Air-Writing Recognition Enabled by a Flexible Dual-Network Hydrogel-Based Sensor and Machine Learning.

Accurate air-writing recognition is pivotal for advancing state-of-the-art text recognizers, encryption tools, and biometric technologies. However, most existing air-writing recognition systems rely on image-based sensors to track hand and finger motion trajectories. Additionally, users' writing is often guided by delimiters and imaginary axes which restrict natural writing movements. Consequently, recognition accuracy falls short of optimal levels, hindering performance and usability for practical applications. Herein, we have developed an approach utilizing a one-dimensional convolutional neural network (1D-CNN) algorithm coupled with an ionic conductive flexible strain sensor based on a sodium chloride/sodium alginate/polyacrylamide (NaCl/SA/PAM) dual-network hydrogel for intelligent and accurate air-writing recognition. Taking advantage of the excellent characteristics of the hydrogel sensor, such as high stretchability, good tensile strength, high conductivity, strong adhesion, and high strain sensitivity, alongside the enhanced analytical ability of the 1D-CNN machine learning (ML) algorithm, we achieved a recognition accuracy of ∼96.3% for in-air handwritten characters of the English alphabets. Furthermore, comparative analysis against state-of-the-art methods, such as the widely used residual neural network (ResNet) algorithm, demonstrates the competitive performance of our integrated air-writing recognition system. The developed air-writing recognition system shows significant potential in advancing innovative systems for air-writing recognition and paving the way for exciting developments in human-machine interface (HMI) applications.

Identification of susceptibility modules and characteristic genes to osteoarthritis by WGCNA.

The susceptibility modules and characteristic genes of patients with osteoarthritis (OA) were determined by weighted gene co-expression network analysis (WGCNA), and the role of immune cells in OA related microenvironment was analyzed. GSE98918 and GSE117999 data sets are from GEO database. R language was used to conduct difference analysis for the new data set after merging. The formation of gene co-expression network, screening of susceptibility modules and screening of core genes are all through WGCNA. GO and KEGG enrichment analyses were used for Hub genes. The characteristic genes of the disease were obtained by Lasso regression screening. SSGSEA was used to estimate immune cell abundance in sample and a series of correlation analyses were performed. WGCNA was used to form 6 gene co-expression modules. The yellow-green module is identified as the susceptible module of OA. 202 genes were identified as core genes. Finally, RHOT2, FNBP4 and NARF were identified as the characteristic genes of OA. The results showed that the characteristic genes of OA were positively correlated with plasmacytoid dendritic cells, NKT cells and immature dendritic cells, but negatively correlated with active B cells. MDSC were the most abundant immune cells in cartilage. This study identified the Hippo signaling pathway, mTOR signaling pathway, and three characteristic genes (RHOT2, FNBP4, NARF) as being associated with osteoarthritis (OA). These three genes are downregulated in the cartilage of OA patients and may serve as biomarkers for early diagnosis and targeted therapy. Proper regulation of immune cells may aid in the treatment of OA. Future research should focus on developing tools to detect these genes and exploring their therapeutic applications.

A colorimetric-aptamer-based assay for the determination of enrofloxacin through triggering the aggregation of gold nanoparticles.

Although enrofloxacin (ENR) is a widely used broad-spectrum antibiotic in veterinary medicine, its residues in animals can pose a risk to human health. Thus, we developed a new method for detecting ENR based on aptamers and AuNPs. In the absence of ENR, the aptamers attached to the surface of the AuNPs via electrostatic interactions to protect the AuNPs from NaCl, and the solution remained red. Conversely, the aptamer bonded with ENR, leading the aptamer to detach from the AuNP surface, and the color of the solution changed from red to blue. Based on this principle, ENR can be qualitatively detected by the naked eye and quantitatively detected by measuring the absorbance ratio at 650 nm and 530 nm. The experimental results showed a good linear relationship within the ENR concentration range of 0-400 nM, with a limit of detection (LOD) of 1.72 nM, which is satisfactory for detection in food safety. Additionally, this method has also been successfully applied to the detection of ENR in tap water, river water, milk, serum and urine, with good recovery rates and RSD values of less than 7%, indicating its great potential for ENR detection in environmental water samples. More importantly, the combination of this method with a smartphone platform provided great convenience for on-site and visual detection of ENR, offering promising applicability prospects.

Occurrence of polycyclic aromatic hydrocarbons in the Yellow River delta: Sources, ecological risks, and microbial response.

This research investigated the distribution, sources, and ecological risks of polycyclic aromatic hydrocarbons (PAHs) in the Yellow River Delta (YRD), China, emphasizing the response of soil microorganisms. The study involved quantitative analyses of 16 PAHs specified by the U.S. Environmental Protection Agency (USEPA) in both water and soil, utilizing metagenomic technique to determine the response of microbial communities and metabolism within the soil. Results noted that PAHs in the water mainly originate from pyrogenic source and in the soil originate from mixture source, with higher concentrations found in wetland areas compared to river regions. The ecological risk assessment revealed low-to-moderate risk. Microbial analysis demonstrated increased diversity and abundance of bacteria associated with PAHs in areas with higher PAHs pollution. Metagenomic insights revealed significant effects of organic carbon on PAHs degradation genes (ko00624 and ko00626), as well as significant differences in specific metabolic pathways including phenanthrene degradation, with key enzymes showing significant differences between the two environments. The study underscores the importance of understanding PAHs distribution and microbial responses to effectively manage and mitigate pollution in estuarine environments.

tRNA-derived fragment 3031B regulates human anterior cruciate ligament cell proliferation and survival by targeting RELA.

tRNA-derived fragments (tRFs) are novel short noncoding RNAs that play pivotal roles in cell proliferation and survival. However, knowledge of the biological roles of tRFs in anterior cruciate ligament (ACL) cells is limited. Here, we intended to investigate the function of tRF-3031B in ACL cell. We used the tRF and tiRNA array to analyze tRF and tiRNA expression profiles in osteoarthritis (OA) ACL cells and normal ACL cells, and qRT-PCR and fluorescence in situ hybridization (FISH) were used to determine tRF-3031B expression. The results showed that tRF-3031B was expressed at low levels in OA ACL and Interleukin-1ß (IL-1ß) treated ACL cells. We found that RELA was the target of tRF-3031B. When ACL cells were transfected with tRF-3031B mimics, RELA expression was suppressed, whereas transfection with tRF-3031B inhibitors had the opposite effect. The rescue and dual-luciferase reporter assays showed that tRF-3031B silenced the RELA expression by binding to its untranslated region (3'-UTR). Hence, this study showed the novel function of tRF-3031B in regulating ACL cell proliferation and survival by targeting RELA, and these findings may offer a new direction for the study of ACL degeneration and pathophysiological of OA.

A prediction model based on MRI and ultrasound to predict the risk of PAS in patient with placenta previa.

INTRODUCTION: To investigate the risk factors affecting patients with placenta previa (PP) and to construct an effective prediction model for the severity of PAS in PP. METHODS: A total of 240 pregnant women with PP were enrolled in this study. An MRI+Ultrasound-based model was developed to classify patients into placental implantation and non-placental implantation groups. Multivariate nomograms were created based on imaging features. The model was evaluated using Receiver Operating Characteristic (ROC) curve analysis. The predictive accuracy of the nomogram was assessed through calibration plots and decision curve analysis. RESULTS: The MRI+Ultrasound-based prediction model demonstrated favorable discrimination between the placental implantation and non-placental implantation groups. The calibration curve exhibited agreement between the estimated and actual probability of placental implantation. Additionally, decision curve analysis indicated a high clinical benefit across a wide range of probability thresholds. The Area under the ROC curve (AUC) was 0.911 (95 % CI: 0.76-0.947), with a sensitivity of 88.40 % and specificity of 88.10 %. CONCLUSION: The MRI+Ultrasound-based prediction model could be a valuable tool for preoperative prediction of the percentage of implantation. Our study enables obstetricians to conduct more adequate preoperative evaluations.

The Optimal Variation Range of Posterior Condylar Offset Associated with Positive Clinical Outcomes of Primary Total Knee Arthroplasty: A Retrospective Analysis.

OBJECTIVE: Posterior condylar offset (PCO) and anterior condylar offset (ACO) exert an influence on the sagittal alignment in total knee arthroplasty (TKA). However, there is no common consensus that the variation range of posterior condylar offset (PCO) is associated with patient-reported outcome measures (PROMs) and the optimum variation range of PCO. This study aims to investigate the correlation between PCO and the PROMs of primary TKA for osteoarthritis (OA) and find out the optimal variation range of the PCO. METHODS: In this study, we performed a radiographic analysis of 106 patients (112 knees) with primary TKA. Patients were divided into two cohorts (A and B) according to the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC). Correlations between the sagittal parameter and WOMAC were investigated using univariate and multivariate analysis. The receiver operating characteristic (ROC) curve was used to establish the cut-off value for the optimal variation range. We then further investigated how different variation range affects the WOMAC subscale score and forgotten-joint-score-12 (FJS-12). RESULTS: Univariate analysis revealed a correlation between the variation range of PCO (p < 0.01), ACO (p < 0.01) and PROMs. Multivariate analysis showed that only PCO was associated with PROMs. In the ROC graph, the cut-off value of the variation range of PCO is 2.85 mm (AUC = 0.66, Youden index = 0.26). The WOMAC functional ability score of the group outside the PCO variation range of 2.85 mm significantly increased compared to the group within the range. CONCLUSION: In this study, PCO variation was significantly associated with clinical outcomes in TKA and the optimal PCO variation range was within 2.85 mm. Maintaining the PCO variation within 2.85 mm could enhance functional recovery and patient satisfaction.

Early identification and conservative treatment of postpartum hemorrhage in the lower uterine segment after vaginal delivery.

OBJECTIVE: This study examined the efficacy of pulling down the cervix and packing it in the vaginal fornix (PC-PVF) on postpartum hemorrhage in the lower uterine segment (PPH-LUS). METHODS: All cases of PPH-LUS after vaginal delivery at two tertiary hospitals between January 2019 and December 2022 were retrospectively investigated. Patients treated successfully with conservative measures were divided into routine treatment only (40 patients), routine treatment + early PC-PVF (33 patients), and routine treatment + late PC-PVF (51 patients) groups. Routine treatment consisted of uterine massage, uterotonics, and tranexamic acid administration. The therapeutic effect was evaluated by comparing the volume and rate of bleeding within 24 h after delivery. RESULTS: A total of 124 patients were treated conservatively, except for three patients who underwent laparotomy for hemostasis after PC-PVF failed for incomplete rupture of the lower uterine segment. The efficacy of treatment was 44% (40/91) for routine treatment only and 100% when combined with PC-PVF for PPH-LUS. There was no significant difference in maternal age, gestational week, neonatal weight, and Apgar score. But the total blood loss in the conventional treatment + early PC-PVF group (657.27 ml ± 131.61 ml) was significantly lower than that in the other two groups, which was 847.13 ml ± 250.37 ml(p < .01) and 1040.78 ml ± 242.70 ml (p < .01), respectively. The bleeding rate in the routine treatment + early PC-PVF group decreased significantly after tamponade. CONCLUSIONS: PC-PVF is a safe and effective treatment for PPH-LUS. Early identification of PPH-LUS and prompt application of PC-PVF can effectively reduce blood loss after vaginal delivery.

Postpartum hemorrhage is a serious threat to maternal safety and remains to be the leading cause of maternal death. At present, there is a lack of early identification and targeted conservative treatment of PPH-LUS after vaginal delivery. Innovations for the treatment of PPH-LUS are still greatly needed because, with currently available management strategies, there is still inconsistency in outcomes, increased risk of complications, and limited access in primary hospitals. Based on clinical data statistics and comparison, it is proved that PC-PVF is a simple, rapid, and noninvasive method for the treatment of PPH-LUS after vaginal delivery in this study. Because of its simple technical requirements, easily accessible materials, and low cost, PC-PVF is suitable for hospitals at all levels.

Prediction models for postoperative pulmonary complications in intensive care unit patients after noncardiac thoracic surgery.

BACKGROUND: Postoperative pulmonary complication (PPC) is a leading cause of mortality and poor outcomes in postoperative patients. No studies have enrolled intensive care unit (ICU) patients after noncardiac thoracic surgery, and effective prediction models for PPC have not been developed. This study aimed to explore the incidence and risk factors and construct prediction models for PPC in these patients. METHODS: This study retrospectively recruited patients admitted to the ICU after noncardiac thoracic surgery at West China Hospital, Sichuan University, from July 2019 to December 2022. The patients were randomly divided into a development cohort and a validation cohort at a 70% versus 30% ratio. The preoperative, intraoperative and postoperative variables during the ICU stay were compared. Univariate and multivariate logistic regression analyses were applied to identify candidate predictors, establish prediction models, and compare the accuracy of the models with that of reported risk models. RESULTS: A total of 475 ICU patients were enrolled after noncardiac thoracic surgery (median age, 58; 72% male). At least one PPC occurred in 171 patients (36.0%), and the most common PPC was pneumonia (153/475, 32.21%). PPC significantly increased the duration of mechanical ventilation (p < 0.001), length of ICU stay (p < 0.001), length of hospital stay (LOS) (p < 0.001), and rate of reintubation (p = 0.047) in ICU patients. Seven risk factors were identified, and then the prediction nomograms for PPC were constructed. At ICU admission, the area under the curve (AUC) was 0.766, with a sensitivity of 0.71 and specificity of 0.60; after extubation, the AUC was 0.841, with a sensitivity of 0.75 and specificity of 0.83. The models showed robust discrimination in both the development cohort and the validation cohort, and they were well calibrated and more accurate than reported risk models. CONCLUSIONS: ICU patients who underwent noncardiac thoracic surgery were at high risk of developing PPCs. Prediction nomograms were constructed and they were more accurate than reported risk models, with excellent sensitivity and specificity. Moreover, these findings could help assess individual PPC risk and enhance postoperative management of patients.

Automatic cardiothoracic ratio calculation based on lung fields abstracted from chest X-ray images without heart segmentation.

Introduction: The cardiothoracic ratio (CTR) based on postero-anterior chest X-rays (P-A CXR) images is one of the most commonly used cardiac measurement methods and an indicator for initially evaluating cardiac diseases. However, the hearts are not readily observable on P-A CXR images compared to the lung fields. Therefore, radiologists often manually determine the CTR's right and left heart border points of the adjacent left and right lung fields to the heart based on P-A CXR images. Meanwhile, manual CTR measurement based on the P-A CXR image requires experienced radiologists and is time-consuming and laborious. Methods: Based on the above, this article proposes a novel, fully automatic CTR calculation method based on lung fields abstracted from the P-A CXR images using convolutional neural networks (CNNs), overcoming the limitations to heart segmentation and avoiding errors in heart segmentation. First, the lung field mask images are abstracted from the P-A CXR images based on the pre-trained CNNs. Second, a novel localization method of the heart's right and left border points is proposed based on the two-dimensional projection morphology of the lung field mask images using graphics. Results: The results show that the mean distance errors at the x-axis direction of the CTR's four key points in the test sets T1 (21 × 512 × 512 static P-A CXR images) and T2 (13 × 512 × 512 dynamic P-A CXR images) based on various pre-trained CNNs are 4.1161 and 3.2116 pixels, respectively. In addition, the mean CTR errors on the test sets T1 and T2 based on four proposed models are 0.0208 and 0.0180, respectively. Discussion: Our proposed model achieves the equivalent performance of CTR calculation as the previous CardioNet model, overcomes heart segmentation, and takes less time. Therefore, our proposed method is practical and feasible and may become an effective tool for initially evaluating cardiac diseases.

Ischemic perfusion radiomics: assessing neurological impairment in acute ischemic stroke.

Introduction: Accurate neurological impairment assessment is crucial for the clinical treatment and prognosis of patients with acute ischemic stroke (AIS). However, the original perfusion parameters lack the deep information for characterizing neurological impairment, leading to difficulty in accurate assessment. Given the advantages of radiomics technology in feature representation, this technology should provide more information for characterizing neurological impairment. Therefore, with its rigorous methodology, this study offers practical implications for clinical diagnosis by exploring the role of ischemic perfusion radiomics features in assessing the degree of neurological impairment. Methods: This study employs a meticulous methodology, starting with generating perfusion parameter maps through Dynamic Susceptibility Contrast-Perfusion Weighted Imaging (DSC-PWI) and determining ischemic regions based on these maps and a set threshold. Radiomics features are then extracted from the ischemic regions, and the t-test and least absolute shrinkage and selection operator (Lasso) algorithms are used to select the relevant features. Finally, the selected radiomics features and machine learning techniques are used to assess the degree of neurological impairment in AIS patients. Results: The results show that the proposed method outperforms the original perfusion parameters, radiomics features of the infarct and hypoxic regions, and their combinations, achieving an accuracy of 0.926, sensitivity of 0.923, specificity of 0.929, PPV of 0.923, NPV of 0.929, and AUC of 0.923, respectively. Conclusion: The proposed method effectively assesses the degree of neurological impairment in AIS patients, providing an objective auxiliary assessment tool for clinical diagnosis.

Consensus for antifungal stewardship in China (2024 edition).

Background: Invasive fungal disease (IFD) has become a serious threat to human health in China and around the world, with high mortality and morbidity. Currently, the misdiagnosis rate of IFD is extremely high, compounded with the low quality of prescription antifungals and the high incidence of adverse events associated with IFD treatment, resulting in lengthy hospitalization, low clinical response, and high disease burden, which have become serious challenges in clinical practice. Antifungal stewardship (AFS) can not only significantly increase the early diagnosis rate of IFD, reduce inappropriate utilization of antifungal drugs, improve patient prognosis, but can also improve therapeutic safety and reduce healthcare expenses. Thus, it is urgent to identify key AFS metrics suitable for China's current situation. Methods: Based on metrics recommended by international AFS consensuses, combined with the current situation of China and the clinical experience of authoritative experts in various fields, several metrics were selected, and experts in the fields of respiratory diseases, hematology, intensive care units (ICUs), dermatology, infectious diseases, microbiology laboratory and pharmacy were invited to assess AFS metrics by the Delphi method. Consensus was considered to be reached with an agreement level of ≥80% for the metric. Results: Consensus was reached for 24 metrics, including right patient metrics (n=4), right time metrics (n=3), and right use metrics (n=17). Right use metrics were further subdivided into drug choice (n=8), drug dosage (n=4), drug de-escalation (n=1), drug duration (n=2), and drug consumption (n=2) metrics. Forty-six authoritative experts assessed and reviewed the above metrics, and a consensus was reached with a final agreement level of ≥80% for 22 metrics. Conclusions: This consensus is the first to propose a set of AFS metrics suitable for China, which helps to establish AFS standards in China and is also the first AFS consensus in Asia, and may improve the standard of clinical diagnosis and treatment of IFD, and guide hospitals to implement AFS, ultimately promoting the rational use of antifungal drugs and improving patient prognosis.

Exploring deep learning strategies for intervertebral disc herniation detection on veterinary MRI.

Intervertebral Disc Herniation (IVDH) is a common spinal disease in dogs, significantly impacting their health, mobility, and overall well-being. This study initiates an effort to automate the detection and localization of IVDH lesions in veterinary MRI scans, utilizing advanced artificial intelligence (AI) methods. A comprehensive canine IVDH dataset, comprising T2-weighted sagittal MRI images from 213 pet dogs of various breeds, ages, and sizes, was compiled and utilized to train and test the IVDH detection models. The experimental results showed that traditional two-stage detection models reliably outperformed one-stage models, including the recent You Only Look Once X (YOLOX) detector. In terms of methodology, this study introduced a novel spinal localization module, successfully integrated into different object detection models to enhance IVDH detection, achieving an average precision (AP) of up to 75.32%. Additionally, transfer learning was explored to adapt the IVDH detection model for a smaller feline dataset. Overall, this study provides insights into advancing AI for veterinary care, identifying challenges and exploring potential strategies for future development in veterinary radiology.

TBN as Organic Redox Cocatalyst for Oxidative Tiffeneau-Demjanov-Type Rearrangement Using O2 as Sole Oxidant.

The Tiffeneau-Demjanov-type rearrangement is a ring-expansion reaction involving the cationic rearrangement of cyclic alcohols. The carbocation intermediates can be generated in situ via various means, including Wacker oxidation. In near recent reports on the reinvestiagtions by Wahl et al. (Sietmann, J.; Tenberge, M.; Wahl, J. M. Wacker Oxidation of Methylenecyclobutanes: Scope and Selectivity in an Unusual Setting. Angew. Chem., Int. Ed. 2023, 62, e202215381) and Zhu et al. (Feng, Q.; Wang, Q.; Zhu, J.-P. Oxidative Rearrangement of 1,1-Disubstituted Alkenes to Ketones. Science 2023, 379, 1363-1368), stoichiometric oxidants were involved. In this work, we report the Tiffeneau-Demjanov-type rearrangement can be smoothly promoted by the Pd-TBN cocatalyzed aerobic Wacker oxidation using molecular oxygen as the sole oxidant. tert-Butanol is essential for achieving high yields. Since the first report by Grigg et al. in 1977 (Boontanonda, P.; Grigg, R. J. Palladium (II)-Catalysed Ring Expansion of Methylenecyclobutanes and Related Systems. J. Chem. Soc. Chem. Commun. 1977, 17, 583-584), the five-decade journey of Pd-catalyzed Tiffeneau-Demjanov-type rearrangement returns to the aerobic again.

Blood Urine Nitrogen Trajectories of Acute Pancreatitis Patients in Intensive Care Units.

Objective: To identify subclasses of acute pancreatitis (AP) patients in the intensive care unit (ICU) by analyzing blood urea nitrogen (BUN) trajectories. Methods: AP patients in West China Hospital System (development cohort) and three public databases in the United States (validation cohort) were included. Latent class trajectory modelling was used to identify subclasses based on BUN trajectories within the first 21 days after ICU admission. Clinical characteristics and outcomes were compared, and results were externally validated. Results: The study comprised 2971 and 930 patients in the development and validation cohorts, respectively, with five subclasses: Class 1 ("Moderate-azotemia, slow decreasing"), Class 2 ("Non-azotemia"), Class 3 ("Severe-azotemia, slow decreasing"), Class 4 ("Moderate-azotemia, rapid increasing"), and Class 5 ('Moderate-azotemia, slow increasing) identified. Azotemia patients showed significantly higher 30-day mortality risk in development and validation cohorts. Specifically, Class 4 patients exhibited notably highest mortality risk in both the development cohort (HR 5.32, 95% CI 2.62-10.82) and validation cohort (HR 6.23, 95% CI 2.93-13.22). Regarding clinical characteristics, AP patients in Class 4 showed lower mean arterial pressure and a higher proportion of renal disease. We also created an online early classification model to further identify Class 4 patients among all patients with moderate azotemia at baseline. Conclusion: This multinational study uncovers heterogeneity in BUN trajectories among AP patients. Patients with "Moderate-azotemia, rapid increasing" trajectory, had a higher mortality risk than patients with severe azotemia at baseline. This finding complements studies that solely rely on baseline BUN for risk stratification and enhanced our understanding of longitudinal progression of AP.

Synthesis Enabled by E-to-Z Isomerization Using CBZ6 as Energy Transfer Photocatalyst.

The reactions of Z-isomers and E-isomers usually are different in consideration of the regioselectivity of chemoselectivity. The syntheses of Z-isomers are not feasible in many cases. The energy transfer (EnT) E/Z-photoisomerization might yield the Z-isomers. In this work, CBZ6 was proven to be an EnT photocatalyst for the E → Z-isomerization of C-C or C-N double bonds. The transformations of in situ generated Z-isomers of oximes and stilbenes consequently afforded the desired reversed Beckmann rearrangement products and phenanthrenes, respectively.

Development of the near-infrared fluorescence probe for detection of ONOO- and its application in vitro and vivo.

Diabetes has become one of the most common endocrine and metabolic diseases threatening human health, which can induce mitochondrial dysfunction and exacerbate the excessive production of reactive oxygen species (ROS). Among them, ONOO- level fluctuation was closely related to diabetes. Hence, it is of great significance to develop a near-infrared fluorescence probe for visualizing ONOO- level fluctuations in diabetes. In this paper, we constructed a fluorescence probe YBL with dicyano-isophorone derivative as fluorophore and diphenyl phosphate as ONOO- response site, which can detect ONOO- with the low detection limit (39.8 nM) and exhibit excellent selectivity and sensitivity. The probe YBL has been applied to monitor intracellular ONOO- level fluctuations. Meanwhile, the image results showed that high sugar promoted the increase of ONOO- level in cells. More important, the probe YBL can be used for imaging in mice, and the results showed that content of ONOO- was increased in diabetic mice. Therefore, the probe YBL provided a tool for understanding diabetes progression by imaging ONOO-.

Topic Modeling Analysis of Chinese Medicine Literature on Gastroesophageal Reflux Disease: Insights into Potential Treatment.

OBJECTIVE: To analyze Chinese medicine (CM) prescriptions for gastroesophageal reflux disease (GERD), we model topics on GERD-related classical CM literature, providing insights into the potential treatment. METHODS: Clinical guidelines were used to identify symptom terms for GERD, and CM literature from the database "Imedbooks" was retrieved for related prescriptions and their corresponding sources, indications, and other information. BERTopic was applied to identify the main topics and visualize the data. RESULTS: A total of 36,207 entries are queried and 1,938 valid entries were acquired after manually filtering. Eight topics were identified by BERTopic, including digestion function abate, stomach flu, respiratory-related symptoms, gastric dysfunction, regurgitation and gastrointestinal dysfunction in pediatric patients, vomiting, stroke and alcohol accumulation are associated with the risk of GERD, vomiting and its causes, regurgitation, epigastric pain, and symptoms of heartburn. CONCLUSIONS: Topic modeling provides an unbiased analysis of classical CM literature on GERD in a time-efficient and scale-efficient manner. Based on this analysis, we present a range of treatment options for relieving symptoms, including herbal remedies and non-pharmacological interventions such as acupuncture and dietary therapy.

Loop technique for anterior cruciate ligament reconstruction combined with anterolateral structure reinforcement: technical description and clinical results.

PURPOSE: We describe a surgical technique for ACL reconstruction combined with anterolateral structure reinforcement and report early clinical follow-up results. METHODS: The semitendinosus and gracilis tendons are braided into 5 strands and the ACL femoral tunnel and tibial tunnel are created. The graft is passed through the tunnel with the use of a traction suture and the tibial end is fixed with absorbable interference screws at 30° of knee flexion. The ACL graft traction suture is used as an anterolateral reconstruction structure to pass through the proximal exit of the ACL femoral tunnel and then through the depth of the iliotibial bundle to the anterior to Gerdy's tubercle, a bony tunnel is created from the anterior to Gerdy's tubercle to the goose foot, and the traction suture is passed through this bony tunnel to form a Loop structure at 20° of knee flexion. Between March 2021 and May 2022 IKDC score, Lysholm score, and Tegner score were performed preoperatively and 6-12 months postoperatively in 24 consecutive patients who met the indications for this procedure and underwent surgery. The patient's maximum flexion angle, the circumference of the thigh, and the stress X-ray between the operated and healthy knee were measured. RESULTS: Patients showed significant improvement in IKDC score, Lysholm score and Tegner score at a mean follow-up of 7 months postoperatively compared to preoperatively. No significant increase in anterior tibial displacement was found between the patient's operated side and the healthy side. CONCLUSION: The Loop technique ACLR combined with ALSA can be used in patients with an ACL tear combined with a high degree of positive pivot shift. The patient's subjective perception was significantly improved from the preoperative period and knee stability was restored. LEVEL OF EVIDENCE: IV, therapeutic study.

A fluorescence probe with targeted mitochondria for detecting hydrogen peroxide in vitro and in diabetic mice.

We designed and prepared probe W-1 for the detection of H2O2. W-1 showed excellent selectivity for H2O2 and was accompanied by colorimetric signal changes. The excellent linear relationship between fluorescence intensity and H2O2 concentration (0-100 µM) provided favorable conditions for its quantitative detection. In addition, the combination of portable test strips with a smartphone platform provided great convenience for on-site visual detection of H2O2. Moreover, W-1 possessed targeting mitochondria property and could be applied to image the exogenous and endogenous H2O2 in cells to distinguish normal cells and cancer cells. Lastly, W-1 was used for monitoring the H2O2 fluctuation of the diabetic process in mice, and the results showed an increase in H2O2 levels in diabetes. Therefore, the probe provided a tool for understanding the pathological and physiological mechanisms of diabetes by imaging H2O2.