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.

BACKGROUND:Multiple studies have confirmed that mitogen-activated protein kinase(MAPK)signaling pathway is involved in cell proliferation,and microRNA(miR)is involved in the occurrence and development of hypertrophic scars.Therefore,the role of miR-27a-3p and MAPK signaling pathways in pathological scar formation has been further explored. OBJECTIVE:To explore the effect of miR-27a-3p on the proliferation of human hypertrophic scar fibroblasts through the MAPK signaling pathway. METHODS:The primary fibroblasts were isolated and collected from the skin samples.The primary fibroblasts were observed by inverted microscope and verified by immunofluorescence.The relative expression level of miR-27a-3p in tissues was detected by qRT-PCR.The target genes of hsa-miR-27a-3p were predicted using the database,and then the predicted target genes were enriched by gene ontology function analysis and biological pathway enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes.There were seven groups:blank control,negative control,miR-27a-3p mimic,miR-27a-3p inhibitor,miR-27a-3p mimic+p38 MAPK inhibitor,miR-27a-3p mimic+extracellular regulated protein kinase inhibitor,miR-27a-3p mimic+c-Jun N-terminal kinase inhibitor.Western blot was used to detect the levels of extracellular regulated protein kinase,c-Jun N-terminal kinase inhibitor.and p38 kinase and their phosphorylation levels.Cell counting kit-8 and EdU were used to detect cell proliferation. RESULTS AND CONCLUSION:Compared with normal skin fibroblasts,hypertrophic scar fibroblasts had stronger proliferative activity(P<0.05)and faster proliferation level(P<0.001).Compared with normal skin,miR-27a-3p was highly expressed in hypertrophic scars(P<0.001).Compared with the negative control group,overexpression of miR-27a-3p could promote cell proliferation activity(P<0.001)and proliferation levels(P<0.001).Compared with the negative control group,knockdown of miR-27a-3p could inhibit the proliferation activity(P<0.05)and proliferation levels(P<0.001).Compared with the negative control group,overexpression of miR-27a-3p promoted the phosphorylated levels of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 mitogen-activated protein kinase(P<0.05).Compared with the negative control group,knockdown of miR-27a-3p inhibited the phosphorylated levels of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 MAPK(P<0.05).Compared with the miR-27a-3p mimic group,specific inhibitors of extracellular regulated protein kinase,c-Jun N-terminal kinase,and p38 MAPK reversed the effects of miR-27a-3p on the proliferative activity(P<0.01)and proliferation level(P<0.001)of fibroblasts.To conclude,these results suggest that miR-27a-3p promotes the proliferation of human hypertrophic scar fibroblasts by activating the MAPK signaling pathway.

Objective To analyze the PLCβ4 gene mRNA expression and its clinical significance in hepatocellular carcinoma (HCC) based on TCGA database. Methods Based on the data on 424 clinical samples (including 374 cases of HCC tissues and 50 cases of nontumor liver tissues) in the TCGA database, Kaplan–Meier method, Cox regression analysis, and immune infiltration analysis were performed to evaluate the relationship between PLCβ4 gene and the clinical characteristics and survival prognosis of HCC patients. Correlation analysis between PLCβ4 gene and 24 types of immune cells was applied to investigate the relationship between PLCβ4 gene and immune cell infiltration and mRNA expression level of TP53 gene, a high-frequency mutation gene in HCC. In addition, paraffin sections of highly, moderately, and poorly differentiated tumor tissues and normal liver tissues from HCC patients were collected. The histopathological observation was carried out via HE staining method, and the expression levels of PLCβ4 and Ki-67 proteins in each clinical sample were verified through the immunohistochemical method. Results The expression level of PLCβ4 gene in HCC was significantly higher than that in normal tissues (P<0.01), and all patients in the PLCβ4 high-expression group had a significantly longer overall survival than those in the low-expression group (P<0.05), which suggested that PLCβ4 substantially affected the prognosis of HCC patients. Correlation analysis showed that the expression level of PLCβ4 gene was highly correlated with immune cell infiltration and the expression level of TP53 gene. As verified by clinical sample experiments, HE staining experiments and immunohistochemical results revealed that PLCβ4 gene expression in HCC tissue samples was significantly higher than that in normal tissues (P<0.001), and it was negatively correlated with the degree of differentiation. Conclusion PLCβ4 may serve as an independent prognostic factor in HCC and is expected to be a novel molecular target for HCC treatment.

OBJECTIVE: To investigate the clinical efficacy and advantages of robot-assisted total knee arthroplasty (TKA) in patients with varus knee osteoarthritis. METHODS: Between October 2022 and June 2023, a total of 59 patients with severe knee osteoarthritis resulting in varus were treated with total knee arthroplasty, aged from 59 to 81 years with an average (70.90±4.63) years, including 19 mals and 40 females. The patients were divided into two groups based on the surgical method used:28 patients in the robot group and 31 patients in the traditional group. The robot group consisted of 8 males and 20 femalse patients, with an average age of (70.54±4.80) years and an average disease duration of (14.89±8.72) months. The traditional group consisted of 11 males and 20 females patients, with an average age of (71.39±4.5) years and an average disease duration of (12.32±6.73) months. The operative duration, amount of bleeding during the operation, postoperative activity time after the operation, hip-knee-ankle angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and complications were compared between the two groups before and after the operation. Lateral tibia component (LTC), frontal tibia component (FTC), frontal femoral component (FFC) and lateral femoral component (LFC) were measured 6 months after operation Additionally, the degree of knee joint motility, American Knee Society score (KSS), and visual analogue scale(VAS) were compared before and after the operation. RESULTS: All patients had gradeⅠwound healing without any complications, and all patients were followed up for 6 to 8 months, with an average of (6.5±1.5) months. There were no significant differences preoperative imaging evaluation indexes (including HKA, LDFA, and MPTA), preoperative knee mobility, preoperative VAS, and preoperative KSS between the two groups (P>0.05). Comparing the operation time (109.11±7.16) min vs. (83.90±7.85) min, length of the incision (16.60±2.33) cm vs. (14.47±1.41) cm, intraoperative bleeding (106.93±6.15) ml vs. (147.97±7.62) ml, postoperative activity time (17.86±1.84) h vs. (21.77±2.68) h, between the two groups showed statistically significant differences (P<0.05). There were significant differences in FFC (88.96±0.84)° vs. (87.93±1.09)° and LFC (88.57±1.10)° vs. (87.16±1.2)° between the two groups at 6 months after operation (P<0.05). The robotic group 1, 3, 6 months after KSS (75.96±3.96), (81.53±3.78), (84.50±3.29) scores, VAS (3.68±0.67), (2.43±0.79), (0.54±0.64), knee joint mobility (113.32±4.72) °, (123.93±3.99) °, (135.36±2.34) °;Traditional group KSS (73.77±4.18), (76.48±3.60), (80.19±3.28) scores, VAS (4.16±1.04), (3.03±0.75), (1.42±0.76) scores, knee joint mobility (109.19±6.95) °, (119.94±6.08) °, (134.48±2.14) °. Compared to before surgery, both groups showed significant improvement in KSS, VAS and knee mobility during the three follow-up visits (P<0.001). Additionally, postoperative HKA (180.39±1.95)° vs. (178.52±2.23)°, LDFA (89.67±0.63) ° vs. (89.63±0.63)°, and MPTA (89.44±0.55)° vs. (89.29±0.60)° were significantly improved in both groups compared to before surgery (P<0.001). The robotic group had higher KSS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). The robotic group also had lower VAS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). Furthermore, knee mobility was higher in the robotic group than those in the traditional group at 1 and 6 months after surgery (P<0.05), but there was no significant difference between the two groups at 6 months after surgery. CONCLUSION Robot-assisted total knee arthroplasty is a safe and effective method for total knee replacement. The use of robotics can improve the limb axis and prosthesis alignment for patients with preoperative varus deformity, resulting in better clinical and imaging outcomes compared to the conventional group.
Humans ; Female ; Male ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Robotic Surgical Procedures/methods*

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.

OBJECTIVE: To examine the effectiveness of Chinese medicine (CM) Lianhua Qingwen Granule (LHQW) and Jingyin Gubiao Prescription (JYGB) in asymptomatic or mild patients with Omicron infection in the shelter hospital. METHODS: This single-center retrospective cohort study was conducted in the largest shelter hospital in Shanghai, China, from April 10, 2022 to May 30, 2022. A total of 56,244 asymptomatic and mild Omicron cases were included and divided into 4 groups, i.e., non-administration group (23,702 cases), LHQW group (11,576 cases), JYGB group (12,112 cases), and dual combination of LHQW and JYGB group (8,854 cases). The length of stay (LOS) in the hospital was used to assess the effectiveness of LHQW and JYGB treatment on Omicron infection. RESULTS: Patients aged 41-60 years, with nadir threshold cycle (C_T) value of N gene <25, or those fully vaccinated preferred to receive CM therapy. Before or after propensity score matching (PSM), the multiple linear regression showed that LHQW and JYGB treatment were independent influence factors of LOS (both P<0.001). After PSM, there were significant differences in LOS between the LHQW/JYGB combination and the other groups (P<0.01). The results of factorial design ANOVA proved that the LHQW/JYGB combination therapy synergistically shortened LOS (P=0.032). CONCLUSIONS Patients with a nadir C_T value <25 were more likely to accept CM. The LHQW/JYGB combination therapy could shorten the LOS of Omicron-infected individuals in an isolated environment.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; China/epidemiology* ; Hospitalization ; COVID-19 Drug Treatment ; COVID-19/epidemiology* ; SARS-CoV-2 ; Retrospective Studies ; Treatment Outcome ; Length of Stay ; Young Adult ; Aged

Coronavirus-related diseases pose a significant challenge to the global health system. Given the diversity of coronaviruses and the unpredictable nature of disease outbreaks, the traditional "one bug, one drug" paradigm struggles to address the growing number of emerging crises. Therefore, there is an urgent need for therapeutic agents with broad-spectrum anti-coronavirus activity. Here, we provide evidence that ATV006, an anti-SARS-CoV-2 nucleoside analog targeting RNA-dependent RNA polymerase (RdRp), has broad antiviral activity against human and animal coronaviruses. Using mouse hepatitis virus (MHV) and human coronavirus NL63 (HCoV-NL63) as a model, we show that ATV006 has potent prophylactic and therapeutic activity against murine coronavirus infection in vivo. Remarkably, ATV006 successfully inhibits viral replication in mice even when administered 96 h after infection. Due to its oral bioavailability and potency against multiple coronaviruses, ATV006 has the potential to become a useful antiviral agent against SARS-CoV-2 and other circulating and emerging coronaviruses in humans and animals.

[This corrects the article DOI: 10.1016/j.apsb.2018.08.009.].

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome