Injectable collagen scaffold with human umbilical cordderived mesenchymal stem cells promotes functional recovery in patients with spontaneous intracerebral hemorrhage:phase Ⅰ clinical trial

Animal expe riments have shown that injectable collagen scaffold with human umbilical cord-derived mesenchymal stem cells can promote recovery from spinal cord injury.To investigate whether injectable collagen scaffold with human umbilical cord-derived mesenchymal stem cells can be used to treat spontaneous intracerebral hemorrhage,this non-randomized phase I clinical trial recruited patients who met the inclusion criteria and did not meet the exclusion crite ria of spontaneous intracerebral hemorrhage treated in the Characteristic Medical Center of Chinese People’s Armed Police Force from May 2016 to December 2020.Patients were divided into three groups according to the clinical situation and patient benefit:control(n=18),human umbilical cord-derived mesenchymal stem cells(n=4),and combination(n=8).The control group did not receive any transplantation.The human umbilical cord-derived mesenchymal stem cells group received human umbilical cord-derived mesenchymal stem cell transplantation.The combination group received injectable collagen scaffold with human umbilical cord-derived mesenchymal stem cells.Patients who received injectable collagen scaffold with human umbilical cord-derived mesenchymal stem cells had more remarkable improvements in activities of daily living and cognitive function and smaller foci of intra cerebral hemorrhage-related encephalomalacia.Severe adve rse events associated with cell transplantation were not observed.Injectable collagen scaffold with human umbilical cord-derived mesenchymal stem cells appears to have great potential treating spontaneous intracerebral hemorrhage.

World Federation of Acupuncture-Moxibustion Societies(WFAS)Technical Benchmark of Acupuncture and Moxibustion:Cupping

World Federation of Acupuncture-Moxibustion Societies(WFAS)Technical Benchmark of Acupuncture and Moxibustion:Cupping,developed under the leadership of Tianjin University of Traditional Chinese Medicine,was approved by WFAS.This technical benchmark was issued on October 9,2023,and implemented on December 31,2023.The main contents include the scope,normative references,terms and definitions,procedures and rules,and safety.This article focuses on the above contents,an outlook on the application,popularization,and update plan of this technical benchmark is proposed.

Risk assessment of malignancy in solitary pulmonary nodules in lung computed tomography:a multivariable predictive model study

Background:Computed tomography images are easy to misjudge because of their complexity,especially images of solitary pulmonary nodules,of which diagnosis as benign or malignant is extremely important in lung cancer treatment.Therefore,there is an urgent need for a more effective strategy in lung cancer diagnosis.In our study,we aimed to externally validate and revise the Mayo model,and a new model was established.Methods:A total of 1450 patients from three centers with solitary pulmonary nodules who underwent surgery were included in the study and were divided into training,internal validation,and external validation sets(n=849,365,and 236,respectively).External verification and recalibration of the Mayo model and establishment of new logistic regression model were performed on the training set.Overall performance of each model was evaluated using area under receiver operating characteristic curve(AUC).Finally,the model validation was completed on the validation data set.Results:The AUC of the Mayo model on the training set was 0.653(95%confidence interval[CI]:0.613–0.694).After re-estimation of the coefficients of all covariates included in the original Mayo model,the revised Mayo model achieved an AUC of 0.671(95%CI:0.635–0.706).We then developed a new model that achieved a higher AUC of 0.891(95%CI:0.865–0.917).It had an AUC of 0.888(95%CI:0.842–0.934)on the internal validation set,which was significantly higher than that of the revised Mayo model(AUC:0.577,95%CI:0.509–0.646)and the Mayo model(AUC:0.609,95%CI,0.544–0.675)(P<0.001).The AUC of the new model was 0.876(95%CI:0.831–0.920)on the external verification set,which was higher than the corresponding value of the Mayo model(AUC:0.705,95%CI:0.639–0.772)and revised Mayo model(AUC:0.706,95%CI:0.640–0.772)(P<0.001).Then the prediction model was presented as a nomogram,which is easier to generalize.Conclusions:After external verification and recalibration of the Mayo model,the results show that they are not suitable for the prediction of malignant pulmonary nodules in the Chinese population.Therefore,a new model was established by a backward stepwise process.The new model was constructed to rapidly discriminate benign from malignant pulmonary nodules,which could achieve accurate diagnosis of potential patients with lung cancer.

Live Cells Process Exogenous Peptide as Fibronectin Fibrillogenesis In Vivo

The human body is one of the most sophisticated material systems.It is still a considerable challenge to biomimic the“life-design”process to construct a part of“life”in vivo.Herein,we mimicked the natural fibronectin(FN)fibrillogenesis system using ligand–receptor interaction-induced self-assembly to construct in situ artificial fibrous FN in vivo,based on exogenous FN mimic peptide(FNMP).We performed the in vivo study with a tumor-bearing mouse model,to which the particle formulated FNMP raw materials were delivered with high efficiency to the tumor site through intravenous(iv)administration.In the tumor,the presence of overexpressed integrin receptors on the cell surface induced the self-assembly of the FNMP into fibrous structures,thereby,creating an artificial fibrous FN.However,the FNMP-based artificial fibrous FN showed different biological functionality from the natural fibrous FN,inhibiting the growth and migration of cells,making our constructed FN able to inhibit tumor growth,invasion,and metastasis.Thus,this study opens an avenue for the precise construction of biomimetic materials for in vivo biomedical applications.