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Abstract Background The criteria for metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remain controversial. This research aimed to identify a potential biomarker to differentiate the subtypes of obesity. Methods The study conducted a lipidomic evaluation of ceramide in the serum of 77 Chinese adults who had undergone hyperinsulinemic-euglycemic clamps. These adults were divided into three groups according to the clinical data: normal weight control group (N = 21), MHO (N = 20), and MUO (N = 36). Results The serum Cer d18:1/24:1 level in the MHO group was lower than that in the MUO group. As the Cer d18:1/24:1 level increased, insulin sensitivity decreased, and the unfavorable parameters increased in parallel. Multivariate logistic regression analysis revealed that serum Cer d18:1/24:1 levels were independently correlated with MUO in obesity. Individuals with higher levels of Cer d18:1/24:1 also had an elevated risk of cardiovascular disease. Most ceramide subtype levels increased in obesity compared to normal-weight individuals, but the levels of serum Cer d18:0/18:0 and Cer d18:1/16:0 decreased in obesity. Conclusions The relationships between ceramide subtypes and metabolic profiles might be heterogeneous in populations with different body weights. Cer d18:1/24:1 could be a biomarker that can be used to differentiate MUO from MHO, and to better predict who will develop unfavorable health outcomes among obese individuals. Trial registration The First Affiliated Hospital of Nanjing Medical University’s Institutional Review Board authorized this study protocol, and all participants provided written informed consent (2014-SR-003) prior to study entry.

BackgroundAtopic dermatitis (AD) has increased rapidly with rapid urbanization; however, the treatment options for AD are lacking because the commonly used therapies can only alleviate symptoms. Limosilactobacillus reuteri (L. reuteri), FN041 is a specific strain isolated from human breast milk, and its protective potential against AD has been confirmed. This study aims to assess the efficacy of maternal consumption of L. reuteri FN041 during late pregnancy and lactation in preventing infantile AD.MethodsFirst, a randomized, double-blind, placebo-controlled intervention study will be conducted on 340 pregnant females with babies at high risk for AD. These subjects will be randomly divided into four groups of different doses of L. reuteri FN041 (1 × 109, 5 × 109, and 1 × 1010 CFU/d) along with a placebo. The safety and efficacy of maternal use of L. reuteri FN041 for preventing infantile AD will be analyzed, and the most efficient dosage of L. reuteri FN041 will be determined. Subsequently, a multicenter cohort study of 500 pregnant females with babies at high risk for AD will be conducted to promote the maternal application of L. reuteri FN041. These subjects will be administered L. reuteri FN041 at the optimal dose determined during the first stage of late pregnancy and lactation, and their babies will be analyzed for AD development. Recruitment was initiated in October 2022.DiscussionThe primary outcome is the cumulative incidence of AD at 24 months after maternal consumption of L. reuteri FN041 during late pregnancy and lactation, whereas the secondary outcome is the efficiency of L. reuteri FN041 transfer from the mother’s gut to breast milk and then the infant’s gut after oral supplementation. This study will demonstrate the efficacy of edible probiotics isolated from breast milk in preventing or treating AD in infants. Accordingly, we provide population-based advice for administering specific probiotics for the primary prevention of AD in pregnant females. Understanding the underlying mechanisms of probiotic strains derived from breast milk can promote their application in preventing infant diseases associated with intestinal microbiota imbalance and immune disorders.Clinical trial registrationhttps://www.chictr.org.cn/, identifier [ChiCTR2300075611].

ObjectivesDigestive system diseases have evolved into a growing global burden without sufficient therapeutic measures. Lactobacillus reuteri (L. reuteri) is considered as a new potential economical therapy for its probiotic effects in the gastrointestinal system. We have provided an overview of the researches supporting various L. reuteri strains’ application in treating common digestive system diseases, including infantile colic, diarrhea, constipation, functional abdominal pain, Helicobacter pylori infection, inflammatory bowel disease, diverticulitis, colorectal cancer and liver diseases.MethodsThe summarized literature in this review was derived from databases including PubMed, Web of Science, and Google Scholar.ResultsThe therapeutic effects of L. reuteri in digestive system diseases may depend on various direct and indirect mechanisms, including metabolite production as well as modulation of the intestinal microbiome, preservation of the gut barrier function, and regulation of the host immune system. These actions are largely strain-specific and depend on the activation or inhibition of various certain signal pathways. It is well evidenced that L. reuteri can be effective both as a prophylactic measure and as a preferred therapy for infantile colic, and it can also be recommended as an adjuvant strategy to diarrhea, constipation, Helicobacter pylori infection in therapeutic settings. While preclinical studies have shown the probiotic potential of L. reuteri in the management of functional abdominal pain, inflammatory bowel disease, diverticulitis, colorectal cancer and liver diseases, its application in these disease settings still needs further study.ConclusionThis review focuses on the probiotic effects of L. reuteri on gut homeostasis via certain signaling pathways, and emphasizes the importance of these probiotics as a prospective treatment against several digestive system diseases.

In the realm of neural network-based noise reduction, conventional models predominantly address Gaussian and blur artifacts across entire images. However, they encounter notable challenges when directly applied to periodic noise characteristics of high-resolution infrared sequential imagery. The high resolution also complicates the construction of suitable datasets. Our study introduces an innovative strategy that transforms two-dimensional images into one-dimensional signals, eliminating the need for processing the full image. We have developed a simulated dataset that closely mirrors natural infrared line scanning images derived from the FLIR dataset. To address low-frequency periodic noise, we propose two neural-network-based denoising approaches. The first employs a neural network to deduce noise from the one-dimensional signal, while the second utilizes discrete Fourier transforms for noise prediction within the frequency domain. Our experimental results highlight the Restormer model’s exemplary performance in direct noise prediction, where denoised images attain a PSNR of around 41 and an SSIM close to 0.9 on simulated data, leaving minimal residual noise in the actual denoised images. Further, we investigate the influence of Fourier coefficients, as predicted by neural networks, on the denoising process in the second approach. Employing 12 frequency coefficients, the Restormer and NAFNet models both reach a PSNR near 34 and an SSIM of approximately 0.842.

The spatial resolution of an infrared focal plane polarization detection system is limited by the structure of the detector, resulting in lower resolution than the actual array size. To overcome this limitation and improve imaging resolution, we propose an infrared polarization super-resolution reconstruction model based on sparse representation, optimized using Stokes vector images. This model forms the basis for our method aimed at achieving super-resolution reconstruction of infrared polarization images. In this method, we utilize the proposed model to initially reconstruct low-resolution images in blocks. Subsequently, we perform a division by weight, followed by iterative back projection to enhance details and achieve high-resolution reconstruction results. As a supplement, we establish a near-real-time short-wave infrared time-sharing polarization system for data collection. The dataset was acquired to gather prior knowledge of the over-complete basis set and to generate a series of simulated focal plane images. Simulation experimental results demonstrate the superiority of our method over several advanced methods in objective evaluation indexes, exhibiting strong noise robustness in quantitative experiments. Finally, to validate the practical application of our method, we establish a split-focal plane polarization short-wave infrared system for scene testing. Experimental results confirm the effective processing of actual captured data by our method.

An ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of tenacissoside G, tenacissoside H, and tenacissoside I in rat plasma. The rat plasma was treated with liquid-liquid extraction using ethyl acetate. The determination was performed on the UPLC HSS T3 column (50 mm × 2.1 mm, 1.8 μm) with a mobile phase consisting of acetonitrile-water (containing 0.1% formic acid) and gradient elution at a flow rate of 0.4 mL/min. Electrospray (ESI) positive ion mode detection and multireaction monitoring (MRM) quantitative analysis were performed. A total of 36 rats were given tenacissoside G, tenacissoside H, and tenacissoside I, respectively, orally (5 mg/kg) and intravenously (1 mg/kg), with 6 rats in each group, to evaluate the pharmacokinetic difference of tenacissoside G, tenacissoside H, and tenacissoside I in rats. The calibration curves showed good linearity in the range of 5–2000 ng/mL, where r was greater than 0.99. The results of precision, accuracy, recovery, matrix effect, and stability met the requirements of biological sample detection methods. The established UPLC-MS/MS method was successfully applied to pharmacokinetic studies of tenacissoside G, tenacissoside H, and tenacissoside I, and the bioavailability was 22.9%, 89.8%, and 9.4%, respectively.

Air pollutants from ship exhaust have a negative impact on air quality in coastal areas, which can be greatly exacerbated by sea breeze circulation. However, our understanding of this issue is still limited, especially in coastal areas with a complex topography and winding coastlines, such as the Bohai Rim region in China. In order to fill this knowledge gap, the Weather Research and Forecast model coupled with the chemistry (WRF/Chem) modeling system was employed to investigate the influence of sea breeze circulation on the transport of PM2.5 emitted by ships from April to September in 2014. The major findings are as follows: (1) The concentration of PM2.5 due to ship emissions was 2.94 μg/m3 on days with a sea breeze and 2.4 times higher than on days without a sea breeze in coastal cities in the region. (2) The difference in the contribution of ship emissions during days with a sea breeze and days without a sea breeze decreases with increasing distance from the coastline but remains non-negligible up to 50 km inland. (3) The shape of the coastline, the topographic height of the land area, and the latitude have a significant impact on sea breeze circulation and thus on the transport of ship emissions. (4) The differences in the contribution of ship emissions under days with a sea breeze versus days without a sea breeze were more evident than those under onshore versus alongshore and offshore winds, indicating that sea breeze circulation can cause cyclic accumulation of pollutants and thus reinforce the impact of ship emissions on coastal air quality more than by onshore winds. It should be emphasized that during the switching from sea breeze to a non-sea breeze, the pollutants that have been transported to the land area by sea breeze have not yet been carried back to sea, resulting in the ship contribution value still not significantly reduced even if the wind is a non-sea breeze at that moment. In addition, other factors e.g., emissions, precipitation, and chemistry can also play an important role in the observed trends in this study.

Background. Serum bilirubin is an endogenous antioxidant that has protective effects against obesity-related metabolic diseases. Objectives. This study aimed to evaluate the characteristics of total bilirubin (TBIL), direct bilirubin (DBIL), and indirect bilirubin (IBIL) and their relationships with insulin sensitivity in obese patients with impaired glucose regulation and type 2 diabetes mellitus (IGR/T2DM) in China. Patients and Methods. Cohort 1 comprised obese patients (n = 71) was divided into the IGR/T2DM group (n = 38, obesity with IGR/T2DM) and control group (n = 33, obesity without IGR/T2DM). Insulin sensitivity was evaluated using the hyperinsulinemic-euglycemic clamp technique (HEC) with glucose disposal rate (GDR, M value). Cohort 2 comprised obese patients with IGR/T2DM who underwent metabolic surgery (n = 109) as complementary to cohort 1. Insulin sensitivity was evaluated with the Matsuda Index and homeostatic model assessment of insulin sensitivity (HOMA-IS). Results. In cohort 1, TBIL, DBIL, and IBIL were higher within the physiological range in the IGR/T2DM group compared with the control group; IBIL was positively correlated with M value (r = 0.342, p=0.044) in the IGR/T2DM group, and multivariate logistic regression showed that IBIL might be independent protective factors against insulin resistance (odds ratio (OR) = 0.602; 95% confidence interval (CI): 0.413–0.878; p=0.008). In cohort 2, at 1 month after metabolic surgery, serum bilirubin levels (TBIL, DBIL, and IBIL) increased, and the percentage change in IBIL was positively correlated with the change of the Matsuda Index (r = 0.195, p=0.045). Conclusions. The relationships between different types of bilirubin and insulin sensitivity varied. Serum indirect bilirubin might be a protective factor that enhances insulin sensitivity.

In this study, a new class of thermal insulation composites was prepared by blending a modified hollow glass microsphere (HGM) with furan resin. The particle dispersion between the microparticles and resin matrix was improved using 3-methacryloxypropyltrimethoxy silane (KH-570). Furthermore, the structure and morphology of the modified HGM were characterised by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). In addition, the effects of the modified HGM on the thermal insulation, flame retardancy, and thermal properties of the composites were investigated. The thermal conductivity of the composites was lower than that of the native furan resin. The minimum thermal conductivity of the composites was 0.0274 W/m·K; the flame retardancy of the composites improved, and the limiting oxygen index become a maximum of 31.6%, reaching the refractory material level. Furthermore, the thermal analysis of the composites demonstrated enhanced thermal stability. This study demonstrates that the composite material exhibited good thermal insulation performance and flame retardancy and that it can be applied in the field of thermal insulation.

Collagen is a functional biomaterial with many applications, including wound healing. 3D collagen hydrogels mimic an in vivo cell culture experience in cell survival and growth studies. In experimentally examining human cells under contact with 3D collagen, it is possible to understand the role of collagen in human epithelial tissue repair. This study explored the growth and attachment response of human MCF-7 cells when exposed to 3D collagen by investigating if the presence of NIH/3T3 fibroblasts embedded within the collagen should produce an increased wound-healing response. 3D collagen and fibroblast presence were able to be analyzed in tandem with a "sandwich-like" configuration of the gels to determine how these variables impact or improve the tissue repair response in MCF-7 cells. Examinations in growth, attachment, viability, and migration patterns demonstrated that MCF-7 repair response may be increased when in contact with NIH/3T3 embedded 3D collagen without impairing viability. Most notably, results from the migration assay revealed that MCF-7 cells migrate the most when covered by and adhered to cellular 3D collagen. Fibroblast-embedded collagen on top of and below MCF-7 cells exceeded quantitative assessment to near confluency, whereas less than 50 counted cells per image migrated without any top collagen layering. The continuation of these methods could involve in vivo experiments that incorporate live animal models to determine if these results will continue to extend to live tissue. [ABSTRACT FROM AUTHOR]

Ship emissions are an important factor affecting air quality in coastal areas. The adverse effects of ship emissions on coastal air pollutants are more pronounced in the presence of onshore wind. However, existing studies are based on the summer half of the year and specific stations, so the frequency of onshore winds and their effect on the transport of ship emissions are not fully understood for the whole year or for different seasons. Therefore, in this study, the Yangtze River Delta (YRD) region was selected as the target study area, and the WRF/Chem (The Weather Research and Forecast model coupled with Chemistry) model was used to investigate the impact of ship emissions on PM2.5 in coastal areas under the influence of onshore wind in 2018. There are three main findings. (1) The contribution of ship emissions to PM2.5 under the influence of onshore wind was more significant than either the annual average contribution or the contribution under the influence of non-onshore wind, especially in coastal areas. The contributions of ship emissions to PM2.5 during onshore wind hours reached 9.3 µg m–3 and 7.4 µg m–3 in Shanghai and Ningbo, respectively, which were 1.8 and 1.3 times the annual average, respectively. (2) During onshore wind periods, the contribution of ship emissions to PM2.5 increases significantly not only in coastal areas, but also inland. In the central region 200 km from the coast, ship emissions contributed 4.5 µg m–3 to PM2.5 during onshore wind hours, while the annual average was only 2.5 µg m–3. (3) Under the influence of onshore wind, the effect of ship emissions on PM2.5 showed obvious seasonal differences. Under the influence of onshore wind, the contribution of ship emissions to PM2.5 was larger in winter than in other seasons. In summer, the contribution of ship emissions to PM2.5 differed the most between onshore and non-onshore wind periods. In spring, the contribution of ship emissions to PM2.5 was greater even though the frequency of onshore wind was the lowest. The contribution of ship emissions to PM2.5 can often be underestimated when only annual or monthly averages are considered. This is detrimental to the accurate prevention and control of ship emissions by relevant authorities during periods of high pollution. The results of this study will help those authorities to understand the transport characteristics of ship emissions in the presence of onshore airflow and provide insights for coastal air pollution control and management. [ABSTRACT FROM AUTHOR]

Abstract Background Gene expression profiling is increasingly being utilised as a diagnostic, prognostic and predictive tool for managing cancer patients. Single-sample scoring approach has been developed to alleviate instability of signature scores due to variations from sample composition. However, it is a challenge to achieve comparable signature scores across different expressional platforms. Methods The pre-treatment biopsies from a total of 158 patients, who have received single-agent anti-PD-1 (n = 84) or anti-PD-1 + anti-CTLA-4 therapy (n = 74), were performed using NanoString PanCancer IO360 Panel. Multiple immune-related signature scores were measured from a single-sample rank-based scoring approach, singscore. We assessed the reproducibility and the performance in reporting immune profile of singscore based on NanoString assay in advance melanoma. To conduct cross-platform analyses, singscores between the immune profiles of NanoString assay and the previous orthogonal whole transcriptome sequencing (WTS) data were compared through linear regression and cross-platform prediction. Results singscore-derived signature scores reported significantly high scores in responders in multiple PD-1, MHC-1-, CD8 T-cell-, antigen presentation-, cytokine- and chemokine-related signatures. We found that singscore provided stable and reproducible signature scores among the repeats in different batches and cross-sample normalisations. The cross-platform comparisons confirmed that singscores derived via NanoString and WTS were comparable. When singscore of WTS generated by the overlapping genes to the NanoString gene set, the signatures generated highly correlated cross-platform scores (Spearman correlation interquartile range (IQR) [0.88, 0.92] and r 2 IQR [0.77, 0.81]) and better prediction on cross-platform response (AUC = 86.3%). The model suggested that Tumour Inflammation Signature (TIS) and Personalised Immunotherapy Platform (PIP) PD-1 are informative signatures for predicting immunotherapy-response outcomes in advanced melanoma patients treated with anti-PD-1-based therapies. Conclusions Overall, the outcome of this study confirms that singscore based on NanoString data is a feasible approach to produce reliable signature scores for determining patients’ immune profiles and the potential clinical utility in biomarker implementation, as well as to conduct cross-platform comparisons, such as WTS.

Background Tumor microenvironment (TME) characteristics are potential biomarkers of response to immune checkpoint inhibitors in metastatic melanoma. This study developed a method to perform unsupervised classification of TME of metastatic melanoma.Methods We used multiplex immunohistochemical and quantitative pathology-derived assessment of immune cell compositions of intratumoral and peritumoral regions of metastatic melanoma baseline biopsies to classify TME in relation to response to anti-programmed cell death protein 1 (PD-1) monotherapy or in combination with anti-cytotoxic T-cell lymphocyte-4 (ipilimumab (IPI)+PD-1).Results Spatial profiling of CD8+T cells, macrophages, and melanoma cells, as well as phenotypic PD-1 receptor ligand (PD-L1) and CD16 proportions, were used to identify and classify patients into one of three mutually exclusive TME classes: immune-scarce, immune-intermediate, and immune-rich tumors. Patients with immune-rich tumors were characterized by a lower proportion of melanoma cells and higher proportions of immune cells, including higher PD-L1 expression. These patients had higher response rates and longer progression-free survival (PFS) than those with immune-intermediate and immune-scarce tumors. At a median follow-up of 18 months (95% CI: 6.7 to 49 months), the 1-year PFS was 76% (95% CI: 64% to 90%) for patients with an immune-rich tumor, 56% (95% CI: 44% to 72%) for those with an immune-intermediate tumor, and 33% (95% CI: 23% to 47%) for patients with an immune-scarce tumor. A higher response rate was observed in patients with an immune-scarce or immune-intermediate tumor when treated with IPI+PD-1 compared with those treated with PD-1 alone.Conclusions Our study provides an automatic TME classification method that may predict the clinical efficacy of immunotherapy for patients with metastatic melanoma.