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Abstract Thorium biosorption by a green microalga, Chlorella Vulgaris, was studied in a stirred batch reactor to investigate the effect of initial solution pH, metal ion concentration, biomass dosage, contact time, kinetics, equilibrium and thermodynamics of uptake. The green microalgae showed the highest Th adsorption capacity at 45 °C for the solution with a thorium concentration of 350 mg L−1 and initial pH of 4. The amount of uptake raised from 84 to 104 mg g−1 as the temperature increased from 15 to 45 °C for an initial metal concentration of 75 mg L−1 at pH 4. Transformation Infrared Spectroscopy (FTIR) was employed to characterize the vibrational frequency changes for peaks related to surface functional groups. Also, the scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDX) were used to determine the morphological changes and elemental analysis of the biosorbent before and after the sorption process. The Langmuir isotherm was in perfect agreement with the equilibrium empirical data of thorium biosorption and the highest sorption capacity of the Chlorella Vulgaris microalgae was determined as 185.19 mg g−1. Also, the results of kinetic studies show that the thorium biosorption process follows a pseudo-second-order kinetic model. The negative value of ΔG0 indicates spontaneity and the positive values of ΔH0 indicate the endothermic nature of the adsorption process.

Abstract Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system’s robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com , empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

Abstract Critical challenges remain in clinical translation of extracellular vesicle (EV)-based therapeutics due to the absence of methods to enrich cells with high EV secretion. Current cell sorting methods are limited to surface markers that are uncorrelated to EV secretion or therapeutic potential. Here, we utilize a nanovial technology for enrichment of millions of single cells based on EV secretion. This approach is applied to select mesenchymal stem cells (MSCs) with high EV secretion as therapeutic cells for improving treatment. The selected MSCs exhibit distinct transcriptional profiles associated with EV biogenesis and vascular regeneration and maintain high levels of EV secretion after sorting and regrowth. In a mouse model of myocardial infarction, treatment with high-secreting MSCs improves heart functions compared to treatment with low-secreting MSCs. These findings highlight the therapeutic importance of EV secretion in regenerative cell therapies and suggest that selecting cells based on EV secretion could enhance therapeutic efficacy.

IntroductionThis study aimed to identify the pathogen responsible for leaf blight in Cyclocodon lancifolius, investigate its biological characteristics, and identify effective synthetic fungicides. Additionally, this study examined changes in physiological and biochemical indices of leaves following pathogen infection and screened biocontrol bacteria that inhibit the pathogen growth, providing a scientific basis for preventing and managing leaf blight in C. lancifolius.MethodsPathogens were isolated from the interface of healthy and infected leaf tissues and identified through morphological and molecular biological methods. Amplification and sequencing of three genomic DNA regions—internal transcribed spacer region, translation elongation factor 1-α, and glyceraldehyde-3-phosphate dehydrogenase of ribosomal DNA—were performed, followed by the construction of a phylogenetic tree. The biological characteristics of pathogens under various temperature and pH conditions and different nitrogen and carbon sources were analyzed using the mycelial growth rate method. The antifungal effects of 13 chemical agents were evaluated using the poisoned medium method and mycelial growth rate method. Changes in physiological and biochemical indicators post-infection were also assessed. An antagonistic experiment was conducted to screen for biocontrol bacteria.ResultsA total of 29 potential pathogenic strains were isolated from infected leaf tissues, with Koch’s Postulates confirming Stemphylium lycopersici as a key pathogen causing the disease. Growth analysis of S. lycopersici revealed optimal growth at 20°C and pH 6, with lactose or maltose serving as the most suitable carbon source and histidine as the preferred nitrogen source. Among the 13 synthetic fungicides tested, strain DHY4 exhibited the greatest sensitivity to 400 g/L flusilazole. Significant differences (p < 0.05) were observed in superoxide dismutase, phenylalanine ammonia-lyase, peroxidase, polyphenol oxidase, catalase, and malondialdehyde levels between treated and control groups 3 days post-inoculation. The biocontrol strain DYHS2, identified as a strain of Bacillus subtilis, demonstrated an inhibition rate of 51.80% against S. lycopersici in dual-culture experiments and showed a relative inhibition rate of 78.82% in detached leaf assays.DiscussionThese findings provide valuable insights into the newly identified causal agent of leaf blight in C. lancifolius and its biological characteristics, underscoring the potential of B. subtilis DYHS2 and synthetic fungicides such as flusilazole as effective disease management strategies.

BackgroundOlder patients with advanced cholangiocarcinoma lack systemic therapy standards. These people have a high risk of chemotherapy, accompanied by adverse reactions and even discontinuation of treatment.Case presentationWe report a 78-year-old female subject with advanced intrahepatic cholangiocarcinoma presenting with unresectable lesions involving the hepatic veins, along with extensive metastatic lymph nodes. After the geriatric assessment, capecitabine was utilized for only one cycle owing to adverse events (AEs). Next, a combination of low-dose lenvatinib and tislelizumab was administrated as a second-line treatment, which resulted in remarkable early tumor shrinkage. The following individual lenvatinib taper enabled a manageable safety profile and durable deep response. A near-complete response was achieved, with the primary tumor significantly reducing from 5.6 cm × 4.7 cm to nearly complete disappearance, accompanied by complete regression of lymph nodes, and both progression-free survival and overall survival exceeding 24 months.ConclusionThe case provides valuable insights that could influence future treatment strategies for older patients with advanced cholangiocarcinoma who are unsuitable for chemotherapy. The dose-individualized chemotherapy-free regime of lenvatinib and tislelizumab might be used in similar cases to improve their outcomes.

Background/Purpose: Biomaterial implants are emerging as a treatment choice for pleurodesis; however, the optimal biomaterial and form for managing spontaneous pneumothorax, particularly post-video-assisted thoracic surgery, remain under investigation. This study evaluated the mechanical and biological properties of the poly-ε-caprolactone (PCL) membrane as a sclerosing agent for pleurodesis in Landrace pigs. Methods: Twenty-four Landrace pigs were split into two groups for mechanical abrasion and PCL membrane pleurodesis, with the latter group's PCL meshes inserted using video-assisted thoracic surgery. The mechanical and biological properties of the PCL membrane were assessed in pigs at three, six, and 12 months after the procedure. This assessment involved a range of techniques, such as the T-Peel test, macroscopic evaluation with a scoring scale, microscopic examination, and biomechanical and molecular weight analysis. Results: The PCL membrane group outperformed the traditional abrasion group, with stronger adhesions seen over longer implantation durations. This group also showed superior and more consistent results in both macroscopic and microscopic evaluations compared to the control group. The membrane-based method was easier and faster to perform than the control group's method, and importantly, no mortality occurred following membrane implantation. Conclusion: This study is the pioneering effort to present long-term findings regarding the mechanical and biological properties of the PCL membrane in an in vivo animal model. The membrane demonstrated better adhesion ability than that of traditional abrasion and showed reassuring biocompatibility in both the pig model, suggesting its potential as treatment for patients with primary spontaneous pneumothorax. Further clinical studies are needed to support these observations.

Variational principles are very important for a lot of nonlinear problems to be analyzed theoretically or solved numerically. By the popular semi-inverse method and designing trial-Lagrange functionals skillfully, new variational principles are constructed successfully for the Kuramoto-Sivashinsky equation and the Coupled KdV equations, respectively, which can model a lot of nonlinear waves in shallow water. The established variational principles are also proved correct. The procedure reveals that the used technologies are very powerful and applicable, and can be extended to other nonlinear physical and mathematical models.

Objective: To investigate the impact of donor–recipient (DR) sex matches on survival after lung transplantation while controlling for size difference in the United Network of Organ Sharing (UNOS) database. Methods: We performed a retrospective study of 27,423 lung transplant recipients who were reported in the UNOS database (January 2005-March 2020). Patients were divided into groups based on their respective DR sex match: male to male (MM), male to female (MF), female to female, (FF), and female to male (FM). Kaplan–Meier curve and Cox regression with log-rank tests were used to assess 1-, 3-, 5-, and 10-year survival. We also modeled survival for each group after controlling for size-related variables via the Cox regression. Results: Kaplan–Meier curves showed overall significance at 1-, 3-, 5-, and 10-year end points (P

Abstract Pancreatic ductal adenocarcinoma (PDAC) is not sensitive to most chemotherapy drugs, leading to poor chemotherapy efficacy. Recently, Trametinib and Palbociclib have promising prospects in the treatment of pancreatic cancer. This article aims to explore the effects of Trametinib on pancreatic cancer and address the underlying mechanism of resistance as well as its reversal strategies. The GDSC (Genomics of Drug Sensitivity in Cancer) and CTD2 (Cancer Target Discovery and Development) were utilized to screen the potential drug candidate in PDAC cell lines. The dose-increase method combined with the high-dose shock method was applied to induce the Trametinib-resistant PANC-1 and MIA PaCa-2 cell lines. The CCK8 proliferation assay, colony formation assay, flow cytometry, and western blot were conducted to verify the inhibitory effect of Trametinib and Palbociclib. RNA-seq was performed in resistant PDAC cell lines to find the differential expression genes related to drug resistance and predict pathways leading to the reversal of Trametinib resistance. The GDSC and CTD2 database screening revealed that Trametinib demonstrates a significant inhibitory effect on PDAC. We found that Trametinib has a lower IC50 than Gemcitabine in PDAC cell lines. Both Trametinib and Gemcitabine can decrease the proliferation capacity of pancreatic cells, induce cell cycle arrest, and increase apoptosis. Simultaneously, the phosphorylation of the AKT and ERK pathways were inhibited by the treatment of Trametinib. In addition, the RNA-seq of Trametinib-induced resistance PDAC cell lines reveals that the cyclin-dependent kinase (CDK)-RB-E2F regulatory axis and G2/M DNA damage checkpoint might lead the drug resistance. Besides, the combination of Trametinib with Palbociclib could inhibit the proliferation and cell cycle of both resistant cells lines and also restore the sensitivity of drug-resistant cells to Trametinib. Last but not least, the interferon-α and interferon-γ expression were upregulated in resistance cell lines, which might lead to the reversal of drug resistance. The study shows Trametinib has a critical inhibitory effect on PDAC. Besides, the combination of Trametinib with Palbociclib can inhibit the proliferation of PDAC-resistant cells.

Abstract Continued emergence of SARS-CoV-2 variants of concern that are capable of escaping vaccine-induced immunity highlights the urgency of developing new COVID-19 therapeutics. An essential mechanism for SARS-CoV-2 infection begins with the viral spike protein binding to the human ACE2. Consequently, inhibiting this interaction becomes a highly promising therapeutic strategy against COVID-19. Herein, we demonstrate that ACE2-expressing human lung spheroid cells (LSC)-derived exosomes (LSC-Exo) could function as a prophylactic agent to bind and neutralize SARS-CoV-2, protecting the host against SARS-CoV-2 infection. Inhalation of LSC-Exo facilitates its deposition and biodistribution throughout the whole lung in a female mouse model. We show that LSC-Exo blocks the interaction of SARS-CoV-2 with host cells in vitro and in vivo by neutralizing the virus. LSC-Exo treatment protects hamsters from SARS-CoV-2-induced disease and reduced viral loads. Furthermore, LSC-Exo intercepts the entry of multiple SARS-CoV-2 variant pseudoviruses in female mice and shows comparable or equal potency against the wild-type strain, demonstrating that LSC-Exo may act as a broad-spectrum protectant against existing and emerging virus variants.

Abstract Chemoselective modification of specific residues within a given protein poses a significant challenge, as the microenvironment of amino acid residues in proteins is variable. Developing a universal molecular platform with tunable chemical warheads can provide powerful tools for precisely labeling specific amino acids in proteins. Cysteine and lysine are hot targets for chemoselective modification, but current cysteine/lysine‐selective warheads face challenges due to cross‐reactivity and unstable reaction products. In this study, a versatile fluorescent platform is developed for highly selective modification of cysteine/lysine under biocompatible conditions. Chloro‐ or phenoxy‐substituted NBSe derivatives effectively labeled cysteine residues in the cellular proteome with high specificity. This finding also led to the development of phenoxy‐NBSe phototheragnostic for the diagnosis and activatable photodynamic therapy of GSH‐overexpressed cancer cells. Conversely, alkoxy‐NBSe derivatives are engineered to selectively react with lysine residues in the cellular environment, exhibiting excellent anti‐interfering ability against thiols. Leveraging a proximity‐driven approach, alkoxy‐NBSe probes are successfully designed to demonstrate their utility in bioimaging of lysine deacetylase activity. This study also achieves integrating a small photosensitizer into lysine residues of proteins in a regioselective manner, achieving photoablation of cancer cells activated by overexpressed proteins.

Introduction Patients with pancreatic ductal adenocarcinoma (PDAC) remain a poor prognosis despite the development of chemotherapy. Although programmed cell death 1 (PD-1) blockade has shown great efficacy in various solid tumours, its application in treating PDAC is limited. Recent studies have indicated that chemotherapy or stereotactic body radiotherapy (SBRT) may improve the antitumour effect of PD-1 blockade in patients with PDAC. The objective of this study is to evaluate the efficacy and safety of combined therapy comprising PD-1 blockade, gemcitabine plus nab-paclitaxel chemotherapy and SBRT for patients with metastatic PDAC.Methods and analysis This is a multicentre, single-arm, prospective phase II clinical trial. Forty-three patients diagnosed with metastatic PDAC will be enrolled. The eligible patients will be intravenously administered 1000 mg/m2 gemcitabine and 125 mg/m2 nab-paclitaxel on days 1 and 8 of the 21-day cycle. Serplulimab (200 mg) will be administered intravenously on day 1 of the 21-day cycle. Furthermore, during the second cycle, the patients will undergo SBRT with doses of 33 Gy in five fractions for primary lesions or doses of 24 Gy in three fractions for metastases. The primary endpoint is the 6-month progression-free survival (PFS) rate. The secondary endpoints overall survival, PFS, overall response rate, disease control rate, time to progression, duration of response, duration of disease control and safety. Moreover, this trial seeks to investigate biomarkers such as circulating tumour DNA and circulating hybrid cells in patients diagnosed with metastatic PDAC.Ethics and dissemination The study was approved by the Ethics Committee on Biomedical Research, West China Hospital of Sichuan University. The study results will be presented at international conferences and published in a peer-reviewed journal.Trial registration number ChiCTR2300073237.

Galectins (Gals) are a type of S-type lectin that are widespread and evolutionarily conserved among metazoans, and can act as pattern recognition receptors (PRRs) to recognize pathogen-associated molecular patterns (PAMPs). In this study, 10 Gals (ToGals) were identified in the Golden pompano (Trachinotus ovatus), and their conserved domains, motifs, and collinearity relationships were analyzed. The expression of ToGals was regulated following infection to Cryptocaryon irritans and Streptococcus agalactiae, indicating that ToGals participate in immune responses against microbial pathogens. Further analysis was conducted on one important member, Galectin-3, subcellular localization showing that ToGal-3like protein is expressed both in the nucleus and cytoplasm. Recombinant protein obtained through prokaryotic expression showed that rToGal-3like can agglutinate red blood cells of rabbit, carp and golden pompano and also agglutinate and kill Staphylococcus aureus, Bacillus subtilis, Vibrio vulnificus, S. agalactiae, Pseudomonas aeruginosa, and Aeromonas hydrophila. This study lays the foundation for further research on the immune roles of Gals in teleosts.

Abstract This study aimed to identify the role of chromothripsis as a novel biomarker in the prognosis and differentiation diagnosis of pancreatic neuroendocrine neoplasms (pNENs). We conducted next‐generation gene sequencing in a cohort of 30 patients with high‐grade (G3) pNENs. As a reference, a similar analysis was also performed on 25 patients with low‐grade (G1/G2) pancreatic neuroendocrine tumors (pNETs). Chromothripsis and its relationship with clinicopathological features and prognosis were investigated. The results showed that DNA damage response and repair gene alteration and TP53 mutation were found in 29 and 11 patients, respectively. A total of 14 out of 55 patients had chromothripsis involving different chromosomes. Chromothripsis had a close relationship with TP53 alteration and higher grade. In the entire cohort, chromothripsis was associated with a higher risk of distant metastasis; both chromothripsis and metastasis (ENETS Stage IV) suggested a significantly shorter overall survival (OS). Importantly, in the high‐grade pNENs group, chromothripsis was the only independent prognostic indicator significantly associated with a shorter OS, other than TP53 alteration or pathological pancreatic neuroendocrine carcinomas (pNECs) diagnosis. Chromothripsis can guide worse prognosis in pNENs, and help differentiate pNECs from high‐grade (G3) pNETs.

A key and urgent scientific issue is how to characterize the complex intergranular contact state and mechanical behavior evolution of sand–fines mixed materials and then show how this state contributes to the static and dynamic properties of such materials. Both theoretical analyses and experimental data suggest that the mixes have different intergranular contact states as the fines content (FC) increases, and the mixed materials can be classified as sand-like, in-transition, or fines-like. The capability of the Rahman semi-empirical formula to predict the threshold fines content FCth—which distinguishes the regime of “fines in sand” (sand-dominated behavior) from that of “sand in fines” (fines-dominated behavior)—is verified using the basic material and mechanical properties of mixed materials from the literature. Developed from the method for determining the theoretical minimum void ratio, a new method that allows unified characterization of the critical intergranular contact state parameters FCin-min and FCin-max for in-transition soils is established based on the binary packing model, and FCin-min and FCin-max can be determined simply through explicit expressions that use some material physical indices of pure-sand and pure-fines materials. The proposed procedure offers significant advantages for evaluating the critical intergranular contact state and mechanical properties of sand–fines mixed materials in geotechnical engineering practice.

Pancreatoblastoma (PB), a neoplasm derived from pancreatic follicular cells, primarily affects the pediatric population. Although infrequent in adults, it is associated with a considerably worse prognosis. Approximately one-third of patients are diagnosed with metastatic disease, with liver metastases being the most prevalent. Diagnosis relies on histopathological alterations including squamous vesicles, positive staining for CK8/CK18/CK19, and nuclear displacement of β-catenin. Additionally, liver metastases demonstrate substantial enhancement during the arterial phase of a contrast-enhanced computed tomography (CT) scan. Surgical resection serves as the principal therapeutic approach for addressing primary lesions and liver metastatic PB. In instances where surgical intervention is not viable, patients may derive benefits from systemic therapy and radiotherapy. This particular case report presents the clinical details of a 27-year-old female patient diagnosed with PB, who subsequently developed multiple liver metastases following a pancreaticoduodenectomy. Genomic examinations revealed the presence of ERBB2 amplification, RAD54L deletion, low TMB-L, and MSS in the patient. Despite the patient undergoing chemotherapy and Her-2 targeted therapy in conjunction with immunotherapy, no reduction in lesion size was observed until the administration of surufatinib. Subsequently, a notable outcome ensued, where the metastatic lesions were effectively excised via surgical intervention. Surufatinib has demonstrated a progression-free survival (PFS) of no less than 14 months, and the patient’s survival has endured for a duration of 33 months. This indicates the potential efficacy of surufatinib as a viable therapeutic alternative for adult patients afflicted with PB.

Abstract Developing heterogeneous photocatalysts for the applications in harsh conditions is of high importance but challenging. Herein, by converting the imine linkages into quinoline groups of triphenylamine incorporated covalent organic frameworks (COFs), two photosensitive COFs, namely TFPA-TAPT-COF-Q and TFPA-TPB-COF-Q, are successfully constructed. The obtained quinoline-linked COFs display improved stability and photocatalytic activity, making them suitable photocatalysts for photocatalytic reactions under harsh conditions, as verified by the recyclable photocatalytic reactions of organic acid involving oxidative decarboxylation and organic base involving benzylamine coupling. Under strong oxidative condition, the quinoline-linked COFs show a high efficiency up to 11831.6 μmol·g−1·h−1 and a long-term recyclable usability for photocatalytic production of H2O2, while the pristine imine-linked COFs are less catalytically active and easily decomposed in these harsh conditions. The results demonstrate that enhancing the linkage robustness of photoactive COFs is a promising strategy to construct heterogeneous catalysts for photocatalytic reactions under harsh conditions.

Abstract Machine learning with optical neural networks has featured unique advantages of the information processing including high speed, ultrawide bandwidths and low energy consumption because the optical dimensions (time, space, wavelength, and polarization) could be utilized to increase the degree of freedom. However, due to the lack of the capability to extract the information features in the orbital angular momentum (OAM) domain, the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model. Here, we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network (CNN) based on Laguerre-Gaussian (LG) beam modes with diverse diffraction losses. The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction, and deep-learning diffractive layers as a classifier. The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding, leading to an accuracy as high as 97.2% for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes, as well as a resistance to eavesdropping in point-to-point free-space transmission. Moreover, through extending the target encoded modes into multiplexed OAM states, we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%. Our work provides a deep insight to the mechanism of machine learning with spatial modes basis, which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

Abstract Intra-abdominal adhesions have consistently posed a challenge for surgeons during procedures. This study aims to investigate the feasibility of utilizing indocyanine green (ICG) in conjunction with near-infrared imaging for the detection of intra-abdominal adhesions. In vitro, we analyzed factors affecting ICG fluorescence. We divided SD rats into groups to study ICG excretion in different digestive tract regions. Additionally, we reviewed surgical videos from previous cholecystectomy cases, categorizing them by ICG injection timing and assessing fluorescence imaging in various digestive tract regions. Finally, we preoperatively injected ICG into two cholecystectomized patients with abdominal adhesions, guiding intraoperative adhesiolysis with near-infrared fluorescence imaging. In vitro, we observed a significant influence of protein and ICG concentrations on ICG fluorescence intensity. Our rat experiments unveiled a strong and highly significant correlation (Kendall’s tau-b = 1, P

Urethral stricture is characterized by the chronic formation of fibrous tissue, leading to the narrowing of the urethral lumen. Despite the availability of various endoscopic treatments, the recurrence of urethral strictures remains a common challenge. Postsurgery pharmacotherapy targeting tissue fibrosis is a promising option for reducing recurrence rates. Although drugs cannot replace surgery, they can be used as adjuvant therapies to improve outcomes. In this regard, many drugs have been proposed based on the mechanisms underlying the pathophysiology of urethral stricture. Ongoing studies have obtained substantial progress in treating urethral strictures, highlighting the potential for improved drug effectiveness through appropriate clinical delivery methods. Therefore, this review summarizes the latest researches on the mechanisms related to the pathophysiology of urethral stricture and the drugs to provide a theoretical basis and new insights for the effective use and future advancements in drug therapy for urethral stricture.

Abstract Background Breath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported. Objective The objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm. Methods We conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard. Results We enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84–0.91), the summary specificity was 1.00 (95% CI 0.85–1.00), the AUC was 0.96 (95% CI 0.94–0.98), the pAUC was 0.92 (95% CI 0.89–0.96), and the DOR was 207.62 (95% CI 24.62–924.64). Conclusion Electronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.

Abstract Background The purpose of this study is to use three-dimensional finite-element analysis to better understand the biomechanical features of various internal fixators for ankle arthrodesis. Methods We used finite-element analysis to compare four different types of internal fixations in ankle arthrodesis: Group A had three crossed screws (Ø6.5 mm); Group B had two crossed screws (Ø6.5 mm) and an anterior plate (Ø2.7 mm); Group C only had an anterior anatomical plate (Ø3.5 mm); Group D had one anterior anatomical plate (Ø3.5 mm) and one posterior–lateral screw (Ø6.5 mm). We adopted Ansys 21.0 software to analyze and compare the four types in terms of the displacement of the arthrodesis surface and the stress peak and stress distribution of these models under intorsion, extorsion, dorsiflexion torque, and neutral vertical load. Results ① Displacement of the arthrodesis surface: In Group A, the maximum displacement was larger than Group D under neutral vertical load and dorsiflexion torque but less than it under intorsion and extorsion torque. In Group B, the maximum displacement against dorsiflexion, neutral vertical load, intorsion, and extorsion was less than that in the other three fixation models. In Group C, the maximum displacement against the above four loading patterns were significantly higher than that in another three fixation models. ② Stress peak and stress distribution: based on the stress distribution of the four models, the peak von Mises stress was concentrated in the central sections of the compression screws, plate joints, and bending parts of the plates. Conclusions The fixation model consisting of two crossed screws and an anterior outperformed the other three fixation models in terms of biomedical advantages; thus, this model can be deemed a safe and reliable internal fixation approach for ankle arthrodesis.

Two-dimensional human pose estimation aims to equip computers with the ability to accurately recognize human keypoints and comprehend their spatial contexts within media content. However, the accuracy of real-time human pose estimation diminishes when processing images with occluded body parts or overlapped individuals. To address these issues, we propose a method based on the YOLO framework. We integrate the convolutional concepts of Kolmogorov–Arnold Networks (KANs) through introducing non-linear activation functions to enhance the feature extraction capabilities of the convolutional kernels. Moreover, to improve the detection of small target keypoints, we integrate the cross-stage partial (CSP) approach and utilize the small object enhance pyramid (SOEP) module for feature integration. We also innovatively incorporate a layered shared convolution with batch normalization detection head (LSCB), consisting of multiple shared convolutional layers and batch normalization layers, to enable cross-stage feature fusion and address the low utilization of model parameters. Given the structure and purpose of the proposed model, we name it KSL-POSE. Compared to the baseline model YOLOv8l-POSE, KSL-POSE achieves significant improvements, increasing the average detection accuracy by 1.5% on the public MS COCO 2017 data set. Furthermore, the model also demonstrates competitive performance on the CrowdPOSE data set, thus validating its generalization ability.