Cryo-electron tomography (cryo-ET) enables the determination of high-resolution three-dimensional structures of macromolecular complexes within cells in a near-physiological state, providing crucial structural insights into fundamental life processes. Cryo-ET has achieved landmark successes in single-cell models. However, many critical biological processes do not occur in isolated cells but emerge from intercellular coordination within tissues. Furthermore, many research subjects, including neural tissues, tumor biopsies, plant tissues, and clinical pathological samples, cannot be obtained through single-cell culture and must be directly dissected from organisms or tissue blocks. Advancing cryo-ET from single-cell to tissue-level applications is therefore crucial for capturing the full complexity of biological activities in their native context. A major technical bottleneck for tissue cryo-ET lies in the preparation of sufficiently thin (<300 nm) lamellae from vitrified tissue specimens. Although high-pressure freezing can vitrify tissues up to 200 µm thick, these samples are far too thick for direct transmission electron microscopy imaging. Among the available thinning methods, cryo-focused ion beam (cryo-FIB) milling has emerged as the most promising approach, as it avoids the mechanical artifacts inherent to cryo-ultramicrotomy. However, conventional on-the-grid cryo-FIB milling is inefficient for thick tissues, requiring excessive milling time and discarding most of the sample. To overcome these limitations, cryo-lift-out has been developed—a technique in which a micromanipulator physically extracts a chunk of interest from deep within the tissue and transfers it to a dedicated grid for final thinning. This approach bypasses the thickness barrier and enables site-specific analysis of internal structures. This review systematically traces the evolution of cryo-lift-out from its origins in materials science to its adaptation for biological tissues. In room-temperature lift-out, reliable attachment is achieved by gas-injection system (GIS)-assisted metal deposition. Transferring this approach to cryogenic conditions proved challenging because precursor gases condense on all cold surfaces, leading to contamination and poor adhesion. The development of copper-assisted redeposition marked a critical turning point: instead of relying on gas deposition, this method uses ion-beam sputtering to deposit copper atoms at the needle-chunk interface, creating a strong, low-contamination bond. This innovation has enabled robust cryo-lift-out workflows and paved the way for serial lift-out, in which multiple consecutive lamellae are prepared from a single tissue chunk, substantially increasing throughput and enabling volumetric imaging. Despite these advances, several technical challenges remain. Curtaining effects caused by uneven chunk surfaces can introduce artifacts into tomograms, requiring careful optimization of milling parameters and protective coating. The cryo-adhesion step still demands precise control of beam angle, needle positioning, and milling depth, making the process highly operator-dependent. Additionally, the choice of grid geometry is critical. Custom-designed grids with double-sided attachment improves stability and offer better compatibility with cryo-ET tilt series. Automation, which has greatly improved room-temperature lift-out, has not yet been achieved for cryo-lift-out due to the complexity of handling heterogeneous biological tissues and the need for real-time adaptation. Future progress will likely focus on integrating cryo-lift-out with volume electron microscopy to correlate ultrastructure across scales, developing intelligent control systems to reduce user intervention, and extending the technology to challenging samples such as plant tissues and some material science samples for interface study. A systematic analysis of the cryo-lift-out technique clarifies the key limiting factors for its large-scale application and lays a foundation for methodological refinement and technological innovation. By consolidating recent advances and identifying remaining bottlenecks, this review aims to support the broader adoption of cryo-lift-out and accelerate the development of tissue-scale in situ structural biology.

The dried mature peel of Citrus reticulata, a plant in the Rutaceae family and its cultivated varieties, is a commonly used Chinese medicinal material known as Chenpi(Citri Reticulatae Pericarpium). It is rich in nutritional components and medicinal value, with pharmacological effects including relieving cough and eliminating phlegm, strengthening the spleen and drying dampness, protecting the liver and benefiting the stomach, tonifying Qi, and calming the mind. Huanglongbing(HLB), also known as Citrus Huanglongbing, is a destructive disease in citrus production that seriously threatens the development of the citrus industry. HLB causes symptoms such as the inability of Rutaceae plants to produce mature fruit, gradual weakening of the tree, and eventual death, posing a significant threat to the yield and quality of Chenpi. Due to the uneven distribution of the HLB pathogen in infected plants, accurate detection of the pathogen requires the collection of a large number of plant samples. Current sample pretreatment methods, such as traditional extraction methods and commercial extraction kits, are time-consuming and involve multiple steps, which significantly increase the difficulty and workload of HLB diagnosis and have become a bottleneck in HLB detection. In this study, a rapid high-throughput detection method combining alkali lysis and TaqMan qPCR was developed. This method allows the pretreatment of multiple samples within 5 min, and the entire detection process can be completed within 45 min, with a detection limit of 6.67 fg·μL~(-1). The alkali lysis method and commercial kits were used for parallel detection of field-collected citrus samples, and the results showed no significant difference. The sample pretreatment method established in this study is characterized by low cost, simplicity, and high efficiency. Combined with TaqMan qPCR, it can provide technical support for early and on-site diagnosis of HLB. This method is of great significance for disease prevention and control in the citrus industry and is expected to help improve the yield and quality of citrus medicinal materials.
Citrus/microbiology* ; Plant Diseases/microbiology* ; Rhizobiaceae/physiology* ; High-Throughput Screening Assays/methods* ; Liberibacter/physiology*

Objective:The objective of this study was to understand the incidence, spatial and temporal distribution characteristics and trends of bacillary dysentery in China from 2005 to 2024 in order to identify the high-risk groups and reveal the potential risk factors and to provide a scientific basis for optimizing the allocation of preventive and control resources, formulating targeted intervention strategies and assessing the effectiveness of the measures.Methods:The nationally reported incidence data of bacillary dysentery was collected from 2005 to 2024 in the Chinese Center for Disease Control and Prevention National Notifiable Diseases Reporting Information System. Descriptive epidemiological methods were used to analyze the population characteristics of bacillary dysentery cases. A Joinpoint regression model was constructed to examine long-term trends in reported incidence rates and spatial dynamic window scanning statistics were applied to detect spatial clusters of bacillary dysentery cases.Results:Between 2005 and 2024, 3 520 247 cases of bacillary dysentery were reported across China, with an average incidence rate of 12.88 per 100 000 people, after which the rate of decline decreased. The incidence rate showed a general downward trend, featuring a significant inflection point in 2016. It exhibited marked seasonality, peaking from May to October (summer-autumn), which weakened over time. From 2005 to 2024, the most likely clusters were in Beijing and Tianjin. Males, infants, the elderly, farmers, and children not in daycare showed many cases.Conclusions:The results revealed that the peak incidence of bacillary dysentery in China from 2005 to 2024 was featured in the summer-autumn months. High-incidence areas were mainly Beijing and Tianjin. The key groups, including males, infants, the elderly, farmers and children not in daycare, were identified. Enhancing surveillance, targeted health education, and preventive measures, especially in these key populations and in regions where the disease shows a high incidence should be strengthened.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective:The objective of this study was to understand the incidence, spatial and temporal distribution characteristics and trends of bacillary dysentery in China from 2005 to 2024 in order to identify the high-risk groups and reveal the potential risk factors and to provide a scientific basis for optimizing the allocation of preventive and control resources, formulating targeted intervention strategies and assessing the effectiveness of the measures.Methods:The nationally reported incidence data of bacillary dysentery was collected from 2005 to 2024 in the Chinese Center for Disease Control and Prevention National Notifiable Diseases Reporting Information System. Descriptive epidemiological methods were used to analyze the population characteristics of bacillary dysentery cases. A Joinpoint regression model was constructed to examine long-term trends in reported incidence rates and spatial dynamic window scanning statistics were applied to detect spatial clusters of bacillary dysentery cases.Results:Between 2005 and 2024, 3 520 247 cases of bacillary dysentery were reported across China, with an average incidence rate of 12.88 per 100 000 people, after which the rate of decline decreased. The incidence rate showed a general downward trend, featuring a significant inflection point in 2016. It exhibited marked seasonality, peaking from May to October (summer-autumn), which weakened over time. From 2005 to 2024, the most likely clusters were in Beijing and Tianjin. Males, infants, the elderly, farmers, and children not in daycare showed many cases.Conclusions:The results revealed that the peak incidence of bacillary dysentery in China from 2005 to 2024 was featured in the summer-autumn months. High-incidence areas were mainly Beijing and Tianjin. The key groups, including males, infants, the elderly, farmers and children not in daycare, were identified. Enhancing surveillance, targeted health education, and preventive measures, especially in these key populations and in regions where the disease shows a high incidence should be strengthened.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

The formulation and revision of the detection methods of indoor air quality standards is an important, rigorous and delicate endeavor. This paper introduced the formulation and revision of the detection methods of the standards for indoor air quality (GB/T 18883-2022), focusing on the revision process, revision principles, main adjustments and technical points of some key indicators to facilitate users to better understand and apply the detection methods in standards for indoor air quality (GB/T 18883-2022).
Humans ; Air Pollution, Indoor ; China ; Reference Standards ; Air Pollutants/analysis*

Objective: To understand the antimicrobial resistance and genome characteristics of Campylobacter isolates recovered from retailed poultry meat samples in 20 provinces in China in 2020. Methods: In 2020, 265 Campylobacter strains including 244 Campylobacter jejuni and 21 Campylobacter coli collected from retailed poultry meat samples in China were tested for antimicrobial resistance to 9 antimicrobial compounds by using the agar dilution method. Forty-two selected isolates were sent for whole genome sequencing and 38 high-quality genomes were analyzed for their antimicrobial resistance genes, virulence genes, sequence types and genetic diversity. Results: The resistance rates of Campylobacter isolates from poultry meats to tetracycline, nalidixic acid and ciprofloxacin were the highest (84%-100%), with 53.2% of the isolates showing multidrug resistance in this study. The resistance rates of C. coli to erythromycin, azithromycin, telithromycin, gentamicin and clindamycin were significantly higher than those of C. jejuni (P<0.05). The resistance genes conferring resistance to β-lactams (100%, 38/38), quinolones (94.7%, 36/38), tetracycline (81.6%, 31/38) and aminoglycosides (50%, 19/38) were the most frequently detected among 38 Campylobacter genomes. C. jejuni carried more virulence genes than C. coli. In total, 19 and 17 sequence types (ST) were obtained from 20 sequenced C. jejuni and 18 C. coli isolates, respectively, including 5 novel STs. The isolates showed a high genetic diversity based on their sequence types. Conclusion: The phenomenon of antimicrobial resistance in Campylobacter from poultry meat sources in China is relatively serious, and resistance and virulence genes are widely distributed in Campylobacter. There is genetic diversity in Campylobacter.
Humans ; Animals ; Anti-Bacterial Agents/pharmacology* ; Campylobacter/genetics* ; Poultry ; Drug Resistance, Bacterial/genetics* ; Genomics ; China ; Tetracycline

The formulation and revision of the detection methods of indoor air quality standards is an important, rigorous and delicate endeavor. This paper introduced the formulation and revision of the detection methods of the standards for indoor air quality (GB/T 18883-2022), focusing on the revision process, revision principles, main adjustments and technical points of some key indicators to facilitate users to better understand and apply the detection methods in standards for indoor air quality (GB/T 18883-2022).
Humans ; Air Pollution, Indoor ; China ; Reference Standards ; Air Pollutants/analysis*