Whole slide image based prognosis prediction in rectal cancer using unsupervised artificial intelligence.

Background: Rectal cancer is a common cancer worldwide and lacks effective prognostic markers. The development of prognostic markers by computational pathology methods has attracted increasing attention. This paper aims to construct a prognostic signature from whole slide images for predicting progression-free survival (PFS) of rectal cancer through an unsupervised artificial intelligence algorithm.

Noninvasive identification of proliferative hepatocellular carcinoma on multiphase dynamic CT: quantitative and LI-RADS lexicon-based evaluation.

Objective: To identify proliferative hepatocellular carcinoma (HCC) preoperatively using quantitative measurements combined with the updated standard 2021 LI-RADS universal lexicon-based qualitative features on multiphase dynamic CT (MDCT).

Methods: We retrospectively analyzed 273 patients (102 proliferative HCCs) who underwent preoperative MDCT with surgically confirmed HCC in two medical centers. Imaging features were evaluated according to the updated 2021 LI-RADS universal lexicon, and quantitative measurements were analyzed.

Role of , , and in determining the prognosis of patients with lung adenocarcinoma.

Background: Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers, and is the leading cause of tumor-related death. Lung adenocarcinoma (LUAD) is the most prevalent subtype of NSCLC. Although significant progress of LUAD treatment has been made under multimodal strategies, the prognosis of advanced LUAD is still poor due to recurrence and metastasis.

Sub-region based histogram analysis of amide proton transfer-weighted MRI for predicting tumor budding grade in rectal adenocarcinoma: a prospective study.

Objective: To explore the sub-regional histogram features of amide proton transfer-weighted (APTw) MRI, compared with those of diffusion-weighted imaging (DWI), in predicting the tumor budding (TB) grade of rectal cancer (RC).

Materials And Methods: This study prospectively enrolled 74 patients with pathologically confirmed RC, who underwent APTw MRI before surgery from July 2022 to March 2023. Hematoxylin-eosin staining was used for TB scoring.

Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method.

Background: Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subtype of HCC and is associated with poor survival.

Purpose: To investigate the performance of a representation learning-based feature fusion strategy that employs a multiphase contrast-enhanced CT (mpCECT)-based latent feature fusion (MCLFF) model for MTM-HCC identification.

Methods: A total of 206 patients (54 MTM HCC, 152 non-MTM HCC) who underwent preoperative mpCECT with surgically confirmed HCC between July 2017 and December 2022 were retrospectively included from two medical centers.

Does Disaster Severity Have a Long-Term Effect on Survivors' Disaster Preparedness? A Survey a Decade after the 2008 Wenchuan Earthquake in China.

Objectives: Disaster experiences have long-term effects on disaster preparedness. This study examined the long-term (10-y) effect of disaster severity of the 2008 Wenchuan earthquake on survivors' disaster preparedness and the moderating effects of household vulnerability.

Methods: The data were collected in January 2018 covering 30 counties in Wenchuan earthquake-stricken areas.

Study on the variation characteristics and influencing factors of stem water content of Acer truncatum during the overwintering period.

Stem water content serves as a pivotal parameter that reflects the plant vitality and maintains their internal water balance. Given the insufficient comprehension regarding the stem water content characteristics and its influencing factors during different stages of the overwintering period, the study focused on Acer truncatum Bunge and developed an Internet of Things (IoT)-based ecological information monitoring system. The system incorporated a proprietary stem water content sensor, allowing non-invasive, in-situ and real time acquisition of stem water content while monitoring diverse environmental parameters.

The high expression of ADRM1 in hepatocellular carcinoma is closely related to tumor immune infiltration and is regulated by miR-891a-5p.

Liver cancer is one of the most common malignant tumors worldwide. Although some progress has been made in the diagnosis and treatment of Hepatocellular carcinoma (HCC), the diagnosis and treatment of HCC is still facing great challenges because of the high mortality rate and poor prognosis of HCC. The purpose of this study was to explore the relationship between adhesion-regulating molecule1 (ADRM1), and liver cancer, and the relationship between prognoses.

PD-1 blockade enhances the effect of targeted chemotherapy on locally advanced pMMR/MSS colorectal cancer.

Background: Patients with DNA mismatch repair-proficient/microsatellite stable (pMMR/MSS) colorectal cancer (CRC), which accounts for 85% of all CRC cases, display a poor respond to immune checkpoint inhibitors (i.e., anti-PD-1 antibodies).

Association of Collagen Changes in Distal Anastomotic Margin and Anastomotic Stenosis after Neoadjuvant Chemoradiotherapy for Rectal Cancer.

Background: Neoadjuvant chemoradiotherapy (nCRT) for rectal cancer can lead to structural changes in collagen in the tumor microenvironment and increase the risk of postoperative anastomotic stenosis (AS). However, the quantitative relationship between AS and collagen has not been defined. This study is to quantitatively analyze the collagen features in rectal cancer and explore the relationship between the changes of collagen and postoperative anastomotic stenosis after nCRT.

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer.

Background: TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of patients with stage III CRC and quantify the classified tumor tissues based on deep learning to explore the prognostic value of the developed tumor risk signature (TRS).

Methods: A tissue classification model was developed to identify nine tissues (adipose, background, debris, lymphocytes, mucus, smooth muscle, normal mucosa, stroma, and tumor) in whole-slide images (WSIs) of stage III CRC patients.

Pathomics Signature for Prognosis and Chemotherapy Benefits in Stage III Colon Cancer.

Importance: The current TNM staging system may not provide adequate information for prognostic purposes and to assess the potential benefits of chemotherapy for patients with stage III colon cancer.

Objective: To develop and validate a pathomics signature to estimate prognosis and benefit from chemotherapy using hematoxylin-eosin (H-E)-stained slides.

Design, Setting, And Participants: This retrospective prognostic study used data from consecutive patients with histologically confirmed stage III colon cancer at 2 medical centers between January 2012 and December 2015.

Association of the pathomics-collagen signature with lymph node metastasis in colorectal cancer: a retrospective multicenter study.

Background: Lymph node metastasis (LNM) is a prognostic biomarker and affects therapeutic selection in colorectal cancer (CRC). Current evaluation methods are not adequate for estimating LNM in CRC. H&E images contain much pathological information, and collagen also affects the biological behavior of tumor cells.

Development and validation of prognostic models for small cell lung cancer patients with liver metastasis: a SEER population-based study.

Background: This study was to establish and validate prediction models to predict the cancer-specific survival (CSS) and overall survival (OS) of small-cell lung cancer (SCLC) patients with liver metastasis.

Methods: In the retrospective cohort study, SCLC patients with liver metastasis between 2010 and 2015 were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into the training group and testing group (3: 1 ratio).

Evaluation of molecular receptors status in breast cancer using an mpMRI-based feature fusion radiomics model: mimicking radiologists' diagnosis.

Objective: To investigate the performance of a novel feature fusion radiomics (R) model that incorporates features from multiparametric MRIs (mpMRI) in distinguishing different statuses of molecular receptors in breast cancer (BC) preoperatively.

Methods: 460 patients with 466 pathology-confirmed BCs who underwent breast mpMRI at 1.5T in our center were retrospectively included hormone receptor (HR) positive (HR+) (n=336) and HR negative (HR-) (n=130).

ADAMTS12 promotes oxaliplatin chemoresistance and angiogenesis in gastric cancer through VEGF upregulation.

Background: While ADAMTS12 (A disintegrin and metalloproteinase with thrombospondin motifs 12) has been established as an important regulator of gastrointestinal tumor development and angiogenic activity, the precise mechanistic functions of ADAMTS12 have yet to be fully clarified in gastric cancer (GC). Accordingly, this study was developed to explore the molecular functions of ADAMTS12 in GC and to examine its utility as a biomarker associated with chemoresistance and prognostic outcomes in this cancer type.

Methods: The ability of ADAMTS12 to modulate the proliferative, migratory, invasive, chemoresistant, and tube formation activity of tumor cells was assessed in vivo and in vitro through gain- and loss-of-function approaches.

Identification of the intersegmental plane via electromagnetic navigation for anatomical segmentectomy.

Accurate identification of the physiological intersegmental plane is crucial for successful anatomical segmentectomy. Current techniques, such as the inflation-deflation method, may result in uncertain cutting lines, leading to unsuitable resection extents. Here, we demonstrated the successful use of electromagnetic navigation with methylene blue dye-marking to preoperatively and precisely identify the physiological intersegmental plane in two patients with small-sized peripheral non-small cell lung cancer (NSCLC).

Association of collagen deep learning classifier with prognosis and chemotherapy benefits in stage II-III colon cancer.

The current tumor-node-metastasis staging system does not provide sufficient prognostic prediction or adjuvant chemotherapy benefit information for stage II-III colon cancer (CC) patients. Collagen in the tumor microenvironment affects the biological behaviors and chemotherapy response of cancer cells. Hence, in this study, we proposed a collagen deep learning (collagen) classifier based on the 50-layer residual network model for predicting disease-free survival (DFS) and overall survival (OS).