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BackgroundPeri-urbanization, the expansion of large metropolitan centers into adjacent peri-urban regions, is a growing concern due to land scarcity and escalating housing costs. These zones, a blend of rural and urban features, blur the line between urban and rural areas, creating new landscapes. This study examines historical, present, and potential growth trends in the peri-urban area surrounding Durgapur Municipal Corporation (DMC). Analytical techniques and spatial metrics are used to track development intensity changes over time, including built-up density, Shannon’s entropy, Landscape expansion index, Average Weighted Mean Expansion Index, Annual Built-Up Expansion Rate, Built-Up Expansion Intensity Index, and Built-Up Expansion Difference Index. Landscape indices like Patch Density, Edge Density, Landscape Shape Index, Largest Patch Index, Ratio of Open Space, and Area Weighted Mean Patch Fractal are used to understand fragmentation, connectivity, and spatial relationships. The Logistic Regression Model (LRM) is used to identify influencing factors and CA-Markov modeling for future built-up areas.ResultsBetween 1991 and 2001, built-up area in the region increased significantly, primarily due to urban development near industrial zones, roadways, and mining areas. The growth was primarily concentrated in the western sector and near National Highway-2 (NH-2). Urban sprawl was a continuous trend, with the highest built-up density in the South-South-East (SSE) direction from 1991 to 2011. Additionally, a key determinant of built-up development was the distance to the city core. By 2031, the built-up area is expected to concentrate in the western and southeast regions, reaching 177.90 km2.ConclusionsThis expansion is attributed to urban development near industrial zones, roadways, mining areas, and other infrastructure. The study identifies distance to the city center as a significant influencing factor for built-up development. The results emphasize the need for inclusive urban planning methods prioritizing sustainable development principles and prudent resource management for future growth and efficient management in the DMC’s peri-urban area.

The antiproliferative action of 2-methoxyestradiol (2-ME), an endogenous estrogen metabolite is specific for cancer cells and is mediated by the induction of programmed cell death or apoptosis. But the identity of the downstream effectors of apoptotic signaling induced by 2-ME is not known. In the present study, we explored the effect of 2-ME on apoptosis in a panel of human pancreatic cancer cell lines. We have identified two categories of pancreatic cancer cell lines, which are either sensitive to 2-ME such as MIA PaCa-2, CFPAC-1, PANC-1, or non-sensitive to 2-ME such as Hs 766T. The results presented here indicated that the cell lines responsive to 2-ME could undergo apoptosis either by G2-M arrest (PANC-1) with Bcl-x(L) phosphorylation or by the accumulation of tetraploid cells in G1-S region (MIA PaCa-2) without Bcl-2/ Bcl-x(L) phosphorylation. Furthermore, 2-ME induced apoptosis in pancreatic cancer cells is mitochondria dependent as evident by the release of cytochrome c into the cytosol. 2-ME exposed cells exhibit Bid cleavage that is accompanied by the translocation of Bax into the mitochondria. Also 2-ME could induce phosphorylation of Bcl-x(L) in G2-M arrested cells, thus indicating the involvement of various anti- and pro-apoptotic regulators in the signaling cascade. The dissection of differential response of pancreatic cancer cell lines holds promise for future therapeutic intervention.

Over the past decade, West Bengal has witnessed an extraordinary rise in the number of Census Towns (CTs), with the state’s urban population swelling by an additional 6.6 million people. This significant increase in both CTs and urban residents has escalated the demand for essential urban services. Consequently, this article aims to examine the disparity in urbanity levels between Proximate Census Towns (PCTs) and Non-Proximate Census Towns (NPCTs). The Kolkata Metropolitan Area has been selected as a case study for this investigation. Utilizing data from the 2011 Census of India and the Socio-Economic and Caste Census, a composite urbanity index has been derived from a set of variables using the Analytic Hierarchy Process method. To determine the significant differences between the variables of PCTs and NPCTs, an independent T-test has been conducted. Furthermore, to analyze the differences in urbanity index categories between PCTs and NPCTs, one-way ANOVA and Post Hoc Tukey tests have been performed. The study’s findings reveal a statistically significant disparity between PCTs and NPCTs, with PCTs predominantly falling into the moderate and high urbanity categories, whereas the majority of NPCTs are categorized as low in terms of urbanity index. This research could be instrumental for urban planners and policymakers in identifying the root causes of inequality in basic urban services between PCTs and NPCTs, thereby aiding in the formulation of tailored policies for both types of Census Towns.

The bcl-2 protein plays a central role in the regulation of programmed cell death in a variety of tissues and is pivotal to the survival of lymphocytes in vivo. The growth factors responsible for survival of normal lymphocytes are unknown but are likely to maintain viability in part through the regulation of bcl-2 expression. A subset of human natural killer (NK) cells (CD3-CD56bright) are unique among lymphocytes in their constitutive expression of c-kit, a tyrosine kinase cell surface receptor that binds c-kit ligand (KL). Alone, KL does not promote proliferation or further differentiation of CD56brightNK cells. We now report that, in the absence of serum or additional growth factors, KL prevents apoptosis of cultured CD56brightNK cells, as assessed by DNA fragmentation studies, and maintains viability, as measured by biologic responses (i.e., proliferation and cytotoxicity) to the subsequent addition of other cytokines. Furthermore, we demonstrate that KL induces CD56brightNK cells to express the bcl-2 protein. In the presence of anti-c-kit antibody, the tyrosine kinase inhibitor genistein, or bcl-2 antisense oligonucleotide, the protective effect of KL on the survival of CD56brightNK cells is dramatically reduced. These data demonstrate that the binding of KL to its tyrosine kinase receptor results in the upregulation of bcl-2, thereby preventing apoptosis in this subset of normal human lymphocytes. As soluble KL is plentiful in normal human serum, this survival mechanism may be operative for CD56brightNK cells in vivo.

The antiapoptosis potential of Bcl-2 protein is well established, but the mechanism of Bcl-2 action is still poorly understood. Using the phosphatase inhibitor okadaic acid or the chemotherapeutic drug taxol, we found that Bcl-2 was phosphorylated in lymphoid cells. Phospho amino acid analysis revealed that Bcl-2 was phosphorylated on serine. Under similar conditions, okadaic acid or taxol treatment led to the induction of apoptosis in these cells. Thus, phosphorylation of Bcl-2 seems to inhibit its ability to interfere with apoptosis. In addition, phosphorylated Bcl-2 can no longer prevent lipid peroxidation as required to protect cells from apoptosis.

This paper reports the measurement of radon concentration in well water at the site of Jalpaiguri (26°32′N, 88°46′E) near the active fault zone of West Bengal, India. Radon concentration has been measured in well water with the help of solid-state nuclear track detectors (SSNTD). The study indicates a positive correlation between radon anomaly and earthquake. The data of radon content in well water have been compared with that in soil gas at the same site.

A survey of radon concentration in the soil gas in order to get premonitory signal of arthquakes is being carried out by us since last 4 years in Kolkata, West Bengal, Indiawhich is known to be situated at non-active fault zone and since last 2 years in an active fault zoneJalpaiguri (26A32BN, 88 A46BE), West Bengal. In extension of our work we have started the experiment in another active fault zone: Matigara, Darjeeling (2643' N, 8823'E), West Bengal, India, to have more confirmatory signal. We present the description of signal of the terrestrial gas 222Radon observed for a period of more than one year at a depth of 70 cm in the soil using passive detector Solid State Nuclear Track Detector (SSNTD). The time series of radon shows a distinctive anomalous fluctuation prior to seismic events that ccurred within 1000 km from the measuring site. The results are obtained at two fault zone sites are compared and the present analysis provides further evidence in favour of using radon signal as a precursor of earthquake.

A gene-transfer approach was used to explore the function of the BCL2 (B-cell lymphoma/leukemia 2) gene in a human T-cell line, Jurkat. Though stable introduction of a BCL2 expression plasmid into Jurkat T cells was by itself insufficient, the combined transfer of BCL2 and MYC genes markedly enhanced the tumorigenicity of these cells in athymic mice. Moreover, a BCL2 antisense expression plasmid ablated tumor formation by Jurkat cells, providing further evidence that this oncogene contributes to the regulation of the in vivo growth of these human T lymphocytes. In addition to their influence on tumor formation, BCL2 sense and antisense expression plasmids increased and decreased, respectively, the in vitro survival of Jurkat T cells in serum-free medium. These observations extend to T cells the finding of synergy of BCL2 with MYC previously reported for B cells and provide evidence that BCL2 can regulate the growth of human T cells.

LITTLE is known about the biochemical or functional nature of the proteins encoded by the bcl-2 gene, which undergoes chromosomal translocation in approximately 85% of follicular lymphoma, 20% of diffuse large cell lymphoma and 10% of chronic lymphocytic leukaemia of B cells 1–5 . Translocation of bcl-2 sequences 5 from chromosome 18 to the J H segment of the immunoglobulin gene at chromosome band 14q32 in B cells results in deregulated expression of this gene, causing high steady state levels of bcl-2 messenger RNA 2 . DNA sequence data indicate that bcl-2 encodes two proteins by virtue of alternative splicing, designated as Bcl-2α and Bcl-2β, with relative molecular masses of 26,000 and 22,000 respectively 1 . Cell fractionation experiments indicate that the bcl-2 α gene product is located at the inner surface of the cell membrane, suggesting a possible role in mitogenic signal transduction 6 . We report here that Bcl-2α has GTP-binding activity and a protein sequence that suggests it belongs to the small molecular weight GTP-binding protein (G protein) family 7–16 .

This investigation explores the application of supervised machine learning regression approaches to predict various responses, including penetration, bead width, bead height, hardness, ultimate tensile strength, and percentage elongation in autogenous TIG-, A-TIG-, and TIG-welded joints of SS304H, which is considered as an advanced high-temperature resistant material. The machine learning (ML) models were constructed based on the data gathered from 50 experimental runs, considering eight key input variables: gas flow rate, torch angle, filler material, welding pass, flux application, root gap, arc gap, and heat input. A total of 80% of the collected dataset was used for training the models, while the remaining 20% was reserved for testing their performance. Six ML algorithms—Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting Regression (GBR), and Extreme Gradient Boosting (XGBoost)—were implemented to assess their predictive accuracy. Among these, the XGBoost model has demonstrated the highest predictive capability, achieving R2 scores of 0.886 for penetration, 0.926 for width, 0.915 for weld bead height, 0.868 for hardness, 0.906 for ultimate tensile strength, and 0.926 for percentage elongation, along with the lowest values of RMSE, MAE, and MSE across all responses. The outcomes establish that machine learning models, particularly XGBoost, can accurately predict welding characteristics, marking a significant advancement in the optimization of TIG welding parameters. Consequently, integrating such predictive models can substantially enhance the precision, reliability, and overall efficiency of welding processes.