A 51-year-old male presented with nasal obstruction, followed by progressive hearing loss and blurred vision. Imaging identified space-occupying lesions in the paranasal sinuses, orbits, and paraspinal regions, while laboratory tests confirmed positive anti-proteinase 3 anti-neutrophil cytoplasmic antibody(PR3- ANCA) immunoglobulin G (IgG)and markedly elevated serum IgG4. Despite treatment with corticosteroids, immunosuppressants, and radiotherapy, the patient exhibited steroid dependency with relentless disease progression. Following multidisciplinary consultation, a diagnosis of inflammatory myofibroblastic tumor (IMT) coexisting with ANCA- associated vasculitis (AAV) was favored, though IgG4-related disease remained a critical differential. Ultimately, profound immunosuppression precipitated a severe herpesvirus infection, leading to disseminated intravascular coagulation and multiple organ dysfunction syndrome. This case underscores the rarity and diagnostic complexity of concurrent IMT and AAV, highlights the therapeutic dilemma of balancing primary disease control against fatal opportunistic infections, and emphasizes the critical role of multidisciplinary collaboration in the diagnosis and treatment of complex diseases.

Narcotic plants are strictly regulated worldwide due to their ability to extract drug alkaloids and drug precursor components. Besides the three traditional core species, cannabis, opium poppy, and coca, the misuse of psychoactive plants with addictive properties has become increasingly prevalent globally in recent years, and the establishment of accurate identification methods for such plants has become an urgent need in the field of narcotics control. Within existing identification frameworks, the conventional morphological and chemical analysis methods, despite their long-term application, have demonstrated considerable limitations. In contrast, DNA-based molecular identification techniques have achieved significant advancement in recent years due to their high specificity and stability. This review comprehensively examines current DNA-based identification approaches for narcotic plants through three key dimensions: DNA molecular marker technology, DNA barcoding technology, and emerging molecular biological techniques, and elaborates on the principles, technical characteristics, application scenarios, and research progress of each technology, providing some reference for the scientific selection of DNA identification strategies for narcotic plants in different specific scenarios.

ObjectiveThis study aimed to investigate whether dexmedetomidine （Dex） alleviates stress-induced mammary tumor progression in mice by inhibiting the TLR4/NF‑κB signaling pathway， and to examine its effects on anxiety‑depression‑like behaviors and stress hormone levels. MethodsAn orthotopic EMT6 mammary tumor model was established in mice， and chronic mild stress （CMS） was applied to induce anxiety‑depression‑like states. The mice were divided into six groups： naive， tumor， CMS， CMS+tumor， CMS+tumor+Dex， and CMS+tumor+Vehicle groups. Behavioral changes were evaluated using the open field test and tail suspension test. Plasma stress hormone levels were measured by high‑performance liquid chromatography. Western blot and RT‑qPCR were performed to detect the expression of TLR4， p‑NF‑κB p65， p‑IκBα， and inflammatory cytokines （IL‑6， IL‑1β， TNF‑α） in tumor tissues. In vitro， EMT6 cells were treated with cortisol to mimic the stress-related microenvironment， and the effects of Dex on the TLR4/NF‑κB pathway were assessed by CCK‑8， Western blot， and RT-qPCR. ResultsTumor‑bearing mice exhibited significant anxiety‑depression‑like behaviors （P＜0.05）， along with markedly elevated plasma levels of norepinephrine， epinephrine， and cortisol （P＜0.05）. Chronic stress further aggravated these behavioral abnormalities and promoted tumor growth （P＜0.05）. Dexmedetomidine intervention significantly improved anxiety‑depression‑like behaviors （P＜0.05） and lowered peripheral stress hormone levels （P＜0.05） in stress‑exposed tumor‑bearing mice. In vitro experiments demonstrated that cortisol treatment activated the TLR4/NF‑κB pathway （P＜0.001） and upregulated the expression of inflammatory cytokines （P＜0.05 in EMT6 cells， whereas dexmedetomidine effectively suppressed this activation （P＜0.001）. In the in vivo model， dexmedetomidine treatment downregulated the expression of TLR4， p‑NF‑κB p65， p‑IκBα， and pro‑inflammatory cytokines in tumor tissues （P＜0.001） and significantly inhibited tumor growth （P＜0.05）. ConclusionDexmedetomidine inhibits the TLR4/NF‑κB signaling pathway， alleviates stress‑induced inflammatory responses， improves anxiety- and depression‑ like behaviors， reduces stress hormone levels， and suppresses mammary tumor progression. These findings provide an experimental basis for understanding anxiety- and depression- associated breast tumor progression and suggest that Dexmedetomidine and the TLR4/NF-κB pathway may serve as potential therapeutic targets.

Immunoglobulin G4-related disease (IgG4-RD) is a rare systemic immune-mediated disorder characterized by infiltration of IgG4-positive plasma cells and multiorgan fibrosis. Among them, cases with multiple pancreatic cystic lesions as the prominent manifestation are relatively rare, and they are easily misdiagnosed as pancreatic tumors or pancreatitis in clinical practice. Herein, we report one patient with IgG4-RD admitted to Peking Union Medical College Hospital. The patient initially presented with multiple pancreatic cystic lesions and aneurysmal dilatation of the abdominal aorta, accompanied by markedly elevated serum IgG4 levels. Combined with pathological findings from submandibular gland biopsy, the diagnosis of IgG4-RD was ultimately established. After treatment with a regimen of glucocorticoids combined with cyclophosphamide, the patient′s condition improved. Meanwhile, we performed a literature review of cases with IgG4-RD-related pancreatic cystic lesions, aiming to improve clinicians′ understanding of this rare disease phenotype.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective To explore the effects of different glucose concentrations on the synthesis and secretion of bone collagen in osteoblasts and the impact of diabetes on bone quality in mice.Methods(1)Primary osteoblasts were extracted from the skulls of neonatal mice via collagenase digestion and cultured in four groups under different glucose concentrations:normal glucose(5.5 mmol/L),moderate glucose(11.5 mmol/L),moderate-high glucose(16.5 mmol/L),and high glucose(25 mmol/L).EdU staining was performed to evaluate cell proliferation,while the Transwell assay was used to assess cell migration.Immunofluorescence and Western blotting were performed to detect and quantitatively analyze the content of type Ⅰ collagen(Col-1).Alizarin red S(ARS)staining and alkaline phosphatase(ALP)staining were applied to assess the effects of different glucose concentrations on osteogenic differentiation.(2)Six-week-old male C57BL/6 mice were randomly divided into control group and model group(5 in each group).The model group was fed a high-fat diet for 4 weeks followed by streptozotocin(STZ)injection to establish a diabetic mouse model.The osteogenic differentiation capacity of primary osteoblasts from both groups was assessed.(3)Micro-computed tomography(Micro-CT)was employed to analyze femoral bone mineral density(BMD),bone volume/tissue volume(BV/TV),trabecular number(Tb.N),and trabecular separation(Tb.Sp).Three-point bending test was conducted to evaluate mechanical parameters including maximum load,Young's modulus,fracture energy,and stiffness.RT-qPCR was employed to assess the expression of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox).Masson staining and Mallory staining were used to evaluate Col-1 content in trabecular bone.Results(1)EdU and Transwell assay results demonstrated that with the gradual increase in glucose concentration,the proliferation and migration abilities of osteoblasts were significantly decreased(P<0.001),and the protein expression levels of Col-1 and lysyl oxidase(LOX)were significantly reduced(P<0.01 or P<0.001).ARS and ALP staining revealed that calcium salt deposition and ALP activity in osteoblasts were significantly decreased with increasing glucose concentration(P<0.05 or P<0.001).(2)Compared with control group,mice in model group exhibited typical"three polies and one weight loss"symptoms(polyuria,polydipsia,polyphagia,and weight loss)of diabetes,and ARS and ALP staining showed a significant reduction in osteoblasts(P<0.001).(3)Micro-CT and three-point bending test results indicated that,compared with control group,mice in model group showed microarchitectural deterioration of bone,decreased Tb.N,increased Tb.Sp,and significantly reduced maximum load,Young's modulus,fracture energy,and stiffness(P<0.05).RT-qPCR results showed that the relative mRNA expression levels of osteogenic differentiation genes(Alp,Opn,Col1a1,and Lox)were significantly decreased in model group compared with control group(P<0.01 or P<0.001).Masson and Mallory staining indicated a significant reduction in collagen content in model group compared with control group(P<0.01).Conclusions High-glucose environment inhibits osteoblast proliferation,differentiation,and migration.Diabetic mice exhibit reduced bone quality and increased bone fragility,potentially mediated by decreased lysyl oxidase and collagen levels.