Aim: To put forward criteria for the pressure assessment in the operation of intercavemous embedding of bulboperineal urethra for the treatment of urinary incontinence after prostatic operation. Methods: A Fl4 urethral catheter is inserted during the operation and upon suturing the corpora cavemosa centrally, the catheter is slowly pushed in and pulled out in order that the operator feels a certain degree of close-fit resistance. The degree of tightness of the stitches,which regulate the compression pressure, is adjusted in accordance with this close-fit sensation. To further ascertain the adequacy of the force of compression, the bladder is filled with 300 ml physiological saline and observe the appropriateness (size and continuity) of the outflow stream when the lower abdomen is depressed with a pressure of 80-90 cm H2O. The operation was given to six patients suffered from urinary incontinence for 20 or more months after prostatic operation. Results: Five cases achieved complete recovery, while the therapeutic effect of the 6th one was not satisfactory. A second stage operation was carried out 3 months later with the addition of one more stitch both proximally and distally to reinforce the compression force. The condition was improved dramatically. The follow-up period averaged 3.5 years. Conclusion: The adequacy of the compression pressure exerted by the juxtaposed corpora cavernosa is the key point determining the outcome of the operation. The measures for assessing the compression pressure suggested by the authors are helpful in obtaining the good results of the present paper (6/6 success) as compared with 25/34success in the previous report.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

According to folk usage of Aconitum carmichaelii Debx., the present study was designed to determine the feasibility of the stems and leaves of Aconitum carmichaelii Debx. as a new medicinal resource. Fourteen alkaloids in mother roots, fibrous roots, stems, and leaves of Aconitum carmichaelii Debx. were measured by HPLC-MS/MS. And multivariate analysis methods, such as clustering analysis and principal component analysis, were applied to analyze the difference among various parts. In addition, the acute toxicity, analgesia, and anti-inflammatory tests were carried out. The results suggested that the contents of alkaloids in mother roots and fibrous roots were approximate, but those of leaves and stems were different from mother roots and fibrous roots. The results of the acute toxicity testing demonstrated the toxicity of fibrous root was strongest, and mother roots were slightly less toxic than fibrous roots. The stems and leaves were far less toxic than mother and fibrous roots. In addition, the analgesia and inflammatory tests showed the effects of the various tissues had no difference each other. These results provided a basis for developing new complementary and alternative treatments for rheumatoid arthritis patients. Simultaneously, the approach may also turn wastes into treasure and promote the development of circular economy.
Aconitum ; chemistry ; Alkaloids ; administration & dosage ; chemistry ; toxicity ; Animals ; Anti-Inflammatory Agents ; administration & dosage ; chemistry ; toxicity ; Arthritis, Rheumatoid ; drug therapy ; Chromatography, High Pressure Liquid ; Drug Evaluation, Preclinical ; Drugs, Chinese Herbal ; administration & dosage ; chemistry ; toxicity ; Female ; Humans ; Male ; Mice ; Plant Leaves ; chemistry ; Plant Roots ; chemistry ; Plant Stems ; chemistry ; Tandem Mass Spectrometry