Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

Gestational Exposure to PM2.5 and Specific Constituents, Meconium Metabolites, and Neonatal Neurobehavioral Development: A Cohort Study.

Exposure to fine particulate matter (PM2.5) during pregnancy has been inversely associated with neonatal neurological development. However, the associations of exposure to specific PM2.5 constituents with neonatal neurological development remain unclear. We investigated these associations and examined the mediating role of meconium metabolites in a Chinese birth cohort consisting of 294 mother-infant pairs. Our results revealed that exposure to PM2.5 and its specific constituents (i.e., organic matter, black carbon, sulfate, nitrate, and ammonium) in the second trimester, but not in the first or third trimester, was inversely associated with the total neonatal behavioral neurological assessment (NBNA) scores. The PM2.5 constituent mixture in the second trimester was also inversely associated with NBNA scores, and sulfate was identified as the largest contributor. Furthermore, meconium metabolome analysis identified four metabolites, namely, threonine, lysine, leucine, and saccharopine, that were associated with both PM2.5 constituents and NBNA scores. Threonine was identified as an important mediator, accounting for a considerable proportion (14.53-15.33%) of the observed inverse associations. Our findings suggest that maternal exposure to PM2.5 and specific constituents may adversely affect neonatal behavioral development, in which meconium metabolites may play a mediating role.

Exploring Video Denoising in Thermal Infrared Imaging: Physics-Inspired Noise Generator, Dataset, and Model.

We endeavor on a rarely explored task named thermal infrared video denoising. Perception in the thermal infrared significantly enhances the capabilities of machine vision. Nonetheless, noise in imaging systems is one of the factors that hampers the large-scale application of equipment. Existing thermal infrared denoising methods, primarily focusing on the image level, inadequately utilize time-domain information and insufficiently conduct investigation of system-level mixed noise, presenting the inferior ability in the video-recorded era; while video denoising methods, commonly applied to RGB cameras, exhibit uncertain effectiveness owing to substantial dissimilarities in the noise models and modalities between RGB and thermal infrared images. In sight of this, we initially revisit the imaging mechanism, while concurrently introducing a physics-inspired noise generator based on the sources and characteristics of system noise. Subsequently, a thermal infrared video denoising dataset consisting of 518 real-world videos is constructed. Lastly, we propose a denoising model called multi-domain infrared video denoising network, capable of concentrating features from the time, space, and frequency domains to restore high-fidelity videos. Extensive experiments demonstrate that the proposed method achieves state-of-the-art denoising quality and can be successfully applied to commercial cameras and downstream vision tasks, providing a new avenue for clear videography in the thermal infrared world. The dataset and code will be available.

Clinical characteristics and prognostic analysis of metachronous bilateral breast carcinoma: a retrospective study based on propensity score matching.

BACKGROUND: To investigate clinical characteristics, treatment, outcomes, and prognostic risk factors of metachronous bilateral breast carcinoma (MBBC) and provide a theoretical basis for clinical management of MBBC. METHODS: This was a retrospective study. From January 1, 2010 to March 31, 2022, a total of 23,010 patients with breast cancer underwent surgical treatment at the Breast Center of the Fourth Hospital of Hebei Medical University, including 386 patients with MBBC. Propensity score matching (PSM) was performed on MBBC patients and unilateral breast cancer (UBC) patients in a 1:1 ratio, and 210 UBC patients and 210 MBBC patients were finally matched. Clinical medical records of all patients were collected, including age of onset, family history of breast cancer, tumor size, lymph node status, TNM stage, mode of surgery, menstruation, pathological type, immunohistochemical (IHC) typing, treatment, disease-free survival (DFS), and overall survival (OS). RESULTS: The result showed that age of onset of the second primary cancer (SPC) was significantly older than that of the first primary cancer (FPC) (P = 0.024). Baseline data from MPPC patients showed that the tumor size of FPC was significantly larger than that of SPC (P = 0.043), and the proportion of PR ( +) in FPC is significantly higher than that in SPC (P = 0.045). Among MBBC patients with FPC for estrogen receptor (ER) or progesterone receptor (PR) ( +) and Her-2 (-), clinical characteristics and treatment results showed that the proportion of PR ( +) in the drug-resistant group was significantly lower than that in the non-drug-resistant group. The 2-year OS rate of SPC in the drug-resistant group was significantly shorter than those of the non-drug-resistant group (78.9% vs 100%, P < 0.05). The result of PSM-based comparison between MBBC patients and UBC patients showed significantly lower proportion of MBBC patients with SPC received chemotherapy compared to UBC patients (P = 0.026), and there was no significant difference in OS and DFS between SPC course of MBBC patients and UBC patients (P > 0.05). The univariate analysis showed that high TNM stage was a risk factor for death and disease progression in MBBC patients, with the risk of death in stage III MBBC patients being about 5 times higher than that in stage I MBBC patients (HR = 4.97, 95%CI = 1.42-17.31, P = 0.012), and the risk of disease recurrence being about 3.5 times higher than that in stage I MBBC patients (HR = 3.55, 95%CI = 1.07-11.81, P = 0.039). CONCLUSION: In summary, this study presented clinical characteristics, treatment options, and outcomes of MBBC patients and patients with MBBC who were resistant to endocrine therapy have a worse SPC survival prognosis. The course of SPC in MBBC patients was similar to that of UBC in terms of prognosis and survival, which suggested that SPC can be treated according to UBC treatment regimen. High TNM stage was a prognostic risk factor for SPC patients.

Multi-Omics analysis reveals molecular insights into the effects of acute ozone exposure on lung tissues of normal and obese male mice.

Certain sub-groups, including men and obese individuals, are more susceptible to ozone (O3) exposure, but the underlying molecular mechanisms remain unclear. In this study, the male mice were divided into two dietary groups: one fed a high-fat diet (HFD), mimicking obesity conditions, and the other fed a normal diet (ND), then exposed to 0.5 ppm and 2 ppm O3 for 4 h per day over two days. The HFD mice exhibited significantly higher body weight and serum lipid biochemical indicators compared to the ND mice. Obese mice also exhibited more severe pulmonary inflammation and oxidative stress. Using a multi-omics approach including proteomics, metabolomics, and lipidomics, we observed that O3 exposure induced significant pulmonary molecular changes in both obese and normal mice, primarily arachidonic acid metabolism and lipid metabolism. Different molecular biomarker responses to acute O3 exposure were also observed between two dietary groups, with immune-related proteins impacted in obese mice and PPAR pathway-related proteins affected in normal mice. Furthermore, although not statistically significant, O3 exposure tended to aggravate HFD-induced disturbances in lung glycerophospholipid metabolism. Overall, this study provides valuable molecular insights into the responses of lung to O3 exposure and highlights the potential impact of O3 on obesity-induced metabolic changes.

Concordance of assessments of four PD-L1 immunohistochemical assays in esophageal squamous cell carcinoma (ESCC).

OBJECTIVE: Given real-world limitations in programmed death-ligand 1 (PD-L1) testing, concordance studies between PD-L1 assays are needed. We undertook comparisons of PD-L1 assays (DAKO22C3, Ventana SP263, Ventana SP142, E1L3N) among observers in esophageal squamous cell carcinoma (ESCC) to provide information on the analytical and clinical comparability of four PD-L1 IHC assays. METHODS: Paraffin embedded samples of 50 cases of esophageal squamous cell carcinoma were obtained, satined with all four PD-L1 assays. PD-L1 was evaluated by 68 pathologists from 19 different hospitals. PD-L1 expression was assessed for combined positive score (CPS). RESULTS: The expression sensitivity of SP263 was the highest in ESCC, followed by 22C3, E1L3N and SP142. Taking CPS 10 as the critical value, inter-observer concordance for CPS scores among 68 physicians was assessed for the 22C3, SP263, SP142, and E1L3N assays, yielding values of 0.777, 0.790, 0.758, and 0.782, respectively. In the comparison between assays, the overall CPS scores concordance rates between 22C3 and SP263, SP142, and E1L3N were 0.896, 0.833, and 0.853, respectively. 22C3 and SP263 have high concordance, with OPA of 0.896, while E1L3N and SP142 have the highest concordance, with OPA of 0.908. CONCLUSION: In ESCC, the concordance of PD-L1 evaluation among observers is good, and the immune cell score is still an important factor affecting the concordance of interpretation among observers. Cases near the specific threshold are still the difficult problem of interpretation. SP263 had the highest CPS score of the four assays. SP263 cannot identify all 22C3 positive cases, but had good concordance with 22C3.E1L3N and SP142 showed high concordance.