An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images.

The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classification and tumor localization in histopathological image analysis.

Empowering coffee farming using counterfactual recommendation based RNN driven IoT integrated soil quality command system.

Soil health is essential for whirling stale soil into rich coffee-growing land. By keeping healthy soil, coffee producers may improve plant growth, leaf health, buds, cherry and bean quality, and yield. Traditional soil monitoring is tedious, time-consuming, and error-prone.

Archimedes optimisation algorithm quantum dilated convolutional neural network for road extraction in remote sensing images.

Roads are closely intertwined with human existence, and the process of extracting road networks has emerged as the most prominent task in remote sensing (RS). The automated road interpretation process of remote sensing images (RSI) efficiently acquires road network data at a reduced expense in comparison to the traditional visual interpretation of RSI. However the manifestation of RSI is completely distinct because of the great difference in length, width, material, and shape of road networks in dissimilar areas.

Dipper throated optimization with deep convolutional neural network-based crop classification for remote sensing image analysis.

Problem: With the rapid advancement of remote sensing technology is that the need for efficient and accurate crop classification methods has become increasingly important. This is due to the ever-growing demand for food security and environmental monitoring. Traditional crop classification methods have limitations in terms of accuracy and scalability, especially when dealing with large datasets of high-resolution remote sensing images.

Computational linguistics based text emotion analysis using enhanced beetle antenna search with deep learning during COVID-19 pandemic.

Computational intelligence and nature-inspired computing have changed the way biologically and linguistically driven computing paradigms are made. In the last few decades, they have been used more and more to solve optimisation problems in the real world. Computational linguistics has its roots in linguistics, but most of the studies being done today are led by computer scientists.

Xpert Carba-R Assay on Flagged Blood Culture Samples: Clinical Utility in Intensive Care Unit Patients with Bacteremia Caused by .

Introduction And Background: Rapid molecular diagnostics to predict carbapenem resistance well before the availability of routine drug sensitivity testing (DST) can serve as an antimicrobial stewardship tool in the context of high rates of Carbapenem-resistant (CRE).

Materials And Methods: A retrospective observational study of patients more than 18 years of age on whom Xpert Carba-R (FDA approved for rectal swab specimen) was done on gram-negative bacteria (GNB) flagged blood culture samples, in an Indian intensive care unit between January 2015 and November 2018. We analyzed the performance of Xpert Carba-R in comparison with routine DST.

Application of Pharmacokinetic/Pharmacodynamic Modeling to Bridge Mouse Antitumor Efficacy and Monkey Toxicology Data for Determining the Therapeutic Index of an Interleukin-10 Fc Fusion Protein.

Pharmacokinetic/pharmacodynamic (PK/PD) modeling was performed to quantitatively integrate preclinical pharmacology and toxicology data for determining the therapeutic index (TI) of an interleukin-10 (IL-10) fragment crystallizable (Fc) fusion protein. Mouse Fc fused with mouse IL-10 (mFc-mIL-10) was studied in mice for antitumor efficacy, and the elevation of interleukin-18 (IL-18) was examined as a PD biomarker. The mFc-mIL-10 EC for the IL-18 induction was estimated to be 2.

Target-Mediated Drug Disposition Affects the Pharmacokinetics of Interleukin-10 Fragment Crystallizable Fusion Proteins at Pharmacologically Active Doses.

Fragment crystallizable (Fc) fusion is commonly used for extending the half-life of biotherapeutics such as cytokines. In this work, we studied the pharmacokinetics of Fc-fused interleukin-10 (IL-10) proteins that exhibited potent antitumor activity in mouse syngeneic tumor models. At pharmacologically active doses of ≥0.

MapReduce-based big data classification model using feature subset selection and hyperparameter tuned deep belief network.

In recent times, big data classification has become a hot research topic in various domains, such as healthcare, e-commerce, finance, etc. The inclusion of the feature selection process helps to improve the big data classification process and can be done by the use of metaheuristic optimization algorithms. This study focuses on the design of a big data classification model using chaotic pigeon inspired optimization (CPIO)-based feature selection with an optimal deep belief network (DBN) model.

Quantification of surrogate monoclonal antibodies in mouse serum using LC-MS/MS.

Surrogate monoclonal antibodies (mAbs) used in preclinical studies can be challenging to quantify due to lack of suitable immunoaffinity reagents or unavailability of the mAb protein sequence. Generic immunoaffinity reagents were evaluated to develop sensitive LC-MS/MS assays. Peptides of unknown sequence can be used for selective LC-MS quantification.

Chest radiography in acute aortic syndrome: pearls and pitfalls.

Acute aortic syndrome is a group of life-threatening diseases of the thoracic aorta that usually present to the emergency department. It includes aortic dissection, aortic intramural hematoma, and penetrating aortic ulcer. Rare aortic pathologies of aorto-esophageal fistula and mycotic aneurysm may also be included in this list.

Quantification of human mAbs in mouse tissues using generic affinity enrichment procedures and LC-MS detection.

Background: The disease state can modulate the penetration of large antibody-sized therapeutic molecules into affected tissues. Suitable bioanalytical methods are required for the quantitative analysis of drug tissue levels to enable a better understanding of the parameters influencing drug penetration and target engagement.

Results: Described is a sensitive and selective LC-MS/MS assay for the quantification of human mAb molecules in mouse tissues.

Validation of a ligand binding assay using dried blood spot sampling.

Dried blood spots (DBS) technology has been introduced as a microsampling alternative to traditional plasma or serum sampling for pharmacokinetics or toxicokinetics evaluation. The application of DBS has been established for many small molecule drugs at discovery, nonclinical, and clinical stages. However, the application of DBS for large molecule therapeutics development is not yet well-established.

Rapid affinity measurement of protein-protein interactions in a microfluidic platform.

A rapid screening method has been developed to determine binding affinities for protein-ligand interactions using the Gyrolab workstation, a commercial microfluidic platform developed to accurately and precisely quantify proteins in solution. This method was particularly suited for assessing the high-affinity interactions that have become typical of therapeutic antibody-antigen systems. Five different commercially available antibodies that bind digoxin and a digoxin-bovine serum albumin (BSA) conjugate with high affinity were rigorously evaluated by this method and by the more conventional kinetic exclusion assay (KinExA) method.

Activity of the isolated HIV RNase H domain and specific inhibition by N-hydroxyimides.

This report describes a procedure to generate enzymatically active, isolated HIV RNase H domain. In contrast to previously described preparations, the RNA cleavage activity of the untagged RNase H domain was surprisingly similar to that of the full-length HIV-RT protein. Signature cleavages at 18 and 9 nucleotides downstream of a recessed RNA 5'-end were retained with the isolated RNase H domain.

HIV Rev self-assembly is linked to a molten-globule to compact structural transition.

By regulating the differential expression of proviral pre mRNA in the host cell, Rev plays a crucial role in the HIV-1 life cycle. The capacity of Rev to function is intimately linked to its ability to self-associate. Nevertheless, little is known about the exact role of self-association in the molecular mechanism defining its biological activity.

Two-metal ion mechanism of RNA cleavage by HIV RNase H and mechanism-based design of selective HIV RNase H inhibitors.

Human immunodeficiency virus (HIV) RNase H activity is essential for the synthesis of viral DNA by HIV reverse transcriptase (HIV-RT). RNA cleavage by RNase H requires the presence of divalent metal ions, but the role of metal ions in the mechanism of RNA cleavage has not been resolved. We measured HIV RNase H activity associated with HIV-RT protein in the presence of different concentrations of either Mg2+, Mn2+, Co2+ or a combination of these divalent metal ions.