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Introduction: Holistic Approach in Lowering and Tracking Chronic Kidney Disease (HALT-CKD) is a nationwide programme that was introduced in 2017 to combat CKD in Singapore. This study aims to evaluate outcomes of the HALT-CKD programme and identify factors influencing disease progression among early CKD patients. Method: We conducted a retrospective cohort study involving adult patients aged 21 to 80 with CKD stages G1–G3A, recruited from 5 Singapore polyclinics between 2017 and 2018. The primary outcome—time to progression to advanced CKD (G3B–G5)—was tracked until March 2023, based on patients’ last known serum creatinine levels. Descriptive statistics and Cox regression were used. Patients who followed up with other institutions, were deceased or defaulted without developing (or experiencing) the outcome were censored. Results: We studied 3800 patients (mean age: 61.9 years) for a median of 4.7 years. Among them, 12.6% developed advanced CKD despite statistically significant improvements in HbA1c, blood pressure and albuminuria levels. Increasing age, female sex, clinic, baseline creatinine, diastolic blood pressure and HbA1c significantly shortened time to CKD progression. Macro-albuminuria at baseline (hazard ratio [HR] 1.77, 95% confidence interval [CI] 1.19–2.61) and at analysis (HR 2.22, 95% CI 1.55–3.19) significantly accelerated advanced CKD progression. Patients who had their angiotensin-converting enzyme inhibitor (ACEi)/angiotensin receptor blocker (ARB) dose reduced or discontinued progressed to advanced CKD earlier (HR 1.92, 95% CI 1.50–2.45). Counselling and sodium-glucose cotransporter-2 inhibitor (SGLT2i) use did not significantly delay CKD progression. Conclusion: Maintaining optimal ACEi/ARB dosage is essential to delay CKD progression. Premature cessation or reduction of this dosage should be discouraged. Further research on counselling and SGLT2i use in early CKD is needed to address the growing burden of CKD.

Objective: This study aims to evaluate the effect of noise management in interventional radiology suites on patients undergoing transarterial chemoembolization (TACE). Methods: A retrospective cohort study design was employed. The study included a total of 141 patients with hepatocellular carcinoma who underwent TACE surgery in interventional radiology suite of the First People’s Hospital of Nantong from January 2022 to December 2022. The patients were divided into an observation group (received noise management, n = 70) and a control group (did not receive noise management, n = 71) on the basis of whether they received noise management. Patient demographics and surgical data were collected, and heart rate, blood pressure, and anxiety levels were assessed before, during and after surgery. Satisfaction and the incidence of adverse reactions were also documented. Results: No significant differences were found in general characteristics. The comparison between the observation and control groups revealed statistically significant differences in noise levels (P < 0.001). Additionally, anxiety levels significantly differed between the two groups (P = 0.040) as well as across different time points (P < 0.001). However, no significant difference was found in the occurrence of adverse events between groups (P = 0.772). Furthermore, patient satisfaction was significantly higher in the observation group than that in the control group (P < 0.001). Although no significant differences were found in heart rate and systolic blood pressure between groups (P > 0.05), and a significant main effect of time was observed for both variables (P < 0.001). Conclusion: Noise management in the interventional radiology suite effectively alleviates intraoperative anxiety among patients with TACE and improves treatment satisfaction but has no significant effect on physiological changes and the incidence of adverse events.

IntroductionTuberculosis (TB) is a serious infectious disease that endangers human health, and TB becomes more difficult in eradiation due to its multidrug resistance (MDR). The objective of this research was to identify novel targets for treating TB.MethodsA 2-fold serial dilution method was used to determine minimal inhibitory concentrations (MIC) of compound M6 against Mycobacterium smegmatis (M. smegmatis). Compound M6 was subjected to reverse molecular docking with seven Mycobacterium tuberculosis proteins, and the best binding protein with the highest LibDock score was evaluated. The target protein with the highest score was purified through prokaryotic expression. Isolated target proteins were investigated for the enzyme activities and for the kinetic effect of compound M6 by absorbance detection. Subsequently, the CRISPR/Cas9 technology was employed to inhibit target gene expression for detecting MIC changes. Finally, potential targets were evaluated for the effect of the compound M6 in bacteria.ResultsThe MIC values of compound M6 against M. smegmatis were 32 μg/mL. The results from reverse molecular docking show that IspD has the highest LibDock score of 142.50, followed by Rv0674, IspF, and Dxr, with docking scores of 110.762, 71.6955, and 57.7446, respectively. IspD is a key enzyme in the 2-C-methyl-D-erythritol 4-phosphate pathway of MTB. The aKi and Ki values of M6 for the substrate MEP are 609.58 μM and 81.33 μM. For CTP, the aKi and Ki values are 657.89 μM and 40.07 μM. With tetracycline inducing CRISPR/Cas9 to suppress the expression of IspD, the MIC value of M6 against IspD went down significantly from 32 μg/mL to 4 μg/mL.ConclusionIspD is a novel target of the compound M6 for treating TB.

Bronchopulmonary dysplasia (BPD) is a chronic lung disease that affects premature infants and leads to long-term pulmonary complications. The pathogenesis of BPD has not been fully elucidated yet. In recent years, the microbiome and its metabolites, especially short-chain fatty acids (SCFAs), in the gut and lungs have been demonstrated to be involved in the development and progression of the disease. This review aims to summarize the current knowledge on the potential involvement of the microbiome and SCFAs, especially the latter, in the development and progression of BPD. First, we introduce the gut-lung axis, the production and functions of SCFAs, and the role of SCFAs in lung health and diseases. We then discuss the evidence supporting the involvement of the microbiome and SCFAs in BPD. Finally, we elaborate on the potential mechanisms of the microbiome and SCFAs in BPD, including immune modulation, epigenetic regulation, enhancement of barrier function, and modulation of surfactant production and the gut microbiome. This review could advance our understanding of the microbiome and SCFAs in the pathogenesis of BPD, which also helps identify new therapeutic targets and facilitate new drug development.

Abstract The regeneration of critical-size bone defects, especially those with irregular shapes, remains a clinical challenge. Various biomaterials have been developed to enhance bone regeneration, but the limitations on the shape-adaptive capacity, the complexity of clinical operation, and the unsatisfied osteogenic bioactivity have greatly restricted their clinical application. In this work, we construct a mechanically robust, tailorable and water-responsive shape-memory silk fibroin/magnesium (SF/MgO) composite scaffold, which is able to quickly match irregular defects by simple trimming, thus leading to good interface integration. We demonstrate that the SF/MgO scaffold exhibits excellent mechanical stability and structure retention during the degradative process with the potential for supporting ability in defective areas. This scaffold further promotes the proliferation, adhesion and migration of osteoblasts and the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) in vitro. With suitable MgO content, the scaffold exhibits good histocompatibility, low foreign-body reactions (FBRs), significant ectopic mineralisation and angiogenesis. Skull defect experiments on male rats demonstrate that the cell-free SF/MgO scaffold markedly enhances bone regeneration of cranial defects. Taken together, the mechanically robust, personalised and bioactive scaffold with water-responsive shape-memory may be a promising biomaterial for clinical-size and irregular bone defect regeneration.

Abstract Acute compartment syndrome (ACS) is a severe orthopedic issue that, if left untreated, can result in lasting nerve and muscle damage or even necessitate amputation. The association between admission laboratory blood test indicators and the occurrence of ACS in patients with tibial diaphysis fractures is currently a subject of debate. The objective of this research was to identify the contributing factors for ACS in individuals suffering from tibial diaphysis fractures. In this retrospective study, we collected data on a total of 705 individuals from our hospital, comprising 86 ACS patients and 619 non-ACS patients with tibial diaphysis fractures. These participants were categorized into two distinct groups: the ACS group and the non-ACS group. Despite the inherent limitations associated with retrospective analyses, such as potential biases in data collection and interpretation, we conducted a comprehensive analysis of demographics, comorbidities, and admission lab results. Our analytical approach included univariate analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis techniques, aiming to mitigate these limitations and provide robust findings. The statistical analysis revealed several predictors of ACS, including gender (p = 0.011, OR = 3.200), crush injuries (p = 0.004, OR = 4.622), lactic dehydrogenase (LDH) levels (p

Abstract Observational studies have found a potential bidirectional positive association between multiple sclerosis and psoriasis, but these studies are susceptible to confounding factors. We examined the directionality of causation using Mendelian randomization and estimated the genetic correlation using the linkage disequilibrium score. We performed Mendelian randomization analysis using large-scale genome-wide association studies datasets from the International Multiple Sclerosis Genetics Consortium (IMSGC, 115,803 individuals of European ancestry) and FinnGen (252,323 individuals of European ancestry). We selected several Mendelian randomization methods including causal analysis using summary effect (CAUSE), inverse variance-weighted (IVW), and pleiotropy-robust methods. According to CAUSE and IVW the genetic liability to MS reduces the risk of psoriasis (CAUSE odds ratio [OR] 0.93, p = 0.045; IVW OR 0.93, p = 2.51 × 10–20), and vice versa (CAUSE OR 0.72, p = 0.001; IVW OR 0.71, p = 4.80 × 10–26). Pleiotropy-robust methods show the same results, with all p-values

Abstract The rising prevalence of harassment in Middle Eastern countries is mirrored in literary works from the region. However, extracting data from these texts to understand the typology and frequency of the cases poses a significant challenge due to human cognitive limitations and potential biases. Thus, this study aims to use natural language processing (NLP) approaches to propose a machine learning framework for text mining of sexual harassment content in literary texts. The data source for this study consists of twelve Middle Eastern novels. The proposed framework involves the classification of physical and non-physical types of sexual harassment using a machine-learning model. Lexicon-based sentiment and emotion detection are applied to sentences containing instances of sexual harassment for data labelling and analysis. Finally, a long short-term memory-gated recurrent unit (LSTM-GRU) deep learning model is built to classify the sentiment characteristics that induce sexual harassment. The proposed model achieved an accuracy of 75.8% while outperforming five other algorithms. Additionally, a sentiment classification with three labels—negative, positive, and neutral—was developed using an LSTM-GRU RNN deep learning model. The accuracy of this model was 84.5%. Most statements, even those involving physical sexual harassment, which had greater levels of sexual harassment, had negative sentiments, according to lexicon-based sentiment analysis. This study contributes to the field of text mining by providing a novel approach to identifying instances of sexual harassment in literature in English from the Middle East. The use of machine learning models and sentiment analysis techniques allows for more accurate identification and classification of different types of sexual harassment. Furthermore, this study sheds light on the prevalence of sexual harassment in Middle Eastern countries and highlights the need for further research and action to address this issue.

Salvianolic acid A (SalA), a bioactive compound extracted from Salvia miltiorrhiza, has garnered considerable interest for its potential in ameliorating the post-stroke neuroinflammation. This review delineates the possible molecular underpinnings of anti-inflammatory and neuroprotective roles of SalA, offering a comprehensive analysis of its therapeutic efficacy in preclinical studies of ischemic stroke. We explore the intricate interplay between post-stroke neuroinflammation and the modulatory effects of SalA on pro-inflammatory cytokines, inflammatory signaling pathways, the peripheral immune cell infiltration through blood-brain barrier disruption, and endothelial cell function. The pharmacokinetic profiles of SalA in the context of stroke, characterized by enhanced cerebral penetration post-ischemia, makes it particularly suitable as a therapeutic agent. Preliminary clinical findings have demonstrated that salvianolic acids (SA) has a positive impact on cerebral perfusion and neurological deficits in stroke patients, warranting further investigation. This review emphasizes SalA as a potential anti-inflammatory agent for the advancement of innovative therapeutic approaches in the treatment of ischemic stroke.

To realize large-scale hydrogen production by electrolysis of water, it is essential to develop non-precious metal catalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Here, we fabricate Sn-, Fe-, and Co-based sulfide/oxyhydroxide heterostructural catalyst on nickel foam (FeSnCo0.2SxOy/NF) by solvothermal method. The FeSnCo0.2SxOy/NF requires low overpotentials of 48 and 186 mV at 10 mA·cm–2, respectively, for HER and OER. When it is assembled into an electrolytic cell as a bifunctional electrocatalyst, it only needs 1.54 V to reach 10 mA·cm–2, far better than IrO2||Pt/C electrolyzer. The formation of sulfide/hydroxide heterostructural interfaces improves the electron transfer and reduces the reaction energy barrier, thus promoting the electrocatalytic processes.

Accurate face recognition technology is of great significance for face anti-counterfeiting. Due to illumination, posture, angle, and other reasons, the existing face liveness detection technology is difficult to adapt the environmental changes, resulting in low detection accuracy. To address this issue, this paper presents a novel high-performance face anti-spoofing detection method named RGCS_ConvNeXt. The data-enhanced face images are fed into the ConvNext network, which group convolution is added to extract the correlation between different features, and the coordinate attention mechanism is used to enhance the facial feature extraction capability both spatially and directionally. Then SPPF is used to extract the features at different scales to enhance the representation of the feature map. Finally, the facial key point detection technique is utilized to calculate the eye EAR value to achieve accurate face anti-counterfeiting recognition. The proposed algorithm shows an average classification error rate of 0.3%, 1.7%, 1.9%±1.5% and 2.8%±3.4%, respectively, on the four protocols of the OULU-NPU public dataset. On the Siw dataset, the average classification error rate is 0.69%, a reduction of 0.02% compared to the MA-Net network. The half-error rate on the MSU-MFSD dataset is 2.39%, a 0.21% reduction compared to the DPCNN network. The algorithm shows good accuracy on the OULU-NPU, MSU-MFSD and Siw datasets, reaching 99.64%, 98.40% and 99.25% respectively, 0.26% higher than the SE-FeatherNet network’s average accuracy.

The feature selection for interval-valued data (IVD) aims to identify representative features from a large set of features, which can reduce the model complexity, minimize the training time, and enhance the generalization ability of the model. Addressing the inter-feature correlations in IVD, we propose a feature selection method called the maximum information coefficient for interval-valued data (IVD_MIC). First, the method balances the relationship between the midpoint and radius of IVD with an adjustment factor, constructing the interval-valued data unified representation frame (URF). Based on the URF, the method measures the degree of correlation between two features by calculating the maximum information coefficient, and obtains the maximum information coefficient matrix for IVD. Then the features with strong correlation are progressively removed from three perspectives(row, column, and both row and column), generating a series of corresponding candidate feature subsets. Finally, IVD_MIC is validated on candidate feature subsets to obtain the final classification accuracy and optimal feature subset. The experiment results on synthetic and real-world datasets with different classifiers demonstrate that the overall performance of IVD_MIC surpasses other methods. The average accuracy of IVD_MIC is higher, improving by 0.23%, 0.53% and 0.45% compared to the second-best method on LIBSVM, CART Tree and KNN, respectively.

Expressions serve as intuitive reflections of a person’s psychological state, making the extraction of effective features for accurate facial expression recognition a crucial research problem. However, when facial information is incomplete, the existing convolutional neural networks face some challenges in extracting features. To address this issue, this paper introduces a pyramidal convolutional attention residual network(PCARNet) based on the ResNet18. PCARNet combines the pyramidal convolution module and an improved convolutional attention mechanism to effectively extract expression features and achieve high-precision facial expression recognition. The proposed model utilizes pyramidal convolution to extract facial expression features at multiple scales, capturing both global and local information of the face. Grouped convolution is employed to reduce the computational complexity and the number of parameters. Additionally, to avoid the adverse effects of channel dimensionality reduction on the attention mechanism and enhance the capacity for information exchange across channels, the Share MLP module within the convolutional attention mechanism was replaced by a one-dimensional convolution with adaptive kernel size. The improved convolutional attention mechanism assigns weights to the extracted multiscale features based on both channel and spatial dimensions, enhancing the representation of crucial facial features. Experimental results demonstrate the high recognition accuracy of the proposed method on public datasets such as Fer2013, RAF-DB, and CK+. The accuracies achieved are 73.725%, 87.516%, and 95.455%, respectively. Compared to other methods, the proposed approach shows improvements of at least 1.4%, 2.4%, and 0.25% on the respective datasets, confirming its high reliability and performance.

(1) Background: This study seeks to employ a machine learning (ML) algorithm to forecast the risk of distant metastasis (DM) in patients with T1 and T2 gallbladder cancer (GBC); (2) Methods: Data of patients diagnosed with T1 and T2 GBC was obtained from SEER, encompassing the period from 2004 to 2015, were utilized to apply seven ML algorithms. These algorithms were appraised by the area under the receiver operating characteristic curve (AUC) and other metrics; (3) Results: This study involved 4371 patients in total. Out of these patients, 764 (17.4%) cases progressed to develop DM. Utilizing a logistic regression (LR) model to identify independent risk factors for DM of gallbladder cancer (GBC). A nomogram has been developed to forecast DM in early T-stage gallbladder cancer patients. Through the evaluation of different models using relevant indicators, it was discovered that Random Forest (RF) exhibited the most outstanding predictive performance; (4) Conclusions: RF has demonstrated high accuracy in predicting DM in gallbladder cancer patients, assisting clinical physicians in enhancing the accuracy of diagnosis. This can be particularly valuable for improving patient outcomes and optimizing treatment strategies. We employ the RF algorithm to construct the corresponding web calculator.

The split-sleeve cold expansion technology is widely used in the aerospace industry, particularly for fastening holes, to enhance the fatigue life of components. However, to ensure proper assembly and improve surface integrity, reaming of the cold-expanded holes is necessary. This study investigates the effects of cold expansion and reaming processes on the fatigue performance of 7050-T7451 aluminum alloy. Fatigue tests, residual stress measurements, and microstructural analyses of the hole edges were conducted on specimens with four different hole diameters after cold expansion and reaming. It was found that the depth of reaming significantly affects fatigue life. During the cold expansion process, the compressive residual stress formed around the hole effectively improves fatigue performance. The experiments demonstrated that reaming by 0.2 mm to 0.4 mm helps eliminate minor defects, thereby improving fatigue life. However, reaming beyond 0.5 mm may lead to stress relief and the removal of dense grains at the hole edges, reducing fatigue life. Therefore, determining the optimal reaming size is crucial for enhancing the reliability of aerospace fasteners.

BackgroundBlood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear.MethodsThis multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.ResultsThree hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198.ConclusionThis study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.

An eleven-wavelength-switchable thulium-doped fiber laser was proposed and demonstrated, incorporating an improved geta-shaped cavity providing bidirectional amplification, and a sandwich four-mode fiber Mach–Zehnder interferometer filter with curvature sensitivity. The filter was fabricated by splicing a segment of four-mode fiber (FMF) between two segments of a no-core fiber (NCF), with two segments of a single mode fiber (SMF) fused outside the two NCFs, and the structural order was SMF-NCF-FMF-NCF-SMF (SNFNS). The mode interference of the SNFNS filter was investigated theoretically in detail. The curvature characteristic was measured experimentally, and the maximum curvature sensitivity of the filter was 5.83 dB/m−1 in the ranges of 1.51 ∼ 2.26 m−1. By adjusting the curvature of the filter and polarization controllers, switchable eleven single-wavelength output can be obtained. The stability of the single-wavelength output was monitored with the fluctuations of the center wavelength and output power being less than 0.05 nm and 0.90 dB, respectively. Additionally, a slope efficiency of 9.797 % was achieved using a bidirectional amplifier configuration. The proposed laser may be suitable for mode-division multiplexing systems and optical sensor applications.

With the sharp increase of the global population, adequate food supply is a great challenge. Grain size is an essential determinant of rice yield and quality. It is a typical quantitative trait controlled by multiple genes. In this paper, we summarized the quantitative trait loci (QTL) that have been molecularly characterized and provided a comprehensive summary of the regulation mechanism and genetic pathways of rice grain size. These pathways include the ubiquitin-proteasome system, G-protein, mitogen-activated protein kinase, phytohormone, transcriptional factors, abiotic stress. In addition, we discuss the possible application of advanced molecular biology methods and reasonable breeding strategies, and prospective on the development of high-yielding and high-quality rice varieties using molecular biology techniques.

Abstract Background Lianhua Qingke (LHQK) is an effective traditional Chinese medicine used for treating acute tracheobronchitis. In this study, we evaluated the effectiveness of LHQK in managing airway mucus hypersecretion in the acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods The AECOPD model was established by subjecting male Wistar rats to 12 weeks of cigarette smoke (CS) exposure (80 cigarettes/day, 5 days/week for 12 weeks) and intratracheal lipopolysaccharide (LPS) exposure (200 μg, on days 1, 14, and 84). The rats were divided into six groups: control (room air exposure), model (CS + LPS exposure), LHQK (LHQK-L, LHQK-M, and LHQK-H), and a positive control group (Ambroxol). H&E staining, and AB-PAS staining were used to evaluate lung tissue pathology, inflammatory responses, and goblet cell hyperplasia. RT-qPCR, immunohistochemistry, immunofluorescence and ELISA were utilized to analyze the transcription, expression and secretion of proteins related to mucus production in vivo and in the human airway epithelial cell line NCI-H292 in vitro. To predict and screen the active ingredients of LHQK, network pharmacology analysis and NF-κB reporter system analysis were employed. Results LHQK treatment could ameliorate AECOPD-triggered pulmonary structure damage, inflammatory cell infiltration, and pro-inflammatory cytokine production. AB-PAS and immunofluorescence staining with CCSP and Muc5ac antibodies showed that LHQK reduced goblet cell hyperplasia, probably by inhibiting the transdifferentiation of Club cells into goblet cells. RT-qPCR and immunohistochemistry of Muc5ac and APQ5 showed that LHQK modulated mucus homeostasis by suppressing Muc5ac transcription and hypersecretion in vivo and in vitro, and maintaining the balance between Muc5ac and AQP5 expression. Network pharmacology analysis and NF-κB luciferase reporter system analysis provided insights into the active ingredients of LHQK that may help control airway mucus hypersecretion and regulate inflammation. Conclusion LHQK demonstrated therapeutic effects in AECOPD by reducing inflammation, suppressing goblet cell hyperplasia, preventing Club cell transdifferentiation, reducing Muc5ac hypersecretion, and modulating airway mucus homeostasis. These findings support the clinical use of LHQK as a potential treatment for AECOPD.

Gene editing with a CRISPR/Cas system is a novel potential strategy for treating human diseases. Pharmacological inhibition of phosphoinositide 3-kinase (PI3K) δ suppresses retinal angiogenesis in a mouse model of oxygen-induced retinopathy. Here we show that an innovative system of adeno-associated virus (AAV)-mediated CRISPR/nuclease-deficient (d)CasX fused with the Krueppel-associated box (KRAB) domain is leveraged to block (81.2% ± 6.5%) in vitro expression of p110δ, the catalytic subunit of PI3Kδ, encoded by Pik3cd. This CRISPR/dCasX-KRAB (4, 269 bp) system is small enough to be fit into a single AAV vector. We then document that recombinant AAV serotype (rAAV)1 efficiently transduces vascular endothelial cells from pathologic retinal vessels, which show high expression of p110δ; furthermore, we demonstrate that blockade of retinal p110δ expression by intravitreally injected rAAV1-CRISPR/dCasX-KRAB targeting the Pik3cd promoter prevents (32.1% ± 5.3%) retinal p110δ expression as well as pathological retinal angiogenesis in a mouse model of oxygen-induced retinopathy. These data establish a strong foundation for treating pathological angiogenesis by AAV-mediated CRISPR interference with p110δ expression.

As the scale of units within virtual power plants (VPPs) continues to expand, establishing an effective operational game model for these internal units has become a pressing issue for enhancing management and operations. This paper integrates photovoltaic generation, wind power, energy storage, and constant-temperature responsive loads, and it also considers micro gas turbines as auxiliary units, collectively forming a typical VPP case study. An operational optimization model was developed for the VPP control center and the micro gas turbines, and the game relationship between them was analyzed. A Stackelberg game model between the VPP control center and the micro gas turbines was proposed. Lastly, an improved D3QN (Dueling Double Deep Q-network) algorithm was employed to compute the VPP’s optimal operational strategy based on Stackelberg game theory. The results demonstrate that the proposed model can balance the energy complementarity between the VPP control center and the micro gas turbines, thereby enhancing the overall economic efficiency of operations.

Abstract Background The number of pneumocystis pneumonia (PCP) cases is increasing in immunocompromised patients without human immunodeficiency virus infection (HIV), causing serious morbidity with high mortality. Trimethoprim/sulfamethoxazole (TMP/SMZ) monotherapy has limited effectiveness in the treatment of PCP. Clinical data on whether initial caspofungin plus TMP/SMZ for this disease is superior to monotherapy in non-HIV-infected patients are limited. We aimed to compare the clinical effectiveness of these regimens for severe PCP in non-HIV patients. Methods A retrospective study reviewed 104 non-HIV-infected patients with confirmed PCP in the intensive care unit between January 2016 and December 2021. Eleven patients were excluded from the study because TMP/SMZ could not be used due to severe hematologic disorders or clinical data were missing. All enrolled patients were divided into three groups according to different treatment strategies: Group 1 received TMP/SMZ monotherapy, Group 2 received caspofungin combined with TMP/SMZ as first-line therapy, and Group 3 initially received TMP/SMZ monotherapy and later received caspofungin as salvage therapy. The clinical characteristics and outcomes were compared among the groups. Results A total of 93 patients met the criteria. The overall positive response rate of anti-PCP treatment was 58.06%, and the overall 90-day all-cause mortality rate was 49.46%. The median APACHE II score was 21.44. The concurrent infection rate was 74.19%, among whom 15.05% (n = 14) of those patients had pulmonary aspergillosis, 21.05% (n = 20) had bacteremia, and 23.65% (n = 22) had CMV infections. The patients who received initial caspofungin combination with TMP/SMZ had the best positive response rate (76.74%) compared to others (p = 0.001). Furthermore, the group that received initial caspofungin combined with TMP/SMZ had a 90-day all-cause mortality rate (39.53%) that was significantly different from that of the shift group (65.51%, p = 0.024), but this rate showed no statistically significant difference compared with that in the monotherapy group (48.62%, p = 0.322). None of the patients had serious adverse events from caspofungin therapy. Conclusions For non-HIV-infected patients with severe PCP, initial combination therapy with caspofungin and TMP/SMZ is a promising first-line treatment option compared with TMP/SMZ monotherapy and combination therapy as salvage therapy.

This study aimed to investigate the minimum number of operations required for itinerant nurses in the operating room to master the skills needed to operate the Ti-robot-assisted spinal surgery equipment. Additionally, we aimed to provide a corresponding basis for the development of qualification admission criteria and skill training for nurses who cooperate with this type of surgery. Nine operating room itinerant nurses independently performed Ti-robot equipment simulations using a spine model as a tool, with 16 operations per trainee. Four evaluation indices were recorded: time spent on equipment preparation and line connections, time spent on image acquisition and transmission, time spent on surgical spine screw placement planning, and time spent on robot arm operation. Individual and general learning curves were plotted using cumulative sum analysis. The number of cases in which the slope of the individual learning curves began to decrease was 3-11 cases, and the number of cases in which the slope of the general learning curve began to decrease was 8 cases. The numbers of cases in which the learning curves began to decrease in the four phases were the 5th, 8th, 11th, and 3rd cases. Itinerant nurses required at least eight cases to master the equipment operation skills of Ti-robot-assisted spinal surgery. Among the four phases, the image acquisition and transmission phases and the surgical spine screw placement planning phase were the most difficult and must be emphasized in future training.

ABSTRACTAlthough previous studies have reported the dysregulation of respiratory tract microbiota in infectious diseases, insufficient data exist regarding respiratory microbiota imbalances in the lower respiratory tracts (LRTs) of children with Mycoplasma pneumoniae pneumonia (MPP). Here, we analysed the microbial community using 16S rRNA gene sequencing. Finally, bronchoalveolar lavage fluid (BALF) samples from 158 children with MPP and 29 with bacterial or viral pneumonia (control group) were collected. The diversity of the microbial community was significantly different between the two groups. A significantly increased abundance of Tenericutes and Mycoplasma was detected in the MPP group, exceeding 67% and 65% of the total bacterial population, respectively. Using Mycoplasma abundance as the diagnostic method, the sensitivity and specificity of the model was 97.5% and 96.6%, respectively. Compared to the mild MPP group, lower alpha diversity and significantly increased Mycoplasma abundance were found in the severe MPP group (P

Abstract Laryngeal cancer is one of the most common malignant tumors of the head and neck, accounting for about 20%. Due to its high disability rate, the diagnosis and treatment of laryngeal cancer have always been the focus and difficulty of head and neck surgery. The outcome of cancer is affected not only by tumor-related factors but also by host-related factors, especially systemic inflammation, this is usually reflected by a variety of hematological markers. Studies have confirmed that there is a significant correlation between hematological markers and the occurrence, development, and prognosis of laryngeal squamous cell carcinoma (LSCC), and has a certain value in auxiliary diagnosis and prognosis prediction of LSCC. We reviewed various hematological markers related to LSCC aim to summarize the role and research progress of hematological markers in LSCC.

Abstract Background Exosomes derived from bone marrow mesenchymal stem cells (BMSC-Exos) are considered as candidates for osteoporosis (OP) therapy. Estrogen is critical in the maintenance of bone homeostasis. However, the role of estrogen and/or its receptor in BMSC-Exos treatment of OP, as well as its methods of regulation during this process remain unclear. Methods BMSCs were cultured and characterized. Ultracentrifugation was performed to collect BMSC-Exos. Transmission electron microscopy, nanoparticle tracking analysis, and western blotting were used to identify BMSC-Exos. We examined the effects of BMSC-Exos on the proliferation, osteogenic differentiation, mineralization, and cell cycle distribution of MG-63 cells. The protein expression of estrogen receptor α (ERα) and the phosphorylation of ERK were investigated through western blotting. We determined the effects of BMSC-Exos on the prevention of bone loss in female rats. The female Sprague–Dawley rats were divided into three groups: the sham group, ovariectomized (OVX) group, and the OVX + BMSC-Exos group. Bilateral ovariectomy was performed in the OVX and OVX + BMSC-Exos groups, while a similar volume of adipose tissue around the ovary was removed in the sham group. The rats in OVX group and OVX + BMSC-Exos group were given PBS or BMSC-Exos after 2 weeks of surgery. Micro-CT scanning and histological staining were used to evaluate the in vivo effects of BMSC-Exos. Results BMSC-Exos significantly enhanced the proliferation, alkaline phosphatase activity, and the Alizarin red S staining in MG-63 cells. The results of cell cycle distribution demonstrated that BMSC-Exos increased the proportion of cells in the G2 + S phase and decreased the proportion of cells in the G1 phase. Moreover, PD98059, an inhibitor of ERK, inhibited both the activation of ERK and the expression of ERα, which were promoted by administration of BMSC-Exos. Micro-CT scan showed that in the OVX + BMSC-Exos group, bone mineral density, bone volume/tissue volume fraction, trabecular number were significantly upregulated. Additionally, the microstructure of the trabecular bone was preserved in the OVX + BMSC-Exos group compared to that in the OVX group. Conclusion BMSC-Exos showed an osteogenic-promoting effect both in vitro and in vivo, in which ERK-ERα signaling might play an important role.

A comparative experimental and numerical study of the impact behaviour of carbon-fiber-reinforced thermoplastic (TP) and thermoset (TS) composites has been carried out. On the one hand, low velocity impact (LVI) tests were performed on TP and TS composites with different lay-up sequences at different energy levels, and the damage modes and microscopic damage mechanisms after impact were investigated using macroscale inspection, C-scan inspection, and X-ray-computed tomography. The comparative results show that the initial damage valve force under LVI depends not only on the material, but also on the layup sequence. The initial valve force of the P2 soft layer with lower stiffness is about 11% lower than that of the P1 quasi-isotropic layer under the same material, while the initial valve force of thermoplastic composites is about 28% lower than that of thermoset composites under the same stacking order. Under the same stacking order and impact energy level, the damage area and depth of TP composites are smaller than those of TS composites; while under the same material and impact energy level, the indentation depth of P2 plies is greater than that of P1 plies, and the damage area of P2 plies is smaller than that of P1 plies, but the change of thermoplastic composites is not as obvious as that of thermoset composites. This indicates that TP composites have a higher initial damage threshold energy and impact resistance at the same lay-up order, while increasing the lay-up ratio of the same material by 45° improves the impact resistance of the structure. In addition, a damage model based on continuum damage mechanics (CDM) was developed to predict different damage modes of thermoplastic composites during low velocity impact, and the analytical results were compared with the experimental results. At an impact energy of 4.45 J/mm, the error of the initial damage valve force is 5.26% and the error of the maximum impact force is 4.36%. The simulated impact energy and impact velocity curves agree with the experimental results, indicating that the finite element model has good reliability.

Abstract LHQK is a patented Traditional Chinese Medicine (TCM) which is clinically used for acute tracheobronchitis, cough, and other respiratory diseases. Recent studies have proved that LHQK exhibits excellent clinical efficacy in the treatment of acute lung injury (ALI). However, the corresponding mechanisms remain largely unexplored. In this study, we investigated the effects and the underlying mechanisms of LHQK on lipopolysaccharide (LPS)‐induced ALI in mice. The pathological examination, inflammatory cytokines assessments, and mucus secretion evaluation indicated that administration of LHQK ameliorated LPS‐induced lung injury, and suppressed the secretion of Muc5AC and pro‐inflammatory cytokines (IL‐6, TNF‐α, and IL‐1β) in plasma and BALF. Furthermore, the results of cell‐free DNA level showed that LHQK significantly inhibited LPS‐induced NETs formation. Western blot revealed that LHQK effectively inhibited LPS‐triggered pyroptosis in the lung. In addition, RNA‐Seq data analysis, relatively bioinformatic analysis, and network pharmacology analysis revealed that LHQK and relative components may play multiple protective functions in LPS‐induced ALI/acute respiratory distress syndrome (ARDS) by regulating multiple targets directly or indirectly related to NETs and pyroptosis. In conclusion, LHQK can effectively attenuate lung injury and reduce lung inflammation by inhibiting LPS‐induced NETs formation and pyroptosis, which may be regulated directly or indirectly by active compounds of LHQK.

Hydrangea macrophylla is popular for its unique physiological characteristics and changeable colors. Previous studies have shown that the pH of the vacuoles of the sepal cells of hydrangea affects the color of the sepals. Located on the vacuolar membrane, NHX1 is an important H+ proton pump that drives the exchange of metal ions. This proton pump affects the physiological environment by controlling the accumulation of H+ in the vacuole. In hydrangea, the HmNHX1 gene has an open reading frame of 1626 bp and encodes a total of 541 amino acids. Bioinformatic analysis showed that HmNHX1, which encodes a Na+/H+ exchanger, is located on the vacuolar membrane. Tissue-specific expression analysis showed that the expression of this gene in the treatment group was higher than that in the control group. The ion flux in the vacuoles of colored hydrangea in the treatment group and the control group were measured, and the results showed that HmNHX1 was indeed a Na+/H+ exchanger. When the results of the HmNHX1 expression analysis and ion flux measurements are combined, it can be seen that HmNHX1 regulates the accumulation of H+ in the vacuole, ultimately affecting the color of the plant.

Face anti-spoofing refers to the computer determining whether the face detected is a real face or a forged face. In user authentication scenarios, photo fraud attacks are easy to occur, where an illegal user logs into the system using a legitimate user’s picture. Aiming at this problem and the influence of illumination in real-time video face recognition, this paper proposes a real-time face detection method based on blink detection. The method first extracts the image texture features through the LBP algorithm, which eliminates the problem of illumination changes to a certain extent. Then the extracted features are input into the ResNet network, and the facial feature extraction is enhanced by adding an attention mechanism is added to enhance the face feature extraction. Meanwhile, the BiLSTM method is used to extract the temporal characteristics of images from different angles or at different times to obtain more facial details. In addition, the fusion of local and global features is realized by SPP pooling, which enriches the expression ability of feature maps and improves detection accuracy. Finally, the eye EAR value is calculated by the face key point detection technology to achieve face anti-spoofing, and then the real-time face recognition against fraud is realized. The experimental results show that the algorithm proposed in this paper has good accuracy on NUAA, CASIA-SURF and CASIA-FASD datasets, which can reach 99.48%, 98.65% and 99.17%, respectively.

Abstract Although titanium (Ti) and Ti-based alloy have been widely used as dental and orthopedic implant materials, its bioinertness hindered the rapid osseointegration. Therefore, it is recommended to acquire ideal topographic and chemical characteristics through surface modification methods. 3D printing is a delicate manufacture technique which possesses superior controllability and reproducibility. While aspirin serve as a well-established non-steroidal anti-inflammatory agent. Recently, the importance of immune system in regulating bone dynamics has attracted increasing attention. We herein superimposed the aspirin/poly (lactic–co–glycolic acid) (ASP/PLGA) coating on the 3D-printed Ti-6Al-4V surface with uniform micro-structure to establish the Ti64-M-ASP/PLGA substrate. Scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS) and contact angle test confirmed the successful fabrication of the Ti64-M-ASP/PLGA substrate, with increased wettability and sustained release pattern of ASP. Compared with the Ti64 base material, the Ti64-M-ASP/PLGA substrate showed enhanced M2 and depressed M1 genes and proteins expressions in macrophages. The novel Ti64-M-ASP/PLGA substrate also displayed enhanced osteoblast proliferation, adhesion, extracellular mineralization ability and osteogenic gene expressions when cultured with macrophage conditioned medium in vitro. Furthermore, rat femora implantation model was used for in vivo evaluation. After 4 weeks of implantation, push out test, micro-computed tomography (micro-CT) and histological analyses all confirmed the superior osseointegration capabilities of the Ti64-M-ASP/PLGA implant than the other groups. Our study revealed the synergistic role played by 3D-printed micro topography and immunoregulatory drug aspirin in promoting osteogenesis in vitro and accelerating osseointegration in vivo, thus providing a promising method for better modifying the implant surface. Graphical abstract

Under specific cultivation conditions, the sepal color of Hydrangea macrophylla (H. macrophylla) changes from red to blue due to the complexation of aluminum ions (Al3+), delphinidin 3-glucoside, and copigments. However, this phenomenon cannot occur in all cultivars despite the presence of sufficient Al3+ and copigments. To explore the mechanism of sepal bluing in H. macrophylla, there is an urgent need to study the molecular regulation of the anthocyanin biosynthesis pathway. However, the key structural genes, other than CHS, regulating anthocyanin biosynthesis in the sepals of H. macrophylla have not been identified. In this study, based on full-length transcriptome data from H.macrophylla ‘Bailmer’, the key structural genes regulating anthocyanin biosynthesis in the sepals of H. macrophylla were isolated and investigated. Ultimately, seven key structural genes, HmCHS1, HmCHI, HmF3H1, HmF3′H1, HmF3′5′H, HmDFR2, and HmANS3, were demonstrated to show high expression levels in colored sepals. The expression levels of these seven genes increased gradually with the development of sepals and were highest in the full-bloom stage. The trend of gene expression was consistent with the trend of anthocyanin contents. It was concluded that the seven selected genes were involved in anthocyanin biosynthesis in the sepals of H. macrophylla. The full-length sequence data have been deposited into the NCBI Sequence Read Archive (SRA) with accession number PRJNA849710. This study lays a good foundation for the further elucidation of the molecular mechanism of sepal coloration in H. macrophylla.

Cancer cells and ischemic diseases exhibit unique metabolic responses and adaptations to energy stress. Forkhead box O 3a (FoxO3a) is a transcription factor that plays an important role in cell metabolism, mitochondrial dysfunction and oxidative stress response. Although the AMP-activated protein kinase (AMPK)/FoxO3a signaling pathway plays a pivotal role in maintaining energy homeostasis under conditions of energy stress, the role of AMPK/FoxO3a signaling in mitochondria-associated ferroptosis has not yet been fully elucidated. We show that glucose starvation induced AMPK/FoxO3a activation and inhibited ferroptosis induced by erastin. Inhibition of AMPK or loss of FoxO3a in cancer cells under the glucose starvation condition can sensitize these cells to ferroptosis. Glucose deprivation inhibited mitochondria-related gene expression, reduced mitochondrial DNA(mtDNA) copy number, decreased expression of mitochondrial proteins and lowered the levels of respiratory complexes by inducing FoxO3a. Loss of FoxO3a promoted mitochondrial membrane potential hyperpolarization, oxygen consumption, lipid peroxide accumulation and abolished the protective effects of energy stress on ferroptosis in vitro. In addition, we identified a FDA-approved antipsychotic agent, the potent FoxO3a agonist trifluoperazine, which largely reduced ferroptosis-associated cerebral ischemia-reperfusion (CIR) injuries in rats through AMPK/FoxO3a/HIF-1α signaling and mitochondria-dependent mechanisms. We found that FoxO3a binds to the promoters of SLC7A11 and reduces CIR-mediated glutamate excitotoxicity through inhibiting the expression of SLC7A11. Collectively, these results suggest that energy stress modulation of AMPK/FoxO3a signaling regulates mitochondrial activity and alters the ferroptosis response. The regulation of FoxO3a by AMPK may play a crucial role in mitochondrial gene expression that controls energy balance and confers resistance to mitochondria-associated ferroptosis and CIR injuries.

Acidification and heavy metal stress pose challenging threats to the terrestrial environment. This investigation endeavors to scrutinize the combined effects of vermicompost and steel slag, either singularly or in concert with Ryegrass (Lolium perenne L.), on the remediation of acidic soil resulting from sulfide copper mining. The findings illuminate substantial ameliorations in soil attributes. The application of these amendments precipitates an elevation in soil pH of 1.39–3.08, an augmentation in organic matter of 4.05–8.65, a concomitant reduction in total Cu content of 43.2–44.7%, and a marked mitigation in Cu bioavailability of 64.2–80.3%. The pronounced reduction in soil Cu bioavailability within the steel slag treatment group (L2) is noteworthy. Characterization analyses of vermicompost and steel slag further elucidate their propensity for sequestering Cu2+ ions in the soil matrix. Concerning botanical analysis, the vermicompost treatment group (L1) significantly enhances soil fertility, culminating in the accumulation of 208.35 mg kg−1 of Cu in L. perenne stems and 1412.05 mg kg−1 in the roots. Additionally, the introduction of vermicompost and steel slag enriches soil OTU (Operational Taxonomic Units) quantity, thereby augmenting soil bacterial community diversity. Particularly noteworthy is the substantial augmentation observed in OTU quantities for the vermicompost treatment group (L1) and the combined vermicompost with steel slag treatment group (L3), exhibiting increments of 126.04% and 119.53% in comparison to the control (CK). In summation, the application of vermicompost and steel slag efficaciously diminishes the bioavailability of Cu in the soil, augments Cu accumulation in L. perenne, induces shifts in the soil microbial community structure, and amplifies soil bacterial diversity. Crucially, the concomitant application of vermicompost and steel slag emerges as a holistic and promising strategy for the remediation of sulfide copper mining acidic soil.

The cultivation of poplar trees is hindered by persistent cropping challenges, resulting in reduced wood productivity and increased susceptibility to soil-borne diseases. These issues primarily arise from alterations in microbial structure and the infiltration of pathogenic fungi. To investigate the impact on soil fertility, we conducted an analysis using soil samples from both perennial poplar trees and three successive generations of continuously cropped poplar trees. The quantity and community composition of bacteria and fungi in the rhizosphere were assessed using the Illumina MiSeq platform. The objective of this study is to elucidate the impact of continuous cropping challenges on soil fertility and rhizosphere microorganisms in poplar trees, thereby establishing a theoretical foundation for investigating the mechanisms underlying these challenges. The study found that the total bacteria in the BT group is 0.42 times higher than the CK group, and the total fungi is 0.33 times lower than the CK group. The BT and CK groups presented relatively similar bacterial richness and diversity, while the indices showed a significant (p < 0.05) higher fungal richness and diversity in the CK group. The fractions of Bacillus were 2.22% and 2.41% in the BT and CK groups, respectively. There was a 35.29% fraction of Inocybe in the BT group, whereas this was barely observed in the CK group. The fractions of Geopora were 26.25% and 5.99%, respectively in the BT and CK groups. Modifying the microbial community structure in soil subjected to continuous cropping is deemed as the most effective approach to mitigate the challenges associated with this agricultural practice.

Patient-derived tumor xenografts (PDXs) are a powerful tool for drug discovery and screening in cancer. However, current studies have led to little understanding of genotype mismatches in PDXs, leading to massive economic losses. Here, we established PDX models from 53 lung cancer patients with a genotype matching rate of 79.2% (42/53). Furthermore, 17 clinicopathological features were examined and input in stepwise logistic regression (LR) models based on the lowest Akaike information criterion (AIC), least absolute shrinkage and selection operator (LASSO)-LR, support vector machine (SVM) recursive feature elimination (SVM-RFE), extreme gradient boosting (XGBoost), gradient boosting and categorical features (CatBoost), and the synthetic minority oversampling technique (SMOTE). Finally, the performance of all models was evaluated by the accuracy, area under the receiver operating characteristic curve (AUC), and F1 score in 100 testing groups. Two multivariable LR models revealed that age, number of driver gene mutations, epidermal growth factor receptor (EGFR) gene mutations, type of prior chemotherapy, prior tyrosine kinase inhibitor (TKI) therapy, and the source of the sample were powerful predictors. Moreover, CatBoost (mean accuracy = 0.960; mean AUC = 0.939; mean F1 score = 0.908) and the eight-feature SVM-RFE (mean accuracy = 0.950; mean AUC = 0.934; mean F1 score = 0.903) showed the best performance among the algorithms. Meanwhile, application of the SMOTE improved the predictive capability of most models, except CatBoost. Based on the SMOTE, the ensemble classifier of single models achieved the highest accuracy (mean = 0.975), AUC (mean = 0.949), and F1 score (mean = 0.938). In conclusion, we established an optimal predictive model to screen lung cancer patients for non-obese diabetic (NOD)/Shi-scid, interleukin-2 receptor (IL-2R) γnull (NOG)/PDX models and offer a general approach for building predictive models.

The carbon emission right is considered as an effective way to reduce carbon emissions in the power industry, especially under the global goal of carbon neutral. Considering that carbon emission cost will affect long-term profits, the bidding strategies of power generation companies in electricity market and carbon emission market need to be coordinated. Given this background, a bi-level bidding strategies optimization model is proposed for power generation companies, which considers the carbon emission right and aims to maximize their annual power generation benefits. The purchase of carbon emission right at the beginning of the year is optimized in the upper-level model with the goal of maximizing the expected annual income and the uncertainty of transaction volume in monthly bidding market considered. The remaining carbon quota, penalty electricity price, and uncertainty of the competitor’s quotation in monthly electricity market are considered in the lower-level model, based on which the bidding strategy for power generation company with the goal of maximizing the monthly expected income is proposed, and the power generation company’s electricity market bidding model and its clearing results are simulated. Simulation results shows that power generation companies’ purchases of carbon emission rights and their bidding strategies in the monthly market are affected by the carbon emission penalty price. The higher the penalty price is, the greater the quotation and the purchase of carbon emission rights are.

ObjectiveTo investigate the clinical efficacy and prognostic factors of transnasal endoscopic optic decompression in the treatment of traumatic optic neuropathy (TON).MethodsA retrospective analysis was performed on 13 TON patients in The Seventh Affiliated Hospital of Sun Yat-sen University and Shenzhen Eye Hospital in Shenzhen City (China) from June 2020 to April 2022. These patients had received transnasal endoscopic optic decompression, and hormonal and neurotrophic drugs were given after surgery. Visual acuity (VA) improvement was used as the criterion to judge clinical efficacy.ResultsIn a total of 13 patients, 13 injured eyes (12 men and 1 woman; mean age, 28.0 ± 11.8 years) received transnasal endoscopic optic decompression. After surgery, nine patients had improved VA, whereas four patients failed to show any improvement, resulting in a total effective rate of 69.2%. Of the six patients with no light perception preoperatively, three had effective results after the operation, giving an effective rate of 50.0%. Of the seven patients with residual light sensation preoperatively, six had effective results after the operation, giving an effective rate of 85.7%. Of the 10 patients operated on within 7 days after injury, seven had effective results, giving an effective rate of 70%. Of the three patients injured and operated on after 7 days, two had effective results, giving an effective rate of 66.7%.ConclusionTransnasal endoscopic optic nerve decompression is an effective treatment method for TON. The presence of residual light perception and the timing of surgery within 7 days are crucial to the prognosis.

BackgroundMycoplasma pneumoniae (MP) is a commonly occurring pathogen causing community-acquired pneumonia (CAP) in children. The global prevalence of macrolide-resistant MP (MRMP) infection, especially in Asian regions, is increasing rapidly. However, the prevalence of MRMP and its clinical significance during the COVID-19 pandemic is not clear.MethodsThis study enrolled children with molecularly confirmed macrolide-susceptible MP (MSMP) and MRMP CAP from Beijing Children’s Hospital Baoding Hospital, Capital Medical University between August 2021 and July 2022. The clinical characteristics, laboratory findings, chest imaging presentations, and strain genotypes were compared between patients with MSMP and MRMP CAP.ResultsA total of 520 hospitalized children with MP-CAP were enrolled in the study, with a macrolide resistance rate of 92.7%. Patients with MRMP infection exhibited more severe clinical manifestations (such as dyspnea and pleural effusion) and had a longer hospital stay than the MSMP group. Furthermore, abnormal blood test results (including increased LDH and D-dimer) were more common in the MRMP group (P

In this paper, the fuzzy scattering problem with semicircular depressions on the boundary of a band-shaped elastic plate with steady SH guided wave incident is studied and an analytical solution is given. First, the SH guided wave is constructed by the guided wave expansion method, and then the scattered wave satisfying the free condition of the boundary stress of the strip domain is constructed by the cumulative mirror method. Finally, a definite solution equation is obtained based on the fact that the shear stress at the edge of the semi-circular recessed hole is zero. In this paper, the ambiguity of the number of waves and the width of the bands is taken into account. In order to avoid the irreversibility of interval algorithm and the difficulty of solving non-linear equations, the membership function of fuzzy quantity is segmented to make the membership degree and fuzzy quantity correspond respectively. A deterministic problem that translates into piecewise processing. Two numerical examples are given to examine the changes in fuzzy response of different numbers of fuzzy waves and fuzzy thicknesses to the dynamic stress concentration factor of the hoop at the collapse limit.

In this paper, the damage initiation/propagation mechanisms and failure modes of open-hole carbon fiber-reinforced thermoplastic composites and thermosetting composites with tension, compression, and bearing loads are investigated, respectively, by experiments and finite element simulations. The experimental evaluations are performed on the specimens using the Combined Loading Compression (CLC) test method, the tensile test method, and the single-shear test method. The differences in macroscopic damage initiation, evolution mode, and damage characteristics between thermoplastic composite materials and thermosetting composite material open-hole structures are obtained and analyzed under compressive load. Based on scanning electron microscope SEM images, a comparative analysis is conducted on the micro-failure modes of fibers, matrices, and fiber/matrix interfaces in the open-hole structures of thermoplastic and thermosetting composites under compressive load. The differences between thermoplastic and thermosetting composites were analyzed from the micro-failure mechanism. Finally, based on continuum damage mechanics (CDM), a damage model is also developed for predicting the initiation and propagation of damage in thermoplastic composites. The model, which can capture fiber breakage and matrix crack, as well as the nonlinear response, is used to conduct virtual compression tests, tensile test, and single-shear test, respectively. Numerical simulation results are compared with the extracted experimental results. The displacement-load curve and failure modes match the experimental result, which indicates that the finite element model has good reliability.

Objective: Based on the expression changes in the TGF-β/ALK5/Smad2/3 signal transduction pathway, the repair of cartilage injury in the rabbit knee joint was investigated and evaluated by oral administration of naringin in combination with acellular dermal matrix implantation. Methods: First, twenty New Zealand white rabbits were randomly divided into five groups: a sham operation group (Sham group), a model group (Mod group), a naringin group (Nar group), an acellular dermal matrix group (ADM group), a naringin ​+ ​acellular dermal matrix group (Nar/ADM group). After the 12th week, the repaired tissues were assessed for histomorphology and repair content of the repaired site by observing the morphological characteristics of articular cartilage. The International Cartilage Repair Society (ICRS)'s macroscopic evaluation of the cartilage repair scale and the quantitative scoring repair effect of the modified O'Driscoll grading system were used as evaluation criteria. In addition, the structure of the rabbit knee joint was evaluated by micro-CT scan, histological staining (H & E staining, Alcian blue staining, Safranin-O staining) and immunohistochemical staining (TGF-β2 immunostaining, TGF-β3 immunostaining, Sox-9 immunostaining). Results: ① The observation of the repair morphology of joint defect tissues showed that the repair effects of the Nar and ADM groups were better than that of the Mod group, and the repair effect of Nar/ADM group was the best (P

To achieve the digitization of all traffic infrastructure elements and enable three-dimensional digital representation of physical facilities, a multilevel road three-dimensional reverse modeling method is proposed based on road point cloud data obtained by a vehicle laser scanning system. First, based on the distribution characteristics of each target structure in the road scene and the modeling requirements, a levels of detail (LOD) modeling specification is designed, and the required feature data format for each level is defined. Next, the three-dimensional characteristic parameters needed for modeling are extracted from the vehicle point cloud data. Finally, the continuous quadrilateral algorithm is used to reconstruct the road model, the topological structure relationship algorithm is used to reconstruct the intersection model, and the instantiation lofting technology is used to reconstruct the rod-shaped target model, all based on the three-dimensional modeling platform. This approach allows for the rapid reverse reconstruction of three-dimensional road models with different LOD levels. The point cloud data of two sections of urban roads with different slopes and one section of expressways were modeled and compared with the original vehicle-mounted laser point cloud data. The data volume of different level models decreases with decreasing model fineness, and the LOD1 level model has the highest similarity with point cloud data, at approximately 92.17%. The similarity of LOD2 and LOD3 decreases in turn, at 82.91% and 75.25%, respectively. For flat or undulating roads, the overall accuracy of the nearest point distance between different levels of road models and point cloud data is better than 10 cm, significantly higher than that of traditional manual modeling. The results demonstrate that vehicle mobile laser scanning technology provides new modeling data for the rapid realization of three-dimensional reverse reconstruction of large-scale traffic infrastructure. Automatic modeling technology can effectively improve modeling efficiency, reduce data redundancy, and ensure model quality.

Abstract Temporal satellite networks can accurately describe the dynamic process of satellite networks by considering the interaction relationship and interaction sequence between satellite nodes. In addition, the measurement of node importance in satellite networks plays a crucial role in understanding the structure and function of the network. The classical supra-adjacency matrix (SAM) temporal model identifies the key nodes in the temporal network to some extent, which ignores the differences of inter-layer connectivity relationships leading to the inability to reflect the dynamic variations of satellite nodes. Therefore, the evaluation method based on time slot correlation is proposed to measure the importance of satellite nodes in this paper. Firstly, the correlation coefficient of time slot nodes is defined to measure the coupling relationship of adjacent time slots. Secondly, the dynamic supra-adjacency matrix (DSAM) temporal network model is proposed considering the correlation between adjacent time slots and the characteristics of link time. Finally, the node importance ranking results in each time slot and a global perspective are obtained by utilizing the eigenvector centrality. Experimental simulations of the Iridium and Orbcomm constellations demonstrate that the DSAM method has a relatively accurate recognition rate and high stability.

Dynamic monitoring data of groundwater level is an important basis for understanding the current situation of groundwater development and for the utilization and planning of sustainable exploitation. Dynamic monitoring data of groundwater level are typical spatio-temporal sequence data, which have the characteristics of non-linearity and strong spatio-temporal correlation. The trend of dynamic change of groundwater level is the key factor for the optimal allocation of groundwater resources. However, most of the existing groundwater level prediction models are insufficient in considering temporal and spatial factors and their spatio-temporal correlation. Therefore, construction of a space–time prediction model of groundwater level considering space–time factors and improving the prediction accuracy of groundwater level dynamic changes is of considerable theoretical and practical importance for the sustainable development of groundwater resources utilization. Based on the analysis of spatial–temporal characteristics of groundwater level of the pore confined aquifer II of Changwu area in the Yangtze River Delta region of China, the wavelet transform method was used to remove the noise in the original data, and the K-nearest neighbor (KNN) method was used to calculate the water level. The spatial–temporal dataset and the long short-term memory (LSTM) were reconstructed by screening the spatial correlation of the monitoring wells in the study area. A spatio-temporal KNN-LSTM prediction model for groundwater level considering spatio-temporal factors was also constructed. The reliability and accuracy of KNN-LSTM, LSTM, support vector regression (SVR), and autoregressive integrated moving average (ARIMA) model were evaluated by a cross-validation algorithm. Results showed that the prediction accuracy of KNN-LSTM is 20.68%, 46.54%, and 55.34% higher than that of the other single prediction models (LSTM, SVR, and ARIMA, respectively). HIGHLIGHTS A KNN-LSTM spatio-temporal prediction model for groundwater level is proposed.; It is vital to use wavelet transform to denoise the original data before prediction.; KNN-LSTM has better applicability and accuracy than traditional single random models.;