A phase III randomized clinical trial comparing laparoscopic radical hysterectomy based on open state with abdominal radical hysterectomy in patients with early-stage cervical cancer.

BACKGROUND: Cervical cancer is the fourth most frequently diagnosed cancer and the fourth leading cause of cancer death in women, The standard treatment recommendation for women with early cervical cancer is radical hysterectomy with pelvic lymph node dissection, however, articles published in recent years have concluded that the treatment outcome of laparoscopic surgery for cervical cancer is inferior to that of open surgery. Thus, we choose a surgically new approach; the laparoscopic cervical cancer surgery in the open state is compared with the traditional open cervical cancer surgery, and we hope that patients can still have a good tumor outcome and survival outcome. This trial will investigate the effectiveness of laparoscopic cervical cancer surgery in the open-state treatment of early-stage cervical cancer. METHOD AND DESIGN: This will be an open-label, 2-armed, randomized, phase-III single-center trial of comparing laparoscopic radical hysterectomy based on open state with abdominal radical hysterectomy in patients with early-stage cervical cancer. A total of 740 participants will be randomly assigned into 2 treatment arms in a 1:1 ratio. Clinical, laboratory, ultrasound, and radiology data will be collected at baseline, and then at the study assessments and procedures performed at baseline and 1 week, 6 weeks, and 3 months, and follow-up visits begin at 3 months following surgery and continue every 3 months thereafter for the first 2 years and every 6 months until year 4.5. The primary aim is the rate of disease-free survival at 4.5 years. The secondary aims include treatment-related morbidity, costs and cost-effectiveness, patterns of recurrence, quality of life, pelvic floor function, and overall survival. CONCLUSIONS: This prospective trial aims to show the equivalence of the laparoscopic cervical cancer surgery in the open state versus the transabdominal radical hysterectomy approach for patients with early-stage cervical cancer following a 2-phase protocol. TRIAL REGISTRATION: ChiCTR2300075118. Registered on August 25, 2023.

Novel GNAI3 mutation in a Chinese family with auriculocondylar syndrome and treatment of severe dentofacial deformities: a 5-year follow-up case report.

BACKGROUND: Auriculocondylar syndrome (ARCND) is an extremely rare autosomal dominant or recessive condition that typically manifests as question mark ears (QMEs), mandibular condyle hypoplasia, and micrognathia. Severe dental and maxillofacial malformations present considerable challenges in patients' lives and clinical treatment. Currently, only a few ARCND cases have been reported worldwide, but most of them are related to genetic mutations, clinical symptoms, and ear correction; there are few reports concerning the treatment of dentofacial deformities. CASE PRESENTATION: Here, we report a rare case of ARCND in a Chinese family. A novel insertional mutation in the guanine nucleotide-binding protein alpha-inhibiting activity polypeptide 3 (GNAI3) was identified in the patient and their brother using whole-exome sequencing. After a multidisciplinary consultation and examination, sequential orthodontic treatment and craniofacial surgery, including distraction osteogenesis and orthognathic surgery, were performed using three-dimensional (3D) digital technology to treat the patient's dentofacial deformity. A good prognosis was achieved at the 5-year follow-up, and the patient returned to normal life. CONCLUSIONS: ARCND is a monogenic and rare condition that can be diagnosed based on its clinical triad of core features. Molecular diagnosis plays a crucial role in the diagnosis of patients with inconspicuous clinical features. We present a novel insertion variation in GNAI3, which was identified in exon 2 of chromosome 110116384 in a Chinese family. Sequential therapy with preoperative orthodontic treatment combined with distraction osteogenesis and orthognathic surgery guided by 3D digital technology may be a practical and effective method for treating ARCND.

FP-Zernike: An Open-source Structural Database Construction Toolkit for Fast Structure Retrieval.

The release of AlphaFold2 has sparked a rapid expansion in protein model databases. Efficient protein structure retrieval is crucial for the analysis of structure models, while measuring the similarity between structures is the key challenge in structural retrieval. Although existing structure alignment algorithms can address this challenge, they are often time-consuming. Currently, the state-of-the-art approach involves converting protein structures into three-dimensional (3D) Zernike descriptors and assessing similarity using Euclidean distance. However, the methods for computing 3D Zernike descriptors mainly rely on structural surfaces and are predominantly web-based, thus limiting their application in studying custom datasets. To overcome this limitation, we developed FP-Zernike, a user-friendly toolkit for computing different types of Zernike descriptors based on feature points. Users simply need to enter a single line of command to calculate the Zernike descriptors of all structures in customized datasets. FP-Zernike outperforms the leading method in terms of retrieval accuracy and binary classification accuracy across diverse benchmark datasets. In addition, we showed the application of FP-Zernike in the construction of the descriptor database and the protocol used for the Protein Data Bank (PDB) dataset to facilitate the local deployment of this tool for interested readers. Our demonstration contained 590,685 structures, and at this scale, our system required only 4-9 s to complete a retrieval. The experiments confirmed that it achieved the state-of-the-art accuracy level. FP-Zernike is an open-source toolkit, with the source code and related data accessible at https://ngdc.cncb.ac.cn/biocode/tools/BT007365/releases/0.1, as well as through a webserver at http://www.structbioinfo.cn/.

Impact of comprehensive air pollution control policies on six criteria air pollutants and acute myocardial infarction morbidity, Weifang, China: A quasi-experimental study.

Comprehensive air pollution control policies may reduce pollutant emissions. However, the impact on disease morbidity of the change for the concentration of air pollutants following the policies has been insufficiently studied. We aim to assess the impact of comprehensive air pollution control policies on the levels of six criteria air pollutants and acute myocardial infarction (AMI) morbidity in Weifang, China. This study performed an interrupted time series analysis. The linear model with spline terms and generalized additive quasi-Poisson model were used to estimate the immediate change from 2016 to 2019 in the daily concentration of six air pollutants (PM2.5, PM10, SO2, NO2, O3, and, CO) and AMI incident cases (Age ≥35) associated with the implementation of air pollution control policies in Weifang, respectively. After the implementation of air pollution control policies, air quality in Weifang had been improved. Specifically, the daily concentrations of PM2.5, PM10, SO2, and, CO immediately decreased by 27.9 % (95 % CI: 6.6 % to 44.3 %), 32.9 % (95 % CI: 17.5 % to 45.5 %), 14.6 % (95 % CI: 0.4 % to 26.8 %), and 33.9 % (95 % CI: 22.0 % to 44.0 %), respectively. In addition, the policies implementation was also associate with the immediate decline in the AMI morbidity (-6.5 %, 95 % CI: -10.4 % to -2.3 %). And subgroup analyses indicate that the health effects of the policy intervention were only observed in female (-9.4 %, 95 % CI: -14.4 % to -4.2 %) and those aged ≥65 years (-10.5 %, 95 % CI: -14.6 % to -6.2 %). During the final 20 months of the study period, the policy intervention was estimated to prevent 1603 (95 % CI: 574 to 2587) cases of incident AMI in Weifang. Our results provide strong rationale that the policy intervention significantly reduced ambient pollutant concentrations and AMI morbidity, which highlighted the importance for a comprehensive and rigorous air pollution control policy in regions with severe air pollution.

Treatment Patterns and Healthcare Resource Utilization of Patients With Paroxysmal Nocturnal Hemoglobinuria: A Retrospective Claims Data Analysis.

Paroxysmal nocturnal hemoglobinuria (PNH) is a rare, acquired hematologic disorder commonly treated with complement inhibitors such as eculizumab, ravulizumab, and pegcetacoplan. This study aims to describe treatment patterns, healthcare resource utilization, and cost for newly diagnosed PNH patients in 2 large, health insurance claims databases: MarketScan and Optum. Among the 271 patients meeting the inclusion criteria in MarketScan, 57.9% were female, and the average age was 46.6 years. Among these newly diagnosed patients, 25.1% (n = 68) of patients received a PNH-specific pharmacologic treatment, and the average time from diagnosis to treatment was 4.7 months. The medication possession ratio was 97.0%, but discontinuation was common (58.8%). The average per-patient-per-month costs were $18,978, driven by pharmacy and infusion ($11,182), outpatient ($4086), and inpatient ($3318) costs. Despite the availability of multiple treatments, 39.9% of patients had an inpatient stay, and 50.9% had an emergency department visit. Better care management and the introduction of new treatment options are needed to address delays between diagnosis and treatment, and high rates of hospitalization and emergency department use among patients with PNH.

In-bag extraction of tissue through an incision in the posterior vaginal wall in laparoscopic myomectomy: a large retrospective study.

BACKGROUND: Our purpose was to describe the outcomes of transvaginal in-bag tissue extraction tissue through an incision in the posterior vaginal wall the middle part incision of posterior vagina in laparoscopic myomectomy. METHODS: This was a retrospective study of patients who received laparoscopic myomectomy and in-bag tissue extraction through an incision in the posterior vaginal wall between January 2016 and December 2022. Patient characteristics, intra- and post-operative complications, and outcomes were collected and analyzed. RESULTS: A total of 511women were included in the analysis. The mean largest myoma diameter was 8.44 ± 3.56 cm; mean specimen weight was 789.23 ± 276.97 g; mean operative time was 129.01 ± 53.13minutes; and mean blood loss was 175.99 ± 210.96 mL. Within 30-days of surgery, no fever, infection, or vaginal bleeding was noted in any patient, and the vaginal incisions of all patients had healed well. There were no incisional hernias, pelvic infections, and vaginal adhesions noted at follow-up 3 months after the operation. There were 37 cases of vaginal delivery of the patients after surgery, and there were no lacerations of the posterior wall vaginal incision. CONCLUSIONS: Transvaginal in-bag extraction though an incision in the posterior vaginal wall is feasible and safe for removing tissue after laparoscopic myomectomy.

Core characteristics of sublingual veins analysis and its relationship with hypertension.

BACKGROUND: The sublingual vein (SV) is a specialized diagnostic method used in Traditional Chinese Medicine (TCM). Despite its ability to objectively reflect blood flow, SV is often overlooked in clinical practice. OBJECTIVE: This study aims to analyze the core characteristics of SV and investigate the in-depth relationship between its digital characteristics and hypertension. The goal is to find a link between SV and hypertension and break out of the current situation. METHODS: Modern digital analysis techniques were applied to the traditional SV diagnostic theory. In a controlled study with 204 participants, the digital characteristics of SV were documented using TFDA-1, and its color value was analyzed using TDAS. Morphological characteristics of SV, such as trunklength, width, and tortuosity, were examined by combining computer vision with expert interpretation. This involved the application of automatic ranging methods and a rectangular approximation algorithm, which are novel approaches in the field of TCM. The t-test and Mann-Whitney U test were used to analyze the digital characteristics of SV in hypertension. Binary logistic regression and neural network models were established using machine learning to explore the deep relationship between SV characteristics and hypertension. RESULTS: There was a significant difference of the tortuosity of SV between the two groups (Z=-2.629, p= 0.009). The results revealed thick width of SV (OR = 2.64, 95% CI: 1.02-6.79) was the risk factor for hypertension. Addition of SV characteristics improved overall percent correct for hypertension prediction to 80%. CONCLUSION: TCM method of diagnosis of SV has been greatly expanded in terms of technical means, and the close relationship between SV and hypertension has been found in clinical data.

Machine learning prediction models for different stages of non-small cell lung cancer based on tongue and tumor marker: a pilot study.

OBJECTIVE: To analyze the tongue feature of NSCLC at different stages, as well as the correlation between tongue feature and tumor marker, and investigate the feasibility of establishing prediction models for NSCLC at different stages based on tongue feature and tumor marker. METHODS: Tongue images were collected from non-advanced NSCLC patients (n = 109) and advanced NSCLC patients (n = 110), analyzed the tongue images to obtain tongue feature, and analyzed the correlation between tongue feature and tumor marker in different stages of NSCLC. On this basis, six classifiers, decision tree, logistic regression, SVM, random forest, naive bayes, and neural network, were used to establish prediction models for different stages of NSCLC based on tongue feature and tumor marker. RESULTS: There were statistically significant differences in tongue feature between the non-advanced and advanced NSCLC groups. In the advanced NSCLC group, the number of indexes with statistically significant correlations between tongue feature and tumor marker was significantly higher than in the non-advanced NSCLC group, and the correlations were stronger. Support Vector Machine (SVM), decision tree, and logistic regression among the machine learning methods performed poorly in models with different stages of NSCLC. Neural network, random forest and naive bayes had better classification efficiency for the data set of tongue feature and tumor marker and baseline. The models' classification accuracies were 0.767 ± 0.081, 0.718 ± 0.062, and 0.688 ± 0.070, respectively, and the AUCs were 0.793 ± 0.086, 0.779 ± 0.075, and 0.771 ± 0.072, respectively. CONCLUSIONS: There were statistically significant differences in tongue feature between different stages of NSCLC, with advanced NSCLC tongue feature being more closely correlated with tumor marker. Due to the limited information, single data sources including baseline, tongue feature, and tumor marker cannot be used to identify the different stages of NSCLC in this pilot study. In addition to the logistic regression method, other machine learning methods, based on tumor marker and baseline data sets, can effectively improve the differential diagnosis efficiency of different stages of NSCLC by adding tongue image data, which requires further verification based on large sample studies in the future.

Effect of a two-phase tobacco control regulation on incidence from ischemic stroke and hemorrhagic stroke, Shenzhen, China, 2007-2016.

INTRODUCTION: The Shenzhen government is widely considered to be most efficiently implementing smoke-free legislation in China. We evaluated and compared the impact of Shenzhen's two-phase smoke-free regulation on the incidence rates for ischemic and hemorrhagic stroke. METHODS: An interrupted time series design was used to capture immediate and annual incidence changes from 2007 to 2016 for both ischemic and hemorrhagic stroke due to two-phase smoke-free regulation in Shenzhen, China, by using a generalized additive model. The first phase, implemented on 9 March 2010, required five main public places to be smoke-free. In the second phase, the comprehensive law was expanded to the whole city on 1 March 2014. RESULTS: The regulation implementation during phase I was associated with a strong immediate decline in the incidence rate of ischemic stroke (-14.2%, 95% CI: -19.6 - -8.4) and hemorrhagic stroke (-10.1%, 95% CI: -18.2 - -1.2), but without showing the annual changes (p>0.05). Following the implementation of the comprehensive law, the gradual annual effect showed a significant change in ischemic stroke, with a 6.3% (95% CI: 8.9 - -3.6) reduction. Neither the immediate nor gradual decreases in hemorrhagic stroke incidences associated with the comprehensive regulation were statistically significant during phase II (p>0.05). Subgroup analyses indicate that a much larger health effect of the regulation during phase I was greater among those aged ≥65 years than among those aged 35-64 years. CONCLUSIONS: Shenzhen's two-phase smoke-free regulation was well implemented. Even though the regulation did not extend to the whole city, the immediate health benefits on the incidence rates of ischemic stroke and hemorrhagic stroke could be seen. However, the health benefits brought by the implementation of comprehensive smoke-free legislation were attenuated by previous smoke-free regulations in five main public places, which were more evident in hemorrhagic stroke.

Relationship chains of subhealth physical examination indicators: a cross-sectional study using the PLS-SEM approach.

Subhealth is a transitional state between health and disease, and it can be detected through routine physical check-ups. However, the complexity and diversity of physical examination items and the difficulty of quantifying subhealth manifestations are the main problems that hinder its treatment. The aim of this study was to systematically investigate the physical examination performance of the subhealthy population and further explore the deeper relationships between indicators. Indicators were obtained for 878 subjects, including basic information, Western medicine indicators, inquiries of traditional Chinese medicine and sublingual vein (SV) characteristics. Statistical differences were analysed using R software. To explore the distribution of symptoms and symptom clusters in subhealth, partial least squares-structural equation modelling (PLS-SEM) was applied to the subhealth physical examination index, and a structural model was developed to verify whether the relationship chain between the latent variables was reasonable. Finally, the reliability and validity of the PLS-SE model were assessed. The most common subclinical clinical symptoms were limb soreness (37.6%), fatigue (31.6%), shoulder and neck pain (30.5%) and dry eyes (29.2%). The redness of the SV in the subhealthy group was paler than that in the healthy group (p < 0.001). This study validates the establishment of the directed acyclic relationship chain in the subhealthy group: the path from routine blood tests to lipid metabolism (t = 7.878, p < 0.001), the path from lipid metabolism to obesity (t = 8.410, p < 0.001), the path from obesity to SV characteristics (t = 2.237, p = 0.025), and the path from liver function to SV characteristics (t = 2.215, p = 0.027). The innovative application of PLS-SEM to the study of subhealth has revealed the existence of a chain of relationships between physical examination indicators, which will provide a basis for further exploration of subhealth mechanisms and causal inference. This study has identified the typical symptoms of subhealth, and their early management will help to advance the treatment of diseases.

A lung cancer risk warning model based on tongue images.

Objective: To investigate the tongue image features of patients with lung cancer and benign pulmonary nodules and to construct a lung cancer risk warning model using machine learning methods. Methods: From July 2020 to March 2022, we collected 862 participants including 263 patients with lung cancer, 292 patients with benign pulmonary nodules, and 307 healthy subjects. The TFDA-1 digital tongue diagnosis instrument was used to capture tongue images, using feature extraction technology to obtain the index of the tongue images. The statistical characteristics and correlations of the tongue index were analyzed, and six machine learning algorithms were used to build prediction models of lung cancer based on different data sets. Results: Patients with benign pulmonary nodules had different statistical characteristics and correlations of tongue image data than patients with lung cancer. Among the models based on tongue image data, the random forest prediction model performed the best, with a model accuracy of 0.679 ± 0.048 and an AUC of 0.752 ± 0.051. The accuracy for the logistic regression, decision tree, SVM, random forest, neural network, and naïve bayes models based on both the baseline and tongue image data were 0.760 ± 0.021, 0.764 ± 0.043, 0.774 ± 0.029, 0.770 ± 0.050, 0.762 ± 0.059, and 0.709 ± 0.052, respectively, while the corresponding AUCs were 0.808 ± 0.031, 0.764 ± 0.033, 0.755 ± 0.027, 0.804 ± 0.029, 0.777 ± 0.044, and 0.795 ± 0.039, respectively. Conclusion: The tongue diagnosis data under the guidance of traditional Chinese medicine diagnostic theory was useful. The performance of models built on tongue image and baseline data was superior to that of the models built using only the tongue image data or the baseline data. Adding objective tongue image data to baseline data can significantly improve the efficacy of lung cancer prediction models.

A new model for predicting the occurrence of polycystic ovary syndrome: Based on data of tongue and pulse.

Background and objective: Polycystic ovary syndrome is one of the most common types of endocrine and metabolic diseases in women of reproductive age that needs to be screened early and assessed non-invasively. The objective of the current study was to develop prediction models for polycystic ovary syndrome based on data of tongue and pulse using machine learning techniques. Methods: A dataset of 285 polycystic ovary syndrome patients and 201 healthy women were investigated to identify the significant tongue and pulse parameters for predicting polycystic ovary syndrome. In this study, feature selection was performed using least absolute shrinkage and selection operator regression. Several machine learning algorithms (multilayer perceptron classifier, eXtreme gradient boosting classifier, and support vector machine) were used to construct the classification models to predict the presence of polycystic ovary syndrome. Results: TB-L, TB-a, TB-b, TC-L, TC-a, h3, and h4/h1 in tongue and pulse parameters were statistically associated with polycystic ovary syndrome presence. Among the several machine learning techniques, the support vector machine model was optimal for the comprehensive evaluation of this dataset and deduced the area under the receiver operating characteristic curve, DeLong test, calibration curve, and decision curve analysis. Conclusion: The machine learning model with tongue and pulse factors can predict the existence of polycystic ovary syndrome precisely.

LncRNA GSCAR promotes glioma stem cell maintenance via stabilizing SOX2 expression.

Gliomas are the most aggressive type of malignant brain tumors. Recent studies have demonstrated that the existence of glioma stem cells (GSCs) is critical for glioma recurrence, metastasis, and chemo- or radio-therapy resistance. Temozolomide (TMZ) has been used as an initial therapy for gliomas. However, the overall survival time is still limiting due to the lack of effective targets and treatment options. Therefore, identifying novel biomarkers for gliomas, especially for GSCs, is important to improve the clinical outcome in the future. In this study, we identify a human-specific long non-coding RNA (lncRNA, ENSG00000250377), termed GSCAR (glioma stem cell associated lncRNA), which is highly expressed in glioma cancerous tissues and cell lines. We reveal that GSCAR positively correlates with tumor grade. Glioma patients with GSCAR high expression exhibit shortened overall survival time, compared to patients with GSCAR low expression. Furthermore, we show that GSCAR knockdown by shRNAs or antisense oligonucleotide (ASO) reduces tumor cell proliferation, migration and xenograft tumor formation abilities. Mechanistic study shows that GSCAR acts as a ceRNA (competing endogenous RNA) for miR-6760-5p to promote the expression of oncogene SRSF1 (serine and arginine rich splicing factor 1). In addition, GSCAR mediates the protein complex formation between DHX9 (DExH-Box helicase 9) and IGF2BP2 (insulin-like growth factor 2 mRNA-binding protein 2), leading to the stabilization of SOX2 (sex-determining region Y-box 2) mRNA and then the transcriptional activation of GSCAR. Depleting GSCAR reduces SOX2 expression and GSC self-renewal ability, but promotes tumor cell responses to TMZ. These findings uncover that GSCAR/miR-6760-5p/SRSF1 axis and GSCAR/DHX9-IGF2BP2/SOX2 positive feedback loop are critical for glioma progression, which could be used as prognostic biomarkers and therapeutic targets in the future.

Generation of Oxygen Vacancies in Metal-Organic Framework-Derived One-Dimensional Ni0.4Fe2.6O4 Nanorice Heterojunctions for ppb-Level Diethylamine Gas Sensing.

Metal-organic frameworks (MOFs) are ideal sensing materials due to their distinctive morphologies, high surface area, and simple calcination to remove sacrificial MOF scaffolds. Oxygen vacancies (Ovs) can be efficiently generated by the thermal annealing of metal oxides in an inert atmosphere. Herein, MIL-53-based Fe and Fe/Ni-MOFs nanorices (NRs) were first prepared by using a solvothermal method, and then one-dimensional (1D) Fe2O3 and Ni0.4Fe2.6O4 NRs were derived from the MOFs after calcination at 350 °C in an air and argon (Ar) atmosphere, respectively. It was found that Ar-annealed Ni0.4Fe2.6O4 NRs have higher Ovs concentrations (82.11%) and smaller NRs (24.3 nm) than air-annealed NRs (65.68% & 31.5 nm). Beneficially, among the synthesized NRs, the Ar-Ni0.4Fe2.6O4 NRs show a higher sensitivity to diethylamine (DEA) (Ra/Rg = 23 @ 5 ppm, 175 °C), low detection limit (Ra/Rg = 1.2 @ 200 ppb), wide dynamic response (Ra/Rg = 93.5@ 30 ppm), high stability (30 days), and faster response/recovery time (4 s/38 s). Moreover, the 1D nanostructure containing heterostructures offers excellent sensing selectivity and a wide detection range from 200 ppb to 30 ppm in the presence of DEA. The outstanding gas sensing behavior can be attributable to synergistic impact, structural advantages, high concentration of Ovs, and the heterojunction interface, which can have profound effects on gas sensor performance. This study provides a unique technique for constructing high-performance gas sensors for ppb-level DEA detection and the formation of Ovs in metal oxides without the need for any additives.

A digital workflow to predict facial aesthetics in patients with maxillofacial trauma with implant retained prostheses.

Purpose To introduce a digital workflow for the prediction of facial aesthetics, especially in patients with dentation deformity caused by maxillofacial trauma.Methods Cone-beam computed tomography (CBCT) and three-dimensional facial scans of patients with radiographic prostheses were collected. The aforementioned data were uploaded to ProPlan CMF software and merged to generate a virtual patient with craniofacial hard tissue, realistic facial soft tissue, and remaining dentition. The radiographic prostheses were scanned to form a digital cast, which was fitted with its CBCT image to create the virtual prostheses. Postoperative facial soft tissue was simulated according to the movement of the virtual prostheses. An appropriate virtual diagnostic prosthesis plan was selected by the patient and dentist. Subsequently, prosthetically driven implant guide and restoration were designed and fabricated.Conclusions A virtual patient was successfully constructed. A 4-mm protrusion of the virtual prosthesis was chosen. Subsequently, implant surgery was performed, and dental prostheses were fabricated based on this location. The fusion of the postoperative facial scan and preoperative facial prediction was found to be coincident. This technique can effectively predict facial aesthetic features of patients with maxillofacial trauma, facilitate communication with patients, reduce chairside time, and guide the multidisciplinary design of implant placement and restoration fabrication.

miR-141-3p Promotes the Cisplatin Sensitivity of Osteosarcoma Cell through Targeting the Glutaminase [GLS]-Mediated Glutamine Metabolism.

AIMS: This study aimed to evaluate the roles and molecular targets of miRNA-141-3p in the cisplatin sensitivity of osteosarcoma. BACKGROUND: Osteosarcoma is one of the most common-type bone tumors, occurring mainly in children and adolescents. Cancer cells display dysregulated cellular metabolism, such as the abnormally elevated glutamine metabolism. OBJECTIVE: Non-coding RNA miRNA-141-3p has been reported to act as a tumor suppressor in osteosarcoma. Currently, the precise molecular mechanisms for the miR- 141-3p-mediated chemosensitivity through regulating glutamine metabolism remain unclear. METHODS: We collected thirty paired OS tumors and their adjacent normal tissues. The osteosarcoma cell lines [Saos-2] and normal osteoblast cells, hFOB1.19, were used for in vitro experiments. RT-qPCR and Western blot were applied for gene expression detections. Targets of miR-141-3p were predicted from starBase. The MTT and flow cytometric assays were performed to determine cell growth and apoptosis rates. The cellular glutamine metabolism was monitored by glutamine uptake assay and the glutaminase [GLS] activity assay. RESULTS: We reported that miR-141-3p were significantly downregulated in osteosarcoma tissues and cells. Overexpression of miR-141-3p suppressed OS cell growth and sensitized OS cells to cisplatin. In addition, glutamine metabolism was significantly increased in osteosarcoma. We characterized that GLS played oncogenic roles in osteosarcoma and validated GLS was a direct target of miR-141-3p in OS cells. Rescue experiments consistently demonstrated that miR-141-3p-promoted cisplatin sensitivity was achieved by targeting GLS directly. CONCLUSION: Overall, our findings revealed new molecular mechanisms of the miR-141- 3p-modulated cisplatin sensitization through targeting the GLS-glutamine metabolism pathway. This study will contribute to developing new therapeutic approaches for the treatments of chemoresistant osteosarcoma.

High-Throughput Electrosynthesis of Gradient Polypyrrole Film Using a Single-Electrode Electrochemical System.

As an effective approach for materials synthesis, bipolar electrochemistry has been earning a renewed interest nowadays thanks to its unique features compared to conventional electrochemistry. Indeed, the wireless mode of electrode reactions and the generation of a gradient potential distribution above the bipolar electrode are among the most appealing qualities of bipolar electrochemistry. In particular, the gradient potential distribution is a highly attractive characteristic for the fabrication of surfaces with gradients in their chemical properties or molecular functionalities. Herein, we report the high-throughput electrosynthesis of gradient polypyrrole films by means of a new electrochemical cell design named the single-electrode electrochemical system (SEES). SEESs are made by attaching an inert plastic board with holes onto an indium tin oxide electrode, constructing multiple microelectrochemical cells on the same electrode. This type of arrangement enables parallel electrochemical reactions to be carried out simultaneously and controlled in a contactless manner by a single electrode. Several experimental conditions for polypyrrole film growth were extensively investigated. Furthermore, the gradient property of the polymer films was evaluated by thickness determination, surface morphology analysis, and contact angle measurements. The use of SEES has been demonstrated as a convenient and cost-effective strategy for high-throughput electrosynthesis and electroanalytical applications and has opened up a new door for gradient film preparation via a rapid condition screening process.

Photoassisted Electrochemical Hydrogen Evolution Reaction of MFe2O4@Ultrathin Black Phosphorus Amorphous-Crystalline Interface.

Exploring highly active, stable, and low-cost catalysts for photoelectrochemical hydrogen evolution reaction (PE-HER) is vital in the field of energy conversion. Herein, we construct a new amorphous crystalline interface that amorphous iron-based spinel oxide (A-MFe2O4 (M = Ni, Co, Zn)) is uniformly anchored on the crystalline exfoliated black phosphorus (C-EBP) nanosheets via electrochemical and solvothermal strategies. Among these A-MFe2O4@C-EBP catalysts, more oxygen defects of A-NiFe2O4@C-EBP interface provide a larger effective electrochemical active area of 32.33 mF cm-2 as well as a turnover frequency of 0.44 s-1 and allow for an optimum equilibrium of the hydrogen-containing adsorption intermediates. Furthermore, A-NiFe2O4@C-EBP exhibits significant PE-HER performance with an overpotential of 42 mV at 10 mA cm-2 under visible-light irradiation. Density functional theory (DFT) calculations show that the amorphous-crystalline composite structure causes a large number of oxygen defects enhancing the intrinsic activity of A-NiFe2O4@C-EBP, which A-NiFe2O4@C-EBP significantly improves its adsorption capacity for H* for HER and has the lowest Gibbs free energy change for HER. This study not only provides a superior multifunctional amorphous-crystalline interface catalysts but also helps to understand the catalytic mechanism of PE-HER.

Facial changes in patients with skeletal class III deformity after bimaxillary surgery: an evaluation based on three-dimensional photographs registered with computed tomography.

The objective of this study was to evaluate facial soft and hard tissue changes, individually and relative to each other, in patients with skeletal class III deformity after bimaxillary surgery using three-dimensional (3D) photos obtained by white light scanning. Thirty patients with skeletal class III deformity who underwent bimaxillary surgery were selected. Each patient underwent white light scanning and spiral computed tomography (CT) within two weeks before (T0) and six months after surgery (T1). The 3D photos were registered with CT soft tissue models for T0 and T1, and the skeletal area unaffected by treatment (cranial base) was used to register T0 and T1. Then, the 3D colour-coded map was analysed to assess both skeletal and soft tissue changes between T0 and T1. Changes in the 3D coordinates of each anatomical landmark were analysed using the Student's t-test. Maxillary advancement by 2-3 mm and mandibular recession by 5-6 mm were observed; the mandible was shortened in the vertical direction. Compared with the preoperative values, the nasal columella was 0.51 mm shorter, the upper lip was 0.71 mm longer, the base of the alar cartilage was 1.38 mm wider, and the nasolabial angle became larger. The ratio of change in the position of soft tissue point Sn to hard tissue point A was 0.73:1, and that of soft tissue point Pg to hard tissue point Pog was 0.86:1. Images obtained by structured white light scanning registered with CT can be used as an alternative to study facial changes after orthognathic surgery.

A Prognostic Model for the Respiratory Function of Patients with Nonsevere Pulmonary Infection Based on Breathing Exercises and Acupuncture Therapy: Development and Validation.

Objective: In this study, a prognostic model for the respiratory function was constructed based on the treatment methods of patients with nonsevere pulmonary infection, aiming to provide a reference for clinical decision-making. Method: A total of 500 patients with nonsevere pulmonary infection were included in this study. The patients were randomized into training set (n = 350) and validation set (n = 150), and the baseline characteristics were collected. All patients received breathing exercises or breathing exercises combined with acupuncture therapy for 3 months, and then the forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) was assessed. Next, an ordinal multinomial logistic regression model was used to analyze prognostic factors affecting respiratory function of patients with nonsevere pulmonary infection. The Test of Parallel Lines was used to determine the accuracy (ACC) of the model and screen the influencing factors. The confusion matrix was drawn, and the ACC and harmonic mean (F1 score) were calculated to evaluate the feasibility of the model results. Results: Results of the ordinal multinomial logistic regression model showed that age (P = 0.000), treatment method (P = 0.000), underlying diseases (P < 0.001), and sex (P = 0.389) were independent factors affecting the respiratory function of patients in the training set. The ACC value of the training set was 88.86%, and that of the validation set was 91.33%, indicating a high accuracy and favorable predictive ability of the model. Besides, the F1 score was 62.38%, indicating a high reliability of the model. Conclusion: The prognostic model for respiratory function of patients with nonsevere pulmonary infection constructed in this study had favorable predictive performance, which is of great significance in the clinical nursing and treatment of patients with pulmonary infection.