Young people exposure to antibiotics: Implication for health risk and the impact from eating habits of takeaway food.

Exposure to antibiotics, mainly from animal food ingestion, may have adverse effects on human health. Takeaway food is the preferred choice for the dietary of most Chinese young people nowadays, but the relationship between takeaway eating and antibiotic exposure is not yet adequately understood. In the present study, 297 young people were recruited to collect urine samples and questionnaires with an emphasis on their takeaway eating habits. The internal exposure to 16 antibiotics and three metabolites was measured in urine samples by high-performance liquid chromatography-tandem mass spectrometry, as well as a DNA oxidative damage marker, 8-hydroxydeoxyguanosine (8-OHdG). At least one kind of antibiotic was found in over 90 % of urine samples, with total concentrations from 0.667 to 3.02 × 104 ng/mL. High exposure levels of antibiotics were more likely to be found in individuals with a larger body mass index. The concentrations of six antibiotics were significantly different among people with different overall weekly eating frequencies, usually an upward trend. The estimated daily intakes of antibiotics were on the levels of 0.001-1.0 µg/kg/day, mainly contributed by clarithromycin, ciprofloxacin and oxytetracycline, indicating a potential health risk based on the microbiological effect. A significantly positive correlation was found between DNA oxidative damage and exposure for four categories of antibiotics, conformed by both Spearman correlation and multiple linear regression analysis. The levels of 8-OHdG were 355 %, 239 %, 234 %, and 334 % higher with elevated levels of phenicols, macrolides, tetracyclines and sulfonamides from quartiles 2 to 4. Our results suggest that high-frequency consumption of takeaways may exacerbate oxidative stress trends through human exposure to antibiotics.

Clinical outcomes of robotic-assisted and manual total hip arthroplasty in the same patient: A case report.

BACKGROUND: Total hip arthroplasty (THA) is an effective treatment for advanced osteonecrosis of the femoral head, which can significantly relieve pain and improve patients' quality of life. Robotic-assisted THA enhances the accuracy and stability of THA surgery and achieves better clinical outcomes than manual THA. CASE SUMMARY: We report the clinical outcomes of robotic-assisted THA and manual THA in the same patient with osteonecrosis of the femoral head. A 49-year-old male patient attended our hospital due to more than 3 years of pain in both hip joints. The left hip was treated with robotic-assisted THA. The patient underwent manual THA of the right hip 3 mo after robotic-assisted THA. We obtained postoperative radiograph parameters, Harris hip score and forgotten joint score of the patient 1 year after surgery. CONCLUSION: Compared with manual THA, the patient's left hip felt better 1 year after robotic-assisted THA. Robotic-assisted THA resulted in a better Harris hip score and forgotten joint score than manual THA in the same patient with osteonecrosis of the femoral head.

Artificial intelligence promotes shared decision-making through recommending tests to febrile pediatric outpatients.

BACKGROUND: To promote the shared decision-making (SDM) between patients and doctors in pediatric outpatient departments, this study was designed to validate artificial intelligence (AI) -initiated medical tests for children with fever. METHODS: We designed an AI model, named Xiaoyi, to suggest necessary tests for a febrile child before visiting a pediatric outpatient clinic. We calculated the sensitivity, specificity, and F1 score to evaluate the efficacy of Xiaoyi's recommendations. The patients were divided into the rejection and acceptance groups. Then we analyzed the rejected examination items in order to obtain the corresponding reasons. RESULTS: We recruited a total of 11,867 children with fever who had used Xiaoyi in outpatient clinics. The recommended examinations given by Xiaoyi for 10,636 (89.6%) patients were qualified. The average F1 score reached 0.94. A total of 58.4% of the patients accepted Xiaoyi's suggestions (acceptance group), and 41.6% refused (rejection group). Imaging examinations were rejected by most patients (46.7%). The tests being time-consuming were rejected by 2,133 patients (43.2%), including rejecting pathogen studies in 1,347 patients (68.5%) and image studies in 732 patients (31.8%). The difficulty of sampling was the main reason for rejecting routine tests (41.9%). CONCLUSION: Our model has high accuracy and acceptability in recommending medical tests to febrile pediatric patients, and is worth promoting in facilitating SDM.

Pre-Consultation System Based on the Artificial Intelligence Has a Better Diagnostic Performance Than the Physicians in the Outpatient Department of Pediatrics.

Artificial intelligence (AI) has been deeply applied in the medical field and has shown broad application prospects. Pre-consultation system is an important supplement to the traditional face-to-face consultation. The combination of the AI and the pre-consultation system can help to raise the efficiency of the clinical work. However, it is still challenging for the AI to analyze and process the complicated electronic health record (EHR) data. Our pre-consultation system uses an automated natural language processing (NLP) system to communicate with the patients through the mobile terminals, applying the deep learning (DL) techniques to extract the symptomatic information, and finally outputs the structured electronic medical records. From November 2019 to May 2020, a total of 2,648 pediatric patients used our model to provide their medical history and get the primary diagnosis before visiting the physicians in the outpatient department of the Shanghai Children's Medical Center. Our task is to evaluate the ability of the AI and doctors to obtain the primary diagnosis and to analyze the effect of the consistency between the medical history described by our model and the physicians on the diagnostic performance. The results showed that if we do not consider whether the medical history recorded by the AI and doctors was consistent or not, our model performed worse compared to the physicians and had a lower average F1 score (0.825 vs. 0.912). However, when the chief complaint or the history of present illness described by the AI and doctors was consistent, our model had a higher average F1 score and was closer to the doctors. Finally, when the AI had the same diagnostic conditions with doctors, our model achieved a higher average F1 score (0.931) compared to the physicians (0.92). This study demonstrated that our model could obtain a more structured medical history and had a good diagnostic logic, which would help to improve the diagnostic accuracy of the outpatient doctors and reduce the misdiagnosis and missed diagnosis. But, our model still needs a good deal of training to obtain more accurate symptomatic information.

A silicon-on-insulator slab for topological valley transport.

Backscattering suppression in silicon-on-insulator (SOI) is one of the central issues to reduce energy loss and signal distortion, enabling for capability improvement of modern information processing systems. Valley physics provides an intriguing way for robust information transfer and unidirectional coupling in topological nanophotonics. Here we realize topological transport in a SOI valley photonic crystal slab. Localized Berry curvature near zone corners guarantees the existence of valley-dependent edge states below light cone, maintaining in-plane robustness and light confinement simultaneously. Topologically robust transport at telecommunication is observed along two sharp-bend interfaces in subwavelength scale, showing flat-top high transmission of ~10% bandwidth. Topological photonic routing is achieved in a bearded-stack interface, due to unidirectional excitation of valley-chirality-locked edge state from the phase vortex of a nanoscale microdisk. These findings show the prototype of robustly integrated devices, and open a new door towards the observation of non-trivial states even in non-Hermitian systems.

[Clinical diagnosis and treatment for iliotibial band syndrome].

As an usually occurs in athletes, iliotibial band syndrome is payed more attention for people, the disease is diagnosed mainly by clinical symptoms, physical examination and MRI, but there is no uniform diagnostic criteria. The pathogenesis of iliotibial band syndrome is considered to be related to pressure and friction factors. As for the treatment, manipulation, muscle exercise, mainly drugs and physical therapy and so on both at home and abroad are recognized to use to achieve desired effect. For conservative failure, refractory iliotibial band syndrome patients, arthroscopy, or release of iliotibial band syndrome surgery are performed. While conservative local drug injection combined with muscle exercise could play a role in pain management besides, arthroscopic as operation method is more advanced, and applicable to all types of patients without absolute contraindication, so it is helpful for patients with early activity. At present, there is still a great deal of controversy about its pathogenesis, and there is no obvious limit for the specific indications of its various therapies in clinic, so it needs further specification.