Trends of older gastric cancer incidence, mortality, and survival in the highest gastric cancer risk area in China: 2010-2019 and prediction to 2024.

BACKGROUND: Gastric cancer is a major health problem worldwide, with a high incidence among older adults. Given the aging overall population, it was crucial to understand the current burden and prospective trend of older gastric cancer. This study aimed to analyze the temporal trends of the incidence, mortality, and survival of older gastric cancer in the highest gastric cancer risk area in China from 2010 to 2019, and to predict the future burden of older gastric cancer up to 2024. METHODS: The study was conducted in Gansu province, an area characterized by the highest gastric cancer incidence and mortality in China. The registration data of gastric cancer incidence and mortality from 2010 to 2019 were pooled from registries in the Gansu Cancer Registration System, while survival data were collected from the First Hospital of Lanzhou University, Lanzhou University Second Hospital, and Gansu Cancer Hospital. Chinese standard population in 2000 and the Segi's world standard population were applied to calculate the age-standardized rate. Joinpoint regression was used to analyze the average annual percentage change (AAPC) in cancer incidence and mortality. Autoregressive Integrated Moving Average (ARIMA) models were employed to generate forecasts for incidence and mortality from 2020 to 2024. RESULTS: Based on registry data from 2010 to 2019, the incidence and mortality rates of gastric cancer among older adults remained stable. The incidence rates declined from 439.65 per 100,000 in 2010 to 330.40 per 100,000 in 2019, with an AAPC of -2.59% (95% confidence interval[CI], -5.14 to 0.04, P = 0.06). Similarly, the mortality rate changed from 366.98 per 100,000 in 2010 to 262.03 per 100,000 in 2019, with an AAPC of -2.55% (95% CI, -8.77-4.08%, P = 0.44). In the hospital-based cohort, the decline in survival rates was reported among older patients with gastric cancer in the highest gastric cancer risk area in China, with the 3-year overall survival (OS) decreasing from 58.5% (95% CI, 53.5-63.2%) in 2010 to 34.4% (95%CI, 32.1-36.7%) in 2019, and the 3-year progression-free survival (PFS) decreasing from 51.3% (95%CI, 47.5-55.1%) in 2010 to 34.2% (95%CI, 32.0-36.3%) in 2019, respectively. Moreover, forecasts generated by ARIMA models revealed a significant decline in the incidence and mortality of older gastric cancer in China from 2020 to 2024. Specifically, the incidence rate of older gastric cancer was expected to decrease from 317.94 per 100,000 population in 2020 to 205.59 per 100,000 population in 2024, while the anticipated mortality rate was estimated to decrease from 222.52 per 100,000 population in 2020 to 186.22 per 100,000 population in 2024. CONCLUSION: From 2010 to 2019, the incidence and mortality of older gastric cancer remained stable in the highest gastric cancer risk area in China, while the survival rates showed a decline. Based on the ARIMA models, it was anticipated that there might be a continued decline in older gastric cancer incidence and mortality in the highest-risk area in China over the next five years.

China's logistics evolution: A study of development characteristics and catalytic effects on economic growth.

The impact of logistics development on the economy covers many aspects, such as production, cost, employment, international trade, etc. It is an indispensable part of the modern economy, which helps to improve overall economic efficiency and social prosperity. This study studies the spatiotemporal dynamic evolution characteristics of China's logistics development from 2008 to 2018 and explores its impact on economic growth in multiple dimensions of time and space. The research findings indicate the following: (1) From 2008 to 2018, China's logistics development level (LDL) exhibited a clear upward trend. The differences between the eastern, central, and western regions showed fluctuating downward patterns, ultimately converging towards a high-level concentration. Concerning spatial distribution, China's logistics development demonstrated a trend towards the west and south. However, the spatial pattern of "strong in the east and weak in the west " has existed for a long time. Moreover, the "T-shaped" pattern between coastal provinces and those along the Yangtze River Basin deepened, and the LDL in the central and western regions significantly improved. (2) The advancement of China's LDL effectively promotes its economic growth, confirming that the Belt and Road Initiative enhances the role of logistics development in driving economic growth. Regarding regional differences, logistics development positively influences economic growth in the eastern and western regions, with a less significant impact on the central region. Regarding the strength of influence, logistics development has a more substantial effect on promoting high-ranking provinces in the entire country, the eastern region, and the central region, as well as boosting economic growth in low-ranking provinces in the western region.

Sex disparity, prediagnosis lifestyle factors, and long-term survival of gastric cancer: a multi-center cohort study from China.

BACKGROUND: This multi-center cohort study aimed to investigate whether sex and prediagnosis lifestyle affect the prognosis of gastric cancer. METHODS: Patients with gastric cancer were from four gastric cancer cohorts of the National Cancer Center of China, The First Hospital of Lanzhou University, Lanzhou University Second Hospital, and Gansu Provincial Cancer Hospital. Prediagnosis lifestyle factors in our study included body mass index (BMI) at diagnosis, usual BMI, weight loss, the history of Helicobacter pylori (Hp) infection, and the status of smoking and drinking. RESULTS: Four gastric cancer cohorts with 29,779 gastric cancer patients were included. In total patients, female patients had a better prognosis than male patients (HR = 0.938, 95%CI: 0.881-0.999, P = 0.046). For prediagnosis lifestyle factors, BMI at diagnosis, usual BMI and the amount of smoking were statistically associated with the prognosis of gastric cancer patients. Female patients with smoking history had a poorer survival than non-smoking females (HR = 0.782, 95%CI: 0.616-0.993, P = 0.044). Tobacco consumption > 40 cigarettes per day (HR = 1.182, 95%CI: 1.035-1.350, P = 0.013) was independent adverse prognostic factors in male patients. Obesity paradox was observed only in male patients (BMI < 18.5, HR = 1.145, 95%CI: 1.019-1.286, P = 0.023; BMI: 23-27.4, HR = 0.875, 95%CI: 0.824-0.930, P < 0.001; BMI ≥ 27.5, HR = 0.807, 95%CI: 0.735-0.886, P < 0.001). CONCLUSIONS: Sex and some prediagnosis lifestyle factors, including BMI at diagnosis, usual BMI and the amount of smoking, were associated with the prognosis of gastric cancer.

Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database.

Objective: Accurate prognosis prediction is critical for individualized-therapy making of gastric cancer patients. We aimed to develop and test 6-month, 1-, 2-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) prediction models for gastric cancer patients following gastrectomy. Methods: We derived and tested Survival Quilts, a machine learning-based model, to develop 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS prediction models. Gastrectomy patients in the development set (n = 20,583) and the internal validation set (n = 5,106) were recruited from the Surveillance, Epidemiology, and End Results (SEER) database, while those in the external validation set (n = 6,352) were recruited from the China National Cancer Center Gastric Cancer (NCCGC) database. Furthermore, we selected gastrectomy patients without neoadjuvant therapy as a subgroup to train and test the prognostic models in order to keep the accuracy of tumor-node-metastasis (TNM) stage. Prognostic performances of these OS and CSS models were assessed using the Concordance Index (C-index) and area under the curve (AUC) values. Results: The machine learning model had a consistently high accuracy in predicting 6-month, 1-, 2-, 3-, 5-, and 10-year OS in the SEER development set (C-index = 0.861, 0.832, 0.789, 0.766, 0.740, and 0.709; AUC = 0.784, 0.828, 0.840, 0.849, 0.869, and 0.902, respectively), SEER validation set (C-index = 0.782, 0.739, 0.712, 0.698, 0.681, and 0.660; AUC = 0.751, 0.772, 0.767, 0.762, 0.766, and 0.787, respectively), and NCCGC set (C-index = 0.691, 0.756, 0.751, 0.737, 0.722, and 0.701; AUC = 0.769, 0.788, 0.790, 0.790, 0.787, and 0.788, respectively). The model was able to predict 6-month, 1-, 2-, 3-, 5-, and 10-year CSS in the SEER development set (C-index = 0.879, 0.858, 0.820, 0.802, 0.784, and 0.774; AUC = 0.756, 0.827, 0.852, 0.863, 0.874, and 0.884, respectively) and SEER validation set (C-index = 0.790, 0.763, 0.741, 0.729, 0.718, and 0.708; AUC = 0.706, 0.758, 0.767, 0.766, 0.766, and 0.764, respectively). In multivariate analysis, the high-risk group with risk score output by 5-year OS model was proved to be a strong survival predictor both in the SEER development set (hazard ratio [HR] = 14.59, 95% confidence interval [CI]: 1.872-2.774, P < 0.001), SEER validation set (HR = 2.28, 95% CI: 13.089-16.293, P < 0.001), and NCCGC set (HR = 1.98, 95% CI: 1.617-2.437, P < 0.001). We further explored the prognostic value of risk score resulted 5-year CSS model of gastrectomy patients, and found that high-risk group remained as an independent CSS factor in the SEER development set (HR = 12.81, 95% CI: 11.568-14.194, P < 0.001) and SEER validation set (HR = 1.61, 95% CI: 1.338-1.935, P < 0.001). Conclusion: Survival Quilts could allow accurate prediction of 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS in gastric cancer patients following gastrectomy.

Construction of a highly specific fluorescence "turn-on" probe for H2S detection and imaging in drug-induced live cells, zebrafish and mice arthritis models.

Quantitatively and selectively detecting the biomarker of hydrogen sulfide (H2S) in arthritis diseases is of great significance for the early diagnosis and treatment of arthritis. Modern medical studies show that H2S as a biomarker is involved in the development of inflammation. In this work, a new highly specific fluorescence "turn-on" probe JMD-H2S was tailored for H2S detection and imaging in drug-induced live cells, zebrafish and mice arthritis models, which utilized pyrazoline molecule as the fluorescence signal reporter group and 2,4-dinitrophenyl ether group (DNB) with strong intramolecular charge transfer (ICT) effect as the H2S recognition moiety and fluorescence quenching group. JMD-H2S showed a fast response time (<60 s), a large fluorescence response ratio (enhanced ∼20 folds) at I453/I0, excellent sensitivity toward H2S over other analytes, and an outstanding limit of detection (LOD) as low as 25.3 nM. In addition, JMD-H2S has been successfully applied for detecting and imaging H2S in drug-induced live cells, zebrafish, and mice arthritis models with satisfactory results, suggesting it can be used as a robust molecular tool for investigating the occurrence and development of H2S and arthritis.

Dielectric barrier discharge low-temperature plasma modification of bamboo charcoal for supercapacitor applications.

Biochar is commonly utilized as an electrode material in supercapacitors. However, the conventional carbonization process often results in macromolecular compounds, which obstruct the porous structure of carbon materials, thereby reducing their capacitance. Dielectric barrier discharge low-temperature plasma (DLTP) is a technology that transforms gases into highly excited states, utilizing high-energy particles for enhanced energy applications. This study investigated the effects of DLTP on the electrochemical performance of bamboo charcoal (BC), utilizing bamboo shavings (BS) as the carbon source. The results indicated that the specific capacitance of BC varied under different atmospheric conditions, input voltages, and treatment durations, thereby achieving a maximum increase of 144 F/g. Furthermore, when combined with KOH activation, DLTP modification further enhanced the specific capacitance of BC to 237 F/g. The DLTP treatment enhanced the specific surface area and the types of functional groups in BC, thereby leading to a significant enhancement of its electrochemical properties.

Highly Graphitized Coal Tar Pitch-Derived Porous Carbon as High-Performance Lithium Storage Materials.

Because of its high specific capacity and superior rate performance, porous carbon is regarded as a potential anode material for lithium-ion batteries (LIBs). However, porous carbon materials with wide pore diameter distributions suffer from low structural stability and low electrical conductivity during the application process. During this study, the calcium carbonate nanoparticle template method is used to prepare coal tar pitch-derived porous carbon (CTP-X). The coal tar pitch-derived porous carbon has a well-developed macroporous-mesoporous-microporous hierarchical porous network structure, which provides abundant active sites for Li+ storage, significantly reduces polarization and charge transfer resistance, shortens the diffusion path and promotes the rapid transport of Li+. More specifically, the CTP-2 anode shows high charge capacity (496.9 mAh g-1 at 50 mA g-1), excellent rate performance (413.6 mAh g-1 even at 500 mA g-1), and high cycling stability (capacity retention rate of about 100 % after 1,000 cycles at 2 A g-1). The clean and eco-friendly large-scale utilization of coal tar pitch will facilitate the development of high-performance anodes in the field of LIBs.

Room temperature high-efficiency welding of an ultra-long silver nanowire network for flexible transparent electrodes.

In the preparation of flexible electronic devices, obtaining a transparent conductive electrode with high electrical conductivity, high transparency, and mechanical flexibility is a significant challenge. This study developed a simple method for preparing ultra-long silver nanowires (ul-AgNWs), obtaining high-purity ul-AgNWs with an average length of 317.66 ± 98.60 µm, an average diameter of 78.06 ± 13.87 nm, and an aspect ratio exceeding 4000. Integrating these ul-AgNWs with a polyethylene terephthalate (PET) film, a flexible transparent electrode (FTE) with Rs = 561 Ω and T = 97% was obtained. The ul-AgNWs were welded by driving the welding liquid to the intersection points through surface tension, resulting in a decrease of Rs to 61 Ω, T = 98.2%, and achieving a FTE with excellent mechanical properties. Furthermore, this FTE was applied in the preparation of OLED devices, showing a turn-on voltage of 2.7 V, and the maximum current efficiency and power efficiency reached 58.6 mA cm-2 and 64.7 lm W-1, respectively, demonstrating its significant potential in flexible optoelectronic devices.

Graph Convolutional Network With Connectivity Uncertainty for EEG-Based Emotion Recognition.

Automatic emotion recognition based on multichannel Electroencephalography (EEG) holds great potential in advancing human-computer interaction. However, several significant challenges persist in existing research on algorithmic emotion recognition. These challenges include the need for a robust model to effectively learn discriminative node attributes over long paths, the exploration of ambiguous topological information in EEG channels and effective frequency bands, and the mapping between intrinsic data qualities and provided labels. To address these challenges, this study introduces the distribution-based uncertainty method to represent spatial dependencies and temporal-spectral relativeness in EEG signals based on Graph Convolutional Network (GCN) architecture that adaptively assigns weights to functional aggregate node features, enabling effective long-path capturing while mitigating over-smoothing phenomena. Moreover, the graph mixup technique is employed to enhance latent connected edges and mitigate noisy label issues. Furthermore, we integrate the uncertainty learning method with deep GCN weights in a one-way learning fashion, termed Connectivity Uncertainty GCN (CU-GCN). We evaluate our approach on two widely used datasets, namely SEED and SEEDIV, for emotion recognition tasks. The experimental results demonstrate the superiority of our methodology over previous methods, yielding positive and significant improvements. Ablation studies confirm the substantial contributions of each component to the overall performance.

Rapid discrimination of Alismatis Rhizoma and quantitative analysis of triterpenoids based on near-infrared spectroscopy.

This study developed a rapid, accurate, objective and economic method to identify and evaluate the quality of Alismatis Rhizoma (AR) commodities. Traditionally, the identification of plant species and geographical origins of AR commodities mainly relied on experienced staff. However, the subjectivity and inaccuracy of human identification negatively impacted the trade of AR. Besides, liquid chromatographic methods such as ultra-high-performance liquid chromatography (UPLC) and high-performance liquid chromatography (HPLC), the major approach for the determination of triterpenoid contents in AR was time-consuming, expensive, and highly demanded in manoeuvre specialists. In this study, the combination of near-infrared (NIR) spectroscopy and chemometrics as the method was developed and utilised to address the two common issues of identifying the quality of AR commodities. Through the discriminant analysis (DA), the raw NIR spectroscopy data on 119 batches samples from two species and four origins in China were processed to the best pre-processed data. Subsequently, orthogonal partial least squares-discriminant analysis (OPLS-DA) and random forest (RF) as the major chemometrics were used to analyse the best pre-processed data. The accuracy rates by OPLS-DA and RF were respectively 100% and 97.2% for the two species of AR, and respectively100% and 94.4% for the four origins of AR. Meanwhile, a quantitative correction model was established to rapidly and economically predict the seven triterpenoid contents of AR through combining the partial least squares (PLS) method and NIR spectroscopy, and taking the triterpenoid contents measured by UPLC as the reference value, and carry out spectral pre-processing methods and band selection. The final quantitative model correlation coefficients of the seven triterpenoid contents of AR ranged from 0.9000 to 0.9999, indicating that prediction ability of this model had good stability and applicability.

Green synthesis of N-rich carbon dot-derived crosslinked covalent organic nanomaterial for multipurpose chromatographic applications.

Carbon dots (CDs) derived crosslinked covalent organic nanomaterials (CONs) possessing high specific surface area and abundant surface functional groups are considered to be potential candidates for multimodal chromatographic separations. Typically, the synthesis of CDs and CONs requires harsh reaction conditions and toxic organic solvents, hence, the pursuit of facile and mild preparation strategies is the goal of researchers. In this work, 3-aminopropyltriethoxysilane and D-glucose were used as nitrogen and carbon sources, respectively, to prepare amino-CDs (AmCDs) by rapid low-temperature polymerization rather than the common high-temperature and high-pressure reaction. Then, surface functionalization of the aminated silica gel was carried out in a deep eutectic solvent by using hydrophilic AmCDs and 1,3,5-triformylbenzene (TFB) as the functional monomers. Consequently, a novel N-rich CDs derived CON surface-functionalized silica gel (AmCDs-CON@SiO2) was obtained under mild reaction conditions. The combination of AmCDs and TFB created an ideal CON based chromatographic stationary phase. The incorporation of TFB not only contributed to the successful construction of a crosslinked CON, but also enhanced the interaction forces. The developed AmCDs-CON@SiO2 has a great potential for versatile applications in liquid chromatography. This study proposes a simple stationary phase preparation strategy by the surface modification of silica gel with CDs-based CON. Moreover, this study verified the application potential of CDs derived CON in chromatographic separation. This not only promotes the development of CDs in the field of liquid chromatographic stationary phase, but also provides some reference value for the wide application of cross-linked CON.

Surface molecularly imprinted polymer/covalent organic framework/silica composite material with specific recognition ability and excellent chromatographic performance.

Facing with the difficulty of specific chromatographic separation of nucleoside drugs, this study prepared a surface molecularly imprinted polymer (SMIP) modified covalent organic framework (COF) coated silica stationary phase based on the specificity of molecular imprinting technology and the powerful chromatographic separation performance of COF. This novel SMIP-COF@SiO2 stationary phase can not only specifically identify template molecule and structural analogs, but can also be used to separate multiple types of analytes, such as B vitamins, sulfonamides, alkylbenzenes, phenyl ketones, polycyclic aromatic hydrocarbons and environmental endocrine disruptors, which satisfies the need for complex sample separation. Various retention mechanisms have been investigated and multiple interactions between the SMIP-COF@SiO2 stationary phase and the analytes are discovered. The chromatographic performance of SMIP-COF@SiO2 is far superior to that of the SMIP@SiO2 and COF@SiO2. Furthermore, the SMIP-COF@SiO2 stationary phase can be successfully used to analyze polycyclic aromatic hydrocarbons in the environmental water sample and detect whitening ingredient in skincare product, indicating its great potential for application in various fields.

Electrochemical Deconstructive and Ring-Expansion Functionalization of Unstrained Cycloalkanols.

An efficient and sustainable electrochemical method for the synthesis of cyclic ethers and acyclic aldehydes from alkanols has been reported. This strategy has been successfully applied to cycloalkanols bearing different ring sizes and different types of nucleophiles. In addition, mechanistic investigations show that the reactions undergo sequential processes, including anodic oxidation, ß-scission, and nucleophilic addition. This method provides a new synthetic approach to constructing cyclic ethers and terminal aldehydes from cycloalkanols and nucleophiles.

Blood transfusion might not be recommended for gastric cancer patients with pretransfusion minimum hemoglobin values higher than 90 g/L: a real-world study covering 20 years of 13470 patients.

BACKGROUND: There was no consistent evidence whether perioperative blood transfusion (PBT) affects the long-term survival of gastric cancer (GC) patients after undergoing gastrectomy. This study aimed to investigate the effects of PBT on long-term survival of GC patients, as well as to determine the threshold of PBT and provide evidence for future surgical practice. METHODS: We performed this real-world study of GC patients undergoing gastrectomy in China National Cancer Center from January 1, 2000 to December 30, 2019. Overall survival (OS) curves were plotted using the Kaplan-Meier method and compared statistically using the log-rank test. Univariate and multivariate Cox proportional hazards models were used to determine the risk factors for OS. RESULTS: In total, 13470 GC patients undergoing gastrectomy from 2000 to 2019 was included, of whom 3465 (34.6%) GC patients received PBT. PBT ratios declined from 29.1% (114/392) in 2000 to 11.2% in 2019 (149/1178), with the highest blood transfusion ratio in 2005 at 43.7% (220/504). For patients transfused with red blood cells, the median value of hemoglobin (Hb) before transfusion in the PBT group decreased from 110 g/L in 2000 to 87 g/L in 2019. Compared with patients who not receiving perioperative blood transfusion (NPBT), PBT group are more likely to be older (≥65, 39.1% vs. 30.1%, P<0.001), open operation (89.7% vs. 78.1%, P<0.001), higher ASA score (>2, 25.3% vs. 14.9%, P<0.001) and in the later pTNM stage (pTNM stage III, 68.5% vs. 51.5%, P<0.001). Results of multivariable Cox regression analysis showed that PBT was an independent prognostic factor for worse OS in GC patients undergoing gastrectomy (HR=1.106, 95% CI, 1.01-1.211, P=0.03). After stratified according to tumor stage, we found that PBT group had a worse prognosis only in pTNM stage III (HR=1.197, 95% CI, 1.119-1.281, P<0.001). OS was obviously poor in the PBT group when Hb levels were higher than 90 g/L (90 g/L120 g/L:HR= 1.207, 95% CI, 1.098-1.327, P<0.001), while there was no difference between the two groups when Hb levels were lower than or equal to 90 g/L (Hb≤90 g/L: HR=1.162, 95% CI, 0.985-1.370, P=0.075). CONCLUSION: In conclusion, PBT was an independent prognostic factor for worse OS. Blood transfusion might not be recommended for gastric cancer patients with perioperative minimum Hb values higher than 90 g/L.

A new method based on melatonin-mediated seed germination to quickly remove pesticide residues and improve the nutritional quality of contaminated grains.

In the present study, we attempted to use melatonin combined with germination treatment to remove pesticide residues from contaminated grains. High levels of pesticide residues were detected in soybean seeds after soaking with chlorothalonil (10 mM) and malathion (1 mM) for 2 hours. Treatment with 50 µM melatonin for 5 days completely removed the pesticide residues, while in the control group, only 61-71% of pesticide residues were removed from soybean sprouts. Compared with the control, melatonin treatment for 7 days further increased the content of ascorbic acid (by 48-66%), total phenolics (by 52-68%), isoflavones (by 22-34%), the total antioxidant capacity (by 37-40%), and the accumulated levels of unsaturated fatty acids (C18:1, C18:2, and C18:3) (by 17-30%) in soybean sprouts. Moreover, melatonin treatment further increased the accumulation of ten components of phenols and isoflavones in soybean sprouts relative to those in the control. The ability of melatonin to accelerate the degradation of pesticide residues and promote the accumulation of antioxidant metabolites might be related to its ability to trigger the glutathione detoxification system in soybean sprouts. Melatonin promoted glutathione synthesis (by 49-139%) and elevated the activities of glutathione-S-transferase (by 24-78%) and glutathione reductase (by 38-61%). In summary, we report a new method in which combined treatment by melatonin and germination rapidly degrades pesticide residues in contaminated grains and improves the nutritional quality of food.

Cotton stalk decomposition with DBD low-temperature plasma: Characteristics and kinetics.

DBD low-temperature plasma (DLTP) is recognized as one of the most efficient technologies for treating cotton stalks. This study investigates the impact of various conditions on the gas production characteristics of cotton stalks (CS) and delves into the DLTP decomposition kinetics of CS and CSC in oxygen-enriched (30 % O2/Ar) and CO2 atmospheres. The decomposition rates of CS followed the order CO2 > N2 > Ar. The decomposition behavior of CSC in oxygen-enriched DLTP (30 % O2/Ar) aligned well with the chemical reaction model. The activation energies for CSC decomposition at 900 °C and 1000 °C were determined to be 23.8 kJ/mol and 33.8 kJ/mol, respectively. Moreover, the reaction rate decreased at higher carbonization temperatures, which proved to be detrimental to the decomposition of CSC. The DLTP decomposition of CSC in CO2 exhibited consistency with the fitting results of the unreacted shrinking core model, revealing an observed activation energy of 19.4 kJ/mol.

Design of smart temperature-sensitive terpolymeric hydrogel for multi-applications in liquid chromatography.

Hydrogels with a unique three-dimensional network structure have been widely used in a variety of fields. However, hydrogels are prone to swelling under water-rich conditions, which severely limits their application in liquid chromatography. Therefore, producing a hydrogel with reliable performance and good mechanical property is essential. Smart temperature-sensitive chromatographic packings have attracted extensive attentions in recent years. In this work, sodium 4-styrenesulfonate and 1-octadecene were introduced into the poly(N-isopropylacrylamide) hydrogel to improve mechanical property and separation performance. As a consequence, a smart temperature-sensitive terpolymeric hydrogel modified silica stationary phase (ION-hydrogel@SiO2) was synthesized for multimode liquid chromatographic separation. It was found that this new ION-hydrogel@SiO2 column exhibited excellent chromatographic separation ability for a wide range of analytes. To a certain extent, this new column has a higher chromatographic separation efficiency compared to the commercial C18 column and XAmide column. Moreover, the use of low proportion of organic phase in chromatographic separation is conducive to the realization of green chromatography. By investigating the chromatographic separation mechanism, it has been demonstrated that the hydrogen bonding interaction is primarily responsible for the temperature-sensitive behavior of the hydrogel. Finally, the ION-hydrogel@SiO2 column was used for the determination of pyridoxine in the commercially available tablet samples. In conclusion, this study presents a feasible idea for the development of novel copolymer hydrogels as liquid chromatographic stationary phases.

Research progress on the improvement of cardiovascular diseases through the autonomic nervous system regulation of the NLRP3 inflammasome pathway.

Cardiovascular disease stands as a leading global cause of mortality. Nucleotide-binding Oligomerization Domain-like Receptor Protein 3 (NLRP3) inflammasome is widely acknowledged as pivotal factor in specific cardiovascular disease progression, such as myocardial infarction, heart failure. Recent investigations underscore a close interconnection between autonomic nervous system (ANS) dysfunction and cardiac inflammation. It has been substantiated that sympathetic nervous system activation and vagus nerve stimulation (VNS) assumes critical roles withinNLRP3 inflammasome pathway regulation, thereby contributing to the amelioration of cardiac injury and enhancement of prognosis in heart diseases. This article reviews the nexus between NLRP3 inflammasome and cardiovascular disorders, elucidating the modulatory functions of the sympathetic and vagus nerves within the ANS with regard to NLRP3 inflammasome. Furthermore, it delves into the potential therapeutic utility of NLRP3 inflammasome to be targeted by VNS. This review serves as a valuable reference for further exploration into the potential mechanisms underlying VNS in the modulation of NLRP3 inflammasome.

Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target.

The electric power industry is a key industry for the country to achieve the double carbon target. Its low carbon development has a double effect on this industry and helps other industries to achieve the carbon peak target. This paper firstly uses the IPCC inventory method to calculate carbon emissions in the production phase of the power industry in Gansu Province from 2000 to 2019, followed by the ridge regression method and the STIRPAT model to analyse the quantitative impact of six major drivers on carbon emissions, and finally, the scenario analysis method is used to forecast carbon emissions in this phase. The results show that the carbon emissions of Gansu Province show a trend of rising and then falling, and reached a peak of 65.66 million tons in 2013. For every 1% increase in population effect, urbanisation level, affluence, clean energy generation share, technology level and industrial structure, carbon emissions will grow by 4.939%, 0.625%, 0.224%, - 0.259%, 0.063% and 0.022% respectively. Because of the clean energy advantage in Gansu Province, the low-carbon development scenario will continue to have low carbon emissions during the scenario cycle, which can be reduced to 53.454 million tons in 2030; the baseline scenario will achieve a carbon peak in 2025, with a peak of 62.627 million tons; the economic development scenario has not achieved carbon peak during the scenario cycle, and carbon emissions will increase to 73.223 million tons in 2030.

Lanthanum hydroxide protects kidney through gut microbiota in a rat model of chronic kidney disease.

The progression of chronic kidney diseases (CKD) is complex, influenced by a myriad of factors including gut microbiota. While emerging evidence suggests that gut microbiota can have beneficial effects in managing CKD, it is also recognized that dysbiosis may contribute to the progression of CKD and associated uremic complications. Our previous research has demonstrated the efficacy of lanthanum hydroxide in delaying kidney failure and preserving renal function. However, the role of lanthanum hydroxide in modulating gut microbiota in this context remains unclear. In our study, we induced CKD in rats using adenine, leading to gut microbial dysbiosis, kidney pathology, and disturbances in amino acid metabolism. In this adenine-induced CKD model with hyperphosphatemia, treatment with lanthanum hydroxide improved renal function. This improvement was associated with the restoration of gut microbial balance and an increase in urine ammonium metabolism. These results suggest that the therapeutic potential of lanthanum hydroxide in CKD may be partly due to its ability to reshape gut microbiota composition. This study underscores the significance of lanthanum hydroxide in kidney protection, attributing its benefits to the modulation of gut microbiota in a rat model of CKD.