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.

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.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

AIM:To explore the role and mechanism of calcium-sensing receptor(CaSR)in regulating macro-phage polarization in hypertensive rats.METHODS:Male spontaneously hypertensive rats(SHR)and Wistar-Kyoto(WKY)rats were categorized into WKY group,SHR group,SHR+R568(CaSR agonist)group,and SHR+NPS2143(CaSR inhibitor)group.The thoracic aorta was isolated,and the expression of CaSR and macrophage polarization markers in the aorta was observed through immunofluorescence staining.The primary peritoneal macrophages of SHR and WKY rats were aseptically extracted following anesthesia.After intervention with R568 and NPS2143,the expression levels of M1 and M2 markers of peritoneal macrophages were observed by Western blot and immunofluorescence staining.The levels of interleukin(IL)-1β and IL-10 were measured by ELISA.The concentration of Ca2+in peritoneal macrophages was mea-sured by immunofluorescence.Western blot was employed to identify the expression of CaSR and nucleotide-binding oligo-merization domain-like receptor protein 3(NLRP3)inflammasome components.Following anesthesia,vascular smooth muscle cells(VSMCs)were isolated from SHR using an adherent method.Subsequently,a co-culture system was estab-lished with macrophage supernatant.The optimal action time for this co-culture system was determined through CCK-8 as-say.RESULTS:Compared with SHR group,activation of CaSR resulted in a significant decrease in the protein expres-sion of M1 polarization markers(P<0.05)and a concomitant increase in the protein expression of M2 polarization markers in the aorta(P<0.05).Compared with SHR group,administration of R568 led to a significant decrease in the protein ex-pression of M1 polarization markers(P<0.05)and a concomitant increase in the protein expression of M2 polarization markers(P<0.05)in peritoneal macrophages.Additionally,there was a notable reduction in the protein levels of NLRP3 inflammasome components(P<0.05).Furthermore,the fluorescence intensity of intracellular Ca2+was significantly en-hanced following R568 treatment(P<0.05).After administration of MCC950,an NLRP3 inflammasome inhibitor,the re-sults were consistent with those observed following R568 treatment,demonstrating statistical significance(P<0.05).This effect was reversed by the combined intervention of U73122,a phospholipase C(PLC)inhibitor(P<0.05).Compared with the control(0 h),the 24-h peritoneal macrophage supernatant exhibited the strongest capacity to enhance the viabili-ty of VSMCs after 24 h of culture(P<0.05).CONCLUSION:In hypertensive rats,the CaSR inhibits NLRP3 inflamma-some activation via the PLC-Ca2+signaling pathway,thereby mediating an increase in macrophage polarization towards the M2 phenotype and a decrease towards the M1 phenotype.

Aim To investigate the effect of hypobaric hypoxia on macrophage necroptosis and atherosclerotic plaque instability and explore the underlying mechanisms.Methods Mouse bone marrow-derived macrophages were i-solated and cultured,and divided into control group(21％oxygen concentration)and hypoxia group(3％oxygen concen-tration).After 48 hours,cell necroptosis was detected,and the expression of cell necroptosis related proteins was deter-mined by Western blot.Healthy male ApoE-/-mice were randomly divided into control group and hypobaric hypoxia group.After the intervention for 16 weeks,the plasma lipids and inflammatory cytokines were measured,the areas of ath-erosclerotic plaque and necrotic core were evaluated by HE staining.The content of plaque collagen was detected by Mas-son staining.The number of macrophages in the plaque and the expression of necrotic apoptosis related proteins were de-tected by immunohistochemical staining and Western blot.Results Hypoxia induced increased necrotic apoptosis of macrophages(P＜0.01),while necroptotic inhibitor necrostatin-1(Nec-1)reduced hypoxia induced cell death(P＜0.05);hypoxia leads to a decrease in the expression of adenosine deaminase acting on RNA 1(ADAR1)in macrophages(P＜0.01),and an increase in the expression of Z-DNA binding protein 1(ZBP1),phosphorylated receptor-interacting serine/threonine-protein kinase(p-RIPK3),and phosphorylated mixed lineage kinase domain-like protein(p-MLKL)(all P＜0.01).Compared with the control group,the plasma lipid levels of ApoE-/-mice in the hypobaric hypoxia group did not change significantly(P＞0.05),the plasma inflammatory cytokines(TNF-α,IL-1β,IL-6 and MCP-1)increased(all P＜0.05),the area of atherosclerotic plaque increased(P＜0.05),the area of plaque necrotic core increased,the content of plaque collagen decreased,the number of macrophages increased,the expression of ADAR1 decreased,and the expres-sion of ZBP1 and p-MLKL increased(all P＜0.01).Conclusion Hypobaric hypoxia causes the imbalance of A-DAR1/ZBP1 expression in macrophages,activates RIPK3/MLKL signaling pathway,promotes macrophage necroptosis,in-creases the area of plaque necrosis core,and leads to increase instability of atherosclerotic plaque.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Aim To investigate the effect of hypobaric hypoxia on macrophage necroptosis and atherosclerotic plaque instability and explore the underlying mechanisms.Methods Mouse bone marrow-derived macrophages were i-solated and cultured,and divided into control group(21％oxygen concentration)and hypoxia group(3％oxygen concen-tration).After 48 hours,cell necroptosis was detected,and the expression of cell necroptosis related proteins was deter-mined by Western blot.Healthy male ApoE-/-mice were randomly divided into control group and hypobaric hypoxia group.After the intervention for 16 weeks,the plasma lipids and inflammatory cytokines were measured,the areas of ath-erosclerotic plaque and necrotic core were evaluated by HE staining.The content of plaque collagen was detected by Mas-son staining.The number of macrophages in the plaque and the expression of necrotic apoptosis related proteins were de-tected by immunohistochemical staining and Western blot.Results Hypoxia induced increased necrotic apoptosis of macrophages(P＜0.01),while necroptotic inhibitor necrostatin-1(Nec-1)reduced hypoxia induced cell death(P＜0.05);hypoxia leads to a decrease in the expression of adenosine deaminase acting on RNA 1(ADAR1)in macrophages(P＜0.01),and an increase in the expression of Z-DNA binding protein 1(ZBP1),phosphorylated receptor-interacting serine/threonine-protein kinase(p-RIPK3),and phosphorylated mixed lineage kinase domain-like protein(p-MLKL)(all P＜0.01).Compared with the control group,the plasma lipid levels of ApoE-/-mice in the hypobaric hypoxia group did not change significantly(P＞0.05),the plasma inflammatory cytokines(TNF-α,IL-1β,IL-6 and MCP-1)increased(all P＜0.05),the area of atherosclerotic plaque increased(P＜0.05),the area of plaque necrotic core increased,the content of plaque collagen decreased,the number of macrophages increased,the expression of ADAR1 decreased,and the expres-sion of ZBP1 and p-MLKL increased(all P＜0.01).Conclusion Hypobaric hypoxia causes the imbalance of A-DAR1/ZBP1 expression in macrophages,activates RIPK3/MLKL signaling pathway,promotes macrophage necroptosis,in-creases the area of plaque necrosis core,and leads to increase instability of atherosclerotic plaque.

Objective:To evaluate the feasibility of using the domestic ArcherQA system for fast and simplified independent verification of CyberKnife (CK) stereotactic radiotherapy (SRT) plans.Methods:SRT plans of 57 patients treated with CK at Tianjin Medical University Cancer Institute and Hospital from August 2021 to August 2022 were retrospectively analyzed, including 15 intracranial, 30 pulmonary, and 12 abdominal tumors cases. Point-dose and planar-dose verifications were performed using an ionization chamber and radiochromic films embedded in a homogeneous phantom, and the results were compared with those calculated by the treatment planning system (TPS). The localization CT images and corresponding SRT plans were imported into the ArcherQA system for independent dose verification and analysis. The correlation between ArcherQA results and phantom measurements was analyzed, with comparisons of target mean dose differences and γ pass rates.Results:Phantom measurement results showed, the measured point-dose differences for intracranial, lung, and abdominal plans were -0.94% ± 3.22%, 1.92% ± 2.05%, and 2.12% ± 0.77%, respectively. The mean dose differences in target dose calculation between ArcherQA and TPS: intracranial in the gross tumor volume (GTV) regions were 0.34% ± 2.21%, lung tumor GTV were -2.47% ± 2.46%, and abdominal tumor GTV were 0.80% ± 2.61%, respectively. Among them, the abdominal GTV region showed the highest correlation between ArcherQA and measured results ( r=0.78). The average two-dimensional γ pass rates (2 mm/2%, threshold=10%) measured using phantom films were 95.92% ± 2.35% for intracranial, 95.70% ± 2.74% for lung, and 96.74% ± 3.41% for abdominal tumors plans, respectively. The three-dimensional ArcherQA results showed comparable γ pass rates (1 mm/2%, threshold=10%) for lung and abdominal GTV and PTV regions, with similar medians and data dispersion to film measurements. Conclusions:The ArcherQA system enables rapid and efficient independent dose verification of CK SRT plans without the need for additional hardware. The verification results show good correlation with phantom measurements, supporting its potential as an auxiliary quality assurance tool in clinical CK SRT implementation.