Search Results (23)

Background: Arthritis, a debilitating joint disease, remains a significant global health burden. This study uncovers the therapeutic potential of the medicinal plant Smilax glabra Roxb. (SGR) in attenuating progression of disease by modulating immune responses. Methods: Through computational approaches, key bioactive compounds in SGR were identified by using freely available databases: TCMSP, TCMID, HIT2.0, HERB, and INPUT in order to elucidate their underlying mechanisms of action. Therapeutic targets for the disease have been retrieved by TTD, GeneCard, and OMIM databases. The STRING database was used to analyze the protein–protein interactions (PPI) of intersecting genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to reveal the functional roles of genes. Mcule was used for molecular docking and binding affinity of compounds and targets were evaluated by DeepPurpose model. ALP activity, cell viability assay, TRAP staining were also performed. Results: A total of 14 active SGR compounds with 59 common targets for arthritis have been identified. These targets have a major role in controlling biological processes such as wound healing, oxygen responses, and chemical stimuli. Molecular docking by Mcule platform demonstrated that quercetin and β-sitosterol showed higher binding energy affinities with TNF, TP53, PTGS2, and JUN as compared to other targets. To explore the complex relationship between compounds and targets, pre-trained Davis and KIBA models were used to predict the affinity values of selected compounds. In MC3T3-E1 cells, ALP activity was significantly increased and bone marrow macrophages (BMM) showed a low number of TRAP-positive cells in SGR-treated cells. Conclusions: Our findings demonstrate that SGR effectively inhibits/regulates inflammatory responses, prevents cartilage degradation, promotes bone regeneration, and can be used as a promising candidate for the development of novel arthritis treatment. Full article

The KEPCO Nuclear Fuel Company (KNF) has undertaken considerable efforts to improve the KARMA/ASTRA nuclear design code system to meet the increasing demand for high-fidelity core analyses. Through years of effort, the KARMA lattice transport code based on the method of characteristics (MOC) has evolved into KARMA2, a direct whole core calculation code using a 3D calculation method based on planar (2D) MOC principles. Simultaneously, ASTRA2, designed as the successor to the ASTRA nodal diffusion code, has been developed. ASTRA2 exhibits enhanced capabilities in multigroup pin-by-pin core calculations, achieved by decoupling the 3D whole core problem into a series of planar and axial problems. The domain size of each axial problem can be adjusted, ranging from pin-cell to assembly scale, thereby optimizing efficiency. The verification and validation process of the KARMA2/ASTRA2 code system involves various benchmark problems and measured data from operational PWRs. In this study, the APR1400 benchmark analysis was performed to verify the neutronics calculation capabilities of both codes. The results underscore the reliability and accuracy of the KARMA2 solutions across various core conditions, exhibiting close agreement with the McCARD reference solutions. Similarly, the ASTRA2 results agree with the corresponding KARMA2 results. These successful results demonstrate the high-fidelity core calculation capabilities of KNF’s next-generation code system. Full article

Obesity, a chronic, preventable disease, has significant comorbidities that are associated with a great human and financial cost for society. The aim of the present work is to reconstruct the interactomes of non-hereditary obesity to highlight recent advances of its pathogenesis, and discover potential therapeutic targets. Obesity and biological-clock-related genes and/or gene products were extracted from the biomedical literature databases PubMed, GeneCards and OMIM. Their interactions were investigated using STRING v11.0 (a database of known and predicted physical and indirect associations among genes/proteins), and a high confidence interaction score of >0.7 was set. We also applied virtual screening to discover natural compounds targeting obesity- and circadian-clock-associated proteins. Two updated and comprehensive interactomes, the (a) stress- and (b) inflammation-induced obesidomes involving 85 and 93 gene/gene products of known and/or predicted interactions with an average node degree of 9.41 and 10.8, respectively, were produced. Moreover, 15 of these were common between the two non-hereditary entities, namely, ADIPOQ, ADRB2/3, CCK, CRH, CXCL8, FOS, GCG, GNRH1, IGF1, INS, LEP, MC4R, NPY and POMC, while phelligridin E, a natural product, may function as a potent FOX1-DBD interaction blocker. Molecular networks may contribute to the understanding of the integrated regulation of energy balance/obesity pathogenesis and may associate chronopharmacology schemes with natural products. Full article

In this study, a similarity coefficient generation code system was established using the Monte Carlo Code for Advanced Reactor Design (McCARD) transport code and the MIG multi-correlated input sampling code. We considered the adjoint-based sensitivity and uncertainty (S/U) and stochastic sampling (S.S.) approaches to the generation of the c_k similarity coefficient. To examine the code system, the c_k similarity coefficients of 23 relevant critical experiments and the System-Integrated Modular Advanced Reactor (SMART) small modular reactor (SMR) target system were generated using ENDF/B-VII.1 covariance data with the Los Alamos National Laboratory (LANL) 30-group energy group structure. Our results show that the similarity coefficients between the 16 LEU thermal-spectrum-based critical experiments and SMART are more than 0.90, which is the recommended criterion of the U.S. Nuclear Regulatory Commission (NRC). These results are very helpful for licensees and can be used to justify the determination of critical experiment benchmarks for computational bias estimations of the SMART target system. To examine the discrepancy in the similarity coefficient, c_k, due to the covariance data, similarity analyses for a 24 × 24 benchmark matrix were performed using ENDF-VIII.0, JENDL-5.0, and JEFF-3.3 covariance data. The results show that the selection of the covariance data used for c_k generation significantly impacts the similarity coefficient. Moreover, it was observed that the current results for the SCALE 6.1 covariance data show a consistent trend with the results reported in earlier studies. Full article

Objective: The therapeutic efficacy and molecular mechanisms of traditional Chinese medicines (TCMs), such as Liuwei Dihuang pills (LWDH pills), in treating osteoporosis (OP) remain an area of active research and interest in modern medicine. This study investigated the mechanistic underpinnings of LWDH pills in the treatment of OP based on network pharmacology, bioinformatics, and in vitro experiments. Methods: The active ingredients and targets of LWDH pills were retrieved through the TCMSP database. OP-related targets were identified using the CTD, GeneCards, and DisGeNET databases. The STRING platform was employed to construct a protein–protein interaction (PPI) network, and core targets for LWDH pills in treating OP were identified. The GO functional and KEGG pathway enrichment analyses for potential targets were performed using the R package “clusterProfiler”. A “drug–target” network diagram was created using Cytoscape 3.7.1 software. The viability of MC3T3-E1 cells was evaluated using the CCK-8 method after treatment with various concentrations (1.25%, 2.5%, 5%, and 10%) of LWDH pill-medicated serum for 24, 48, and 72 h. Following a 48 h treatment of MC3T3-E1 cells with LWDH pill-medicated serum, the protein levels of collagen Ⅰ, RUNX2, Wnt3, and β-catenin were quantified using the Western blot analysis, and the activity of alkaline phosphatase (ALP) was measured. Results: A total of 197 putative targets for LWDH pills for OP treatment were pinpointed, from which 20 core targets were singled out, including TP53, JUN, TNF, CTNNB1 (β-catenin), and GSK3B. The putative targets were predominantly involved in signaling pathways such as the Wnt signaling pathway, the MAPK signaling pathway, and the PI3K-Akt signaling pathway. The intervention with LWDH pill-medicated serum for 24, 48, and 72 h did not result in any notable alterations in the cell viability of MC3T3-E1 cells relative to the control group (all p > 0.05). Significant upregulation in protein levels of collagen Ⅰ, RUNX2, Wnt3, and β-catenin in MC3T3-E1 cells was observed in response to the treatment with 2.5%, 5%, and 10% of LWDH pill-medicated serum in comparison to that with the 10% rabbit serum group (all p < 0.05). Furthermore, the intervention with LWDH pill-medicated serum resulted in the formation of red calcified nodules in MC3T3-E1 cells, as indicated by ARS staining. Conclusions: LWDH pills may upregulate the Wnt/β-catenin signaling pathway to elevate the expression of osteogenic differentiation proteins, including collagen Ⅰ and RUNX2, and to increase the ALP activity in MC3T3-E1 cells for the treatment of OP. Full article

Backgound: Pyeongwi-san (PWS) is a widely used formula for treating digestive disorders in Korea and China. Inflammatory bowel disease (IBD) is characterized by progressive inflammation of the gastrointestinal tract. Emerging evidence supports the protective effect of PWS against IBD, but specific mechanisms are still elusive. Methods: Active compounds of PWS were screened from the medicinal materials and chemical compounds in Northeast Asian traditional medicine (TM-MC) in the consideration of drug-likeness and oral bioavailability. Target candidates of active compounds were predicted using the ChEMBL database. IBD-related targets were obtained from the GeneCards and DisGeNET databases. The network of composition-targets-disease was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Molecular docking was used to simulate the binding affinity of active compounds on target proteins and molecular dynamics was used to validate the molecular docking result. Results: A total of 26 core target proteins of PWS were related to IBD. Enrichment analysis suggested that PWS is highly associated with tumor necrosis factor signaling pathway, apoptosis, and the collapse of tight junctions. Moreover, molecular docking and molecular dynamics simulation proposed β-eudesmol and (3R,6R,7S)-1,10-bisaboladien-3-ol to ameliorate IBD through the binding to TNF and MMP9, respectively. Conclusion: Present in silico analysis revealed potential pathways and insight of PWS to regulate IBD. These results imply that the therapeutic effect of PWS might be achieved via an inhibitory effect. Full article

High repetition rate lidar is typically equipped with a low-energy, high repetition rate laser, and small aperture telescopes. Therefore, it is small, compact, low-cost, and can be networked for observation. However, its data acquisition and control functions are generally not specially designed, and the data acquisition, storage, and control programs need to be implemented on an IPC (Industrial Personal Computer), which increases the complexity and instability of the lidar system. Therefore, this paper designs an integrated off-line echo signal acquisition system (IOESAS) for lidar developed based on SoC FPGA (System-On-Chip Field Programmable Gate Array). Using a hardware–software co-design approach, the system is implemented in a heterogeneous multi-core chip ZYNQ-7020 (integrated FPGA and ARM). The FPGA implements dual-channel echo data acquisition (gated counting and hardware accumulation). At the same time, the ARM performs laser control and monitoring, laser pointing control, pulse energy monitoring, data storage, and wireless transmission. Offline data acquisition and control software was developed based on LabVIEW, which can remotely control the status of the lidar and download the echo data stored in IOESAS. To verify the performance of the data acquisition system, IOESAS was compared with the photon counting card P7882 and MCS-PCI, respectively. The test results show that they are in good agreement; the linear correlation coefficients were 0.99967 and 0.99884, respectively. IOESAS was installed on lidar outdoors for continuous detection, and the system was able to work independently and stably in different weather conditions, and control functions were tested normally. The gating delay and gating width time jitter error are ±5 ns and ±2 ns, respectively. The IOESAS is now used in several small lidars for networked observations. Full article

Background: SARS-CoV-2 related immunopathology may be the driving cause underlying severe COVID-19. Through an immunophenotyping analysis on paired bronchoalveolar lavage fluid (BALF) and blood samples collected from mechanically ventilated patients with COVID-19-associated Acute Respiratory Distress Syndrome (CARDS), this study aimed to evaluate the cellular immune responses in survivors and non-survivors of COVID-19. Methods: A total of 36 paired clinical samples of bronchoalveolar lavage fluid (BALF) mononuclear cells (BALF-MC) and peripheral blood mononuclear cells (PBMC) were collected from 18 SARS-CoV-2-infected subjects admitted to the intensive care unit (ICU) of the Policlinico Umberto I, Sapienza University Hospital in Rome (Italy) for severe interstitial pneumonia. The frequencies of monocytes (total, classical, intermediate and non-classical) and Natural Killer (NK) cell subsets (total, CD56^bright and CD56^dim), as well as CD4⁺ and CD8⁺ T cell subsets [naïve, central memory (TCM) and effector memory (TEM)], and those expressing CD38 and/or HLADR were evaluated by multiparametric flow cytometry. Results: Survivors with CARDS exhibited higher frequencies of classical monocytes in blood compared to non-survivors (p < 0.05), while no differences in the frequencies of the other monocytes, NK cell and T cell subsets were recorded between these two groups of patients (p > 0.05). The only exception was for peripheral naïve CD4⁺ T cells levels that were reduced in non-survivors (p = 0.04). An increase in the levels of CD56^bright (p = 0.012) and a decrease in CD56^dim (p = 0.002) NK cell frequencies was also observed in BALF-MC samples compared to PBMC in deceased COVID-19 patients. Total CD4⁺ and CD8⁺ T cell levels in the lung compartment were lower compared to blood (p = 0.002 and p < 0.01, respectively) among non-survivors. Moreover, CD38 and HLA-DR were differentially expressed by CD4⁺ and CD8⁺ T cell subsets in BALF-MC and in PBMC among SARS-CoV-2-infected patients who died from COVID-19 (p < 0.05). Conclusions: These results show that the immune cellular profile in blood and pulmonary compartments was similar in survivors and non-survivors of COVID-19. T lymphocyte levels were reduced, but resulted highly immune-activated in the lung compartment of patients who faced a fatal outcome. Full article

Background: Investigating the health-related quality of life (HRQoL) after intensive care unit (ICU) discharge is necessary to identify possible modifiable risk factors. The primary aim of this study was to investigate the HRQoL in COVID-19 critically ill patients one year after ICU discharge. Methods: In this multicenter prospective observational study, COVID-19 patients admitted to nine ICUs from 1 March 2020 to 28 February 2021 in Italy were enrolled. One year after ICU discharge, patients were required to fill in short-form health survey 36 (SF-36) and impact of event-revised (IES-R) questionnaire. A multivariate linear or logistic regression analysis to search for factors associated with a lower HRQoL and post-traumatic stress disorded (PTSD) were carried out, respectively. Results: Among 1003 patients screened, 343 (median age 63 years [57–70]) were enrolled. Mechanical ventilation lasted for a median of 10 days [2–20]. Physical functioning (PF 85 [60–95]), physical role (PR 75 [0–100]), emotional role (RE 100 [33–100]), bodily pain (BP 77.5 [45–100]), social functioning (SF 75 [50–100]), general health (GH 55 [35–72]), vitality (VT 55 [40–70]), mental health (MH 68 [52–84]) and health change (HC 50 [25–75]) describe the SF-36 items. A median physical component summary (PCS) and mental component summary (MCS) scores were 45.9 (36.5–53.5) and 51.7 (48.8–54.3), respectively, considering 50 as the normal value of the healthy general population. In all, 109 patients (31.8%) tested positive for post-traumatic stress disorder, also reporting a significantly worse HRQoL in all SF-36 domains. The female gender, history of cardiovascular disease, liver disease and length of hospital stay negatively affected the HRQoL. Weight at follow-up was a risk factor for PTSD (OR 1.02, p = 0.03). Conclusions: The HRQoL in COVID-19 ARDS (C-ARDS) patients was reduced regarding the PCS, while the median MCS value was slightly above normal. Some risk factors for a lower HRQoL have been identified, the presence of PTSD is one of them. Further research is warranted to better identify the possible factors affecting the HRQoL in C-ARDS. Full article

In the reactivity measurements of the China Experimental Fast Reactor (CEFR) start-up tests, five independent control rods were moved to compensate for the reactivity insertion. Since the recorded control rod positions were converted to reactivity via S-curves (rod worth curves), any uncertainty in the S-curves can propagate to all reactivity measurements. In this work, we rigorously derived the uncertainty of the reactivity in terms of the statistical uncertainty of the S-curves with Monte Carlo (MC) simulations. Additionally, the average error of the control rod worth from the MC calculation was estimated from experiments and embedded into the uncertainty formulation. The formulation shows that the error of the reactivity is highly correlated to the changes in the control rod position during the reactivity measurements. McCARD MC simulations were then conducted for the CEFR start-up tests, and the calculated reactivity and uncertainty were compared with the measurements. The main error factor of each reactivity calculation was figured out by quantifying the uncertainty components. With the uncertainty formulation, the calculation results showed a better agreement compared with the measurements, as the relative errors were observed mostly within $2\sigma$ of the uncertainty. Full article

Low and high birth weight (BW) are associated with obesity later in life; however, this association has not been extensively studied in African countries. This study determines the association between BW and body composition derived from deuterium oxide (D₂O) dilution in 6- to 8-year-old South African children (n = 91; 40 boys, 51 girls). BW was recorded retrospectively from the children’s Road-to-Health cards. Weight and height were measured using standard procedures, and D₂O dilution was used to determine total body water and, subsequently, to determine body fat. Fatness was classified using the McCarthy centiles, set at 2nd, 85th, and 95th (underfat, overfat and obese). BW correlated with body composition measures, such as body weight (r = 0.23, p = 0.03), height (r = 0.33, p < 0.001), and fat free mass (FFM; r = 0.27, p = 0.01). When multiple regression analysis was employed, BW significantly and positively associated with FFM (β = 0.24, p = 0.013; 95% CI: 0.032; 0.441) and fat mass (β = 0.21, p = 0.02, 95%CI: 0.001; 0.412) in girls and boys combined. A total of 13% of the children had a low BW, with 21% being overweight and 17% obese. More girls than boys were overweight and obese. Intervention strategies that promote healthy uterine growth for optimal BW are needed in order to curb the global obesity pandemic. Full article

The performance of the Monte Carlo (MC) algorithm for calibration-free LIBS was studied on the example of a simulated spectrum that mimics a metallurgical slag sample. The underlying model is that of a uniform, isothermal, and stationary plasma in local thermodynamical equilibrium. Based on the model, the algorithm generates from hundreds of thousands to several millions of simultaneous configurations of plasma parameters and the corresponding number of spectra. The parameters are temperature, plasma size, and concentrations of species. They are iterated until a cost function, which indicates a difference between synthetic and simulated slag spectra, reaches its minimum. After finding the minimum, the concentrations of species are read from the model and compared to the certified values. The algorithm is parallelized on a graphical processing unit (GPU) to reduce computational time. The minimization of the cost function takes several minutes on the GPU NVIDIA Tesla K40 card and depends on the number of elements to be iterated. The intrinsic accuracy of the MC calibration-free method is found to be around 1% for the eight elements tested. For a real experimental spectrum, however, the efficiency may turn out to be worse due to the idealistic nature of the model, as well as incorrectly chosen experimental conditions. Factors influencing the performance of the method are discussed. Full article

International Criticality Safety Benchmark Evaluation Project (ICSBEP) criticality analyses were conducted using the McCARD Monte Carlo code for 85 selected benchmark problems with 7 evaluated nuclear data libraries (ENDLs): ENDF/B-VII.1, ENDF/B-VIII.0, JENDL-4.0, JENDL-5.0, JEFF-3.3, TENDL-2021, and CENDL-3.2. Regarding the analyses, it was confirmed that the k_eff results are sensitive to the ENDL. It is noted that the new-version ENDLs show better performance in the fast benchmark cases, while on the other hand, there are no significant differences in k_eff among the different ENDLs in the thermal benchmark cases. The sensitivity of the k_eff results depending on the ENDL may impact nuclear core design parameters such as the shutdown margin, critical boron concentration, and power defects. This study and k_eff results will be a good reference in the development of new types of nuclear cores or new design codes. Full article

This work aims to fabricate a large-area ceramic substrate for the application of probe cards. Mullite (M) and cordierite (C), which both have a low thermal expansion coefficient, excellent resistance to thermal shock, and high durability, were selected as starting powders. The mullite–cordierite composites were produced through different composition ratios of starting powders (M:C = 100:0, M:C = 90:10, M:C = 70:30, M:C = 50:50, M:C = 30:70, and M:C = 0:100). The effects of composition ratio and sintering temperature on the density, porosity, thermal expansion coefficient, and flexural strength of the mullite–cordierite composite pellets were investigated. The results showed that the mullite–cordierite composite pellet containing 70 wt% mullite and 30 wt% cordierite sintered at 1350 °C performed exceptionally well. Based on these findings, a large-area mullite–cordierite composite substrate with a diameter of 320 mm for use in semiconductor probe cards was successfully fabricated. Additionally, the changes in sheet resistance and flexural strength were measured to determine the effect of the environmental tests on the large-area substrate such as damp heat and thermal shock. The results indicated that the mullite–cordierite composite substrate was extremely reliable and durable. Full article

For ground-based lidars in atmospheric observation, their data acquisition unit and control unit usually work independently. They usually require the cooperation of large-volume, high-power-consumption Industrial Personal Computer (IPC). However, the space-borne lidar has high requirements on the stability and integration of the acquisition control system. In this paper, a new data acquisition and lidar control system (DALCS) was developed based on System-on-Chip Field-Programmable Gate Array (SoC FPGA) technology. It can be used in lidar systems with high repetition rate and photon-counting mode and has functions such as data storage, laser control, automatic collimation, wireless communication, and fault self-test. DALCS has two working modes: in online mode, the echo data collected by DALCS are transmitted to the computer for display in real-time and then stored with the current time as the file name; in offline mode, the data are stored in local non-volatile memory, which can be read remotely and can work autonomously when there is no IPC. The test results showed that in the frequency range of 0–70 M, the counting linearity of DALCS reached 0.9999, and the maximum relative error between the DALCS card and the standard signal source was 0.211%. The comparison results showed that the correlation coefficient between DALCS and MCS-PCI was as high as 0.99768. The DALCS was placed in a self-developed lidar sensor system for continuous observation, and the system worked stably under different weather conditions. The range-squared-corrected signal profiles obtained from the observations reflect the spatial and temporal distribution characteristics of aerosols and clouds well. This provides scheme verification and experimental support for the development of space-borne lidar data acquisition and control system. Full article