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High purity and ultrafine DAAF (u-DAAF) is an emerging insensitive charge in initiators. Although there are many ways to obtain u-DAAF, developing a preparation method with stable operation, accurate control, good quality consistency, equipment miniaturization, and minimum manpower is an inevitable requirement to adapt to the current social technology development trend. Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor. Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor, the key parameters (liquid flow rate, explosive concentration and crystallization temperature) were screened and optimized through screening experiments. Under the condition that no surfactant is added and only experimental parameters are controlled, the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm, and the corresponding specific surface area is 8.45 m2·g−1 to 1.33 m2·g−1. In addition, the preparation method has good batch stability, high yield (90.8%–92.6%) and high purity (99.0%–99.4%), indicating a high practical application potential. Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF, and comparable to that of the refined DAAF by conventional spraying crystallization method. This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

Abstract Background To mitigate hospital-acquired transmission of coronavirus disease 2019 (COVID-19), various prevention and control measures have been strictly implemented in medical institutions. These stringent measures can potentially reduce the incidence of hospital-acquired respiratory infections. This study aimed to assess if there were changes in the prevalence of hospital-acquired respiratory infections during a period of national attention focused on COVID-19 prevention. Methods A retrospective analysis of the clinical data from adult patients with hospital-acquired respiratory infections admitted between October and December 2019 and during the same period in 2020 was performed. All patients were referred from a general hospital in Beijing China and COVID-19 patients were not treated at the hospital. Hospital-acquired respiratory infections were diagnosed based on the criteria of the Centers for Disease Control and Prevention/National Healthcare Safety Network (CDC/NHSN). A comparison of the incidence and mortality rate of hospital-acquired respiratory infections between the two selected time periods was conducted. Additionally, multivariate logistics regression analysis was used to identify mortality-associated risk factors. Results This study included 2,211 patients from October to December 2019 (pre-COVID-19 pandemic) and 2,921 patients from October to December 2020 (during the COVID-19 pandemic). The incidence of hospital-acquired respiratory infections in 2019 and 2020 was 4.7% and 2.9%, respectively, with odds ratio (OR): 0.61, 95% confidence interval (CI): 0.46–0.81, and P = 0.001. In-hospital mortality of hospital-acquired respiratory infections in 2019 and 2020 was 30.5% and 38.4%, respectively, with OR: 1.42, 95%CI: 0.78–2.59, and P = 0.25. Multivariate logistics regression analysis revealed that a history of previous malignancy (OR: 2.50, 95%CI: 1.16–5.35, P = 0.02), was associated with in-hospital mortality. Conclusions The incidence of hospital-acquired respiratory infections was significantly decreased following the implementation of various prevention and control measures during the COVID-19 pandemic. A history of previous malignancy was associated with higher in-hospital mortality in older inpatients with hospital-acquired respiratory infections.

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportunities. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the HB properties of 38 known DES and 111 known non-DES systems using their molecular dynamics (MD) simulation trajectories. The analysis reveals that DES systems have two unique features compared to non-DES systems: The DESs have ① more imbalance between the numbers of the two intra-component HBs and ② more and stronger inter-component HBs. Based on these results, we develop 30 ML models using ten algorithms and three types of HB-based descriptors. The model performance is first benchmarked using the average and minimal receiver operating characteristic (ROC)-area under the curve (AUC) values. We also analyze the importance of individual features in the models, and the results are consistent with the simulation-based statistical analysis. Finally, we validate the models using the experimental data of 34 systems. The extra trees forest model outperforms the other models in the validation, with an ROC-AUC of 0.88. Our work illustrates the importance of HBs in DES formation and shows the potential of ML in discovering new DESs.

Abstract Background The purpose of this study was to explore the job burnout of primary healthcare workers in Guangzhou during the prevention and control of COVID-19 epidemic and its influencing factors from the perspective of institutional operation and management in 2021–2022. Methods A cross-sectional study involved 866 primary healthcare workers from different districts of Guangzhou, China. The Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS) was utilized to assess job burnout. From the perspective of organizational operation and management, the possible causes of job burnout among primary healthcare workers during COVID-19 have been categorized into 7 major aspects. Univariate and multivariate logistic regression analyses were conducted to identify influencing factors for job burnout in primary healthcare workers. Results The detection rate of job burnout among primary healthcare workers was 78.29%. Men (OR = 2.39) and whose institution was located in urban–rural fringe (OR = 1.56) were more likely to detect job burnout. Conversely, institution heads showed a lower risk of job burnout. From the perspective of institutional operation and management, workers who were not satisfied with personnel management (OR = 2.41), materials and vehicles (OR = 2.89), subsidies and compensation (OR = 2.18), humanistic care (OR = 2.11), superior management (OR = 8.32) were found to have a higher risk of job burnout. Conclusion The detection rate of job burnout among primary healthcare workers in Guangzhou was relatively high during the period of COVID-19. When there is another sudden major epidemic, the managers of institutions can focus on and deal with the problems related to the operation and management of institutions such as personnel management, materials and vehicles, subsidies and compensation, humanistic care, and superior management, so as to provide logistical support for the workers and alleviate their job burnout.

In order to explore the application value of different grape varieties in fruit beer brewing and their effects on beer quality, we studied the effects of addition of different levels (30% and 40%, V/V) of Syrah or Merlot grape mashes on the aroma, physical and chemical indexes and antioxidant activity of fruit beer. Besides, grape beer with better quality was determined by sensory evaluation. The results showed that both grape varieties increased the concentration and antioxidant properties of phenols including 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging capacity, ferric and cupric ion reducing power abilities, and significantly elevated the acidity and alcohol concentration of beer. The beer made with the addition of 30% Syrah or 40% (V/V) Merlot exhibited the highest content of aroma compounds, which increased by 190.55% and 152.65%, respectively, when compared with the control group. Sensory evaluation showed that the beer made with the addition of 30% Syrah tasted best. In general, the addition of different varieties of grape mashes had a positive effect on improving beer quality and aroma, which could become an important direction for the development of diversified beer products in the future.

Abstract Background and objectives The aim of this study is to assess and examine the risk variables associated with pulmonary infections in non-small cell lung cancer (NSCLC) and to offer evidence-based recommendations for clinical prophylaxis. Methods Up to December 2023, database such as CNKI, Wanfang, VIP Chinese Science and Technology Journals, Chinese Biomedical, Pubmed, Web of science, and the Cochrane library were searched in order to find randomized controlled trials pertaining to non-small cell lung cancer complicated by pulmonary infection. The NOS scale was utilized to assess the quality of the included research, and the Q test findings were utilized to ascertain the degree of heterogeneity among the studies. Results After retrieving 957 studies in total, 10 literatures were ultimately included for additional analysis. Diabetes mellitus [OR, 2.89; 95% CI: 1.85–4.52; P

Abstract Contemporary studies in polarization multiplexing are hindered by the intrinsic orthogonality constraints of polarization states, which restrict the scope of multiplexing channels and their practical applications. This research transcends these barriers by introducing an innovative nonorthogonal polarization-basis multiplexing approach. Utilizing spatially varied eigen-polarization states within metaatoms, we successfully reconstruct globally nonorthogonal channels that exhibit minimal crosstalk. This method not only facilitates the generation of free-vector holograms, achieving complete degrees-of-freedom in three nonorthogonal channels with ultra-low energy leakage, but it also significantly enhances the dimensions of the Jones matrix, expanding it to a groundbreaking 10 × 10 scale. The fusion of a controllable eigen-polarization engineering mechanism with a vectorial diffraction neural network culminates in the experimental creation of 55 intricate holographic patterns across these expanded channels. This advancement represents a profound shift in the field of polarization multiplexing, unlocking opportunities in advanced holography and quantum encryption, among other applications.

Abstract Background Acute pancreatitis (AP) is characterized as a systemic inflammatory condition posing challenges in diagnosis and prognosis assessment. Lipid metabolism abnormalities, especially triacylglycerol (TAG) levels, have been reported, indicating their potential as biomarkers in acute pancreatitis. However, the performance of the TAG cycle, including phospholipid and glycerolipid metabolism, in AP patients has not yet been reported. Methods This study enrolled 91 patients with acute biliary pancreatitis (ABP), 27 with hyperlipidaemic acute pancreatitis (HLAP), and 58 healthy controls (HCs), and their plasma phospholipid and glycerolipid levels were analyzed through liquid chromatography‒mass spectrometry. The phospholipid and glycerolipid contents of plasma collected from AP patients on the first, third, and seventh days of hospitalization were also measured. An orthogonal partial least squares discriminant analysis model served to differentiate the ABP, HLAP and HC groups, and potentially diagnostic lipids were evaluated via receiver operating characteristic curves in both the test and validation sets. Correlations between clinical data and lipids were conducted using Spearman’s method. Clustering via the ‘mfuzz’ R package and the Kruskal‒Wallis H test were conducted to monitor changes during hospitalization. Results Compared with those in HCs, the levels of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidic acid (PA) were lower in AP patients, whereas the levels of phosphatidylinositol (PI) and phosphatidylglycerol (PG) showed the opposite trend. Interestingly, TAG levels were positively correlated with white blood cell counts in ABP patients, and TAGs containing 44–55 carbon atoms were highly correlated with plasma TAG levels in HLAP patients. Phospholipid levels exhibited an inverse correlation with AP markers, in contrast to glycerolipids, which demonstrated a positive correlation with these markers. Additionally, PE (O-16:0/20:4) and PE (18:0/22:6) emerged as potential biomarkers because of their ability to distinguish ABP and HLAP patients from HCs, showing area under the curve (AUC) values of 0.932 and 0.962, respectively. PG (16:0/18:2), PG (16:0/20:4), PE (P-16:0/20:2), PE (P-18:2/18:2), PE (P-18:1/20:3), PE (P-18:1/20:4), PE (O-16:0/20:4), and TAG (56:6/FA18:0) were significantly changed in ABP patients who improved. For HLAP patients, PC (18:0/20:3), TAG (48:3/FA18:1), PE (P-18:0/16:0), and TAG (48:4/FA18:2) showed different trends in patients with improvement and deterioration, which might be used for prognosis. Conclusions Phospholipids and glycerolipids were found to be potential biomarkers in acute pancreatitis, which offers new diagnostic and therapeutic insights into this disease.

Abstract Renal cell carcinoma (RCC) is considered a “metabolic disease” characterized by elevated glycolysis in patients with advanced RCC. Tyrosine kinase inhibitor (TKI) therapy is currently an important treatment option for advanced RCC, but drug resistance may develop in some patients. Combining TKI with targeted metabolic therapy may provide a more effective approach for patients with advanced RCC. An analysis of 14 RCC patients (including three needle biopsy samples with TKI resistance) revealed by sing-cell RNA sequencing (scRNA-seq) that glycolysis played a crucial role in poor prognosis and drug resistance in RCC. TCGA-KIRC and glycolysis gene set analysis identified DEPDC1 as a target associated with malignant progression and drug resistance in KIRC. Subsequent experiments demonstrated that DEPDC1 promoted malignant progression and glycolysis of RCC, and knockdown DEPDC1 could reverse TKI resistance in RCC cell lines. Bulk RNA sequencing (RNA-seq) and non-targeted metabolomics sequencing suggested that DEPDC1 may regulate RCC glycolysis via AKT/mTOR/HIF1α pathway, a finding supported by protein-level analysis. Clinical tissue samples from 98 RCC patients demonstrated that DEPDC1 was associated with poor prognosis and predicted RCC metastasis. In conclusion, this multi-omics analysis suggests that DEPDC1 could serve as a novel target for TKI combined with targeted metabolic therapy in advanced RCC patients with TKI resistance.

Abstract Duchenne muscular dystrophy (DMD) affecting 1 in 3500–5000 live male newborns is the frequently fatal genetic disease resulted from various mutations in DMD gene encoding dystrophin protein. About 70% of DMD-causing mutations are exon deletion leading to frameshift of open reading frame and dystrophin deficiency. To facilitate translating human DMD-targeting CRISPR therapeutics into patients, we herein establish a genetically humanized mouse model of DMD by replacing exon 50 and 51 of mouse Dmd gene with human exon 50 sequence. This humanized mouse model recapitulats patient’s DMD phenotypes of dystrophin deficiency and muscle dysfunction. Furthermore, we target splicing sites in human exon 50 with adenine base editor to induce exon skipping and robustly restored dystrophin expression in heart, tibialis anterior and diaphragm muscles. Importantly, systemic delivery of base editor via adeno-associated virus in the humanized male mouse model improves the muscle function of DMD mice to the similar level of wildtype ones, indicating the therapeutic efficacy of base editing strategy in treating most of DMD types with exon deletion or point mutations via exon-skipping induction.

Abstract Background Acute ischemic stroke (AIS) is a major global public health issue. There is limited research on the relationship between ambient temperature and AIS hospital admissions, and the results are controversial. Our objective is to assess the short-term impact of ambient temperature on the risk of AIS hospital admissions in Yancheng, China. Methods We collected data on daily AIS hospital admissions, meteorological factors, and air quality in Yancheng from 2014 to 2019. We used Poisson regression to fit generalized linear models and distributed lag non-linear models to explore the association between ambient temperature and AIS hospital admissions. The effects of these associations were evaluated by stratified analysis by sex and age. Results From 2014 to 2019, we identified a total of 13,391 AIS hospital admissions. We observed that the influence of extreme cold and heat on admissions for AIS manifests immediately on the day of exposure and continues for a duration of 3–5 days. Compared to the optimal temperature (24.4 °C), the cumulative relative risk under extreme cold temperature (-1.3 °C) conditions with a lag of 0–5 days was 1.88 (95%CI: 1.28, 2.78), and under extreme heat temperature (30.5 °C) conditions with a lag of 0–5 days was 1.48 (95%CI: 1.26, 1.73). Conclusions There is a non-linear association between ambient temperature and AIS hospital admission risk in Yancheng, China. Women and older patients are more vulnerable to non-optimal temperatures. Our findings may reveal the potential impact of climate change on the risk of AIS hospital admissions.

Long-term mapping of winter wheat is vital for assessing food security and formulating agricultural policies. Landsat data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this area. Although various methods, such as index-based methods, curve similarity-based methods and machine learning-based methods, have been developed for winter wheat mapping based on remote sensing, the former two often require satellite data with high temporal resolution, which are unsuitable for Landsat data with sparse time-series. Machine learning is an effective method for crop classification using Landsat data. Yet, applying machine learning for winter wheat mapping in the North China Plain encounters two main issues: 1) the lack of adequate and accurate samples for classifier training; and 2) the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this area. To address these two issues, we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data, with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop maps. Then, we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion, which divided the study area into six subzones with uniform classification features. For each subzone, a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI data. Field sample validation confirmed the high accuracy of the produced maps, with an average overall accuracy of 91.1% and an average kappa coefficient of 0.810 across different years. The derived winter wheat area also has a good correlation (R2 = 0.949) with census area at the provincial level. The results underscore the reliability of the produced annual winter wheat maps. Additional experiments demonstrate that our proposed optimal zoning method outperforms other zoning methods, including Köppen climate zoning, wheat planting zoning and non-zoning methods, in enhancing wheat mapping accuracy. It indicates that the proposed zoning is capable of generating more reasonable subzones for large-scale crop mapping.

Background The level and quality of diagnosis and treatment of Helicobacter pylori (Hp) infections in Shanghai's community health service institutions is unclear, and there is a lack of systematic evaluation and monitoring. Objective To understand the current status of diagnosis, treatment and management of Hp infection in community health centers in Shanghai, to evaluate the quality of diagnosis and treatment, and to explore the problems and improvement measures. Methods A questionnaire was distributed to a total of 249 community health centers in 16 administrative districts of Shanghai and 3 875 general practitioners (GPs) working in the community health centers from May to June 2022 to investigate the standardization of prescriptions for the eradication of Hp infections in the community health centers, the detection of Hp infections, the provision of drugs for the eradication of Hp infections, the management of Hp infections, the difficulties of Hp infections in the treatment of Hp infections, as well as the knowledge of community-based GPs on the diagnosis and treatment of Hp infections. Results The result of the prescription eradication program for Hp infection in primary health care facilities in Shanghai was only 32.0 percent correct. The proportion of health service centers with the ability to conduct Hp infection testing in primary healthcare institutions in Shanghai is high, nearly 80.0%. Most of the community health service centers were able to equip the basic medicines needed for the eradication of Hp, but the rate of bismuth equipment was low, 54.6%. The rate of Hp diagnosis and treatment standard supervision was 80.0%. The demand for the training of standardized diagnosis and treatment of Hp infections was high, accounting for 66.7%. The main difficulties in Hp infection diagnosis and treatment were incomplete drug provision, insufficient doctor's diagnosis and treatment ability and insufficient equipment. Community general practitioners do not have enough basic knowledge about the diagnosis and treatment of Hp infection. Conclusion The capacity to conduct Hp testing needs to be further strengthened in primary care organizations in Shanghai, especially in remote community health service centers, including the purchase of more Hp-related testing equipment and reagents, and the completion of related medications needed for the eradication of Hp. In addition, it is necessary to further strengthen the standardized diagnosis and treatment training of Hp infection for community health centers, improve the diagnosis and treatment ability of general practitioners on Hp infection, and at the same time, strengthen the supervision of Hp diagnosis and treatment standardization, so as to further improve the diagnosis and treatment ability of community general practitioners on Hp infection.

Abstract Lead-free halide double perovskite Cs2AgInCl6 has been extensively studied in recent years due to the lead toxicity and poor stability of common lead halide perovskites. In this study, sodium (Na+) and bismuth (Bi3+) doped into Cs2AgInCl6 double perovskite, then Cs2Ag1− xNaxIn1 − yBiyCl6 films with broadband warm-yellow emissions were achieved by the blade coating method. Herein, Na and Bi content were changed as variables at a series of parameter optimization experiments, respectively. In the Cs2Ag1− xNaxIn1 − yBiyCl6 systems, Na+ broke the parity-forbidden transition of Cs2AgInCl6, and Bi3+ suppressed non-radiative recombination. The partial replacement of Ag+ with Na+ ions and doping with Bi3+ cations were crucial for increasing the intensity of the PL emission. The experimental results showed that the photoluminescence quantum yield of the Cs2Ag0.4Na0.6In0.8Bi0.2Cl6 film was 66.38%, which was the highest data among all samples. It demonstrated remarkable stability under heat and ultraviolet conditions. After five thermal cycles, the PL intensity of the Cs2Ag0.4Na0.6In0.8Bi0.2Cl6 film is only reduced to approximately 5.7% of the initial value. After 720 h continuous ultraviolet irradiation, there occurred 31.9% emission decay of the film.

Abstract NOTCH receptor 3 (NOTCH3) is known to regulate the transcription of oncogenes or tumor suppressor genes, thereby playing a crucial role in tumor development, invasion, maintenance, and chemotherapy resistance. However, the specific mechanism of how NOTCH3 drives immune infiltration in gastrointestinal cancer remains uncertain. The expression of NOTCH3 was analyzed through Western blot, PCR, Oncomine database, and the Tumor Immune Estimation Resource (TIMER) site. Kaplan–Meier plotter, PrognoScan database, and gene expression profile interactive analysis (GEPIA) were used to assess the impact of NOTCH3 on clinical prognosis. The correlation between NOTCH3 expression and immune infiltration gene markers was investigated using TIMER and GEPIA. NOTCH3 was found to be commonly overexpressed in various types of gastrointestinal tumors and was significantly associated with poor prognosis. Furthermore, the expression level of NOTCH3 showed a significant correlation with the tumor purity of gastrointestinal tumors and the extent of immune infiltration by different immune cells. Our findings suggest that NOTCH3 may act as a crucial regulator of tumor immune cell infiltration and can serve as a valuable prognostic biomarker in gastrointestinal cancers.

Abstract Apolipoprotein O (APOO) plays a critical intracellular role in regulating lipid metabolism. Here, we investigated the roles of APOO in metabolism and atherogenesis in mice. Hepatic APOO expression was increased in response to hyperlipidemia but was inhibited after simvastatin treatment. Using a novel APOO global knockout (Apoo −/− ) model, it was found that APOO depletion aggravated diet-induced obesity and elevated plasma cholesterol levels. Upon crossing with low-density lipoprotein receptor (LDLR) and apolipoprotein E (APOE) knockout hyperlipidemic mouse models, Apoo −/− Apoe −/− and Apoo −/− Ldlr −/− mice exhibited elevated plasma cholesterol levels, with more severe atherosclerotic lesions than littermate controls. This indicated the effects of APOO on cholesterol metabolism independent of LDLR and APOE. Moreover, APOO deficiency reduced cholesterol excretion through bile and feces while decreasing phospholipid unsaturation by inhibiting NRF2 and CYB5R3. Restoration of CYB5R3 expression in vivo by adeno-associated virus (AAV) injection reversed the reduced degree of phospholipid unsaturation while decreasing blood cholesterol levels. This represents the first in vivo experimental validation of the role of APOO in plasma cholesterol metabolism independent of LDLR and elucidates a previously unrecognized cholesterol metabolism pathway involving NRF2/CYB5R3. APOO may be a metabolic regulator of total-body cholesterol homeostasis and a target for atherosclerosis management. Apolipoprotein O (APOO) regulates plasma cholesterol levels and atherosclerosis through a pathway involving CYB5R3 that regulates biliary and fecal cholesterol excretion, independently of the LDL receptor. In addition, down-regulation of APOO may lead to impaired mitochondrial function, which in turn aggravates diet-induced obesity and fat accumulation.

Objective The clinical distribution and drug resistance of Escherichia coli and Klebsiella pneumoniae in a hospital of Nanjing from 2020 to 2022 were analyzed in order to provide the basis for clinical rational use of antibiotics. Methods The distribution and drug resistance of Escherichia coli and Klebsiella pneumoniae specimens in Zhongda Hospital Southeast University from 2020 to 2022 were retrospectively analyzed. Results A total of 3 507, 4 323 and 4 806 pathogenic bacteria were detected from 2020 to 2022. There were 616, 748 and 840 strains of Escherichia coli , and 456, 631 and 757 strains of Klebsiella pneumoniae , with the total 3-year detection rate of 17.4% and 14.6%. There was a statistically significant difference in the constituent ratio of pathogenic bacteria between 2020 and 2022 (P＜0.01). From 2020 to 2022, the top three samples of pathogenic bacteria were sputum, blood and urine. From 2020 to 2022, the drug resistance rates of Escherichia coli to cefepime, ceftriaxone, cefazolin, gentamicin, ciprofloxacin, levofloxacin and compound trimethoprim were significantly different (P＜0.01). The drug resistance rates of Klebsiella pneumoniae to imipenem, ertapenem, cefepime, ceftriaxone, cefoperazone sulbactam, cefazolin, cefoxitin, piperacillin tazobactam, ampicillin, amikacin, gentamicin, levofloxacin, nitrofurantoin and compound trimethoprim were significantly different (P＜0.01). Conclusion The average detection rate of Escherichia coli and Klebsiella pneumoniae was more than 30% in 2020—2022. The resistance of Escherichia coli and Klebsiella pneumoniae to various antibacterial drugs is statistically different. The clinically targeted drugs need to be selected in strict accordance with the drug sensitivity results.

Abstract During the crucial stage of the energy transition for combating extreme climate changes, it has been frequently discussed: Whether clean and fossil energies are substitutes or complements? To answer this question, we first analyze the correlations of some main clean and fossil energy markets in 2015–2022. After identifying and measuring the volatility spillovers in these energy markets, the original sequence is decomposed into three subsequences in each time-frequency to accurately capture the temporal relations in the short or long term. Furthermore, we select three periods when global climate change issues occurred frequently for the event analysis, then explore the linkages between the energy markets when experiencing climate uncertainties from different time dimensions. We find that the close interactions between clean energy markets are mainly presented in the long term. Meanwhile, even though the spillover effects between the oil market and others are not obvious in the original sequence, significant spillovers could be observed in the selected periods. Therefore, we can infer that the frequently-occurred climate change issues could be one of the reasons that trigger the volatility spillovers between the oil and other energy markets. As climate uncertainties increase, different reactions between the energy markets can be seen in the short term, while a synchronized trend is also easily observed in the long term. Hence, we conclude that these energies could be substitutes in the short term, while complements in the long run. The above analytic results could be helpful for policymakers and investors to cope with the market fluctuations that are brought by climate issues.

Abstract Owing to concerns about animal proteins, resource limitations, and population growth, there is growing interest in exploring soybeans as animal protein alternatives to fulfill consumption requirements. Black soybean (BS) has superior nutritional and health benefits, compared to yellow soybean (YS). However, BS has been explored less often than YS. While previous reviews have individually focused on the nutritional composition, bioactive compounds, or health benefits of BS, they have not delved into the intricate mechanisms underlying these interactions, especially the distinct roles of the individual components. This comprehensive review aims to bridge this gap by providing an overview of the key nutritional composition and bioactive compounds in BS associated with health benefits, as well as the possible mechanisms underlying these changes. Various processing technologies (physical, biological, and thermal) have been applied to BS. Additionally, the bioavailability, biotransformation, and safety concerns of BS were studied, as these factors are crucial for its potential application, such as natto, films, and microcapsules. However, there are some gaps in the application of BS and YS. In the future, it will be worth exploring the effects of BS protein as meat analogs, 3D printing constituents, and amyloid fibrils, as well as BS lipids as oleogels and BS seed coats as bioactive ingredients in pharmaceutical products.

The purpose of this paper was to introduce several $ b $-generalized contractive mappings in the framework of cone $ b $-metric spaces over Banach algebras. The obtained contractions generalized and extended the counterparts in metric spaces, cone metric spaces, and $ b $-metric spaces. Moreover, via weakening the completeness of the spaces, we gave some fixed point theorems for asymptotically regular mappings without considering the orbital continuity and $ k $-continuity of the mappings. Those who need a specification is our results do not rely on the continuity of $ b $-metric and the normality of cones. In addition, some nontrivial examples were presented to illustrate the superiority of our fixed point theorems.

Quantitative descriptive sensory analysis (QDSA), gas chromatography-ion mobility spectrometry (GC-IMS) and Heracles NEO electronic nose (E-nose) combined with chemometrics were used for differential analysis of volatile compounds in essential oils (EOs) extracted from sweet orange peels (blood and navel) using cold pressing (CP), microwave-assisted hydrodistillation (MAHD) or spinning cone column (SCC). The results indicated that significant variations in flavor composition were found among the three EOs. The CP oil had the highest sensory preference with stronger fruity, sweet, and floral aromas. The MAHD oil had stronger fatty, green, and woody aromas, and the SCC oil had a lower aroma intensity. A total of 64 volatile components were identified by GC-IMS, terpenes, alcohols and aldehydes being the major ones, followed by acids, esters and other compounds. The fingerprint indicated that the contents of terpenes in the CP and MAHD oils were significantly higher than that in the SCC oil, whereas the contents of alcohols and aldehydes in the MAHD and SCC oils were significantly higher than those in the CP oil. Based on relative odor activity value (ROAV), β-myrcene and linalool were identified as the major contributors to the flavor of sweet orange EO. Moreover, using GC-IMS combined with partial least square discriminant analysis (PLS-DA) and variable importance in the projection (VIP), 13 differential volatile compounds were identified as aroma markers to distinguish among the 6 oils. Additionally, E-nose combined with principal component analysis (PCA) and discriminant factor analysis (DFA) also successfully distinguished among the 6 EOs according to their volatile compounds.

Abstract Background This study aimed to explore the expression, molecular mechanism and its biological function of potassium two pore domain channel subfamily K member 1 (KCNK1) in bladder cancer (BC). Methods We integrated large numbers of external samples (n = 1486) to assess KCNK1 mRNA expression levels and collected in-house samples (n = 245) for immunohistochemistry (IHC) experiments to validate at the KCNK1 protein level. Single-cell RNA sequencing (scRNA-seq) analysis was performed to further assess KCNK1 expression and cellular communication. The transcriptional regulatory mechanisms of KCNK1 expression were explored by ChIP-seq, ATAC-seq and ChIA-PET data. Highly expressed co-expressed genes (HECEGs) of KCNK1 were used to explore potential signalling pathways. Furthermore, the immunoassay, clinical significance and molecular docking of KCNK1 were calculated. Results KCNK1 mRNA was significantly overexpressed in BC (SMD = 0.58, 95% CI [0.05; 1.11]), validated at the protein level (p

Abstract Background The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis. Methods A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis’s evidence. Results The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58–0.74) and 0.74 (95% CI 0.67–0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99–3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37–0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80–8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI’s sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p

Abstract Immune checkpoint blockade (ICB) therapy holds promise for bringing long-lasting clinical gains for the treatment of cancer. However, studies show that only a fraction of patients respond to the treatment. In this regard, it is valuable to develop gene expression signatures based on RNA sequencing (RNAseq) data and machine learning methods to predict a patient’s response to the ICB therapy, which contributes to more personalized treatment strategy and better management of cancer patients. However, due to the limited sample size of ICB trials with RNAseq data available and the vast number of candidate gene expression features, it is challenging to develop well-performed gene expression signatures. In this study, we used several published melanoma datasets and investigated approaches that can improve the construction of gene expression-based prediction models. We found that merging datasets from multiple studies and incorporating prior biological knowledge yielded prediction models with higher predictive accuracies. Our finding suggests that these two strategies are of high value to identify ICB response biomarkers in future studies.

Abstract Background Human adipose stromal cells-derived extracellular vesicles (haMSC-EVs) have been shown to alleviate inflammation in acute lung injury (ALI) animal models. However, there are few systemic studies on clinical-grade haMSC-EVs. Our study aimed to investigate the manufacturing, quality control (QC) and preclinical safety of clinical-grade haMSC-EVs. Methods haMSC-EVs were isolated from the conditioned medium of human adipose MSCs incubated in 2D containers. Purification was performed by PEG precipitation and differential centrifugation. Characterizations were conducted by nanoparticle tracking analysis, transmission electron microscopy (TEM), Western blotting, nanoflow cytometry analysis, and the TNF-α inhibition ratio of macrophage [after stimulated by lipopolysaccharide (LPS)]. RNA-seq and proteomic analysis with liquid chromatography tandem mass spectrometry (LC–MS/MS) were used to inspect the lot-to-lot consistency of the EV products. Repeated toxicity was evaluated in rats after administration using trace liquid endotracheal nebulizers for 28 days, and respiratory toxicity was evaluated 24 h after the first administration. In vivo therapeutic effects were assessed in an LPS-induced ALI/ acute respiratory distress syndrome (ARDS) rat model. Results The quality criteria have been standardized. In a stability study, haMSC-EVs were found to remain stable after 6 months of storage at − 80°C, 3 months at − 20 °C, and 6 h at room temperature. The microRNA profile and proteome of haMSC-EVs demonstrated suitable lot-to-lot consistency, further suggesting the stability of the production processes. Intratracheally administered 1.5 × 108 particles/rat/day for four weeks elicited no significant toxicity in rats. In LPS-induced ALI/ARDS model rats, intratracheally administered haMSC-EVs alleviated lung injury, possibly by reducing the serum level of inflammatory factors. Conclusion haMSC-EVs, as an off-shelf drug, have suitable stability and lot-to-lot consistency. Intratracheally administered haMSC-EVs demonstrated excellent safety at the tested dosages in systematic preclinical toxicity studies. Intratracheally administered haMSC-EVs improved the lung function and exerted anti-inflammatory effects on LPS-induced ALI/ARDS model rats.

Abstract Legumain (or asparagine endopeptidase/AEP) is a lysosomal cysteine endopeptidase associated with increased invasive and migratory behavior in a variety of cancers. In this study, co-delivery of Cas9 mRNA and guide RNA (gRNA) by lipid nanoparticles (LNP) for editing of LGMN gene was performed. For in-vitro transcription (IVT) of gRNA, two templates were designed: linearized pUC57-T7-gRNA and T7-gRNA oligos, and the effectiveness of gRNA was verified in multiple ways. Cas9 plasmid was modified and optimized for IVT of Cas9 mRNA. The effects of LGMN gene editing on lysosomal/autophagic function and cancer cell metastasis were investigated. Co-delivery of Cas9 mRNA and gRNA resulted in impaired lysosomal/autophagic degradation, clone formation, migration, and invasion capacity of cancer cells in-vitro. Experimental lung metastasis experiment indicates co-delivery of Cas9 mRNA and gRNA by LNP reduced the migration and invasion capacity of cancer cells in-vivo. These results indicate that co-delivery of Cas9 mRNA and gRNA can enhance the efficiency of CRISPR/Cas9-mediated gene editing in-vitro and in-vivo, and suggest that Cas9 mRNA and gRNA gene editing of LGMN may be a potential treatment for breast tumor metastasis.

Abstract Children's interest in nature is crucial for their understanding and appreciation of the natural environment, as well as for their mental health and biodiversity conservation efforts. To foster this interest, it is important to establish a theoretical framework and explore practical applications. Given the current trend of children spending more time with screens and less time in nature, school gardens offer potential solutions. This study aimed to investigate the effectiveness of a 4‐month teaching programme conducted in a school garden to promote children's individual interest in nature. 24 Grade‐4 students participated in weekly 40‐min activities, which were divided into three treatments: natural observation with assigned tasks, natural observation with open‐ended tasks and inquiry‐based activities. Participants maintained individual portfolios consisting of questionnaires, nature journals, observation descriptions and interviews. Qualitative and quantitative data were analysed to categorize children into three types: those with initiated interest, those with enhanced interest and those with no significant change. Thematic analysis was used to identify factors influencing children's interest in nature based on qualitative data. The results showed that 17 out of 24 children were classified as either ‘interest‐initiated’ or ‘interest‐enhanced’, indicating a generally positive outcome. The school garden provided a novel and safe environment that empowered children to learn and explore autonomously. Teacher scaffolding further supported their curiosity towards the garden's organisms, potentially leading to the development of their individual interests in nature. This study emphasizes the positive impact of involving children in garden‐based activities in primary schools. Implementing a diverse school garden with informative labels and explanation boards, along with teacher support, represents a promising approach to cultivating children's interest in nature. We recommend implementing mini botanical gardens and club activities in schools to bridge formal and informal education. Read the free Plain Language Summary for this article on the Journal blog.