DCTR U-Net: automatic segmentation algorithm for medical images of nasopharyngeal cancer in the context of deep learning

Nasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the wall of the nasopharyngeal cavity and is prevalent in Southern China, Southeast Asia, North Africa, and the Middle East. According to studies, NPC is one of the most common malignant tumors in Hainan, China, and it has the highest incidence rate among otorhinolaryngological malignancies. We proposed a new deep learning network model to improve the segmentation accuracy of the target region of nasopharyngeal cancer. Our model is based on the U-Net-based network, to which we add Dilated Convolution Module, Transformer Module, and Residual Module. The new deep learning network model can effectively solve the problem of restricted convolutional fields of perception and achieve global and local multi-scale feature fusion. In our experiments, the proposed network was trained and validated using 10-fold cross-validation based on the records of 300 clinical patients. The results of our network were evaluated using the dice similarity coefficient (DSC) and the average symmetric surface distance (ASSD). The DSC and ASSD values are 0.852 and 0.544 mm, respectively. With the effective combination of the Dilated Convolution Module, Transformer Module, and Residual Module, we significantly improved the segmentation performance of the target region of the NPC

Significant contrasts in aerosol acidity between China and the United States

Aerosol acidity governs several key processes in aerosol physics and chemistry, thus affecting aerosol mass and composition and ultimately climate and human health. Previous studies have reported aerosol pH values separately in China and the United States (USA), implying different aerosol acidity between these two countries. However, there is debate about whether mass concentration or chemical composition is the more important driver of differences in aerosol acidity. A full picture of the pH difference and the underlying mechanisms responsible is hindered by the scarcity of simultaneous measurements of particle composition and gaseous species, especially in China. Here we conduct a comprehensive assessment of aerosol acidity in China and the USA using extended ground-level measurements and regional chemical transport model simulations. We show that aerosols in China are significantly less acidic than in the USA, with pH values 1&ndash;2&nbsp;units higher. Based on a proposed multivariable Taylor series method and a series of sensitivity tests, we identify major factors leading to the pH difference. Compared to the USA, China has much higher aerosol mass concentrations (gas + particle, by a factor of 8.4 on average) and a higher fraction of total ammonia (gas + particle) in the aerosol composition. Our assessment shows that the differences in mass concentrations and chemical composition play equally important roles in driving the aerosol pH difference between China and the USA &ndash; increasing the aerosol mass concentrations (by a factor of 8.4) but keeping the relative component contributions the same in the USA as the level in China increases the aerosol pH by &sim;&thinsp;1.0&nbsp;units and further shifting the chemical composition from US conditions to China's that are richer in ammonia increases the aerosol pH by &sim;&thinsp;0.9 units. Therefore, China being both more polluted than the USA and richer in ammonia explains the aerosol pH difference. The difference in aerosol acidity highlighted in the present study implies potential differences in formation mechanisms, physicochemical properties, and toxicity of aerosol particles in these two countries. &nbsp;</p

Improved On-Orbit MTF Measurement Method Based on Point Source Arrays

The modulation transfer function (MTF) is a key characteristic used to assess the performance of optical remote sensing satellite sensors. MTF detection can directly measure a sensor’s two-dimensional (2D) point spread function (PSF); therefore, it has been applied to various high-resolution remote sensing satellites (e.g., Pleiades) using point sources. However, current point source methods mainly use 2D Gaussian functions to fit the discrete digital number (DN) of the point source on the image to extract the center of the point source and fit the PSF after encrypting multiple point sources; thus, noise robustness is poor and measurement accuracy varies widely. In this study, we developed a noise-resistant on-orbit MTF detection method based on the object space constraint among point source arrays. Utilizing object space constraint relationships among points in a point source array, a homography transformation model was established, enabling accurate extraction of sub-pixel coordinates for each point source response. Subsequently, aligning the luminosity distribution of all point sources concerning a reference point source, the encrypted PSF was obtained and then fitted to obtain the MTF. To validate the method, Gaofen-2 (GF-2) satellite images were used to conduct an in-orbit imaging experiment on the point source array of the Chinese Zhongwei remote sensing satellite calibration site. Compared with the Gaussian model methods, the proposed method yielded more accurate peak positions for each point source. Standard deviations of peak position constant ratios in along- and cross-track directions improved by 2.8 and 4.8 times, respectively. The root-mean-square error (RMSE) of the collinearity test results increased by 92%, and the noise resistance of the MTF curve improved by two times. Dynamic MTF values at the Nyquist frequency for the GF-2 panchromatic band in along- and cross-track directions were 0.0476 and 0.0705, respectively, and MTF values in different directions were well distinguished

Efficient implementation of high-order WENO schemes with sharing function for solving Euler equations

Due to the high-order accuracy and essentially non-oscillatory (ENO) property, the weighted ENO (WENO) schemes have a wide range of successful applications. The component-wise reconstruction WENO (CP WENO) scheme for fluxes or variables has simple formulations but it may produce numerical oscillations near discontinuities when solving the Euler equations. Although the characteristic-wise reconstruction WENO (CH WENO) scheme can reduce such oscillations, it involves too many characteristic projection operations. In this paper, first, we introduced a sharing function to indicate the discontinuities in the Euler equations and then constructed new adaptive characteristic-wise WENO (Ada-WENO) scheme and common-weights WENO (Co-WENO) scheme with this function. Several one and two dimensional problems are used to test the performances of Ada-WENO and Co-WENO. Numerical results show that, Ada-WENO can reduce the computational cost of CH WENO while maintaining its oscillation-free property since it only switches from CP WENO to CH WENO near discontinuities, and Co-WENO can reduce the cost and oscillations of CP WENO, but it may still generate few oscillations

Plasma Asprosin Levels Are Associated with Glucose Metabolism, Lipid, and Sex Hormone Profiles in Females with Metabolic-Related Diseases

Asprosin is a white adipose tissue-derived hormone that increases abnormally in mammals with insulin resistance. However, the role of asprosin in polycystic ovary syndrome (PCOS), a disease partly characterized by insulin resistance, and its potential connection with type 2 diabetes mellitus (T2DM) and PCOS has not been thoroughly elucidated to date. To investigate the association of asprosin with metabolic profiles, sex-related hormones, or inflammation in females with T2DM or PCOS, plasma asprosin and metabolic indicators were measured in 66 healthy females, 53 female patients with T2DM, and 41 patients with PCOS. Spearman’s correlation analysis and binary logistic regression analysis models were used. Plasma asprosin was significantly higher in T2DM females than in healthy subjects (P<0.001) and was positively correlated with fasting blood glucose (FBG), hemoglobin A1c (HbA1c), and HOMA-IR (P<0.05). Asprosin in PCOS subjects was also higher than in healthy subjects (P<0.001) but lower than in T2DM subjects (P<0.05), and it was positively correlated with FBG, HbA1c, HOMA-IR, LDL-c, APOB, APOE, and testosterone (P<0.05). The BMI-categorized subgroups of PCOS subjects also showed correlations of asprosin with metabolic profiles and sex-related hormones. Binary logistic regression analysis revealed that plasma asprosin level acted as an independent risk factor for T2DM or PCOS. These findings suggest the correlation of plasma asprosin level with glucose metabolism, lipid metabolism, sex-related hormones, and inflammation in females, supporting asprosin as a potential predictive factor for females with metabolic-related diseases. This trial is registered with ChiCTR-ROC-17010719

CircHAS2 activates CCNE2 to promote cell proliferation and sensitizes the response of colorectal cancer to anlotinib

Abstract Background Tyrosine kinase inhibitors (TKIs) are crucial in the targeted treatment of advanced colorectal cancer (CRC). Anlotinib, a multi-target TKI, has previously been demonstrated to offer therapeutic benefits in previous studies. Circular RNAs (circRNAs) have been implicated in CRC progression and their unique structural stability serves as promising biomarkers. The detailed molecular mechanisms and specific biomarkers related to circRNAs in the era of targeted therapies, however, remain obscure. Methods The whole transcriptome RNA sequencing and function experiments were conducted to identify candidate anlotinib-regulated circRNAs, whose mechanism was confirmed by molecular biology experiments. CircHAS2 was profiled in a library of patient-derived CRC organoids (n = 22) and patient-derived CRC tumors in mice. Furthermore, a prospective phase II clinical study of 14 advanced CRC patients with anlotinib-based therapy was commenced to verify drug sensitivity (ClinicalTrials.gov identifier: NCT05262335). Results Anlotinib inhibits tumor growth in vitro and in vivo by downregulating circHAS2. CircHAS2 modulates CCNE2 activation by acting as a sponge for miR-1244, and binding to USP10 to facilitate p53 nuclear export as well as degradation. In parallel, circHAS2 serves as a potent biomarker predictive of anlotinib sensitivity, both in patient-derived organoids and xenograft models. Moreover, the efficacy of anlotinib inclusion into the treatment regimen yields meaningful clinical responses in patients with high levels of circHAS2. Our findings offer a promising targeted strategy for approximately 52.9% of advanced CRC patients who have high circHAS2 levels. Conclusions CircHAS2 promotes cell proliferation via the miR-1244/CCNE2 and USP10/p53/CCNE2 bidirectional axes. Patient-derived organoids and xenograft models are employed to validate the sensitivity to anlotinib. Furthermore, our preliminary Phase II clinical study, involving advanced CRC patients treated with anlotinib, confirmed circHAS2 as a potential sensitivity marker

Docosapentaenoic acid and lung cancer risk: A Mendelian randomization study

Abstract Background Observational studies have shown that excessive dietary fat may be associated with lung carcinogenesis. However, findings from previous studies are inconsistent and it remains unclear whether docosapentaenoic acid (DPA), a kind of polyunsaturated fatty acid, is linked to the risk of lung cancer. The aim of this study is to investigate the causal effect of DPA on lung cancer with Mendelian randomization (MR) method. Methods With a two‐sample MR approach, we analyzed the summary data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE, 8866 individuals of European ancestry) Consortium and International Lung Cancer Consortium (ILCCO, 11 348 lung cancer cases and 15 861 controls; European ancestry) to assess the possible causal relationship of DPA on the risk of lung cancer. Results Our results indicated that genetically predicted higher DPA level has a positive association with lung cancer, where 1% higher DPA was associated with a 2.01‐fold risk of lung cancer (odds ratio [OR]: 2.01, 95% CI = 1.34‐3.01; P = 7.40 × 10−4). Additionally, lung cancer was not a causal factor for DPA. The results of MR‐Egger regression analysis showed that there was no evidence for the presence of directional horizontal pleiotropy. Conclusions Genetically elevated DPA is positively associated with risk of lung cancer, and more work is needed to investigate the potential mechanisms

Nutrient-sensing growth hormone secretagogue receptor in macrophage programming and meta-inflammation

Objective: Obesity-associated chronic inflammation, aka meta-inflammation, is a key pathogenic driver for obesity-associated comorbidity. Growth hormone secretagogue receptor (GHSR) is known to mediate the effects of nutrient-sensing hormone ghrelin in food intake and fat deposition. We previously reported that global Ghsr ablation protects against diet-induced inflammation and insulin resistance, but the site(s) of action and mechanism are unknown. Macrophages are key drivers of meta-inflammation. To unravel the role of GHSR in macrophages, we generated myeloid-specific Ghsr knockout mice (LysM-Cre;Ghsrf/f). Methods: LysM-Cre;Ghsrf/f and control Ghsrf/f mice were subjected to 5 months of high-fat diet (HFD) feeding to induce obesity. In vivo, metabolic profiling of food intake, physical activity, and energy expenditure, as well as glucose and insulin tolerance tests (GTT and ITT) were performed. At termination, peritoneal macrophages (PMs), epididymal white adipose tissue (eWAT), and liver were analyzed by flow cytometry and histology. For ex vivo studies, bone marrow-derived macrophages (BMDMs) were generated from the mice and treated with palmitic acid (PA) or lipopolysaccharide (LPS). For in vitro studies, macrophage RAW264.7 cells with Ghsr overexpression or Insulin receptor substrate 2 (Irs2) knockdown were studied. Results: We found that Ghsr expression in PMs was increased under HFD feeding. In vivo, HFD-fed LysM-Cre;Ghsrf/f mice exhibited significantly attenuated systemic inflammation and insulin resistance without affecting food intake or body weight. Tissue analysis showed that HFD-fed LysM-Cre;Ghsrf/f mice have significantly decreased monocyte/macrophage infiltration, pro-inflammatory activation, and lipid accumulation, showing elevated lipid-associated macrophages (LAMs) in eWAT and liver. Ex vivo, Ghsr-deficient macrophages protected against PA- or LPS-induced pro-inflammatory polarization, showing reduced glycolysis, increased fatty acid oxidation, and decreased NF-κB nuclear translocation. At molecular level, GHSR metabolically programs macrophage polarization through PKA-CREB-IRS2-AKT2 signaling pathway. Conclusions: These novel results demonstrate that macrophage GHSR plays a key role in the pathogenesis of meta-inflammation, and macrophage GHSR promotes macrophage infiltration and induces pro-inflammatory polarization. These exciting findings suggest that GHSR may serve as a novel immunotherapeutic target for the treatment of obesity and its associated comorbidity