BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

OBJECTIVE: Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control. METHODS: Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes. RESULTS: Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16. CONCLUSION A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans ; Adenoviruses, Human/isolation & purification* ; Respiratory Tract Infections/epidemiology* ; Child, Preschool ; Child ; Recombination, Genetic ; Male ; Beijing/epidemiology* ; Infant ; Female ; Phylogeny ; Adenovirus Infections, Human/epidemiology* ; Acute Disease ; Genome, Viral

Infrared spectroscopy technology has many advantages such as high efficiency and non-destructiveness,and has an important research and application value in the field of petroleum pollutant classification and detection.In this study,a petroleum pollutant classification method by combing the discrete wavelet transform(DWT)algorithm and a one-dimensional convolutional neural network based on the Inception module(Inception-1D-CNN)was proposed.Firstly,the DWT algorithm was used to denoise the original infrared spectral data to eliminate the interference information caused by experimental environment,instrument error and manual operation.Then,the inception-1D-CNN model was used to obtain multi-scale infrared spectroscopy feature information,and then classify the petroleum pollutants.Experimental results showed that compared with preprocessing methods such as standard normal variable(SNV),adaptive iteratively reweighted penalized least squares(AirPLS),and Savitzky-Golay smoothing(S-G),the prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 3×1 was 86.6%,which was 6.6%,6.6%and 3.3%higher,respectively.The prediction accuracy of DWT algorithm combined with 1D-CNN model with a convolutional kernel size of 5×1 was 93.3%,which was 10.0%,7.0%and 3.3%higher,respectively.The prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 7×1 was 90.0%,which was 6.7%,10.0%and 3.4%higher,respectively.The prediction accuracy of the DWT algorithm combined with the inception-1D-CNN model was 100.0%,which was 10.0%,10.0%and 3.4%higher,respectively.Therefore,the DWT algorithm combined with the inception-1D-CNN model could accurately classify and predict petroleum pollutants,and provided a certain basis for the subsequent treatment of oil spills on the sea surface.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

In the study, to explore the anti-tumor effects and mechanisms of chlorpromazine (CPZ) and perphenazine (PPZ) combined with temozolomide (TMZ) on human glioma cell lines, we performed MTT assays to determine the growth inhibitory rate of CPZ, PPZ and TMZ in mono and combined treatments. The anti-tumor effects of CPZ and PPZ alone or in combination with TMZ were determined by colony formation, cell apoptosis, cell cycle arrest, reactive oxygen species (ROS) production and mitochondrial membrane potential (MMP) detection (JC-1). The expression level of p53 was detected by immunofluorescence assay. Furthermore, autophagy under different administrations was detected by flow cytometry and confocal imaging to explore the anti-tumor mechanism of CPZ and TMZ. Protein phosphatase 2A (PP2A), cancerous inhibitor of protein phosphatase 2A (CIP2A) and proto-oncogene protein (c-Myc) were detected by immunofluorescence assay, tumor stem cell markers (CD44, CD133) and aldehyde dehydrogenase (ALDH) were detected by flow cytometry to explore the anti-tumor mechanism of PPZ and TMZ. The results showed that after 72 h treatments of combinations, the values of half maximal inhibitory concentration (IC₅₀) of TMZ on U87 and U251 cells were reduced, and the ability of TMZ to induce apoptosis and cycle arrest was improved. In addition, the combination of CPZ and TMZ could induce an increased effect of autophagy via activating the relevant pathway of p53 gene in glioma cells. The combination of PPZ and TMZ increased the sensitivity of glioma cells to TMZ, and the underlying mechanism might be related to the inhibition of CIP2A/PP2A/c-Myc signaling pathway. In conclusion, CPZ and PPZ combined with TMZ, showed the significant synergistic effects in cancer treatment, which are the novel and potential therapeutic regimens providing a new treatment strategy for human glioma.

Humans ; Intervertebral Disc Displacement/surgery* ; Skull ; Lumbar Vertebrae/surgery* ; Blindness ; Treatment Outcome ; Intervertebral Disc Degeneration/surgery*

Objective: To understand the population structure of food-borne Staphylococcus (S.) aureus in China. Methods: Whole genome sequencing was used to analyze 763 food-borne S. aureus strains from 16 provinces in China from 2006 to 2020. Multilocus sequence typing (MLST), staphylococcal protein A gene (spa) typing, and staphylococcal chromosome cassettemec (SCCmec) typing were conducted, and minimum spanning tree based on ST types (STs) was constructed by BioNumerics 7.5 software. Thirty-one S. aureus strains isolated from imported food products were also included in constructing the genome phylogenetic tree. Results: A total of 90 STs (20 novel types) and 160 spa types were detected in the 763 S. aureus isolates. The 72 STs (72/90, 80.0%) were related to 22 clone complexes. The predominant clone complexes were CC7, CC1, CC5, CC398, CC188, CC59, CC6, CC88, CC15, and CC25, accounting for 82.44% (629/763) of the total. The STs and spa types in the predominant clone complexes changed over the years. The methicillin-resistant S. aureus (MRSA) detection rate was 7.60%, and 7 SCCmec types were identified. The ST59-t437-Ⅳa (17.24%, 10/58), ST239-t030-Ⅲ (12.07%, 7/58), ST59-t437-Ⅴb (8.62%, 5/58), ST338-t437-Ⅴb (6.90%, 4/58) and ST338-t441-Ⅴb (6.90%, 4/58) were the main types in MRSA strains. The genome phylogenetic tree had two clades, and the strains with the same CC, ST, and spa types clustered together. All CC7 methicillin sensitive S. aureus strains were included in Clade1, while 21 clone complexes and all MRSA strains were in Clade2. The MRSA strains clustered according to the SCCmec and STs. The strains from imported food products in CC398, CC7, CC30, CC12, and CC188 had far distances from Chinese strains in the tree. Conclusions: In this study, the predominant clone complexes of food-borne strains were CC7, CC1, CC5, CC398, CC188, CC59, CC6, CC88, CC15, and CC25, which overlapped with the previously reported clone complexes of hospital and community-associated strains in China, suggesting that close attention needs to be paid to food, a vehicle of pathogen transmission in community and food poisoning.
Humans ; Staphylococcus aureus/genetics* ; Methicillin-Resistant Staphylococcus aureus/genetics* ; Multilocus Sequence Typing ; Phylogeny ; Staphylococcal Infections/epidemiology* ; China/epidemiology*

According to the theory of 'Xingben Dazao' of Psoralea corylifolia Linn. (BL), the susceptible syndromes and biomarkers of liver injury caused by BL were searched. Rat models of kidney-yin deficiency syndrome (M_yin) and kidney-yang deficiency syndrome (M_yang) were established, and all animal experimental operations and welfare following the provisions of the First Affiliated Experimental Animal Ethics and Animal Welfare Committee of Henan University of Traditional Chinese Medicine (No. YFYDW2020017). The results showed that BL significantly decreased the body weight, water intake, and urine weight of M_yin rats and increase the organ indexes of the liver, testis, adrenal gland, and spleen and the expression of alanine aminotransferase (ALT). Meantime, BL significantly increased the urine weight of M_yang rats and decreased the expression of ALT and aspartate aminotransferase (AST). Hematoxylin and eosin (HE) staining showed that BL could aggravate inflammatory infiltration of hepatocytes in rats with M_yin and alleviate liver injury in rats with M_yang. Metabolomics identified 17 BL co-regulated significant differential metabolic markers in M_yin and M_yang rats. Among them, 8 metabolites such as glutamine, quinolinate, biliverdin, and lactosylceramide showed opposite trends, mainly involving cysteine and methionine metabolism, tyrosine metabolism, tryptophan metabolism, purine metabolism, sphingolipid metabolism, glycerol phospholipid metabolism, glutamine metabolism, and other pathways. M_yin/M_yang may be the susceptible constitution of BL for liver damage or protection, which may be related to the regulation of amino acid metabolism and sphingolipid metabolism. The study can provide some experimental data support for the safe and accurate use of BL in the clinical practice of traditional Chinese medicine.

Abstract: Objective To explore and analyze the diagnostic value of multicolor melting curve analysis (MMCA) for the resistance of five anti-tuberculosis drugs, so as to clarify the clinical value of MMCA in detecting drug resistance of Mycobacterium tuberculosis. Methods From April 2021 to May 2022, 200 patients with positive Mycobacterium tuberculosis admitted to the Fourth People's Hospital of Qinghai Province were selected as research objects, and sputum specimens were taken from the patients. Traditional Mycobacterium tuberculosis drug sensitivity test (modified Löwenstein-Jensen medium method) and MMCA analysis were respectively given to detect the resistance of five anti-tuberculosis drugs, including isoniazid, ethambutol, streptomycin, rifampicin and isoniazid, respectively. Those samples with inconsistent results between the two diagnosis methods were subjected to gene sequencing verification, and the diagnosis efficiency of MMCA for the five anti-tuberculosis drugs was compared. Results Using Mycobacterium tuberculosis drug sensitivity as the gold standard for drug resistance diagnosis, the sensitivity of MMCA for detecting drug resistance of rifampicin, ethambutol, streptomycin, isoniazid and levofloxacin were 95.83% (46/48), 93.75% (15/16), 100.00% (15/15), 100.00% (20/20) and 70.00% (7/10), respectively, with statistical differences between groups (P<0.05). There were no statistically significant differences in the specificity, positive predictive value, negative predictive value and accuracy of MMCA for the five anti-tuberculosis drugs (P>0.05). For the 8 samples with inconsistent results between MMCA and modified Löwenstein-Jensen medium method, gene sequencing was performed and compared with the results of gene sequencing. After comparison with gene sequencing results, it was found that the coincidence rate of MMCA and gene sequencing results was 75.00% (6/8). Conclusions In the detection of drug-resistant mutations in TB patients, multi-color probe fusion curve analysis has high diagnostic efficacy for first-line anti-tuberculosis drugs, but is not sensitive to second-line anti-tuberculosis drug levofloxacin. Therefore, for the detection of first-line anti-tuberculosis drugs, MMCA has a good clinical application prospect.