Pseudouridine (Ψ) at position 55 in tRNAs plays an important role in their structure and function. This modification is catalyzed by TruB/Pus4/Cbf5 family of pseudouridine synthases in bacteria and yeast. However, the mechanism of TRUB family underlying the formation of Ψ55 in the mammalian tRNAs is largely unknown. In this report, the CMC/reverse transcription assays demonstrated the presence of Ψ55 in the human mitochondrial tRNAAsn, tRNAGln, tRNAGlu, tRNAPro, tRNAMet, tRNALeu(UUR) and tRNASer(UCN). TRUB1 knockout (KO) cell lines generated by CRISPR/Cas9 technology exhibited the loss of Ψ55 modification in mitochondrial tRNAAsn, tRNAGln, tRNAGlu and tRNAPro but did not affect other 18 mitochondrial tRNAs. An in vitro assay revealed that recombinant TRUB1 protein can catalyze the efficient formation of Ψ55 in tRNAAsn and tRNAGln, but not in tRNAMet and tRNAArg. Notably, the overexpression of TRUB1 cDNA reversed the deficient Ψ55 modifications in these tRNAs in TRUB1KO HeLa cells. TRUB1 deficiency affected the base-pairing (18A/G-Ψ55), conformation and stability but not aminoacylation capacity of these tRNAs. Furthermore, TRUB1 deficiency impacted mitochondrial translation and biogenesis of oxidative phosphorylation system. Our findings demonstrated that human TRUB1 is a highly conserved mitochondrial pseudouridine synthase responsible for the Ψ55 modification in the mitochondrial tRNAAsn, tRNAGln, tRNAGlu and tRNAPro.

IMPORTANCEThe effectiveness of mobile health (mHealth) apps for reducing obesity is not ideal in daily life. Therefore, it would be useful to explore factors associated with user satisfaction with weight loss apps. Currently, research on these factors from the perspective of user-generated content is lacking. OBJECTIVE To mine the themes and topics frequently discussed in user-generated content in mHealth apps for weight loss, explore correlations of the topics with user satisfaction and dissatisfaction, and assess whether these correlations were asymmetric. DESIGN, SETTING, AND PARTICIPANTSIn this population-based cross-sectional study, unsupervised machine learning was used to identify themes and topics in online discussions generated between January 1, 2019, and May 20, 2021, by Chinese users of mHealth apps for weight loss. MAIN OUTCOMES AND MEASURESBased on the 2-factor theory, a tobit regression model was used to explore the correlation of various app discussion topics with user satisfaction and dissatisfaction. Differences of the coefficients in models of positive rating deviation (PD) and negative rating deviation (ND), defined as the difference between the users' rating of the app and the app's comprehensive rating in the app stores, were analyzed by the Wald test. RESULTSIn total, 191 619 reviews and ratings from unique usernames were collected for 2139 weight loss apps; 86 423 reviews (45.1%) from 339 apps (15.8%) were included in the study. Most users (65 249 [75.5%]) were satisfied with the mHealth app. Eighteen topics were identified and summarized into 9 themes. Nine topics had significant positive correlations with the PD of user satisfaction, and 6 had significant negative correlations. The factor with the strongest positive correlation with the PD was celebrity effect (β = 0.307; 95% CI, 0.290-0.323), and the factor with the weakest correlation was economic cost (β = −0.426; 95% CI, −0.447 to −0.406). Nine topics had significant positive correlations with the ND of user satisfaction, whereas 7 topics had significant negative correlations. The factor with the strongest positive correlation with the ND was fitness effect (β = 1.369; 95% CI, 1.283-1.455), and the factor with the strongest negative correlation was economic cost (β = −2.813; 95% CI, −2.875 to −2.751). There were significant differences in the PD and ND of user satisfaction. Nine motivation factors (ie, value-added attributes) and 7 hygiene factors (ie, user-expected attributes) for mHealth apps were identified. CONCLUSIONS AND RELEVANCEIn this cross-sectional study, 16 factors had asymmetric correlations with user satisfaction and dissatisfaction with weight loss apps; 7 were related to basic expected attributes of the apps and 9 to value-added attributes. By distinguishing between expected and value-added factors, the use of weight loss apps may be improved.

Background The China Hospital Information Network Conference (CHINC) is one of the most influential academic and technical exchange activities in medical informatics and medical informatization in China. It collects frontier ideas in medical information and has an important reference value for the analysis of China's medical information industry development. Objective This study summarizes the current situation and future development of China's medical information industry and provides a future reference for China and abroad in the future by analyzing the characteristics of CHINC exhibitors in 2021. Methods The list of enterprises and participating keywords were obtained from the official website of CHINC. Basic characteristics of the enterprises, industrial fields, applied technologies, company concepts, and other information were collected from the TianYanCha website and the VBDATA company library. Descriptive analysis was used to analyze the collected data, and we summarized the future development directions. Results A total of 205 enterprises officially participated in the exhibition. Most of the enterprises were newly founded, of which 61.9% (127/205) were founded in the past 10 years. The majority of these enterprises were from first-tier cities, and 79.02% (162/205) were from Beijing, Zhejiang, Guangdong, Shanghai, and Jiangsu Provinces. The median registered capital is 16.67 million RMB (about US $2.61 million), and there are 35 (72.2%) enterprises with a registered capital of more than 100 million RMB (about US $15.68 million), 17 (8.3%) of which are already listed. A total of 126 enterprises were found in the VBDATA company library, of which 39 (30.9%) are information technology vendors and 57 (45.2%) are application technology vendors. In addition, 16 of the 57 (28%) use artificial intelligence technology. Smart medicine and internet hospitals were the focus of the enterprises participating in this conference. Conclusions China's tertiary hospital informatization has basically completed the construction of the primary stage. The average grade of hospital electronic medical records exceeds grade 3, and 78.13% of the provinces have reached grade 3 or above. The characteristics are as follows: On the one hand, China's medical information industry is focusing on the construction of smart hospitals, including intelligent systems supporting doctors' scientific research, diagnosis-related group intelligent operation systems, and office automation systems supporting hospital management, single-disease clinical decision support systems assisting doctors' clinical care, and intelligent internet of things for logistics. On the other hand, the construction of a compact county medical community is becoming a new focus of enterprises under the guidance of practical needs and national policies to improve the quality of grassroots health services. In addition, whole-course management and digital therapy will also become a new hotspot in the future.

BACKGROUND The China Hospital Information Network Conference (CHINC) is one of the most influential academic and technical exchange activities in medical informatics and medical informatization in China. It collects frontier ideas in medical information and has an important reference value for the analysis of China's medical information industry development. OBJECTIVE This study summarizes the current situation and future development of China's medical information industry and provides a future reference for China and abroad in the future by analyzing the characteristics of CHINC exhibitors in 2021. METHODS The list of enterprises and participating keywords were obtained from the official website of CHINC. Basic characteristics of the enterprises, industrial fields, applied technologies, company concepts, and other information were collected from the TianYanCha website and the VBDATA company library. Descriptive analysis was used to analyze the collected data, and we summarized the future development directions. RESULTS A total of 205 enterprises officially participated in the exhibition. Most of the enterprises were newly founded, of which 61.9% (127/205) were founded in the past 10 years. The majority of these enterprises were from first-tier cities, and 79.02% (162/205) were from Beijing, Zhejiang, Guangdong, Shanghai, and Jiangsu Provinces. The median registered capital is 16.67 million RMB (about US $2.61 million), and there are 35 (72.2%) enterprises with a registered capital of more than 100 million RMB (about US $15.68 million), 17 (8.3%) of which are already listed. A total of 126 enterprises were found in the VBDATA company library, of which 39 (30.9%) are information technology vendors and 57 (45.2%) are application technology vendors. In addition, 16 of the 57 (28%) use artificial intelligence technology. Smart medicine and internet hospitals were the focus of the enterprises participating in this conference. CONCLUSIONS China's tertiary hospital informatization has basically completed the construction of the primary stage. The average grade of hospital electronic medical records exceeds grade 3, and 78.13% of the provinces have reached grade 3 or above. The characteristics are as follows: On the one hand, China's medical information industry is focusing on the construction of smart hospitals, including intelligent systems supporting doctors' scientific research, diagnosis-related group intelligent operation systems, and office automation systems supporting hospital management, single-disease clinical decision support systems assisting doctors' clinical care, and intelligent internet of things for logistics. On the other hand, the construction of a compact county medical community is becoming a new focus of enterprises under the guidance of practical needs and national policies to improve the quality of grassroots health services. In addition, whole-course management and digital therapy will also become a new hotspot in the future.

BACKGROUND Tinnitus has become a global medical problem, can seriously harm human health, is challenging to alleviate, and ranks among the top three complex diseases in otolaryngology. OBJECTIVE This study aimed to analyse the research progress of mHealth for tinnitus treatment with related marketed products to further understand the research trends, product characteristics, problems, and transformation of tinnitus treatment software. METHODS Bibliometric methods were used to describe the characteristics of the relevant literature in terms of the number, authors, institutions, and topics. Using comparative product analysis, we compared the product features and problems of currently available tinnitus treatment software. RESULTS The data search was conducted for the period up to Feb 28, 2022. Following the PRISMA standardised screening process, 75 papers were finally included. The country with the most publications was Germany, followed by the UK and the USA, while China had only one relevant study. The most published journals were the American Journal of Audiology and Journal of the American Academy of Audiology (18,24%). As for the topics of publication, cognitive behavioural therapy started to become a hot topic in 2017, and research on mHealth increased. Including 22 pieces (78.6%) were medical or health apps; developers were mainly from the US (35.7%) and China (32.1%), with 35.7% (10) and 32.1% (9) respectively; the main treatment methods were sound therapy (10,35.7%) and cognitive behavioural therapy (2,7.1%). Seven (9.3%) of the 75 publications described products at the market stage, and 22 (78.6%) of the 28 marketed products lacked literature studies or evidence from professional bodies. CONCLUSIONS The use of mHealth for the treatment and intervention of tinnitus has shown an overall rapid development trend, in which good progress has been made in research on acoustic and cognitive behavioural therapies, and most studies have focused on treatment effects.