Multimodal deep learning radiomics model for predicting postoperative progression in solid stage I non-small cell lung cancer.

Purpose: To explore the application value of a multimodal deep learning radiomics (MDLR) model in predicting the risk status of postoperative progression in solid stage I non-small cell lung cancer (NSCLC).

Materials And Methods: A total of 459 patients with histologically confirmed solid stage I NSCLC who underwent surgical resection in our institution from January 2014 to September 2019 were reviewed retrospectively. At another medical center, 104 patients were reviewed as an external validation cohort according to the same criteria.

Clerodendranthus Spicatus: A review of its active compounds, mechanisms of action, and clinical studies in urinary diseases.

Clerodendranthus spicatus (Thunb.) C.Y.

Maximizing arsenic trioxide's anticancer potential: Targeted nanocarriers for solid tumor therapy.

Arsenic trioxide (ATO) has gained significant attention due to its promising therapeutic effects in treating different diseases, particularly acute promyelocytic leukemia (APL). Its potent anticancer mechanisms have been extensively studied. Despite the great efficacy ATO shows in fighting cancers, drawbacks in the clinical use are obvious, especially for solid tumors, which include rapid renal clearance and short half-life, severe adverse effects, and high toxicity to normal cells.

An integrative pan-cancer analysis of the molecular characteristics of dietary restriction in tumour microenvironment.

Background: Dietary restriction (DR), a general term for dieting, has been demonstrated as an effective intervention in reducing the occurrence of cancers. Molecular activities associated with DR are crucial in mediating its anti-cancer effects, yet a comprehensive exploration of the landscape of these activities at the pan-cancer level is still lacking.

Methods: We proposed a computational approach for quantifying DR-related molecular activities and delineating the landscape of these activities across 33 cancer types and 30 normal tissues within 27,320 samples.

Proton-Gradient-Driven Porphyrin-Based Liposome Remote-Loaded with Imiquimod as In Situ Nanoadjuvants for Synergistically Augmented Tumor Photoimmunotherapy.

Cancer immunotherapy is expected to achieve tumor treatment mainly by stimulating the patient's own immune system to kill tumor cells. However, the low immunogenicity of the tumor and the poor efficiency of tumor antigen presentation result in a variety of solid tumors that do not respond to immunotherapy. Herein, we designed a proton-gradient-driven porphyrin-based liposome (PBL) with highly efficient Toll-like receptor 7 (TLR7) agonist (imiquimod, R837) encapsulation (R837@PBL).

Development and validation of a deep learning signature for predicting lymphovascular invasion and survival outcomes in clinical stage IA lung adenocarcinoma: A multicenter retrospective cohort study.

Purpose: The presence of lymphovascular invasion (LVI) influences the management and outcomes of patients with clinical stage IA lung adenocarcinoma. The objective was the development of a deep learning (DL) signature for the prediction of LVI and stratification of prognosis.

Methods: A total of 2077 patients from three centers were retrospectively enrolled and divided into a training set (n = 1515), an internal validation set (n = 381), and an external set (n = 181).

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

Background: This study aimed to develop and validate radiomics and deep learning (DL) signatures for predicting distal metastasis (DM) of non-small cell lung cancer (NSCLC) in low-dose computed tomography (LDCT).

Methods: Images and clinical data were retrospectively collected for 381 NSCLC patients and prospectively collected for 114 patients at the Fifth Affiliated Hospital of Sun Yat-Sen University. Additionally, we enrolled 179 patients from the Jiangmen Central Hospital to externally validate the signatures.

A CT-based deep learning model: visceral pleural invasion and survival prediction in clinical stage IA lung adenocarcinoma.

Pathologic visceral pleural invasion (VPI) in patients with early-stage lung cancer can result in the upstaging of T1 to T2, in addition to having implications for surgical resection and prognostic outcomes. This study was designed with the goal of establishing and validating a CT-based deep learning (DL) model capable of predicting VPI status and stratifying patients based on their prognostic outcomes. In total, 2077 patients from three centers with pathologically confirmed clinical stage IA lung adenocarcinoma were enrolled.

Metagenomic analysis reveals gut plasmids as diagnosis markers for colorectal cancer.

Background: Colorectal cancer (CRC) is linked to distinct gut microbiome patterns. The efficacy of gut bacteria as diagnostic biomarkers for CRC has been confirmed. Despite the potential to influence microbiome physiology and evolution, the set of plasmids in the gut microbiome remains understudied.

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

Objectives: Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs).

Methods: Between October 2008 and May 2020, 257 consecutive patients with surgically and pathologically confirmed TETs were enrolled from three medical centers. We extracted deep learning features from all lesions using a transformer-based convolutional neural network and created a deep learning signature (DLS) using selector operator regression and least absolute shrinkage.

Charge reversal yolk-shell liposome co-loaded JQ1 and doxorubicin with high drug loading and optimal ratio for synergistically enhanced tumor chemo-immunotherapy via blockade PD-L1 pathway.

Antitumor immunotherapy has become a powerful therapeutic modality to identify and kill various malignant tumors by harnessing the immune system. However, it is hampered by the immunosuppressive microenvironment and poor immunogenicity in malignant tumors. Herein, in order to achieve multi-loading of drugs with different pharmacokinetic properties and targets, a charge reversal yolk-shell liposome co-loaded with JQ1 and doxorubicin (DOX) into the poly (D,L-lactic-co-glycolic acid) (PLGA) yolk and the lumen of the liposome respectively was engineered to increase hydrophobic drug loading capacity and stability under physiological conditions and further enhance tumor chemotherapy via blockade programmed death ligand 1 (PD-L1) pathway.

Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer Learning.

Purpose: This study aimed to find suitable source domain data in cross-domain transfer learning to extract robust image features. Then, a model was built to preoperatively distinguish lung granulomatous nodules (LGNs) from lung adenocarcinoma (LAC) in solitary pulmonary solid nodules (SPSNs).

Methods: Data from 841 patients with SPSNs from five centres were collected retrospectively.

Targeted Nanophotoimmunotherapy Potentiates Cancer Treatment by Enhancing Tumor Immunogenicity and Improving the Immunosuppressive Tumor Microenvironment.

Cancer immunotherapy, such as immune checkpoint blockade, chimeric antigen receptor, and cytokine therapy, has emerged as a robust therapeutic strategy activating the host immune system to inhibit primary and metastatic lesions. However, low tumor immunogenicity (LTI) and immunosuppressive tumor microenvironment (ITM) severely compromise the killing effect of immune cells on tumor cells, which fail to evoke a strong and effective immune response. As an exogenous stimulation therapy, phototherapy can induce immunogenic cell death (ICD), enhancing the therapeutic effect of tumor immunotherapy.

Chamomile: A Review of Its Traditional Uses, Chemical Constituents, Pharmacological Activities and Quality Control Studies.

Matricaria chamomilla L. (MC) and Chamaemelum nobile (L.) All.

Puerarin: A review of its mechanisms of action and clinical studies in ophthalmology.

Background: Pueraria is the common name of the dried root of either Pueraria montana var. lobata (Willd.) Maesen & S.

Fine-Grained Assessment of COVID-19 Severity Based on Clinico-Radiological Data Using Machine Learning.

Background: The severe and critical cases of COVID-19 had high mortality rates. Clinical features, laboratory data, and radiological features provided important references for the assessment of COVID-19 severity. The machine learning analysis of clinico-radiological features, especially the quantitative computed tomography (CT) image analysis results, may achieve early, accurate, and fine-grained assessment of COVID-19 severity, which is an urgent clinical need.

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma.

Objective: To develop and validate a deep learning nomogram (DLN) model constructed from non-contrast computed tomography (CT) images for discriminating minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IAC) in patients with subsolid pulmonary nodules (SSPNs).

Materials And Methods: In total, 365 consecutive patients who presented with SSPNs and were pathologically diagnosed with MIA or IAC after surgery, were recruited from two medical institutions from 2016 to 2019. Deep learning features were selected from preoperative CT images using convolutional neural network.

Continuous infusion of lidocaine in pediatric colonoscopy: A randomized double-blind placebo-controlled study.

Background: Propofol is commonly used for providing procedural sedation during pediatric colonoscopy. Intravenous (i.v.

Antiviral Properties of Baicalin: a Concise Review.

Unlabelled: Baicalin is one of the bioactive flavonoid glycosides isolated from the dried root of Georgi, Lamiaceae, with antiviral properties. In recent years, the antiviral activity of baicalin has been widely investigated to explore its molecular mechanism of action. In this mini-review, the molecular mechanisms of action of baicalin as an antiviral agent are evaluated, which included three categories: the inhibition or stimulation of JAK/STAT, TLRs, and NF-κB pathways; up or down modulation of the expression levels of IFN, IL, SOCS1/3, PKR protein, Mx1 protein, and AP-1 protein; and inhibition of cell apoptosis caused by virus infection.

Sophoridine: A review of its pharmacology, pharmacokinetics and toxicity.

Background: Sophoridine is a bioactive alkaloid found in many Chinese herbs, such as Sophora alopecuroides l, Euchresta japonica Benth and Sophora moocrorftinan. Sophoridine hydrochloride injection has been approved as an anticancer drug in China.

Purpose: This review aims to provide a comprehensive summary on the pharmacological, molecular mechanism, pharmacokinetic and toxicity studies of sophoridine.

Fructus arctii: an overview on its traditional uses, pharmacology and phytochemistry.

Objectives: Fructus arctii (F. arctii) is the dried ripe fruit of Arctium lappa Willd (Asteraceae). It is being used as a traditional medicine in China, Japan, Iran, Europe, Afghanistan, India, etc.