Accelerated generation of elite inbreds in maize using doubled haploid technology

The creation of homozygous parental lines for hybrid development is one of the key components of commercial maize breeding programs. It usually takes up to 6 to 7 generations of selfing to obtain homozygous inbreds from the initial cross using the conventional pedigree method. Using doubled haploid (DH) method, concurrent fixation of all the genes covering entire chromosomes is possible within a single generation. For generation of DH lines, haploids are generated first by several means such as in-vitro method using tissue culture technique and in-vivo method using the haploid inducer (HI) lines. Of which, tissue culture-based methods have shown little promise for large-scale DH production as it needs good infrastructures and technical requirements. In contrast, inducer-based method provides more optimistic solutions for large-scale DH lines production. Due to its rapidity, DH technology is now being adopted in many countries including India for reducing the breeding cycle

Expression analysis of maize genes during Bipolaris maydis infection and assessing their role in disease resistance and symptom development

82-93Bipolaris maydis causing maydis leaf blight (MLB) is an aggressive fungal pathogen of maize. The present study focused on the responses of certain defence genes in the resistant and susceptible maize inbred lines viz., SC-7 and CM 119, respectively, against MLB and symptom development in the host. Biochemical activity of the PR protein β-1, 3-glucanase and phenylalanine ammonia lyase (PAL) assay, with total chlorophyll content was recorded for both the inbred lines before and after pathogen inoculation. Gene expression was studied by quantitative polymerase chain reaction (qPCR) at different time intervals post inoculation. Differential expression pattern was observed even at the same time point in both the inbred lines. Enhanced expression of the pathogenesis related (PR) protein and phenylalanine ammonia lyase (PAL) enzyme at different time points in resistant lines indicated their association with infection stages of B. maydis and response of the resistant line against disease establishment. Down regulated gene expression of pheophytinase suggests reduced enzyme activity linked with less chlorophyll degradation in the resistant line compared to the susceptible line. This fact directly correlates with symptom development of MLB disease. The present study thus revealed that the expression of defence related genes is aligned with developmental stages of the pathogen to restrict its growth and gene expression of constitutive genes also changes differentially during the disease development in resistant and susceptible lines

An Enhanced Ensemble Deep Neural Network Approach for Elderly Fall Detection System Based on Wearable Sensors

Fatal injuries and hospitalizations caused by accidental falls are significant problems among the elderly. Detecting falls in real-time is challenging, as many falls occur in a short period. Developing an automated monitoring system that can predict falls before they happen, provide safeguards during the fall, and issue remote notifications after the fall is essential to improving the level of care for the elderly. This study proposed a concept for a wearable monitoring framework that aims to anticipate falls during their beginning and descent, activating a safety mechanism to minimize fall-related injuries and issuing a remote notification after the body impacts the ground. However, the demonstration of this concept in the study involved the offline analysis of an ensemble deep neural network architecture based on a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) and existing data. It is important to note that this study did not involve the implementation of hardware or other elements beyond the developed algorithm. The proposed approach utilized CNN for robust feature extraction from accelerometer and gyroscope data and RNN to model the temporal dynamics of the falling process. A distinct class-based ensemble architecture was developed, where each ensemble model identified a specific class. The proposed approach was evaluated on the annotated SisFall dataset and achieved a mean accuracy of 95%, 96%, and 98% for Non-Fall, Pre-Fall, and Fall detection events, respectively, outperforming state-of-the-art fall detection methods. The overall evaluation demonstrated the effectiveness of the developed deep learning architecture. This wearable monitoring system will prevent injuries and improve the quality of life of elderly individuals

Characterization of maize genotypes using microsatellite markers associated with QTLs for kernel iron and zinc

224-234Crop genetic resources rich in Fe and Zn provide sustainable and cost-effective solution to alleviate micronutrient malnutrition. Maize being the leading staple crop assumes great significance as a target crop for biofortification. We report here wide genetic variation for kernel Fe and Zn among 20 diverse maize inbreds lines, majority of which were bred for quality protein maize (QPM) and provitamin-A. Kernel Fe ranged from 30.0 - 46.13 mg/kg, while kernel Zn ranged from 8.68-39.56 mg/kg. Moderate but positive correlation was observed between the micronutrients. Characterization using 25 Single sequence repeats (SSRs) linked to QTLs for kernel Fe produced 58 alleles. Similarly, 86 alleles were identified from 35 SSRs linked to QTLs for kernel Zn. One unique allele for kernel Fe and three unique alleles for kernel Zn were identified. The mean polymorphic information content (PIC) was 0.40 for both kernel Fe and  Zn. Jaccard’s dissimilarity coefficients varied from 0.25 - 0.91 with a mean of 0.58 for kernel-Fe while 0.27- 0.88 with a mean of 0.57 for kernel Zn. Principal coordinate analysis depicted diversity of inbreds. Cluster analysis grouped the inbreds into three major clusters for both kernel Fe and Zn. Potential cross combinations have been proposed to develop micronutrient rich hybrids and novel inbreds with higher Fe and Zn. The information generated here would help the maize biofortification programme to develop nutritionally enriched hybrids

A 30-day follow-up study on the prevalence of SARS-COV-2 genetic markers in wastewater from the residence of COVID-19 patient and comparison with clinical positivity

Wastewater based epidemiology (WBE) is an important tool to fight against COVID-19 as it provides insights into the health status of the targeted population from a small single house to a large municipality in a cost-effective, rapid, and non-invasive way. The implementation of wastewater based surveillance (WBS) could reduce the burden on the public health system, management of pandemics, help to make informed decisions, and protect public health. In this study, a house with COVID-19 patients was targeted for monitoring the prevalence of SARS-CoV-2 genetic markers in wastewa-ter samples (WS) with clinical specimens (CS) for a period of 30 days. RT-qPCR technique was employed to target non-structural (ORF1ab) and structural-nucleocapsid (N) protein genes of SARS-CoV-2, according to a validated experimental protocol. Physiological, environmental, and biological parameters were also measured following the American Public Health Association (APHA) standard protocols. SARS-CoV-2 viral shedding in wastewater peaked when the highest number of COVID-19 cases were clinically diagnosed. Throughout the study period, 7450 to 23,000 gene copies/1000 mL were detected, where we identified 47 % (57/120) positive samples from WS and 35 % (128/360) from CS. When the COVID-19 patient number was the lowest (2), the highest CT value (39.4; i.e., lowest copy number) was identified from WS. On the other hand, when the COVID-19 patients were the highest (6), the lowest CT value (25.2 i.e., highest copy numbers) was obtained from WS. An advance signal of increased SARS-CoV-2 viral load from the COVID-19 patient was found in WS earlier than in the CS. Using customized primer sets in a traditional PCR approach, we confirmed that all SARS-CoV-2 variants identified in both CS and WS were Delta variants (B.1.617.2). To our knowledge, this is the first follow-up study to determine a temporal relationship be-tween COVID-19 patients and their discharge of SARS-CoV-2 RNA genetic markers in wastewater from a single house including all family members for clinical sampling from a developing country (Bangladesh), where a proper sewage system is lacking. The salient findings of the study indicate that monitoring the genetic markers of the SARS-CoV-2 virus in wastewater could identify COVID-19 cases, which reduces the burden on the public health system during COVID-19 pandemics.Peer reviewe

Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition

Acknowledgments This work was funded in part by the William and Melinda Gates Foundation, award 42917 to JPN and OCS; US National Institutes of Health grants 5R01HG005220 to HCB, 5R01HG004885 to MP; US National Science Foundation Graduate Research Fellowship award DGE0750616 to JNP; AWW and JP are funded by The Wellcome Trust (Grant No. WT098051).Peer reviewedPublisher PD

Modified coptisine derivatives as an inhibitor against pathogenic Rhizomucor miehei, Mycolicibacterium smegmatis (Black Fungus), Monkeypox, and Marburg virus by molecular docking and molecular dynamics simulation-based drug design approach

During the second phase of SARS-CoV-2, an unknown fungal infection, identified as black fungus, was transmitted to numerous people among the hospitalized COVID-19 patients and increased the death rate. The black fungus is associated with the Mycolicibacterium smegmatis, Mucor lusitanicus, and Rhizomucor miehei microorganisms. At the same time, other pathogenic diseases, such as the Monkeypox virus and Marburg virus, impacted global health. Policymakers are concerned about these pathogens due to their severe pathogenic capabilities and rapid spread. However, no standard therapies are available to manage and treat those conditions. Since the coptisine has significant antimicrobial, antiviral, and antifungal properties; therefore, the current investigation has been designed by modifying coptisine to identify an effective drug molecule against Black fungus, Monkeypox, and Marburg virus. After designing the derivatives of coptisine, they have been optimized to get a stable molecular structure. These ligands were then subjected to molecular docking study against two vital proteins obtained from black fungal pathogens: Rhizomucor miehei (PDB ID: 4WTP) and Mycolicibacterium smegmatis (PDB ID 7D6X), and proteins found in Monkeypox virus (PDB ID: 4QWO) and Marburg virus (PDB ID 4OR8). Following molecular docking, other computational investigations, such as ADMET, QSAR, drug-likeness, quantum calculation and molecular dynamics, were also performed to determine their potentiality as antifungal and antiviral inhibitors. The docking score reported that they have strong affinities against Black fungus, Monkeypox virus, and Marburg virus. Then, the molecular dynamic simulation was conducted to determine their stability and durability in the physiological system with water at 100 ns, which documented that the mentioned drugs were stable over the simulated time. Thus, our in silico investigation provides a preliminary report that coptisine derivatives are safe and potentially effective against Black fungus, Monkeypox virus, and Marburg virus. Hence, coptisine derivatives may be a prospective candidate for developing drugs against Black fungus, Monkeypox and Marburg viruses

Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.This research was supported by Water Aid Bangladesh, North South University, Dhaka, COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University (NSTU), Noakhali, Bangladesh, the International Training Network of Bangladesh University of Engineering and Technology (ITN-BUET) - Centre for Water Supply and Waste Management, and KTH Royal Institute of Technology, Sweden. We acknowledge the sincere help and support of the staff and volunteers of NSTU-COVID-19 Diagnostic Lab, Noakhali Science and Technology University, Bangladesh during the different phases of the study. PB and MTI acknowledge the Life Science Technology Platform, Science for Life Laboratory for the seed funding to initiate the wastewater-based epidemiological studies for SARS-CoV-2 in Bangladesh. We would also like to acknowledge the two anonymous reviewers for their critical comments as well as their thoughtful insights, which has significantly improved the manuscript.Peer reviewe

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Not AvailablePhytic acid (PA) is an important antinutritional component in maize that affects the availability of major micro-nutrients like di- and multivalent mineral cations like iron (Fe) and zinc (Zn). The long-term consumption of maize as a staple food crop leads to micronutrient malnutrition especially iron and zinc deficiency in the human population. In addition, it also acts as a storehouse of a major part of mineral phosphorous (P), approximately 80% of the total P stored as phytate P is not available to monogastric animals like humans and poultry birds, and it gets excreted as such, leading to one of the major environmental pollution called eutrophication. Of the various low phytic acid (lpa) mutants, lpa2-2 generated through mutagenesis reduces PA by 30%. BML 6 and BML 45, the parents of the popular maize hybrid DHM 121 with high PA were selected to introgress lpa2-2 through marker-assisted backcross breeding (MABB). The percent recurrent parental genome (RPG) in the selected BC2F2 plants ranged from 88.68 to 91.04% and 90.09–91.51% in the genetic background of BML 6 and BML 45, respectively. Based on the highest percentage of RPG, best five BC2F2 plants, viz., #3190, #3283, #3230, #3263 and #3292 with RPG 88.68–91.04% in the genetic background of BML 6 and #3720, #3776, #3717, #3828 and #3832 with RPG 90.09–91.51% in the genetic background of BML 45 were advanced to BC2F3. The newly developed near-isogenic lines (NILs) possessed low phytate content (2.37 mg/g in BML 6 and 2.40 mg/g in BML 45) compared to 3.59 mg/g and 3.16 mg/g in recurrent parents BML 6 and BML 45, respectively thereby reducing the phytate by an average of 34 and 24 per cent, respectively. These newly developed progenies were similar to their recurrent parents for various morphological traits. These inbreds assume great significance in alleviating Fe and Zn deficiencies in worldwide.Not Availabl