Development of Temporal Model for Forecasting of Helicoverpa armigera (Noctuidae: Lepidopetra) Using Arima and Artificial Neural Networks.

Helicoverpa armigera (Hübner) (Noctuidae: Lepidopetra) is a polyphagous pest of major crops grown in India. To prevent the damage caused by H. armigera farmers rely heavily on insecticides of diverse groups on a regular basis which is not a benign practice, environmentally and economically. To provide more efficient and accurate information on timely application of insecticides, this research was aimed to develop a forecast model to predict population dynamics of pod borer using Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN). The data used in this study were collected from the randomly installed sex pheromone traps at International Crops Research Institute for the Semi-arid Tropics (ICRISAT), Patancheru, Hyderabad. Several ARIMA (p, d, q) (P, D, Q) and ANN models were developed using the historical trap catch data. ARIMA model (1,0,1), (1,0,2) with minimal BIC, RMSE, MAPE, MAE, and MASE values and higher R2 value (0.53) was selected as the best ARIMA fit model, and neural network (7-30-1) was found to be the best fit to predict the catches of male moths of pod borer from September 2021 to August 2023. A comparative analysis performed between the ARIMA and ANN, shows that the ANN based on feed forward neural networks is best suited for effective pest prediction. With the developed ARIMA model, it would be easier to predict H. armigera adult population dynamics round the year and timely intervention of control measures can be followed by appropriate decision-making schedule for insecticide application.

Whole genome sequencing of spotted stem borer, Chilo partellus, reveals multiple genes encoding enzymes for detoxification of insecticides.

Spotted stem borer, Chilo partellus, is the most important constraint for increasing the production and productivity of maize and sorghum, the two major coarse cereals in Asia and Africa. The levels of resistance to this pest in the cultivated germplasm are low to moderate, and hence, farmers have to use insecticides for effective control of this pest. However, there is no information on the detoxification mechanisms in C. partellus, which is one of the constraints for deployment of appropriate insecticides to control this pest. The ability to detoxify insecticides varies across insect populations, and hence, we sequenced different populations of C. partellus to identify and understand detoxification mechanisms to devise appropriate strategies for deployment of different insecticides for controlling this pest. Larval samples were sequenced from three different cohorts of C. partellus using the Illumina HiSeq 2500 platform. The data were subjected to identify putative genes that are involved in detoxification on insecticides in our cohort insect species. These studies resulted in identification of 64 cytochrome P450 genes (CYP450s), and 36 glutathione S-transferases genes (GSTs) encoding metabolic detoxification enzymes, primarily responsible for xenobiotic metabolism in insects. A total of 183 circadian genes with > 80% homolog and 11 olfactory receptor genes that mediate chemical cues were found in the C. partellus genome. Also, target receptors related to insecticide action, 4 acetylcholinesterase (AChE), 14 γ-aminobutyric acid (GABA), and 15 nicotinic acetylcholine (nAChR) receptors were detected. This is the first report of whole genome sequencing of C. partellus useful for understanding mode of action of different insecticides, and mechanisms of detoxification and designing target-specific insecticides to develop appropriate strategies to control C. partellus for sustainable crop production.

Data-Driven Deep Supervision for Medical Image Segmentation.

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-dependent difficulties such as low image contrast, noisy background, and complicated objects of interest render the segmentation problem challenging. These difficulties diminish dense prediction and make it tough for known approaches to explore data-specific attributes for robust feature extraction. In this paper, we study medical image segmentation by focusing on robust data-specific feature extraction to achieve improved dense prediction. We propose a new deep convolutional neural network (CNN), which exploits specific attributes of input datasets to utilize deep supervision for enhanced feature extraction. In particular, we strategically locate and deploy auxiliary supervision, by matching the object perceptive field (OPF) (which we define and compute) with the layer-wise effective receptive fields (LERF) of the network. This helps the model pay close attention to some distinct input data dependent features, which the network might otherwise 'ignore' during training. Further, to achieve better target localization and refined dense prediction, we propose the densely decoded networks (DDN), by selectively introducing additional network connections (the 'crutch' connections). Using five public datasets (two retinal vessel, melanoma, optic disc/cup, and spleen segmentation) and two in-house datasets (lymph node and fungus segmentation), we verify the effectiveness of our proposed approach in 2D and 3D segmentation.

Objective Outcome Measures for Trials in Patients With Chronic Limb-Threatening Ischemia Across 2 Decades: Analysis and Recommendations.

Chronic limb-threatening ischemia (CLTI) is prevalent and associated with morbidity and mortality. The published research concerning CLTI therapeutics is evolving. The goals of this review are to: 1) summarize the endpoints that are being used in trials assessing interventions for patients with CLTI; and 2) review gaps and discrepancies in current outcome definitions. A search was conducted of the PubMed database and ClinicalTrials.gov to identify studies published between January 2000 and March 2020 that evaluated treatment options for patients with CLTI. Meta-analyses, case series, case reports, abstracts, and expert opinion were excluded. Forty-nine studies (n = 11,667) were identified that fulfilled the inclusion criteria. Most trials reported clinical outcomes (mortality, 69.4%; limb events, 87.8%; target lesion revascularization, 83.7%). Mean follow-up duration was 23.7 months. In investigational device exemption trials, total follow-up and follow-up to primary outcomes were discordant (12 months vs 6 months; P = 0.0018). Hemodynamic testing was reported in 71.4%, usually ankle-brachial index. Patency was assessed in 89.8% of trials; ultrasound was used in 65.3% and invasive angiography in 85.7%, at baseline and/or during follow-up. Wound assessment was performed in 49.0% of studies, qualitative in 28.6% and quantitative in 20.4%. Finally, quality of life assessment was performed in 55% of studies. Definitions for many outcomes varied across studies. Consensus regarding which outcomes to study, uniform definitions, and optimal methods to measure some of these outcomes are yet to be established. A comprehensive effort by all stakeholders is needed to move the field of CLTI forward.

Design and Assessment of Convolutional Neural Network Based Methods for Vitiligo Diagnosis.

Background: Today's machine-learning based dermatologic research has largely focused on pigmented/non-pigmented lesions concerning skin cancers. However, studies on machine-learning-aided diagnosis of depigmented non-melanocytic lesions, which are more difficult to diagnose by unaided eye, are very few. Objective: We aim to assess the performance of deep learning methods for diagnosing vitiligo by deploying Convolutional Neural Networks (CNNs) and comparing their diagnosis accuracy with that of human raters with different levels of experience. Methods: A Chinese in-house dataset (2,876 images) and a world-wide public dataset (1,341 images) containing vitiligo and other depigmented/hypopigmented lesions were constructed. Three CNN models were trained on close-up images in both datasets. The results by the CNNs were compared with those by 14 human raters from four groups: expert raters (>10 years of experience), intermediate raters (5-10 years), dermatology residents, and general practitioners. F1 score, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity metrics were used to compare the performance of the CNNs with that of the raters. Results: For the in-house dataset, CNNs achieved a comparable F1 score (mean [standard deviation]) with expert raters (0.8864 [0.005] vs. 0.8933 [0.044]) and outperformed intermediate raters (0.7603 [0.029]), dermatology residents (0.6161 [0.068]) and general practitioners (0.4964 [0.139]). For the public dataset, CNNs achieved a higher F1 score (0.9684 [0.005]) compared to the diagnosis of expert raters (0.9221 [0.031]). Conclusion: Properly designed and trained CNNs are able to diagnose vitiligo without the aid of Wood's lamp images and outperform human raters in an experimental setting.

VTG-Net: A CNN Based Vessel Topology Graph Network for Retinal Artery/Vein Classification.

From diagnosing cardiovascular diseases to analyzing the progression of diabetic retinopathy, accurate retinal artery/vein (A/V) classification is critical. Promising approaches for A/V classification, ranging from conventional graph based methods to recent convolutional neural network (CNN) based models, have been known. However, the inability of traditional graph based methods to utilize deep hierarchical features extracted by CNNs and the limitations of current CNN based methods to incorporate vessel topology information hinder their effectiveness. In this paper, we propose a new CNN based framework, VTG-Net (vessel topology graph network), for retinal A/V classification by incorporating vessel topology information. VTG-Net exploits retinal vessel topology along with CNN features to improve A/V classification accuracy. Specifically, we transform vessel features extracted by CNN in the image domain into a graph representation preserving the vessel topology. Then by exploiting a graph convolutional network (GCN), we enable our model to learn both CNN features and vessel topological features simultaneously. The final predication is attained by fusing the CNN and GCN outputs. Using a publicly available AV-DRIVE dataset and an in-house dataset, we verify the high performance of our VTG-Net for retinal A/V classification over state-of-the-art methods (with ~2% improvement in accuracy on the AV-DRIVE dataset).

Vascular Access for Large Bore Access.

Recent advances in the field of interventional cardiology have allowed for more complex procedures to be performed percutaneously. Ability to obtain safe large bore vascular access is frequently the key factor to procedural success. Meticulous technique for successful vascular access incorporates the understanding of anatomic landmarks, ultrasound, fluoroscopy, and micropuncture. Adequate hemostasis at the end of the case can be achieved through careful use of commercially available vascular closure devices. Although access-related vascular complications are uncommon, early recognition is key to successful management. Arterial tortuosity and calcification can present a significant challenge to successful common femoral artery access.

Development of a dense genetic map and QTL analysis for pod borer Helicoverpa armigera (Hübner) resistance component traits in chickpea (Cicer arietinum L.).

Genetic enhancement for resistance against the pod borer, Helicoverpa armigera is crucial for enhancing production and productivity of chickpea. Here we provide some novel insights into the genetic architecture of natural variation in H. armigera resistance in chickpea, an important legume, which plays a major role in food and nutritional security. An interspecific recombinant inbred line (RIL) population developed from a cross between H. armigera susceptible accession ICC 4958 (Cicer arietinum) and resistant accession PI 489777 (Cicer reticulatum) was evaluated for H. armigera resistance component traits using detached leaf assay and under field conditions. A high-throughput AxiomCicerSNP array was utilized to construct a dense linkage map comprising of 3,873 loci and spanning a distance of 949.27 cM. Comprehensive analyses of extensive genotyping and phenotyping data identified nine main-effect QTLs and 955 epistatic QTLs explaining up to 42.49% and 38.05% phenotypic variance, respectively, for H. armigera resistance component traits. The main-effect QTLs identified in this RIL population were linked with previously described genes, known to modulate resistance against lepidopteran insects in crop plants. One QTL cluster harbouring main-effect QTLs for three H. armigera resistance component traits and explaining up to 42.49% of the phenotypic variance, was identified on CaLG03. This genomic region, after validation, may be useful to improve H. armigera resistance component traits in elite chickpea cultivars.

Identification and Characterization of a Streptomyces albus Strain and Its Secondary Metabolite Organophosphate against Charcoal Rot of Sorghum.

Streptomycesalbus strain CAI-21 has been previously reported to have plant growth-promotion abilities in chickpea, pigeonpea, rice, and sorghum. The strain CAI-21 and its secondary metabolite were evaluated for their biocontrol potential against charcoal rot disease in sorghum caused by Macrophomina phaseolina. Results exhibited that CAI-21 significantly inhibited the growth of the pathogen, M. phaseolina, in dual-culture (15 mm; zone of inhibition), metabolite production (74% inhibition), and blotter paper (90% inhibition) assays. When CAI-21 was tested for its biocontrol potential under greenhouse and field conditions following inoculation of M. phaseolina by toothpick method, it significantly reduced the number of internodes infected (75% and 45% less, respectively) and length of infection (75% and 51% less, respectively) over the positive control (only M. phaseolina inoculated) plants. Under greenhouse conditions, scanning electron microscopic analysis showed that the phloem and xylem tissues of the CAI-21-treated shoot samples were intact compared to those of the diseased stem samples. The culture filtrate of the CAI-21 was purified by various chromatographic techniques, and the active compound was identified as "organophosphate" by NMR and MS. The efficacy of organophosphate was found to inhibit the growth of M. phaseolina in the poisoned food technique. This study indicates that S.albus CAI-21 and its active metabolite organophosphate have the potential to control charcoal rot in sorghum.

Cangrelor and Heparin for Pulmonary Thromboendarterectomy in Heparin-Induced Thrombocytopenia.

Perioperative anticoagulation management for patients with heparin-induced thrombocytopenia requiring cardiopulmonary bypass and deep hypothermic circulatory arrest presents a clinical challenge. Alternative anticoagulants have been used but can cause significant postoperative bleeding. We report the successful use of cangrelor and heparin in a 30-year-old patient with severe heparin-induced thrombocytopenia undergoing urgent pulmonary thromboendarterectomy.

Determination of Optimal Coronary Flow for the Preservation of "Donation after Circulatory Death" in Murine Heart Model.

Donation after circulatory death donors (DCD) have the potential to increase the number of heart transplants. The DCD hearts undergo an extended period of warm ischemia, which mandates the use of machine perfusion preservation if they are to be successfully recovered for transplantation. Because the minimum coronary artery flow needed to meet the basal oxygen demand (DCRIT) of a DCD heart during machine perfusion preservation is critical and yet unknown, we studied this in a DCD rat heart model. Adult male rats were anesthetized, intubated, heparinized, and paralyzed with vecuronium. The DCD hearts (n = 9) were recovered 30 minutes after circulatory death whereas non-DCD control hearts (n = 12) were recovered without circulatory death. Hearts were perfused through the aorta with an oxygenated Belzer Modified Machine Perfusion Solution (A3-Bridge to Life Ltd. Columbia, SC) at 15°C or 22°C starting at a flow index of 300 ml/100 g/min and decreasing by 40 ml/100 g/min every 10 minutes. Inflow (aortic) and outflow (inferior vena cava) perfusate samples were collected serially to assess the myocardial oxygen consumption index (MVO2) and O2 extraction ratio. The DCRIT is the minimum coronary flow below which the MVO2 becomes flow dependent. The MVO2, DCRIT, and oxygen extraction ratios were higher in DCD hearts compared with control hearts. The DCRIT for DCD hearts was achieved only at 15°C and was significantly higher (131.6 ± 7 ml/100 g/min) compared with control hearts (107.7 ± 8.4 ml/100 gm/min). The DCD hearts sustain warm ischemic damage and manifest higher metabolic needs during machine perfusion. Establishing adequate coronary perfusion is critical to preserving organ function for potential heart transplantation.

Prolonged Delayed Renal Graft Function Secondary to Venous Hypertension.

The case of a 39-year-old highly sensitized woman who underwent second renal transplantation after being on warfarin because of a history of frequent thromboses of her left femoral arteriovenous graft (AVG) is reported here. The patient received a flow cytometric positive crossmatch kidney transplant from a deceased donor. Her posttransplant course was complicated by prolonged delayed graft function (DGF) lasting for 9 months. Antibody-mediated rejection occurred in the immediate postoperative period. This resolved after treatment, and resolution was confirmed by repeat biopsy. Despite this, she had persistent DGF and remained dialysis dependent. A computed tomography scan due to the development of perinephric hematoma after posttransplant biopsy demonstrated venous collateralization around the allograft. At 7 months posttransplant, a venogram during declotting of AVG revealed chronic thrombus in the inferior vena cava (IVC) above the level of native renal veins with a venous gradient of 26 mmHg. After declotting of the graft, iliac venoplasty, and subsequent IVC stent, her renal function continues to improve with a most recent creatinine of 1.4 mg/dL at 36 months posttransplant. Venous hypertension secondary to IVC thrombosis in presence of patent femoral AVG should be considered as a rare cause of prolonged DGF.

Restoration of immune surface molecules in Kaposi sarcoma-associated herpes virus infected cells by lenalidomide and pomalidomide.

Kaposi sarcoma-associated herpesvirus (KSHV) is the cause of several tumors, including Kaposi sarcoma and primary effusion lymphoma (PEL). Most viruses have evolved means of escaping immune recognition. KSHV downregulates MHC-I expression during lytic infection, and expression of ICAM-1 and B7-2 (CD86) during latent infection, allowing evasion of T cell and natural killer immunity respectively. These effects are largely mediated by two KSHV-encoded proteins, K3 and K5. We show here that lenalidomide (Len) and pomalidomide (Pom) prevent down-regulation of MHC-I during lytic activation, and restore ICAM-1 and B7-2 surface expression in latently infected PEL cells. Importantly, these changes occurred at clinically achievable concentrations and prior to any cytotoxic effects. Exploration of the mechanism revealed that Pom blocked lytic down-regulation of MHC-I induced by transfection with K3 but not K5. Although Pom alone did not significantly increase HLA mRNA expression in PEL cells, it did blunt the butyrate-induced decrease in MHC-I mRNA expression and decreased the upregulation of K3 mRNA in lytic cells. Virus-induced tumors express foreign antigens, but immunotherapy can be thwarted by viral strategies to evade immune recognition. The effects of Pom and Len described here can prevent these strategies and support the use of these drugs to treat KSHV-induced tumors.

Tacrolimus-Induced Type IV Renal Tubular Acidosis following Liver Transplantation.

Calcineurin inhibitors remain an integral component of immunosuppressive therapy regimens following solid organ transplantation. Although nephrotoxicity associated with these agents is well documented, type IV renal tubular acidosis is a rare and potentially underreported complication following liver transplantation. Hepatologists must be able to recognize this adverse effect as it can lead to fatal hyperkalemia. We describe a case of tacrolimus-induced hyperkalemic type IV renal tubular acidosis in a patient following an orthotopic liver transplant for alcoholic cirrhosis.