Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE: To explore the effect of bear bile powder (BBP) on acute lung injury (ALI) and the underlying mechanism. METHODS: The chemical constituents of BBP were analyzed by ultra-high-pressure liquid chromatography-mass spectrometry (UPLC-MS). After 7 days of adaptive feeding, 50 mice were randomly divided into 5 groups by a random number table (n=10): normal control (NC), lipopolysaccharide (LPS), dexamethasone (Dex), low-, and high-dose BBP groups. The dosing cycle was 9 days. On the 12th and 14th days, 20 µL of Staphylococcus aureus solution (bacterial concentration of 1 × 10^-7 CFU/mL) was given by nasal drip after 1 h of intragastric administration, and the mice in the NC group was given the same dose of phosphated buffered saline (PBS) solution. On the 16th day, after 1 h intragastric administration, 100 µL of LPS solution (1 mg/mL) was given by tracheal intubation, and the same dose of PBS solution was given to the NC group. Lung tissue was obtained to measure the myeloperoxidase (MPO) activity, the lung wet/dry weight ratio and expressions of CD14 and other related proteins. The lower lobe of the right lung was obtained for pathological examination. The concentrations of inflammatory cytokines including interleukin (IL)-6, tumour necrosis factor α (TNF-α ) and IL-1β in the bronchoalveolar lavage fluid (BALF) were detected by enzyme linked immunosorbent assay, and the number of neutrophils was counted. The colonic contents of the mice were analyzed by 16 sRNA technique and the contents of short-chain fatty acids (SCFAs) were measured by gas chromatograph-mass spectrometer (GC-MS). RESULTS: UPLC-MS revealed that the chemical components of BBP samples were mainly tauroursodeoxycholic acid and taurochenodeoxycholic acid sodium salt. BBP reduced the activity of MPO, concentrations of inflammatory cytokines, and inhibited the expression of CD14 protein, thus suppressing the activation of NF-κB pathway (P<0.05). The lung histopathological results indicated that BBP significantly reduced the degree of neutrophil infiltration, cell shedding, necrosis, and alveolar cavity depression. Moreover, BBP effectively regulated the composition of the intestinal microflora and increased the production of SCFAs, which contributed to its treatment effect (P<0.05). CONCLUSIONS BBP alleviates lung injury in ALI mouse through inhibiting activation of NF-κB pathway and decreasing expression of CD14 protein. BBP may promote recovery of ALI by improving the structure of intestinal flora and enhancing metabolic function of intestinal flora.
Animals ; Acute Lung Injury/pathology* ; Lipopolysaccharides ; Ursidae ; Gastrointestinal Microbiome/drug effects* ; Bile/chemistry* ; Lipopolysaccharide Receptors/metabolism* ; Powders ; Male ; Lung/drug effects* ; Mice ; Peroxidase/metabolism* ; Signal Transduction/drug effects* ; Cytokines/metabolism*

Triple-negative breast cancer (TNBC) is a highly aggressive malignancy predominantly managed via chemotherapy. Our clinical sample analysis revealed a significant correlation between elevated CD24 expression in TNBC tumor cells and patient survival rates. We developed a novel antibody-drug conjugate (ADC), named HN03, consisting of an antibody with engineered cysteines for site-specific conjugation with a low toxic nitric oxide (NO) precursor as its payload through a novel Pt(IV)-mediated bioorthogonal self-cleavable linker. HN03 specifically targets tumor cells expressing high levels of CD24, concurrently generating cisplatin and releasing NO upon activation. HN03 also exhibited potent in vitro and in vivo antitumor activity. It significantly reduced tumor growth at various doses, prevented tumor metastasis, with markedly lower toxicity than traditional chemotherapy agents. We found that a key mechanism of its action involved inducing apoptosis and endoplasmic reticulum stress, substantially decreasing the number of M2-type macrophages. Overall, HN03 stands out as a promising therapeutic option for TNBC, offering a targeted treatment with reduced side effects and the potential for improved outcomes. Furthermore, using Pt(IV) in the linker and an NO precursor as the payload enhances the versatility of the Antibody-NO donor Conjugate (ANC), offering new avenues for the design of the next generation of ADCs.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

OBJECTIVE: Glucocorticoid-induced osteoporosis (GIOP) is a common complication of prolonged glucocorticoid therapy. Chlorogenic acid (CGA), a polyphenol with antioxidant properties that is extracted from traditional Chinese medicines such as Eucommiae Cortex, has potential anti-osteoporotic activity. This study aimed to investigate the possible effects of CGA on GIOP in mice and murine long bone osteocyte Y4 (MLO-Y4) cells and explore the underlying molecular mechanisms. METHODS: The protective effects of CGA were initially evaluated in the GIOP mouse model induced by dexamethasone (Dex). The micro-computed tomography, hematoxylin-eosin staining, silver nitrate staining, and serum detection were used to assess the efficacy of CGA for improving bone formation in vivo. Then, network pharmacology analysis was used to predict the potential targets and molecular mechanisms underlying the therapeutic efficacy of CGA against GIOP. After that, 2',7'-dichlorofluorescein diacetate staining, flow cytometry, real-time quantitative reverse transcription polymerase chain reaction, and Western blotting were used to verify the mechanisms of CGA against GIOP in vitro. RESULTS: Animal experiments showed that CGA treatment effectively attenuated Dex-induced decreases in bone mass and strength and improved disrupted osteocyte morphology in mice. The protein-protein interaction analysis highlighted erb-b2 receptor tyrosine kinase (ERBB2), which is also known as human epidermal growth factor receptor 2 (HER2), caspase-3, kinase insert domain receptor, matrix metallopeptidase 9, matrix metallopeptidase 2, proto-oncogene tyrosine-protein kinase Src, and epidermal growth factor receptor as core targets. The Kyoto Encyclopedia of Genes and Genomes analysis revealed several significantly enriched pathways (P < 0.05), including the ERBB, phosphoinositide 3 kinase-AKT serine/threonine kinase 1 (AKT), and mechanistic target of rapamycin kinase (mTOR) pathways. Cellular experiments verified that CGA enhanced bone formation and promoted autophagy while inhibiting apoptosis in MLO-Y4 cells exposed to Dex, which was associated with the upregulated expression of HER2 and activation of the HER2/AKT/mTOR signaling pathway. CONCLUSION CGA exerted anti-osteoporotic effects against GIOP, partially through targeting osteocytes and modulating the HER2/AKT/mTOR signaling pathway. Please cite this article as: Xie AN, Zhang SZY, Zhang Y, Cao JL, Wang CL, Wang LB, Wu HJ, Zhang J, Dai WW. Chlorogenic acid mitigates glucocorticoid-induced osteoporosis via modulation of HER2/AKT/mTOR signaling pathway. J Integr Med. 2025; 23(6):670-682.
Animals ; Chlorogenic Acid/therapeutic use* ; Osteoporosis/metabolism* ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Mice ; Glucocorticoids/adverse effects* ; Receptor, ErbB-2/metabolism* ; Proto-Oncogene Mas ; Dexamethasone/adverse effects* ; Osteocytes/drug effects* ; Osteogenesis/drug effects* ; Male ; Cell Line ; Mice, Inbred C57BL ; Humans