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BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign and malignant VCFs. PURPOSE: To explore the value of multiple machine learning (ML) models based on CT radiomics features for differentiating benign and malignant VCFs in patients with malignant tumors. MATERIAL AND METHODS: This study retrospectively analyzed 78 patients with malignant tumors accompanied by VCFs, 45 patients with benign VCFs, and 33 patients with malignant VCFs. A total of 140 lesions (86 benign lesions, 54 malignant lesions) were ultimately included in this study. All patients were divided into training sets (n = 98) and validation sets (n = 42) according to the 7:3 ratio. The radiomics features were screened and dimensioned, and multiple radiomics ML models were constructed. The receiver operating characteristic (ROC) curve was performed to assess the diagnostic performance. RESULTS: Five radiomics features were included in the model. All the ML models built have good diagnostic efficiency, among which the support vector machine (SVM) model performs better. The area under the curve (AUC), sensitivity, specificity, and accuracy in the training set were 0.908, 0.816, 0.883, and 0.857, respectively, while those in the validation set were 0.911, 0.647, 0.92, and 0.81, respectively. CONCLUSION: A variety of ML models built based on CT radiomics features have good value for differentiating benign and malignant VCFs in malignant tumor patients, and the SVM model has a better performance.

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A visible-light-promoted reduction of nitrobenzenes using formate salts as the reductant was developed. A wide range of nitrobenzenes can be converted into aniline products in a transition metal free fashion. Mechanistic studies revealed that radical species (carbon dioxide radical anion and thiol radical) are key intermediates for the transformation. We anticipate that this method will provide a valuable and green strategy for the reduction of nitrobenzenes.

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The development of efficient methods for synthesizing ß-silyl amines has long been a significant goal in organic synthesis. Previous methods mainly relied on the use of prefunctionalized substrates or special reagents. Herein, we present a visible-light-promoted synthesis approach for ß-silyl amines, utilizing a combination of photoinduced energy and hydrogen atom transfer processes. Using flow chemistry technology, a variety of valuable skeletons, including ß-silyl amines and α-amino esters, can be produced from readily available feedstocks such as hydrosilanes and simple alkanes. Moreover, the strategy's full-process fluidized production capability highlights its potential for industrial-scale manufacturing. Mechanistic studies revealed that oxime esters can act as radical precursors as well as hydrogen atom transfer reagents.

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PURPOSE: Hobnail features may enhance the clinical aggressiveness of papillary thyroid carcinoma (PTC). However, whether a low proportion (<30%) of these features contributes to increased PTC aggressiveness remains unclear. This study investigated whether PTC cases with a low proportion hobnail features (<30%) exhibit clinical invasiveness and pathological features of aggressiveness. METHODS: Pathological specimens from patients with postoperatively diagnosed PTC were retrospectively analyzed. Among them, 29 PTC cases with a low proportion of hobnail features (<30%) were compared with 173 consecutive classical PTC (cPTC) cases. Data regarding age at presentation, sex, tumor size, number of tumors, and histological characteristics were obtained by reviewing electronic medical records. Postoperative information was obtained during follow-up visits and telephone interviews. RESULTS: Twenty-nine patients with PTC with a low proportion of hobnail features (<30%) were identified, exhibiting a median age of 34 years. At a median follow-up of 31 (IQR, 23-37) months, two patients had recurrent disease in the PTC with a low proportion of hobnail features (<30%) group, whereas there was no recurrence in the cPTC group. No distant metastasis and postoperative mortality were observed in either group. Compared with the cPTC group, patients with PTC and a low proportion of hobnail features exhibited larger tumor volumes and higher susceptibility to capsular invasion and lymph node metastasis. Tumor size and hobnail features emerged as independent risk factors for lymph node metastasis. CONCLUSION: PTC with a low proportion hobnail features (<30%) and larger tumor volumes are associated with the occurrence of lymph node metastasis. A low proportion of hobnail features (<30%) in PTC may heighten invasiveness, elevating the risk of recurrence.

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To improve the accuracy of the Hami melon discrete element model, the parameters of the Hami melon seed discrete element model were calibrated by combining practical experiments and simulation tests. The basic physical parameters of Hami melon seeds were obtained through physical experiments, including triaxial size, 100-grain mass, moisture content, density, Poisson's ratio, Young's modulus, shear modulus, angle of repose, suspension speed and various contact parameters. Taking the repose angle of seed simulation as an index, the parameters of each simulation model were significantly screened by the Plackett-Burman test. The results showed that the recovery coefficient, static friction coefficient and rolling friction coefficient of Hami melon seeds had significant effects on repose angle. Based on the steepest climbing test and quadratic regression orthogonal rotation combination test, it was determined that the significant order of the influence of various contact parameters on the angle of repose was static friction coefficient, collision recovery coefficient, and rolling friction coefficient. The optimal parameter combination was obtained through the mathematical regression model between the angle of repose and various contact parameters, namely, the collision recovery coefficient of Hami melon seeds was 0.518, the static friction coefficient of Hami melon seeds was 0.585 and the rolling friction coefficient of Hami melon seeds was 0.337. Under this condition, three static seed-dropping experiments and dynamic rolling accumulation experiments were carried out. The average simulated angle of repose was 31.93°, and the relative error with the actual value was only 1.71%. The average simulated rolling accumulation angle was 51.98°, and the relative error with the actual value was only 1.92%.

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Extracellular vesicles (EVs) are lipid bilayer-enclosed vesicles released by cells. EVs encapsulate proteins and nucleic acids of their parental cell and efficiently deliver the cargo to recipient cells. These vesicles act as mediators of intercellular communication and thus play a crucial role in various physiological and pathological processes. Moreover, EVs hold promise for clinical use. They have been explored as drug delivery vehicles, therapeutic agents, and targets for disease diagnosis. In the landscape of cancer research, while strides have been made in EV-focused cancer physiopathology, liquid biopsy, and drug delivery, the exploration of EVs as immunotherapeutic agents may not have seen substantial progress to date. Despite promising findings reported in cell and animal studies, the clinical translation of EV-based cancer immunotherapeutics encounters challenges. Here, we review the existing strategies used in EV-based cancer immunotherapy, aiming to propel the development of this emerging yet crucial field.

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Purpose: To develop an anthropomorphic diagnosis system of pulmonary nodules (PN) based on Deep learning (DL) that is trained by weak annotation data and has comparable performance to full-annotation based diagnosis systems. Methods: The proposed system uses deep learning (DL) models to classify PNs (benign vs. malignant) with weak annotations, which eliminates the need for time-consuming and labor-intensive manual annotations of PNs. Moreover, the PN classification networks, augmented with handcrafted shape features acquired through the ball-scale transform technique, demonstrate capability to differentiate PNs with diverse labels, including pure ground-glass opacities, part-solid nodules, and solid nodules. Results: The experiments were conducted on two lung CT datasets: (1) public LIDC-IDRI dataset with 1,018 subjects, (2) In-house dataset with 2740 subjects. Through 5-fold cross-validation on two datasets, the system achieved the following results: (1) an Area Under Curve (AUC) of 0.938 for PN localization and an AUC of 0.912 for PN differential diagnosis on the LIDC-IDRI dataset of 814 testing cases, (2) an AUC of 0.943 for PN localization and an AUC of 0.815 for PN differential diagnosis on the in-house dataset of 822 testing cases. These results demonstrate comparable performance to full annotation-based diagnosis systems. Conclusions: Our system can efficiently localize and differentially diagnose PNs even in resource-limited environments with good robustness across different grade and morphology sub-groups in the presence of deviations due to the size, shape, and texture of the nodule, indicating its potential for future clinical translation. Summary: An anthropomorphic diagnosis system of pulmonary nodules (PN) based on deep learning and weak annotation was found to achieve comparable performance to full-annotation dataset-based diagnosis systems, significantly reducing the time and the cost associated with the annotation. Key Points: A fully automatic system for the diagnosis of PN in CT scans using a suitable deep learning model and weak annotations was developed to achieve comparable performance (AUC = 0.938 for PN localization, AUC = 0.912 for PN differential diagnosis) with the full-annotation based deep learning models, reducing around 30%∼80% of annotation time for the experts.The integration of the hand-crafted feature acquired from human experts (natural intelligence) into the deep learning networks and the fusion of the classification results of multi-scale networks can efficiently improve the PN classification performance across different diameters and sub-groups of the nodule.

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Accumulated evidence highlights that exercise can modulate multiple cytokines, influencing transcriptional pathways, and reprogramming certain metabolic processes, ultimately promoting antitumor immunity and enhancing the efficacy of immune checkpoint inhibitors in cancer patients. Exploring the mechanisms behind this will, for one thing, help us uncover key factors and pathways in exercise-assisted cancer immunotherapy, offering more possibilities for future treatment methods. For another, it will support the development of more personalized and effective exercise prescriptions, thereby improving the prognosis of cancer patients.

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Fat deposition affects beef quantity and quality via preadipocyte proliferation. Beta-sitosterol, a natural small molecular compound, has various functions, such as anti-inflammation, antibacterial, and anticancer properties. The mechanism of action of Beta-sitosterol on bovine preadipocytes remains unclear. This study, based on RNA-seq, reveals the impact of Beta -sitosterol on the proliferation of bovine preadipocytes. Compared to the control group, Beta-sitosterol demonstrated a more pronounced inhibitory effect on cell proliferation after 48 hours of treatment than after 24 hours, as evidenced by the results of EdU staining and flow cytometry. RNA-seq and Western Blot analyses further substantiated these findings. Our results suggest that the impact of Beta-sitosterol on the proliferation of bovine preadipocytes is not significant after a 24-hour treatment. It is only after extending the treatment time to 48 hours that Beta-sitosterol may induce cell cycle arrest at the G2/M phase by suppressing the expression of CCNB1, thereby inhibiting the proliferation of bovine preadipocytes.

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Early detection and postoperative assessment are crucial for improving overall survival among lung cancer patients. Here, we report a non-invasive technique that integrates Raman spectroscopy with machine learning for the detection of lung cancer. The study encompassed 88 postoperative lung cancer patients, 73 non-surgical lung cancer patients, and 68 healthy subjects. The primary aim was to explore variations in serum metabolism across these cohorts. Comparative analysis of average Raman spectra was conducted, while principal component analysis was employed for data visualization. Subsequently, the augmented dataset was used to train convolutional neural networks (CNN) and Resnet models, leading to the development of a diagnostic framework. The CNN model exhibited superior performance, as verified by the receiver operating characteristic curve. Notably, postoperative patients demonstrated an increased likelihood of recurrence, emphasizing the crucial need for continuous postoperative monitoring. In summary, the integration of Raman spectroscopy with CNN-based classification shows potential for early detection and postoperative assessment of lung cancer.

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The aim of this study was to obtain egg-derived peptides with facilitating alcohol metabolism (EPs) by enzymolysis, to identify their structures, and screen small polypeptides with higher activity by molecular docking. The optimum conditions for preparing EPs with facilitating alcohol metabolism were obtained by a single factor experiment, adding 2% Protamex and performing enzymolysis for 3 h with a liquid-material ratio of 35:1. The dose-response relationship experiment showed that 800 mg/kg·bw EPs played a better role in facilitating alcohol metabolism. EPs contained 40% hydrophobic amino acids (HAA), including 9.24% Leu. Eighty-four peptides were identified by HPLC-MS/MS and four peptides with potential activation of alcohol dehydrogenase were further selected by molecular docking. The tetrapeptide Trp-Ile-Val-Asp (WIVD) with the highest binding energy reached -7.16 kcal/mol. These findings suggest that egg is a good source for the preparation of peptides with facilitating alcohol metabolism activity.

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Microbiomes in the lung, gut, and oral cavity are correlated with lung cancer initiation and progression. While correlations have been preliminarily established in earlier studies, delving into microbe-mediated carcinogenic mechanisms will extend our understanding from correlation to causation. Building upon the causative relationships between microbiome and lung cancer, a novel concept of microbial biomarkers has emerged, mainly encompassing cancer-specific bacteria and circulating microbiome DNA. They might function as noninvasive liquid biopsy techniques for lung cancer early detection. Furthermore, potential microbial therapies have displayed initial efficacy in lung cancer treatment, providing multiple avenues for therapeutic intervention. Herein, we will discuss the molecular mechanisms and signaling pathways through which microbes influence lung cancer initiation and development. Additionally, we will summarize recent findings on microbial biomarkers as a member of tumor liquid biopsy techniques and provide an overview of the latest advances in various microbe-assisted/mediated therapeutic approaches for lung cancer.

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Pulmonary Mucormycosis is a fatal infectious disease with high mortality rate. The occurrence of Mucormycosis is commonly related to the fungal virulence and the host's immunological defenses against pathogens. Mucormycosis infection and granulation tissue formation occurred in the upper airway was rarely reported. This patient was a 60-year-old male with diabetes mellitus, who was admitted to hospital due to progressive cough, sputum and dyspnea. High-resolution computed tomography (HRCT) and bronchoscopy revealed extensive tracheal mucosal necrosis, granulation tissue proliferation, and severe airway stenosis. The mucosal necrotic tissue was induced by the infection of Rhizopus Oryzae, confirmed by metagenomic next-generation sequencing (mNGS) in tissue biopsy. This patient was treated with the placement of a covered stent and local instillation of amphotericin B via bronchoscope. The tracheal mucosal necrosis was markedly alleviated, the symptoms of cough, shortness of breath, as well as exercise tolerance were significantly improved. The placement of airway stent and transbronchial microtube drip of amphotericin B could conduce to rapidly relieve the severe airway obstruction due to Mucormycosis infection.

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A PCR- and sequencing-free mutation detection assay facilitates cancer diagnosis and reduces over-reliance on specialized equipment. This benefit was highlighted during the pandemic when high demand for viral nucleic acid testing often sidelined mutation analysis. This shift led to substantial challenges for patients on targeted therapy in tracking mutations. Here, we report a 30-minute DNA mutation detection technique using Cas12a-loaded liposomes in a microplate reader, a fundamental laboratory tool. CRISPR-Cas12a complex and fluorescence-quenching (FQ) probes are introduced into tumor-derived extracellular vesicles (EV) through membrane fusion. When CRISPR-RNA hybridizes with the DNA target, activated Cas12a can trans-cleave FQ probes, resulting in fluorescence signals for the quantification of DNA mutation. Future advancements in multiplex and high-throughput mutation detection using this assay will streamline self-diagnosis and treatment monitoring at home.

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Human bronchial epithelial cells in the airway system, as the primary barrier between humans and the surrounding environment, assume a crucial function in orchestrating the processes of airway inflammation. Target to develop a new three-dimensional (3D) inflammatory model to airway system, and here we report a strategy by using self-assembling D-form peptide to cover the process. By testing physicochemical properties and biocompatibility of Sciobio-Ⅲ, we confirmed that it can rapidly self-assembles under the trigger of ions to form a 3D nanonetwork-like scaffold, which supports 3D cell culture including the cell strains like BEAS-2B cells. Subsequently, inflammation model was established by lipopolysaccharide (LPS), the expression of some markers of tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and interleukin-8 (IL-8), the levels of relevant inflammatory factors were measured by RT-qPCR and the secretion profile of inflammatory cytokines by ELISA, are obtained the quite difference effects in 2D and 3D microenvironment, which suggested Sciobio-Ⅲ hydrogel is an ideal scaffold that create the microenvironment for 3D cell culture. Here we are success to establish a 3D inflammation model for airway system. This innovative model allows for rapid and accurate evaluation of drug metabolism and toxicological side effects, hope to use in drug screening for airway inflammatory diseases and beyond.

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Liposomes as drug vehicles have advantages, such as payload protection, tunable carrying capacity and improved biodistribution. However, due to the dysfunction of targeting moieties and payload loss during preparation, immunoliposomes have yet to be favoured in commercial manufacturing. Here we report a chemical modification-free biophysical approach for producing immunoliposomes in one step through the self-assembly of a chimeric nanobody (cNB) into liposome bilayers. cNB consists of a nanobody against human epidermal growth factor receptor 2 (HER2), a flexible peptide linker and a hydrophobic single transmembrane domain. We determined that 64% of therapeutic compounds can be encapsulated into 100-nm liposomes, and up to 2,500 cNBs can be anchored on liposomal membranes without steric hindrance under facile conditions. Subsequently, we demonstrate that drug-loaded immunoliposomes increase cytotoxicity on HER2-overexpressing cancer cell lines by 10- to 20-fold, inhibit the growth of xenograft tumours by 3.4-fold and improve survival by more than twofold.

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Eggs, with their high nutritional value, are great carriers for enriching nutrients. In this study, selenium- and/or zinc-enriched eggs (SZE) were obtained and their effects on ameliorating oxidative stress injury, alleviating cognitive impairment, and maintaining intestinal flora balance in a D-gal-induced aging mice model were investigated. As determined by the Y-maze test, SZE restored the learning and memory abilities and increased the Ach level and AChE activity of aging mice (p < 0.05). Meanwhile, supplementation of low-dose SZE increased antioxidant levels and decreased inflammation levels (p < 0.05). High-dose SZE increased anti-inflammatory levels but were less effective than low dose. Additionally, SZE maintained the intestinal flora balance and significantly increased the ratio of Firmicutes and Bacteroidota. Blautia, as a probiotic, was negatively correlated with pro-inflammatory factors and positively correlated with antioxidant levels (p < 0.05). These results suggest that SZE might improve organ damage and cognitive function by attenuating oxidative stress and inflammatory response and maintaining healthy gut flora.

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Lentils have potential to improve metabolic health but there are limited randomized clinical trials evaluating their comprehensive impact on metabolism. The aim of this study was to assess the impact of lentil-based vs. meat-based meals on fasting and postprandial measures of glucose and lipid metabolism and inflammation. Thirty-eight adults with an increased waist circumference (male ≥ 40 inches and female ≥ 35 inches) participated in a 12-week dietary intervention that included seven prepared midday meals totaling either 980 g (LEN) or 0 g (CON) of cooked green lentils per week. Linear models were used to assess changes in fasting and postprandial markers from pre- to post-intervention by meal group. Gastrointestinal (GI) symptoms were assessed through a survey randomly delivered once per week during the intervention. We found that regular consumption of lentils lowered fasting LDL (F = 5.53, p = 0.02) and total cholesterol levels (F = 8.64, p < 0.01) as well as postprandial glucose (ß = -0.99, p = 0.01), IL-17 (ß = -0.68, p = 0.04), and IL-1ß (ß = -0.70, p = 0.03) responses. GI symptoms were not different by meal group and all symptoms were reported as "none" or "mild" for the duration of the intervention. Our results suggest that daily lentil consumption may be helpful in lowering cholesterol and postprandial glycemic and inflammatory responses without causing GI stress. This information further informs the development of pulse-based dietary strategies to lower disease risk and to slow or reverse metabolic disease progression in at-risk populations.

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