The risk prediction approach integrating disease and syndrome aligns more precisely with the clinical diagnosis and treatment needs of osteoporosis.Prior research has established a consensus on the model development methodology encompassing"Target outcome selection→ Key information collection→ Data mining and modeling →Model performance evaluation".Building on this foundation,a cohort of osteoporosis patients and syndrome cases with stable follow-up is established.Utilizing artificial intelligence algorithms,critical information in traditional Chinese medicine(TCM)symptoms and syndromes is objectively characterized and quantified alongside imaging data.Employing multi-omics sequencing technology,we seek to identify highly specific microscopic molecular information,analyze potential correlations among various dimensions of information,and develop a multidimensional risk prediction model for osteoporosis with distinctive TCM attributes.This model aims to identify biomarkers with both"disease"and"syndrome"characteristics,thereby advancing the precision diagnosis and treatment system for osteoporosis.

The risk prediction approach integrating disease and syndrome aligns more precisely with the clinical diagnosis and treatment needs of osteoporosis.Prior research has established a consensus on the model development methodology encompassing"Target outcome selection→ Key information collection→ Data mining and modeling →Model performance evaluation".Building on this foundation,a cohort of osteoporosis patients and syndrome cases with stable follow-up is established.Utilizing artificial intelligence algorithms,critical information in traditional Chinese medicine(TCM)symptoms and syndromes is objectively characterized and quantified alongside imaging data.Employing multi-omics sequencing technology,we seek to identify highly specific microscopic molecular information,analyze potential correlations among various dimensions of information,and develop a multidimensional risk prediction model for osteoporosis with distinctive TCM attributes.This model aims to identify biomarkers with both"disease"and"syndrome"characteristics,thereby advancing the precision diagnosis and treatment system for osteoporosis.

Objective To evaluate the feasibility and safety of the robot - assisted system YunSRobot for remote manipulation endoscopy. Methods When the master of YunSRobot was installed in the gastroenterology office in Chinese PLA General Hospital, the robot slave and upper gastrointestinal simulation model (Takahashi Lm103,Japan) were installed at the same time in the State Key Laboratory of Robotics, Shenyang Institute of Automation. Three physicians were trained to operate the master robotics and performed gastroscopy on the simulation model based on network cloud. Each physician performed 3 procedures of oesophagogastroduodenoscopy (EGD) by YunSRobot using traditional manual endoscopy, on-site operating mode, and remote manipulation mode, respectively. The operating time, lumenal anatomic exposure,man-machine interaction and other parameters were recorded. Results The number of standard pictures obtained by traditional manual endoscopy group, on-site operating group and remote manipulation group were 39.9±0.3, 39.8±0.4, 39.9±0.3, respectively. The images of all five lesions could be obtained by each operation. The operating time in the duodenum of remote group was longer than that of on-site group, with average time (78.2±16.0)s vs. (68.9±15.8)s (P=0.021) respectively. As to the operating time on other parts or total time, all three groups were comparable. Although there was a mean delay of (572.1±48.5) ms in remote operation group, the operation was still smooth. However, compared with on-site group, the percentage of clear view time in the duodenum was significantly shortened in remote group: [(77.8±8.2)% vs. (83.9 ± 6.4)% , P=0.024]. Statistically significant difference was detected in percentage of clear view time neither in other sites, nor was in the total operating time between two groups. The operating time in each part of remote group was obviously longer than that of manual group as followings, pharyngeal (27.3±4.2) s vs. (9.2±1.3)s (P<0.001), esophageal (29.7±6.4)s vs. (19.3±1.6)s (P=0.004), stomach (56.7±17.0)s vs. (40.3±7.0)s (P=0.003), pylorus (20.2±5.5)s vs. (9.3±1.3)s (P<0.001), duodenum (78.2±16.0)s vs. (29.3±5.6)s (P<0.001). Thus the total operating time was also longer in remote group as (559.0±87.2)s vs. (253.1±16.6)s (P<0.001). The respective time in pharynx, esophagus, stomach, pylorus, duodenum, or the overall time was all longer in remote group than that in manual group. Conclusions The soft endoscopy robot YunSRobot has satisfactory safety and stability. Remote upper gastrointestinal endoscopy can be completed based on common network and an endoscope simulation model with smooth operation. The inspection time by YunSRobot robot per part and the overall time are longer than those of manual operation on site, still, remote operating time meets the standard of upper gastrointestinal endoscopy.

Thioesterase catalyzes the hydrolysis of acyl-ACP and saturated fatty acyl chain. It plays a key role in the accumulation of medium chain fatty acids in vivo. In this study, to construct an engineering strain to produce MCFAs, the Arabidopsis acyl-ACP thioesterase gene AtFatA was amplified by PCR from cDNA of arabidopsis and double digested by EcoR I/Xba I, then linked to the plasmid digested with same enzymes to get the recombinant plasmid pPICZaA-AtFatA. We transformed the gene into Pichia pastoris GS115 by electroporation and screened positive colonies by YPD medium with Zeocin. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) results showed that the recombinant enzyme had a molecular of 45 kDa band which was consistent with the predicted molecular mass and we constructed the expression system of gene AtFatA in fungus for the first time. Under shake-flask conditions, Gas Chromatograph-Mass Spectrometer-computer results indicated that recombinant strain produced 51% more extracellular free MCFAs than the wild and its yield reached 28.7% of all extracellular fatty acids. This figure is 10% higher than the control group. The result provides a new way to produce MCFAs.
Arabidopsis ; genetics ; Arabidopsis Proteins ; biosynthesis ; DNA, Complementary ; Electrophoresis, Polyacrylamide Gel ; Electroporation ; Pichia ; metabolism ; Plasmids ; Polymerase Chain Reaction ; Recombinant Proteins ; biosynthesis ; Thiolester Hydrolases ; biosynthesis ; Transformation, Genetic