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Determining the individual roles of the two dopamine D1-like receptors (D1R and D5R) on sodium transport in the human renal proximal tubule has been complicated by their structural and functional similarity. Here we used a novel D5R-selective antagonist (LE-PM436) and D1R- or D5R-specific gene silencing to determine second messenger coupling pathways and heterologous receptor interaction between the two receptors. D1R and D5R colocalize in renal proximal tubule cells and physically interact, as determined by co-immunoprecipitation and fluorescent resonance energy transfer microscopy. Stimulation of renal proximal tubule cells with fenoldopam (D1R/D5R agonist) led to both adenylyl cyclase and phospholipase C (PLC) activation using real-time fluorescent resonance energy transfer biosensors ICUE3 and CYPHR, respectively. Fenoldopam increased cAMP accumulation and PLC activity and inhibited both NHE3 and NaKATPase activities. LE-PM436 and D5R siRNA blocked the fenoldopam-stimulated PLC pathway but not cAMP accumulation, whereas D1R siRNA blocked both fenoldopam-stimulated cAMP accumulation and PLC signaling. Either D1R or D5R siRNA, or LE-PM436 blocked the fenoldopam-dependent inhibition of sodium transport. Further studies using the cAMP-selective D1R/D5R agonist SKF83822 and PLC-selective D1R/D5R agonist SKF83959 confirmed the cooperative influence of the two pathways on sodium transport. Thus, D1R and D5R interact in the inhibition of NHE3 and NaKATPase activity, the D1R primarily by cAMP, whereas the D1R/D5R heteromer modulates the D1R effect through a PLC pathway.

Photocatalytic degradation technology has received much attention from researchers in the last few decades, due to its easy and cost-effective nature. A lot of review articles have been published on dyes via photocatalytic degradation, but most of the review articles lack a detailed and in-depth photocatalytic degradation mechanism of dyes. Numerous review articles are available on photocatalysis. Here, in this review article, we are mainly focused on the complete and in-depth photocatalytic degradation mechanism of four commonly used dyes such as Malachite Green, Methylene Blue, Congo Red and Rhodamine B, which will be highly useful for the new researchers that work on dyes’ photocatalytic degradation. Initially, various aspects of dyes have been included in this review article, comprehensively. The main focus was on the covalent organic framework-based photocatalysts for dyes’ photocatalytic degradation, due to their porous nature and various unique properties. Various synthesis routes and the photocatalytic performance of covalent organic frameworks and composite of covalent organic frameworks have been highlighted in this review article. In the last section of this review article, the main stimulus was the four mentioned dyes’ properties, uses, and toxicity, and the photocatalytic degradation mechanism through various paths into environmentally friendly and less-harmful compounds in the presence of photocatalysts. Factors effecting the photocatalytic degradation, economic cost, challenges and future aspects of photocatalytic technology were also included in this review article. This review article will be highly useful for those researchers that work on the photocatalytic degradation of various dyes and search for the complete degradation of complex dye molecules.

Herein, elastomeric fibers that have shape memory properties due to the presence of a gallium core that can undergo phase transition from solid to liquid in response to mild heating are described. The gallium is injected into the core of a hollow fiber formed by melt processing. This approach provides a straightforward method to create shape memory properties from any hollow elastic fiber. Solidifying the core changes the effective fiber modulus from 4 to 1253 MPa. This increase in stiffness can preserve the fiber in a deformed shape. The elastic energy stored in the polymer shell during deformation drives the fiber to relax back to its original geometry upon melting the solid gallium core, allowing for shape memory. Although waxes are used previously for this purpose, the use of gallium is compelling because of its metallic electrical and thermal conductivity. In addition, the use of a rigid metallic core provides perfect fixity of the shape memory fiber. Notably, the use of gallium—with a melting point above room temperature but below body temperature—allows the user to melt and deform local regions of the fiber by hand and thereby tune the effective modulus and shape of the fiber. Herein, soft and ultrastretchable elastic shape memory fibers with electrical conductivity are demonstrated fabricated by injecting liquid metal, gallium, into the elastic and hollow fibers. The ability to change the core of the fiber from liquid to solid allows an enormous modulus change and thus, excellent shape memory effects.

Oral squamous cell carcinoma (OSCC), which accounts for 90% of head and neck cancers ( HNSC), is a prevalent cancer, especially in India, where it ranks among the top three cancers. Despite treatment advancements, OSCC incidence is rising, and recurrence remains a major concern. To improve patient prognosis, effective biomarkers for tumor demarcation are crucial. RNA isolation, library preparation, and RNA sequencing were performed on tumor and adjacent normal oral tissue samples. Transcriptomic analysis identified differentially expressed genes (DEGs) between tumor and normal tissues, which may serve as potential biomarkers. These findings were subsequently validated using RT-qPCR. The analysis revealed 704 upregulated and 1540 downregulated genes. Among these from the top 100 upregulated and downregulated genes, 15 and 9 genes respectively were also reported in the HNSC database of TCGA (The Cancer Genome Atlas). To identify potential biomarkers, the study evaluated multiple factors, including log2 fold change, average RPKM, ROC curve analysis, protein-protein interaction (PPI) network analysis and gene ontology (GO) analysis. The differential expression across various cancer stages and individual sample comparisons were also assessed. The upregulated genes MMP1 , MMP10 , MMP13 , MMP3 , ADAM12 , IL24 , and ISG15 demonstrated potential as biomarkers, with the highest log2 fold change, average RPKM, and AUC values. These significant genes could be valuable biomarkers for efficient demarcation between tumor and non-tumor tissues in oral cancer. This could lead to improved margin clearance, addressing concerns related to high recurrence rate of OSCC and ultimately enhance patient prognosis.

Gastrointestinal stromal tumors (GIST) are mesenchymal spindle cell tumors of the gastrointestinal tract with the rarest occurrence in anal canal sites accounting for approximately only 2-8% of the anorectal GISTs. GISTs involve the expression of KIT (CD117) tyrosine kinase with the presence of mutations in KIT or platelet-derived growth factor alpha (PDGFRα) and are identified as an important target in therapy. The elderly population in the age of 70s appears to be at the highest risk with abdominal pain, GI bleeding, anemia, or weight loss as non-specific presenting symptoms. Here, we describe a case of a 56-year-old man who presented with vague dull pain in his left buttock diagnosed with GIST with a submucosal mass in the posterior wall of the anal canal and rectum and a tumor size of 45x42x37 mm. An immunohistological study of the biopsy sample reported positive for CD 117, CD 34, and DOG 1. The patient was prescribed neoadjuvant imatinib for 8 months with a good response and subsequently underwent transanal endoscopic microsurgical resection. Post-operatively, the patient was continued on adjuvant imatinib followed by regular restaging CT chest/abdomen/pelvis and surveillance flexible sigmoidoscopy every 6 months.

Clostridium difficile infection (CDI) is mediated by two major exotoxins, toxin A (TcdA) and toxin B (TcdB), that damage the colonic epithelial barrier and induce inflammatory responses. The function of the colonic vascular barrier during CDI has been relatively understudied. Here we report increased colonic vascular permeability in CDI mice and elevated vascular endothelial growth factor A (VEGF-A), which was induced in vivo by infection with TcdA- and/or TcdB-producing C. difficile strains but not with a TcdA − TcdB − isogenic mutant. TcdA or TcdB also induced the expression of VEGF-A in human colonic mucosal biopsies. Hypoxia-inducible factor signalling appeared to mediate toxin-induced VEGF production in colonocytes, which can further stimulate human intestinal microvascular endothelial cells. Both neutralization of VEGF-A and inhibition of its signalling pathway attenuated CDI in vivo. Compared to healthy controls, CDI patients had significantly higher serum VEGF-A that subsequently decreased after treatment. Our findings indicate critical roles for toxin-induced VEGF-A and colonic vascular permeability in CDI pathogenesis and may also point to the pathophysiological significance of the gut vascular barrier in response to virulence factors of enteric pathogens. As an alternative to pathogen-targeted therapy, this study may enable new host-directed therapeutic approaches for severe, refractory CDI. Clostridium difficile toxins TcdA and TcdB enhance pathogenesis by inducing vascular endothelial growth factor A (VEGF-A) production and promoting colonic vascular permeability.

Chemotherapy-induced peripheral neuropathy (CIPN), a side effect of chemotherapy, is particularly difficult to treat. We explored whether phosphosulindac (PS), a modified NSAID, could treat CIPN. CIPN was induced in male C57BL/6 J mice by paclitaxel, vincristine or oxaliplatin. Mechanical allodynia was measured with the von Frey test and cold allodynia with the acetone test. To determine the preventive effect of PS, it was administered 2 days before the induction of CIPN. Mouse Lewis lung carcinoma xenografts were used to determine if PS altered the chemotherapeutic efficacy of paclitaxel. Cultured cell lines were used to evaluate the effect of PS on neuroinflammation. Treatment with each of the three chemotherapeutic agents used to induce CIPN lowered the mechanical allodynia scores by 56 to 85% depending on the specific agent. PS gel was applied topically 3x/day for 16-22 days to the hind paws of mice with CIPN. This effect was dose-dependent. Unlike vehicle, PS returned mechanical allodynia scores back to pre-CIPN levels. PS had a similar effect on paclitaxel-induced CIPN cold allodynia. Sulindac, a metabolite of PS, had no effect on CIPN. PS significantly prevented CIPN compared to vehicle. Given concomitantly with paclitaxel to mice with lung cancer xenografts, PS relieved CIPN without affecting the anticancer effect of paclitaxel. The enantiomers of PS were equally efficacious against CIPN, suggesting the therapeutic suitability of the racemate PS. There were no apparent side effects of PS. PS suppressed the levels of IL-6, IL-10, CXCL1, and CXCL2 induced by paclitaxel in a neuroblastoma cell line, and macrophage activation to the M1 proinflammatory phenotype. Topically applied PS demonstrated broad therapeutic and preventive efficacy against CIPN, preserved the anticancer effect of paclitaxel, and was safe. Its anti-CIPN effect appears to be mediated, in part, by suppression of neuroinflammation. These data support further evaluation of topical PS for the control of CIPN.

The term “big data analytics (BDA)” defines the computational techniques to study complex datasets that are too large for common data processing software, encompassing techniques such as data mining (DM), machine learning (ML), and predictive analytics (PA) to find patterns, correlations, and insights in massive datasets. Cardiovascular diseases (CVDs) are attributed to a combination of various risk factors, including sedentary lifestyle, obesity, diabetes, dyslipidaemia, and hypertension. We searched PubMed and published research using the Google and Cochrane search engines to evaluate existing models of BDA that have been used for CVD prediction models. We critically analyse the pitfalls and advantages of various BDA models using artificial intelligence (AI), machine learning (ML), and artificial neural networks (ANN). BDA with the integration of wide-ranging data sources, such as genomic, proteomic, and lifestyle data, could help understand the complex biological mechanisms behind CVD, including risk stratification in risk-exposed individuals. Predictive modelling is proposed to help in the development of personalized medicines, particularly in pharmacogenomics; understanding genetic variation might help to guide drug selection and dosing, with the consequent improvement in patient outcomes. To summarize, incorporating BDA into cardiovascular research and treatment represents a paradigm shift in our approach to CVD prevention, diagnosis, and management. By leveraging the power of big data, researchers and clinicians can gain deeper insights into disease mechanisms, improve patient care, and ultimately reduce the burden of cardiovascular disease on individuals and healthcare systems.