ObjectiveTo evaluate the efficacy,safety and clinical value of anterior urethral fusion to treat diphallia.MethodsA 17-year-old male patient with complete penile diphallia was treated in March 2011.The physical examination showed two completely separated mature penis; urethrography,and urethroscope showed the two urethras were completely separated and entered the bladder respectively.Two anterior urethras were incised respectively at ventral sides ( from the meatus to bulbar urethra) and then two incised anterior urethras were splintered by a continuous suture with 4-0 polyglactin sutures in side and side.Two penises were splintered into one.The nocturnal penile tumescence test and the penis vibration thresholds were assessed before,and after surgery..ResultsThe patient was followed up for 12 months.There was no hematoma,urinary fistula,urinary incontinence and other complications postoperatively.The penis was recovered with normal appearance; urination and morning erection of penile were normal.6 months after surgery,there was no significant difference in the nocturnal penile tumescence and penis vibration thresholds detection ( P ＞ 0.05).ConclusionThe operation of anterior urethral fusion is a safe and efficient surgical treatment to treat partial complete penile diphallia with less complication and no worse effect on urination and erection of penile.

One of the major challenges in single-cell data analysis is the determination of cellular developmental trajectories using single-cell data.Although substantial studies have been conducted in recent years,more effective methods are still strongly needed to infer the developmental processes accurately.This work devises a new method,named DTFLOW,for determining the pseudo-temporal trajectories with multiple branches.DTFLOW consists of two major steps:a new method called Bhattacharyya kernel feature decomposition (BKFD) to reduce the data dimensions,and a novel approach named Reverse Searching on k-nearest neighbor graph (RSKG) to identify the multi-branching processes of cellular differentiation.In BKFD,we first establish a stationary dis-tribution for each cell to represent the transition of cellular developmental states based on the ran-dom walk with restart algorithm,and then propose a new distance metric for calculating pseudotime of single cells by introducing the Bhattacharyya kernel matrix.The effectiveness of DTFLOW is rigorously examined by using four single-cell datasets.We compare the efficiency of DTFLOW with the published state-of-the-art methods.Simulation results suggest that DTFLOW has superior accuracy and strong robustness properties for constructing pseudotime trajectories.The Python source code of DTFLOW can be freely accessed at https://github.com/statway/DTFLOW.