OBJECTIVE To analyze the distribution characteristics of mirtazapine steady-state trough concentration and concentration-to-dose ratio （ C / D ）， and to investigate the influence of clinical and genetic factors on C / D . METHODS A retrospective study was conducted on hospitalized patients with depression who received mirtazapine treatment and underwent therapeutic drug monitoring at the First Hospital of Hebei Medical University from May 2022 to May 2025. The collected data included patients’ gender， age， body mass index， daily dose， steady-state trough concentration， smoking status， history of liver disease， drug type， concomitant medications， and CYP2D6 metabolic phenotype. The C / D was calculated. Spearman rank correlation was used to analyze the relationship between mirtazapine steady-state trough concentration and daily dose. Univariate analysis and multiple linear regression model were employed to screen the factors potentially influencing the C / D of mirtazapine. RESULTS A total of 226 patients were included. The daily dose of mirtazapine was 25.00 （24.82， 30.00） mg/d， the steady-state trough concentration was 44.46 （20.00， 70.00） ng/mL， and the C / D was 1.83 （1.00， 2.00） （ng·d）/（mL·mg）. Steady-state trough concentrations were within the reference range （30-80 ng/mL） in 121 patients （53.54%）， below the lower limit in 80 patients （35.40%）， and above the upper limit in 25 patients （11.06%）. A positive correlation was observed between mirtazapine steady-state trough concentration and daily dose （coefficient of determination was 0.320 8， P ＜0.001）. Gender， smoking status， and CYP2D6 metabolic phenotype were significantly associated with the mirtazapine C / D （ P ＜0.05）. CONCLUSIONS Significant interindividual variability exists in mirtazapine steady-state trough concentrations. Gender， smoking status， and CYP2D6 metabolic phenotype are identified as independent influencing factors for the mirtazapine C / D ， with higher C / D ratios observed in females， non-smokers， and intermediate metabolizers.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To observe the morphology of the superficial,middle,and deep layers of the masseter muscle and related bony structures in the lateral facial region of adults through gross anatomy,and to probe into the effects of these muscle layers on the bony structures of the lateral facial region.Methods The bilateral masseter muscles of 12 adult cadavers were exposed,and the superficial,middle,and deep layers were separated and measured for muscle length,tendon length,and muscle belly length.After the masseter muscles were stripped,the total thickness was measured,and the mandible and zygomatic arch were exposed to measure the angle of the mandibular angle,thickness of the zygomatic arch,and width of the zygomatic arch.Observations were made of the masseter tuberosities,and statistical analysis was conducted on their interrelations.Results The zygomatic arch thickness was positively correlated with the length of superficial,middle and deep masseter muscles and the length of superficial and middle masseter belly(r superficial masseter length=0.624,r middle masseter length=0.787,r deep masseter length=0.423,r superficial masseter belly length=0.493,r middle masseter belly length=0.548).The width of the zygomatic arch was positively correlated with the lengths of the superficial and middle muscle layers and the middle muscle belly length(r superficial masseter length=0.527,r middle masseter length=0.521,r middle masseterbelly length=0.437).The angle of the mandibular angle was only negatively correlated with the middle muscle belly length(r=-0.422).The tuberosities of the superficial and middle masseter muscles were not affected by the corresponding muscle layers;However,the tuberosity of the deep masseter was negatively correlated with the length of the deep muscle and the length of the deep tendon(r deep masseter length=-0.543,r deep masseter tendon length=-0.443).Conclusion In the masseter muscle layers of Chinese individuals,the superficial and middle layers have the most significant impact on the bony structures structures of the lateral facial region.These findings are of guiding significance for the remodeling of structures in the lateral facial region.

Objective:To compare the diagnostic, staging, and prognostic performance of three AKI criteria (KDIGO, cROCK, and APKD) in patients with pre-existing kidney dysfunction (PKD).Methods:Clinical data from 570 PKD patients admitted to the ICU of the First Affiliated Hospital of Wenzhou Medical University (October 2020-October 2022) were analyzed. Patients were classified by three AKI diagnostic criteria. We compared AKI detection rates and mortality predictions using ROC analysis and logistic regression (reporting ORs with 95% CIs). Results:AKI detection rates differed significantly: APKD 80.7% (460/570), KDIGO 66.0% (376/570), and cROCK 47.0% (268/570) (both P<0.001 vs. APKD). Mortality rates were comparable across criteria (APKD 32.4%, KDIGO 33.0%, cROCK 33.6%; P>0.85). APKD showed superior predictive value for in-hospital mortality (AUC=0.736, 95% CI 0.691-0.781), with significantly higher sensitivity than KDIGO (0.738 vs. 0.663, P<0.001) and cROCK (0.738 vs. 0.613, P<0.001). KDIGO staging identified few AKI2 cases (1.1%), with mortality rates of 27.3% (AKI1), 0% (AKI2), and 37.0% (AKI3). APKD staging demonstrated graded mortality risks: 20.1% (AKI1), 28.1% (AKI2), and 40.9% (AKI3) (all P<0.05). Multivariate analysis revealed increasing mortality risk with APKD stage (AKI1: OR=2.34, 95% CI 1.09-5.31; AKI2: OR=4.50, 95% CI 2.05-10.46; AKI3: OR=7.03, 95% CI 3.59-15.01). APKD staging outperformed KDIGO in mortality prediction (AUC=0.756 vs. 0.724, P=0.02). Conclusions:The APKD criteria demonstrate superior AKI detection in PKD patients and better prognostic prediction compared to KDIGO and cROCK. APKD staging provides more clinically meaningful risk stratification than KDIGO for this population.

To investigate the association between obesity-related metabolic indices and the risk of knee osteoarthritis(KOA) in middle-aged and older Chinese adults(≥45 years) using data from the China Health and Retirement Longitudinal Study(CHARLS).

Aromatic traditional Chinese medicine(TCM) has played an important role against epidemics and viruses, and volatile components are the main components that exert the pharmacological effects of aromatic TCM. By screening the related monomer components in aromatic TCM against epidemic and viruses and analyzing and endowing TCM with medicinal properties based on its clinical application and pharmacological research according to the theoretical thinking of TCM, the key technical issues of compatibility of TCM monomer components were solved from a theoretical perspective, providing new ideas and methods for screening raw materials and formulas for the development of new TCM drugs. Based on the conditions of antiviral activity, clinical application foundation, definite therapeutic effect, and high safety, a gradient screening of aromatic TCM was carried out. Firstly, 30 aromatic TCM were screened from anti-epidemic literature and clinical trial formulas, and seven volatile monomers were further screened from them. Then, four monomer components with significant effects, namely patchouli alcohol, carvacrol, p-cymene, and eucalyptol were screened. By adopting the "four-step method for a systematic study of TCM properties", the four monomer components were endowed with medicinal properties, and compatibility and combination studies were conducted to explore the theoretical basis of monomer formulas and form monomer formulas guided by TCM theory. The screening results of volatile monomers in aromatic TCM against viral pneumonia included patchouli alcohol, carvacrol, p-cymene, and eucalyptol. The medicinal properties and compatibility theory of volatile monomer components in TCM were explored. Patchouli alcohol was the main herb, with a cool and pungent nature. It entered the lung meridian to dispel evil Qi and has the effects of aromatization, detoxification, and epidemic prevention. Carvacrol was a minister drug with a cool and pungent taste. It had the effects of aromatizing, moistening, and dissolving the exterior, as well as strengthening the spleen and stomach. p-Cymene was an adjunctive medicine with a mild and pungent nature. It entered the lungs and kidneys and had the effects of aromatic purification, cough relief, and asthma relief. Eucalyptol was also an adjunctive medicine with a pungent and warm taste. It had the functions of aromatic purification, cough relief, phlegm reduction, and pain relief. The combination of the four medicines had the effects of aromatizing, moistening, detoxifying, and epidemic prevention, as well as relieving cough and asthma and strengthening the spleen and stomach. They were used to treat viral pneumonia caused by upper respiratory tract viral infections, with symptoms such as chest tightness, cough, wheezing, fatigue, nasal congestion, runny nose, nausea, and vomiting. This study has laid a literature and theoretical foundation for further drug efficacy verification experiments, compatibility efficacy experiments, and subsequent product development and clinical applications, and it serves as an innovative practice that combines literature research, theoretical research, experimental research, and clinical practice to develop new products.
Drugs, Chinese Herbal/therapeutic use* ; Antiviral Agents/pharmacology* ; Humans ; Pneumonia, Viral/virology* ; Medicine, Chinese Traditional ; Volatile Organic Compounds/pharmacology* ; Animals