Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Intervertebral disc degeneration(IDD)is a prevalent clinical degenerative disease that currently can only be treated through conservative and surgical treatments,which only alleviate symptoms and are not significantly effective.In recent years,nanoparticles have been widely studied in the biomedical field due to their biodegradability,biocompatibility,extended body circulation,sustained and controlled release,and precise drug targeting.Nanoparticle drug delivery systems have the potential to deliver a range of therapeutic agents including proteins,drugs,genes,and cells,thereby promoting tissue and cell repair and regeneration,which offers hope for IDD treatment.However,there are still challenges in translating experimental data into practical therapies applicable to humans.This review summarizes recent research progress on drug delivery systems for IDD treatment based on nanoparticles and provides insights and prospects for the challenges faced by nanoparticles,aiming to provide a reference for the clinical translation of nanoparticle-based treatment for IDD.

Cardiovascular diseases are the leading cause of mortality, posing a significant threat to human health due to the high incidence rate. Atherosclerosis, a chronic inflammatory disease, serves as the primary pathological basis for most such conditions. The incidence of atherosclerosis continues to rise, but its pathogenesis has not been fully elucidated. As an important member of the small GTPase superfamily, Ras-association proximate 1 (Rap1) is an important molecular switch involved in the regulation of multiple physiological functions including cell differentiation, proliferation, and adhesion. Rap1 achieves the utility of the molecular switch by cycling between Rap1-GTP and Rap1-GDP. Rap1 may influence the occurrence and development of atherosclerosis in a cell-specific manner. This article summarizes the potential role and mechanism of Rap1 in the progression of atherosclerosis in different cells, aiming to provide new therapeutic targets and strategies for clinical intervention.
Humans ; Atherosclerosis/metabolism* ; rap1 GTP-Binding Proteins/physiology* ; Animals ; Cell Differentiation ; Cell Adhesion ; Cell Proliferation

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional

OBJECTIVE: A new three-dimensional(3D) classification of posterior cruciate ligament (PCL) tibial avulsion fracture based on computed tomography(CT) features was established and the significance in clinical treatment was explored in this study. METHODS: From May 2013 to November 2023, 43 cases of PCL tibial avulsion fracture in the Second Hospital of Jilin University were analyzed retrospectively, including 29 males and 14 females, aged (34.3±8.5) years. According to traditional Meyers and McKeever classification, 3 cases were typeⅠ;2 cases of typeⅡ;38 cases were type Ⅲ. Based on the characteristics of CT images, 43 patients were given specific treatment strategies and followed up to evaluate the curative effect. According to the degree of fracture displacement, involved range and the integrity of fracture block demonstrated by CT images, the new three-dimensional classification of PCL avulsion fracture was established. Kappa coefficient was used for consistency test. RESULTS: A new 3D classification of PCL tibial avulsion fracture was established. TypeⅠwas the non-displaced fracture (displacement degree ≤3 mm), in which typeⅠa was the avulsion range limited in the posterior intercondylar fossa, and Ib was the avulsion range beyond the posterior intercondylar fossa. TypeⅡrepresented the displaced fracture in the posterior intercondylar fossa (avulsion limited to the posterior intercondylar fossa and fracture displacement>3 mm), in which typeⅡa represented a slight displacement with a intact broken block and the posterior elevation of the avulsion (hinge mechanism), typeⅡb represented the complete separation of fracture ends with a intact fracture block, and typeⅡc was the comminuted fracture. Type Ⅲ was the displaced fracture beyond the posterior intercondylar fossa (avulsion involving the articular surface of the tibial plateau or the intercondylar ridge and the degree of displacement > 3 mm), among which type Ⅲa was the simple fracture with intact broken block, type Ⅲb represented the comminuted fracture, and type Ⅲc was the complex fracture with tibial plateau fracture. According to this new 3D classification, 43 patients were classified as type Ia in 2 cases and typeⅠb in 1 case;typeⅡa in 2 cases, typeⅡb in 15 cases and typeⅡc in 7 cases;type Ⅲa in 2 cases, type Ⅲb in 5 cases and type Ⅲc in 9 cases. All the 43 cases in this study achieved bone union. At the last follow-up, according to the hospital for special surgery knee score(HSS)evaluation system for the knee joint function, 27 cases were excellent, 11 cases were good, 5 cases were fair. The average Kappa value of inter-observer reliability in the first stage was 0.793, and the second stage was 0.855. The average Kappa value of the whole stage was 0.839, indicating high level of consistency. The average Kappa value of intra-observer reliability was 0.893, indicating high level of consistency. CONCLUSION The 3D classification of PCL tibial avulsion fracture is intuitive, demonstrating a high level of reliability. It has a certain guiding significance for the selection of clinical treatment methods, and it is suggested to be promoted and applied as a new classification system in clinical practice.
Humans ; Male ; Female ; Posterior Cruciate Ligament/surgery* ; Adult ; Tibial Fractures/classification* ; Tomography, X-Ray Computed ; Middle Aged ; Retrospective Studies ; Fractures, Avulsion/classification* ; Imaging, Three-Dimensional ; Young Adult

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

A deep learning-based method for recognizing the minutiae in fingerprint,as well as a Python programming-based evaluation system for quantifying the evidence value of fingerprint was proposed.Firstly,latent fingerprints,which were developed using a series of fluorescent nanomaterials synthesized by chemical methods,were used as unknown fingerprint(UKFP),while ink impressed fingerprints were used as known fingerprint(KFP).Then,the bifurcations and terminations in minutiae were recognized using the improved YOLOv8 deep learning model.After that,the similarity index(Sim.)of UKFP vs KFP were calculated by analyzing the angle similarity factor(α)and the curve similarity factor(β)between UKFP and KFP,meanwhile,the sensitivity index(Sen.)were calculated by analyzing the fineness factor(γ)between UKFP and KFP.The evidence value(EV)of fingerprint was thus obtained by the combination of Sim.and Sen..The calculation formulas for above evaluation factors(i.e.α,β and γ),evaluation indexes(i.e.Sim.and Sen.),and EV were also put forward.Finally,the evaluation system for quantifying the evidence value of fingerprint was established,the feasibility and reliability of this system were verified,and the external factors that impacted on Sim.,Sen.,and EV were investigated in detail.The Python-based evaluation system for quantifying the evidence value of fingerprint could achieve the goals objectively,comprehensively,accurately and efficiently,exhibiting easy operability,high efficiency,responsiveness and reliability.This research was expected to provide beneficial references for quantitatively evaluating and thoroughly developing the evidence value.

The influence of material properties on fingerprint development effects were systematically studied.Firstly,carbon dots/NaYF4 and Cu nanoclusters/starch nanocomposites respectively possessing different fluorescent intensities and dual fluorescent colors,as well as NaYF4 micro-/nano-materials exhibiting different morphologies,sizes,and surface properties were chemically synthesized and further used for latent fingerprint development.Then,the developing effects were comprehensively evaluated by visual analysis combining with spectral characterization and Python-based calculation.Finally,the influences of material properties on latent fingerprint development were quantitatively evaluated from three dimensions including contrast,sensitivity,and selectivity.The fluorescence properties of developing materials and substrates could significantly affect the developing contrast,namely,the stronger the developing signal,the higher the contrast;the weaker the background noise,the higher the contrast.The sizes and morphologies of the developing materials could respectively influence the quantity and quality of developed minutiae,and significantly affect the developing sensitivity,namely,the smaller the particle size of developing materials,the more the quantity of developed minutiae and the higher the sensitivity;the smaller the surface area of developing materials,the higher the quality of developed minutiae and the higher the sensitivity.The surface properties together with the sizes and morphologies of developing materials could influence their adsorption performances,and significantly affect the developing selectivity,namely,the stronger the specific adsorption of developing materials with fingerprint substance,and the weaker the non-specific adsorption of developing materials with substrate,the higher the selectivity.Moreover,the fingerprint development using the materials with suitable surface area and appropriate mass would have a high selectivity.

The anti-counterfeiting application of three-color fluorescent carbon dots(CDs)in high-quality inkjet printing was studied.Blue,green and red fluorescent CDs were synthesized by solvothermal method using three kinds of isomers of phenylenediamine as precursor,and ethanol-glycerol mixture as solvent.The morphology,composition,structure,and optical properties were characterized.Blue,green and red fluorescent inks were then prepared by diluting CDs with water.The dilution ratio,excitation light source and filtering method were also optimized.The optimal dilution ratio of blue,green and red fluorescent ink was 5,5 and 20,respectively.Under 365,415 and 450 nm light excitation,bright blue,green and red fluorescence from above inks could be observed by using a blue,green and red filter,respectively.These fluorescent inks were finally used for high-quality inkjet printing through monochrome printing mode and polychrome printing mode.In addition,the sensitivity and contrast of printing were quantitatively investigated.The series of three-color fluorescent inks possessed great prospects in ordinary and invisible fluorescent anti-counterfeiting application.