Association between tertiary lymphoid structures and clinical outcomes in cancer patients treated with immune checkpoint inhibitors: an updated meta-analysis.

Background: Although numerous studies have reported the association between tertiary lymphoid structures (TLSs) and clinical outcomes in cancer patients treated with immune checkpoint inhibitors (ICIs), there remains a lack of a newer and more comprehensive meta-analysis. The main objective of this study is to explore prognostic biomarkers in immunotherapy-related patients, through analyzing the associations between tertiary lymphoid structures (TLSs) and clinical outcomes in cancer patients treated with ICIs, so as to investigate their prognostic value in cancer patients treated with ICIs. Methods: A comprehensive search was conducted until February 2024 across PubMed, Embase, Web of Science, and the Cochrane Library databases to identify relevant studies evaluating the association between tertiary lymphoid structures and clinical outcomes in cancer patients treated with ICIs. The clinical outcomes were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Results: Thirteen studies were incorporated in this meta-analysis, among which nine evaluated the prognostic value of TLSs. The results showed the high levels of TLSs predicted a significantly prolonged OS (pooled HR = 0.35, 95% CI: 0.24-0.53, p < 0.001) and PFS (pooled HR = 0.47, 95% CI: 0.31-0.72, p < 0.001), while lower ORR (pooled OR = 3.78, 95% CI: 2.26-6.33, p < 0.001) in cancer patients treated with ICIs. Conclusion: Our results indicated that high levels of TLSs could predict a favorable prognosis for cancer patients treated with ICIs and have the potential to become a prognostic biomarker of immunotherapy-related patients.

Empagliflozin alleviates neuroinflammation by inhibiting astrocyte activation in the brain and regulating gut microbiota of high-fat diet mice.

A high-fat diet can modify the composition of gut microbiota, resulting in dysbiosis. Changes in gut microbiota composition can lead to increased permeability of the gut barrier, allowing bacterial products like lipopolysaccharides (LPS) to enter circulation. This process can initiate systemic inflammation and contribute to neuroinflammation. Empagliflozin (EF), an SGLT2 inhibitor-type hypoglycemic drug, has been reported to treat neuroinflammation. However, there is a lack of evidence showing that EF regulates the gut microbiota axis to control neuroinflammation in HFD models. In this study, we explored whether EF could improve neuroinflammation caused by an HFD via regulation of the gut microbiota and the mechanism underlying this phenomenon. Our data revealed that EF alleviates pathological brain injury, reduces the reactive proliferation of astrocytes, and increases the expression of synaptophysin. In addition, the levels of inflammatory factors in hippocampal tissue were significantly decreased after EF intervention. Subsequently, the results of 16S rRNA gene sequencing showed that EF could change the microbial community structure of mice, indicating that the abundance of Lactococcus, Ligilactobacillus and other microbial populations decreased dramatically. Therefore, EF alleviates neuroinflammation by inhibiting gut microbiota-mediated astrocyte activation in the brains of high-fat diet-fed mice. Our study focused on the gut-brain axis, and broader research on neuroinflammation can provide a more holistic understanding of the mechanisms driving neurodegenerative diseases and inform the development of effective strategies to mitigate their impact on brain health. The results provide strong evidence supporting the larger clinical application of EF.

Trifolium repens L. recruits root-associated Microbacterium species to adapt to heavy metal stress in an abandoned Pb-Zn mining area.

Root-associated microbiota provide great fitness to hosts under environmental stress. However, the underlying microecological mechanisms controlling the interaction between heavy metal-stressed plants and the microbiota are poorly understood. In this study, we screened and isolated representative amplicon sequence variants (strain M4) from rhizosphere soil samples of Trifolium repens L. growing in areas with high concentrations of heavy metals. To investigate the microecological mechanisms by which T. repens adapts to heavy metal stress in abandoned mining areas, we conducted potting experiments, bacterial growth promotion experiments, biofilm formation experiments, and chemotaxis experiments. The results showed that high concentrations of heavy metals significantly altered the rhizosphere bacterial community structure of T. repens and significantly enriched Microbacterium sp. Strain M4 was demonstrated to significantly increased the biomass and root length of T. repens under heavy metal stress. Additionally, L-proline and stigmasterol could promote bacterial growth and biofilm formation and induce chemotaxis for strain M4, suggesting that they are key rhizosphere secretions of T. repens for Microbacterium sp. recruitment. Our results suggested that T. repens adapted the heavy metal stress by reshaping rhizosphere secretions to modify the rhizosphere microbiota.

Integrated Transcriptomic and Metabolomic Analysis Reveals the Molecular Regulatory Mechanism of Flavonoid Biosynthesis in Maize Roots under Lead Stress.

Flavonoids are secondary metabolites that play important roles in the resistance of plants to abiotic stress. Despite the widely reported adverse effects of lead (Pb) contamination on maize, the effects of Pb on the biosynthetic processes of flavonoids in maize roots are still unknown. In the present work, we employed a combination of multi-omics and conventional assay methods to investigate the effects of two concentrations of Pb (40 and 250 mg/kg) on flavonoid biosynthesis in maize roots and the associated molecular regulatory mechanisms. Analysis using conventional assays revealed that 40 and 250 mg/kg Pb exposure increased the lead content of maize root to 0.67 ± 0.18 mg/kg and 3.09 ± 0.02 mg/kg, respectively, but they did not result in significant changes in maize root length. The multi-omics results suggested that exposure to 40 mg/kg of Pb caused differential expression of 33 genes and 34 metabolites related to flavonoids in the maize root system, while 250 mg/kg of Pb caused differential expression of 34 genes and 31 metabolites. Not only did these differentially expressed genes and metabolites participate in transferase activity, anthocyanin-containing compound biosynthetic processes, metal ion binding, hydroxyl group binding, cinnamoyl transferase activity, hydroxycinnamoyl transferase activity, and flavanone 4-reductase activity but they were also significantly enriched in the flavonoid, isoflavonoid, flavone, and flavonol biosynthesis pathways. These results show that Pb is involved in the regulation of maize root growth by interfering with the biosynthesis of flavonoids in the maize root system. The results of this study will enable the elucidation of the mechanisms of the effects of lead on maize root systems.

Discrimination between raw and ginger juice processed Fructus Gardeniae based on UHPLC-Q-TOF-MS and Heracles NEO ultra-fast gas phase electronic nose.

INTRODUCTION: Fructus Gardeniae (ZZ), a traditional Chinese herb, has been used in treating patients with jaundice, inflammation, etc. When mixed with ginger juice and stir-baked, ginger juice-processed Fructus Gardeniae (JZZ) is produced, and the chemical compositions in ZZ would be changed by adding the ginger juice. OBJECTIVE: To illuminate the differential components between ZZ and JZZ. METHODS: HPLC, UHPLC-Q-TOF-MS, and Heracles NEO ultra-fast gas phase electronic nose were applied to identify the differential components between ZZ and JZZ. RESULTS: HPLC fingerprints of ZZ and JZZ were established, and 24 common peaks were found. The content determination results showed that the contents of shanzhiside, geniposidic acid, genipin-1-ß-D-gentiobioside and geniposide increased, while the contents of crocin I and crocin II decreased in JZZ. By UHPLC-Q-TOF-MS, twenty-six possible common components were inferred, among which 11 components were different. In further investigation, eight components were identified as the possible distinctive non-volatile compounds between ZZ and JZZ. By Heracles NEO ultra-fast gas phase electronic nose, four substances were inferred as the possible distinctive volatile compounds in JZZ. CONCLUSION: Shanzhiside, caffeic acid, genipin-1-ß-D-gentiobioside, geniposide, rutin, crocin I, crocin II, and 4-Sinapoyl-5-caffeoylquinic acid were identified as the possible differential non-volatile components between ZZ and JZZ. Aniline, 3-methyl-3-sulfanylbutanol-1-ol, E-3-octen-2-one, and decyl propaonate were inferred as the possible distinctive volatile compounds in JZZ. This experiment explored a simple approach with objective and stable results, which would provide new ideas for studying decoction pieces with similar morphological appearance, especially those with different odors.

Changes in soil microbe-mediated carbon, nitrogen and phosphorus cycling during spontaneous succession in abandoned PbZn mining areas.

The mechanism through which soil microorganisms mediate carbon and nutrient cycling during mine wasteland restoration remained unknown. Using soil metagenome sequencing, we investigated the dynamic changes in soil microbial potential metabolic functions during the transition from biological soil crusts (BSC) to mixed broad-conifer forest (MBF) in a typical PbZn mine. The results showed soil microorganisms favored carbon sequestration through anaerobic and microaerobic pathways, predominantly using efficient, low-energy pathways during succession. Genes governing carbon degradation and aerobic respiration increased by 19.56 % and 24.79 %, respectively, reflecting change toward more efficient and intensive soil carbon utilization in late succession. Nitrogen-cycling genes mediated by soil microorganisms met their maximum influence during early succession (sparse grassland, SGL), leading to a respective increase of 75.29 % and 76.81 % in the net potential nitrification rate and total nitrogen content. Mantel and correlation analyses indicated that TOC, TN, Zn and Cd contents were the main factors affecting the soil carbon and phosphorus cycles. Soil AP content emerged as the primary influencer of genes associated with the nitrogen cycle. These results shed light on the dynamic shifts in microbial metabolic activities during succession, providing a genetic insight into biogeochemical cycling mechanisms and underscoring crucial factors influencing soil biogeochemical processes in mining regions.

Soil microbial communities' contributions to soil ecosystem multifunctionality in the natural restoration of abandoned metal mines.

On a global scale, the restoration of metal mine ecosystem functions is urgently required, and soil microorganisms play an important role in this process. Conventional studies frequently focused on the relationship between individual functions and their drivers; however, ecosystem functions are multidimensional, and considering any given function in isolation ignores the trade-offs and interconnectedness between functions, which complicates obtaining a comprehensive understanding of ecosystem functions. To elucidate the relationships between soil microorganisms and the ecosystem multifunctionality (EMF) of metal mines, this study investigated natural restoration of metal mines, evaluated the EMF, and used high-throughput sequencing to explore the bacterial and fungal communities as well as their influence on EMF. Bacterial community diversity and composition were more sensitive to mine restoration than fungal community. Bacterial diversity exhibited redundancy in improving N-P-K-S multifunctionality; however, rare bacterial taxa including Dependentiae, Spirochaetes, and WPS-2 were important for metal multifunctionality. Although no clear relationship between fungal diversity and EMF was observed, the abundance of Glomeromycota had a significant effect on the three EMF categories (N-P-K-S, carbon, and metal multifunctionality). Previous studies confirmed a pronounced positive association between microbial diversity and multifunctionality; however, the relationship between microbial diversity and multifunctionality differs among functions' categories. In contrast, the presence of critical microbial taxa exerted stronger effects on mine multifunctionality.

TRIM56 protects against nonalcoholic fatty liver disease by promoting the degradation of fatty acid synthase.

Nonalcoholic fatty liver disease (NAFLD) encompasses a disease continuum from simple steatosis to nonalcoholic steatohepatitis (NASH). However, there are currently no approved pharmacotherapies for NAFLD, although several drugs are in advanced stages of clinical development. Because of the complex pathophysiology and heterogeneity of NAFLD, the identification of potential therapeutic targets is clinically important. Here, we demonstrated that tripartite motif 56 (TRIM56) protein abundance was markedly downregulated in the livers of individuals with NAFLD and of mice fed a high-fat diet. Hepatocyte-specific ablation of TRIM56 exacerbated the progression of NAFLD, while hepatic TRIM56 overexpression suppressed it. Integrative analyses of interactome and transcriptome profiling revealed a pivotal role of TRIM56 in lipid metabolism and identified the lipogenesis factor fatty acid synthase (FASN) as a direct binding partner of TRIM56. TRIM56 directly interacted with FASN and triggered its K48-linked ubiquitination-dependent degradation. Finally, using artificial intelligence-based virtual screening, we discovered an orally bioavailable small-molecule inhibitor of FASN (named FASstatin) that potentiates TRIM56-mediated FASN ubiquitination. Therapeutic administration of FASstatin improved NAFLD and NASH pathologies in mice with an optimal safety, tolerability, and pharmacokinetics profile. Our findings provide proof of concept that targeting the TRIM56/FASN axis in hepatocytes may offer potential therapeutic avenues to treat NAFLD.

Opposite response of constructed wetland performance in nitrogen and phosphorus removal to short and long terms of operation.

Constructed wetlands (CWs) have been widely used for treating polluted water since the 1950s, with applications in over 50 countries worldwide. Most studies investigating the pollutant removal efficiency of these wetlands have focused on differences among wetland designs, operation strategies, and environmental conditions. However, there still remains a gap in understanding the variation in wetland pollutant removal efficiency over different time scales. Therefore, the main aim of the study is to address this gap by conducting a global meta-analysis to estimate the variation in nitrogen (N) and phosphorus (P) removal by wetland in short- and long-term pollutant treatment. The findings of this study indicated that the total efficiencies of N and P removal increased during short-term wetland operation but decreased during long-term operation. However, for surface flow CWs specifically, the efficiencies of N and P removal increased during short-term operation and remained stable during long-term operation. Moreover, the study discovered that wetland N removal efficiency was influenced by seasons, with an increase in spring and summer and a decrease in autumn and winter. Conversely, there was no significant seasonal effect on P removal efficiency. Additionally, high hydraulic load impaired wetland N and P removal efficiency during long-term operation. This study offers a critical review of the role of wetlands in wastewater treatment and provides valuable reference data for the design and selection of CWs types during wastewater treatment in the aspect of sustainability.

Drivers and mechanisms of spontaneous plant community succession in abandoned PbZn mining areas in Yunnan, China.

The drivers and mechanisms underlying succession and the spontaneous formation of plant communities in mining wasteland remain largely unknown. This study investigated the use of nature-based restoration to facilitate the recovery of viable plant communities in mining wasteland. It was found that scientific analyses of spontaneously formed plant communities in abandoned mining areas can provide insights for nature-based restoration. A chronosequence ("space for time") approach was used to establish sites representing three successional periods with six successional stages, and 90 quadrats were constructed to investigate changes in plant species and functional diversity during succession in abandoned PbZn mining areas. A total of 140 soil samples were collected to identify changes in soil properties, including plant nutrient and heavy metal concentrations. Then, this paper used structural equation models to analyze the mechanisms that drive succession. It was found that the functional diversity of plant communities fluctuated substantially during succession. Species had similar functional traits in early and mid-succession, but traits tended to diverge during late succession. Soil bulk density and soil organic matter gradually increased during succession. Total nitrogen (N), pH, and soil Zn concentrations first increased and then decreased during succession. Concentrations of Mn and Cd gradually decreased during succession. During early succession, soil organic matter was the key factor driving plant colonization and succession. During mid-succession, soil Zn functioned as an environmental filter factor limiting the rates of succession in mining wasteland communities. During late succession, soil bulk density and competition for nutrient resources contributed to more balanced differentiation among plant species. This thesis proposed that a nature-based strategy for the stabilization of abandoned mining lands could facilitate effective plant community restoration that promotes ecosystem services and functioning.

[Processing Magnoliae Officinalis Cortex with ginger juice: process optimization based on AHP-CRITIC weighting method and composition changes after processing].

The weight coefficients of appearance traits, extract yield of standard decoction, and total content of honokiol and magnolol were determined by analytic hierarchy process(AHP), criteria importance though intercrieria correlation(CRITIC), and AHP-CRITIC weighting method, and the comprehensive scores were calculated. The effects of ginger juice dosage, moistening time, proces-sing temperature, and processing time on the quality of Magnoliae Officinalis Cortex(MOC) were investigated, and Box-Behnken design was employed to optimize the process parameters. To reveal the processing mechanism, MOC, ginger juice-processed Magnoliae Officinalis Cortex(GMOC), and water-processed Magnoliae Officinalis Cortex(WMOC) were compared. The results showed that the weight coefficients of the appearance traits, extract yield of standard decoction, and total content of honokiol and magnolol determined by AHP-CRITIC weighting method were 0.134, 0.287, and 0.579, respectively. The optimal processing parameters of GMOC were ginger juice dosage of 8%, moistening time of 120 min, and processing at 100 ℃ for 7 min. The content of syringoside and magnolflorine in MOC decreased after processing, and the content of honokiol and magnolol followed the trend of GMOC>MOC>WMOC, which suggested that the change in clinical efficacy of MOC after processing was associated with the changes of chemical composition. The optimized processing technology is stable and feasible and provides references for the modern production and processing of MOC.

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model.

Recently, the global background concentration of ozone (O3) has demonstrated a rising trend. Among various methods, groun-based monitoring of O3 concentrations is highly reliable for research analysis. To obtain information on the spatial characteristics of O3 concentrations, it is necessary that the ground monitoring sites be constructed in sufficient density. In recent years, many researchers have used machine learning models to estimate surface O3 concentrations, which cannot fully provide the spatial and temporal information contained in a sample dataset. To solve this problem, the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network (R-ConvLSTM) to estimate daily maximum 8-hr average (MDA8) O3 over Jiangsu province, China during 2020. In this research, the R-ConvLSTM model not only provides the spatiotemporal information of MDA8 O3, but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network layers. We utilized the TROPOMI total O3 column retrieved from Sentinel-5 Precursor, ERA5 reanalysis meteorological data, and other supplementary data to build a pre-trained dataset. The R-ConvLSTM model achieved an overall sample-base cross-validation (CV) R2 of 0.955 with root mean square error (RMSE) of 9.372 µg/m3. Model estimation also showed a city-based CV R2 of 0.896 with RMSE of 14.029 µg/m3, the highest MDA8 O3 in spring being 122.60 ± 31.60 µg/m3 and the lowest in winter being 69.93 ± 18.48 µg/m3.

Effects of Heavy Metals on Stomata in Plants: A Review.

Stomata are one of the important structures for plants to alleviate metal stress and improve plant resistance. Therefore, a study on the effects and mechanisms of heavy metal toxicity to stomata is indispensable in clarifying the adaptation mechanism of plants to heavy metals. With the rapid pace of industrialization and urbanization, heavy metal pollution has been an environmental issue of global concern. Stomata, a special physiological structure of plants, play an important role in maintaining plant physiological and ecological functions. Recent studies have shown that heavy metals can affect the structure and function of stomata, leading to changes in plant physiology and ecology. However, although the scientific community has accumulated some data on the effects of heavy metals on plant stomata, the systematic understanding of the effects of heavy metals on plant stomata remains limited. Therefore, in this review, we present the sources and migration pathways of heavy metals in plant stomata, analyze systematically the physiological and ecological responses of stomata on heavy metal exposure, and summarize the current mechanisms of heavy metal toxicity on stomata. Finally, the future research perspectives of the effects of heavy metals on plant stomata are identified. This paper can serve as a reference for the ecological assessment of heavy metals and the protection of plant resources.

Bio-straw or not? Determinants of consumption intention under the plastic straw ban.

A new plastic ban has banned the use of single-use non-degradable plastic drinking straws in China's food and beverage industry by the end of 2020. However, this has caused widespread discussion and complaints on social media. What are consumers' reactions and what factors influence consumers to choose bio-straws (substitutes for plastic straws) are unclear. Therefore, this research collected 4367 effective comments (177,832 words in total) on "bio-straws" from social media and extracted keywords based on grounded theory to generate questionnaires. Structural equation modeling was used to analyze the consumption intention and influencing factors of 348 consumers regarding the ban. The results indicate the following: (1) consumer opinion on straws can be summarized into five main categories, namely, consumers' user experience, consumer subjectivity, policy awareness, policy acceptance, and consumption intention; (2) consumer subjectivity, policy awareness, and policy acceptance directly affect consumption intention significantly, while user experience affects consumption intention indirectly; and (3) user experience and consumer subjectivity play significant roles in mediating these relationships. From the perspective of consumers, this study provides an important basis for policymakers to formulate single-use plastic alternative policies in the future.

Shen Qi Wan attenuates renal interstitial fibrosis through upregulating AQP1.

Renal interstitial fibrosis (RIF) is the crucial pathway in chronic kidney disease (CKD) leading to the end-stage renal failure. However, the underlying mechanism of Shen Qi Wan (SQW) on RIF is not fully understood. In the current study, we investigated the role of Aquaporin 1 (AQP1) in SQW on tubular epithelial-to-mesenchymal transition (EMT). A RIF mouse model induced by adenine and a TGF-ß1-stimulated HK-2 cell model were etablished to explore the involvement of AQP 1 in the protective effect of SQW on EMT in vitro and in vivo. Subsequently, the molecular mechanism of SQW on EMT was explored in HK-2 cells with AQP1 knockdown. The results indicated that SQW alleviated kidney injury and renal collagen deposition in the kidneys of mice induced by adenine, increased the protein expression of E-cadherin and AQP1 expression, and decreased the expression of vimentin and α-smooth muscle actin (α-SMA). Similarly, treatmement with SQW-containing serum significantly halted EMT process in TGF-ß1 stimulated HK-2 cells. The expression of snail and slug was significantly upregulated in HK-2 cells after knockdown of AQP1. AQP1 knockdown also increased the mRNA expression of vimentin and α-SMA, and decreased the expression of E-cadherin. The protein expression of vimentin increased, while the expression of E-cadherin and CK-18 significantly decreased after AQP1 knockdown in HK-2 cells. These results revealed that AQP1 knockdown promoted EMT. Furthermore, AQP1 knockdown abolished the protective effect of SQW-containing serum on EMT in HK-2 cells. In sum, SQW attentuates EMT process in RIF through upregulation of the expression of AQP1.

Essential oil of Acorus tatarinowii Schott inhibits neuroinflammation by suppressing NLRP3 inflammasome activation in 3 × Tg-AD transgenic mice.

BACKGROUND: Shi chang pu (Acorus tatarinowii Schott) is a herbal used in the treatment of Alzheimer's disease (AD) in China. The essential oil of Shi chang pu (SCP-oil) is the main active component. However, its effects on the neuroinflammation of AD have not been well studied. PURPOSE: Neuroinflammation mediated by the NLRP3 inflammasome plays a crucial role in AD. This study was designed to evaluate the effect of SCP-oil on cognitive impairment of AppSwe/PSEN1M146V/MAPTP301L triple transgenic (3 × Tg-AD) mice model and investigate the mechanism underlying its anti-inflammation effects. METHODS: Thirty-two 3 × Tg-AD mice at 12 months and 8 wild-type B6 mice were used for this experiment. The 3 × Tg-AD mice were administered with SCP-oil or donepezil hydrochloride for 8 weeks. Morris water maze test and step-down test were used to evaluate the cognitive ability of mice. The pathological changes, neuroinflammation, and the NLRP3 inflammasome related-protein of AD mice were detected by histomorphological examination, TUNEL staining, immunofluorescence, immunohistochemistry, qRT-PCR, Elisa, and western blot assays. RESULTS: SCP-oil treatment attenuated cognitive dysfunction of 3 × Tg-AD mice. Moreover, SCP-oil also ameliorated characteristics pathological of AD, such as pathological changes damage, deposition of Aß, phosphorylation of Tau, and neuronal loss. Additionally, SCP-oil treatment alleviated the neuroinflammation and inhibited phosphorylation of IKKß, NF-κB, and NLRP3 inflammasome related-protein NLRP3, ASC, Caspase-1, cleaved-Caspase-1, and GSDMD-N in the hippocampus of 3 × Tg-AD mice. CONCLUSION: Overall, SCP-oil contributed to neuroprotection in 3 × Tg-AD mice by reduced activation of NLRP3 inflammasome by inhibiting the NF-κB signaling pathway.

Factors influencing caring behaviour among registered nurses during the COVID-19 pandemic in China: A qualitative study using the COM-B framework.

AIM: The aim of this work is to explore the influencing factors of nurses' caring behaviour during the COVID-19 pandemic based on the Capability, Opportunity, Motivation as determinants of Behaviour (COM-B) theoretical framework. BACKGROUND: Nurse caring behaviour is vital to reduce and speed up the healing process of COVID-19 patients. It is important to understand the factors that influence caring behaviour among nurses during the COVID-19 pandemic. Research suggests that when it comes to understanding behaviour, using a theoretical framework is likely to be most effective, and the COM-B framework is a recommended approach. METHODS: Semistructured interviews with 42 nurses working in 11 Chinese cities were conducted, and their verbatim statements were transcribed and analysed using thematic analysis. The results were mapped to COM-B framework. RESULTS: Ten key themes emerged: Capability (professional knowledge and skills, emotional intelligence, cross-cultural care competence); opportunity (resources, organizational culture, social culture); motivation (past experience, character, role, beliefs). CONCLUSIONS: Ten factors were found to influence nurses' caring behaviour. This study added two new influencing factors, social culture and past experiences, that further contributed to the understanding of nurses' care behaviours. IMPLICATIONS FOR NURSING MANAGEMENT: Nurses' caring behaviour is influenced not only by themselves but also by institutions and society, so interventions aiming to improve their caring behaviour should consider these elements. The negative impact of the pandemic on capability factors that influence nurses' caring behaviour should be counteracted as soon as possible.

A Cluster of Metabolic-Related Genes Serve as Potential Prognostic Biomarkers for Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is the most common type of renal cancer, characterized by the dysregulation of metabolic pathways. RCC is the second highest cause of death among patients with urologic cancers and those with cancer cell metastases have a 5-years survival rate of only 10-15%. Thus, reliable prognostic biomarkers are essential tools to predict RCC patient outcomes. This study identified differentially expressed genes (DEGs) in the gene expression omnibus (GEO) database that are associated with pre-and post-metastases in clear cell renal cell carcinoma (ccRCC) patients and intersected these with metabolism-related genes in the Kyoto encyclopedia of genes and genomes (KEGG) database to identify metabolism-related DEGs (DEMGs). GOplot and ggplot packages for gene ontology (GO) and KEGG pathway enrichment analysis of DEMGs with log (foldchange) (logFC) were used to identify metabolic pathways associated with DEMG. Upregulated risk genes and downregulated protective genes among the DEMGs and seven independent metabolic genes, RRM2, MTHFD2, AGXT2, ALDH6A1, GLDC, HOGA1, and ETNK2, were found using univariate and multivariate Cox regression analysis, intersection, and Lasso-Cox regression analysis to establish a metabolic risk score signature (MRSS). Kaplan-Meier survival curve of Overall Survival (OS) showed that the low-risk group had a significantly better prognosis than the high-risk group in both the training cohort (p < 0.001; HR = 2.73, 95% CI = 1.97-3.79) and the validation cohort (p = 0.001; HR = 2.84, 95% CI = 1.50-5.38). The nomogram combined with multiple clinical information and MRSS was more effective at predicting patient outcomes than a single independent prognostic factor. The impact of metabolism on ccRCC was also assessed, and seven metabolism-related genes were established and validated as biomarkers to predict patient outcomes effectively.

Shen Qi Wan Ameliorates Learning and Memory Impairment Induced by STZ in AD Rats through PI3K/AKT Pathway.

Alzheimer's disease is the most common form of neurodegenerative disease, and increasing evidence shows that insulin signaling has crucial roles in AD initiation and progression. In this study, we explored the effect and underlying mechanism of SQW, a representative formula for tonifying the kidney and promoting yang, on improving the cognitive function in a streptozotocin-induced model of AD rats. We investigated memory impairment in the AD rats by using the Morris water test. HE and Nissl staining were employed to observe the histomorphological changes in the hippocampal. Expression levels of NeuN and proteins related to Tau and apoptosis were measured using immunohistochemistry and Western blotting, respectively. Additionally, we performed RNA sequencing, and the selected hub genes were then validated by qRT-PCR. Furthermore, the protein expression levels of PI3K/AKT pathway-related proteins were detected by Western blot. We found that SQW treatment significantly alleviated learning and memory impairment, pathological damage, and apoptosis in rats, as evidenced by an increased level of NeuN and Bcl-2, and decreased phosphorylation of Tau, Bax, and Caspase-3 protein expression. SQW treatment reversed the expression of insulin resistance-related genes (Nr4a1, Lpar1, Bdnf, Atf2, and Ppp2r2b) and reduced the inhibition of the PI3K/AKT pathway. Our results demonstrate that SQW could contribute to neuroprotection against learning and memory impairment in rats induced by STZ through activation of the PI3K/AKT pathway.

New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China.

Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studies. We developed a deep learning model based on a long short-term memory (LSTM) network to estimate the daily maximum 8 h average (MDA8) O3 across eastern China in 2020. The proposed model combines LSTM with an attentional mechanism and residual connection structure. The model employed total O3 column product from the Tropospheric Monitoring Instrument, meteorological data, and other covariates as inputs. Then, the estimates from our model were compared with real observations of the China air quality monitoring network. The results indicated that our model performed better than other traditional models, such as the random forest model and deep neural network. The sample-based cross-validation R2 and RMSE of our model were 0.94 and 10.64 µg m−3, respectively. Based on the O3 distribution over eastern China derived from the model, we found that people in this region suffered from excessive O3 exposure. Approximately 81% of the population in eastern China was exposed to MDA8 O3 > 100 µg m−3 for more than 150 days in 2020.