes like "no-ROSC" and 24-h mortality.

Esterification of fluorinated aromatic carboxylic acids with methanol by using UiO-66-NH2 as a heterogeneous catalyst and process optimization by the Taguchi method.

Fluorobenzoic acids (FBAs) are used as chemical tracers in enhanced oil recovery and reduction in their limit of detection is a crucial issue. GC-MS is a versatile tool to detect and quantify FBAs at very low limits of concentration, but they require esterification prior to analysis by GC-MS. The present article presents a study of the catalytic methyl esterification of fluorinated aromatic carboxylic acids (FBAs) using methanol as methyl source and UiO-66-NH2 as a heterogeneous catalyst. The reaction time was reduced to 10 hours which is a 58% reduction in time over the traditional BF3·MeOH complex as derivatizing agent. The yield of the esterification reaction was evaluated with respect to the BF3-MeOH complex and determined by GC-EI-MS. The catalytic procedure was optimized by the Taguchi model with a 99.99% fit. Good catalytic performance was observed for 23 different isomers of fluorinated aromatic acids showing a relative conversion yield of up to 169.86%, which reduced the detection limit of FBAs up to 2.60 ng mL-1.

The potentialities of omics resources for millet improvement.

Millets are nutrient-rich (nutri-rich) cereals with climate resilience attributes. However, its full productive potential is not realized due to the lack of a focused yield improvement approach, as evidenced by the available literature. Also, the lack of well-characterized genomic resources significantly limits millet improvement. But the recent availability of genomic data and advancement in omics tools has shown its enormous potential to enhance the efficiency and precision faced by conventional breeding in millet improvement. The development of high throughput genotyping platforms based on next-generation sequencing (NGS) has provided a low-cost method for genomic information, specifically for neglected nutri-rich cereals with the availability of a limited number of reference genome sequences. NGS has created new avenues for millet biotechnological interventions such as mutation-based study, GWAS, GS, and other omics technologies. The simultaneous discovery of high-throughput markers and multiplexed genotyping platform has aggressively aided marker-assisted breeding for millet improvement. Therefore, omics technology offers excellent opportunities to explore and combine useful variations for targeted traits that could impart high nutritional value to high-yielding cultivars under changing climatic conditions. In millet improvement, an in-depth account of NGS, integrating genomics data with different biotechnology tools, is reviewed in this context.

MmLwThV framework: A masked face periocular recognition system using thermo-visible fusion.

In wake of COVID-19, the world has adapted to a new order. People have started wearing mask on their faces to prevent getting infected. The present face recognition models are no longer proving to be efficient in the current circumstances. This is because, most of the informative part of the face is covered by mask. The periocular recognition therefore holds the key to future of face recognition. However, the periocular region proves to be insufficiently enough to generate highly discriminative features. Also, most of the pre-COVID-19 algorithms fail to work in cases, where the number of training images available is very less. We propose a lightweight periocular recognition framework that uses thermo-visible features and ensemble subspace network classifier to improve upon the existing periocular recognition systems named as Masked Mobile Lightweight Thermo-visible Face Recognition (MmLwThV). The framework successfully improves the accuracy over a single visible modality by mitigating the effect of noise present in the thermo-visible features. The experiments on WHU-IIP dataset and an in-house collected dataset named, CVBL masked dataset, successfully validate the efficacy of our proposed framework. The MmLwFR framework is lightweight and can be easily deployed on mobile phones with a visible and an infrared camera.

Prospective Validation of a Novel Triage System Developed in a Middle Income Country - AIIMS Triage Protocol.

Introduction: Triage is a crucial process not only to identify sick patients and prioritize prompt management but also to foster efficient resource utilization. In low-and middle-income countries (LMICs) most emergency departments (ED) still have an informal triage process. Although an important element of emergency care, triage research has not been a priority in LMICs, and hence, very few triage systems have been validated. The All India Institute of Medical Sciences (AIIMS) triage protocol or ATP for adult patients was developed by expert consensus at AIIMS using the Delphi method. We attempted a prospective validation of the ATP in terms of mortality and intensive care unit (ICU)/hospital admission at 24 h. Methods: Patients presenting to the ED, who were 14 years and above were included in the study. The patients were followed up at 24 h and their outcome documented on a standardized data collection form. Mortality and ICU admission were noted at 24 h. Results: A total of 15,505 patients were recruited. After exclusion, among 13,754 patients, 6303 (45.83%) were triaged red and 7451 (54.17%) were triaged yellow. Mortality at 24 h was 10.31% (650) in red triaged patients and 0.35% (26) in yellow triaged patients. The 24-h mortality of red triaged patients was significantly higher (P <0.001) than that of yellow triaged patients. The presence of one or more ATP "Red" criteria was 96.2% (95% confidence interval [CI]: 94.42%-97.47%) sensitive and 56.8% (95% CI: 55.92%-57.63%) specific in predicting 24-h mortality. The sensitivity and specificity of ATP "Red" criteria for 24-h ICU admission were 98.5% (95% CI: 97.7%-99.1%) and 59.6% (95% CI: 58.8%-60.5%), respectively. Conclusion: When applied to adult nontrauma patients, ATP had a high accuracy in recognizing sick patients presenting to the ED. A time-tested and validated triage system like ATP may be a good starting point for public hospital EDs in LMICs.

Application of Sewage Sludge in a Rice (Oryza sativa L.)-Wheat (Triticum aestivum L.) System Influences the Growth, Yield, Quality and Heavy Metals Accumulation of Rice and Wheat in the Northern Gangetic Alluvial Plain.

For a sustainable and profitable agriculture production system, balanced and integrated use of nutrients is a key strategy. In addition, partial replacement of chemical fertilizers with organics ones reduces both environmental concerns and economic costs and provides greater soil health benefits. With this hypothesis, an experiment was conducted to assess the yield and economic benefits of a rice-wheat cropping system (RWCS) as influenced by the joint application of sewage sludge (SSL) and fertilizer. The treatments comprised: without fertilizer or SSL; 100% recommended dose of fertilizers (RDF); 100% RDF + 20 Mg ha-1 SSL; 100% RDF + 30 Mg ha-1 SSL; 50% RDF + 20 Mg ha-1 SSL; 60% RDF + 20 Mg ha-1 SSL; 70% RDF + 20 Mg ha-1 SSL; 50% RDF + 30 Mg ha-1 SSL; 60% RDF + 30 Mg ha-1 SSL and 70% RDF + 30 Mg ha-1 SSL. The experiment was laid out in a randomized block design with three replications. The result of our study indicate that the highest percent increase in mean plant height i.e., ~14.85 and ~13.90, and grain yield i.e., ~8.10 and ~18.90 for rice and wheat, respectively, were recorded under 100% RDF + 30 Mg SSL ha-1 treatment compared to 100% RDF, while 70% RDF + 20 Mg ha-1 SSL produced a statistically equivalent grain yield of 100% RDF in RWCS. The application of 20 and 30 Mg SSL ha-1 along with recommended or reduced fertilizer dose, significantly increased the heavy metal content in plant and soil systems above that of 100% RDF, but this enhancement was found within permissible limits. Moreover, the reduced use of SSL i.e., 20 Mg SSL ha-1, resulted in lower heavy metal content in grain and soil than did the 30 Mg ha-1 SSL treatment, but significantly higher than in the absolute control or 100% RDF treatment. In summary, the use of 20 Mg ha-1 SSL along with 70% RDF provided a safer, profitable and sustainable option in a rice-wheat cropping system in the middle Ganegatic alluvial plain.

Interaction of zinc oxide nanoparticles with soil: Insights into the chemical and biological properties.

Widespread use of zinc oxide nanoparticles (ZnO-NPs) threatens soil, plants, terrestrial and aquatic animals. Thus, it is essential to explore the fate and behavior of NPs in soil and also its mechanism of interaction with soil microbial biodiversity to maintain soil health and quality to accomplish essential ecosystem services. With this background, the model experiment was conducted in the greenhouse to study the impact of ZnO-NPs on soil taking maize as a test crop. The X-ray diffraction, Fourier transform infrared spectroscopy, Scanning electron microscopy and Particles size analysis of engineered NPs confirmed that the material was ZnO-NPs (particle size--65.82 nm). The application of ZnO-NPs resulted in a significant decrease in soil pH. Significantly high EC (0.13 dS m-1) was recorded where ZnO-NPs were applied at the rate of 2.5 mg Zn kg-1 soil over control (0.12 dS m-1). A significant increase in soil available phosphorus was observed on applying ZnO-NPs (15.29 mg kg-1 of soil) as compared to control (11.84 mg kg-1 of soil). Maximum soil available Zn (2.09 mg kg-1) was recorded in ZnO-NPs-amended soil (T11) which was significantly higher than control (0.33 mg kg-1) as well as treatments containing conventional zincatic fertilizers. The inhibition rates of dehydrogenase enzyme activity in the presence of 0.5 mg, 1.25 mg and 2.5 mg ZnO-NPs per kg soil were 31.3, 46.2 and 49.7%, respectively. Soil microbial biomass carbon was significantly reduced (103.33 µg g-1 soil) in soils treated with ZnO-NPs over control (111.33 µg g-1 soil). Soil bacterial count was also significantly lesser (12.33 × 105 CFU) in the case where 2.5 mg kg-1 ZnO-NPs were applied as compared to control (21.33 × 105 CFU). The corresponding decrease in fungal and actinomycetes colony count was 24.16, 37.35, 46.15% and 14.59, 17.97, 22.45% with the application of 0.5 mg, 1.25 mg and 2.5 mg ZnO-NPs per kg soil, respectively, as compared to control. Thus, the use of ZnO-NPs resulted in an increase in soil available Zn but inhibited soil microbial activity.

Evaluation of phytoremediation capability of French marigold (Tagetes patula) and African marigold (Tagetes erecta) under heavy metals contaminated soils.

The pot experiment was conducted to explore the phytoremediation potential of two different marigold species grown in heavy metals contaminated red, black, alluvial, recent river clay, sewage irrigated, sewage sludge, and garden soil. Different soil types were treated uniformly with lead (20 mg Pb kg-1 soil), cadmium (5 mg Cd kg-1 soil), chromium (30 mg Cr kg-1 soil) and nickel (10 mg Ni kg-1 soil). Completely randomized design (CRD) was used with three replications. African marigold (Tagetes erecta) recorded ∼89.4% more dry matter yield over French marigold (Tagetes patula) when grown under metals treated soils. Both the marigold species were highly effective for removing Cd and Ni from contaminated soils (TF >1) however, Ni (TF ∼14.9) was more efficiently accumulated by T. patula and Cd (TF ∼12.1) by T. erecta. Higher biomass yield in T. erecta resulted higher accumulation of heavy metals (except Cr) compared to T. patula. Assessment of contamination factor (CF) and geo-accumulation index (Igeo) of heavy metals indicates that post-harvest soils had moderate to high degree of contamination by different metals, Cr being the highest. It may be concluded that T. erecta was more efficient in extracting heavy metals from different heavy metals contaminated soils.Novelty statement Contamination of land with heavy metals poses severe environmental threats. Physical and chemical remediation techniques are generally used for remediating metals contaminated sites. These methods are cost-intensive and therefore, commercially non-viable, besides being disruptive in nature and causing deterioration of soil. Alternatively, bio-remediation techniques are cost-effective and environment friendly. Among the various phytoremediation techniques, hyperaccumulator plants are most commonly used for the remediation of the contaminated sites. It has been found that different species of the same plant (marigold) differ in their ability to accumulate metals under various contaminated soils having different properties. Thus, this experiment provided an unique opportunity to investigate the effect of various soil properties on metal accumulation efficacy of marigold under metal-spiked soils. Marigold plants can grow rapidly by developing a robust root system which helps them to survive under contaminated soil environment. Thus, marigold being ornamental plant could be used to decontaminate polluted sites while providing ornamental value and may serve as a source of commercially valuable products extracting metals from biomass by way of incineration. However, meager information is available about the usage of various marigold species for phytoremediation of heavy metals under different metal-polluted soils. In the current experiment, we intend to evaluate the potential use of two different marigold species (Tagetes patula and Tagetes erecta) in remediating heavy metals under nine soils of different nature spiked with metals and assessing heavy metals pollution load indexes in these polluted soils.

MiR-592 activates the mTOR kinase, ERK1/ERK2 kinase signaling and imparts neuronal differentiation signature characteristic of Group 4 medulloblastoma.

Medulloblastoma, a common malignant brain tumor in children, consists of four molecular subgroups WNT, SHH, Group 3 and Group 4. Group 3, Group 4 tumors have an overlap in their expression profiles and genetic alterations but differ significantly in their clinical characteristics, with Group 3 having the worst 5-year overall survival of <60%. MiR-592 is overexpressed predominantly in Group 4 tumors. MiR-592 expression reduced the anchorage-independent growth, invasion potential and tumorigenicity of Group 3 medulloblastoma cells. DEPTOR, an endogenous inhibitor of the mTOR kinase, and EML1 were identified as novel targets of miR-592. The miR-592 mediated decrease in the DEPTOR expression levels activated both mTORC1 and mTORC2 complex in medulloblastoma cells. However, the miR-592 expression also decreased the AKT kinase activity, likely to be due to the activation of the inhibitory feedback of the mTOR signaling. MiR-592 expression upregulated several neuronal differentiation-related genes, a characteristic of Group 4 medulloblastoma in Group 3 cell lines. The expression of miR-592 also upregulated the activity of ERK1/ERK2 kinases indicating activation of the MAPK signaling pathway. The inhibition of MAPK signaling by the ERK1/ERK2 inhibitor and mTOR signaling by rapamycin abrogated the miR-592-mediated upregulation of neuronal differentiation-related genes. Group 4 medulloblastomas showed higher activity of the mTOR and MAPK signaling compared to Group 3 tumors. Thus, miR-592 overexpression appears to be a driver event and a determining factor of Group 4 biology, which activates the mTOR and MAPK signaling pathways and thereby imparts its characteristic expression profile of neuronal differentiation-related genes.

Visible light active Zr- and N-doped TiO2 coupled g-C3N4 heterojunction nanosheets as a photocatalyst for the degradation of bromoxynil and Rh B along with the H2 evolution process.

Herein, we drastically increased the l ight-harvesting abilities of TiO2 by creating a defect level with doping using zirconium (Zr) and nitrogen (N). Titanium was substantially replaced by Zr from its lattice point, and N was bound on the surface as (NO)x. The doped system comes with a reduced band edge of 2.8 eV compared to pure TiO2 (3.2 eV), and the doping was accompanied by a higher rate of recombination of photogenerated electron-hole pairs. A heterostructure was fabricated between the modified titania and g-C3N4 to efficiently separate the carriers. An easy and cost-effective sol-gel process followed by a co-calcination technique was used to synthesize the nanostructured composite. The optimum dopant concentration and the extent of doping were investigated via XRD, Raman, XPS, TEM, and PL analyses, followed by a photocatalytic study. The impact of the band positions was investigated via UV-DRS and EIS. The dynamic nature of the band alignment at the depletion region of the heterojunction increased the carrier mobility from the bulk to active sites. The photogenerated electrons and holes retained their characteristic redox abilities to generate both OH˙ and O2 -˙ through a z-scheme mechanism. The photocatalytic activity resulted in superior photocatalytic H2 evolution along with the defragmentation of bromoxynil, a persistent herbicide. The active catalyst exhibited 97% degradation efficiency towards pollutants along with 0.86% apparent quantum efficiency during the H2 evolution reaction.

An end-to-end breast tumour classification model using context-based patch modelling - A BiLSTM approach for image classification.

Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. The large resolution makes WSIs infeasible to be fed directly into the machine learning models due to computational constraints. However, due to patch-based analysis, most of the current methods fail to exploit the underlying spatial relationship among the patches. In our work, we have tried to integrate this relationship along with feature-based correlation among the extracted patches from the particular tumorous region. The tumour regions extracted from WSI have arbitrary dimensions having the range 20,570 to 195 pixels across width and 17,290 to 226 pixels across height. For the given task of classification, we have used BiLSTMs to model both forward and backward contextual relationship. Also, using RNN based model, the limitation of sequence size is eliminated which allows the modelling of variable size images within a deep learning model. We have also incorporated the effect of spatial continuity by exploring different scanning techniques used to sample patches. To establish the efficiency of our approach, we trained and tested our model on two datasets, microscopy images and WSI tumour regions. Both datasets were published by ICIAR BACH Challenge 2018. Finally, we compared our results with top 5 teams who participated in the BACH challenge and achieved the top accuracy of 90% for microscopy image dataset. For WSI tumour region dataset, we compared the classification results with state of the art deep learning networks such as ResNet, DenseNet, and InceptionV3 using maximum voting technique. We achieved the highest performance accuracy of 84%. We found out that BiLSTMs with CNN features have performed much better in modelling patches into an end-to-end Image classification network. Additionally, the variable dimensions of WSI tumour regions were used for classification without the need for resizing. This suggests that our method is independent of tumour image size and can process large dimensional images without losing the resolution details.

Ibrutinib Resistance Mechanisms and Treatment Strategies for B-Cell lymphomas.

Chronic activation of B-cell receptor (BCR) signaling via Bruton tyrosine kinase (BTK) is largely considered to be one of the primary mechanisms driving disease progression in B-Cell lymphomas. Although the BTK-targeting agent ibrutinib has shown promising clinical responses, the presence of primary or acquired resistance is common and often leads to dismal clinical outcomes. Resistance to ibrutinib therapy can be mediated through genetic mutations, up-regulation of alternative survival pathways, or other unknown factors that are not targeted by ibrutinib therapy. Understanding the key determinants, including tumor heterogeneity and rewiring of the molecular networks during disease progression and therapy, will assist exploration of alternative therapeutic strategies. Towards the goal of overcoming ibrutinib resistance, multiple alternative therapeutic agents, including second- and third-generation BTK inhibitors and immunomodulatory drugs, have been discovered and tested in both pre-clinical and clinical settings. Although these agents have shown high response rates alone or in combination with ibrutinib in ibrutinib-treated relapsed/refractory(R/R) lymphoma patients, overall clinical outcomes have not been satisfactory due to drug-associated toxicities and incomplete remission. In this review, we discuss the mechanisms of ibrutinib resistance development in B-cell lymphoma including complexities associated with genomic alterations, non-genetic acquired resistance, cancer stem cells, and the tumor microenvironment. Furthermore, we focus our discussion on more comprehensive views of recent developments in therapeutic strategies to overcome ibrutinib resistance, including novel BTK inhibitors, clinical therapeutic agents, proteolysis-targeting chimeras and immunotherapy regimens.

Spatial variability of arsenic in Indo-Gangetic basin of Varanasi and its cancer risk assessment.

The Indo-Gangetic alluvium is prime region for intensive agricultural. In some areas of this region, groundwater is now becoming progressively polluted by contamination with poisonous substances like arsenic. Intensive irrigation with arsenic contaminated ground water in dry spell results in the formation of As(III) which is more toxic. Thus groundwater quality assessment of Gangetic basin has become essential for its safer use. Therefore we under took study on the spatial variability of arsenic by collecting georeferred groundwater samples on grid basis from various water sources like dug well, bore and hand pumps covering the river bank region of Ganga basin. Water quality was investigated through determination pH, EC, TDS, salinity, Na, K, Ca, Mg, SAR, SSP, CO3, HCO3, RSC, Cl, As, Fe, Zn, Mn and Cu, etc. Results pointed severe As contamination in ground water of three sites of the study area. ARC GIS software is now able to process maps along with tabular data and compare them well, to provide the spatial visualization of information and using this tool, the Geographical Information System (GIS) of arsenic was developed. It was noticed from spatial maps that concentration of arsenic was more near the meandering points of Ganga.

diffGrad: An Optimization Method for Convolutional Neural Networks.

Stochastic gradient descent (SGD) is one of the core techniques behind the success of deep neural networks. The gradient provides information on the direction in which a function has the steepest rate of change. The main problem with basic SGD is to change by equal-sized steps for all parameters, irrespective of the gradient behavior. Hence, an efficient way of deep network optimization is to have adaptive step sizes for each parameter. Recently, several attempts have been made to improve gradient descent methods such as AdaGrad, AdaDelta, RMSProp, and adaptive moment estimation (Adam). These methods rely on the square roots of exponential moving averages of squared past gradients. Thus, these methods do not take advantage of local change in gradients. In this article, a novel optimizer is proposed based on the difference between the present and the immediate past gradient (i.e., diffGrad). In the proposed diffGrad optimization technique, the step size is adjusted for each parameter in such a way that it should have a larger step size for faster gradient changing parameters and a lower step size for lower gradient changing parameters. The convergence analysis is done using the regret bound approach of the online learning framework. In this article, thorough analysis is made over three synthetic complex nonconvex functions. The image categorization experiments are also conducted over the CIFAR10 and CIFAR100 data sets to observe the performance of diffGrad with respect to the state-of-the-art optimizers such as SGDM, AdaGrad, AdaDelta, RMSProp, AMSGrad, and Adam. The residual unit (ResNet)-based convolutional neural network (CNN) architecture is used in the experiments. The experiments show that diffGrad outperforms other optimizers. Also, we show that diffGrad performs uniformly well for training CNN using different activation functions. The source code is made publicly available at https://github.com/shivram1987/diffGrad.

Arrhythmias in Type 2 Diabetes Mellitus.

Chronic hyperglycaemia of Type 2 diabetes mellitus causes long term damage to heart resulting in coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF), and sudden death from arrhythmias. AIMS: To study the prevalence of different types of arrhythmias in T2DM, particularly in association with Cardiac Autonomic Neuropathy (CAN). METHODS: A cross-sectional study including 100 patients of Type 2 Diabetes Mellitus (T2DM) presenting with cardiac arrhythmias, was done at our hospital over 2 years. Detailed history along with physical examination and tests for CAN were done. Routine investigations along with echocardiography, stress test, Holter monitoring were done. RESULTS: Sinus Tachycardia (ST) was the commonest arrhythmia, found in 32% of patients. 20% had Complete Heart Block (CHB), 15% had Sinus Bradycardia (SB), and 15% had Atrial Fibrillation (AF). Ventricular Premature Complex (VPC) was found in 10% and 3% had Atrial Premature Complex (APC). 3% had first degree AV block, whereas 1% had Paroxysmal Supra Ventricular Tachycardia (PSVT), and another 1% had Ventricular Tachycardia (VT). Poorly controlled diabetes and co-morbidities was associated with higher incidence of arrhythmias. 62% of patients had prolonged QTc, majority of which had CAN. Most of the patients responded to standard therapy.