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In the present study, genetic screening of Sahiwal and Holstein Friesian (HF) cattle and its crosses was conducted using the PCR-RFLP technique to detect the presence of CVM and DUMPS disorders. Genomic DNA was extracted from 50 Sahiwal and 100 HF animals and its crosses using commercially available kits. Gene-specific primers were utilized for in vitro amplification of SLC35A3 and UMPS genes by PCR, followed by RFLP analysis using PstI and AvaI restriction endonucleases for CVM and DUMPS, respectively. Subsequently, the PCR products were purified and sequenced to confirm any mutations in the DNA target sequences. Notably, no affected or carrier animals for CVM and DUMPS disorders were identified among the screened animals. Thus, the gene and genotype frequency of CVM and DUMPS carriers was zero, indicating a 100% frequency of normal animals. The study underscores the importance of continued screening for these genetic disorders, involving a larger sample size across the state, and advocates for mandatory screening before utilizing animals for breeding purposes, in adherence to minimum standard protocols.

Good quality of single droplet image acquisition in imaging flow cytometry (IFC) is crucial for a wide range of biological analyses. Recently, there have been significant advances in droplet microfluidic data analysis; however, acquiring blur-free single object images is still a great challenge because of the tradeoff between high flow rate and hardware setup complexity and cost. State-of-the-art hardware setups for blur-free single image acquisition are often complex, cumbersome, and not portable, limiting their suitability for point-of-care diagnostics. Moreover, motion blur and duplicate droplet image acquisition can occur with flow rate variation. To address these issues, this paper proposes a lightweight imaging pipeline for acquiring blur-free single droplet images for portable applications; this pipeline is capable of acquiring every single droplet image. While most of the existing literature focuses on complex hardware setups, utilizing high frame rate cameras that are not cost effective and complex optical solutions for droplet focusing, our pipeline utilizes minimum hardware and a lightweight algorithm for detecting, counting, and acquiring single object images from the video stream. The proposed pipeline was evaluated experimentally using videos of fast-moving droplets in which the input fluid flow rate was as high as $67.7~\mu $ L/min. The proposed pipeline achieves 100% counting accuracy on the tested videos and 2 ms, 25 ms and 10 ms processing time for each droplet on a desktop PC, single-board computer Raspberry Pi-4, and Nvidia Jetson Nano, respectively. This yields a maximum of 500, 40, and 100 blur free detected droplets per second (DPS), respectively. The Jetson Nano implementation, achieving 100 DPS with processing time of 10 ms, is faster than existing similar studies and fast enough for the target application. The results suggest that the proposed lightweight pipeline is suitable for efficient single object image acquisition in IFC on an embedded portable platform.

Droplet microfluidics enables studying large cell populations in chemical isolation, at a single-cell resolution. Applications include studying cellular response to drugs, cell-to-cell interaction studies. Such applications need a reliable and repeatable droplet generation with high monodispersity. Most systems used in research rely on manual tuning of flow parameters on off-the-shelf instruments. Setups are highly customized, limiting reproduction of experimental results. We propose an integrated, modular system for automated aqueous droplet generation with high monodispersity. The system provides dynamic feedback control of droplet size and input pressure. Input pressure is generated by two piezoelectric micropumps. Droplet sizes are determined via light intensity measurement in an LED-photodiode setup. The system is capable of wireless communication and has a low enough power consumption for battery-powered operation. We report on the assembly and the underlying working principle, as well as an in-depth experimental evaluation of the performance of the proof-of-concept prototype in aqueous droplet generation. Evaluation was performed on a modular as well as on a system level. During module-level evaluations, aqueous droplets were generated in a light mineral oil + Span 80 surfactant carrier medium, using 3 different flow-focusing junction geometries. The presented prototype had a significantly faster pressure stabilization time (10 s) compared to a syringe pump-based reference setup (120 s). During system-level evaluation, deionized water droplets were generated in a carrier medium of HFE7500 + PEG-PFPE triblock surfactant. Resultant droplet sizes were benchmarked with microscopy. The system was able to repeatedly generate mono- and polydisperse droplets on demand, with CVs between 5-10% in the $\sim $ 50- $200 \mu \text{m}$ droplet diameter range.