Differential gene expression based on RNA-seq is widely used.Bioinformatics skills are required since no algorithm is appropriate for all experimental designs.Moreover, when working with organisms without reference genome, functional analysis is less than straightforward in most situations. DEgenes Hunter, an attempt to automate the process, is based on two independent scripts, one for differential expression and one for functional interpretation. Based on replicates, the R script decides which of the edgeR, DEseq2, NOISeq and limma algorithms are appropriate. It performs quality control calculations and provides the prevalent, most reliable, set of differentially expressed genes, and lists all other possible candidates for further functional interpretation. It also provides a combined P-value that allows differentially expressed genes ranking. It has been tested with synthetic and real-world datasets, showing in both cases ease of use and reliable results. With real data, DEgenes Hunter offers straightforward functional interpretation.

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The paper proposes a new design of a scalable, heat sink containing 3-D micro/nano network, utilizing liquid mixed with nano phase change materials (NPCM) and having a high surface-to-volume ratio geometry. The conceptual design is capable of reaching 105 W/cm3 using encapsulated nano-size phase change materials, which would result in an order of magnitude higher cooling capacity than typical microchannel heat sink of the same volume and same pumping power. It is also scalable to submicron range, resulting even higher cooling capacity. An analysis for a working model (10 × 10 × 1 mm) is presented utilizing energy conservation principle and uniform temperature and uniform heat flux boundary conditions. The average phase change heat transfer coefficient is obtained using the numerical model results. A process of micro electrochemical deposition to fabricate the target model is illustrated, and the issues associated with system-level applications are discussed.

Lung cancer (LC) is the most common cause of cancer death worldwide mostly due to the low survival rate: 75% of cases are identified in advanced stages. In this study, the list of useful biomarkers to make an early diagnosis using liquid biopsies was expanded. A total of 30 samples of LC were analyzed to define potential miRNA biomarkers in liquid biopsies for LC. The biomarkers have been identified in interaction networks miRNA–mRNA. The potential biomarkers have been then validated in large cohorts. A total of 15 candidate miRNAs, that regulate the repression of 30 mRNAs, have been identified as a specific functional interaction network for squamous carcinoma, while the specific functional interaction network of adenocarcinoma consists of four candidate miRNAs that seem to handle the repression of five mRNA. Inspection of expression levels in larger cohorts validates the usefulness of the 11 candidates as biomarkers in liquid biopsies. The 11 candidate miRNAs found could be utilized to form diagnostic predictive biomarkers for LC in liquid biopsies.

In this paper recent works from the areas of entropy generation minimization and constructal theory are extended and combined with previous works from the area of physiological transport geometry prediction. From this a design methodology is developed which can be applied to branching fluid networks having the objective of maximizing the removal of heat from a given volume while minimizing the pumping power required. The methods are essentially a set of equations that serve as a resource for designers incorporating branching fluid networks as components within fluid-thermal systems that have the goal of transferring and remove heat while minimizing the entropy generation or destruction of available work.