Differential Uptake of Murine and Human Exosomes by Normal and Inflamed Peripheral Tissues and Brain

Background: Exosomes function as an intercellular communication system conveying messages from donor to target cells in nearby or distant tissues. Many aspects of exosome trafficking remain unresolved, however. Here, we investigated uptake of ten radiolabeled murine or human exosomes of various cellular origins by the liver, kidney, spleen, and lung of male CD-1 mice. Methods: We radioactively labeled 10 exosomes from mouse or human cancerous or non-cancerous lines, injected them intravenously into male CD-1 mice, and studied their tissue uptake. We examined the ability of wheatgerm agglutinin (WGA), mannose-6 phosphate (M6P), and inflammation induced by lipopolysaccharide (LPS) to modulate uptake. We measured uptake rate using multiple-time regression analysis and used heat mapping and path analysis to correlate tissue and exosomal influences on uptake. Results: Except for the uptake of SCCVII exosomes by kidney, all exosomes were taken up by all tissues, although the uptake levels varied broadly among exosomes and tissues. The liver/serum uptake ratio for exosomes from primary human T-cells was the highest at 4,500 mL/g. Species of origin (mouse vs human) or source (cancerous vs noncancerous cells) did not influence tissue uptake. The uptake of some exosomes was altered by WGA and LPS but not by M6P, except for uptake inhibition of J774A.1 exosomes by liver, suggesting use of the M6P receptor. WGA or LPS treatments enhanced uptake of exosomes by brain and lung but inhibited uptake by liver and spleen. Response to LPS was not, however, predictive of response to WGA. No evidence for a universal binding site controlling exosome uptake was obtained. Applying path analysis and heat map analysis to the data, including our published results for brain, we found that exosome uptake patterns for lung and brain responded similarly to WGA or to LPS, whereas those for liver and spleen clustered together. In path analysis, the 10 exosomes clustered into distinct groups, suggesting that their bindings sites are similarly clustered. Conclusions: Uptake of exosomes by peripheral tissues is differentially regulated by both exosomes and target tissues and is dependent on the number and types of mutually interactive binding sites.

Beyond the In-Practice CBC: The Research CBC Parameters-Driven Machine Learning Predictive Modeling for Early Differentiation among Leukemias

A targeted and timely treatment can be a beneficial tool for patients with hematological emergencies (particularly acute leukemias). The key challenges in the early diagnosis of leukemias and related hematological disorders are their symptom-sharing nature and prolonged turnaround time as well as the expertise needed in reporting confirmatory tests. The present study made use of the potential morphological and immature fraction-related parameters (research items or cell population data) generated during complete blood cell count (CBC), through artificial intelligence (AI)/machine learning (ML) predictive modeling for early (at the pre-microscopic level) differentiation of various types of leukemias: acute from chronic as well as myeloid from lymphoid. The routine CBC parameters along with research CBC items from a hematology analyzer in the diagnosis of 1577 study subjects with hematological neoplasms were collected. The statistical and data visualization tools, including heat-map and principal component analysis (PCA,) helped in the evaluation of the predictive capacity of research CBC items. Next, research CBC parameter-driven artificial neural network (ANN) predictive modeling was developed to use the hidden trend (disease’s signature) by increasing the auguring accuracy of these potential morphometric parameters in differentiation of leukemias. The classical statistics for routine and research CBC parameters showed that as a whole, all study items are significantly deviated among various types of leukemias (study groups). The CPD parameter-driven heat-map gave clustering (separation) of myeloid from lymphoid leukemias, followed by the segregation (nodding) of the acute from the chronic class of that particular lineage. Furthermore, acute promyelocytic leukemia (APML) was also well individuated from other types of acute myeloid leukemia (AML). The PCA plot guided by research CBC items at notable variance vindicated the aforementioned findings of the CPD-driven heat-map. Through training of ANN predictive modeling, the CPD parameters successfully differentiate the chronic myeloid leukemia (CML), AML, APML, acute lymphoid leukemia (ALL), chronic lymphoid leukemia (CLL), and other related hematological neoplasms with AUC values of 0.937, 0.905, 0.805, 0.829, 0.870, and 0.789, respectively, at an agreeably significant (10.6%) false prediction rate. Overall practical results of using our ANN model were found quite satisfactory with values of 83.1% and 89.4.7% for training and testing datasets, respectively. We proposed that research CBC parameters could potentially be used for early differentiation of leukemias in the hematology–oncology unit. The CPD-driven ANN modeling is a novel practice that substantially strengthens the predictive potential of CPD items, allowing the clinicians to be confident about the typical trend of the “disease fingerprint” shown by these automated potential morphometric items.

Comparative Study of Abiotic Stress Factors on GC-MS-Detected Phytoconstituents of Aloe greatheadii var: davyana Using Heat Map and Hierarchical Clustering Dendrogram

Aloe greatheadii var. davyana or spotted aloe is indigenous to South Africa and widely distributed in the northern provinces. The plant has a vast ethnopharmacological application which is mostly attributed to its phytochemical content. The aim of the study was to examine the effect of abiotic stress factors on the plant’s phytochemical content. The phytochemical content of A. greatheadii hexane extracts from four different provinces (Limpopo, Mpumalanga, Gauteng, and North West), harvested from the wild at varied altitudes, rainfall patterns, and soil types, was examined using gas chromatography-mass spectra (GC-MS). The phytochemical content of hexane extracts from the four South African provinces was analysed using heat map analysis and hierarchical clustering dendrogram. The phytochemical content of A. greatheadii hexane extracts was composed of fatty acids, alkanes, benzene, carboxylic acids, ketones, phytosterols, and vitamins. Eicosane, henicosane, and [(2S)-2-[(2R)-4-hexadecanoyloxy-3-hydroxy-5-oxo-2H-furan-2-yl]-2-hydroxyethyl] hexadecanoate were the only compounds detected in all samples from the four provinces. The concentration levels of 2-(((2-ethylhexyl)oxy)carbonyl) benzoic acid, beta-sitosterol, tritetracontane, and ethyl 13-methyltetradecanoate were closely related and expressed a low clustering distance amongst the samples. Variations in soil pH, soil type, and rainfall patterns were detected and differed in the four provinces. The different abiotic stress factors affected the biochemical pathways for the different compounds, with conditions in Gauteng being less favourable for many of the compounds detected. Abiotic stress factors have shown to influence phytochemical biochemical pathways and quantity. Aloe greatheadii plants can be selected based on location seemingly due to the variations that persist in their phytochemical content.

Computer-Aided Classification of New Psychoactive Substances

The appearance on the free market of synthetic cannabinoids raised the researchers’ interest in establishing their molecular similarity by QSAR analysis. A rigorous criterion for classifying drugs is their chemical structure. Therefore, this article presents the structural similarity of two groups of drugs: benzoylindoles and phenylacetylindoles. Statistical analysis and clustering of the molecules are performed based on their numerical characteristics extracted using Cheminformatics methods. Their similarities/dissimilarities are emphasized using the dendrograms and heat map. The highest discrepancies are found in the phenylacetylindoles group.

Implementation of a DPU-Based Intelligent Thermal Imaging Hardware Accelerator on FPGA

Thermal imaging has many applications that all leverage from the heat map that can be constructed using this type of imaging. It can be used in Internet of Things (IoT) applications to detect the features of surroundings. In such a case, Deep Neural Networks (DNNs) can be used to carry out many visual analysis tasks which can provide the system with the capacity to make decisions. However, due to their huge computational cost, such networks are recommended to exploit custom hardware platforms to accelerate their inference as well as reduce the overall energy consumption of the system. In this work, an energy adaptive system is proposed, which can intelligently configure itself based on the battery energy level. Besides achieving a maximum speed increase that equals 6.38X, the proposed system achieves significant energy that is reduced by 97.81% compared to a conventional general-purpose CPU.

Motor Point Heatmap of the Calf

Background: Contractions of muscles in the calf induced by neuromuscular electrical stimulation (NMES) may prevent venous thromboembolism. However, compliance to NMES-treatment is limited by the use of suboptimal stimulation points which may cause discomfort. Knowledge of where one is most likely to find muscle motor points (MP) could improve NMES comfort and compliance.Aims: To anatomically map the MPs of the calf as well as to calculate the probability of finding a MP in different areas of the calf. Material and Methods: On 30 healthy participants (mean age 37 years) anatomical landmarks on the lower limbs were defined. The location of the four most responsive MPs on respectively the medial and lateral calf muscle bellies were determined in relation to these anatomical landmarks using a MP search pen and a pre-set MP search program with 3 Hz continuous stimulation. The anatomy of the calves was normalized and subdivided into a matrix of 48 (6x8) smaller areas (3x3cm), from upper medial to lower lateral, in order to calculate the probability of finding a MP in one of these areas. The probability of finding a MP was then calculated for each area and presented with a 95% confidence interval.Results: The MP heat map displayed a higher concentration of MPs proximally and centrally on the calf. However, there were wide inter-individual differences in the location of the MPs. The highest probability of finding a MP was in area 4, located proximally and medially, and in area 29, located centrally and around the maximum circumference, both with 50% probability (95% CI: 0.31-0.69). The second highest probability of finding MPs was in areas 9, 10, 16, proximally and medially, all with 47% probability (95% CI: 0.28-0.66). These areas 4, 9, 10, 16 and 29 exhibited significantly higher probability of finding motor points than all areas with a mean probability of 27% and lower (p<0.05) The lateral and distal outskirts exhibited almost zero probability of finding MPs. Conclusions: This MP heat map of the calf could be used to expedite electrode placement and to improve compliance in order to receive consistent and enhanced results of NMES treatments.

Variability and trends of climate extremes indices from the observed and downscaled GCMs data over 1950–2020 period in Chattogram City, Bangladesh

This study was intended to evaluate the variability and trends of climate extremes by incorporating daily data from Chattogram station and from the high-resolution Coordinated Regional Climate Downscaling Experiment (CORDEX) for two different time series. Here, we also focused on evaluating the performance of the selected RCMs (CanESM2, CSIRO, and GFDL from CORDEX) using Taylor diagrams and heat map analysis. Twenty-two extreme climate indices from ETCCDI were computed for 1950–1989 and 1990–2020 periods. Mann–Kendall and Sen's slope test were performed to estimate the trends from the indices from both station and RCMs data. Highly significant increasing trend for the warm days and warm nights’ frequencies were found, whereas, the frequency of cold days and cold nights indicated significantly decreasing trend. On the other hand, mild increasing trend in 1-day and 5-day maximum rainfall was detected. Also, the average annual precipitation has increased by 6% from the 1950–1989 to 1990–2020 period. During the last three decades, the region has experienced more heavier rainfall in the monsoon but increased water stress in the dry season. The two-fold effects of climate change on the local hydrology revealed by this study need to be addressed properly for the sustainable development of this region.

Open Learning Experience Bingo

Definitions of openness and open education abound, but with so many, how can we use them effectively to explore the openness of assignments, activities, classes, or programs? Open Learning Experience Bingo is a game that a group of collaborators have created to give people a way to surface and discuss the many different ways that educational experiences can “open” beyond traditional practices. Each bingo card includes boxes containing possible “ingredients” in a learning experience, and radiating from the center of each box, “dimensions” of openness along which an ingredient might be opened. You “play” bingo by reading or hearing about a learning experience and marking areas on the bingo card that you think the experience opens. The game incorporates broad concepts of openness and seeks not to measure the openness of learning experiences, but to identify and spark discussion about areas in which experiences are opening — or might be opened further. As artifacts, completed bingo cards display a sort of “heat map” of openness that can be used to compare and contrast bingo evaluations of various learning experiences.

Impact of Headworks of River Chenab on Surrounding Vegetation and Phytodiversity Analysis

This study focused on the impact assessment of the wild flora and environmental gradients encompassed by the River Chenab headworks using quantitative ecological indices. Quadrats of 1 × 1, 5 × 5 and 10 × 10 m2 sizes were used for vegetation. Considering environmental data, grazing and anthropogenic effects, soil analysis based on different physical and chemical properties was studied. The relationship between different sites and their surroundings was analyzed by Canonical and Detrended Correspondence Analysis. Similarity indices were revealed through the use of a heat map and dendrogram. As many as 130 plant species, 60 families, comprising 104 species of dicots, 17 monocots, 7 pteridophytes and 2 species of bryophytes were recorded. Different soil properties including organic matter, soil moisture and soil pH affect the vegetation on different sites. Anthropogenic activities such as construction, fishing and animal grazing were the main threats for vegetation that need to be restricted strategically to conserve surrounding vegetation.

Lactic Acid Bacteria From Saltwater Fish Samples: Probiotic Potential Characterization and Clustering Using Unsupervised Algorithms

This research aimed to isolate lactic acid bacteria (LAB) from the bowl of saltwater fish to assess their probiotic properties. Nineteen isolates of LAB including Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus fermentum, Lactococcus lactis, Enterococcus hirae, Enterococcus lactis, Pediococcus pentosaceus, Pediococcus acidilactici, and Pediococcus lolli were recognized using molecular tools. All the isolates survived in the simulated conditions of the GI tract. Auto-aggregation ranged from 01.3 ± 0.5% to 82.6 ± 1.4% and hydrophobicity with toluene ranged from 3.7 ± 1.6% to 69.4 ± 1.3%, while the range of hydrophobicity with xylene was from 02.2 ± 1.6% to 56.4 ± 2.1%. All the isolates of lactobacilli, pediococci, enterococci, and lactococci indicated variable sensitivity and resistance towards clinical antibiotics. Non-neutralized cell free supernatant of isolates F12 and F15 showed antimicrobial activity against all the 8 evaluated enteric pathogens. Cluster analysis of identified potential probiotic bacteria based on heat-map and PCA methods also highlighted the priority of isolates F3, F7, F12, and F15 as bio-control agents in fishery industry. The findings of this study may essentially contribute to the understanding of the probiotic potential of LAB in saltwater fish, in order to access their probiotic characterization for use as biocontrol in fishery.