White River Technologies (United States)

In this study, we introduce an innovative Fusion-Based Deep Learning Network (FusionDLNet) architecture designed specifically for detecting diseases in citrus plants. This network utilizes two parallel convolutional pathways, each featuring different kernel sizes to enhance feature extraction. The first pathway uses 3×3 convolutional filters, while the second uses 5×5 filters, allowing the model to capture both detailed and broader spatial features. Before putting images into the model, they undergo several pre-processing steps including rescaling, and normalization. These techniques aim to boost the generalization capabilities of the model. Subsequently, features extracted from both pathways are merged and directed through a fully connected layer that uses a softmax activation function for classification. The FusionDLNet model has been evaluated on citrus datasets and Sweet Orange leaf datasets and has shown superior performance against ResNet-50, VGG16, and VGG19. It reflects approximately 21%, 18%, and 23% improvement in accuracy metrics on Citrus leaves dataset and 17%, 13%, and 10% improvement in accuracy metrics on the Sweet Orange leaf dataset. The comparative results showcase the validity of the proposed architecture towards improving representation and classification of features for detecting diseases in plants. This proposed model presents a valuable tool for smart agricultural practices by facilitating identification of diseases that can lead to improved crop management and improved yield optimization

Acute leukemia, particularly AML, is closely associated with thrombotic events, driven by complex factors like coagulation system changes, endothelial dysfunction, and leukemic cell interactions with the vascular system. Certain chemotherapy drugs can exacerbate the prothrombotic state. Understanding these dynamics is crucial for effective thromboprophylaxis in carefully selected patients with leukemia. Thrombosis is a significant complication of acute leukemia. Thrombotic events mostly occur at diagnosis or during induction therapy. Here we report the occurrence of myocardial infarction (MI) before initiation of therapy, in a patient with acute myeloid leukemia not otherwise specified (AML NOS) who had no other significant risk factors for coronary artery disease. The occurrence of MI in this patient limited the choice of induction therapy and resulted in mortality. We discuss the pathogenesis and risk factors associated with increased thrombosis in AML and advocate for risk-adapted thromboprophylaxis in this patient population.

While dietary supplements are generally “safe,” they must be appropriately consumed as they have different regulatory standards than traditional pharmaceutical medications and require oversight to ensure that a good thing does not become harmful.

We present development, testing, and deployment of a next generation advanced EMI sensor from a cart-based sensing platform to combine the mapping capability of previous digital geophysical survey instruments with the high-resolution discrimination capability of advanced characterization arrays. The intended end users of the system are non-technical field personnel. Therefore, system development, including sensor operation, data acquisition, and post-processing methods were customized for ease-of-use and robust automated discrimination. The EMI sensor employs a multi-axis receiver configuration to produce data sufficient for anomaly discrimination. Platform development and design focused on navigation and EMI sensor integration onto a custom, low-noise, metal-free platform. Data acquisition is via an Android application with emphasis on ease-of-use and real-time quality control (QC) of collected data. Post-processing methods emphasize QC, inversion-based anomaly location estimation, and automated or supervised polarizability-based discrimination methods to produce a prioritized dig list. Streamlining of the detection, clutter rejection and QC methods into the post-processing software module reduces analysis complexity and the time required between sensor data collection and generation of a prioritized dig list. System concept of operations (CONOPs), data collection, QC, and data processing procedures, will be discussed. System performance versus standard digital geophysical mapping sensors in production OCONUS UXO remediation operations will also be discussed.

We present results from recent efforts to develop a dynamic electromagnetic induction sensor qualified by the DoD Advanced Geophysical Classification Accreditation Program (DAGCAP) for use on munitions response projects. During the last 10 years we have developed several advanced terrestrial and marine sensors capable of providing effective classification of UXO during dynamic (i.e., mapping) surveys. Most recently, we have implemented a sensor form factor and electronics design that is optimized to produce classification quality data during digital geophysical mapping surveys at terrestrial sites. We discuss sensor validation requirements, quality control procedures, sensor performance, and concept of operations for implementation of the system in munitions response projects.

Pancytopenia is a decrease across cellular hematological lines. Many different etiologies can cause this clinical picture including viral and bacterial infections, chemicals, malignancy, and medications. Particular attention should be paid to the onset, timing, and severity as they can indicate the underlying cause. In cases of iatrogenic-induced pancytopenia, the offending agent should be stopped immediately and the patient should be monitored for recovery of cell lines. While not well reported in the literature, trimethoprim–sulfamethoxazole (TMP-SMX) is a cause of pancytopenia. We present a case of drug-induced pancytopenia secondary to TMP-SMX that resolved quickly with cessation of use.

A 43-year-old female patient presented with large bilateral pulmonary emboli. During patient’s stay, a fleeting episodes of bradycardia and hypotension with drop in systolic pressure over 40mmHg on slight movements were noted.Being in a rural hospital, patient was transferred in which following that she was pronounced dead relating her presentation.

Background and objective: E6 and E7 proteins in human papillomavirus (HPV) 16 are major oncogenes in several types of tumors, including lung cancer. Previous studies have demonstrated that both E6 and E7 oncoproteins can upregulate GLUT1 protein and mRNA expression levels in lung cancer cells. Thus, the present study aimed to investigate the main differences in the molecular mechanisms of GLUT1 expression regulated by E6 and E7. Methods: The double directional genetic manipulation and immunofluorescence were performed to explore the molecular mechanism of E6 or E7 upregulating the expression of GLUT1 in H1299 and A549 cell lines. Results: The overexpression of E6 in well-established lung cancer cell lines upregulated thioredoxin (Trx) protein expression. Notably, plasmid transfection or small interfering RNA transfection with E7 had no regulatory effect on Trx expression. As an important disulfide reductase of the intracellular antioxidant system, Trx plays important role in maintaining oxidative stress balance and protecting cells from oxidative damage. The overexpression of Trx increased the activation of NF-κB by upregulating p65 expression and promoting p65 nuclear translocation, and further upregulated GLUT1 protein and mRNA expression levels. The results of the present study demonstrated that E6, but not E7, upregulated GLUT1 expression in lung cancer cells by activating NF-κB due to the participation of Trx. Conclusion: These results suggest that Trx plays an important role in the pathogenesis of HPV-associated lung cancer, and propose a novel therapeutic target for HPV-associated lung cancer.