ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveBased on the concept of quality by design（QbD）， the processing process of calcined Pyritum was optimized， and its X-ray diffraction（XRD） fingerprint was established. MethodsThe safety， effectiveness and quality controllability of calcined Pyritum were taken as the quality profile（QTPP）， the color， hardness， metallic luster， phase composition， the contents of heavy metals and hazardous elements were taken as the critical quality attributes（CQAs）， and the calcination temperature， calcination time， paving thickness and particle size were determined as the critical process parameters（CPPs）. Differential thermal analysis， X-ray diffraction（XRD） and inductively coupled plasma mass spectrometry（ICP-MS） were used to analyze the correlation between the calcination temperature and CQAs of calcined Pyritum. Then， based on the criteria importance through intercriteria correlation（CRITIC）-entropy weight method， the optimal processing process of calcined Pyritum was optimized by orthogonal test. Powder XRD was used to analyze the phase of calcined Pyritum samples processed according to the best process， and the mean and median maps of calcined Pyritum were established by the superposition of geometric topological figures， and similarity evaluation and cluster analysis were carried out. ResultsThe results of single factor experiments showed that the physical phase of Pyritum changed from FeS₂ to Fe₇S₈ during the process of temperature increase， the color gradually deepened from dark yellow， and the contents of heavy metals and harmful elements decreased. The optimized processing process of calcined Pyritum was as follows：calcination temperature at 750 ℃， calcination time of 2.5 h， paving thickness of 3 cm， particle size of 0.8-1.2 cm， vinegar quenching 1 time［Pyritum-vinegar（10∶3）］. After calcination， the internal structure of Pyritum was honeycomb-shaped， which was conducive to the dissolution of active ingredients. XRD fingerprints of 13 batches of calcined Pyritum characterized by 10 common peaks were established. The similarities of the relative peak intensities of the XRD fingerprints of the analyzed samples were>0.96， and it could effectively distinguish the raw products and unqualified products. ConclusionTemperature is the main factor affecting the quality of calcined Pyritum. After processing， the dissolution of the effective components in Pyritum increases， and the contents of heavy metals and harmful substances decrease， reflecting the function of processing to increase efficiency and reduce toxicity. The optimized processing process is stable and feasible， and the established XRD fingerprint can be used as one of the quality control standards of calcined Pyritum.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveBased on the concept of quality by design（QbD）， the processing process of calcined Pyritum was optimized， and its X-ray diffraction（XRD） fingerprint was established. MethodsThe safety， effectiveness and quality controllability of calcined Pyritum were taken as the quality profile（QTPP）， the color， hardness， metallic luster， phase composition， the contents of heavy metals and hazardous elements were taken as the critical quality attributes（CQAs）， and the calcination temperature， calcination time， paving thickness and particle size were determined as the critical process parameters（CPPs）. Differential thermal analysis， X-ray diffraction（XRD） and inductively coupled plasma mass spectrometry（ICP-MS） were used to analyze the correlation between the calcination temperature and CQAs of calcined Pyritum. Then， based on the criteria importance through intercriteria correlation（CRITIC）-entropy weight method， the optimal processing process of calcined Pyritum was optimized by orthogonal test. Powder XRD was used to analyze the phase of calcined Pyritum samples processed according to the best process， and the mean and median maps of calcined Pyritum were established by the superposition of geometric topological figures， and similarity evaluation and cluster analysis were carried out. ResultsThe results of single factor experiments showed that the physical phase of Pyritum changed from FeS₂ to Fe₇S₈ during the process of temperature increase， the color gradually deepened from dark yellow， and the contents of heavy metals and harmful elements decreased. The optimized processing process of calcined Pyritum was as follows：calcination temperature at 750 ℃， calcination time of 2.5 h， paving thickness of 3 cm， particle size of 0.8-1.2 cm， vinegar quenching 1 time［Pyritum-vinegar（10∶3）］. After calcination， the internal structure of Pyritum was honeycomb-shaped， which was conducive to the dissolution of active ingredients. XRD fingerprints of 13 batches of calcined Pyritum characterized by 10 common peaks were established. The similarities of the relative peak intensities of the XRD fingerprints of the analyzed samples were>0.96， and it could effectively distinguish the raw products and unqualified products. ConclusionTemperature is the main factor affecting the quality of calcined Pyritum. After processing， the dissolution of the effective components in Pyritum increases， and the contents of heavy metals and harmful substances decrease， reflecting the function of processing to increase efficiency and reduce toxicity. The optimized processing process is stable and feasible， and the established XRD fingerprint can be used as one of the quality control standards of calcined Pyritum.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Metabolic dysfunction-associated steatotic liver disease (MASLD), the most prevalent chronic liver condition globally, lacks adequate and effective therapeutic remedies in clinical practice. Recent studies have increasingly highlighted the close connection between the ubiquitin-proteasome system (UPS) and the progression of MASLD. This relationship is crucial for understanding the disease's underlying mechanism. As a sophisticated process, the UPS govern protein stability and function, maintaining protein homeostasis, thus influencing a multitude of elements and biological events of eukaryotic cells. It comprises four enzyme families, namely, ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), ubiquitin-protein ligases (E3), and deubiquitinating enzymes (DUBs). This review aims to delve into the array of pathways and therapeutic targets implicated in the ubiquitination within the pathogenesis of MASLD. Therefore, this review unveils the role of ubiquitination in MASLD while spotlighting potential therapeutic targets within the context of this disease.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.