Effects of Temperature and Host Plant on Hedgehog Grain Aphid, Demographics.

The hedgehog grain aphid (HGA), Passerini (Hemiptera: Aphididae), is a cereal pest in many regions of the world. It was first documented in the United States in 2007, and it has a range that appears to be expanding. Understanding the effects of temperature and the host plant on HGA development, survival, and reproduction is crucial for understanding its population dynamics, potential distribution, and management strategies.

A Novel Machine Learning Model for Predicting Orthodontic Treatment Duration.

In the field of orthodontics, providing patients with accurate treatment time estimates is of utmost importance. As orthodontic practices continue to evolve and embrace new advancements, incorporating machine learning (ML) methods becomes increasingly valuable in improving orthodontic diagnosis and treatment planning. This study aimed to develop a novel ML model capable of predicting the orthodontic treatment duration based on essential pre-treatment variables.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity.

A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population.

Introduction: The purpose of the present study was to create a machine learning (ML) algorithm with the ability to predict the extraction/non-extraction decision in a racially and ethnically diverse sample.

Methods: Data was gathered from the records of 393 patients (200 non-extraction and 193 extraction) from a racially and ethnically diverse population. Four ML models (logistic regression [LR], random forest [RF], support vector machine [SVM], and neural network [NN]) were trained on a training set (70% of samples) and then tested on the remaining samples (30%).

Can we predict orthodontic extraction patterns by using machine learning?

Objective: To investigate the utility of machine learning (ML) in accurately predicting orthodontic extraction patterns in a heterogeneous population.

Materials And Methods: The material of this retrospective study consisted of records of 366 patients treated with orthodontic extractions. The dataset was randomly split into training (70%) and test sets (30%) and was stratified according to race/ethnicity and gender.

A large-scale genetic screen identifies genes essential for motility in Agrobacterium fabrum.

The genetic and molecular basis of flagellar motility has been investigated for several decades, with innovative research strategies propelling advances at a steady pace. Furthermore, as the phenomenon is examined in diverse bacteria, new taxon-specific regulatory and structural features are being elucidated. Motility is also a straightforward bacterial phenotype that can allow undergraduate researchers to explore the palette of molecular genetic tools available to microbiologists.

Online Tools for Teaching Cancer Bioinformatics.

The rise of deep molecular characterization with omics data as a standard in biological sciences has highlighted a need for expanded instruction in bioinformatics curricula. Many large biology data sets are publicly available and offer an incredible opportunity for educators to help students explore biological phenomena with computational tools, including data manipulation, visualization, and statistical assessment. However, logistical barriers to data access and integration often complicate their use in undergraduate education.

Directional biases in whole hand motion perception revealed by mid-air tactile stimulation.

Many emerging technologies are attempting to leverage the tactile domain to convey complex spatiotemporal information translated directly from the visual domain, such as shape and motion. Despite the intuitive appeal of touch for communication, we do not know to what extent the hand can substitute for the retina in this way. Here we ask whether the tactile system can be used to perceive complex whole hand motion stimuli, and whether it exhibits the same kind of established perceptual biases as reported in the visual domain.