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In this study, the trajectory mapping domain-filling technology, which can provide more reliable statistical estimates of long-lived gas concentrations in a broader geographical area based on limited station data, is used to map the CO2 concentration data of six ground observation stations to the entire Shanxi Province. The technology combines a dynamical model of the atmosphere with trace gas observations, combining forward and backward trajectories to greatly expand the information on long-lived CO2 gas concentrations over a trajectory path. The mapped results show good agreement with the observation results, which reveals the generalizability of the trajectory mapping domain-filling technology. The results show that the spatio-temporal distribution characteristics of CO2 concentration in the entire Shanxi region is significant: during the five years, the provincial average CO2 concentration exhibits an overall increasing trend. The CO2 concentration increases from the north to the south across the province. Influenced by the economic growth rate and COVID-19, there are differences in the annual variation characteristics of the CO2 concentration across the entire province, with the highest year-on-year growth in 2019 and a year-on-year decrease in 2020. The increasing rate of the CO2 concentration in the northern low-value areas is faster than that in the southern high-value areas. Overall, there is a decreasing trend in the CO2 concentration growth from the north to the south in the entire province. There are seasonal differences in the CO2 concentration distribution across the entire province. The CO2 concentration and amplitude are higher in autumn and winter than they are in spring and summer. This study can provide scientific support and methodological reference for the spatio-temporal distribution characteristics analysis of GHGs at the provincial–regional scale, as well as at the national and global scales. [ABSTRACT FROM AUTHOR]

In order to study the mechanical properties of inverted cone bottom oil storage tanks under earthquakes when the foundation is uneven, finite element modeling calculation for a 20,000 m3 storage tank is carried out based on ANSYS Workbench. Wind load, hydraulic pressure load, and seismic load are all equalized as distributed loads with varying spatial positions. Considering various combinations of different heterogeneous foundations and seismic loads, and by adjusting the preset foundation bed coefficient, the final foundation bed coefficient and the maximum foundation settlement value when the equivalent stress of the tank floor reaches yield strength under different conditions are calculated. The results show that under the condition of heterogeneous foundation stiffness considering seismic action, when the coefficient of local foundation bed is higher than that of natural silty clay, the requirement for safe use of the inverted cone bottom storage tank can be met. Among the seven simulated heterogeneous foundation forms, the form with high foundation stiffness on the windward side has a great influence on the safety of storage tanks. [ABSTRACT FROM AUTHOR]

Background: Mining gene regulatory network (GRN) is an important avenue for addressing cancer mechanism. Mutations in cancer genome perturb GRN and cause a rewiring in an orchestrated network. Hence, the exploration of gene regulatory network rewiring is significant to discover potential biomarkers and indicators for discriminating cancer phenotypes. Results: Here, we propose a new bioinformatics method of identifying biomarkers based on network rewiring in different states. It firstly reconstructs GRN in different phenotypic conditions from gene expression data with a priori background network. We employ the algorithm based on path consistency algorithm and conditional mutual information to delete false-positive regulatory interactions between independent nodes/genes or not closely related gene pairs. And then a differential gene regulatory network (D-GRN) is constructed from the rewiring parts in the two phenotype-specific GRNs. Community detection technique is then applied for D-GRN to detect functional modules. Finally, we apply logistic regression classifier with recursive feature elimination to select biomarker genes in each module individually. The extracted feature genes result in a gene set of biomarkers with impressing ability to distinguish normal samples from controls. We verify the identified biomarkers in external independent validation datasets. For a proof-of-concept study, we apply the framework to identify diagnostic biomarkers of breast cancer. The identified biomarkers obtain a maximum AUC of 0.985 in the internal sample classification experiments. And these biomarkers achieve a maximum AUC of 0.989 in the external validations. Conclusion: In conclusion, network rewiring reveals significant differences between different phenotypes, which indicating cancer dysfunctional mechanisms. With the development of sequencing technology, the amount and quality of gene expression data become available. Condition-specific gene regulatory networks that are close to the real regulations in different states will be established. Revealing the network rewiring will greatly benefit the discovery of biomarkers or signatures for phenotypes. D-GRN is a general method to meet this demand of deciphering the high-throughput data for biomarker discovery. It is also easy to be extended for identifying biomarkers of other complex diseases beyond breast cancer. [ABSTRACT FROM AUTHOR]

Few-layer and 1T-rich MoS2 is synthesized by a one-step solvothermal process using a rigid segment-containing polysulfide as a concomitant sulfur source and in situ intercalator. The prepared MoS2 displays superior hydrogen evolution reaction activity, providing a facile and mild approach for the development of high performing MoS2 and other two-dimensional lamellar materials. [ABSTRACT FROM AUTHOR]

A nitrogen doped bio-carbon catalyst with high specific surface area and a hierarchical interconnected porous structure was fabricated by an in situ gas-foaming strategy from sodium alginate and ammonium chloride. The optimized catalyst displays a fabulous ORR activity, providing a facile approach for the mass production of metal-free bio-carbon catalysts in fuel cells and metal–air batteries. [ABSTRACT FROM AUTHOR]

Abstract: Microparticles can serve as substrates for cell amplification and deliver the expanded cells to the site of the defect. It was hypothesized that a novel microparticle combined of sustained and localized delivery of proliferative growth factors and gyrus-patterned surface would influence the cell behaviours of adherence and expansion on the microparticle in the present study. To test the hypothesis, gelatin particles with diameter ranging from 280 to 350 µm were fabricated and were modified by cryogenic freeze-drying treatment and basic fibroblast growth factor (bFGF) incorporation. The results of in vitro chondrocyte culture illustrated that cells could proliferate more obviously on the microparticles with bFGF addition, but no correlation between attachment rate and bFGF was observed. On the other hand, microparticles with gyrus-patterned surface demonstrated the highest cell attachment rate and higher rate of cell growth, in particular on bFGF combined ones. It seems to be a promising candidate as a chondrocyte microparticle and could be the potential application in cartilage tissue engineering. [Copyright &y& Elsevier]

This article discusses a study on the synthesis of temperature and pH-sensitive poly(acrylic acid-g-N-isopropylacrylamide)(P(AA-g-NIPAM)) graft copolymers. The study used a macromonomer technique in the synthesis of the copolymers free-radical copolymerization. It employed ultraviolet-vis transmittance measurements, fluorescence probe and fluorescence quenching techniques in the phase behavior and conformation change of P(AA-g-NIPAM) in aqueous solutions.

Photothermal therapy using near‐infrared radiation and local heating agents can induce selective tumor ablation with limited harm to the surrounding normal tissue. Graphene sheets are promising local heating agents because of their strong absorbance of near‐infrared radiation. Experimental studies have been conducted to study the heating effect of graphene in photothermal therapy, yet few efforts have been devoted to the quantitative understanding of energy conversion and transport in such systems. Herein, a computational study of cancer photothermal therapy using near‐infrared radiation and graphene is presented using a Monte Carlo approach. A three‐dimensional model was built with a cancer cell inside a cube of healthy tissue. Functionalized graphene nanosheets were randomly distributed on the surface of the cancer cell. The effects of the concentration and morphology of the graphene nanosheets on the thermal behavior of the system were quantitatively investigated. The interfacial thermal resistance around the graphene sheets, which affects the transfer of heat in the nanoscale, was also varied to probe its effect on the temperature increase of the cancer cell and the healthy tissue. The results of this study could guide researchers to optimize photothermal therapy with graphene, while the modeling approach has the potential to be applied for investigating alternative treatment plans. [ABSTRACT FROM AUTHOR]

Poultry farming is an indispensable part of global agriculture, playing a crucial role in food safety and economic development. Managing and preventing diseases is a vital task in the poultry industry, where semantic segmentation technology can significantly enhance the efficiency of traditional manual monitoring methods. Furthermore, traditional semantic segmentation has achieved excellent results on extensively manually annotated datasets, facilitating real-time monitoring of poultry. Nonetheless, the model encounters limitations when exposed to new environments, diverse breeding varieties, or varying growth stages within the same species, necessitating extensive data retraining. Overreliance on large datasets results in higher costs for manual annotations and deployment delays, thus hindering practical applicability. To address this issue, our study introduces HSDNet, an innovative semantic segmentation model based on few-shot learning, for monitoring poultry farms. The HSDNet model adeptly adjusts to new settings or species with a single image input while maintaining substantial accuracy. In the specific context of poultry breeding, characterized by small congregating animals and the inherent complexities of agricultural environments, issues of non-smooth losses arise, potentially compromising accuracy. HSDNet incorporates a Sharpness-Aware Minimization (SAM) strategy to counteract these challenges. Furthermore, by considering the effects of imbalanced loss on convergence, HSDNet mitigates the overfitting issue induced by few-shot learning. Empirical findings underscore HSDNet's proficiency in poultry breeding settings, exhibiting a significant 72.89% semantic segmentation accuracy on single images, which is higher than SOTA's 68.85%., Competing Interests: The authors declare that they have no competing interests., (© 2024 Liu et al.)

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3 , were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Acute coronary syndrome (ACS) is one of the main syndromes of coronary artery disease with high mortality. The identification of biomarkers associated with disease occurrence and progression could improve early detection and risk prediction. This study was aimed to reveal the clinical significance and function of miR-3646 in ACS.The expression of miR-3646 was evaluated in ACS patients, healthy volunteers, and non-ACS patients and estimated the clinical significance of miR-3646. The ACS modeling rats were also established in this study to explore the potential mechanism underlying the function of miR-3646. miR-3646 was upregulated in ACS patients compared with healthy volunteers and non-ACS patients. The expression of miR-3646 was positively correlated with the severity and progression of ACS patients and could discriminate ACS patients from healthy volunteers and non-ACS patients. The knockdown of miR-3646 could reverse the inflammatory response induced by ACS.miR-3646 serves as a diagnostic biomarker for ACS. The knockdown of miR-3646 could alleviate ACS by reversing inflammatory response. These results provide a potential therapeutic target of ACS.

Few-layer and 1T-rich MoS 2 is synthesized by a one-step solvothermal process using a rigid segment-containing polysulfide as a concomitant sulfur source and in situ intercalator. The prepared MoS 2 displays superior hydrogen evolution reaction activity, providing a facile and mild approach for the development of high performing MoS 2 and other two-dimensional lamellar materials.

The present study aimed to evaluate the effectiveness of erythropoietin (EPO) for improving cancer-associated malignant anemia. A search was performed for randomized clinical trials, conducted according to the Cochrane manual, using electronic databases including PubMed, EMBASE, the Cochrane Library and ClinicalTrails.gov up to 15 August 2015. A total of 6 eligible studies from 5 articles enrolling a total of 453 patients were entered into the current meta-analysis. Upon EPO treatment, there were significant differences in the change in hemoglobin (HB) levels compared with the placebo at short-term follow-up [mean difference (MD)=0.66; 95% confidence interval (CI), 0.14-1.18; I2=Not applicable; P=0.01) and long-term follow-up (MD=0.10; 95% CI, 0.02-0.18; I2=Not applicable; P=0.01) under the random effects model. For changes in hematocrit (HCT) compared with the placebo, the results revealed there were significant differences at short-term follow-up (MD=2.47; 95% CI, 0.75-4.19; I2=Not applicable; P=0.005) and long-term follow-up (MD=7.60; 95% CI, 6.15-9.05; I2=Not applicable; P<0.00001) under the random effects model. Compared with the placebo in short-term follow-up under the fixed effects model with homogeneity, the result was a significant difference for the transfusion ratio [relative risk (RR)=0.81; 95% CI, 0.67- 0.97; I2=34%; P=0.02) and the transfusion requirements (MD=-0.45; 95% CI, -0.92, 0.03; I2=6%; P=0.07). Funnel plots did not detect any publication bias. These results suggest that EPO was beneficial to alleviate cancer-associated anemia and improve survival outcomes for patients with cancer.

To evaluate the efficacy of members of the H2RA family for the treatment of gastro-esophageal reflux disease (GERD). We performed a thorough electronic search on PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) for eligible randomized clinical trials that investigated H2RAs and the treatment of GERD up to July 28, 2015. A comprehensive network meta-analysis was conducted to compare the effects of each subset of H2RAs. A total of 13 randomized controlled trials (RCTs) were included in our network meta-analysis. Our results showed that, compared with placebos, H2RAs were more effective for the treatment of GERD. Within the H2RA family, famotidine 80 mg per day (OR = 0.17, 95% CI: 0.06 - 0.38) was determined to be the most effective, followed by famotidine 40 mg per day (odds ratio (OR) = 0.23, 95% confidence interval (CI), 0.11 - 0.44); ranitidine 1,200 mg per day (OR, 0.32; 95% CI, 0.13 - 0.63); ranitidine 600 mg per day (OR, 0.27; 95% CI, 0.14 - 0.47); ranitidine 300 mg per day (OR, 0.31; 95% CI, 0.15 - 0.55); cimetidine 1,600 mg per day (OR, 0.36; 95% CI, 0.14 - 0.73); nizatidine 600 mg per day (OR, 0.58; 95% CI, 0.24 - 1.24); and finally nizatidine 300 mg per day (OR, 0.61; 95% CI, 0.25 - 1.26). The placebo was determined to be the least effective treatment. Compared with other H2RAs, famotidine had the best short-term therapeutic effect in adults with GERD, especially at a dosage of 80 mg per day.

An ampholytic N-carboxyethyl chitosan (CEC), with various isoelectric points (IPs), was synthesized by grafting acrylic acid on chitosan utilizing Michael's reaction. Compared to native chitosan, CEC has enhanced water solubility and dramatically accelerated enzymatic degradation; the rate of degradation is proportional to the degree of substitution (DS). The results from turbidimetric titration and fluorescence studies revealed that CEC formed complexes with either hyaluronic acid (HA) or bovine serum albumin (BSA) within a certain pH range. The HA/CEC/BSA ternary complexes could be prepared by colloid titration with quantitative yield and BSA entrapment. The rate of BSA release from the complexes was affected by pH, ionic strength, DS of CEC, and the molecular weight (MW) of HA. The endurance of BSA release from the complexes could be extended up to 20 d by formulating them with high-MW HA and CEC with low DS.BSA release profiles from HA/CEC-2/BSA complexes.