A Tri-Stage Wrapper-Filter Feature Selection Framework for Disease Classification

In machine learning and data science, feature selection is considered as a crucial step of data preprocessing. When we directly apply the raw data for classification or clustering purposes, sometimes we observe that the learning algorithms do not perform well. One possible reason for this is the presence of redundant, noisy, and non-informative features or attributes in the datasets. Hence, feature selection methods are used to identify the subset of relevant features that can maximize the model performance. Moreover, due to reduction in feature dimension, both training time and storage required by the model can be reduced as well. In this paper, we present a tri-stage wrapper-filter-based feature selection framework for the purpose of medical report-based disease detection. In the first stage, an ensemble was formed by four filter methods-Mutual Information, ReliefF, Chi Square, and Xvariance-and then each feature from the union set was assessed by three classification algorithms-support vector machine, naïve Bayes, and k-nearest neighbors-and an average accuracy was calculated. The features with higher accuracy were selected to obtain a preliminary subset of optimal features. In the second stage, Pearson correlation was used to discard highly correlated features. In these two stages, XGBoost classification algorithm was applied to obtain the most contributing features that, in turn, provide the best optimal subset. Then, in the final stage, we fed the obtained feature subset to a meta-heuristic algorithm, called whale optimization algorithm, in order to further reduce the feature set and to achieve higher accuracy. We evaluated the proposed feature selection framework on four publicly available disease datasets taken from the UCI machine learning repository, namely, arrhythmia, leukemia, DLBCL, and prostate cancer. Our obtained results confirm that the proposed method can perform better than many state-of-the-art methods and can detect important features as well. Less features ensure less medical tests for correct diagnosis, thus saving both time and cost.

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans

COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives of several people. Although potential vaccines are being tested and supplied around the world, it will take a long time to reach every human being, more so with new variants of the virus emerging, enforcing a lockdown-like situation on parts of the world. Thus, there is a dire need for early and accurate detection of COVID-19 to prevent the spread of the disease, even more. The current gold-standard RT-PCR test is only 71% sensitive and is a laborious test to perform, leading to the incapability of conducting the population-wide screening. To this end, in this paper, we propose an automated COVID-19 detection system that uses CT-scan images of the lungs for classifying the same into COVID and Non-COVID cases. The proposed method applies an ensemble strategy that generates fuzzy ranks of the base classification models using the Gompertz function and fuses the decision scores of the base models adaptively to make the final predictions on the test cases. Three transfer learning-based convolutional neural network models are used, namely VGG-11, Wide ResNet-50-2, and Inception v3, to generate the decision scores to be fused by the proposed ensemble model. The framework has been evaluated on two publicly available chest CT scan datasets achieving state-of-the-art performance, justifying the reliability of the model. The relevant source codes related to the present work is available in: GitHub.

Integrative metabolomics and transcriptomics identifies itaconate as an adjunct therapy to treat ocular bacterial infection

The eye is highly susceptible to inflammation-mediated tissue damage evoked during bacterial infection. However, mechanisms regulating inflammation to protect the eye remain elusive. Here, we used integrated metabolomics and transcriptomics to show that the immunomodulatory metabolite itaconate and immune-responsive gene 1 (Irg1) are induced in bacterial (Staphylococcus aureus)-infected mouse eyes, bone-marrow-derived macrophages (BMDMs), and Müller glia. Itaconate levels are also elevated in the vitreous of patients with bacterial endophthalmitis. Irg1 deficiency in mice led to increased ocular pathology. Conversely, intraocular administration of itaconate protects both Irg1-/- and wild-type mice from bacterial endophthalmitis by reducing inflammation, bacterial burden, and preserving retinal architecture and visual function. Notably, itaconate exerts synergistic effects with antibiotics. The protective, anti-inflammatory effects of itaconate are mediated via activation of NRF2/HO-1 signaling and inhibition of NLRP3 inflammasome. Collectively, our study demonstrates the Irg1/itaconate axis is a regulator of intraocular inflammation and provides evidence for using itaconate, along with antibiotics, to treat bacterial infections.

Aging, But Not Sex and Genetic Diversity, Impacts the Pathobiology of Bacterial Endophthalmitis

Purpose

Age, sex, and genetics are important biological variables in determining an individual's susceptibility or response to infectious agents; however, their role has not been evaluated in intraocular infections. In this study, we comprehensively examined the impact of these host biological factors in the pathogenesis of experimental bacterial endophthalmitis.

Methods

Endophthalmitis was induced by intravitreal injection of bacteria (Staphylococcusaureus) in the eyes of male and female C57BL/6 mice of different ages: group I (young, 6–8 weeks), group II (mid-age, 18–20 weeks), and group III (old, 1 year). Highly heterogeneous outbred J:DO mice were used for genetic diversity analysis. Eyes were subjected to clinical examination, retinal function testing using electroretinography (ERG), histopathological analysis (hematoxylin and eosin staining), and bacterial burden estimation. The levels of inflammatory mediators were measured using qPCR and ELISA, and the infiltration of neutrophils was determined by flow cytometry.

Results

Both inbred C57BL/6 and diversity outbred (J:DO) mice were equally susceptible to S. aureus endophthalmitis, as evidenced by a time-dependent increase in clinical scores, bacterial burden, intraocular inflammation, and retinal tissue damage, in addition to decreased retinal function. However, no significant differences were observed in disease severity and innate responses in male versus female mice. Older mice (group III) exhibited higher clinical scores coinciding with increased bacterial proliferation and intraocular inflammation, resulting in enhanced disease severity. Moreover, bone-marrow-derived macrophages from old mice exhibited reduced phagocytic activity but increased inflammatory response toward S. aureus challenge.

Conclusions

Age, but not sex, is an important biological variable in bacterial endophthalmitis. Identification of pathways underlying altered innate immunity and impaired bacterial clearance in aging eyes could provide new insights into the pathobiology of intraocular infections in elderly patients.

GraphCovidNet: A graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest

COVID-19, a viral infection originated from Wuhan, China has spread across the world and it has currently affected over 115 million people. Although vaccination process has already started, reaching sufficient availability will take time. Considering the impact of this widespread disease, many research attempts have been made by the computer scientists to screen the COVID-19 from Chest X-Rays (CXRs) or Computed Tomography (CT) scans. To this end, we have proposed GraphCovidNet, a Graph Isomorphic Network (GIN) based model which is used to detect COVID-19 from CT-scans and CXRs of the affected patients. Our proposed model only accepts input data in the form of graph as we follow a GIN based architecture. Initially, pre-processing is performed to convert an image data into an undirected graph to consider only the edges instead of the whole image. Our proposed GraphCovidNet model is evaluated on four standard datasets: SARS-COV-2 Ct-Scan dataset, COVID-CT dataset, combination of covid-chestxray-dataset, Chest X-Ray Images (Pneumonia) dataset and CMSC-678-ML-Project dataset. The model shows an impressive accuracy of 99% for all the datasets and its prediction capability becomes 100% accurate for the binary classification problem of detecting COVID-19 scans. Source code of this work can be found at GitHub-link .

Epidemiological and Clinical factors associated with mortality of confirmed Covid-19 cases admitted and treated in a tertiary care hospital of Patna, Bihar

Background: A significant proportion of the individuals having the illness of moderate to severe nature due to COVID-19 infection require immediate critical care. High incidence of mortality among elderly population or those with comorbid conditions were reported. Objectives: The study was carried out with objectives to assess the epidemiological and clinical factors associated with mortality among the COVID-19 cases admitted and treated in AIIMS, Patna. Methods: This was a hospital‑based cross‑sectional analytical study of epidemiological and clinical features of COVID‑19‑positive patients admitted and treated during the outbreak from March 20, to August 31, 2020. Results: The median age of COVID-19 cases was 51.5 years (IQR : 37-62 years) which was significantly higher (p-value = 0.001) as compared to females. Male-female ratio of cases was 2.88:1. Out of 1696 cases, the case-fatality rate was 309 (18.22%). The mean age of cases who died due to COVID-19 was significantly higher (p-value=0.001) as compared to those who survived. The odds of mortality was significantly higher in males as compared to females (Adjusted OR = 1.534, 95% CI = 1.10 – 2.13, p=0.011). The odds of mortality showed a significant increasing trend with increasing age (Mantel-Hanszel p-value for trend = 0.015). The covariates like gender, age groups 45-59, 60-74 and 75>=, breathlessness and CKD were found to be significantly associated with mortality after controlling for the confounders. Conclusions: Factors like gender, higher age, lower oxygen saturation causing breathlessness and chronic kidney diseases could be attributed to high risk of mortality in COVID-19 patients.

Tocilizumab plus standard care versus standard care in patients in India with moderate to severe COVID-19-associated cytokine release syndrome (COVINTOC): an open-label, multicentre, randomised, controlled, phase 3 trial

BACKGROUND

Global randomised controlled trials of the anti-IL-6 receptor antibody tocilizumab in patients admitted to hospital with COVID-19 have shown conflicting results but potential decreases in time to discharge and burden on intensive care. Tocilizumab reduced progression to mechanical ventilation and death in a trial population enriched for racial and ethnic minorities. We aimed to investigate whether tocilizumab treatment could prevent COVID-19 progression in the first multicentre randomised controlled trial of tocilizumab done entirely in a lower-middle-income country.

METHODS

COVINTOC is an open-label, multicentre, randomised, controlled, phase 3 trial done at 12 public and private hospitals across India. Adults (aged ≥18 years) admitted to hospital with moderate to severe COVID-19 (Indian Ministry of Health grading) confirmed by positive SARS-CoV-2 PCR result were randomly assigned (1:1 block randomisation) to receive tocilizumab 6 mg/kg plus standard care (the tocilizumab group) or standard care alone (the standard care group). The primary endpoint was progression of COVID-19 (from moderate to severe or from severe to death) up to day 14 in the modified intention-to-treat population of all participants who had at least one post-baseline assessment for the primary endpoint. Safety was assessed in all randomly assigned patients. The trial is completed and registered with the Clinical Trials Registry India (CTRI/2020/05/025369).

FINDINGS

180 patients were recruited between May 30, 2020, and Aug 31, 2020, and randomly assigned to the tocilizumab group (n=90) or the standard care group (n=90). One patient randomly assigned to the standard care group inadvertently received tocilizumab at baseline and was included in the tocilizumab group for all analyses. One patient randomly assigned to the standard care group withdrew consent after the baseline visit and did not receive any study medication and was not included in the modified intention-to-treat population but was still included in safety analyses. 75 (82%) of 91 in the tocilizumab group and 68 (76%) of 89 in the standard care group completed 28 days of follow-up. Progression of COVID-19 up to day 14 occurred in eight (9%) of 91 patients in the tocilizumab group and 11 (13%) of 88 in the standard care group (difference -3·71 [95% CI -18·23 to 11·19]; p=0·42). 33 (36%) of 91 patients in the tocilizumab group and 22 (25%) of 89 patients in the standard care group had adverse events; 18 (20%) and 15 (17%) had serious adverse events. The most common adverse event was acute respiratory distress syndrome, reported in seven (8%) patients in each group. Grade 3 adverse events were reported in two (2%) patients in the tocilizumab group and five (6%) patients in the standard care group. There were no grade 4 adverse events. Serious adverse events were reported in 18 (20%) patients in the tocilizumab group and 15 (17%) in the standard care group; 13 (14%) and 15 (17%) patients died during the study.

INTERPRETATION

Routine use of tocilizumab in patients admitted to hospital with moderate to severe COVID-19 is not supported. However, post-hoc evidence from this study suggests tocilizumab might still be effective in patients with severe COVID-19 and so should be investigated further in future studies.

FUNDING

Medanta Institute of Education and Research, Roche India, Cipla India, and Action COVID-19 India.

COVID-19 Detection by Optimizing Deep Residual Features with Improved Clustering-Based Golden Ratio Optimizer

The COVID-19 virus is spreading across the world very rapidly. The World Health Organization (WHO) declared it a global pandemic on 11 March 2020. Early detection of this virus is necessary because of the unavailability of any specific drug. The researchers have developed different techniques for COVID-19 detection, but only a few of them have achieved satisfactory results. There are three ways for COVID-19 detection to date, those are real-time reverse transcription-polymerize chain reaction (RT-PCR), Computed Tomography (CT), and X-ray plays. In this work, we have proposed a less expensive computational model for automatic COVID-19 detection from Chest X-ray and CT-scan images. Our paper has a two-fold contribution. Initially, we have extracted deep features from the image dataset and then introduced a completely novel meta-heuristic feature selection approach, named Clustering-based Golden Ratio Optimizer (CGRO). The model has been implemented on three publicly available datasets, namely the COVID CT-dataset, SARS-Cov-2 dataset, and Chest X-Ray dataset, and attained state-of-the-art accuracies of 99.31%, 98.65%, and 99.44%, respectively.

New QTLs for Spot Blotch Disease Resistance in Wheat (Triticum aestivum L.) Using Genome-Wide Association Mapping

Spot blotch disease caused by Bipolaris sorokiniana is a major constraint for wheat production in tropics and subtropics. The introgression of spot blotch resistance alleles to the disease susceptible lines is critical to securing the wheat production in these regions. Although genome-wide association studies (GWASs) for spot blotch were attempted earlier, the present study focused on identifying new quantitative trait loci (QTLs) for spot blotch under natural disease pressure in diverse field conditions. A total of 139 advanced spring wheat lines were evaluated in three environments (three years and two locations) in India and Bangladesh. The GWAS using 14,063 polymorphic genotyping-by-sequencing (GBS) markers identified eight QTLs associated with spot blotch disease resistance belonging to eight chromosomes across the wheat genome. Here, we report the identified marker–trait associations (MTAs), along with the allele effects associated with the disease. The functional annotation of the significant markers identified NBS-LRR, MADS-box transcription factor, and 34 other plant-related protein families across multiple chromosomal regions. The results indicate four promising new QTLs on chromosomes 1A (497.2 Mb), 1D (89.84 Mb), 2B (421.92 Mb), and 6D (6.84 Mb) associated with several disease resistance protein families. These results provide insights into new genomic regions associated with spot blotch disease, and with additional validation, could be utilized in disease resistance breeding efforts in wheat development.

Changes in fecal microbiota with CFTR modulator therapy: A pilot study

Studies have demonstrated that people with CF with pancreatic insufficiency (PI) have fecal dysbioses. Evidence suggests the causes of these dysbioses are multifactorial, and that important drivers include antibiotic exposure, dietary intake, and CF gastrointestinal tract dysfunction, including nutrient malabsorption. In this pilot study, we tested whether initiation of the CFTR modulator treatments ivacaftor (in a cohort of pancreatic sufficient (PS) people with CF and an R117H CFTR variant) or lumacaftor/ivacaftor (in a cohort of PI people with CF and an F508del variant) changed fecal measures of malabsorption or fecal microbiomes. While we identified no statistically significant fecal changes with either treatment, we detected trends in the PI cohort when initiating lumacaftor/ivacaftor towards decreased fecal fat content and towards fecal microbiomes that more closely resembled the fecal microbiota of people without PI. While these findings support a model in which nutrient malabsorption resulting from CF-induced PI drives fecal dysbiosis, they must be validated in future, larger studies of fecal microbiome and malabsorption outcomes with highly effective CFTR modulator therapies.

Predictability of Sex from Frontal Sinus in Nepalese Population

Background Various methods had been used for personal identification. Scientific basis of identification was initiated and progressed after 19th century which may be attributed to various scientists. With the invention of X-ray the field of identification further progressed. Modern radiological diagnostic equipments have greatly assisted in the field of forensic. Frontal sinuses are paired lobulated air cavities located posterior to superciliary arches in the frontal bone. Computed Tomography is best used to study frontal sinuses. Objective To evaluate bilateral Frontal sinus for sexual dimorphism using Computed Tomography. Method Anterior posterior length, transverse width and height of the bilateral Frontal sinus were directly measured on CT DICOM image, using Electronic Caliper in DICOM viewer software. A total 100 CT scans, 50 of each sex were collected was analysed using SPSS-20 in present study. Result The mean age distribution for male is 34.74±8.66, and for females 35.34±8.88. The mean of all the measurements take was larger in males in comparison to females with p < 0.00. The paired t test showed left side is larger than right. The discriminant function showed high significance for each measurement and also when all the measurements were combined. Conclusion Though the study being unique for Nepalese population, caution should be taken when frontal sinus is used as the only parameter. However in combination with other morphometric data is advised.

Synergistic absorbents based on SnFe2O4@ZnO nanoparticles decorated with reduced graphene oxide for highly efficient dye adsorption at room temperature

Recently, adsorption techniques have emerged as practical and effective methods for removing organic dyes, dramatically extending practical capabilities for treating deleterious pollutants in wastewater. However, an urgent issue restricting the performance of these techniques is that no available absorbents that can be used to treat both cationic and anionic organic dyes have been made with simple and reliable methods until now. Herein, we report a green synthetic strategy for the preparation of SnFe₂O₄/ZnO nanoparticles decorated on reduced graphene oxide (rGO), exhibiting a remarkably large surface area (120.33 m² g⁻¹). Substantial adsorption efficiency for removing MB dye was achieved, with 91.3% removal within 20 min at room temperature, and efficiencies of 79.6 to 92.8% are maintained as the pH conditions are varied from 3 to 11. Moreover, under mixed-dye conditions, involving MB, RhB, MO, RB5, and R6G organic materials, with dye concentrations ranging from 0.005 mM to 0.09 mM, an adsorption efficiency of above 50% can be reliably reached within 20 min. Such striking features can be interpreted as arising from a synergistic effect involving the hybrid composite based on a rGO matrix with negative charge and the dispersed SnFe₂O₄/ZnO nanoparticles with positive charge, additionally offering abundant adsorptive sites to allow reliable dye-adsorption kinetics.

Magnetically separable SnFe₂O₄/ZnO nanoparticles decorated on rGO sheets with remarkable dye adsorption capabilities are demonstrated.

Terbinafine resistance in dermatophytes: Time to revisit alternate antifungal therapy

Resistant superficial dermatophytic infections of the skin and its appendages have emerged as a major health problem in India. Mutations in Squalene epoxidase gene have led to increasing incidence of resistance to terbinafine in dermatophytic isolates. We examined six patients with recalcitrant dermatophytosis attending Dermatology OPD at a tertiary care hospital and demonstrated terbinafine resistance by molecular method. Immediate hyperitivity (IH) reaction to Trichophytin antigen was highlighted in these patients. The patients were treated with alternate antifungals after demonstration of resistance to terbinafine based on the antifungal susceptibility testing (AFST). On follow up the patients responded well to the substitute but the duration of therapy had to be prolonged beyond six weeks.

Toll-like receptor 2 (TLR2) engages endoplasmic reticulum stress sensor IRE1α to regulate retinal innate responses in Staphylococcus aureus endophthalmitis

Endoplasmic reticulum (ER) stress response has been implicated in a variety of pathophysiological conditions, including infectious and inflammatory diseases. However, its contribution in ocular bacterial infections, such as endophthalmitis, which often cause blindness is not known. Here, using a mouse model of Staphylococcus (S.) aureus endophthalmitis, our study demonstrates the induction of inositol-requiring enzyme 1α (IRE1α) and splicing of X-box binding protein-1 (Xbp1) branch of the ER-stress pathway, but not the other classical ER stress sensors. Interestingly, S aureus-induced ER stress response was found to be dependent on Toll-like receptor 2 (TLR2), as evident by reduced expression of IRE1α and Xbp1 mRNA splicing in TLR2 knockout mouse retina. Pharmacological inhibition of IRE1α using 4µ8C or experiments utilizing IRE1α-/- macrophages revealed that IRE1α positively regulates S aureus-induced inflammatory responses. Moreover, IRE1α inhibition attenuated S aureus-triggered NF-κB, p38, and ERK pathways activation and cells treated with these pathway-specific inhibitors reduced Xbp1 splicing, suggesting a positive feedback inhibition. In vivo, inhibition of IRE1α diminished the intraocular inflammation and reduced PMN infiltration in mouse eyes, but, increased the bacterial burden and caused more retinal tissue damage. These results revealed a critical role of the IRE1α/XBP1 pathway as a regulator of TLR2-mediated protective innate immune responses in S aureus-induced endophthalmitis.

Bunching of light ions driven by heavy-ion front in multispecies ion beam accelerated by laser

Deeply modulated ion spectra from contaminants present on the target surface were measured at the interaction of ultraintense (2-5)×10^{20}W/cm^{2} and high-contrast laser pulses (≲10^{-10}) with thin (∼μm) and ultrathin (∼nm) targets. This phenomenon, observed over a wide range of laser and target parameters, suggests that it is a generic feature of multispecies ion acceleration at high laser pulse contrast. The modulation is ascribed to the acceleration of various ion species at the rear of the target with steplike density profiles which provide well-separated ion species in the accelerated beam. The observed coincidence of the velocity of the modulated region in the ion spectra with the maximum velocity of another ion with a lower mass-to-charge ratio is consistent with this model. The impact of heavy ions on light ions leads to a spectral "bunching" of light ions. Two-dimensional modeling has shown that high laser contrast prevents backside plasma expansion, which provides a well separated ion species with a steplike density profile that allows for the additional acceleration of "light" ions by the slower moving "heavy"-ion front. Spectral modulations can be controlled by tuning the ratio of heavy to light ions in future experiments with ultrathin rear coatings.

Correction to: Immunotherapy Alone or in Combination with Chemotherapy as First-Line Treatment of Non-Small Cell Lung Cancer

The original version of this article unfortunately contained mistakes. In Table 2, under the column 'Lead to death' in Row 5 [CheckMate-026], the figures should read as '0.7' for Experimental Arm and '1.1' for Comparator. Right now, these are printed as 0.007 and 0.011 respectively.

Evaluation of Susceptibility and Innate Immune Response in C57BL/6 and BALB/c Mice During Candida albicans Endophthalmitis

Purpose

Candida remains the leading cause of fungal endophthalmitis. However, the pathobiology and innate immune responses in this disease are not well characterized. Here, we developed two murine models of candida endophthalmitis and evaluated their disease susceptibility and differential immune response.

Methods

Endophthalmitis was induced in C57BL/6 (B6) and BALB/c mice by intravitreal injection of Candida albicans (CA). Disease progression was monitored by slit-lamp examination and clinical scoring, followed by retinal function assessment using electroretinography (ERG). Enucleated eyes were used to estimate fungal burden and retinal tissue damage by hematoxylin and eosin and TUNEL staining. The level of inflammatory mediators were determined by quantitative Polymerase Chain Reaction (qPCR) and enzyme-linked immunosorbent assay, whereas neutrophil infiltration was assessed by flow cytometry and immunostaining.

Results

Intravitreal injection of CA at 6500 colony-forming units resulted in sustained (non-resolving) ocular inflammation in both B6 and BALB/c mice as evidenced by increased levels of inflammatory cytokines (tumor necrosis factor-α, interleukin-1β, and interleukin-6) and chemokine (CXCL2/MIP-2). In both mouse strains, fungal burden peaked at 24 to 48 hours post-infection (hpi) and decreased by 72 to 96 hpi. CA-infected eyes exhibited increased polymorphonuclear neutrophils (PMN) infiltration and retinal tissue damage. Overall retinal function declined rapidly, with a significant reduction in ERG response at 12 hpi and near-total loss by 24 hpi. Differential analyses revealed increased pathology in BALB/c versus B6 mice.

Conclusions

C. albicans was able to cause endophthalmitis in mice. Although BALB/c mice were found to be more susceptible to CA endophthalmitis, both BALB/c and B6 models could be used to study fungal endophthalmitis and test therapeutic modalities.

Development of an Evaluation System for Fusarium Resistance in Wheat Grains and Its Application in Assessment of the Corresponding Effects of Fhb1

Fusarium head blight (FHB) caused by Fusarium species is a globally important wheat disease. Host resistance to FHB is composed of multiple mechanisms, including resistance to initial infection (type I), disease spread (type II), toxin accumulation (type III), kernel infection (type IV), and yield loss (type V), of which the last three have been less studied. Traditionally, the Fusarium-damaged kernel rate (FDK; percentage of Fusarium-infected grains) from point- or spray-inoculated experiments was used as the parameter for type IV resistance, which may be problematic because of the influence of type II resistance. Here we propose a new definition for type IV resistance: that is, the resistance against Fusarium infection expressed in wheat grains that have the same chance in contact with the pathogen, under favorable temperature and humidity for infection. Fhb1 confers strong type II resistance, leading to significantly reduced FHB severity and FDK. To investigate the role of Fhb1 in type IV resistance, a pair of near-isogenic lines, R22W (Fhb1 carrier, resistant in terms of type II resistance) and S22V (non-Fhb1, susceptible), along with eight wheat genotypes differing at Fhb1 were inoculated at different grain development stages with Fusarium macrospores both in vivo and in vitro. The in vivo experiments with all florets inoculated demonstrated a significant reduction in thousand kernel weight (TKW) in inoculated grains, regardless of their Fhb1 status and developmental stages. Surprisingly, R22W showed more TKW reduction than S22V, which was supported by the scanning electron microscopy observation that confirmed the more severe degradation of starch granules in R22W grains. The in vitro experiments demonstrated that grains from both R22W and S22V promoted fungal colonization, but no significant difference was found between the two lines. In summary, our results indicated that the proposed type IV evaluation system is effective in determining different grain resistance levels, providing novel tools for FHB resistance breeding. The finding that Fhb1 is not associated with type IV resistance enriches our understanding of this gene.

Immunotherapy Alone or in Combination with Chemotherapy as First-Line Treatment of Non-Small Cell Lung Cancer

OPINION STATEMENT

Immune checkpoint inhibitors (ICIs) have revolutionized the management of metastatic and selected cases of unresectable advanced non-small cell lung cancer (NSCLC). Importantly for patients, this implies that in the absence of a targetable oncogenic driver [especially epidermal growth factor receptor (EGFR) gene mutations and anaplastic lymphoma kinase (ALK) gene rearrangements] and in the presence of high programmed death-ligand 1 (PD-L1) expression (≥ 50%), they are eligible for mono-therapy with pembrolizumab thereby avoiding chemotherapy as the first line of treatment. This mono-immunotherapy approach for high PD-L1 metastatic NSCLC is associated with improved overall survival (OS) and radiological responses (RR) with lesser toxicity as compared with conventional platinum doublet chemotherapy for both non-squamous and squamous histological types.However, majority of NSCLC patients either have no or low expression of PD-L1 (< 50%) and such patients derive greater benefit from a combination of PD-1/PD-L1 ICIs with platinum doublet chemotherapy as compared with chemotherapy alone. Again, benefits are seen for both OS and RRs. However, combining immunotherapy with chemotherapy, in general, does lead to higher toxicity than those seen with either of the two alone.Additionally, for non-squamous NSCLC patients, clinicians should not initiate ICI treatment till the results of common targetable genetic alterations like EGFR mutation, ALK, and ROS1 gene rearrangement testing are known (preferably on broad next generation sequencing) and are negative (even if results of PD-L1 testing are available)-as targeted therapies remain the cornerstone of treatment for patients harboring these oncogenic drivers.It is worth mentioning that PD-1 and PD-L1 ICIs are very expensive, and their usage is associated with occurrence of immune-related adverse events (irAEs) which occasionally can be severe. Hence, it is important to discuss efficacy, toxicity, and cost-related to ICI treatment with each and every patient at diagnosis in order to help them decide if they are willing to go ahead with this form of therapy either singly (for high PD-L1 expressors) or in combination with chemotherapy (for others).

Identification of a new potential native Indian cattle breed by population differentiation based on microsatellite markers

India has a rich heritage of rearing cattle where farmers selected native cattle suitable to their local agro-ecological conditions for centuries. It is reflected in 50 indigenous breeds of cattle, besides many lesser known populations not explored so far. It is the need of the hour to characterize such populations to have prudent improvement and conservation options. Thus, present study was carried out to assess the genetic diversity and relationship between an unexplored local cattle population (Kathani) and four established cattle breeds of adjoining area (Gaolao, Kosali, Ongole and Motu) by using 20 FAO recommended microsatellite markers. High variability was recorded in the Kathani population with a total of 198 alleles that varied between 5 (ILSTS11, TGLA22, INRA05) and 17 (ILSTS34) with a mean of 9.9 ± 0.73. The average observed heterozygosity (Ho) was 0.658 ± 0.054. Heterozygote deficiency was not significant (F_IS = 0.029 ± 0.063) indicating random mating prevalent across this population. Mean estimates of observed number of alleles and heterozygosity over all the loci and five populations were 9.73 ± 0.421 and 0.617 ± 0.022, respectively. In the overall populations, the homozygote excess (F_IT) of 0.293 ± 0.032, was partly due to the homozygote excess within breeds (F_IS = 0.121 ± 0.025) and to a larger extent due to high (0.05 < F_ST < 0.15) genetic differentiation among them (F_ST = 0.195 ± 0.029). Substantial pairwise Nei's genetic distance and high population differentiation indicated towards separate genetic identity of Kathani cattle. The analysis of genetic structure based on Bayesian approach indicated that the most probable number of clusters is five confirming definitive genetic differentiation among all the popultions. Entire analysis showed that a significant amount of genetic variation is maintained in Kathani, a lesser known cattle population that is distinct from the recognized breeds in the proximity. As this autochthonous cattle plays role in the economic sustainability of a marginal and disadvantaged area, it is important to preserve and develop its breeding.

Allelic sequence variation in the Sub1A, Sub1B and Sub1C genes among diverse rice cultivars and its association with submergence tolerance

Erratic rainfall leading to flash flooding causes huge yield losses in lowland rice. The traditional varieties and landraces of rice possess variable levels of tolerance to submergence stress, but gene discovery and utilization of these resources has been limited to the Sub1A-1 allele from variety FR13A. Therefore, we analysed the allelic sequence variation in three Sub1 genes in a panel of 179 rice genotypes and its association with submergence tolerance. Population structure and diversity analysis based on a 36-plex genome wide genic-SNP assay grouped these genotypes into two major categories representing Indica and Japonica cultivar groups with further sub-groupings into Indica, Aus, Deepwater and Aromatic-Japonica cultivars. Targetted re-sequencing of the Sub1A, Sub1B and Sub1C genes identfied 7, 7 and 38 SNPs making 8, 9 and 67 SNP haplotypes, respectively. Haplotype networks and phylogenic analysis revealed evolution of Sub1B and Sub1A genes by tandem duplication and divergence of the ancestral Sub1C gene in that order. The alleles of Sub1 genes in tolerant reference variety FR13A seem to have evolved most recently. However, no consistent association could be found between the Sub1 allelic variation and submergence tolerance probably due to low minor allele frequencies and presence of exceptions to the known Sub1A-1 association in the genotype panel. We identified 18 cultivars with non-Sub1A-1 source of submergence tolerance which after further mapping and validation in bi-parental populations will be useful for development of superior flood tolerant rice cultivars.

Cost-Effective Home Mechanical Ventilation in Neurosurgery Patients: Case Series of Three Patients

Background  Neurological patients who are ventilator-dependent occupy scarce beds in the hospitals for prolonged periods of time. Most, if not all, can be discharged on home mechanical ventilation (HMV). However, due to lack of insurance and state support, it remains prohibitively expensive for the vast majority of those who require it most.

Materials and Methods  The authors discuss three patients admitted in the Department of Neurosurgery between January and August 2019, who were discharged on HMV after remaining on ventilator support for prolonged period in the hospital. Each patient was discharged with two units (one as standby) of AgVa home ventilator (AgVa Healthcare; New Delhi, India), one Ambu-bag, one pulse oximeter, and one backup power supply unit capable of supplying power to ventilator for a minimum of 24 hours. All the equipment were given free-of-cost through donations by hospital staffs and other donors. All patients were followed up telephonically from their homes and the incidence of complications, ventilator malfunction, and additional cost of HMV on the families were ascertained.

Observation and Results  Of the three patients, two were male and one female. Age ranged from 12 to 17 years. The duration of in-hospital ventilator support prior to discharge on HMV varied from 1 to 5 years. There was no insurance cover available for any of the patients with all expenses being “out of pocket.” The equipment cost Indian Rupees (INR) 115,700 (USD 1,615: two units of AgVa home ventilator costing INR 100,000 [USD 1,396], one Ambu-bag costing INR 1,100 [USD 15], one pulse oximeter costing INR 1,600 [USD 22], and one backup power supply unit costing INR 13,000 [USD 182]). Discharge on HMV was planned on specific request from patients’ families and informed consent was taken from all. All patients had tracheostomies. Mode of HMV was pressure support ventilation in all. Telephonic follow-up ranged from 1 to 7 months. The cost of disposables was INR 100 per month (USD 0.7) for all the patients. No complications occurred in any patient. There was no incidence of ventilator-associated pneumonia (VAP) or ventilator malfunction.

Conclusions  Availability of cost-effective indigenous ventilator like AgVa home has made HMV possible, even for poor patients with neurological diseases, and has the potential to improve quality of life, decrease VAP rates, and free up scarce ventilator beds in hospitals. Longer-term follow-up in larger number of patients will improve the data on safety and feasibility in developing countries like India.