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Electrochromism or electrochromic contrast in electropolymerized thin films of dioxythiophenes based conjugated polymers is known to be sensitive to the structure of monomer and the polymerizing conditions. However in our studies we found that it is also sensitive to the electrode surface wherein a significantly high electrochromic contrast is observed in the electropolymerized thin films of poly(3,4-ethylenedioxythiophene), PEDOT deposited on platinum (71%) as compared to that on indium tin oxide, ITO, coated glass surface (54%). This is attributed to the formation of more conjugated polymer on the metallic surfaces as confirmed by narrow and red shifted absorption peak for PEDOT on platinum compared to broad and blue shifted peak on ITO in the UV–vis absorption spectra. This difference in the electrochromic properties of electropolymerized PEDOT thin films on the two surfaces is investigated by studying their electrochemical growth using UV–vis absorption, Raman spectroscopy and atomic force microscopy techniques. These results suggest the deposition of more conjugated polymer in the initial stages of growth (≤3 mC/cm 2 ) on both the substrates whereas it continues the same way into the intermediate stages (up to ∼15 mC/cm 2 ) only on platinum, thereby, resulting in higher electrochromic contrast on platinum. The coloration efficiency of PEDOT thin film was also found to be improved on platinum (465 cm 2 /C) compared to that on ITO (230 cm 2 /C). Moreover, we observed that the EC contrast of electropolymerized PEDOT thin films on platinum was found to be insensitive to polymerizing solvent that is generally not the case when polymerized on ITO. The cyclic stability of PEDOT-Pt films are better compared to that of PEDOT-ITO which is attributed to the improved reversibility of these films with respect to potential switching. [ABSTRACT FROM AUTHOR]

The synthesis of a new alkylmethylimidazolium ionic liquid wherein the alkyl group is functionalized with dihexylphosphine oxide moiety at the terminal position has been achieved in four steps from 1-methylimidazole. This hybrid ionic liquid effectively catalyzed the nucleophilic fluorination of primary alkyl mesylates under mild conditions using CsF as the fluoride source with a faster rate compared to butylmethylimidazolium mesylate. The hybrid catalyst was recycled 5 times without compromising the yield and purity of the product. The nucleophilic fluorination has been used for the synthesis of diethyl 2-(5-fluoropentyl)-2-methyl malonate, a precursor of 18 F isotopomer of an apoptosis imaging agent and the protected form of O -(2′-fluoroethyl)- l -tyrosine, a 18 F isotopomer of a tumor imaging agent. [ABSTRACT FROM AUTHOR]

Polyurethane/multi-walled carbon nanotube nanodielectric thin films of 25 μm thick were prepared by solution grown method. The microstructure of the nanodielectric was examined by scanning electron microscopy. The MWCNTs are observed to be dispersed in PU matrix well apart from a few of clusters. The MWCNTs/polymer nanodielectrics characterized with decrease in energy band gap and crystallinity. The analysis of dielectric properties of the composite samples of different weight ratio was studied by measuring the permittivity and tangential loss at room temperature. The frequency dependent permittivity obeys the percolation theory. Further, it has been observed that the dielectric properties of PU and PU nanodielectric are unaffected by UV-irradiation. XRD characteristics confirm the formation of PU/MWCNTs nanodielectrics. [ABSTRACT FROM AUTHOR]

Polyurethane (PU)/Polysulfone (PSF)/Multi Wall Carbon Nanotubes (CNTs) hybrid nanocomposite films were prepared by solution grown method with different wt% of functionalized CNTs. The structural and thermal properties of PU, PSF and PU + PSF + CNTs nanocomposite films were studied by various techniques such as scanning electron microscopy (SEM), X-ray diffraction (XRD), FTIR and TGA/DTG. The dispersion of CNTs in polymer was studied by SEM spectra, which indicates the presence of CNTs on the surface of the polymeric material. XRD results show the increases of crystallinity with different weight percentage of CNTs in polymer matrix. FTIR spectra reveal the position of different chemical bonds in pure and hybrid nanocomposite films. TGA and DTG show that the thermal stability of hybrid nanocomposite is better than PU and PSF due to reinforcement of CNTs in PU-PSF matrix. Surface charge decay study represents the charge stability in hybrid nanocomposite is due the localization of charge carriers in deeper traps. [ABSTRACT FROM AUTHOR]

Abstract: A novel route to a chiral functionalized [3]dendralene attached to a (−)-menthol auxiliary has been developed, which involves a dimethylsulfonium methylide mediated olefination of a substituted ethenylidene phosphonoacetate (−)-menthyl ester, followed by a Horner–Wordsworth–Emmons reaction with 4-bromobenzaldehyde. The chiral [3]dendralene was reactive enough to undergo intermolecular Diels–Alder cyclodimerization to give the highly substituted cyclohexene with very high regio- and diastereoselectivity. [Copyright &y& Elsevier]

Abstract: Microgel–clay composite particles were prepared by one-step surfactant–free precipitation polymerization. Laponite nanoparticles present in the reaction mixture become encapsulated during the microgel formation process. Microgel–clay composites based on poly(N-vinylcaprolactam-co-acetoacetoxyethyl methacrylate) containing different amount of incorporated clay nanoparticles were synthesized. The clay content was varied from 2 wt% to 18 wt%. The extremely high incorporation efficiency of the clay nanoparticles into microgels was detected. The size of the hybrid microgels was decreased from 700 nm to 100 nm by increase of the clay concentration in the reaction mixture. Obtained hybrid microgels exhibit negative surface charge and excellent colloidal stability. Microgel–clay composite particles display temperature-sensitive behaviour in water. The swelling degree of the hybrid microgels decreases with increase of the clay loading. Microgel–clay composite particles exhibit temperature-controlled uptake of the cationic dye, Methylene blue, and can be used as scavenger systems in aqueous media. [ABSTRACT FROM AUTHOR]

Abstract: The reactions between dimethylsulfonium methylide and 1,3-diene- or 1,3,5-triene-1,1-dioates under specific conditions enable the highly regioselective tandem ylide addition–eliminative olefination to provide 1,3-butadien-2-yl- or 1,3,5-hexatriene-2-yl-malonates. Alkylation at malonate methine carbon of 1,3-butadien-2-ylmalonates with a suitable alkyl halide having in-built functionalities for a dienophile generation led to quick assembly of precursors for type 2 intramolecular Diels–Alder reaction. Syntheses of functionalized bicyclo[n.3.1] alkenes (n=5 or 6) with the double bond at the bridgehead position have been achieved via the IMDA. An asymmetric version of this reaction has been developed using a MacMillan''s imidazolidinone catalyst, which provided a bicyclo[5.3.1] alkene with very high enantioselectivity. In situ methylation at malonate methine carbon of 1,3,5-hexatriene-2-yl-malonates followed by intermolecular Diels–Alder reaction with N-methylmaleimide provided the cycloadduct with complete regiocontrol and high diastereoselectivity. [Copyright &y& Elsevier]

Abstract: High glucose causes increased matrix synthesis by glomerular mesangial cells and angiotensin II (Ang II) has been shown to mediate this effect of glucose. These studies investigate whether inhibition of Ang II formation can block high glucose-induced increase in mesangial matrix. Human mesangial cells were incubated with 25mM glucose (HG) along with captopril, an ACE inhibitor, to block Ang II formation. In other experiments, cells were nucleofected with siRNA to knockdown angiotensinogen (Agt), the precursor of Ang II, and then exposed to high glucose. Captopril blocked high glucose-induced increase in Ang II levels in the cell media (extracellular) but failed to inhibit it in the cell lysate (intracellular). Moreover, captopril treatment did not block the stimulatory effect of high glucose on TGF-β1 and fibronectin. In contrast, knockdown of the Agt gene prevented high glucose-induced increase in both extracellular and intracellular Ang II levels, and was accompanied by normalization of TGF-β1 and fibronectin. These data suggest that intracellular Ang II may play an important role in the mediation of the high glucose effect on matrix and that ACE inhibitors may not be effective in blocking intracellular Ang II formation in mesangial cells. [Copyright &y& Elsevier]

Abstract: Reaction of dimethylsulfoxonium methylide with a β-silylmethylene malonate gives diversified products, cyclopropane, cyclobutane or allyl and homoallyl silanes depending upon the stoichiometry of the reactants and reaction conditions. Contrary to this, reaction of a β-arylmethylene malonate gives only the cyclopropane product. The product(s) formed are unique and the silicon group played a crucial role either by assisting and/or by participating in the process. [Copyright &y& Elsevier]

Abstract: A highly regio- and stereoselective [Pd(allyl)Cl]2 catalyzed Heck reaction of aryl iodides and electronically neutral terminal olefins generated in situ by fluoride induced protiodesilylation of alkenylsilanol derivatives under mild conditions has been developed. The products, viz. terminally substituted styrenes and (E)-1,4-diaryl-1-butenes were obtained in very good yields. The dibenzylbutyrolactone lignan skeletons have been prepared employing two regio- and stereoselective Bu3SnH-mediated radical cyclization routes. [Copyright &y& Elsevier]

B7 costimulation plays a major role in herpes simplex virus (HSV) immunity. Effects of immunoregulatory cytokines (interferon-γ [IFN-γ] and interleukin-10 [IL-10]) and HSV antigens on B7-1 (CD80) and B7-2 (CD86) expression on monocytes during HSV-2 infection were investigated using flow cytometry. Our results demonstrate that HSV-2 infection effects the expression of B7 isoforms (B7-1 and B7-2) on monocytes in two ways, with opposing outcomes. It abrogates the IFN-γ upregulation of B7-1 and B7-2 and also augments expression of B7-1 and B7-2 on monocytes through an IFN-γ independent mechanism. The clinical significance of these opposing effects may be related to the pathogenesis of recurrent HSV disease in immunocompetent hosts. [Copyright &y& Elsevier]

Role of viral genes in modulating T helper 1 (Th1) and T helper 2 (Th2) balance is of principal interest in the study of cytomegalovirus (CMV) immunity. Murine CMV (MCMV) mutants were used to explore a possible mechanism for the ability of virus to induce a predominant Th1 response and to suppress Th2 response by examining the production of Th1 (IFN-γ, IL-2) and Th2 (IL-4, IL-10) cytokines by the splenocytes of mice infected with wild type (WT) and MCMV mutants. Results (n=6) show that as compared with WT, the MCMV mutant with specific disruption of M43 gene upregulates the production of IL-4 (P=0.0002) and to a lesser extent IL-10 (P=0.015) at 14 days post infection. This indicates that M43 gene may play a role in suppressing Th2 (IL-4) production, especially in the later stage of infection. The IL-4 and IL-10 production during infection with M43 mutant occurs in the presence of a strong IFN-γ (Th1) response, overriding the cross-regulatory effects of these cytokines within the Th1/Th2 paradigm and suggesting that the predominant response during CMV infection is still a Th1 type response. [Copyright &y& Elsevier]

A stereoselective total synthesis of (+)-carpamic acid 1 has been achieved from the σ-symmetric 3-[dimethyl(phenyl)silyl]glutaric anhydride 11 featuring its asymmetric desymmetrisation using oxazolidinone 12. The dimethyl(phenyl)silyl group is not only acting as a masked hydroxy group but also stereodirects ester enolate methylation and facilitates the Curtius reaction of the β-silyl-amide 23. A highly stereoselective hydrogenation of the imine 10 is the key step in the construction of the all cis-2,3,6-trisubstituted piperidine. [Copyright &y& Elsevier]

The hydrolytic stability of norcantharidine derived conformationally constrained diamides in acidic media is solely governed by the type of amide. Tertiary diamides underwent smooth acid catalyzed hydrolysis due to anchimeric assistance whereas other diamides were stable. This was corroborated from conformational proximity of the amide groups for anchimeric assistance based on single crystal X-ray structure analysis. Theoretical calculations on the diamide structures also predict the similar proximity of the diamides in those conformations. Thus norcantharidine based diamides could probably serve as promising systems for delayed release of certain types of drugs which possess secondary amine component as exemplified by the release of m -chlorophenylpiperazine at a pH range of 1–2. Image 1 • Norcantharidine derived tertiary diamides hydrolyzed easily under acid catalysis. • Their primary, secondary and mixed diamides do not hydrolyze easily. • Hydrolysis of tertiary diamides occurred due to NGP of proximal amide carbonyls. • Hydrolysis of tertiary diamides has been supported by X-ray structure & calculations. • These tertiary diamides could serve for delayed release of certain types of drugs. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel feature selection approach for breast cancer prediction is proposed. • Feature selection was based on the three soft-computing algorithms. • The Bacterial foraging algorithm and the Emperor penguin algorithm are implemented. • Hybrid of Bacterial foraging algorithm and Emperor penguin algorithm is proposed. • Nine performance metrics are computed for six machine learning classifiers. Feature selection is one of the crucial data preprocessing techniques for improving the performance of machine learning (ML) models. Recently, metaheuristic feature selection algorithms have become popular because they select optimal features for ML problems. This paper presents three feature selection strategies based on metaheuristic algorithms: Bacterial Foraging (BFOA), Emperor Penguin (EPO), and a hybrid (hBFEPO) combining BFOA and EPO. The baseline algorithms have been investigated for feature selection in other ML tasks, but not for breast cancer classification. A hybrid of these two has been used for the first time. These strategies were initially tested on the COVID-19 dataset. After achieving satisfactory results, these strategies are evaluated on the WDBC Breast Cancer dataset. The performance of our models on WDBC is compared with recent eighteen state-of-the-art studies. The results indicate that the hBFEPO model outperforms other models, achieving 100% precision and specificity, 98.49% accuracy, 95.43% sensitivity, a 95.99% F1-score, and a 99.60% AUC. [ABSTRACT FROM AUTHOR]

• A soft-computing and machine learning based medical decision support system is proposed for breast cancer disease classification. • Two soft-computing algorithms eagle strategy optimization (ESO) algorithm and the gravitational search optimization (GSO) algorithm are employed for the first time for this problem. A novel intelligent classification approach based on these two algorithms for breast cancer infection is also proposed. • 12 experiments have been performed using three soft-computing algorithms(for feature selection) and 6 state-of-the-art machine learning classifier(for classification).WDBC dataset is used for the method evaluation. • We have been able to attain astonishing results with accuracy up to 98.9578%, sensitivity up to 0.9696, specificity up to 1.000, precision 1.000, F1- score up to 0.9696, and an AUC 0.9980(close to maximum i.e., 1.0000). Feature selection, which picks the optimal subset of characteristics related to the target data by deleting unnecessary data, is one of the most important aspects of the machine learning area. A major part of big data preprocessing is feature selection (reduction). There are 2n alternative feature subsets for every n features, making it difficult to choose the best set of features from a dataset using typical feature selection techniques. Consequently, the present study proposes and suggests a unique feature selection method based on the Eagle Strategy(ESO) Optimization, Gravitational Search Optimization (GSO) algorithm, and their hybrid algorithm. We chose this infection as our subject of investigation since the number of women with breast cancer is increasing rapidly on a global scale. After lung cancer, which affects more women than any other kind of cancer, breast cancer is the second leading cause of cancer mortality. The goal of this study is to categorize breast cancer into two groups using the benchmark feature set (Wisconsin Diagnostic Breast Cancer (WDBC)) and to choose the fewest features (feature selection) to achieve maximum accuracy. This work also provides a hybrid technique for finding important features that combines two algorithms, ESO and the GSO algorithm, while reducing insignificant characteristics (features) and complexity. Soft computing technologies and machine learning algorithms provide a framework for prognostic research by classifying data instances as relevant or irrelevant depending on cancer severity. Thus, this work presented a new approach for classifying breast cancer tumors. In this research, we coupled soft computing methodologies—our implemented algorithms are applied for the first time to this problem—with artificial intelligence-based machine learning strategies to create a prediction model. The efficacy of our suggested technique was evaluated using WDBC breast cancer data sets, and the findings show that our proposed hybrid algorithm performs very well in breast cancer classification. We have been able to attain astonishing results with accuracy up to 98.9578%, sensitivity up to 0.9705, specificity up to 1.000, precision up to 1.000, F1-score up to 0.9696, and an AUC up to 0.9980 (close to maximum, i.e., 1.0000). Our study's goal is to incorporate our findings into a valid clinical prediction system, allowing visual science specialists to make more accurate and effective judgments in the future. Furthermore, our suggested technology might be used to detect a wide range of diseases. [ABSTRACT FROM AUTHOR]

• Wastewater-based surveillance has focused almost exclusively on urban areas. • Rural-urban public health surveillance and healthcare service disparities persist. • Recent research identifies pathways for implementing rural wastewater surveillance. The sampling and analysis of sewage for pathogens and other biomarkers offers a powerful tool for monitoring and understanding community health trends and potentially predicting disease outbreaks. Since the early months of the COVID-19 pandemic, the use of wastewater-based testing for public health surveillance has increased markedly. However, these efforts have focused on urban and peri‑urban areas. In most rural regions of the world, healthcare service access is more limited than in urban areas, and rural public health agencies typically have less disease outcome surveillance data than their urban counterparts. The potential public health benefits of wastewater-based surveillance for rural communities are therefore substantial – though so too are the methodological and ethical challenges. For many rural communities, population dynamics and insufficient, aging, and inadequately maintained wastewater collection and treatment infrastructure present obstacles to the reliable and responsible implementation of wastewater-based surveillance. Practitioner observations and research findings indicate that for many rural systems, typical implementation approaches for wastewater-based surveillance will not yield sufficiently reliable or actionable results. We discuss key challenges and potential strategies to address them. However, to support and expand the implementation of responsible, reliable, and ethical wastewater-based surveillance for rural communities, best practice guidelines and standards are needed. [Display omitted] [ABSTRACT FROM AUTHOR]

• A feature selection strategy which selects the optimal subset of features, by employing GSOA, from the original set is developed, in which the elimination of extraneous features takes place which enhances the classification performance and reduces the computational cost. This improves glaucoma detection while lowering model training computational costs and execution time. The performance is evaluated on the customized dataset of public and private images. • Further in this research, we discuss the application of machine learning in anticipating diseases,thus expanding the field of medical services and bringing in the most recent technology. It is demonstrated how to use the suggested technique, and a comprehensive analysis of different parameters is given. To determine the most effective presentation, various efficiency assessment criteria for many machine learning classifiers were implemented. The parameters included are accuracy, sensitivity,specificity, ROC curves and many more. • Through this study, we offer the best features(selected through soft-computing approach) to researchers, a reliable and effective system of support for medical professionals, and a software-based tool for the human race to slow down this infection spreading through early, quick, and accurate identification of this infection. It might be used in locations with a shortage of qualified medical workers like doctors and nurses. It can also be altered to work with wearable and portable medical devices. • For the detection of this infection from retinal fundus images, our proposed method outperforms existing techniques. This testing procedure will be advantageous for doctors and the state because it is significantly less expensive than other diagnostic instruments used by medical professionals to detect the disease. In addition, owing to its high performance, the proposed medical prediction system can be used to develop mobile applications that aid physicians in the early diagnosis of glaucoma. The process of feature selection (FS) is vital aspect of machine learning (ML) model's performance enhancement where the objective is the selection of the most influential subset of features. This paper suggests the Gravitational search optimization algorithm (GSOA) technique for metaheuristic-based FS. Glaucoma disease is selected as the subject of investigation as this disease is spreading worldwide at a very fast pace; 111 million instances of glaucoma are expected by 2040, up from 64 million in 2015. It causes widespread vision impairment. Optic nerve fibres can be degraded and cannot be replaced later in this disease. As a starting point, the retinal fundus images of glaucoma infected persons and healthy persons are used, and 36 features were retrieved from these images of public benchmark datasets and private dataset. Six ML models are trained for classification on the basis of the GSOA's returned subset of features. The suggested FS technique enhances classification performance with selection of most influential features. The eight statistical performance evaluating parameters along with execution time are calculated. The training and testing have been performed using a split approach (70:30), 5-fold cross validation (CV), as well as 10-fold CV. The suggested approach achieved 95.36 % accuracy. Due to its auspicious performance, doctors might use the suggested method to receive a second opinion, which would also help overburdened skilled medical practitioners and save patients from vision loss. [ABSTRACT FROM AUTHOR]

• We 65 extracted structural and non-structural feature sets for glaucoma prediction. • Our selected three nature-computing algorithms and two novel algorithms have been applied first time to these glaucoma datasets in combination with these characteristics. As a result, the results from this series of experiments are entirely novel. • The performance test of Bat Algorithm and Binary Cuckoo Search on two typical publicly accessible datasets demonstrates that they are highly efficient in glaucoma prediction. Extensive testing and analysis were conducted (3 machine learning and 5 soft computing techniques were tested on three combinations of two datasets). • This work adds to scientific research by suggesting a unique classifier strategy that achieves astonishing results, up to 98.95% accuracy in detecting glaucoma illness in the binary class. The suggested system's categorization accuracy is evaluated against two widely used and publicly accessible datasets. • This work provides an automated primary glaucoma screening system based on quantitative analysis of fundus pictures to aid ophthalmologists in detecting glaucoma disease more quickly and affordably. It could also be used as a second opinion. With this system, human race has been equipped with a low-cost, rapid, robust, readily implementable, and reliable intelligence system for screening this infection. As a result, the pace of eyesight loss may be minimized. Glaucoma is the second most common cause of vision loss. Manual screening of a patient's eye or screening through a fundus image of the patient's eye requires expert ophthalmologists. This screening analysis is time-consuming, requires expert human involvement, and is subject to human intra-observer variability. Thus, medical imaging professionals are working to solve these issues by investigating retinal images for glaucoma detection using artificial intelligence-based computer-aided diagnosis systems (CAD). Machine learning algorithms (for classification) and nature-inspired computing (for feature selection/reduction) embedded CAD systems can successfully identify retinal pictures and can be employed to overcome these challenges. This proposed work is a productive attempt in which we have proposed two novel two-layered approaches (BA-BCS, BCS-PSO) which are based on Particle Swarm Optimization (PSO), Binary Cuckoo Search (BCS), and Bat Algorithm (BA). We have also analyzed the performances of BA, BCS, and PSO separately. These five (single and two-layered) approaches are used to compose subsets of reduced features that can generate the maximum accuracy when forwarded to three machine learning classifiers. Benchmark publicly available datasets, ORIGA and REFUGE, and their combinations are used to validate the proposed methodology. A maximum accuracy of up to 98.95% is achieved using these approaches. Apart from this, many other trade-off solutions are also suggested for the researcher's community. This study therefore presents novel efforts with new and efficient results that are beneficial to ophthalmologists, researchers, and humanity. [ABSTRACT FROM AUTHOR]

Considerable evidence suggests that the intrarenal renin-angiotensin system plays an important role in diabetic nephropathy, Angiotensin-converting enzyme (ACE) inhibitors and angiotensin II (Ang II) receptor blockers (ARBs) can attenuate progressive glomerulosclerosis in disease models and can slow disease progression in humans. Because agents that interfere with Ang II action may decrease glomerular injury without altering glomerular pressures, it has been suggested that Ang II has direct effects on glomerular cells to induce sclerosis in dependent of its hemodynamic actions. To study nonhemodynamic effects of Ang II on matrix metabolism, many investigators have used cell culture systems. Glucose and Ang II have been shown to produce similar effects on renal cells in culture. For instance, incubation of mesangial cells in high-glucose media or in the presence of Ang II stimulates matrix protein synthesis and inhibits degradative enzyme (e.g., collagenase, plasmin) activity. Glucose and Ang II also can inhibit proximal tubule proteinases. Glucose increases expression of the angiotensinogen gene in proximal tubule cells and Ang II production in primary mesangial cell culture, which indicates that high glucose itself can activate the renin-angiotensin system. The effects of glucose and Ang II on mesangial matrix metabolism may be mediated by transforming growth factor-β (TGF-β). Exposure of mesangial cells to glucose or Ang II increases TGF-β expression and secretion. Their effects on matrix metabolism can be blocked by ant-TGF-β antibody or ARBs such as losartan, which also prevents the glucose-induced increment in TGF-β secretion. Taken together, these findings support the hypothesis that the high-glucose milieu of diabetes increases Ang II production by renal and especially, mesangial cells, which results in stimulation of TGF-β1 secretion, leading to increased synthesis and decreased degradation of matrix proteins, thus... [ABSTRACT FROM AUTHOR]

Role of angiotensin II in diabetic nephropathy. Considerable evidence suggests that the intrarenal renin-angiotensin system plays an important role in diabetic nephropathy. Angiotensin-converting enzyme (ACE) inhibitors and angiotensin II (Ang II) receptor blockers (ARBs) can attenuate progressive glomerulosclerosis in disease models and can slow disease progression in humans. Because agents that interfere with Ang II action may decrease glomerular injury without altering glomerular pressures, it has been suggested that Ang II has direct effects on glomerular cells to induce sclerosis independent of its hemodynamic actions. To study nonhemodynamic effects of Ang II on matrix metabolism, many investigators have used cell culture systems. Glucose and Ang II have been shown to produce similar effects on renal cells in culture. For instance, incubation of mesangial cells in high-glucose media or in the presence of Ang II stimulates matrix protein synthesis and inhibits degradative enzyme (e.g., collagenase, plasmin) activity. Glucose and Ang II also can inhibit proximal tubule proteinases. Glucose increases expression of the angiotensinogen gene in proximal tubule cells and Ang II production in primary mesangial cell culture, which indicates that high glucose itself can activate the renin-angiotensin system. The effects of glucose and Ang II on mesangial matrix metabolism may be mediated by transforming growth factor-β (TGF-β). Exposure of mesangial cells to glucose or Ang II increases TGF-β expression and secretion. Their effects on matrix metabolism can be blocked by anti-TGF-β antibody or ARBs such as losartan, which also prevents the glucose-induced increment in TGF-β secretion. Taken together, these findings support the hypothesis that the high-glucose milieu of diabetes increases Ang II production by renal, and especially, mesangial cells, which results in stimulation of TGF-β1 secretion, leading to increased synthesis and decreased degradation of matrix proteins, thus producing matrix accumulation. This may be an important mechanism linking hyperglycemia and Ang II in the pathogenesis of diabetic nephropathy. [ABSTRACT FROM AUTHOR]