Numerical and experimental analysis of a hybrid material acoustophoretic device for manipulation of microparticles.

Acoustophoretic microfluidic devices have been developed for accurate, label-free, contactless, and non-invasive manipulation of bioparticles in different biofluids. However, their widespread application is limited due to the need for the use of high quality microchannels made of materials with high specific acoustic impedances relative to the fluid (e.g., silicon or glass with small damping coefficient), manufactured by complex and expensive microfabrication processes. Soft polymers with a lower fabrication cost have been introduced to address the challenges of silicon- or glass-based acoustophoretic microfluidic systems. However, due to their small acoustic impedance, their efficacy for particle manipulation is shown to be limited. Here, we developed a new acoustophoretic microfluid system fabricated by a hybrid sound-hard (aluminum) and sound-soft (polydimethylsiloxane polymer) material. The performance of this hybrid device for manipulation of bead particles and cells was compared to the acoustophoretic devices made of acoustically hard materials. The results show that particles and cells in the hybrid material microchannel travel to a nodal plane with a much smaller energy density than conventional acoustic-hard devices but greater than polymeric microfluidic chips. Against conventional acoustic-hard chips, the nodal line in the hybrid microchannel could be easily tuned to be placed in an off-center position by changing the frequency, effective for particle separation from a host fluid in parallel flow stream models. It is also shown that the hybrid acoustophoretic device deals with smaller temperature rise which is safer for the actuation of bioparticles. This new device eliminates the limitations of each sound-soft and sound-hard materials in terms of cost, adjusting the position of nodal plane, temperature rise, fragility, production cost and disposability, making it desirable for developing the next generation of economically viable acoustophoretic products for ultrasound particle manipulation in bioengineering applications

Drawing inferences for high‐dimensional linear models: A selection‐assisted partial regression and smoothing approach

Drawing inferences for high‐dimensional models is challenging as regular asymptotic theories are not applicable. This article proposes a new framework of simultaneous estimation and inferences for high‐dimensional linear models. By smoothing over partial regression estimates based on a given variable selection scheme, we reduce the problem to low‐dimensional least squares estimations. The procedure, termed as Selection‐assisted Partial Regression and Smoothing (SPARES), utilizes data splitting along with variable selection and partial regression. We show that the SPARES estimator is asymptotically unbiased and normal, and derive its variance via a nonparametric delta method. The utility of the procedure is evaluated under various simulation scenarios and via comparisons with the de‐biased LASSO estimators, a major competitor. We apply the method to analyze two genomic datasets and obtain biologically meaningful results.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151307/1/biom13013.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151307/2/biom13013-sup-0001-SuppData.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151307/3/biom13013_am.pd

Targeted photothermal therapy of melanoma in C57bl/6 mice using Fe3 O4 @Au core-shell nanoparticles and near-infrared laser

Background: Gold nanoshells can be tuned to absorb a particular wavelength of light. As a result, these tunable nanoparticles (NPs) can efficiently absorb light and convert it to heat. This phenomenon can be used for cancer treatment known as photothermal therapy. In this study, we synthesized Fe3 O4 @Au core-shell NPs, magnetically targeted them towards tumor, and used them for photothermal therapy of cancer. Objective: The main purpose of this research was to synthesize Fe3 O4 @Au coreshell NPs, magnetically target them towards tumor, and use them for photothermal therapy of cancer. Material and Methods: In this experimental study, twenty mice received 2 � 106 B16-F10 melanoma cells subcutaneously. After tumors volume reached 100 mm3,the mice were divided into five groups including a control group, NPs group, laser irradiation group, NPs + laser group and NPs + magnet + laser group. NPs were injected intravenously. After 6 hours, the tumor region was irradiated by laser (808 nm, 2.5 W/cm2, 6 minutes). The tumor volumes were measured every other day. Results: The effective diameter of Fe3 O4 @Au NPs was approximately 37.8 nm. The average tumor volume in control group, NPs group, laser irradiation group, NPs + laser irradiation group and NPs + magnet + laser irradiation group increased to 47.3, 45.3, 32.8, 19.9 and 7.7 times, respectively in 2 weeks. No obvious change in the average body weight for different groups occurred. Conclusion: Results demonstrated that magnetically targeted nano-photothermal therapy of cancer described in this paper holds great promise for the selective destruction of tumors. © 2021, Shriaz University of Medical Sciences. All rights reserved

Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in [arXiv:1109.4424] a strategy that allows compressed sensing to be performed at acquisition rates approaching to the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation max- imization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distribution of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.Comment: 42 pages, 37 figures, 3 appendixe

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches. MethodsRNA-Seq data from peripheral blood mononuclear cells (PSPRINGER NATUREs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules. ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis. ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic

Comparison of DNA polymorphism of bovine pituitary-specific transcription Factor and Leptin Gene Between Iranian Bos indicus and Bos taurus Cattle Using PCR-RFLP.

Variations at DNA level contribute to the genetic characterization of livestock populations and this may help to identify possible hybridization events as well as past evolutionary trends. The leptin and Pit-1 are attractive candidate genes for production and reproduction traits in cattle. A total of 247 animals from four breeds from two species of Iranian cattle populations in include Bos taurus (Sarabi, Golpayegani) and Bos indicus (Sistani, Taleshi) were genotyped for the Pit-1 Hinfl and leptin Sau3AI polymorphisms by the Polymerase Chain Reaction and Restriction Fragment Length Polymorphism (PCR-RFLP). The genotype and gene frequencies for each group were determined and shown to be quite variable among the breeds. The allele B for the leptin gene and allele A for the Pit-1 gene were investigated high frequency in Bos indicus. Candidate gene approach may be a useful method to measure of genetic distance for cross breeding program between taurin and indicine cattle

Construction of a circRNA– lincRNA–lncRNA–miRNA–mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq.Methods: Thirty samples from Ji’ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs).Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤−5) and false discovery rate (FDR <0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine–cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development

GM-CSF Signalling Boosts Dramatically IL-1Production

GM-CSF is mostly known for its capacity to promote bone marrow progenitor differentiation, to mobilize and mature myeloid cells as well as to enhance host immune responses. However the molecular actions of GM-CSF are still poorly characterized. Here we describe a new surprising facet of this “old” growth factor as a key regulator involved in IL-1βsecretion. We found that IL-1β release, a pivotal component of the triggered innate system, is heavily dependent on the signaling induced by GM-CSF in such an extent that in its absence IL-1β is only weakly secreted. GM-CSF synergizes with LPS for IL-1β secretion mainly at the level of pro-IL-1β production via strengthening the NF-κB signaling. In addition, we show that expression of Rab39a, a GTPase required for caspase-1 dependent IL-1β secretion is greatly augmented by LPS and GM-CSF co-stimulation suggesting a potential GM-CSF contribution in enhancing IL-1β exocytosis. The role of GM-CSF in regulating IL-1β secretion is extended also in vivo, since GM-CSF R−/− mice are more resistant to LPS-mediated septic shock. These results identify GM-CSF as a key regulator of IL-1β production and indicate GM-CSF as a previously underestimated target for therapeutic intervention

The relationship of air pollution and surrogate markers of endothelial dysfunction in a population-based sample of children

<p>Abstract</p> <p>Background</p> <p>This study aimed to assess the relationship of air pollution and plasma surrogate markers of endothelial dysfunction in the pediatric age group.</p> <p>Methods</p> <p>This cross-sectional study was conducted in 2009-2010 among 125 participants aged 10-18 years. They were randomly selected from different areas of Isfahan city, the second large and air-polluted city in Iran. The association of air pollutants' levels with serum thrombomodulin (TM) and tissue factor (TF) was determined after adjustment for age, gender, anthropometric measures, dietary and physical activity habits.</p> <p>Results</p> <p>Data of 118 participants was complete and was analyzed. The mean age was 12.79 (2.35) years. The mean pollution standards index (PSI) value was at moderate level, the mean particular matter measuring up to 10 μm (PM₁₀) was more than twice the normal level. Multiple linear regression analysis showed that TF had significant relationship with all air pollutants except than carbon monoxide, and TM had significant inverse relationship with ozone. The odds ratio of elevated TF was significantly higher in the upper vs. the lowest quartiles of PM₁₀, ozone and PSI. The corresponding figures were in opposite direction for TM.</p> <p>Conclusions</p> <p>The relationship of air pollutants with endothelial dysfunction and pro-coagulant state can be an important factor in the development of atherosclerosis from early life. This finding should be confirmed in future longitudinal studies. Concerns about the harmful effects of air pollution on children's health should be considered a top priority for public health policy; it should be underscored in primordial and primary prevention of chronic diseases.</p