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Extensive testing is essential to break the transmission of SARS-CoV-2, which causes the ongoing COVID-19 pandemic. Here, we present a CRISPR-based diagnostic assay that is robust to viral genome mutations and temperature, produces results fast, can be applied directly on nasopharyngeal (NP) specimens without RNA purification, and incorporates a human internal control within the same reaction. Specifically, we show that the use of an engineered AsCas12a enzyme enables detection of wildtype and mutated SARS-CoV-2 and allows us to perform the detection step with loop-mediated isothermal amplification (LAMP) at 60-65 °C. We also find that the use of hybrid DNA-RNA guides increases the rate of reaction, enabling our test to be completed within 30 minutes. Utilizing clinical samples from 72 patients with COVID-19 infection and 57 healthy individuals, we demonstrate that our test exhibits a specificity and positive predictive value of 100% with a sensitivity of 50 and 1000 copies per reaction (or 2 and 40 copies per microliter) for purified RNA samples and unpurified NP specimens respectively. As the COVID-19 pandemic continues, variants of the virus are emerging. Here the authors present a diagnostic assay that can detect wildtype and known variants using engineered Cas12a.

Objective: This study aimed to comprehensively investigate the correlation of ERCC1 expression and chemosensitivity of ovarian cancer. Methods: The literature on the relationship between the excision repair cross complementary gene 1 (ERCC1) and the chemosensitivity of ovarian cancer published in PubMed, Web of Science, EMBASE, CNKI, and the China Wanfang database from the establishment of the databases to June 2020 were searched. Chemosensitivity is evaluated by clinical effective rate (complete remission plus partial remission). Statistical analysis was carried out by using Stata 15.1 software. Results: A total of 11 articles met the inclusion criteria, consisting of 758 patients with ovarian cancer. The results showed a significant difference in chemosensitivity between the low expression group and the high expression group of ERCC1 (odds ratio 4.23; 95% confidence interval 2.96, 6.06; P < 0. 01). The same result was shown in the ethnicity subgroup. Conclusion: The chemosensitivity of ovarian cancer patients with a low expression of ERCC1 is better than that of patients with a high expression.

Background Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of lung cancer patients with mutated EGFR. However, the efficacy of EGFR-TKIs in wild-type EGFR tumors has been shown to be marginal. Methods that can sensitize EGFR-TKIs to EGFR wild-type NSCLC remain rare. Hence, we determined whether combination treatment can maximize the therapeutic efficacy of EGFR-TKIs. Methods We established a focused drug screening system to investigate candidates for overcoming the intrinsic resistance of wild-type EGFR NSCLC to EGFR-TKIs. Molecular docking assays and western blotting were used to identify the binding mode and blocking effect of the candidate compounds. Proliferation assays, analyses of drug interactions, colony formation assays, flow cytometry and nude mice xenograft models were used to determine the effects and investigate the molecular mechanism of the combination treatment. Results Betulinic acid (BA) is effective at targeting EGFR and synergizes with EGFR-TKIs (gefitinib and osimertinib) preferentially against wild-type EGFR. BA showed inhibitory activity due to its interaction with the ATP-binding pocket of EGFR and dramatically enhanced the suppressive effects of EGFR-TKIs by blocking EGFR and modulating the EGFR-ATK-mTOR axis. Mechanistic studies revealed that the combination strategy activated EGFR-induced autophagic cell death and that the EGFR-AKT-mTOR signaling pathway was essential for completing autophagy and cell cycle arrest. Activation of the mTOR pathway or blockade of autophagy by specific chemical agents markedly attenuated the effect of cell cycle arrest. In vivo administration of the combination treatment caused marked tumor regression in the A549 xenografts. Conclusions BA is a potential wild-type EGFR inhibitor that plays a critical role in sensitizing EGFR-TKI activity. BA combined with an EGFR-TKI effectively suppressed the proliferation and survival of intrinsically resistant lung cancer cells via the inhibition of EGFR as well as the induction of autophagy-related cell death, indicating that BA combined with an EGFR-TKI may be a potential therapeutic strategy for overcoming the primary resistance of wild-type EGFR-positive lung cancers. Graphical abstract Highlights 1. BA is a potent wild-type EGFR inhibitor. 2. BA enhances the anticancer efficacy of erlotinib/gefitinib in NSCLC patients with wild-type EGFR. 3. The combination of BA and gefitinib/osimertinib synergistically blocks EGFR and inhibits the PI3K-AKT-mTOR signaling pathway, leading to autophagic cell death and cell cycle arrest. 4. This combination strategy targets wild-type EGFR in NSCLC and induces autophagy and tumor suppression in vivo. BA, an EGFR inhibitor, sensitizes EGFR-TKIs’ activity, indicating that BA plus EGFR-TKIs may be a potential therapeutic strategy to overcome the primary resistance of wild-type EGFR NSCLC.

Herein we investigated the morphology, chemical characteristics, and source apportionment of fine particulate matter (PM 2.5 ) samples collected from five sites in Jiaxing. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that soot aggregates and coal-fired fly ash were generally the most abundant components in the samples. All the samples were analyzed gravimetrically for mass concentrations and their various compositions were determined. Our results revealed that the PM 2.5 concentrations in the samples were in the following order: winter > spring > autumn > summer. The PM 2.5 concentrations in winter and spring were higher than those in autumn and summer, except for inorganic elements. Carbonaceous species and water-soluble inorganic ions were the most abundant components in the samples, accounting for 26.17–50.44% and 34.27–49.6%, respectively. The high secondary organic carbon/organic carbon ratio indicated that secondary organic pollution in Jiaxing was severe. The average ratios of NO 3 − /SO 4 2− , ranging from 1.01 to 1.25 at the five sites, indicated that mobile pollution sources contributed more to the formation of PM 2.5 than stationary sources. The BeP/(BeP + BaP) ratio (0.52–0.71) in samples reflected the influence of transportation from outside of Jiaxing. The positive matrix factorization (PMF) model identified eight main pollution sources: secondary nitrates (26.95%), secondary sulfates (15.49%), secondary organic aerosol (SOA) (19.64%), vehicle exhaust (15.67%), coal combustion (8.6%), fugitive dust (7.7%), ships and heavy oil (5.23%), biomass burning, and other sources (0.91%). Therefore, PM 2.5 pollution in Jiaxing during the winter and spring seasons was more severe than that in the summer and autumn. Secondary aerosols were the most important source of PM 2.5 pollution; therefore, focus should be placed on controlling gaseous precursors.

Studying the energy use behavior of occupants is crucial for accurately predicting building energy consumption. However, few studies have considered the impact of occupant behaviors on energy consumption in university dormitories. The objective of this study is to establish an agent-based model of energy consumption for university dormitories based on energy use behavior. The dormitories of a typical university in Sichuan, China, were subdivided into three clusters using a two-step cluster analysis. Subsequently, the energy use behaviors of occupants in each type of dormitory were characterized to establish a stochastic energy use behavior model. On the basis of the above, NETLOGO was used to construct an agent-based model for dormitories’ energy consumption to dynamically simulate energy use behavior. The accuracy of the model was verified by comparing the simulated values with the measured data. Finally, a building-energy-friendly retrofit scheme was proposed, and it was found that the optimized dormitory reduced energy consumption by 16.07%. Therefore, the results can provide information support for energy-saving decisions during the early design and retrofit phases of buildings. With the popularity of centralized supply, the research methodology may provide an extensive reference for energy management policies and sustainable strategies in the building sector.

Drought stress severely impairs seed germination and early seedling establishment, and disrupts the uptake and distribution of essential mineral nutrients in plants. This study investigated the effects of polyethylene glycol (PEG)-simulated drought and Na2SeO3 application on the accumulation and redistribution of phosphorus (P), potassium (K), calcium (Ca), sulphur (S), magnesium (Mg), iron (Fe), zinc (Zn), copper (Cu), and manganese (Mn) in wheat roots and shoots. Under PEG-simulated drought, increasing PEG concentrations resulted in a progressive decline in nutrient concentrations in both roots and shoots, with significant reductions in K, Ca, S, Zn, and Mn in roots, and K, Ca, Mg, and Mn in shoots. However, Na2SeO3 application mitigated these adverse effects by enhancing nutrient redistribution during early seedling growth. Specifically, under 15% PEG-simulated drought stress, Na2SeO3 treatments significantly increased shoot K, Mg, Fe, and Cu concentrations, highlighting selenium’s role in facilitating the translocation of these key elements. These results demonstrate that Na2SeO3 effectively mitigates drought-related nutrient imbalances and promotes ion remobilisation from germinating seeds to developing roots and shoots under water-deficient conditions.

Resveratrol (RES) suffers from low bioavailability and poor gastrointestinal stability, limiting its health benefits. To overcome these challenges, we developed biomimetic mineralized nanoparticles based on walnut protein peptides (WPP-RES@CaP) for intestinal-targeted RES delivery. WPP with a 31.83% degree of hydrolysis was optimal for RES encapsulation. Subsequent mineralization with 5 mM Ca2+ significantly enhanced the encapsulation efficiency (EE) to 95.86%, compared to 73.69% for non-mineralized WPP-RES nanoparticles. The particle size and zeta potential of WPP-RES@CaP were 795 ± 16 nm and −27 ± 1 mV, respectively. Beyond the initial hydrophobic and π-π interactions, mineralization introduced additional stabilizing forces, including metal–ligand coordination, salt bridges, and electrostatic interactions, which collectively enhanced the structural integrity and RES retention of WPP-RES@CaP. During in vitro gastrointestinal digestion, the formation of a CaP shell protected RES and WPP from excessive degradation in the gastric phase. The 77.57% RES in WPP-RES@CaP was continuously released in the intestinal phase, which was higher than that of WPP-RES (49.73%). Meanwhile, the introduction of Ca2+ promoted the antioxidant activity of WPP-RES@CaP, which demonstrated higher DPPH and ABTS radical-scavenging activity assays than WPP-RES both before and after digestion. It was probably due to the synergistic effect of more released RES, antioxidant-free amino acids, and peptides. This mineralized peptide-based system provided a strategy for improving the delivery of hydrophobic bioactive compounds in functional foods.

This article focuses on predicting holiday flight passenger flow to optimize airline resource allocation. Analyzing daily passenger data during key holidays, including New Year’s Day, Qingming Festival, Labour Day, Dragon Boat Festival, Mid-Autumn Festival, and National Day, the study employs four machine learning models: Random Forest, Multilayer Perceptron, LightGBM, and Stacking. Findings reveal that all models effectively capture holiday flow patterns, with LightGBM demonstrating superior prediction accuracy. Moreover, creating unified models for all holidays outperforms individual holiday-specific models. The study delves into the factors influencing the varying performance of the best model across different features, providing insightful analysis and discussion.

Herein we investigated the morphology, chemical characteristics, and source apportionment of fine particulate matter (PM ) samples collected from five sites in Jiaxing. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that soot aggregates and coal-fired fly ash were generally the most abundant components in the samples. All the samples were analyzed gravimetrically for mass concentrations and their various compositions were determined. Our results revealed that the PM concentrations in the samples were in the following order: winter > spring > autumn > summer. The PM concentrations in winter and spring were higher than those in autumn and summer, except for inorganic elements. Carbonaceous species and water-soluble inorganic ions were the most abundant components in the samples, accounting for 26.17-50.44% and 34.27-49.6%, respectively. The high secondary organic carbon/organic carbon ratio indicated that secondary organic pollution in Jiaxing was severe. The average ratios of NO /SO , ranging from 1.01 to 1.25 at the five sites, indicated that mobile pollution sources contributed more to the formation of PM than stationary sources. The BeP/(BeP + BaP) ratio (0.52-0.71) in samples reflected the influence of transportation from outside of Jiaxing. The positive matrix factorization (PMF) model identified eight main pollution sources: secondary nitrates (26.95%), secondary sulfates (15.49%), secondary organic aerosol (SOA) (19.64%), vehicle exhaust (15.67%), coal combustion (8.6%), fugitive dust (7.7%), ships and heavy oil (5.23%), biomass burning, and other sources (0.91%). Therefore, PM pollution in Jiaxing during the winter and spring seasons was more severe than that in the summer and autumn. Secondary aerosols were the most important source of PM pollution; therefore, focus should be placed on controlling gaseous precursors.