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Transforming growth factor-β (TGF-β) is a multifunctional cytokine that regulates the expression of ECM-associated genes during early injury. Tissue fibrosis development is driven by synergistic cues between the evolving biochemical and mechanical milieu. Few studies have addressed the role of substrate stiffness on TGF-β activity and extracellular matrix (ECM)-associated genes. We used a commercial formulation of polydimethylsiloxane (PDMS) to fabricate substrates of 40 kPa, 300 kPa, and 1.5 MPa stiffness, and cultured the HMF3S fibroblasts on substrates. We quantified TGF-β protein secreted by HMF3S cells on different substrates using a TGF-β responsive promoter reporter assay. We also tested for variations in gene expression levels on the substrates using RT-PCR and Western blotting and determined the MMP-2 and MMP-9 activities with gelatin zymography. The results showed that TGF-β protein activation was significantly compromised at lower stiffnesses. The expression of integrin α5 decreased on lower stiffness substrates and correlated with inefficient TGF-β protein activation. Collagen I, collagen III, and MMP-2 expression levels were lower on softer substrates; there was little MMP-9 activity on all substrates. Cell and nuclear morphologies were more rounded on compliant substrates, correlating with increased tubulin expression. Proliferations were higher on stiffer substrates, whereas cells on softer substrates showed cell cycle arrest. These results demonstrated critical feedback mechanisms between substrate stiffness and ECM regulation by fibroblasts, relevant in fibrosis.

Identifying patients with Coronavirus disease-2019 (COVID-19) who may have a severe illness is essential for timely intervention and decreasing the fatality rate. In the present study, we evaluated the performance of Monocyte Distribution Width (MDW) as a prognostic marker for identifying disease severity in COVID-19 patients. We included 145 patients with PCR-confirmed COVID-19 infection in the study. The performance of MDW was evaluated by calculating the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, negative predictive value, and positive predictive value. Further analysis was conducted for the disease outcome, comparing COVID-19 patients discharged ( n  = 135) to deceased COVID-19 patients ( n  = 10). As a marker of disease severity, MDW demonstrated an AUC of 0.702 (95% CI 0.620-0.775) in ROC analysis. If MDW is considered a marker of patient outcome, AUC was 0.916 (95% CI 0.862-0.953), comparing deceased COVID-19 patients vs. those who survived. At a cut-off of > 25.4 on admission, MDW correlates well with poor disease outcomes in COVID-19 patients. MDW can be considered a helpful parameter in predicting the severity of COVID-19 disease and patient outcomes. Its role and incorporation in the standard diagnostic algorithm and management of COVID-19 patients need further validation., Supplementary Information: The online version contains supplementary material available at 10.1007/s12288-023-01665-y., Competing Interests: Conflict of interestSandhya Bastian and Elena Sukhacheva work for Beckman Coulter Inc., (© The Author(s), under exclusive licence to Indian Society of Hematology and Blood Transfusion 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Purpose: Glioblastoma (GBM) is a highly invasive tumor. Despite advances in treatment modalities, tumor recurrence is common, seen mainly in the peritumoral brain zone (PBZ). We aimed to molecularly characterize PBZ, to understand the pathobiology of tumor recurrence., Methods/patients: We selected eight differentially regulated genes from our previous transcriptome profiling study on tumor core and PBZ. Expression of selected genes were validated in GBM (tumor core and PBZ, n = 37) and control (n = 22) samples by real time quantitative polymerase chain reaction (qPCR). Serine protease inhibitor clade A, member 3 (SERPINA3) was selected for further functional characterization in vitro by gene knockdown approach in glioma cells. Its protein expression by immunohistochemistry (IHC) was correlated with other clinically relevant GBM markers, patient prognosis and tumor recurrence., Results: The mRNA expression of selected genes from the microarray data validated in tumor core and PBZ and was similar to publicly available databases. SERPINA3 knock down in vitro showed decreased tumor cell proliferation, invasion, migration, transition to mesenchymal phenotype, stemness and radioresistance. SERPINA3 protein expression was higher in PBZ compared to tumor core and also was higher in older patients, IDH wild type and recurrent tumors. Finally, its expression showed positive correlation with poor patient prognosis., Conclusions: SERPINA3 expression contributes to aggressive GBM phenotype by regulating pro-tumorigenic actions in vitro and is associated with adverse clinical outcome.

Ensemble classifiers using clustering have significantly improved classification and prediction accuracies of many systems. These types of ensemble approaches create multiple clusters to train the base classifiers. However, the problem with this is that each class might have many clusters and each cluster might have different number of samples, so an ensemble decision based on large number of clusters and different number of samples per class within a cluster produces biased and inaccurate results. Therefore, in this article, we propose a novel methodology to create an appropriate number of strong data clusters for each class and then balance them. Furthermore, an ensemble framework is proposed with base classifiers trained on strong and balanced data clusters. The proposed approach is implemented and evaluated on 24 benchmark data sets from the University of California Irvine (UCI) machine learning repository. An analysis of results using the proposed approach and the existing state-of-the-art ensemble classifier approaches is conducted and presented. A significance test is conducted to further validate the efficacy of the results and a detailed analysis is presented.

Purpose: IGFBP2 is one of the highly expressed genes in glioblastoma (GBM). It has both IGF dependent and independent activities. IGF independent actions are mediated by the activation of integrin signalling through its RGD motif present at C-terminal domain. One of the actions of IGFBP2 is to regulate β-catenin by the inactivation of GSK3β, which preferentially accumulates in the cytoplasm. The mechanism of nuclear β-catenin regulation by IGFBP2 and role of cytoplasmic β-catenin is not clear. We aimed to understand the mechanism in GBM cell lines., Methods: The gene expression studies were performed by RT-PCR, western blot analysis; the knockdown of genes was performed by shRNA transfection; RNAIP and luciferase reporter assays were utilized to study the cytoplasmic regulation of genes by β-catenin; neurosphere assays were performed to study the stemness of cells., Results: IGFBP2 overexpression or treatment in GBM cells regulates β-catenin, TRIM33 (E3 ubiquitin ligase) and Oct4 genes. TRIM33 was induced by IGFBP2. β-catenin was found to accumulate predominantly in the cytoplasm and nuclear β-catenin was depleted by IGFBP2 induced TRIM33. IGFBP2 regulated cytoplasmic β-catenin binds to 3' UTR of Oct4 RNA. IGFBP2 was also able to induce stemness of glioma cells., Conclusions: IGFBP2 induces TRIM33 which regulates the nuclear β-catenin protein. In addition, IGFBP2 stabilizes the cytoplasmic β-catenin which is involved in the regulation of Oct4 transcript and consequently induction of stemness of glioma cells.

Mixed-ligand oxidovanadium(IV) β-diketonates having NNN-donor dipicolylamine-conjugated to boron-dipyrromethene (BODIPY in L 1 ) and diiodo-BODIPY (in L 2 ) moieties, namely, [VO(L 1 )(acac)]Cl ( 1 ), [VO(L 2 )(acac)]Cl ( 2 ), and [VO(L 1 )(dbm)]Cl ( 3 ), where acac and dbm are monoanionic O,O-donor acetylacetone and 1,3-diphenyl-1,3-propanedione, were prepared, characterized, and tested for their photoinduced anticancer activity in visible light. Complexes 1 and 2 were structurally characterized as their PF 6 - salts ( 1a and 2a ) by X-ray crystallography. They showed V IV N 3 O 3 six-coordinate geometry with dipicolylamine base as the facial ligand. The non-iodinated BODIPY complexes displayed absorption maxima at ∼501 nm, while it is ∼535 nm for the di-iodinated 2 in 10% DMSO-PBS buffer medium (pH = 7.2). Complexes 1 and 3 being green emissive (λ em , ∼512 nm; λ ex , 470 nm; Φ F , ∼0.10) in 10% aqueous DMSO were used for cellular imaging studies. Complex 3 localized primarily in the mitochondria of the cervical HeLa cells with a co-localization coefficient value of 0.7. The non-emissive diiodo-BODIPY complex 2 showed generation of singlet oxygen (Φ Δ ≈ 0.47) on light activation. Annexin-V assay showed singlet oxygen-mediated cellular apoptosis, making this complex a targeted PDT agent., Competing Interests: The authors declare no competing financial interest., (Copyright © 2020 American Chemical Society.)

We introduce a self-assembling polypeptide-based nanotube system having the ability to specifically target cancer cells. The nanotubes target the cancer cell surface through integrin engagement with the help of multiple RGD units present along their surface. While the nanotubes are non-toxic towards cells in general, they can be loaded with suitable drugs to be released in a sustained manner in cancer cells. In addition, the nanotubes can be utilized for cellular imaging using any covalently tagged fluorescent dye. They are stable over a wide range of temperature due to intermolecular disulphide bonds formed during the self-assembly process. At the same time, presence of disulphide bonds provides a redox molecular switch for their degradation. Taken together this system provides a unique avenue for multimodal formulation in cancer therapy.