Revealing Novel Genes Related to Parkinson's Disease Pathogenesis and Establishing an associated Model.

Parkinson's disease (PD) represents a multifaceted neurological disorder whose genetic underpinnings warrant comprehensive investigation. This study focuses on identifying genes integral to PD pathogenesis and evaluating their diagnostic potential. Initially, we screened for differentially expressed genes (DEGs) between PD and control brain tissues within a dataset comprising larger number of specimens. Subsequently, these DEGs were subjected to weighted gene co-expression network analysis (WGCNA) to discern relevant gene modules. Notably, the yellow module exhibited a significant correlation with PD pathogenesis. Hence, we conducted a detailed examination of the yellow module genes using a cytoscope-based approach to construct a protein-protein interaction (PPI) network, which facilitated the identification of central hub genes implicated in PD pathogenesis. Employing two machine learning techniques, including XGBoost and LASSO algorithms, along with logistic regression analysis, we refined our search to three pertinent hub genes: FOXO3, HIST2H2BE, and HDAC1, all of which demonstrated a substantial association with PD pathogenesis. To corroborate our findings, we analyzed two PD blood datasets and clinical plasma samples, confirming the elevated expression levels of these genes in PD patients. The association of the genes with PD, as reflected by the area under the curve (AUC) values for FOXO3, HIST2H2BE, and HDAC1, were moderate for each gene. Collectively, this research substantiates the heightened expression of FOXO3, HIST2H2BE, and HDAC1 in both PD brain and blood samples, underscoring their pivotal contribution to the pathogenesis of PD.

Safety Profile of Paxlovid in the Treatment of COVID-19.

BACKGROUND: With the urgent and widespread application of Paxlovid, a novel antiviral drug for Coronavirus Disease 2019 (COVID-19) in clinical practice, concerns regarding its actual efficacy and safety have emerged. In order to provide more evidence to support its clinical application, we sought to perform a descriptive analysis of cases who experienced at least one Paxlovid-related adverse event (AEs) and reported to the FDA Adverse Event Reporting System (FAERS) in the post-marketing period. METHODS: Individual adverse event reports between January 1, 2022 and September 30, 2022, were downloaded from the FAERS website. We completed a descriptive study about the safety of Paxlovid in the treatment of COVID-19. Further, we also analyzed the onset time of Paxlovid-related AEs. RESULTS: As of 30 September 2022, 16,529 de-duplicated cases were submitted to the FDA, and 5,860 (35.45%) were female. The average age was 58.38 years (S.D. 15.50). Most reports (12,390, 74.96%) were submitted by consumers and 1,436 (8.68%) concerned serious outcomes. The most frequently reported AEs were disease recurrence (7,724, 16.23%), dysgeusia (2,877, 6.05%), and diarrhoea (1,448, 3.04%). The median onset time of Paxlovid-related AEs was 8 days (interquartile range,1-10 days), and most of the cases (2,629, 19.12%) occurred on the day after Paxlovid initiation. CONCLUSION: This study indicates that the most common AEs reported with Paxlovid in post-marketing experience are consistent with the safety assessment of antiviral drugs. Even without emerging apparent safety concerns, the incidence of serious outcomes was unexpectedly high, and a few cases of potential new AEs occurred.

Distribution characteristics of perioperative deep vein thrombosis (DVT) and risk factors of postoperative DVT exacerbation in patients with thoracolumbar fractures caused by high-energy injuries.

OBJECTIVE: To investigate the distribution characteristics of perioperative deep venous thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries and analyze the risk factors of postoperative DVT exacerbation. METHODS: From October 2016 to July 2021, a total of 550 patients with thoracolumbar fractures due to high-energy injuries in our hospital were retrospectively analyzed. Both lower limbs were examined by ultrasound before and after operation. Depending on whether the postoperative DVT was exacerbating, the group was divided into a DVT exacerbation group and a non-DVT exacerbation group. Clinical data were used to study the characteristics of perioperative DVT. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to explore the risk factors of postoperative DVT exacerbation. RESULTS: DVT was found in 97 patients before operation, including 78 cases of distal thrombus, 6 cases of proximal thrombus, and 13 cases of mixed thrombus. Postoperative DVT increased to 116, including 87 distal thrombus, 10 proximal thrombus, and 19 mixed thrombus. The intermuscular vein was the most easily involved vein. Compared with lumbar fractures, thoracic fractures were more likely to have postoperative proximal thrombus (P=0.014). There were 48 cases of thrombus exacerbation after operation. Logistic regression analysis revealed that age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation. CONCLUSIONS: The intermuscular vein is the most easily involved vein. The anatomical distribution of DVT at different fracture sites is different, and patients with thoracic fractures are more likely to have proximal DVT after operation. Age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation.

Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries.

OBJECTIVE: Deep venous thrombosis (DVT) is a common complication in patients with spinal fractures caused by high-energy injuries. Early identification of patients at high risk of postoperative DVT is essential for the prevention of thrombosis. This study aimed to develop and validate a prediction model based on a nomogram to predict DVT in patients with spinal fractures caused by high-energy injuries. METHODS: Clinical data were collected from 936 patients admitted to our hospital between January 2016 and December 2021 with spinal fractures caused by high-energy injuries. Multivariate logistic regression analysis was used to identify the risk factors for postoperative DVT and to develop a nomogram. The predictive performance of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. RESULTS: The incidence of preoperative DVT was 15.38% (144/936). The postoperative incidence of DVT was 20.5% (192/936). The multivariate analysis revealed that age, operation time, blood transfusion, duration of bed rest, American Spinal Injury Association (ASIA) score and D-dimer were risk factors for postoperative DVT. The area under the ROC curve of the nomogram was 0.835 and the calibration curve showed good calibration. CONCLUSIONS: The nomogram showed a good ability to predict postoperative DVT in patients with spinal fractures caused by high-energy injuries, which may benefit pre- and postoperative DVT prophylaxis strategy development.

Bioinspired Polyoxo-titanium Cluster for Greatly Enhanced Solar-Driven CO2 Reduction.

Developing artificial enzymes with excellent catalytic activities and uncovering the structural and chemical determinants remain a grand challenge. Discrete titanium-oxo clusters with well-defined coordination environments at the atomic level can mimic the pivotal catalytic center of natural enzymes and optimize the charge-transfer kinetics. Herein, we report the precise structural tailoring of a self-assembled tetrahedral Ti4Mn3-cluster for photocatalytic CO2 reduction and realize the selective evolution of CO over specific sites. Experiments and theoretical simulation demonstrate that the high catalytic performance of the Ti4Mn3-cluster should be related to the synergy between active Mn sites and the surrounding functional microenvironment. The reduced energy barrier of the CO2 photoreduction reaction and moderate adsorption strength of CO* are beneficial for the high selective evolution of CO. This work provides a molecular scale accurate structural model to give insight into artificial enzyme for CO2 photoreduction.

Novel Autophagy-Related Blood Biomarkers Associated with Immune Cell Infiltration in Ankylosing Spondylitis.

Background: This study aims to identify new therapeutic targets and explore the molecular mechanism of ankylosing spondylitis (AS), a rheumatic immune disease that mainly affects the sacroiliac and spinal joints. Despite extensive research, the exact cause of AS is still unknown. The research team utilized a bioinformatics approach to achieve their objectives. Methods: The GSE73754 dataset was downloaded from GEO database. Autophagy-related genes (ARGs) were collected from the Human Autophagy-dedicated Database. The limma package was used to screen for differentially expressed genes (DEGs), which were then intersected with the autophagy-related genes (ARGs) to identify differentially expressed autophagy-related genes (DEARGs). Subsequently, the DEARGs associated with AS were subjected to GO-BP and KEGG enrichment analyses using the clusterProfiler package. Core genes were identified using the cytoHubba plug-in of Cytoscape and were validated by clinical blood samples. Additionally, the Cell algorithm was utilized to evaluate the proportion of immune cell infiltration. Results: A total of 29 DEARGs were identified, which were found to be mainly enriched in autophagy, apoptosis, and necroptosis through functional enrichment analysis. Two core genes, HSPA5 and SQSTM1, were confirmed to have diagnostic value in AS. Immune cell infiltration analysis revealed CD8+ T cells, CD8+ T effector memory (Tem), natural killer (NK) cells, T gamma delta (Tgd) cells, and T-helper 1 (Th1) cells as major participants in AS development. Furthermore, HSPA5 expression was significantly correlated with Th1 cells, CD8+ T cells, CD4+ memory cells, and macrophages. Conclusion: This study suggested that HSPA5 and SQSTM1 can serve as useful diagnostic biomarkers for AS. These findings lay the foundation for identifying crucial mRNAs in the whole blood of AS patients, which may aid in the development of novel markers for AS.

Stability of mpox virus on different commonly contacted surfaces.

Mpox is still spreading globally and is mostly reported to be transmitted by skin and mucosal contact. However, transmission through contact with fomites, contaminated objects, or surfaces has been reported in general population. Evaluation of the stability of mpox virus (MPXV) on different surfaces is important to minimize mpox transmission. In the study, the stability of MPXV on different kinds of commonly contacted surfaces was determined. MPXV was observed to have a surface-dependent stability pattern. Viable virus was detected on both glass and stainless steel for up to 5 days, and on plastic surfaces for up to 3 days. In contrast, no viable MPXV was detected on wooden board and cardboard, which are porous and water-absorbent surfaces, after 1 and 2 days of incubation, respectively. In addition, MPXV nucleic acids were more stable and showed better correlation with viral titers on stainless steel, plastic, and glass. The results indicate that fomite transmission of MPXV is plausible. Moreover, the stability of MPXV was highly surface-dependent and more stable on smooth surfaces, which could provide more information for minimizing the transmission of mpox and emphasize the significance of environmental disinfection in mpox prevention and control.

A systematic review and meta-analysis of artificial intelligence-diagnosed endoscopic remission in ulcerative colitis.

Endoscopic remission is an important therapeutic goal in ulcerative colitis (UC). The Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and Mayo Endoscopic Score (MES) are the commonly used endoscopic scoring criteria. This systematic review and meta-analysis aimed to evaluate the accuracy of artificial intelligence (AI) in diagnosing endoscopic remission in UC. We also performed a meta-analysis of each of the four endoscopic remission criteria (UCEIS = 0, MES = 0, UCEIS = <1, MES = <1). Eighteen studies involving 13,687 patients were included. The combined sensitivity and specificity of AI for diagnosing endoscopic remission in UC was 87% (95% confidence interval [CI]:81-92%) and 92% (95% CI: 89-94%), respectively. The area under the curve (AUC) was 0.96 (95% CI: 0.94-0.97). The results showed that the AI model performed well regardless of which criteria were used to define endoscopic remission of UC.

Controllable Fabrication of Vertical Graphene with Tunable Growth Nature by Remote Plasma-Enhanced Chemical Vapor Deposition.

As an important member of the graphene family, vertical graphene (VG) has broad applications like field emission, energy storage, and sensors owing to its fascinating physical and chemical properties. Among various fabrication methods for VG, plasma enhanced chemical vapor deposition (PECVD) is most employed because of the fast growth rate at relatively low temperature for the high-quality VG. However, to date, relations between growth manner of VG and growth parameters such as growth temperature, dosage of gaseous carbon source, and electric power to generate plasma are still less known, which in turn hinder the massive production of VG for further applications. In this study, the growth behavior of VG was studied as functions of temperature, plasma power, and gas composition (or chamber pressure). It was found that the growth behavior of VG is sensitive to the growth conditions mentioned above. Although conditions with high growth temperature, large flow rate of mixed gas of methane and carrier gases, and high plasma power may be helpful for the fast growth of VG, brunching of VG is simultaneously enhanced, which in turn decreases the vertical growth nature of VG. High-quality VG can be achieved by optimizing the growth parameters. It was revealed that the vertical growth nature of VG is governed by the electric field at the interfacial layer between VG and the substrate, for which its strength is influenced by the density of plasma. These findings are important for the general understanding of the VG growth and provided a feasible way for the controllable fabrication of VG using the remote PECVD method which is usually believed to be unsuitable for the fabrication of VG.

Electron transport, ferroelectric, piezoelectric and optical properties of two-dimensional In2Te3: a first-principles study.

Two-dimensional (2D) materials have garnered significant interest in the fields of optoelectronics and electronics due to their unique and diverse properties. In this work, the electron transport, ferroelectric, piezoelectric, and optical properties of 2D In2Te3 were systematically investigated using first-principles based on density functional theory. The analysis of the phonon spectrum and elastic modulus of the Born effective criterion indicates that the structure of the novel 2D In2Te3 is dynamically stable. The calculation results show that 2D In2Te3 exhibits a carrier mobility as high as 3680.99 cm2 V-1 s-1 (y direction), a high in-plane polarization of 2.428 × 10-10 C m-1, and an excellent ferroelectric phase transition barrier (52.847 meV) and piezoelectric properties (e11 = 1.52 × 10-10 C m-1). The higher carrier mobility is attributed to the band degeneracy and small carrier effective mass. In addition, biaxial strain is an effective way to modulate the band gap and optical properties of 2D In2Te3. These properties indicate that 2D In2Te3 is a promising candidate material for flexible electronic devices and ferroelectric photovoltaic devices.

Syndecan-2 modulates the YAP pathway in epithelial-to-mesenchymal transition-related migration, invasion, and drug resistance in colorectal cancer.

Epithelial-to-mesenchymal transition (EMT) is associated with an invasive phenotype in colorectal cancer (CRC). Here, we examined the roles of YES-associated protein (YAP) and syndecan-2 (SDC2) in EMT-related progression, invasion, metastasis, and drug resistance in CRC. The expression levels of YAP and SDC2 in CRC patient tumor tissue were quantified by PCR and western blotting. EMT-associated characteristics were assessed using Transwell assays and immunohistochemistry. Co-immunoprecipitation, glutathione S-transferase pull-down, and luciferase reporter assays were used to assess interactions between YAP and SDC2. YAP was found to be highly expressed in tumor tissue from 13/16 CRC patients, while SDC2 was highly expressed in the tumor tissue of 12/16 CRC patients. Overexpression of YAP in colon cancer cells led to increased cell viability, invasion, migration, and oxaliplatin resistance demonstrating that YAP plays a role in EMT. In addition, overexpression of YAP led to decreased expression of the large tumor suppressor kinase 1 (LATS1) and mammalian sterile 20-like kinases (MST1/2). Decreased LATS1 expression was associated with increased levels of cell proliferation. Knockdown of YAP by shRNA interference led to decreased cell invasion, migration, and drug resistance in colon cancer cells and reduced tumorigenesis in a mouse xenograft model. Finally, we established that YAP interacted with SDC2, and demonstrated that SDC2 mediated the YAP pathway through the EMT-related factors BMP4, CTGF and FOXM1.

Clinical characteristics of abruptly increased paediatric patients with Omicron BF.7 or BA.5.2 in Beijing.

BACKGROUND: The coronavirus disease 2019 outbreak has hit Beijing since mid-Nov, 2022, with soaring growth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among children. Therefore, it is vital to determine the clinical manifestations of epidemic SARS-CoV-2 strains in paediatric patients. METHODS: In this study, nucleic acid tests (NATs) for SARS-CoV-2 were performed in paediatric outpatients with symptoms of acute respiratory tract infection during 18 Nov-6 Dec, 2022. Half of the outpatients positive for SARS-CoV-2 were randomly selected to screen for other respiratory pathogens, whereas those with low cycle threshold values in SARS-CoV-2 NATs were amplified and sequenced to determine the SARS-CoV-2 variants. Finally, children positive for SARS-CoV-2 with clinical information in detail were enrolled in a follow-up study to identify potential factors significantly associated with long recovery. RESULTS: Among 9625 paediatric outpatients tested for nucleic acid of SARS-CoV-2, 733 (7.62%, 733/9625) were identified as SARS-CoV-2 NAT positive, with only three (0.82%, 3/366) co-infected with other pathogens among 366 randomly selected patients, and 71 (62.83%) determined as Omicron subvariant BF.7 and 42 (37.22%) as BA.5.2 among 113 successfully sequenced. Among the 681 patients with complete clinical information, fever was the most common symptom (96.8%). In a follow-up study of 592 patients, 46.96% became asymptomatic on the third day and 65.71% on the fifth day. Only 1.7% of infected children experienced febrile seizures. Combined with abnormal C-reactive protein, a higher percentage of antibiotics administration was observed. More co-living members and longer duration of first symptoms served as independent risk factors for long-term recovery, especially in children vaccinated for SARS-CoV-2. CONCLUSIONS: BF.7 and BA.5.2 were the dominate Omicron subvariants and caused milder infections during the SARS-CoV-2 outbreak in Beijing. The number of co-living members and duration of first symptoms were independent risk factors for long-term recovery.

Diagnostic value of deep learning-assisted endoscopic ultrasound for pancreatic tumors: a systematic review and meta-analysis.

Background and aims: Endoscopic ultrasonography (EUS) is commonly utilized in the diagnosis of pancreatic tumors, although as this modality relies primarily on the practitioner's visual judgment, it is prone to result in a missed diagnosis or misdiagnosis due to inexperience, fatigue, or distraction. Deep learning (DL) techniques, which can be used to automatically extract detailed imaging features from images, have been increasingly beneficial in the field of medical image-based assisted diagnosis. The present systematic review included a meta-analysis aimed at evaluating the accuracy of DL-assisted EUS for the diagnosis of pancreatic tumors diagnosis. Methods: We performed a comprehensive search for all studies relevant to EUS and DL in the following four databases, from their inception through February 2023: PubMed, Embase, Web of Science, and the Cochrane Library. Target studies were strictly screened based on specific inclusion and exclusion criteria, after which we performed a meta-analysis using Stata 16.0 to assess the diagnostic ability of DL and compare it with that of EUS practitioners. Any sources of heterogeneity were explored using subgroup and meta-regression analyses. Results: A total of 10 studies, involving 3,529 patients and 34,773 training images, were included in the present meta-analysis. The pooled sensitivity was 93% (95% confidence interval [CI], 87-96%), the pooled specificity was 95% (95% CI, 89-98%), and the area under the summary receiver operating characteristic curve (AUC) was 0.98 (95% CI, 0.96-0.99). Conclusion: DL-assisted EUS has a high accuracy and clinical applicability for diagnosing pancreatic tumors. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023391853, identifier CRD42023391853.

Diagnostic value of artificial intelligence-assisted endoscopy for chronic atrophic gastritis: a systematic review and meta-analysis.

Background and aims: The diagnosis of chronic atrophic gastritis (CAG) under normal white-light endoscopy depends on the endoscopist's experience and is not ideal. Artificial intelligence (AI) is increasingly used to diagnose diseases with good results. This review aimed to evaluate the accuracy of AI-assisted diagnosis of CAG through a meta-analysis. Methods: We conducted a comprehensive literature search of four databases: PubMed, Embase, Web of Science, and the Cochrane Library. Studies published by November 21, 2022, on AI diagnosis CAG with endoscopic images or videos were included. We assessed the diagnostic performance of AI using meta-analysis, explored the sources of heterogeneity through subgroup analysis and meta-regression, and compared the accuracy of AI and endoscopists in diagnosing CAG. Results: Eight studies that included a total of 25,216 patients of interest, 84,678 image training set images, and 10,937 test set images/videos were included. The results of the meta-analysis showed that the sensitivity of AI in identifying CAG was 94% (95% confidence interval [CI]: 0.88-0.97, I2 = 96.2%), the specificity was 96% (95% CI: 0.88-0.98, I2 = 98.04%), and the area under the summary receiver operating characteristic curve was 0.98 (95% CI: 0.96-0.99). The accuracy of AI in diagnosing CAG was significantly higher than that of endoscopists. Conclusions: AI-assisted diagnosis of CAG in endoscopy has high accuracy and clinical diagnostic value. Systematic review registration: http://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42023391853.

Excellent thermoelectric properties of the Tl2S3 monolayer for medium-temperature applications.

Exploring materials with high thermoelectric (TE) performance can alleviate energy pressure and protect the environment, and thus, TE materials have attracted extensive attention in the new energy field. In this paper, we systematically study the TE properties of Tl2S3 using first-principles combined with Boltzmann transport theory (BTE). The calculation results show an excellent power factor (1.12 × 10-2 W m-1 K-2) and ultra-low lattice thermal conductivity (kl = 0.88 W m-1 K-1) at room temperature. Through analysis, we attribute the ultra-low kl of Tl2S3 to the lower phonon group velocity (vg) and larger phonon anharmonicity. Meanwhile, discussion of chemical bonding showed that the filling of the anti-bonding state leads to the weakening of the Tl-S chemical bond, resulting in low vg. Furthermore, this research also investigates the scattering processes (the out-of-plane acoustic mode (ZA) + optical mode (O) → O (ZA + O → O), the in-plane transverse acoustic mode (TA) + O → O (TA + O → O), and the in-plane longitudinal acoustic mode (LA) + O → O (LA + O → O)), from which we find that 2D Tl2S3 possesses strong acoustic-optical scattering. Based on the analysis of electron transport properties under electron-phonon coupling, 2D Tl2S3, as a novel TE material, exhibits a ZT value as high as 2.8 at 400 K. Our calculations suggest that Tl2S3 is a potential TE material at medium temperature.

Deep learning-assisted diagnosis of chronic atrophic gastritis in endoscopy.

Background: Chronic atrophic gastritis (CAG) is a precancerous condition. It is not easy to detect CAG in endoscopy. Improving the detection rate of CAG under endoscopy is essential to reduce or interrupt the occurrence of gastric cancer. This study aimed to construct a deep learning (DL) model for CAG recognition based on endoscopic images to improve the CAG detection rate during endoscopy. Methods: We collected 10,961 endoscopic images and 118 video clips from 4,050 patients. For model training and testing, we divided them into two groups based on the pathological results: CAG and chronic non-atrophic gastritis (CNAG). We compared the performance of four state-of-the-art (SOTA) DL networks for CAG recognition and selected one of them for further improvement. The improved network was called GAM-EfficientNet. Finally, we compared GAM-EfficientNet with three endoscopists and analyzed the decision basis of the network in the form of heatmaps. Results: After fine-tuning and transfer learning, the sensitivity, specificity, and accuracy of GAM-EfficientNet reached 93%, 94%, and 93.5% in the external test set and 96.23%, 89.23%, and 92.37% in the video test set, respectively, which were higher than those of the three endoscopists. Conclusions: The CAG recognition model based on deep learning has high sensitivity and accuracy, and its performance is higher than that of endoscopists.

Multiple-Intercalation Stages and Universal Tc Enhancement through Polar Organic Species in Electron-Doped 1T-SnSe2.

In this work, we report multiple-intercalation stages and universal Tc enhancement of superconductivity in 1T-SnSe2 through Li and organic molecule co-intercalation. We observe significantly increased lattice parameters of up to 40 Šand a dramatically enlarged interlayer distance of up to ∼11 Šin Li and N,N-dimethylformamide (DMF) co-intercalated SnSe2. Well-separated co-intercalation stages with different stacking patterns have been discovered by carefully controlled reaction times and concentrations of solutions. These co-intercalation stages are superconductors showing different superconducting signals. In addition, Li and various organic species such as acetone, dimethyl sulfoxide (DMSO), and tetrahydrofuran (THF) have been co-intercalated into SnSe2 crystals; all of which show an enhanced superconducting Tc compared to solely Li-intercalated SnSe2. Our findings may provide more insight into effectively tuning the electronic structure of the lamellar structure through organic molecule co-regulation and open a new strategy to engineer the physical properties of these layered materials by controlling their different intercalation stages.

Dynamic Changes and Relevant Factors of Perioperative Deep Vein Thrombosis in Patients with Thoracolumbar Fractures Caused by High-Energy Injuries.

OBJECTIVE: To investigate the dynamic changes and relevant factors of deep vein thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries. METHODS: From January 2016 to June 2021, a total of 655 patients with thoracolumbar fractures who underwent surgical treatment in our hospital were retrospectively analyzed. The patients were examined by preoperative and postoperative ultrasonography, and divided into thrombus growth group, thrombus invariant group, and thrombus regression group according to the preoperative and postoperative ultrasonographic results. Medical record data, including demographic data, surgical data, and laboratory results, were collected and the differences in various factors among the groups were compared. RESULTS: DVT was found in 99 patients (15.1%, 99/655) before surgery, including 79 cases of distal thrombus, 7 cases of proximal thrombus, and 13 cases of mixed thrombus. The incidence of postoperative DVT increased to 20.6% (134/655), including 96 cases of distal thrombus, 15 cases of proximal thrombus, and 23 cases of mixed thrombus. Among them, 39.7% had thrombus growth, 49.3% had thrombus basically unchanged and 11.0% had thrombolysis. There were significant differences in age, lower extremity muscle strength, time from trauma to surgery, operation time, blood loss, blood transfusion, and post 3-D-dimer among the three groups. CONCLUSIONS: In patients with thoracolumbar fractures caused by high-energy injuries, the majority of patients with DVT do not change or grow after surgery, and only a few of them have thrombolysis. Younger age, lower extremity motor, and fewer blood transfusion contribute to thrombolysis. Delayed surgical intervention, longer operation time, and higher blood loss can lead to thrombosis growth. Post 3-D-dimer is closely related to the dynamic changes of thrombus.

Elucidation of the Key Therapeutic Targets and Potential Mechanisms of Marmesine against Knee Osteoarthritis via Network Pharmacological Analysis and Molecular Docking.

Background: Marmesine, a major active ingredient isolated from Radix Angelicae biseratae (Duhuo), has been reported to have multiple pharmacological activities. However, its therapeutic effects against knee osteoarthritis (OA) remain poorly investigated. The present study is aimed at uncovering the core targets and signaling pathways of marmesine against osteoarthritis using a combined method of bioinformatics and network pharmacology. Methods: We utilized SwissTargetPrediction and PharmMapper to collect the potential targets of marmesine. OA-related differentially expressed genes (DEGs) were identified from GSE98918 dataset. Then, the intersection genes between DEGs and candidate genes of marmesine were subjected to protein-protein interaction (PPI) network construction and functional enrichment analysis. The core targets were verified using the molecular docking technology. Results: A total of 320 marmesine-related genes and 5649 DEGs and 60 ingredient-disease targets between them were identified. The results of functional enrichment analyses revealed that response to oxygen levels, neuroinflammatory response, PI3K-Akt signaling pathway, MAPK signaling pathway, FoxO signaling pathway, and osteoclast differentiation was identified as the potential mechanisms of marmesine against OA. EGFR, CASP3, MMP9, PPARG, and MAPK1 served as hub genes regulated by marmesine in the treatment of OA, and the molecular docking further verified the results. Conclusion: Marmesine exerts the therapeutic effects against OA through multitarget and multipathways, in which EGFR, CASP3, MMP9, PPARG, and MAPK1 might be hub genes. Our research indicated that the combination of bioinformatics and network pharmacology could serve as an effective approach for investigating the potential mechanisms of natural product.

Narrow Linewidth Half-Open-Cavity Random Laser Assisted by a Three-Grating Ring Resonator for Strain Detection.

A stabilized narrow-linewidth random fiber laser for strain detection, based on a three-grating ring (TGR) resonator and half-open-cavity structure, is proposed and investigated experimentally. The half-open-cavity structure proved to provide double optical gain of erbium-doped fiber, which was beneficial to increase the photon lifetime as well as further narrow the linewidth. Meanwhile, the stability and frequency noise of narrow lasing output was improved by suppressing the competition-induced undesired residual random lasing modes with the TGR resonator. The TGR resonator is composed of a double-cavity fiber Bragg grating Fabry-Perot (FBG-FP) interferometer, a section of single-mode fiber, and a circulator. The specially designed double-cavity FBG-FP interferometer embedded in the TGR resonator acted as the strain-sensing element and improved the resolution of the dynamic strain. A stable ultra-narrow linewidth of about 205 Hz was obtained. The frequency noise was reduced to about 2 Hz/√Hz. A high dynamic strain measuring resolution of 35 femto-strain (fε)/√Hz was achieved.