Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*

Objective: To assess the impact of long-term antiretroviral therapy (ART) on human immunodeficiency virus (HIV) blood screening outcomes in post-exposure prophylaxis (PEP) failure cases through a longitudinal analysis of blood screening results over a 7-year period in a patient with HIV PEP failure. Methods: This study conducted 13 follow-up assessments for a high-risk individual who initiated ART shortly after exposure. The effectiveness of various blood screening methods, including immunological assays and nucleic acid testing (NAT), was analyzed. Blood samples were also tested with HIV RNA quantification testing, Western blot (WB) confirmation testing, chemiluminescence immunoassay (CLIA), and HIV rapid tests utilizing gold and selenium labels. A comprehensive analysis was performed to evaluate the changes in diagnostic capabilities of different testing methods for HIV biomarkers over an extended period following PEP failure. Results: The patient had two high-risk exposures: one day before ART initiation (BA1) and seven days preceding treatment (BA7). On the first day after the ART treatment (AA1), the HIV RNA concentration (viral load) was 9.07×10 copies/mL; by day five (AA5), the viral load decreased to 1.04×10 copies/mL. At day eleven (AA11), NAT and ELISA tests were both positive, with the WB result remaining indeterminate (gp160+). At day 48 (AA48), the S/CO value of the fourth generation ELISA reagent was 1.07, while results from a 6-sample pool and quantitative NAT were negative. However, a single sample NAT returned a positive result and WB tests indicated positivity for p17, p24, and gp160. At AA74, the quantitative NAT rebounded to 2.83×10 copies/mL, with positive NAT results for single and 6-sample pool NAT tests. The S/CO values of the imported and domestic ELISA reagents were 3.39 and 23.44, respectively. At AA201, 6-sample pool and quantitative NAT were negative again, while single sample NAT remained positive. From AA319 to AA2221, all NAT results have remained consistently below the minimum detection limit. At AA2221, S/CO values of the imported and domestic ELISA reagents were 3.47 and 23.44, respectively. Conclusion: The findings indicate that patients experiencing PEP failure after high-risk HIV exposure are at a higher risk of being missed by mixed-sample NAT pools and individual serological tests. Nonetheless, anti-HIV antibody levels are sustained at elevated values for an extended duration, underscoring antibody testing as an effective measure for blood screening.

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

This study was aimed at providing basic data for the control and prevention of Yersinia enterocolitica(Ye)infections.Ye isolates from stool samples collected from patients with diarrhea in a Beijing district between January 2019 and June 2024 were studied.Basic patient information and stool samples were collected,and quantitative polymerase chain reaction(qPCR)was applied to enriched cultures.Further analyses included virulence gene detection,whole-genome sequencing,and drug resistance detection.The detection rate of Ye was 0.76%(11/1 439),according to culture methods,thus yielding 12 Ye strains from distinct patients:11 isolated during the study period and 1 from 2017.The 12 Ye positive patients were 6-41 years of age,and their clinical presentations predominantly featured watery stools(66.67%,8/12)and loose stools(33.33%,4/12).The frequencies of nausea,vomiting,and fever were 41.67%(5/12),41.67%(5/12),and 8.33%(1/12),respectively.The drug resistance rates of Ye to TET,AMP,and NAL were 50.00%(6/12),33.33%(4/12),and 25.00%(3/12),respectively.One Ye strain exhibited multidrug resistance to ETP,MEM,TET,CIP,NAL,and AMP.According to qPCR detection of five common virulence genes,two Ye strains were identified as ystA+/ystB-type(ystA+/ystB-/ail+/yadA+/virF+),whereas ten strains were identified as ystA-/ystB+type(ystA-/ystB+/ail-/yadA-/virF-).VFDB database analysis based on genome sequences indicated that 12 Ye strains carried an average of 11 key virulence genes associated with adhesion,invasion,protease activity,and flagellar movement,and predicted 106 virulence genes and 12 virulence gene profiles.Only the two ystA+/ystB-Ye strains contained elements related to the TTSS and ABC transporter function.Detection of ystA-/ystB+Ye in stool isolation and culture of diarrhea cases might potentially have been missed in some cases,thus highlighting the importance of fluorescence PCR screening of fecal growth solutions to enhance isolation efficiency.Moreover,our findings revealed the genetic diversity of Ye isolated from diarrhea cases,thereby indicating the presence of multiple types of virulence genes within this pathogen.

Objective To investigate the effect of the use of glycopyrrolate before anesthesia on the perioperative circulation of patients undergoing laparoscopic cholecystectomy(LC).Methods 88 patients undergoing LC from March to June in 2024 were enrolled and randomly divided into two groups:the glycopyrrolate group(group G)and the control group(group C),with 44 patients in each.Three patients from group G and four from group C were excluded,leaving 41 patients in group G and 40 patients in group C.Ten minutes before anesthesia induction,group G received an intravenous dose of 4 μg/kg glycopyrrolate diluted to 5 mL with normal saline.The control group received an equal volume of normal saline.Both groups then received an intravenous infusion of dexmedetomidine at 1 μg/kg over 10 minutes.Heart rate(HR)and mean arterial pressure(MAP)were monitored immediately before infusion of glycopyrrolate/saline(T0),5 min after infusion(T1),10 min after infusion(T2),1 min after tracheal intubation(T3),immediately at skin incision(T4),2 min after pneumoperitoneum(T5),dissociating the cholecyst(T6),and 1 min after tracheal tube drawing(T7).Intraoperative amounts of propofol,rocuronium bromide,sufentanil,remifentanil,oral secretion score,PACU stay time,first postoperative flatus time and the occurrence of perioperative adverse reactions were observed.Results HR at T2,T3,T4,T5,and T6 time points was significantly higher in group G than in group C,while MAP at T1,T2,T3,T4,T5 time points was also significantly higher in group G(P<0.05).HR at T2 time points in Group G was significantly lower than that at T0,while T7 was significantly higher than that at T0 time points.In Group C,HR at T1,T2,T4,T5,and T6 time points was significantly lower than that at T0 time points,while T7 time points was significantly higher than that at T0 time points,with the differences being statistically significant(P<0.05).In Group G,MAP at T1 and T2 time pointswas significantly higher than that at T0,and MAP at T6 was significantly lower than that at T0 time points,and in Group C,MAP at T4,T5 and T6 time points was significantly lower than that at T0 time points,and the differences were all statistically significant(P<0.05);Oral secretion was lower in group G compared to group C,with a significant difference(P<0.05).The incidence of bradycardia was significantly lower in group G compared to group C(P<0.05).The incidence of oral dryness within 24 h postoperatively was higher in group G compared to group C(P<0.05).There were no significant differences of HR at T0,T1,and T7 time points,MAP at T0,T6,and T7 time points between the two groups(P>0.05);There were no significant differences of operation time,propofol usage,sufentanil usage,remifentanil usage,rocuronium bromide usage during operation,rate of atropine use,incidence of intraoperative hypotension,PACU stay time,first postoperative flatus,and nausea vomiting rate between the two groups(P>0.05);No delirium occurred in either group of patients 24 h after the operation.Conclusion Use of glycopyrrolate before anesthesia can be effectively applied to patients undergoing LC,is beneficial in reducing the incidence of bradycardia,maintaining the stability of intraoperative circulation,and has no significant effect on the incidence of postoperative delirium and nausea and vomiting.It is a worthy clinical application.

Objective To explore the pathogenic mechanisms of Legionella pneumophila(L.pneumophila)infection inhibiting the fusion of endosome-lysosome fusion in mouse macrophages.Methods Twelve C57 mice were randomly divided into control group and L.pneumophila infection group(n=6 each).After anesthesia,an equal volume of physiological saline or L.pneumophila solution was administered nasally.Body weight changes were monitored for 3 consecutive days,and the lungs were extracted to assess injury.Hematoxylin and eosin(HE)staining and immunohistochemical staining were performed to observe the pathological characteristics of lung tissue in both groups.Transcriptome sequencing was utilized to analyze differentially expressed genes(DEGs)and associated signaling pathways in lung tissues.Mouse bone marrow macrophages(BMDMs)were isolated and co-cultured with L.pneumophila,with infection status confirmed by immunofluorescence staining.Transcriptome sequencing was employed to analyze DEGs and enriched related signaling pathways before and after infection.Core genes involved in the post-infection signaling pathway were identified,and the consistency of their mRNA expression levels in vivo and in vitro was verified using RT-qPCR.The expression of relevant proteins was detected by Western Blotting,and bacterial proliferation assays were conducted to evaluate the intracellular replication of L.pneumophila.Results Compared with control group,the body weight of mice in L.pneumophila infection group significantly decreased(P<0.001)on the second and third day post-infection.Edema and red hepatoid degeneration were observed in both left and right lung tissues,with lesion areas spreading from the hilum to the lung periphery.HE staining revealed increased inflammatory cell infiltration in the alveolar spaces,thickening of alveolar septa and increased fibrin exudation in L.pneumophila infection group.Immunohistochemistry results showed a significant increase in myeloperoxidase(MPO)activity in the lung tissue infected mice(P<0.001).Transcriptome sequencing identified 2550 DEGs,with 1444 up-regulated genes and 1106 down-regulated genes.KEGG enrichment analysis indicated that these DEGs were mainly involved in pathways related to tumor necrosis factor,rheumatoid arthritis,Rap1,PI3K-Ak,and phagosome pathways.Immunofluorescence results showed in vitro proliferation of L.pneumophila within mouse BMDMs.Transcriptome sequencing identified 2550 DEGs,including 1677 up-regulated genes and 873 down-regulated genes.KEGG enrichment analysis showed that enrichment in pathway related to transcription dysregulation in cancer,PI3K-Akt and phagosome pathways.Thirteen core genes,including tubulin β1(Tubb1),were identified from the overlap between mouse lung tissue and BMDMs.RT-qPCR results demonstrated a significant decrease in Tubb1 expression in both lung tissue and BMDMs infected with L.pneumophila(P<0.001).Western Blotting results revealed significant decreases in Rab7,Tubb1,and LAMP2 protein expression(P<0.05),and increases in iNOS and MPO expression(P<0.05).Intracellular proliferation experiments indicated that L.pneumophila gradually increased within BMDMs over time.Conclusion The potential mechanism of L.pneumophila infection in mouse macrophages involves the down-regulation of Rab7/Tubb1/LAMP2 which inhibits the endosome-lysosome fusion.