ObjectiveTo explore the function and related molecular mechanisms of magnoflorine against colon cancer via network pharmacology， molecular docking， and in vitro cell experiments. MethodsIn this study， the canonical SMILES of magnoflorine was obtained from the PubChem database， and the potential targets of magnoflorine were predicted by the Swiss Target Prediction database， while the disease targets of colon cancer were obtained from the DisGeNET， GeneCards and OMIM databases. The intersecting targets between magnoflorine's predicted targets and colon cancer disease targets were taken， and a protein-protein interaction （PPI） network was constructed and analyzed. The DAVID online database was employed to conduct Gene Ontology （GO） and KEGG pathway enrichment analyses on core targets. The top five key targets screened were docked with magnoflorine using AutoDock software. Finally， cellular experiments including CCK-8 assays， EdU experiments， cell scratch assays， and Transwell assays were conducted to validate the results from network pharmacology and molecular docking. Results44 key targets of magnoflorine in resisting colon cancer were acquired. The molecular docking results showed that magnoflorine had a strong binding activity with the core target signal transducer and activator of transcription 3 （STAT3） in the top five of the PPI network. Cellular experiments confirmed that magnoflorine could inhibit the proliferation and migration of colon cancer cells by suppressing the JAK/STAT3 signaling pathway. ConclusionMagnoflorine may inhibit the proliferation and migration of colon cancer cells by regulating the JAK/STAT3 signaling pathway.

Objective: For patients with elevated hematocrit (Hct), platelet-rich plasma (PRP) apheresis is prone to red blood cell contamination—commonly referred to as “flushing” or erythrocyte carryover—which compromises product quality and therapeutic efficacy. This study reports two clinicaly derived measures to mitigate this issue. Methods: For 21 patients with Hct ≥53%, intravenous 0.9% sodium chloride infusion before apheresis process (replacement method, n=13) or 0.9% sodium chloride fluids hemodilution within the centrifuge bowl during PRP apheresis process (dilution method, n=8) were given, respectively. The collection time, adverse reactions, and the celluar composition of PRP—including white blood cells, red blood cells, and platelet counts—were recorded and compared. Results: Neither method resulted in visible RBC contamination (“flushing”). The red blood cell counts [(0.021±0.014)×10 /L vs (0.019±0.011)×10 /L, P>0.05], white blood cell counts [(2.258±3.288) ×10 /L vs (0.557 5±1.203) ×10 /L, P>0.05], and platelet counts [(1 140±308.2)×10 /L vs (1 105±309.9)×10 /L, P>0.05] in the PRP products obtained by two methods all met the control standards of PRP. There was no significant difference [(2.268±0.927) vs (2.438±0.762) mL/min, P=0.669 2] between the two methods in terms of the speed of PRP collection. One case of adverse reaction occurred with the fluid replacement method, while no adverse reaction occurred with the dilution method. Conclusion: For patients with elevated Hct, both fluid replacement and dilution methods can effectively prevent RBC contamination during PRP collection, yielding products that meet clinical quality standards.

BACKGROUND: G protein-coupled receptor kinase 2 (GRK2) could participate in the regulation of diverse cells via interacting with non-G-protein-coupled receptors. In the present work, we explored how paroxetine, a GRK2 inhibitor, modulates the differentiation and activation of immune cells in rheumatoid arthritis (RA). METHODS: The blood samples of healthy individuals and RA patients were collected between July 2021 and March 2022 from the First Affiliated Hospital of Anhui Medical University. C57BL/6 mice were used to induce the collagen-induced arthritis (CIA) model. Flow cytometry analysis was used to characterize the differentiation and function of dendritic cells (DCs)/T cells. Co-immunoprecipitation was used to explore the specific molecular mechanism. RESULTS: In patients with RA, high expression of GRK2 in peripheral blood lymphocytes, accompanied by the increases of phosphatidylinositol 3 kinase (PI3K), protein kinase B (AKT), and mammalian target of rapamycin (mTOR). In animal model, a decrease in regulatory T cells (T regs ), an increase in the cluster of differentiation 8 positive (CD8 + ) T cells, and maturation of DCs were observed. Paroxetine, when used in vitro and in CIA mice, restrained the maturation of DCs and the differentiation of CD8 + T cells, and induced the proportion of T regs . Paroxetine inhibited the secretion of pro-inflammatory cytokines, the expression of C-C motif chemokine receptor 7 in DCs and T cells. Simultaneously, paroxetine upregulated the expression of programmed death ligand 1, and anti-inflammatory cytokines. Additionally, paroxetine inhibited the PI3K-AKT-mTOR metabolic pathway in both DCs and T cells. This was associated with a reduction in mitochondrial membrane potential and changes in the utilization of glucose and lipids, particularly in DCs. Paroxetine reversed PI3K-AKT pathway activation induced by 740 Y-P (a PI3K agonist) through inhibiting the interaction between GRK2 and PI3K in DCs and T cells. CONCLUSION Paroxetine exerts an immunosuppressive effect by targeting GRK2, which subsequently inhibits the metabolism-related PI3K-AKT-mTOR pathway of DCs and T cells in RA.
G-Protein-Coupled Receptor Kinase 2/metabolism* ; Arthritis, Rheumatoid/immunology* ; Animals ; Dendritic Cells/metabolism* ; Paroxetine/therapeutic use* ; Proto-Oncogene Proteins c-akt/metabolism* ; Mice ; Humans ; Mice, Inbred C57BL ; Signal Transduction/drug effects* ; Male ; Phosphatidylinositol 3-Kinases/metabolism* ; Lymphocyte Activation/drug effects* ; Female ; T-Lymphocytes/metabolism* ; Middle Aged

Objective To construct a classification model for surgical patients and apply it in the allocation of nursing human resources,providing a reference for nursing human resource management.Methods A convenience sampling method was used to retrospectively select 5,431 hospitalized surgical patients admitted to 6 surgical nursing units of a tertiary general hospital in Suzhou from July to November 2022 as the subjects of this study.The nursing hours were measured,and related influencing factors were analyzed.A decision tree classification method was used to establish a classification model for surgical patients.From August to October 2022,1,527 hospitalized surgical patients admitted to 3 nursing units of the same hospital were conveniently selected.The minimum number of nurses required daily was calculated using the surgical patient classification model,actual nursing hours measurement method,nurse-to-bed ratio method,and 8-hour continuous shift scheduling method.The application effect of the surgical patient classification model in nursing human resource allocation was evaluated with the actual nursing hours measurement method as the standard.Results The surgical patient classification model includes 7 classification indicators:length of hospital stay,diagnosis-related group weight,presence or absence of secondary care orders,surgical grade,anesthesia method,age,and presence or absence of critical illness orders.Patients were divided into 14 groups,and the model explained 90.5％of the total variance in nursing workload.The minimum number of nurses required in surgical nursing units calculated based on this model was closest to the result of the actual nursing hours measurement method and was superior to the results of the nurse-to-bed ratio method and the 8-hour continuous shift scheduling method.Conclusion The surgical patient classification model can accurately reflect the nursing workload of such patients.The classification indicators are simple and easy to obtain,and can guide the allocation of human resources in surgical nursing units.

OBJECTIVES: Verrucous epidermal nevus (VEN), seborrheic keratosis (SK), verruca plana (VP), verruca vulgaris (VV), and nevus sebaceous (NS) are common verrucous proliferative skin diseases with similar clinical appearances, often posing diagnostic challenges. Dermoscopy and reflectance confocal microscopy (RCM) can aid in their differentiation, yet their specific features under these tools have not been systematically described. This study aims to summarize and analyze the dermoscopic and RCM features of VEN, SK, VP, VV, and NS. METHODS: A total of 121 patients with histopathologically confirmed verrucous proliferative skin diseases were enrolled. Dermoscopy and RCM imaging was used to observe and analyze the microscopic features of these conditions. RESULTS: Under dermoscopy, the 5 diseases displayed distinct characteristics: VEN typically showed gyriform structures; SK was characterized by gyriform structures, comedo-like openings, and milia-like cysts; VP and VV featured dotted vessels and frogspawn-like structures; NS presented as brownish-yellow globules. RCM revealed shared features such as hyperkeratosis and acanthosis across all 5 diseases. Specific features included gyriform structures and elongated rete ridges in VEN; pseudocysts and gyriform structures in SK; evenly distributed ring-like structures in VP; vacuolated cells and papillomatous proliferation in VV; and frogspawn-like structures in NS. CONCLUSIONS These 5 verrucous proliferative skin conditions exhibit distinguishable features under both dermoscopy and RCM. The combination of these 2 noninvasive imaging modalities holds significant clinical value for the differential diagnosis of verrucous proliferative skin diseases.
Humans ; Dermoscopy/methods* ; Diagnosis, Differential ; Microscopy, Confocal/methods* ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; Keratosis, Seborrheic/pathology* ; Young Adult ; Warts/diagnosis* ; Child ; Aged ; Skin Diseases/pathology* ; Nevus, Sebaceous of Jadassohn/diagnosis* ; Skin Neoplasms/diagnosis* ; Child, Preschool

Objective To explore the risk signals of niraparib and provide references for rational and safe clinical medication.Methods Niraparib-related adverse drug events(ADEs)reports from Q1 2017 to Q2 2023 were extracted from the US FDA Adverse Event Reporting System(FAERS)database.Risk signals were identified using the reporting odds ratio(ROR),proportional reporting ratio(PRR),Bayesian confidence propagation neural network(BCPNN),and multi-item gamma Poisson shrinker(MGPS)methods.The Risk signals were described and classified by preferred system organ classes(SOCs)and preferred terms(PTs)from the Medical Dictionary for Regulatory Activities(MedDRA)version 26.1,and the occurrence of niraparib-related ADEs was also analyzed.Results A total of 16,961 ADE reports with niraparib as the primary suspected drug were extracted.Through screening and analysis,32 PTs were identified involving 11 SOCs,which were largely consistent with the information in the drug label.However,suspicious signals not mentioned in the label,including neuropathy peripheral,decreased red blood cell count,reduced hematocrit,dehydration,and hot flashes,require further attention.The median occurrence time was 22 days(IQR 2-98 days),and the Weibull distribution test indicated an early failure-type curve.Conclusion When using niraparib,particularly in early stages of treatment,it is essential to monitor not only the ADEs mentioned in the drug instructions,such as decreased platelet count,nausea and fatigue,but also to pay close attention to the ADEs not included in the instructions,such as peripheral neuropathy and decreased red blood cell count,which exhibit strong signal values,to ensure patient medication safety.

Objective:To develop a training curriculum targeting the core competences of neurosurgery nurses, so as to provide a reference for standardized training of neurosurgery nurses and to strengthen their professionality.Methods:Centering on the core competences required for neurosurgery nurses, we formed the curriculum framework based on the cell structure-inspired concept proposed by the School of Nursing of The Hong Kong Polytechnic University, and determined the contents through a literature analysis and two rounds of questionnaire-based Delphi consultations with 16 experts. We increased, reduced, or modified the items and dimensions, and finally estabilished the curriculum for neurosurgery nurse training. SPSS 18.0 software was used to analyze the general information of experts, coordination coefficient, variation coefficient, full mark ratio, and mean importance value. Categorical data were described as frequencies and percentages, and continuous data were described as mean±standard deviation. Ranked data were analyzed by using the chi-square test.Results:In the two rounds of expert consultations, questionnaires were both 100.00% returned, and the coefficients of expert authority were 0.873 and 0.888, respectively. The coordination coefficient of curriculum modules and curriculum contents were 0.416 and 0.221, respectively ( P<0.001). For individual items across the curriculum modules, the mean importance value was 3.188-3.938, the variation coefficient was 0.063-0.178, and the full mark ratio was 0.250-0.875. For content items, the mean importance value was 3.250-4.000, the variation coefficient was 0-0.238, and the full mark ratio was 0.375-1.000. The established clinical practice-directed curriculum for neurosurgery nursing training included 6 course modules (anatomy and physiology of the nervous system, neurosurgery patient evaluation and monitoring, neurosurgery disease nursing, commonly used neurosurgery nursing techniques, nursing management, and scientific research basis) and 77 content items. Conclusions:The established training curriculum targeting the core competences for neurosurgery nurses is reliable, which can provide a reference for standardized training of neurosurgery nurses.

Objective:To develop a training curriculum targeting the core competences of neurosurgery nurses, so as to provide a reference for standardized training of neurosurgery nurses and to strengthen their professionality.Methods:Centering on the core competences required for neurosurgery nurses, we formed the curriculum framework based on the cell structure-inspired concept proposed by the School of Nursing of The Hong Kong Polytechnic University, and determined the contents through a literature analysis and two rounds of questionnaire-based Delphi consultations with 16 experts. We increased, reduced, or modified the items and dimensions, and finally estabilished the curriculum for neurosurgery nurse training. SPSS 18.0 software was used to analyze the general information of experts, coordination coefficient, variation coefficient, full mark ratio, and mean importance value. Categorical data were described as frequencies and percentages, and continuous data were described as mean±standard deviation. Ranked data were analyzed by using the chi-square test.Results:In the two rounds of expert consultations, questionnaires were both 100.00% returned, and the coefficients of expert authority were 0.873 and 0.888, respectively. The coordination coefficient of curriculum modules and curriculum contents were 0.416 and 0.221, respectively ( P<0.001). For individual items across the curriculum modules, the mean importance value was 3.188-3.938, the variation coefficient was 0.063-0.178, and the full mark ratio was 0.250-0.875. For content items, the mean importance value was 3.250-4.000, the variation coefficient was 0-0.238, and the full mark ratio was 0.375-1.000. The established clinical practice-directed curriculum for neurosurgery nursing training included 6 course modules (anatomy and physiology of the nervous system, neurosurgery patient evaluation and monitoring, neurosurgery disease nursing, commonly used neurosurgery nursing techniques, nursing management, and scientific research basis) and 77 content items. Conclusions:The established training curriculum targeting the core competences for neurosurgery nurses is reliable, which can provide a reference for standardized training of neurosurgery nurses.

Objective To construct a classification model for surgical patients and apply it in the allocation of nursing human resources,providing a reference for nursing human resource management.Methods A convenience sampling method was used to retrospectively select 5,431 hospitalized surgical patients admitted to 6 surgical nursing units of a tertiary general hospital in Suzhou from July to November 2022 as the subjects of this study.The nursing hours were measured,and related influencing factors were analyzed.A decision tree classification method was used to establish a classification model for surgical patients.From August to October 2022,1,527 hospitalized surgical patients admitted to 3 nursing units of the same hospital were conveniently selected.The minimum number of nurses required daily was calculated using the surgical patient classification model,actual nursing hours measurement method,nurse-to-bed ratio method,and 8-hour continuous shift scheduling method.The application effect of the surgical patient classification model in nursing human resource allocation was evaluated with the actual nursing hours measurement method as the standard.Results The surgical patient classification model includes 7 classification indicators:length of hospital stay,diagnosis-related group weight,presence or absence of secondary care orders,surgical grade,anesthesia method,age,and presence or absence of critical illness orders.Patients were divided into 14 groups,and the model explained 90.5％of the total variance in nursing workload.The minimum number of nurses required in surgical nursing units calculated based on this model was closest to the result of the actual nursing hours measurement method and was superior to the results of the nurse-to-bed ratio method and the 8-hour continuous shift scheduling method.Conclusion The surgical patient classification model can accurately reflect the nursing workload of such patients.The classification indicators are simple and easy to obtain,and can guide the allocation of human resources in surgical nursing units.