An International Consensus Survey among Pediatric Surgeons on the Role of Appendectomy in Malrotation.

Introduction: Ladd's procedure, originally described in 1936 for the treatment of malrotation, does not traditionally include appendectomy as a standard step. We conducted a multinational survey to investigate the current consensus on the role of appendectomy in Ladd's procedure. Methodology: An anonymous online survey was distributed to pediatric surgeons worldwide. The survey collected demographic data and explored surgical preferences related to the management of malrotation. Open-ended questions were used to assess the opinions regarding the necessity of appendectomy, decision-making factors, and complications associated with appendectomy during Ladd's procedure. Results: A total of 343 responses were received from 46 countries. Of the respondents, 319 (93%) were consultants and 24 (7%) were residents/trainees. When asked about the choice between open and laparoscopic Ladd's procedure, 292 (85%) preferred open surgery. Overall, 184 (53%) respondents favored appendectomy in both open and laparoscopic Ladd's procedure. Furthermore, 172 (50%) surgeons advocated for appendectomy in all malrotation cases, citing concerns about potential future appendicitis. While differences existed between all comparisons, none of them reached statistical significance. The factors influencing the decision to preserve the appendix included the risk of postoperative complications and the potential future use of the appendix as a surgical conduit. The surgical complications following appendectomy included surgical site infections in 14 (33%) patients, adhesive obstruction in 13 (31%) patients, intrabdominal abscesses in 10 (24%) patients, and fecal fistulas in 5 (12%) patients. Conclusion: The majority of surgeons aim to perform appendectomy in all malrotation cases, considering the potential risks and benefits of this approach. These findings offer valuable insights for clinical practice and may inform future guidelines and decision-making algorithms.

Cachexia Index as a Predictor of Reduced Survival in Patients with Gastrointestinal Cancer: A Systematic Review and Meta-Analysis.

The cachexia index is a novel indicator of cachexia, but its prognostic implications for survival outcomes have not been systematically assessed in patients with gastrointestinal cancer. This systematic review and meta-analysis aimed to examine the association between the cachexia index and survival outcomes in gastrointestinal cancer patients. Two independent reviewers searched PubMed, Embase, and Web of Science to identify studies that evaluated the prognostic significance of the cachexia index in patients with gastrointestinal cancer. The prognostic value of the cachexia index was determined by combining the adjusted hazard ratios (HR) and 95% confidence intervals (CI). Thirteen studies were identified, including a total of 4207 patients. Meta-analysis indicated that a lower cachexia index was associated with shorter overall survival (HR 2.18; 95% CI 1.78-2.66) and disease-free survival (HR 1.72; 95% CI 1.50-1.97) in gastrointestinal cancer patients. Further stratified analysis confirmed the significant association between a lower cachexia index and shorter overall survival in different study designs, regions, patients' age, sample sizes, gastrointestinal cancer subtypes, tumor stages, and follow-up duration subgroups. The cachexia index could be utilized as a predictor of overall survival and disease-free survival in patients with gastrointestinal cancer. However, future prospective studies are required to confirm these findings.

Output-feedback path-following control of underactuated AUVs via singular perturbation and interconnected-system technique.

This paper focuses on the output-feedback control for path-following of underactuated autonomous underwater vehicles subject to multiple uncertainties and unmeasured velocities. First, a novel extended state observer is proposed to estimate the mismatched lumped disturbance and recover the unmeasured velocities. Based on this premise, to overcome the limitation of relying solely on the accurate kinematic model, a disturbance observer-based stabilizing controller is developed. The difference in bandwidths between the observer and the vehicle dynamics allows for a mathematical setup amenable to standard singular perturbation theory. In the fast mode, a kinematic observer is designed to reject system uncertainty caused by unknown attack angular velocity and prohibitive path-tangential angular velocity, using a novel physical perspective. In the slow mode, an interconnected-system control law is proposed by integrating the backstepping technique with the time scale decomposition method. Furthermore, the stability of the overall closed-loop system is established. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method for path-following of underactuated autonomous underwater vehicles in the vertical plane.

Enzyme-Mediated Bioorthogonal Cascade Catalytic Reaction for Metabolism Intervention and Enhanced Ferroptosis on Neuroblastoma.

It remains a tremendous challenge to explore effective therapeutic modalities against neuroblastoma, a lethal cancer of the sympathetic nervous system with poor prognosis and disappointing treatment outcomes. Considering the limitations of conventional treatment modalities and the intrinsic vulnerability of neuroblastoma, we herein develop a pioneering sequential catalytic therapeutic system that utilizes lactate oxidase (LOx)/horseradish peroxidase (HRP)-loaded amorphous zinc metal-organic framework, named LOx/HRP-aZIF, in combination with a 3-indole-acetic acid (IAA) prodrug. On the basis of abnormal lactate accumulation that occurs in the tumor microenvironment, the cascade reaction of LOx and HRP consumes endogenous glutathione and a reduced form of nicotinamide adenine dinucleotide to achieve the first stage of killing cancer cells via antioxidative incapacitation and electron transport chain interference. Furthermore, the generation of reactive oxygen species induced by HRP and IAA through bioorthogonal catalysis promotes ferritin degradation and lipid peroxidation, ultimately provoking self-enhanced ferroptosis with positive feedback by initiating an endogenous Fenton reaction. This work highlights the superiority of the natural enzyme-dependent cascade and bioorthogonal catalytic reaction, offering a paradigm for synergistically enzyme-based metabolism-ferroptosis anticancer therapy.

Cells in the liver microenvironment regulate the process of liver metastasis.

The research of liver metastasis is a developing field. The ability of tumor cells to invade the liver depends on the complicated interactions between metastatic cells and local subpopulations in the liver (including Kupffer cells, hepatic stellate cells, liver sinusoidal endothelial cells, and immune-related cells). These interactions are mainly mediated by intercellular adhesion and the release of cytokines. Cell populations in the liver microenvironment can play a dual role in the progression of liver metastasis through different mechanisms. At the same time, we can see the participation of liver parenchymal cells and nonparenchymal cells in the process of liver metastasis of different tumors. Therefore, the purpose of this article is to summarize the relationship between cellular components of liver microenvironment and metastasis and emphasize the importance of different cells in the occurrence or potential regression of liver metastasis.

Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign.

This study systematically developed a deep transfer network for near-infrared spectrum detection using convolutional neural network modules as key components. Through meticulous evaluation, specific modules and structures suitable for constructing the near-infrared spectrum detection model were identified, ensuring its effectiveness. This study extensively analyzed the basic network components and explored three unsupervised domain adaptation structures, highlighting their applications in the nondestructive testing of wood. Additionally, five transfer networks were strategically redesigned to substantially enhance their performance. The experimental results showed that the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network outperformed the Direct Standardization, Piecewise Direct Standardization, and Spectral Space Transformation models. The coefficients of determination for the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network are 82.11% and 83.59%, respectively, with root mean square error prediction values of 12.237 and 11.582, respectively. These achievements represent considerable advancements toward the practical implementation of an efficient and reliable near-infrared spectrum detection system using a deep transfer network.

Cold-water coral diversity along the continental shelf margin of northwestern South China Sea.

Scleractinian cold-water corals (CWCs) are one of the most important habitat engineers of the deep sea. Although the South China Sea (SCS) abuts the biodiversity center of scleractinian CWCs in the western Pacific, only a few sporadic records are available. We discovered new CWC sites by means of trawl sampling and video observation along the continental shelf of the northwestern SCS. All trawled scleractinian CWC specimens were identified to species level according to skeleton morphology and structure. The living CWCs and associated fauna recorded in the video were -identified to a higher level of classification. Scleractinian corals were identified to genus level, while non-scleractinian CWCs were identified to family level and given general names such as gorgonian corals, bamboo corals and black corals. Associated benthic dwellers were divided into major categories. A total of 28 scleractinian CWC species were identified to 7 families, 15 genera, and 1 additional subgenus. Among them, 13 species were colonial, including important habitat-forming species in the genera Eguchipsammia, Dendrophyllia and Cladopsammia. Non-scleractinian CWCs were identified to 7 families, including 4 families gorgonian corals, 1 family bamboo corals, and 2 families black corals. Gorgonian corals were the most abundant non-scleractinian CWCs in this region. Meanwhile, starfish, sea anemones, fish, gastropods, echinoderms, and other associated benthic fauna were recorded in the CWC habitats, with starfish belonging to the order Brisingida being most common. New scleractinian CWC assemblages were discovered along the continental seabed mounds in the northwestern SCS. This study highlights the remarkable diversity of cold-water scleractinian corals in the whole SCS, and shows the potential widespread distribution and conservation prospect of CWC habitats in this region.

Wood Veneer Defect Detection Based on Multiscale DETR with Position Encoder Net.

Wood is one of the main building materials. However, defects on veneers result in substantial waste of wood resources. Traditional veneer defect detection relies on manual experience or photoelectric-based methods, which are either subjective and inefficient or need substantial investment. Computer vision-based object detection methods have been used in many realistic areas. This paper proposes a new deep learning defect detection pipeline. First, an image collection device is constructed and a total of more than 16,380 defect images are collected coupled with a mixed data augmentation method. Then, a detection pipeline is designed based on DEtection TRansformer (DETR). The original DETR needs position encoding functions to be designed and is ineffective for small object detection. To solve these problems, a position encoding net is designed with multiscale feature maps. The loss function is also redefined for much more stable training. The results from the defect dataset show that using a light feature mapping network, the proposed method is much faster with similar accuracy. Using a complex feature mapping network, the proposed method is much more accurate with similar speed.

Suppression of viral RNA polymerase activity is necessary for persistent infection during the transformation of measles virus into SSPE virus.

Subacute sclerosing panencephalitis (SSPE) is a fatal neurodegenerative disease caused by measles virus (MV), which typically develops 7 to 10 years after acute measles. During the incubation period, MV establishes a persistent infection in the brain and accumulates mutations that generate neuropathogenic SSPE virus. The neuropathogenicity is closely associated with enhanced propagation mediated by cell-to-cell fusion in the brain, which is principally regulated by hyperfusogenic mutations of the viral F protein. The molecular mechanisms underlying establishment and maintenance of persistent infection are unclear because it is impractical to isolate viruses before the appearance of clinical signs. In this study, we found that the L and P proteins, components of viral RNA-dependent RNA polymerase (RdRp), of an SSPE virus Kobe-1 strain did not promote but rather attenuated viral neuropathogenicity. Viral RdRp activity corresponded to F protein expression; the suppression of RdRp activity in the Kobe-1 strain because of mutations in the L and P proteins led to restriction of the F protein level, thereby reducing cell-to-cell fusion mediated propagation in neuronal cells and decreasing neuropathogenicity. Therefore, the L and P proteins of Kobe-1 did not contribute to progression of SSPE. Three mutations in the L protein strongly suppressed RdRp activity. Recombinant MV harboring the three mutations limited viral spread in neuronal cells while preventing the release of infectious progeny particles; these changes could support persistent infection by enabling host immune escape and preventing host cell lysis. Therefore, the suppression of RdRp activity is necessary for the persistent infection of the parental MV on the way to transform into Kobe-1 SSPE virus. Because mutations in the genome of an SSPE virus reflect the process of SSPE development, mutation analysis will provide insight into the mechanisms underlying persistent infection.

Ferroptosis Inducers Kill Mesenchymal Stem Cells Affected by Neuroblastoma.

Bone marrow (BM) is the most common site of neuroblastoma (NB) metastasis, and its involvement represents poor patient prognosis. In accordance with the "seed and soil" theory of tumor metastasis, BM provides a favorable environment for NB metastasis while bone marrow mesenchymal stem cells (BMSCs) have been recognized as a central part of tumor stroma formation. Yet, there is currently no effective method for intervening these BMSCs. We found that BMSCs affected by NB (NB-BMSCs) could significantly promote NB growth and migration. Additionally, tumor cell-endowed BMSCs showed stronger resistance to several chemotherapeutic agents. Surprisingly, NB-BMSCs were more sensitive to ferroptosis than normal BMSCs. NB-BMSCs had lower levels of intracellular free iron while synthesizing more iron-sulfur clusters and heme. Moreover, the Xc-/glutathione/glutathione peroxidase 4 (Xc-/GSH/GPX4) pathway of the anti-ferroptosis system was significantly downregulated. Accordingly, ferroptosis inducers erastin and RAS-selective lethal 3 (RSL3) could significantly kill NB-BMSCs with limited effects on normal BMSCs. BMSCs from NB patients with BM metastasis also showed poor anti-ferroptosis ability compared with those from NB patients without BM metastasis. In vivo studies suggested that co-injection of mice with BMSCs and NB cells could significantly promote the growth of tumor tissues compared with injecting NB cells alone. However, treatment with erastin or RSL3 resulted in the opposite effect to some extent. Our results revealed that NB-BMSCs were vulnerable to ferroptosis from downregulation of the Xc-/GSH/GPX4 pathway. Ferroptosis inducers could effectively kill NB-BMSCs, but not normal BMSCs. This study provides possible new ideas for the treatment of tumor-associated BMSCs in NB patients.

Quercetin inhibits the amphiregulin/EGFR signaling-mediated renal tubular epithelial-mesenchymal transition and renal fibrosis in obstructive nephropathy.

Quercetin is a widely distributed, bioactive flavonoid compound, which displays potential to inhibit fibrosis in several diseases. The purpose of our study was to determine the effect of quercetin treatment on renal fibrosis and investigate the mechanism. Human proximal tubular epithelial cells (HK-2) stimulated by transforming growth factor-ß1 (TGF-ß1) and a rat model of unilateral ureter obstruction (UUO) that contributes to fibrosis were used to investigate the role and molecular mechanism of quercetin. PD153035 (N-[3-Bromophenyl]-6,7-dimethoxyquinazolin-4-amine) was used to inactivate EGFR (epidermal growth factor receptor). The level of fibrosis, proliferation, apoptosis, and oxidative stress in HK-2 were measured. All data are presented as means ± standard deviation (SD). p-value < .05 was considered statistically significant. In UUO rats, quercetin reduced the area of fibrosis as well as inflammation, oxidative stress, and cell apoptosis. In cultured HK-2 cells, quercetin significantly ameliorated the EMT induced by TGF-ß1, which was accompanied by increased amphiregulin (AREG) expression. Moreover, quercetin inhibited AREG binding to the EGFR receptor, thereby further affecting other downstream pathways. Quercetin may alleviate fibrosis in vitro and in vivo by inhibiting the activation of AREG/EGFR signaling indicating a potential therapeutic effect of quercetin in renal fibrosis.

A vegetation classification method based on improved dual-way branch feature fusion U-net.

Aiming at the problems of complex structure parameters and low feature extraction ability of U-Net used in vegetation classification, a deep network with improved U-Net and dual-way branch input is proposed. Firstly, The principal component analysis (PCA) is used to reduce the dimension of hyperspectral remote sensing images, and the effective bands are obtained. Secondly, the depthwise separable convolution and residual connections are combined to replace the common convolution layers of U-Net for depth feature extraction to ensure classification accuracy and reduce the complexity of network parameters. Finally, normalized difference vegetation index (NDVI), gray level co-occurrence matrix (GLCM) and edge features of hyperspectral remote sensing images are extracted respectively. The above three artificial features are fused as one input, and PCA dimension reduction features are used as another input. Based on the improved U-net, a dual-way vegetation classification model is generated. Taking the hyperspectral remote sensing image of Matiwan Village, Xiong'an, Beijing as the experimental object, the experimental results show that the precision and recall of the improved U-Net are significantly improved with the residual structure and depthwise separable convolution, reaching 97.13% and 92.36% respectively. In addition, in order to verify the effectiveness of artificial features and dual-way branch design, the accuracy of single channel and the dual-way branch are compared. The experimental results show that artificial features in single channel network interfere with the original hyperspectral data, resulting in reduction of the recognition accuracy. However, the accuracy of the dual-way branch network has been improved, reaching 98.67%. It shows that artificial features are effective complements of network features.

EBE-YOLOv4: A lightweight detecting model for pine cones in forest.

Pine cones are important forest products, and the picking process is complex. Aiming at the multi-objective and dispersed characteristics of pine cones in the forest, a machine vision detection model (EBE-YOLOV4) is designed to solve the problems of many parameters and poor computing ability of the general YOLOv4, so as to realize rapid and accurate recognition of pine cones in the forest. Taking YOLOv4 as the basic framework, this method can realize a lightweight and accurate recognition model for pine cones in forest through optimized design of the backbone and the neck networks. EfficientNet-b0 (E) is chosen as the backbone network for feature extraction to reduce parameters and improve the running speed of the model. Channel transformation BiFPN structure (B), which improves the detection rate and ensures the detection accuracy of the model, is introduced to the neck network for feature fusion. The neck network also adds a lightweight channel attention ECA-Net (E) to solve the problem of accuracy decline caused by lightweight improvement. Meanwhile, the H-Swish activation function is used to optimize the model performance to further improve the model accuracy at a small computational cost. 768 images of pine cones in forest were used as experimental data, and 1536 images were obtained after data expansion, which were divided into training set and test set at the ratio of 8:2. The CPU used in the experiment was Inter Core i9-10885@2.40Ghz, and the GPU was NVIDIA Quadro RTX 5000. The performance of YOLOv4 lightweight design was observed based on the indicators of precision (P), recall (R) and detection frames per second (FPS). The results showed that the measurement accuracy (P) of the EBE-YOLOv4 was 96.25%, the recall rate (F) was 82.72% and the detection speed (FPS) was 64.09F/S. Compared with the original YOLOv4, the precision of detection had no significant change, but the speed increased by 70%, which demonstrated the effectiveness of YOLOv4 lightweight design.

Optimizing bowel preparation for colonoscopy: A cross-sectional study of the Chinese population.

Background: The quality of bowel preparation is an important factor in the success of colonoscopy. However, the quality of bowel preparation is often affected by multiple factors. The main objective of this study was to explore the specific factors that affect the quality of bowel preparation. Methods: Patients were consecutively recruited from the gastroenterology department in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology in Wuhan from May 2018 to December 2018. All patients were undergoing colonoscopy. Bowel preparation was evaluated by the Ottawa Bowel preparation Scale (OBPS) and all patients were categorized into 2 groups according to the OBPS. Multivariate analysis was conducted to identify the factors associated with bowel preparation quality. Results: A total of 910 patients were included in the analysis with an average age of 48.62 ± 13.57 years. Patient source (P < 0.001) and the preparation method (P = 0.029) were correlated with OBPS adequacy. In addition, after stratified by age, preparation method (P = 0.022) was a significant factor among patients under 50 years old; whereas waiting time (P = 0.005) was a significant factor among patients over 50 years old. Conclusion: Bowel preparation should be tailored based on the age of the patients to determine the most appropriate plan, including the most appropriate waiting time and the most appropriate purgative combination. Doctors should also focus more on the quality of bowel preparation in inpatients, who are more likely than outpatients to have an inadequate bowel preparation.

Eugenol-Preconditioned Mesenchymal Stem Cell-Derived Extracellular Vesicles Promote Antioxidant Capacity of Tendon Stem Cells In Vitro and In Vivo.

Tendon stem cells (TSCs) are often exposed to oxidative stress at tendon injury sites, which impairs their physiological effect as well as therapeutic application. Recently, extracellular vesicles (EVs) derived from bone marrow mesenchymal stem cells (BMSCs) were shown to mediate cell protection and survival under stress conditions. The function of BMSC-EVs may be affected by pretreatment with various factors such as eugenol (EUG)-a powerful antioxidant. In our previous study, we found that H2O2 significantly impaired TSC proliferation and tenogenic differentiation capabilities. Apoptosis and intracellular ROS accumulation in TSCs were induced by H2O2. However, such H2O2-induced damage was prevented by treatment with EUG-BMSC-EVs. Furthermore, EUG-BMSC-EVs activated the Nrf2/HO-1 pathway to counteract H2O2-induced damage in TSCs. In a rat patellar tendon injury model, the ROS level was significantly higher than that in the normal tendon and TSCs not pretreated showed a poor therapeutic effect. However, EUG-BMSC-EV-pretreated TSCs significantly improved tenogenesis and matrix regeneration during tendon healing. Additionally, the EUG-BMSC-EV group had a significantly improved fiber arrangement. Overall, EUG-BMSC-EVs protected TSCs against oxidative stress and enhanced their functions in tendon injury. These findings provide a basis for potential clinical use of EUG-BMSC-EVs as a new therapeutic vehicle to facilitate TSC therapies for tendon regeneration.

M protein of subacute sclerosing panencephalitis virus, synergistically with the F protein, plays a crucial role in viral neuropathogenicity.

Subacute sclerosing panencephalitis (SSPE) is a rare fatal neurodegenerative disease caused by a measles virus (MV) variant, SSPE virus, that accumulates mutations during long-term persistent infection of the central nervous system (CNS). Clusters of mutations identified around the matrix (M) protein in many SSPE viruses suppress productive infectious particle release and accelerate cell-cell fusion, which are features of SSPE viruses. It was reported, however, that these defects of M protein function might not be correlated directly with promotion of neurovirulence, although they might enable establishment of persistent infection. Neuropathogenicity is closely related to the character of the viral fusion (F) protein, and amino acid substitution(s) in the F protein of some SSPE viruses confers F protein hyperfusogenicity, facilitating viral propagation in the CNS through cell-cell fusion and leading to neurovirulence. The F protein of an SSPE virus Kobe-1 strain, however, displayed only moderately enhanced fusion activity and required additional mutations in the M protein for neuropathogenicity in mice. We demonstrated here the mechanism for the M protein of the Kobe-1 strain supporting the fusion activity of the F protein and cooperatively inducing neurovirulence, even though each protein, independently, has no effect on virulence. The occurrence of SSPE has been estimated recently as one in several thousand in children who acquired measles under the age of 5 years, markedly higher than reported previously. The probability of a specific mutation (or mutations) occurring in the F protein conferring hyperfusogenicity and neuropathogenicity might not be sufficient to explain the high frequency of SSPE. The induction of neurovirulence by M protein synergistically with moderately fusogenic F protein could account for the high frequency of SSPE.

Ascorbic acid mitigates the deleterious effects of nicotine on tendon stem cells.

Purpose: Nicotine causes tendon degeneration, whereas ascorbic acid imparts beneficial effects on tendon cells. Tendon stem cells (TSCs) play a vital role in maintaining tissue integrity and promoting restoration of structure and function after tendon injury. In the present study, cell culture experiments were performed to determine the effects of nicotine on TSCs and whether ascorbic acid supplementation could antagonize the action of high concentration nicotine. Methods: After treatment with nicotine and ascorbic acid, TSC proliferation, migration, stemness, apoptosis, and differentiation were analyzed. Results: TSC proliferation and expression of stem cell markers were significantly impaired by a high concentration of nicotine (1000 ng/mL), but a lower concentration (100 ng/mL) induced proliferative effects in TSCs. Moreover, the highest concentration of nicotine tested (1000 ng/mL) significantly inhibited the migratory ability of TSCs, while relatively high concentrations (100 and 1000 ng/mL) significantly (p < 0.05) up-regulated non-tenocyte genes. When ascorbic acid was added, the inhibitory effects of nicotine on the proliferation, migration, and stemness of TSCs were reversed. In addition, flow cytometry analysis showed that these nicotine concentrations could induce cell apoptosis, while the addition of ascorbic acid inhibited apoptosis. Conclusion: Addition of ascorbic acid partially reversed the inhibitory effect of a high concentration of nicotine. These findings indicate that while nicotine impairs the biological characteristics of TSCs, ascorbic acid can mitigate these deleterious effects and, therefore, may be useful for decreasing nicotine-induced tendon degeneration.

The preventative effect of bone marrow-derived mesenchymal stem cell exosomes on urethral stricture in rats.

BACKGROUND: Urethral stricture (US) is a major challenge in urology and there is an urgent need for effective therapies for its treatment. Exosomes derived from bone marrow mesenchymal stem cells (BMSCs-Exos) have been shown to be effective in preventing scar and fibrosis formation after tissue injury. However, the potential utility of BMSCs-Exos in the prevention of US remains unknown. We hypothesized that local administration of BMSCs-Exos may influence urethral healing and scar formation in a rat model of US. METHODS: A previously established model of rat US was used in this study. Sprague Dawley rats were randomly assigned into sham, US, and US + BMSCs-Exos groups. Micro-ultrasound assessment, histopathology, immunohistochemistry, and gene expression analysis were performed at four weeks post-surgery. RESULTS: US rats exhibited thick urethral walls with a narrowed lumen, when compared with sham rats. However, these changes were suppressed in the US + BMSCs-Exos group. The preventative effects of BMSCs-Exos on US formation were also apparent histologically. US + BMSCs-Exos rats demonstrated decreased expression of several fibrosis-related genes in urethral tissues, including Col I, fibronectin, and elastin, when compared with US rats. BMSCs-Exos treatment also led to an increase in the expression of angiogenesis-related genes in these tissues, including VEGF, eNOS, and bFGF. CONCLUSIONS: Our findings therefore demonstrate that the local administration of BMSCs-Exos prevents urethral stricture formation by regulating fibrosis and angiogenesis. These findings provide a basis for an innovative strategy involving the clinical application of exosomes to counteract US formation.

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

BACKGROUND: Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients' prognosis early and administer precise treatment are of great significance. OBJECTIVE: The aim of this study was to use machine learning to construct a model for the analysis of risk factors and prediction of mortality among ICU patients with COVID-19. METHODS: In this study, 123 patients with COVID-19 in the ICU of Vulcan Hill Hospital were retrospectively selected from the database, and the data were randomly divided into a training data set (n=98) and test data set (n=25) with a 4:1 ratio. Significance tests, correlation analysis, and factor analysis were used to screen 100 potential risk factors individually. Conventional logistic regression methods and four machine learning algorithms were used to construct the risk prediction model for the prognosis of patients with COVID-19 in the ICU. The performance of these machine learning models was measured by the area under the receiver operating characteristic curve (AUC). Interpretation and evaluation of the risk prediction model were performed using calibration curves, SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), etc, to ensure its stability and reliability. The outcome was based on the ICU deaths recorded from the database. RESULTS: Layer-by-layer screening of 100 potential risk factors finally revealed 8 important risk factors that were included in the risk prediction model: lymphocyte percentage, prothrombin time, lactate dehydrogenase, total bilirubin, eosinophil percentage, creatinine, neutrophil percentage, and albumin level. Finally, an eXtreme Gradient Boosting (XGBoost) model established with the 8 important risk factors showed the best recognition ability in the training set of 5-fold cross validation (AUC=0.86) and the verification queue (AUC=0.92). The calibration curve showed that the risk predicted by the model was in good agreement with the actual risk. In addition, using the SHAP and LIME algorithms, feature interpretation and sample prediction interpretation algorithms of the XGBoost black box model were implemented. Additionally, the model was translated into a web-based risk calculator that is freely available for public usage. CONCLUSIONS: The 8-factor XGBoost model predicts risk of death in ICU patients with COVID-19 well; it initially demonstrates stability and can be used effectively to predict COVID-19 prognosis in ICU patients.

Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds.

Lipid content is an important indicator of the edible and breeding value of Pinus koraiensis seeds. Difference in origin will affect the lipid content of the inner kernel, and neither can be judged by appearance or morphology. Traditional chemical methods are small-scale, time-consuming, labor-intensive, costly, and laboratory-dependent. In this study, near-infrared (NIR) spectroscopy combined with chemometrics was used to identify the origin and lipid content of P. koraiensis seeds. Principal component analysis (PCA), wavelet transformation (WT), Monte Carlo (MC), and uninformative variable elimination (UVE) methods were used to process spectral data and the prediction models were established with partial least-squares (PLS). Models were evaluated by R2 for calibration and prediction sets, root mean standard error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP). Two dimensions of input data produced a faster and more accurate PLS model. The accuracy of the calibration and prediction sets was 98.75% and 97.50%, respectively. When the Donoho Thresholding wavelet filter 'bior4.4' was selected, the WT-MC-UVE-PLS regression model had the best predictions. The R2 for the calibration and prediction sets was 0.9485 and 0.9369, and the RMSECV and RMSEP were 0.0098 and 0.0390, respectively. NIR technology combined with chemometric algorithms can be used to characterize P. koraiensis seeds.