Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

The clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein 9 (CRISPR /Cas9) immune system is an adaptive immune system widely distributed in bacteria and archaea. It precisely defends against invasion by exogenous phages, viruses, and plasmids through sequence-specific endogenous immune response mechanisms. As the most prominent member of this family, the CRISPR/Cas9 system has evolved into the most widely applied, flexible, and efficient technical platform in the field of genome engineering due to its exceptional genome modification capabilities. Within the CRISPR/Cas9 system, the Cas9 protein, precisely guided by a single-stranded guide RNA (gRNA), can specifically recognize target DNA sequences and induce double-strand breaks. This activates the cell’s DNA repair mechanisms, enabling gene knockout, knock-in, or modification. Demonstrating significant advantages in specificity, flexibility, and operability, CRISPR/Cas9 technology has shown immense potential in the medical field, opening new avenues for modernizing traditional Chinese medicine (TCM) research. On one hand, this technology can be used to construct precise disease models and tailor personalized treatment plans. It enables in-depth elucidation of the molecular mechanisms underlying the action targets and signaling pathways of TCM formulas and active components, thereby unraveling the scientific secrets of their complex mechanisms of action. On the other hand, it demonstrates powerful tool value in improving TCM germplasm resources, identifying and screening superior varieties, evaluating the controllability of TCM quality, and producing innovative drugs, providing technical support for the standardization and precision of TCM. Simultaneously, the high-throughput omics data generated by CRISPR technology is driving artificial intelligence (AI) to construct virtual disease models and drug prediction systems. This empowers the intelligent screening of effective TCM components, the precise prediction of potential targets, and the exploration of “reducing toxicity while enhancing efficacy” through formula combinations. This synergistic innovation between CRISPR and AI aligns perfectly with precision medicine’s urgent demand for personalized, efficient drug development, injecting new momentum into the modernization and transformation of TCM. This paper first systematically reviews and explains the developmental trajectory, structural basis, and action mechanisms of the CRISPR/Cas9 system, tracing its scientific evolution from a bacterial immune system to a gene-editing tool. It then comprehensively outlines the current state of convergence between precision medicine concepts and modernization research in TCM, analyzing the synergistic points and potential spaces for their integration. Against the backdrop of rapid precision medicine advancement, this paper emphasizes how CRISPR/Cas9 gene editing technology empowers in-depth analysis of TCM mechanisms—including specific applications in disease model construction, therapeutic target validation, and multi-target network regulation studies. It further elaborates on its multidimensional practical contributions to modernizing TCM, spanning key domains such as germplasm resource innovation, bioactive compound biosynthesis, quality standardization control, and novel TCM drug development. Finally, this paper envisions the future landscape of deep integration between CRISPR technology and AI: from data-driven intelligent drug screening to high-throughput precision discovery of effective TCM components, and further to intelligent model construction based on “reducing toxicity while enhancing efficacy” mechanisms. The synergistic convergence of these multidimensional technologies will pioneer new scientific paradigms and translational pathways for TCM modernization, propelling TCM toward leapfrogging development in the era of precision medicine.

ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

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.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Liver transplantation is the standard treatment for end-stage liver disease， but it has long been limited by the shortage of donor livers. In clinical practice， three types of donor liver （domino donor livers， small-for-size grafts， and steatotic donor livers） are limited due to issues such as metabolic defects， insufficient volume， and poor quality. This article systematically reviews the definition， clinical application， and bottlenecks of the above three types of donor livers and elaborates on the unique value and clinical practice advances of auxiliary liver transplantation （a special surgical procedure that retains part or all of the recipient’s own liver and superimposes donor liver function support） in avoiding small-for-size syndrome， compensating for metabolic defects， and expanding the application of marginal livers， in order to provide a targeted clinical practice reference for optimizing liver transplantation strategies for end-stage liver disease and improving donor liver utilization rate.

Objective To analyze the increase in hearing thresholds in different frequency bands of workers exposed to different characteristic noises and the influencing factors of binaural high-frequency hearing loss, and to provide theoretical support for occupational health monitoring in enterprises. Methods In 2021, noise-exposed workers were selected from typical noise-exposing enterprises as research subjects, and their occupational health examination data were tracked for three consecutive years. According to the on-site detection from 2021 to 2023, the cumulative noise exposure (CNE) was calculated. The chi-square test was used to compare the increase of the hearing threshold of workers exposed to different characteristic noises in different frequency bands. A generalized estimation equation was constructed to explore the influencing factors of high-frequency hearing loss in the research subjects. Results The age of the study subjects was 23-54 years old, with 1.6-20.1 years of working experience, mainly distributed in manufacturing workshops, technical workshops and public works workshops. The median LAeq,8h was 85.90 (84.5, 86.1) dB(A), and the average CNE was 94.3±2.6 dB(A). The number of people with increased hearing thresholds in each frequency band was 0.5kHz>6kHz>4kHz>3kHz>1kHz>2kHz. There were statistically significant differences in the increase of hearing thresholds in each frequency band, binaural speech frequency impairment, and high-frequency hearing loss among subjects with different characteristics (P<0.05). The detection rate of binaural speech frequency hearing loss was the highest in subjects aged>45 years, with a length of service of>15 years, and with a CNE>96dB(A). The detection rate of binaural high-frequency hearing loss was the highest in subjects aged 35-40 years, with a length of service of 5-10 years, and with a CNE>96dB(A).In addition, the detection rate of binaural speech frequency and high-frequency hearing loss increased with the increase of CNE(P<0.05). The GEE model showed that age>40 years and CNE>96dB(A) were risk factors for high-frequency hearing loss in both ears. Conclusion With increasing age and CNE, hearing thresholds rise across all frequency bands, elevating the risk of binaural speech-frequency and high-frequency hearing loss, thereby increasing the likelihood of occupational noise-induced deafness.

BACKGROUND:Spinal canal decompression using uniportal endoscopic surgery is a new minimally invasive surgery in the treatment of lumbar spinal stenosis.However,this technique needs a steep learning curve and high requirements for surgical equipment and instruments,which limits its clinical application.We previously use the spinal endoscopy as a monitoring endoscopy and combined with unilateral biportal endoscopy to propose a hybrid technique of spinal endoscopy to achieve coaxial endoscopic operation and hands-separate operation. OBJECTIVE:To compare the clinical outcome of hybrid technique and uniportal endoscopic surgery in treatment of lumbar spinal stenosis with bilateral lower limb pain symptoms. METHODS:Ninety patients diagnosed of lumbar spinal stenosis with bilateral symptoms were included and retrospectively analyzed at First People's Hospital,Shanghai Jiao Tong University from August 2020 to August 2022.44 cases were included in group A(hybrid technique group),while 46 cases were included in group B(uniportal endoscopic surgery).The nerve decompression was observed during the surgery.Operation time,hospital stay time,and expenses were recorded in both groups.The visual analog scale scores of lower back pain and both lower extremities pain,Oswestry disability index scores of quality of life and excellent and good rate of modified Macnab criteria were recorded and compared at preoperative,postoperative 3 days,and postoperative 3 and 6 months. RESULTS AND CONCLUSION:(1)The operation time of group A was significantly shorter than that of group B(P<0.05).(2)The lower back pain and lower extremity pain of the severe side at postoperative 3 days,and 3 and 6 months were significantly relieved in both groups(P<0.05).The visual analog scale score of lower extremity pain on the mild side was significantly decreased at postoperative 3 days,3 and 6 months than preoperative score in the group A(P<0.05).The visual analog scale score of lower extremity pain on the mild side was significantly decreased at postoperative 3 days than preoperative score in the group B(P<0.05).The visual analog scale scores of lower extremity pain on the mild side at postoperative 3 and 6 months did not show significant difference than preoperative score in the group B.The comparison between the two groups showed that there was no significant difference in the visual analog scale scores of postoperative lower back pain and lower extremity pain of the severe side(P>0.05).The visual analog scale scores of lower extremity pain on the mild side in the group A were significantly lower than those of group B at postoperative 3 and 6 months(P<0.05).(3)The Oswestry disability index scores of both groups at postoperative 3 day were significantly lower than preoperative score(P<0.05),and there was no significant difference between the two groups 3 days after operation.Oswestry disability index scores of group A at postoperative 3 and 6 months were significantly decreased than preoperative score(P<0.05).The Oswestry disability index scores of group B at postoperative 3 and 6 months did not show significant differences than preoperative score(P>0.05).The comparison between the two groups showed the Oswestry disability index scores of group A were significantly lower than group B at postoperative 3 and 6 months(P<0.05).(4)The results of modified Macnab showed that the excellent and good rate of group A was significantly higher than that of group B(95%,78%,P<0.05).(5)It is indicated that the hybrid technique is a new spinal endoscopy technique,which has the advantages of less trauma and faster recovery as a minimally invasive surgery.The clinical outcome of hybrid technique is superior to that of uniportal endoscopic surgery in the treatment of lumbar spinal stenosis with bilateral symptoms.Additionally,it also has the advantages of good operational flexibility and high decompression efficiency as an open surgery.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.