Models and Biomarkers for Local Response Prediction in Early-Stage and Oligometastatic Non-small Cell Lung Cancer Patients Treated With Stereotactic Body Radiation Therapy Using Machine Learning.

Background A minority of patients receiving stereotactic body radiation therapy (SBRT) for non-small cell lung cancer (NSCLC) are not good responders. Radiomic features can be used to generate predictive algorithms and biomarkers that can determine treatment outcomes and stratify patients to their therapeutic options. This study investigated and attempted to validate the radiomic and clinical features obtained from early-stage and oligometastatic NSCLC patients who underwent SBRT, to predict local response.

miR-92a-3p regulates egg fertilization through ribogenesis in the invasive fall armyworm Spodoptera frugiperda.

Understanding the epigenetic molecular mechanisms (EMMs) of reproduction is crucial for developing advanced and targeted control strategies for Spodoptera frugiperda. Differential expression analysis revealed 11 known miRNAs with varying expression levels, including nine upregulated and two downregulated miRNAs, in virgin females compared with males. The predictive analysis identified 426 target genes for these miRNAs, with ribogenesis highlighted as a key process in oogenesis and egg fertilization.

Intrusion detection system for V2X communication in VANET networks using machine learning-based cryptographic protocols.

Vehicle-to-everything (V2X) communication has many benefits. It improves fuel efficiency, road safety, and traffic management. But it raises privacy and security concerns.

Radiomics As Biomarkers for the Treatment of Non-small Cell Lung Cancer With Stereotactic Body Radiation Therapy: A Review of Concepts.

Stereotactic body radiation therapy (SBRT) is currently the alternative for inoperable early-stage and oligometastatic non-small cell lung cancer (NSCLC) patients. While most patients are good responders among this specific group, some patients do not experience the benefits of this treatment. Even though physicians use clinical variables and semantic radiological features to make treatment decisions, medical images contain a wealth of personalized pathophysiological information that can be extracted and used for clinical decision support systems.

Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature.

With the advent of artificial intelligence (AI), it is now possible to design diverse and novel molecules from previously unexplored chemical space. However, a challenge for chemists is the synthesis of such molecules. Recently, there have been attempts to develop AI models for retrosynthesis prediction, which rely on the availability of a high-quality training dataset.

Self-supervised learning for chest computed tomography: training strategies and effect on downstream applications.

Purpose: Self-supervised pre-training can reduce the amount of labeled training data needed by pre-learning fundamental visual characteristics of the medical imaging data. We investigate several self-supervised training strategies for chest computed tomography exams and their effects on downstream applications.

Approach: We benchmark five well-known self-supervision strategies (masked image region prediction, next slice prediction, rotation prediction, flip prediction, and denoising) on 15 M chest computed tomography (CT) slices collected from four sites of the Mayo Clinic enterprise, United States.

Gene expression changes in Maconellicoccus hirsutus in response to sublethal dose of buprofezin.

The pink or hibiscus mealybug, Maconellicoccus hirsutus, is a serious pest of grapes, jute, and mesta, causing severe yield losses in India and other countries. Chemical control remains the foremost choice for farmers to manage this pest. As insecticides break down over time due to biotic and abiotic factors, insects are exposed to varying levels of these exogenous compounds.

Transcriptome mining and expression analysis of ABC transporter genes in a monophagous herbivore, Leucinodes orbonalis (Crambidae: Lepidoptera).

Insecticide resistance is a global concern and requires immediate attention to manage dreadful insect pests. One of the resistance mechanisms adopted by insects is through ATP-binding cassette (ABC) transporter proteins. These proteins rapidly transport and eliminate the insecticidal molecules across the lipid membranes (Phase III detoxification mechanism).

Identification and expression dynamics of CYPome across different developmental stages of Maconellicoccus hirsutus (Green).

Maconellicoccus hirsutus is a highly polyphagous insect pest, posing a substantial threat to various crop sp., especially in the tropical and sub-tropical regions of the world. While extensive physiological and biological studies have been conducted on this pest, the lack of genetic information has hindered our understanding of the molecular mechanisms underlying its growth, development, and xenobiotic metabolism.

Role of inflammation in a rat model of radiation retinopathy.

Radiation retinopathy (RR) is a major side effect of ocular tumor treatment by plaque brachytherapy or proton beam therapy. RR manifests as delayed and progressive microvasculopathy, ischemia and macular edema, ultimately leading to vision loss, neovascular glaucoma, and, in extreme cases, secondary enucleation. Intravitreal anti-VEGF agents, steroids and laser photocoagulation have limited effects on RR.

Thoracic Proton Minibeam Radiation Therapy: Tissue Preservation and Survival Advantage Over Conventional Proton Therapy.

Purpose: Proton minibeam radiation therapy (pMBRT) is an innovative radiation therapy approach that highly modulates the spatial dimension of the dose delivery using narrow, parallel, and submillimetric proton beamlets. pMBRT has proven its remarkable healthy tissue preservation in the brain and skin. This study assesses the potential advantages of pMBRT for thoracic irradiations compared with conventional radiation therapy in terms of normal tissue toxicity.

Accurate, Robust, and Scalable Machine Abstraction of Mayo Endoscopic Subscores From Colonoscopy Reports.

Background: The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in routine clinical care usually characterize ulcerative colitis disease activity using free text description, limiting their utility for clinical research and quality improvement. We sought to develop algorithms to classify colonoscopy reports according to their MES.

Multisystem inflammatory syndrome in children characterized by enhanced antigen-specific T-cell expression of cytokines and its reversal following recovery.

Background: Multisystem inflammatory syndrome (MIS) in children is considered to be a post-infectious complication of COVID-19. T-cell responses in children with this condition have not been well-studied.

Methods: We aimed to study the immune responses in children with MIS in comparison to children with acute COVID-19 and children with other infections.

Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability.

Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness.

Efficacy of Siddha Therapeutics on Mantha Sanni (Autism Spectrum Disorder) Among Pediatric Patients: An Interventional Non-randomized Open-Label Clinical Trial.

Background: Autism Spectrum Disorder (ASD) refers to a collection of neurodevelopmental disorders that affect brain development and can lead to various psychological imbalances in caregivers of affected children. Siddha formulations have been shown to have a role beyond the physical body and play a significant role in managing or ASD. The objective of this study was to examine the impacts of in the pediatric population diagnosed with ASD.

Exploring bixin from L. seeds: quantification and insights into its anti-cancer potential.

Bixin, the key pigment of L., is an apo-carotenoid found in the seed arils. The present study aimed to quantitatively determine the bixin content of seeds and explore its anti-cancer activity through studies.

Evolution of Breast Cancer Recurrence Risk Prediction: A Systematic Review of Statistical and Machine Learning-Based Models.

Purpose: Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been developed using retrospective clinical data and have evolved significantly over the years in terms of predictors of recurrence, data usage, and predictive techniques (statistical/machine learning [ML]).

Methods: Following PRISMA guidelines, we performed a systematic literature review of the aforementioned statistical and ML models published between January 2008 and December 2022 through searching five digital databases-PubMed, ScienceDirect, Scopus, Cochrane, and Web of Science.

Altering Stomatal Density for Manipulating Transpiration and Photosynthetic Traits in Rice through CRISPR/Cas9 Mutagenesis.

Stomata regulates conductance, transpiration and photosynthetic traits in plants. Increased stomatal density may contribute to enhanced water loss and thereby help improve the transpirational cooling process and mitigate the high temperature-induced yield losses. However, genetic manipulation of stomatal traits through conventional breeding still remains a challenge due to problems involved in phenotyping and the lack of suitable genetic materials.

Targeting bone cancer with 4-Allylbenzene-1,2-diol purified from L.: an and cytotoxicity scrutiny.

L., a well-known medicinal plant with rich source of bioactive compounds, is widely used in several therapeutics. The present study was performed to scrutinize the anti-cancer potential of compounds petiole by means of studies, purification of 4-Allylbenzene-1,2-diol from petioles and assessing its cytotoxicity on bone cancer metastasis.

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data.

An increasingly large dataset of pharmaceutics disciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy.

Reference genes selection for expression studies in Maconellicoccus hirsutus (Green) (Pseudococcidae: Hemiptera) under specific experimental conditions.

Background: Maconellicoccus hirsutus is a destructive pest which causes severe losses of agricultural and horticultural crops. For the management of M. hirsutus, many insecticides have been used and it has been exposed to insufficient dosage or uneven spray coverage which resulted in the development of insecticide resistance.

Comparative Transcriptome Analysis to Reveal Differentially Expressed Cytochrome P450 in Response to Imidacloprid in the Aphid Lion, (Esben-Petersen).

The aphid lion, (Neuroptera: Chrysopidae) is a highly effective beneficial predator of many agricultural pests and has developed resistance to several insecticides. Understanding the molecular mechanism of insecticide resistance in the predators is crucial for its effective application in IPM programs. Therefore, transcriptomes of imidacloprid-resistant and susceptible strains have been assessed using RNA-seq.

Whole genome sequencing of ASD 16 and ADT 43 to identify predominant grain size and starch associated alleles in rice.

Background: The rice cultivars ASD 16 and ADT 43 are the most popular high-yielding Indica rice cultivars in southern India. Despite their popularity very little is known about their genetic basis due to lack of studies on the complete genome. In the current study, efforts were made to identify alleles and SNP markers that differentiate the two contrasting rice genotypes, ASD 16 and ADT 43 for grain shape and starch content.

Evaluation of the Role of the Immune System Response After Minibeam Radiation Therapy.

Purpose: Minibeam radiation therapy (MBRT) is an innovative technique that uses a spatial dose modulation. The dose distribution consists of high doses (peaks) in the path of the minibeam and low doses (valleys). The underlying biological mechanism associated with MBRT efficacy remains currently unclear and thus we investigated the potential role of the immune system after treatment with MBRT.

Enhanced Severe Acute Respiratory Syndrome Coronavirus 2 Antigen-Specific Systemic Immune Responses in Multisystem Inflammatory Syndrome in Children and Reversal After Recovery.

Background: Multisystem inflammatory syndrome in children (MIS-C) presents with inflammation and pathology of multiple organs in the pediatric population in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Methods: We characterized the SARS-CoV-2 antigen-specific cytokine and chemokine responses in children with MIS-C, coronavirus disease 2019 (COVID-19), and other infectious diseases.

Results: MIS-C is characterized by elevated levels of type 1 (interferon-γ, interleukin [IL] 2), type 2 (IL-4, IL-13), type 17 (IL-17), and other proinflammatory cytokines (IL-1α, IL-6, IL-12p70, IL-18, and granulocyte-macrophage colony-stimulating factor) in comparison to COVID-19 and other infectious diseases following stimulation with SARS-CoV-2-specific antigens.