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Temperature control is crucial for live cell imaging, particularly in studies involving plant responses to high ambient temperatures and thermal stress. This study presents the design, development, and testing of two cost-effective heating devices tailored for confocal microscopy applications: an aluminum heat plate and a wireless mini-heater. The aluminum heat plate, engineered to integrate seamlessly with the standard 160 mm × 110 mm microscope stage, supports temperatures up to 36°C, suitable for studies in the range of non-stressful warm temperatures (e.g., 25-27°C forArabidopsis thaliana) and moderate heat stress (e.g., 30-36°C forA. thaliana). We also developed a wireless mini-heater that offers rapid, precise heating directly at the sample slide, with a temperature increase rate over 30 times faster than the heat plate. The wireless heater effectively maintained target temperatures up to 50°C, ideal for investigating severe heat stress and heat shock responses in plants. Both devices performed well in controlled studies, including the real-time analysis of heat shock protein accumulation and stress granule formation inA. thaliana. Our designs are effective and affordable, with total construction costs lower than $300. This accessibility makes them particularly valuable for small laboratories with limited funding. Future improvements could include enhanced heat uniformity, humidity control to mitigate evaporation, and more robust thermal management to minimize focus drift during extended imaging sessions. These modifications would further solidify the utility of our heating devices in live cell imaging, offering researchers reliable, budget-friendly tools for exploring plant thermal biology. 

In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes. 

Sleep is a fundamental feature of life for virtually all multicellular animals, but many questions remain about how sleep is regulated and what biological functions it plays. Substantial headway has been made in the study of both circadian rhythms and sleep in the fruit flyDrosophila melanogaster, much of it through studies of individual fly activity using beam break counts fromDrosophilaactivity monitors (DAMs). The number of laboratories worldwide studying sleep inDrosophilahas grown from only a few 20 years ago to hundreds today. The utility of these studies is limited by the quality of the metrics that can be extracted from the data. Many software options exist to help analyze DAM data; however, these are often expensive or have significant limitations. Therefore, we describe here a method for analyzing DAM-based data using the sleep and circadian analysis MATLAB program (SCAMP). This user-friendly software has an advantage of combining several analyses of both sleep and circadian rhythms in one package and produces graphical outputs as well as spreadsheets of the outputs for further statistical analysis. The version of SCAMP described here is also the first published software package that can analyze data from multibeam DAM5Ms, enabling determination of positional preference over time. 

This study employs supervised machine learning algorithms to test whether locomotive features during exploratory activity in open field arenas can serve as predictors for the genotype of fruit flies. Because of the nonlinearity in locomotive trajectories, traditional statistical methods that are used to compare exploratory activity between genotypes of fruit flies may not reveal all insights. 10-minute-long trajectories of four different genotypes of fruit flies in an open-field arena environment were captured. Turn angles and step size features extracted from the trajectories were used for training supervised learning models to predict the genotype of the fruit flies. Using the first five minute locomotive trajectories, an accuracy of 83% was achieved in differentiating wild-type flies from three other mutant genotypes. Using the final 5 min and the entire ten minute duration decreased the performance indicating that the most variations between the genotypes in their exploratory activity are exhibited in the first few minutes. Feature importance analysis revealed that turn angle is a better predictor than step size in predicting fruit fly genotype. Overall, this study demonstrates that features of trajectories can be used to predict the genotype of fruit flies through supervised machine learning methods. 

Abstract Delivering cargo to the central nervous system (CNS) remains a pharmacological challenge. For infectious diseases such as HIV, the CNS acts as a latent reservoir that is inadequately managed by systemic antiretrovirals (ARTs). ARTs thus cannot eradicate HIV, and given CNS infection, patients experience neurological deficits collectively referred to as “neuroHIV”. Herein, the development of bioinspired ionic liquid‐coated nanoparticles (IL‐NPs) for in situ hitchhiking on red blood cells (RBCs) is reported, which enables 48% brain delivery of intracarotid arterial‐ infused cargo. Moreover, IL choline trans‐2‐hexenoate (CA2HA 1:2) demonstrates preferential accumulation in parenchymal microglia over endothelial cells post‐delivery. This study further demonstrates successful loading of abacavir (ABC), an ART that is challenging to encapsulate, into IL‐NPs, and verifies retention of antiviral efficacy in vitro. IL‐NPs are not cytotoxic to primary human peripheral blood mononuclear cells (PBMCs) and the CA2HA 1:2 coating itself confers notable anti‐viremic capacity. In addition, in vitro cell culture assays show markedly increased uptake of IL‐NPs into neural cells compared to bare PLGA nanoparticles. This work debuts bioinspired ionic liquids as promising nanoparticle coatings to assist CNS biodistribution and has the potential to revolutionize the delivery of cargos (i.e., drugs, viral vectors) through compartmental barriers such as the blood‐brain‐barrier (BBB).