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Tropical tuber crops such as cassava, sweet potatoes and elephant foot yam play vital roles in global food security and economic development, particularly in developing nations. The present study examines the current scenario of tuber crop production and trade dynamics, focusing on India's role both as a producer and an exporter. Using empirical data from various sources including Food and Agriculture Organization of the United Nations and Agricultural and Processed Food Products Export Development Authority, the study analyses production trends, trade patterns and policy frameworks, to elucidate potential pathways for enhancing productivity, sustainability and competitiveness in the tuber crops sector. The analysis reveals significant growth in cassava and sweet potato production globally, with India emerging as a key player. However, climate change, pests and diseases, soil degradation, and trade barriers pose hurdles to the growth of the sector. This study also recommends comprehensive strategies, including climate-resilient agricultural practices, integrated pest management, soil health enhancement and infrastructure development, to address these challenges and promote the sustainable growth of tuber crops. [ABSTRACT FROM AUTHOR]

Pneumonia remains a critical health concern worldwide, necessitating efficient diagnostic tools to enhance patient care. This research proposes a concatenated modified LeNet classifier to classify pneumonia images accurately. The model leverages deep learning techniques to improve the diagnosis of Pneumonia, leading to more effective and timely treatment. Our modified LeNet architecture incorporates a revised Rectified Linear Unit (ReLU) activation function. This enhancement aims to boost the discriminative capacity of the features learned by the model. Furthermore, we integrate batch normalization to stabilize the training process and enhance performance within smaller, less complex, CNN architectures like LeNet. Batch normalization addresses internal covariate shift, a phenomenon where the distribution of activations within a network alter during training. These modifications help to prevent overfitting and decrease computational time. A comprehensive dataset is used to evaluate the model's performance, and the model is benchmarked against relevant deep-learning models. The results demonstrate a high recognition rate, with an accuracy of 96% in pneumonia image recognition. This research suggests that the Concatenated Modified LeNet classifier has the potential to be a highly useful tool for medical professionals in the diagnosis of pneumonia. By offering accurate and efficient image classification, our model could contribute to improved treatment decisions and patient outcomes.

Breast cancer remains a significant global public health concern, emphasizing the critical role of accurate histopathological analysis in diagnosis and treatment planning. In recent years, the advent of deep learning techniques has showcased notable potential in elevating the precision and efficiency of histopathological data analysis. The proposed work introduces a novel approach that harnesses the power of Transfer Learning to capitalize on knowledge gleaned from pre-trained models, adapting it to the nuanced landscape of breast cancer histopathology. Our proposed model, a Transfer Learning-based concatenated model, exhibits substantial performance enhancements compared to traditional methodologies. Leveraging well-established pretrained models such as VGG-16, MobileNetV2, ResNet50, and DenseNet121-each Convolutional Neural Network architecture designed for classification tasks-this study meticulously tunes hyperparameters to optimize model performance. The implementation of a concatenated classification model is systematically benchmarked against individual classifiers on histopathological data. Remarkably, our concatenated model achieves an impressive training accuracy of 98%. The outcomes of our experiments underscore the efficacy of this four-level concatenated model in advancing the accuracy of breast cancer histopathological data analysis. By synergizing the strengths of deep learning and transfer learning, our approach holds the potential to augment the diagnostic capabilities of pathologists, thereby contributing to more informed and personalized treatment planning for individuals diagnosed with breast cancer. This research heralds a promising stride toward leveraging cutting-edge technology to refine the understanding and management of breast cancer, marking a significant advancement in the intersection of artificial intelligence and healthcare.

Convolutional neural networks (CNNs) have been extensively utilized in medical image processing to automatically extract meaningful features and classify various medical conditions, enabling faster and more accurate diagnoses. In this paper, LeNet, a classic CNN architecture, has been successfully applied to breast cancer data analysis. It demonstrates its ability to extract discriminative features and classify malignant and benign tumors with high accuracy, thereby supporting early detection and diagnosis of breast cancer. LeNet with corrected Rectified Linear Unit (ReLU), a modification of the traditional ReLU activation function, has been found to improve the performance of LeNet in breast cancer data analysis tasks via addressing the "dying ReLU" problem and enhancing the discriminative power of the extracted features. This has led to more accurate, reliable breast cancer detection and diagnosis and improved patient outcomes. Batch normalization improves the performance and training stability of small and shallow CNN architecture like LeNet. It helps to mitigate the effects of internal covariate shift, which refers to the change in the distribution of network activations during training. This classifier will lessen the overfitting problem and reduce the running time. The designed classifier is evaluated against the benchmarking deep learning models, proving that this has produced a higher recognition rate. The accuracy of the breast image recognition rate is 89.91%. This model will achieve better performance in segmentation, feature extraction, classification, and breast cancer tumor detection.

Background: Abnormal macrophage function caused by dysfunctional cystic fibrosis transmembrane conductance regulator (CFTR) is a critical contributor to chronic airway infections and inflammation in people with cystic fibrosis (PWCF). Elexacaftor/tezacaftor/ivacaftor (ETI) is a new CFTR modulator therapy for PWCF. Host-pathogen and clinical responses to CFTR modulators are poorly described. We sought to determine how ETI impacts macrophage CFTR function, resulting effector functions and relationships to clinical outcome changes., Methods: Clinical information and/or biospecimens were obtained at ETI initiation and 3, 6, 9 and 12 months post-ETI in 56 PWCF and compared with non-CF controls. Peripheral blood monocyte-derived macrophages (MDMs) were isolated and functional assays performed., Results: ETI treatment was associated with increased CF MDM CFTR expression, function and localisation to the plasma membrane. CF MDM phagocytosis, intracellular killing of CF pathogens and efferocytosis of apoptotic neutrophils were partially restored by ETI, but inflammatory cytokine production remained unchanged. Clinical outcomes including increased forced expiratory volume in 1 s (+10%) and body mass index (+1.0 kg·m -2 ) showed fluctuations over time and were highly individualised. Significant correlations between post-ETI MDM CFTR function and sweat chloride levels were observed. However, MDM CFTR function correlated with clinical outcomes better than sweat chloride., Conclusion: ETI is associated with unique changes in innate immune function and clinical outcomes., Competing Interests: Conflict of interest: The authors declare that no conflicts of interest exists., (Copyright ©The authors 2023. For reproduction rights and permissions contact permissions@ersnet.org.)

Background: Cystic fibrosis (CF) is a multisystem disease with progressive deterioration. Recently, CF transmembrane conductance regulator (CFTR) modulator therapies were introduced that repair underlying protein defects. Objective of this study was to determine the impact of elexacaftor-tezacaftor-ivacaftor (ETI) on clinical parameters and inflammatory responses in people with CF (pwCF)., Methods: Lung function (FEV 1 ), body mass index (BMI) and microbiologic data were collected at initiation and 3-month intervals for 1 year. Blood was analyzed at baseline and 6 months for cytokines and immune cell populations via flow cytometry and compared to non-CF controls., Results: Sample size was 48 pwCF, 28 (58.3%) males with a mean age of 28.8 ± 10.7 years. Significant increases in %predicted FEV 1 and BMI were observed through 6 months of ETI therapy with no change thereafter. Changes in FEV 1 and BMI at 3 months were significantly correlated (r = 57.2, p < 0.01). There were significant reductions in Pseudomonas and Staphylococcus positivity (percent of total samples) in pwCF through 12 months of ETI treatment. Healthy controls (n = 20) had significantly lower levels of circulating neutrophils, interleukin (IL)-6, IL-8, and IL-17A and higher levels of IL-13 compared to pwCF at baseline (n = 48). After 6 months of ETI, pwCF had significant decreases in IL-8, IL-6, and IL-17A levels and normalization of peripheral blood immune cell composition., Conclusions: In pwCF, ETI significantly improved clinical outcomes, reduced systemic pro-inflammatory cytokines, and restored circulating immune cell composition after 6 months of therapy., (© 2022 The Authors. Pediatric Pulmonology published by Wiley Periodicals LLC.)

Plant precursor miRNAs (pre-miRNA) have conserved evolutionary footprints that correlate with mode of miRNA biogenesis. In plants, base to loop and loop to base modes of biogenesis have been reported. Conserved structural element(s) in pre-miRNA play a major role in turn over and abundance of mature miRNA. Pre-miR396c sequences and secondary structural characteristics across Oryza species are presented. Based on secondary structure, twelve Oryza pre-miR396c sequences are divided into three groups, with the precursor from halophytic Oryza coarctata forming a distinct group. The miRNA-miRNA* duplex region is completely conserved across eleven Oryza species as are other structural elements in the pre-miRNA, suggestive of an evolutionarily conserved base-to-loop mode of miRNA biogenesis. SNPs within O. coarctata mature miR396c sequence and miRNA* region have the potential to alter target specificity and association with the RNA-induced silencing complex. A conserved SNP variation, rs10234287911 (G/A), identified in O. sativa pre-miR396c sequences alters base pairing above the miRNA-miRNA* duplex. The more stable structure conferred by the 'A 10234287911 ' allele may promote better processing vis-à-vis the structure conferred by 'G 10234287911 ' allele. We also examine pri- and pre-miR396c expression in cultivated rice under heat and salinity and their correlation with miR396c expression., (© 2023. The Author(s).)

Soil salinity is a leading cause for yield losses in rice, affecting nearly 6% of global rice cultivable area. India is host to a rich diversity of coastal rice landraces that are naturally tolerant to salinity and an untapped source to identify novel determinants of salinity tolerance. In the present study, we have assessed the relative salinity tolerance of 43 previously genotyped rice landraces at seedling stage, using thirteen morpho-physiological and biochemical parameters using a hydroponics system. Among 43 rice varieties, 25 were tolerant, 15 were moderately tolerant, 1 was moderately susceptible and 2 sensitive checks were found to be highly susceptible based on standard salinity scoring methods. In addition to previously known saline tolerant genotypes (Pokkali, FL478 and Nona Bokra), the present study has novel genotypes such as Katrangi, Orkyma, Aduisen 1, Orumundakan 1, Hoogla, and Talmugur 2 as potential sources of salinity tolerance through measurement of morpho-physiological and biochemical parameters including Na + , K + estimations and Na + /K + ratios. Further, Pallipuram Pokkali may be an important source of the tissue tolerance trait under salinity. Four marker trait associations (RM455-root Na + ; RM161-shoot and root Na + /K + ratios; RM237-salinity tolerance index) accounted for phenotypic variations in the range of 20.97-39.82%. A significant increase in root endodermal and exodermal suberization was observed in selected rice landraces under salinity. For the first time, variation in the number of suberized sclerenchymatous layers as well as passage cells is reported, in addition to expression level changes in suberin biosynthetic genes (CYP86A2, CYP81B1, CYP86A8 and PERL)., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

Chickpea production is vulnerable to drought stress. Identifying the genetic components underlying drought adaptation is crucial for enhancing chickpea productivity. Here, we present the fine mapping and characterization of 'QTL-hotspot', a genomic region controlling chickpea growth with positive consequences on crop production under drought. We report that a non-synonymous substitution in the transcription factor CaTIFY4b regulates seed weight and organ size in chickpea. Ectopic expression of CaTIFY4b in Medicago truncatula enhances root growth under water deficit. Our results suggest that allelic variation in 'QTL-hotspot' improves pre-anthesis water use, transpiration efficiency, root architecture and canopy development, enabling high-yield performance under terminal drought conditions. Gene expression analysis indicated that CaTIFY4b may regulate organ size under water deficit by modulating the expression of GRF-INTERACTING FACTOR1 (GIF1), a transcriptional co-activator of Growth-Regulating Factors. Taken together, our study offers new insights into the role of CaTIFY4b and on diverse physiological and molecular mechanisms underpinning chickpea growth and production under specific drought scenarios., (© 2022 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Cystic fibrosis (CF) is caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Chronic inflammation and decline in lung function are major reasons for morbidity in CF. Mutant CFTR expressed in phagocytic cells such as macrophages contributes to persistent infection, inflammation, and lung disease in CF. Macrophages play a central role in innate immunity by eliminating pathogenic microbes by a process called phagocytosis. Phagocytosis is required for tissue homeostasis, balancing inflammation, and crosstalk with the adaptive immune system for antigen presentation. This review focused on (1) current understandings of the signaling underlying phagocytic mechanisms; (2) existing evidence for phagocytic dysregulation in CF; and (3) the emerging role of CFTR modulators in influencing CF phagocytic function. Alterations in CF macrophages from receptor initiation to phagosome formation are linked to disease progression in CF. A deeper understanding of macrophages in the context of CFTR and phagocytosis proteins at each step of phagosome formation might contribute to the new therapeutic development of dysregulated innate immunity in CF. Therefore, the review also indicates future areas of research in the context of CFTR and macrophages.

Fragrance in rice grains is a key quality trait determining its acceptability and marketability. Intensive research on rice aroma identified mutations in betaine aldehyde dehydrogenase (OsBADH2) leading to production of aroma in rice. Gene editing technologies like CRISPR/Cas9 system has opened new avenues for accelerated improvement of rice grain quality through targeted mutagenesis. In this study, we have employed CRISPR/Cas9 tool to create novel alleles of OsBADH2 leading to introduction of aroma into an elite non-aromatic rice variety ASD16. PCR analysis of putative transformants using primers targeting the flanking regions of sgRNA in the 7th exon of OsBADH2 identified 37.5% potential multi-allelic mutations in T0 generation. Sensory evaluation test in the leaves of T0 lines identified thirteen lines belonging to five independent events producing aroma. Sequence analysis of these aromatic T0 lines identified 22 different types of mutations located within -17 bp to +15bp of sgRNA region. The -1/-2 bp deletion in the line # 8-19 and -8/-5 bp deletion in the line # 2-16 produced strong aroma and the phenotype was stably inherited in the T1 generation. Comparative volatile profiling detected novel aromatic compounds viz., pyrrolidine, pyridine, pyrazine, pyradazine and pyrozole in the grains of T1 progenies of line # 8-19. This study has demonstrated the use of CRISPR/Cas9 in creating novel alleles of OsBADH2 to introduce aroma into any non-aromatic rice varieties., Competing Interests: The authors have no competing interests

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Naturally evolved saline tolerant rice landraces found along the coastline of India are a valuable genomic resource to explore the complex, polygenic nature of salinity tolerance. In the present study, a set of 28 genome wide SSR markers, 11 salt responsive genic SSR markers and 8 Saltol QTL linked SSR markers were used to estimate genetic relatedness and population structure within a collection of 47 rice landraces (including a tolerant and 2 sensitive checks) originating from geographically divergent coastal regions of India. All three marker types identified substantial genetic variation among the landraces, as evident from their higher PIC values (0.53 for genomic SSRs, 0.43 for Genic SSRs and 0.59 for Saltol SSRs). The markers RM431, RM484 (Genomic SSRs), OsCAX (D), OsCAX (T) (Genic SSRs) and RM562 (Saltol SSR) were identified as good candidates to be used in breeding programs for improving salinity tolerance in rice. STRUCTURE analysis divided the landraces into five distinct populations, with classification correlating with their geographical locations. Principal coordinate and hierarchical cluster analyses (UPGMA and neighbor joining) are in close agreement with STRUCTURE results. AMOVA analysis indicated a higher magnitude of genetic differentiation within individuals of groups (58%), than among groups (42%). We also report the development and validation of a new Cleavage Amplified Polymorphic Sequence (CAPS) marker (OsHKT1;5V395) that targets a codon in the sodium transporter gene OsHKT1;5 (Saltol/SKC1 locus) that is associated with sodium transport rates in the above rice landraces. The CAPS marker was found to be present in all landraces except in IR29, Kamini, Gheus, Matla 1 and Matla 2. Significant molecular genetic diversity established among the analyzed salt tolerant rice landraces will aid in future association mapping; the CAPS marker, OsHKT1;5V395 can be used to map rice landraces for the presence of the SNP (Single Nucleotide Polymorphism) associated with increased sodium transport rates and concomitant salinity tolerance in rice., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Herpes simplex virus hepatitis is a rare but potentially fatal disease without early intervention. Impaired immunity is a major predisposing risk factor but infection in immunocompetent individuals is not unheard of. Diagnosis is complicated by its rarity and nonspecific signs and symptoms on presentation. Identification by liver biopsy is often limited due to concurrent coagulopathy. Early and aggressive treatment is centered on antiviral therapy with acyclovir. We present a case of herpes hepatitis in an immunocompetent woman following abdominal instrumentation.