• Book : ()
• Pub. Date : 2025
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• Book : ()
• Pub. Date : 2025
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Molecular clouds (MCs) are the places where stars are formed and their feedback starts to take place, regulating the evolution of galaxies. Therefore, MCs represent the critical scale at which to study how ultraviolet (UV) photons emitted by young stars are reprocessed in the far-infrared (FIR) by interaction with dust grains, thereby determining the multiwavelength continuum emission of galaxies. Our goal is to analyze the UV and IR emission of a MC at different stages of its evolution and relate its absorption and emission properties with its morphology and star formation rate. Such a study is fundamental to determining how the properties of MCs shape the emission from entire galaxies. We considered a radiation-hydrodynamic simulation of a MC with self-consistent chemistry treatment. The MC has a mass of M_ MC is resolved down to a scale of $0.06 pc$, and evolves for ≃ 2.4 Myr after the onset of star formation. We post-processed the simulation via Monte Carlo radiative transfer calculations to compute the detailed UV-to-FIR emission of the MC. Such results were compared with data from physically motivated analytical models, other simulations, and observations. We find that the simulated MC is globally UV-optically thick, but optically thin channels allow for photon escape ($0.1%-10%$), a feature that is not well captured in analytical models. The dust temperature spans a wide range (T_ dust ∼ 20-300 K) depending on the dust-to-stellar geometry, which is reproduced reasonably well by analytical models. However, the complexity of the dust temperature distribution is not captured in the analytical models, as is evidenced by the 10 K (20 K) difference in the mass (luminosity) average temperature. Indeed, the total IR luminosity is the same in all the models, but the IR emission peaks at shorter wavelengths in the analytical ones. Compared to a sample of Galactic clouds and other simulations, our spectral energy distribution (SED) is consistent with mid-IR data, but peaks at shorter wavelengths in the IR. This is due to a lack of cold dust, as a consequence of the high gas -- and thus dust -- consumption in our simulated MC. The attenuation properties of our MC change significantly with time, evolving from a Milky-Way-like relation to a flatter, featureless one. On the IRX-β plane, the MC position strongly depends on the observing direction and on its evolutionary stage. When the MC starts to disperse, the cloud settles at log( IRX) ∼ 1 and β ∼ -0.5, slightly below most of the local empirical relations. This work represents an important test for MC simulations and a first step toward the implementation of a physically informed, sub-grid model in large-scale numerical simulations to describe the emission from unresolved MC scales and its impact on the global galaxy SED.

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• Pub. Date : 2025
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Abstract Glioblastomas (GBM) are routinely treated with high doses of ionizing radiation (IR), yet these tumors recur quickly, and the recurrent tumors are highly therapy resistant. Here, we report that IR-induced senescence of tumor cells counterintuitively spurs GBM recurrence, driven by the senescence-associated secretory phenotype (SASP). We find that irradiated GBM cell lines and patient derived xenograft (PDX) cultures senesce rapidly in a p21-dependent manner. Senescent glioma cells upregulate SASP genes and secrete a panoply of SASP factors, prominently interleukin IL-6, an activator of the JAK-STAT3 pathway. These SASP factors collectively activate the JAK-STAT3 and NF-κB pathways in non-senescent GBM cells, thereby promoting tumor cell proliferation and SASP spreading. Transcriptomic analyses of irradiated GBM cells and the TCGA database reveal that the cellular inhibitor of apoptosis protein 2 (cIAP2), encoded by the BIRC3 gene, is a potential survival factor for senescent glioma cells. Senescent GBM cells not only upregulate BIRC3 but also induce BIRC3 expression and promote radioresistance in non-senescent tumor cells. We find that second mitochondria-derived activator of caspases (SMAC) mimetics targeting cIAP2 act as novel senolytics that trigger apoptosis of senescent GBM cells with minimal toxicity towards normal brain cells. Finally, using both PDX and immunocompetent mouse models of GBM, we show that the SMAC mimetic birinapant, administered as an adjuvant after radiotherapy, can eliminate senescent GBM cells and prevent the emergence of recurrent tumors. Taken together, our results clearly indicate that significant improvement in GBM patient survival may become possible in the clinic by eliminating senescent cells arising after radiotherapy.

• Book : ()
• Pub. Date : 2025
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Abstract This study aims to obtain the absorbed dose rate in outdoor air and related health risks for the Çorum province in Turkey. Absorbed gamma dose rate readings were taken from 56 stations using portable NaI(Tl) scintillation detector. The outdoor absorbed gamma dose rates (terrestrial and cosmic) varied from 21 to 110 nGyh−1 with an average value of 44.96 ± 17.27 nGyh−1. Because of the exposure of the inhabitants to the outdoor gamma the average annual effective dose was calculated as 55.14 ± 21.18 µSvy−1. The risk value of cancer for adults in this region was estimated as 1.93 × 10–4 which is below the world average.

• Book : ()
• Pub. Date : 2025
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• Book : 201(3)
• Pub. Date : 2025
• Page : pp.207-209
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Aim: To assess the prognostic value of pretreatment 18F-FDG-PET/CT quantitative metabolic parameters in patients with advanced high-grade serous ovarian cancer (HGSOC). Methods: A review of 47 patients diagnosed with advanced HGSOC between 2012 and 2020 in our center was performed, evaluating pretreatment 18F-FDG-PET/CT metabolic parameters: maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumoral volume (MTV). Two experienced nuclear medicine physicians evaluated the images, thereby obtaining quantitative parameters semiautomatically classifying the volume of interest (VOI) as the target (t): VOI with the highest SUVmax normalized by lean body mass (SUVmax(lbm)), non target (nt) and total (sum of target and non-target VOIs). The disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with ROC curves/median values were used. The Correlation between metabolic parameters and DFS/OS was determined using univariate and survival-curves analysis. Results: The median DFS was 18 months (2.5–55) and the OS 33.6 months (2.5–92). The MTVtotal, MTV(t), TLGtotal and TLG(t) were significantly associated with DFS (p = 0.005, 0.01, 0.04 and 0.04, respectively). The patients with MTVtotal > 427.8 cm3 and MTVtarget > 434 cm3 had shorter DFS than the patients with lower values (18.8 versus 31 months and 15.6 versus 30, p = 0.02 and 0.01, respectively). The patients with higher TLGtotal and TLG(t) values tended to have worse DFS (p = 0.26 and 0.31, respectively). In a multivariate analysis, the MTVtotal was statistically significantly associated with DFS (p = 0.003). No correlation was found with OS. Conclusions: Pretreatment MTVtotal and MTV(t) appear to be predictive of relapse in patients with advanced HGSOC.

• Book : 17(4)
• Pub. Date : 2025
• Page : pp.698-698
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Abstract Motivation Missing data present a pervasive challenge in data analysis, potentially biasing outcomes and undermining conclusions if not addressed properly. Missing data are commonly classified into Missing Completely at Random (MCAR), Missing at Random (MAR), and Missing Not at Random (MNAR). While MCAR poses a minimal risk of data distortion, both MAR and MNAR can seriously affect the results of subsequent analyses. Therefore, it is important to know the type of missing data and appropriately handle them. Results To facilitate efficient handling of missing data, we introduce a Python package named XeroGraph that is designed to evaluate data quality, categorize the nature of missingness, and guide imputation decisions. By comparing how various imputation methods influence underlying distributions, XeroGraph provides a systematic framework that supports more accurate and transparent analyses. Through its comprehensive preliminary assessments and user-friendly interface, this package facilitates the selection of optimal strategies tailored to the specific missing data mechanisms present in a dataset. In doing so, XeroGraph may significantly improve the validity and reproducibility of research findings, making it a valuable tool for professionals in data-intensive fields. Availability and implementation XeroGraph is compatible with all operating systems and requires Python version 3.9 or higher. It can be freely downloaded from PyPI (https://pypi.org/project/XeroGraph). The source code is accessible on GitHub (https://github.com/kazilab/XeroGraph), and comprehensive documentation is available at Read the Docs (https://xerograph.readthedocs.io). This software is distributed under the Apache License 2.0.

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• Pub. Date : 2025
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Kazakhstan’s pasture, as a spatially extended agricultural resource for sustainable animal husbandry, requires effective monitoring with connected rational uses. Ranking number nine globally in terms of land size, Kazakhstan, with an area of about three million square km, requires proper assessment technologies for climate change and anthropogenic impact to track the pasture lands’ degradation. Remote sensing (RS)-based adaptive approaches for assessing pasture load, combined with field cross-checking of pastures, have been applied to evaluate the quality of vegetation cover, economic potential, service function, regenerative capacity, pasture productivity, and changes in plant species composition for five pilot regions in Kazakhstan. The current stages of these efforts are presented in this project report. The pasture lands in five regions, including Pavlodar (8,340,064 ha), North Kazakhstan (2,871,248 ha), Akmola (5,783,503 ha), Kostanay (11,762,318 ha), Karaganda (19,709,128 ha), and Ulytau (18,260,865 ha), were evaluated. Combined RS data were processed and the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Fraction of Vegetation Cover (FCover), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Canopy Chlorophyll Content (CCC), and Canopy Water Content (CWC) indices were determined, in relation to the herbage of pastures and their growth and development, for field biophysical analysis. The highest values of LAI, FCOVER, and FARAR were recorded in the Akmola region, with index values of 18.5, 126.42, and 53.9, and the North Kazakhstan region, with index values of 17.89, 143.45, and 57.91, respectively. The massive 2024 spring floods, which occurred in the Akmola, North Kazakhstan, Kostanay, and Karaganda regions, caused many problems, particularly to civil constructions and buildings; however, these same floods had a very positive impact on pasture areas as they increased soil moisture. Further detailed investigations are ongoing to update the flood zones, wetlands, and swamp areas. The mapping of proper flood zones is required in Kazakhstan for pasture activities, rather than civil building construction. The related sustainable permissible grazing husbandry pasture loads are required to develop also. Recommendations for these preparation efforts are in the works.

• Book : 15(3)
• Pub. Date : 2025
• Page : pp.526-526
• Keyword :

The nuclear factor kappa B (NF-kB) signaling module is a complex and highly interconnected molecular network with important functions in all nucleated cells. Most chronic diseases caused by lifestyle factors appear to be related to inflammation. The NF-kB plays a major role in the pathogenesis of the inflammation and its intimate molecular mechanism. This transcription factor participates in the evolution of diabetes and its complications. In T1D (Type 1 Diabetes), proinflammatory cytokines such as interleukin-1β (IL-1β), tumor necrosis factor (TNF), and CD40L secreted by immune cells in islets induce the activation of NF-kB in β-cells through both canonical and noncanonical roads. NF-kB activation increases the expression of genes, including TNF-α, IL-1β, IL-6, MCP-1, and ICAM-1, that initiate and promote atherosclerosis. In particular, the severity and lethality of acute lung injury or acute respiratory distress syndrome (ALI/ARDS) caused by pneumonia or sepsis is primarily associated with an NF-kB-mediated “cytokine storm,” in which massive polymorphonuclear (PMN) extravasation and the subsequent release of cytokines cause rapid deterioration due to widespread inflammation and coagulation. Nuclear translocation of NF-kB p65 can induce the transcription of several genes involved in the induction of EMT (epithelial-to-mesenchymal transition). This has been confirmed in various types of cancer, including brain, breast, lung, and gastric cancer. Cutaneous T-cell lymphoma (CTCL) encompasses a group of lymphoproliferative disorders characterized by invasive neoplastic T cells in the skin and various clinical prognoses. In the early stages of CTCL, NF-kB activation and cell proliferation are stimulated by the autocrine production of TNFα, leading to increased NF-kB activation and resistance to apoptosis. Bladder cancer is the second most common genitourinary cancer and is often recurrent and/or chemoresistant after tumor resection. NF-kB is a transcription factor that plays a critical role in normal physiology and bladder cancer. Bladder cancer patients have pathologically active NF-kB induced by proinflammatory cytokines, chemokines, and hypoxia, enhancing carcinogenesis and progression of the disease.

• Book : 72()
• Pub. Date : 2025
• Page : pp.1-13
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