Insect pest resistance: an alternative approach for crop protection

From experience with insect resistance caused by synthetic chemical insecticides, it is clear that no single management tactic can provide lasting solutions to the insect pest problem. Biological control is a component of integrated pest management strategies that minimize insecticide spray applications and move towards ecofriendly systems of pest management. Successful utilization of host plant resistance, phytochemical products, pheromones, biological control agents such as predators, parasitoids, entomopathogenic bacteria, virus, nematodes, and fungi can help to control many destructive pests to achieve sustainable crop protection

Far-Field DOA Estimation of Uncorrelated RADAR Signals through Coprime Arrays in Low SNR Regime by Implementing Cuckoo Search Algorithm

For the purpose of attaining a high degree of freedom (DOF) for the direction of arrival (DOA) estimations in radar technology, coprime sensor arrays (CSAs) are evaluated in this paper. In addition, the global and local minima of extremely non-linear functions are investigated, aiming to improve DOF. The optimization features of the cuckoo search (CS) algorithm are utilized for DOA estimation of far-field sources in a low signal-to-noise ratio (SNR) environment. The analytical approach of the proposed CSAs, CS and global and local minima in terms of cumulative distribution function (CDF), fitness function and SNR for DOA accuracy are presented. The parameters like root mean square error (RMSE) for frequency distribution, RMSE variability analysis, estimation accuracy, RMSE for CDF, robustness against snapshots and noise and RMSE for Monte Carlo simulation runs are explored for proposed model performance estimation. In conclusion, the proposed DOA estimation in radar technology through CS and CSA achievements are contrasted with existing tools such as particle swarm optimization (PSO).This project has received funding from Universidad Carlos III de Madrid and the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant 801538

Macrophage signaling in HIV-1 infection

The human immunodeficiency virus-1 (HIV-1) is a member of the lentivirus genus. The virus does not rely exclusively on the host cell machinery, but also on viral proteins that act as molecular switches during the viral life cycle which play significant functions in viral pathogenesis, notably by modulating cell signaling. The role of HIV-1 proteins (Nef, Tat, Vpr, and gp120) in modulating macrophage signaling has been recently unveiled. Accessory, regulatory, and structural HIV-1 proteins interact with signaling pathways in infected macrophages. In addition, exogenous Nef, Tat, Vpr, and gp120 proteins have been detected in the serum of HIV-1 infected patients. Possibly, these proteins are released by infected/apoptotic cells. Exogenous accessory regulatory HIV-1 proteins are able to enter macrophages and modulate cellular machineries including those that affect viral transcription. Furthermore HIV-1 proteins, e.g., gp120, may exert their effects by interacting with cell surface membrane receptors, especially chemokine co-receptors. By activating the signaling pathways such as NF-kappaB, MAP kinase (MAPK) and JAK/STAT, HIV-1 proteins promote viral replication by stimulating transcription from the long terminal repeat (LTR) in infected macrophages; they are also involved in macrophage-mediated bystander T cell apoptosis. The role of HIV-1 proteins in the modulation of macrophage signaling will be discussed in regard to the formation of viral reservoirs and macrophage-mediated T cell apoptosis during HIV-1 infection

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

New Techniques in Understanding Cancer Biology and Metabolism

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Supervised Single Channel Speech Enhancement Based on Dual-Tree Complex Wavelet Transforms and Nonnegative Matrix Factorization Using the Joint Learning Process and Subband Smooth Ratio Mask

In this paper, we propose a novel speech enhancement method based on dual-tree complex wavelet transforms (DTCWT) and nonnegative matrix factorization (NMF) that exploits the subband smooth ratio mask (ssRM) through a joint learning process. The discrete wavelet packet transform (DWPT) suffers the absence of shift invariance, due to downsampling after the filtering process, resulting in a reconstructed signal with significant noise. The redundant stationary wavelet transform (SWT) can solve this shift invariance problem. In this respect, we use efficient DTCWT with a shift invariance property and limited redundancy and calculate the ratio masks (RMs) between the clean training speech and noisy speech (i.e., training noise mixed with clean speech). We also compute RMs between the noise and noisy speech and then learn both RMs with their corresponding clean training clean speech and noise. The auto-regressive moving average (ARMA) filtering process is applied before NMF in previously generated matrices for smooth decomposition. An ssRM is proposed to exploit the advantage of the joint use of the standard ratio mask (sRM) and square root ratio mask (srRM). In short, the DTCWT produces a set of subband signals employing the time-domain signal. Subsequently, the framing scheme is applied to each subband signal to form matrices and calculates the RMs before concatenation with the previously generated matrices. The ARMA filter is implemented in the nonnegative matrix, which is formed by considering the absolute value. Through ssRM, speech components are detected using NMF in each newly formed matrix. Finally, the enhanced speech signal is obtained via the inverse DTCWT (IDTCWT). The performances are evaluated by considering an IEEE corpus, the GRID audio-visual corpus, and different types of noises. The proposed approach significantly improves objective speech quality and intelligibility and outperforms the conventional STFT-NMF, DWPT-NMF, and DNN-IRM methods

Aiding Cancer’s “Sweet Tooth”: Role of Hexokinases in Metabolic Reprogramming

Hexokinases (HKs) convert hexose sugars to hexose-6-phosphate, thus trapping them inside cells to meet the synthetic and energetic demands. HKs participate in various standard and altered physiological processes, including cancer, primarily through the reprogramming of cellular metabolism. Four canonical HKs have been identified with different expression patterns across tissues. HKs 1–3 play a role in glucose utilization, whereas HK 4 (glucokinase, GCK) also acts as a glucose sensor. Recently, a novel fifth HK, hexokinase domain containing 1 (HKDC1), has been identified, which plays a role in whole-body glucose utilization and insulin sensitivity. Beyond the metabolic functions, HKDC1 is differentially expressed in many forms of human cancer. This review focuses on the role of HKs, particularly HKDC1, in metabolic reprogramming and cancer progression

Spectrum of infections in different regimens of post-induction chemotherapy in acute myeloid leukemia (de-novo): A comparative retrospective study

Background: Patients diagnosed with acute myeloid leukemia (AML) face a heightened susceptibility to infections, which significantly elevates their risk of mortality and disability. The intensity of the chemotherapy treatment and its specific focus on inhibiting myeloid cell divisions render patients especially vulnerable, particularly during the early stages of chemotherapy. This vulnerability is compounded by the occurrence of repeated episodes of prolonged neutropenia, leaving patients highly susceptible to infections. The compromised immune systems of these individuals make them more susceptible to infections, which adversely affect their physical health and overall well-being. Consequently, our study aimed to investigate the range of infections experienced by patients with newly diagnosed AML undergoing different induction chemotherapy. Methods: This was a comparative retrospective study, conducted at a tertiary hospital providing comprehensive cancer care in North India. All newly diagnosed patients with AML, who received induction chemotherapy from January 1, 2012 to November 1, 2022, were identified from the hospital database and included in this study. Results: Four hundred and twenty AML patients treated with either high-intensity or low-intensity induction chemotherapy was observed in this study. It was found that patients who received high-intensity treatment had a higher rate of clinically and microbiologically documented infections, fever without a known cause, and more cases of febrile neutropenia than those who got low-intensity treatment. These differences between the two groups were particularly evident on day 14 (p = 0.0002) and persisted through day 28 (p = 0.005). Conclusions: These findings underscore the effectiveness and downside of high-intensity induction chemotherapy regimens, as evidenced by the higher incidence of infections observed. Further investigation through prospective clinical studies is warranted to better evaluate and validate the efficacy of this approach

GIS-based assessment of groundwater vulnerability to heavy metal contamination via water quality pollution indices in urban Aligarh, India

The study presents an assessment of groundwater vulnerability due to heavy-metal contamination using Heavy Metal Pollution and Contamination Index of Urban Aligarh. Globally, hazardous compounds in industrially contaminated sites are pressing and high-priority issue. A detailed risk assessment was carried out to determine the potential health hazards linked to locations that were recently polluted. A total of 17 groundwater samples were taken from hand-pump and 20 industrial drainage samples were collected from selected areas of Aligarh. The concentration of heavy-metals in the collected samples analyzed were shown on maps using ArcGIS software and interpreted for Heavy Metal Pollution Index (HPIx) and Contamination Index (CDx). These analyzed values were subsequently compared with the permissible limits established by the agencies like EPA, WHO, and BIS. The mean concentration of heavy-metals in groundwater of different locations was observed as follows particular sequence: Ni (1.40), Cu (0.58), Zn (0.06), Fe (0.08), Mn (0.04), Cr (0.001), Pb (0.00025) mg/l. Additionally in industrial effluent, Cr (18.3), Ni (13.34), Mn (1.16), Cu (1.99), Pb (1.2), Fe (6.3), Zn (0.51) mg/l. According to HPIx, the analysis reveals 64.7%, of visited areas belonged to have safe groundwater. Conversely, a smaller proportion, 35.3%, was found falling into heavy metal-polluted group. HIGHLIGHTS The study provides a comprehensive assessment of heavy metal contamination.; GIS-driven vulnerability mapping is conducted in the study.; The study includes an evaluation of real-world impact.; The study systematically validates scientific indices for accuracy and reliability.; The study investigates health effects resulting from heavy metal contamination.; A comprehensive analysis of drinking water quality.

Is post-COVID osteonecrosis of jaw (PCONJ) Masquerading as osteomyelitis ? A largest unicentric report of 13 cases

Objective: The purpose of this study was to ascertain the correlation between COVID-19 infection and jaw osteonecrosis, along with the identification of risk factors that could be associated with the development of the condition. Another aim of our study is to establish whether maxillofacial osteonecrosis is an early or late complication seen in COVID-19 patients. Material and method: This was a retrospective study conducted over a period of two years. Case records of patients with a history of severe COVID and steroid treatment who later developed jaw osteonecrosis were evaluated. Result: 13 patients with an age range from 8 years to 70 years were identified. Osteonecrosis was seen as late as 21 months after COVID-19. The majority of the cases involved maxilla, one case was of bi-jaw involvement, and one case presented with isolated mandibular involvement. 6 patients were diabetic and 11 patients gave a history of provocative dental treatment like extraction. Conclusion: A triad of post-COVID coagulopathy, steroid administration, and a provocative dental treatment may contribute to jaw osteonecrosis which may be seen in patients without pre-existing systemic illness and may present as late as 21 months after COVID-19