Tunable extraordinary optical transmission spectrum properties of long-wavelength infrared metamaterials.

Metamaterial filters represent an essential method for researching the miniaturization of infrared spectral detectors. To realize an 8-2 µm long-wave infrared tunable transmission spectral structure, an extraordinary optical transmission metamaterial model was designed based on the grating diffraction effect and surface plasmon polariton resonance theory. The model consisted of an Al grating array in the upper layer and a Ge substrate in the lower layer. We numerically simulated the effects of different structural parameters on the transmission spectra, such as grating height (h), grating width (w), grating distance (d), grating constant (p), and grating length (S 1), by utilizing the finite-difference time-domain method. Finally, we obtained the maximum transmittance of 81.52% in the 8-12 µm band range, with the corresponding structural parameters set to h=50n m, w=300n m, d=300n m, and S 1=48µm, respectively. After Lorentz fitting, a full width at half maximum of 0.94±0.01µm was achieved. In addition, the Ge substrate influence was taken into account for analyzing the model's extraordinary optical transmission performance. In particular, we first realized the continuous tuning performance at the transmission center wavelength (8-12 µm) of long-wave infrared within the substrate tuning thickness (D) range of 1.9-2.9 µm. The structure designed in this paper features tunability, broad spectral bandwidth, and miniaturization, which will provide a reference for the development of miniaturized long-wave infrared spectral filter devices.

A gradient aligned domain adversarial network for unsupervised intelligent fault diagnosis of gearboxes.

Unsupervised domain adaptation alleviates the dependencies of conventional fault diagnosis methods on sufficient labeled data and strict data distributions. Nonetheless, the current domain adaptation methods only concentrate on the data distributions and ignore the feature gradient distributions, leading to some samples being misclassified due to large gradient discrepancies, thus affecting diagnosis performance. In this paper, a gradient aligned domain adversarial network (GADAN) is proposed. First, the discrepancies of the marginal and conditional distribution between the source and target domain are reduced by minimizing the joint maximum mean discrepancy. Then, a pseudo-labeling approach based on a clustering self-supervised strategy is utilized to attain high-quality pseudo-labels of target domains, and most importantly in the dimension of the data gradient, the feature gradient distributions are aligned by adversarial learning to further reduce the domain shift, even if the distributions of the two domains are close enough. Finally, experiments and engineering applications demonstrate the effectiveness and superiority of GADAN for transfer diagnosis between various working conditions or different machines.

Deep profiling of potential substrate atlas of porcine epidemic diarrhea virus 3C-like protease.

Coronavirus (CoV) 3C-like protease (3CLpro) is essential for viral replication and is involved in immune escape by proteolyzing host proteins. Deep profiling the 3CLpro substrates in the host proteome extends our understanding of viral pathogenesis and facilitates antiviral drug discovery. Here, 3CLpro from porcine epidemic diarrhea virus (PEDV), an enteropathogenic CoV, was used as a model which to identify the potential 3CLpro cleavage motifs in all porcine proteins. We characterized the selectivity of PEDV 3CLpro at sites P5-P4'. We then compiled the 3CLpro substrate preferences into a position-specific scoring matrix and developed a 3CLpro profiling strategy to delineate the protein substrate landscape of CoV 3CLpro. We identified 1,398 potential targets in the porcine proteome containing at least one putative cleavage site and experimentally validated the reliability of the substrate degradome. The PEDV 3CLpro-targeted pathways are involved in mRNA processing, translation, and key effectors of autophagy and the immune system. We also demonstrated that PEDV 3CLpro suppresses the type 1 interferon (IFN-I) cascade via the proteolysis of multiple signaling adaptors in the retinoic acid-inducible gene I (RIG-I) signaling pathway. Our composite method is reproducible and accurate, with an unprecedented depth of coverage for substrate motifs. The 3CLpro substrate degradome establishes a comprehensive substrate atlas that will accelerate the investigation of CoV pathogenicity and the development of anti-CoV drugs.IMPORTANCECoronaviruses (CoVs) are major pathogens that infect humans and animals. The 3C-like protease (3CLpro) encoded by CoV not only cleaves the CoV polyproteins but also degrades host proteins and is considered an attractive target for the development of anti-CoV drugs. However, the comprehensive characterization of an atlas of CoV 3CLpro substrates is a long-standing challenge. Using porcine epidemic diarrhea virus (PEDV) 3CLpro as a model, we developed a method that accurately predicts the substrates of 3CLpro and comprehensively maps the substrate degradome of PEDV 3CLpro. Interestingly, we found that 3CLpro may simultaneously degrade multiple molecules responsible for a specific function. For instance, it cleaves at least four adaptors in the RIG-I signaling pathway to suppress type 1 interferon production. These findings highlight the complexity of the 3CLpro substrate degradome and provide new insights to facilitate the development of anti-CoV drugs.

Machine Learning Model Based on the Neutrophil-to-Eosinophil Ratio Predicts the Recurrence of Hepatocellular Carcinoma After Surgery.

Background: Circulating eosinophils are associated with tumor development. An eosinophil-related index, the neutrophil to eosinophil ratio (NER), can be used to predict the prognosis of patients with tumors. However, there is still a lack of efficient prognostic biomarkers for HCC. In this study, we aimed to investigate the predictive value of the NER and develop an optimal machine learning model for the recurrence of HCC patients. Patients and methods: A retrospective collection of 562 patients who underwent hepatectomy with a pathologic diagnosis of HCC was performed. The relationship between NER and progression-free survival (PFS) was investigated. We developed a new machine learning framework with 10 machine learning algorithms and their 101 combinations to select the best model for predicting recurrence after hepatectomy. The performance of the model was assessed by the area under the curve (AUC) of characteristics and calibration curves, and clinical utility was evaluated by decision curve analysis (DCA). Results: Kaplan‒Meier curves showed that the PFS in the low NER group was significantly better than that in the high NER group. Multivariate Cox regression analysis showed that NER was an independent risk factor for recurrence after surgery. The random survival forests (RSF) model was selected as the best model that had good predictive efficacy and outperformed the TNM, BCLC, and CNLC staging systems. Conclusion: The NER has good predictive value for postoperative recurrence in patients with hepatocellular carcinoma. Machine learning model based on NER can be used for accurate predictions.

Bi2Te3-Based Thermoelectric Modules for Efficient and Reliable Low-Grade Heat Recovery.

Bismuth-telluride-based alloy has long been considered as the most promising candidate for low-grade waste heat power generation. However, optimizing the thermoelectric performance of n-type Bi2Te3 is more challenging than that of p-type counterparts due to its greater sensitivity to texture, and thus limits the advancement of thermoelectric modules. Herein, the thermoelectric performance of n-type Bi2Te3 is enhanced by incorporating a small amount of CuGaTe2, resulting in a peak ZT of 1.25 and a distinguished average ZT of 1.02 (300-500 K). The decomposed Cu+ strengthens interlayer interaction, while Ga+ optimizes carrier concentration within an appropriate range. Simultaneously, the emerged numerous defects, such as small-angle grain boundaries, twin boundaries, and dislocations, significantly suppresses the lattice thermal conductivity. Based on the size optimization by finite element modelling, the constructed thermoelectric module yields a high conversion efficiency of 6.9% and output power density of 0.31 W cm-2 under a temperature gradient of 200 K. Even more crucially, the efficiency and output power little loss after subjecting the module to 40 thermal cycles lasting for 6 days. This study demonstrates the efficient and reliable Bi2Te3-based thermoelectric modules for broad applications in low-grade heat harvest.

Diagnostic utility and sensitivities of matrix Gla protein (MGP), TRPS1 and GATA3 in breast cancer: focusing on metastatic breast cancer, invasive breast carcinoma with special features, and salivary gland-type tumours.

Matrix Gla protein (MGP) and trichorhinophalangeal syndrome type 1 (TRPS1) have recently emerged as novel breast-specific immunohistochemical (IHC) markers, particularly for triple-negative breast cancer (TNBC) and metaplastic carcinoma. The present study aimed to validate and compare the expression of MGP, TRPS1 and GATA binding protein 3 (GATA3) in metastatic breast carcinoma (MBC), invasive breast carcinoma (IBC) with special features, including special types of invasive breast carcinoma (IBC-STs) and invasive breast carcinoma of no special type with unique features, and mammary and non-mammary salivary gland-type tumours (SGTs). Among all enrolled cases, MGP, TRPS1 and GATA3 had comparable high positivity for ER/PR-positive (p=0.148) and HER2-positive (p=0.310) breast carcinoma (BC), while GATA3 positivity was significantly lower in TNBC (p<0.001). Similarly, the positive rates of MGP and TRPS1 in MBCs (99.4%), were higher than in GATA3 (90.9%, p<0.001). Among the IBC-STs, 98.4% of invasive lobular carcinomas (ILCs) were positive for all three markers. Among neuroendocrine tumours (NTs), all cases were positive for TRPS1 and GATA3, while MGP positivity was relatively low (81.8%, p=0.313). In the neuroendocrine carcinoma (NC) subgroup, all cases were positive for GATA3 and MGP, while one case was negative for TRPS1. All carcinomas with apocrine differentiation (APOs) were positive for GATA3 and MGP, while only 60% of the cases demonstrated moderate staining for TRPS1. Among mammary SGTs, MGP demonstrated the highest positivity (100%), followed by TRPS1 (96.0%) and GATA3 (72.0%). Positive staining for these markers was also frequently observed in non-mammary SGTs. Our findings further validate the high sensitivity of MGP and TRPS1 in MBCs, IBC-STs, and breast SGTs. However, none of these markers are capable of distinguishing between mammary and non-mammary SGTs.

Liraglutide Protects Pancreatic Islet From Ischemic Injury by Reducing Oxidative Stress and Activating Akt Signaling During Cold Preservation to Improve Islet Transplantation Outcomes.

BACKGROUND: Islet transplantation is a promising therapy for patients with type 1 diabetes. However, ischemic injury to the donor islets during cold preservation leads to reduced islet quality and compromises transplant outcome. Several studies imply that liraglutide, a glucagon-like peptide-1 receptor agonist, has a positive effect on promoting islet survival, but its impact on islet cold-ischemic injury remains unexplored. Therefore, the aim of this study was to investigate whether liraglutide can improve islet transplantation efficacy by inhibiting cold-ischemic injury and to explore the underlying mechanisms. METHODS: Liraglutide was applied in a mouse pancreas preservation model and a human islets cold-preservation model, and islet viability, function, oxidative stress levels were evaluated. Furthermore, islet transplantation was performed in a syngeneic mouse model and a human-to-nude mouse islet xenotransplantation model. RESULTS: The supplementation of liraglutide in preservation solution improved islet viability, function, and reduced cell apoptosis. Liraglutide inhibited the oxidative stress of cold-preserved pancreas or islets through upregulating the antioxidant enzyme glutathione levels, inhibiting reactive oxygen species accumulation, and maintaining the mitochondrial membrane integrity, which is associated with the activation of Akt signaling. Furthermore, the addition of liraglutide during cold preservation of donor pancreas or donor islets significantly improved the subsequent transplant outcomes in both syngeneic mouse islet transplantation model and human-to-nude mouse islet xenotransplantation model. CONCLUSIONS: Liraglutide protects islets from cold ischemia-related oxidative stress during preservation and hence improved islet transplantation outcomes, and this protective effect of liraglutide in islets is associated with the activation of Akt signaling.

Targeting urinary calcium oxalate crystallization with inulin-type AOFOS from Aspidopterys obcordata Hemsl. for the management of rat urolithiasis.

ETHNOPHARMACOLOGICAL RELEVANCE: Calcium oxalate crystals play a key role in the development and recurrence of kidney stones (also known as urolithiasis); thus, inhibiting the formation of these crystals is a central focus of urolithiasis prevention and treatment. Previously, we reported the noteworthy in vitro inhibitory effects of Aspidopterys obcordata fructo oligosaccharide (AOFOS), an active polysaccharide of the traditional Dai medicine Aspidopterys obcordata Hemsl. (commonly known as Hei Gai Guan), on the growth of calcium oxalate crystals. AIM OF THE STUDY: To investigated the effectiveness and mechanism of AOFOS in treating kidney stones. MATERIALS AND METHODS: A kidney stones rats model was developed, followed by examining AOFOS transport dynamics and effectiveness in live rats. Additionally, a correlation between the polysaccharide and calcium oxalate crystals was studied by combining crystallization experiments with density functional theory calculations. RESULTS: The results showed that the polysaccharide was transported to the urinary system. Furthermore, their accumulation was inhibited by controlling their crystallization and modulating calcium ion and oxalate properties in the urine. Consequently, this approach helped effectively prevent kidney stone formation in the rats. CONCLUSIONS: The present study emphasized the role of the polysaccharide AOFOS in modulating crystal properties and controlling crystal growth, providing valuable insights into their potential therapeutic use in managing kidney stone formation.

DR10627, a Novel Dual Glucagon­like Peptide­1 and Gastric Inhibitory Polypeptide Receptor Agonist for the Treatment of Obesity and Type 2 Diabetes Mellitus.

Introduction: Diabetes and obesity are momentous risk factors threatening people's lives and health. Currently available incretin analogue glucagon-like peptide 1 (GLP-1) possesses huge hypoglycemic effect with the unsatisfactory effect of weight loss. Co-agonists targeting GLP-1R plus glucagon receptor (GCGR) or gastric inhibitory polypeptide receptor (GIPR) show synergistic benefits in glycaemic control and weight loss. Here, we describe a novel dual GIP and GLP-1 receptor agonist, DR10627, and performed a preclinical assessment of it. Methods: The agonistic ability of DR10627 was indirectly assessed by inducing cAMP accumulation in Chinese hamster ovary (CHO) cells transfected with GLP-1R or GIPR in vitro. The plasma pharmacokinetics of DR10627 were analysed in cynomolgus monkeys. The OGTTs were performed in Sprague­Dawley (SD) rats. The glucose lowering effects were evaluated by repeated administration of DR10627 in diabetic (db/db) mice for 4 weeks. The effects of anti-obesity and improving metabolism of DR10627 were evaluated by repeated administration of DR10627 in diet-induced obesity (DIO) mice for 57 days. Results: DR10627 had the capacity to activate both GLP-1R and GIPR in vitro. The terminal half-life of DR10627 was found to be approximately 4.19-5.8 h in cynomolgus monkeys. DR10627 had a great improvement in oral glucose tolerance in SD rats. Moreover, DR10627 had a potent glucose-lowering effect in db/db mice, and the hypoglycemic effect of 18 nmol/kg DR10627 was better than that of 50 nmol/kg liraglutide. In addition, 10 and 30 nmol/kg DR10627 possessed the ability of potentiating the weight-loss, lipid-lowing efficacy and improving metabolism to a greater extent than 80 nmol/kg liraglutide. Conclusion: Preclinical assessment demonstrated that administration of DR10627 resulted in glucose lowering in SD rats and db/db mice, and substantial body weight reduction and metabolism improvement in DIO mice. DR10627 is a promising agent deserving further investigation for the treatment of type 2 diabetes and obesity.

HAIC Combined with lenvatinib plus PD-1 versus lenvatinib Plus PD-1 in patients with high-risk advanced HCC: a real-world study.

BACKGROUND: The treatment of hepatocellular carcinoma (HCC) patients exhibiting high-risk characteristics (Vp4, and/or bile duct invasion, and/or tumor occupancy ≥ 50%) lacks standardized approaches and yields unfavorable results. This study endeavors to evaluate the safety, efficacy, and prognostic impacts of employing hepatic arterial infusion chemotherapy (HAIC), lenvatinib, and humanized programmed death receptor-1 (PD-1) in the treatment of high-risk HCC patients. METHODS: In this retrospective analysis, HCC patients with high-risk features were treated with either lenvatinib combined with PD-1 (LEN-PD1) or a combination of HAIC, lenvatinib, and PD-1 (HAIC-LEN-PD1). The study assessed the antitumor efficacy by calculating overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). Treatment-related adverse events (TRAEs) were analyzed to assess the safety profiles. RESULTS: Between June 2019 and September 2022, a total of 61 patients were included in the LEN-PD1 group, while 103 patients were enrolled in the HAIC-LEN-PD1 group. The OS was 9.8 months in the LEN-PD1 group, whereas the HAIC-LEN-PD1 group exhibited a significantly longer median OS of 19.3 months (HR = 0.43, p < 0.001). Furthermore, PFS was notably extended in the HAIC-LEN-PD1 group compared to the LEN-PD1 group (9.6 months vs. 4.9 months, HR = 0.48, p < 0.001). Patients in the HAIC-LEN-PD1 group had a higher ORR and DCR according to the modified RECIST (76.7% vs. 23.0%, p < 0.001; 92.2% vs. 72.1%, p = 0.001). HAIC-LEN-HAIC group led to more adverse events than LEN-PD1 group, most of which were tolerable and controllable. CONCLUSION: Lenvatinib, HAIC and PD-1 showed safe and promising anti-tumor activity compared with lenvatinib alone for HCC with high-risk features.

Inadvertently enriched cyanobacteria prompted bacterial phosphorus uptake without aeration in a conventional anaerobic/oxic reactor.

The enhanced biological phosphorus removal (EBPR) process requires alternate anaerobic and aerobic conditions, which are regulated respectively by aeration off and on. Recently, in an ordinary EBPR reactor, an abnormal orthophosphate concentration (PO43--P) decline in the anaerobic stage (namely non-aerated phosphorus uptake) aroused attention. It was not occasionally but occurred in each cycle and lasted for 101 d and shared about 16.63 % in the total P uptake amount. After excluding bio-mineralization and surface re-aeration, indoor light conditions (180 to 260 lx) inducing non-aerated P uptake were confirmed. High-throughput sequencing analysis revealed that cyanobacteria could produce oxygen via photosynthesis and were inhabited inside wall biofilm. The cyanobacteria (Pantalinema and Leptolyngbya ANT.L52.2) were incubated in a feeding transparent silicone hose, entered the reactor along with influent, and outcompeted Chlorophyta, which existed in the inoculum. Eventually, this work deciphered the reason for non-aerated phosphorus uptake and indicated its potential application in reducing CO2 emissions and energy consumption via the cooperation of microalgal-bacterial and biofilm-sludge.

Constructing amidoxime adsorption sites on the core-shell structured natural silk protein for uranium capture.

Amidoxime-based fiber adsorbents hold significant promise for uranium extraction. However, a notable issue is that these adsorbents primarily originate from synthetic polymer materials, which, aside from providing good mechanical support, have no other functions. In recent study, we shifted our focus to silk fiber (SF), a natural protein fiber known for its unique core-shell structure and rich amino acids. The shell layer, due to its abundant functional groups, makes it easily modifiable, while the core layer provides excellent mechanical strength. Leveraging these inherent properties, an amidoxime-based fiber adsorbent was developed. This adsorbent utilizes amino and carboxyl groups for enhanced performance synergistically. This method involves establishing uranium affinity sites on the outer sericin layer of SF via chemical initiation of graft polymerization (CIGP) and amidoximation (SF-g-PAO). The water absorption ratio of SF-g-PAO is as high as 601.16 % (DG = 97.17 %). Besides, SF-g-PAO demonstrates an exceptional adsorption capacity of 15.69 mg/g in simulated seawater, achieving a remarkable removal rate of uranyl ions at 95.06 %. It can withstand a minimum of five adsorption-elution cycles. Over a 4-week period in natural seawater, SF-g-PAO displayed an adsorption capacity of 4.95 mg/g. Furthermore, SF-g-PAO also exhibits impressive uranium removal efficiency in real nuclear wastewater, with a removal rate of 63 % in just 15 min and a final removal rate of 90 %. It is hoped that this SF-g-PAO, prepared through this straightforward method and characterized by the synergistic action of amino and carboxyl groups, can offer innovative insights into the development of uranium extraction adsorbents.

Mechanical behaviors of a new elliptical valve stent in bicuspid aortic valve.

BACKGROUND AND OBJECTIVE: The conventional valve stents that are cylindrical in shape will become elliptical when implanted in bicuspid aortic valve, thereby reducing the durability of the artificial valve. In this study, a new design of valve stent is presented where valve stents have elliptical cross-section at the annulus and it is expected to have better expandability and circle shape during the interaction between the stent and bicuspid aortic valve, thereby extending the durability of artificial valve. METHODS: Finite element method (FEM) is used to study the mechanical behavior of the novel valve stent in the bicuspid aortic valve. The effects of three matching relationship between the ellipticity of the stents and the ellipticity of the annulus (i.e., the ellipticity of the stent is greater than, equal to and less than the annulus ellipticity, respectively) on the mechanical behavior of stent expansion are studied. In addition, the expansion mechanical behavior of the novel valve stent at different implantation depths is also compared. RESULTS: Results indicate that novel valve stent implantation with elliptical features is superior to conventional circular valve stent. When the novel valve stent ellipticity is less than the annulus ellipticity, the ellipticity of the novel valve stent after implantation is smaller than that of the conventional circular valve stent. This indicated that the novel valve stent has better expandability and post-expansion shape, making artificial valve to have better durability. The risk of paravalvular leak after implantation is lowest when the novel valve stent ellipticity is less than annulus ellipticity. When the novel valve stent ellipticity coincides with annulus ellipticity, the aortic wall is subjected to greatest stress. With the increase of implantation depth, the stress on the novel valve stent decrease. CONCLUSIONS: This study might provide insights for improving stent design for bicuspid aortic valve.

The survival after thyroidectomy versus lobectomy in multifocal papillary thyroid microcarcinoma patients.

BACKGROUND: The extent of thyroid surgery for multifocal papillary thyroid microcarcinoma (PTMC) remains controversial. Studies on the optimal surgical approach for a multifocal PTMC are scarce. This study aimed to compare the effectiveness of thyroidectomy and lobectomy for the treatment of multifocal PTMC. METHODS: A population-based retrospective cohort of patients with multifocal PTMC was analyzed using the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017, and divided into two groups (thyroidectomy, lobectomy) based on the surgical approach. The clinicopathologic features and survival outcomes were compared between the two groups. Cox proportional hazards regression analysis to explore prognostic factors of survival. Propensity score matching (PSM) was used to balance covariates. RESULTS: Overall, a total of 9387 multifocal PTMC patients were included in the study. Among them, 8,107 (86.36%) patients received thyroidectomy, and 1280 (13.64%) patients underwent lobectomy. Compared to patients in the thyroidectomy group, patients in the lobectomy group were diagnosed with older age (50.47 years vs. 49.32 years, p = 0.003), a higher proportion of males (20.47% vs. 14.99%, p < 0.001), larger tumors (6.22 mm vs. 4.97 mm, p < 0.001), and more frequently underwent radiotherapy (35.40% vs. 10.16%, p < 0.001). Multivariate Cox regression analysis revealed that age was the only independent prognostic factor for thyroid cancer-specific survival (TCSS), and the determinants of overall survival (OS) were age and gender. Unadjusted survival analysis revealed no difference between the two treatment groups in TCSS (p = 0.598) and OS (p = 0.126). After 1:1 Propensity Score Matching (PSM), there was still no difference in TCSS (p = 0.368) or OS (p = 0.388). The stratified analysis revealed that for patients aged under or above 55, thyroidectomy was not associated with superior BCSS or OS (p > 0.05). CONCLUSIONS: Thyroidectomy was not associated with improved survival compared to thyroid lobectomy for patients with multifocal PTMC.

Combining T1rho and advanced diffusion MRI for noninvasively staging liver fibrosis: an experimental study in rats.

PURPOSE: To investigate the value of imaging parameters derived from T1 relaxation times in the rotating frame (T1ρ or T1rho), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in assessment of liver fibrosis in rats and propose an optimal diagnostic model based on multiparametric MRI. METHODS: Thirty rats were divided into one control group and four fibrosis experimental groups (n = 6 for each group). Liver fibrosis was induced by administering thioacetamide (TAA) for 2, 4, 6, and 8 weeks. T1ρ, mean kurtosis (MK), mean diffusivity (MD), perfusion fraction (f), true diffusion coefficient (D), and pseudo-diffusion coefficient (D*) were measured and compared among different fibrosis stages. An optimal diagnostic model was established and the diagnostic efficiency was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: The mean AUC values, sensitivity, and specificity of T1ρ and MD derived from DKI across all liver fibrosis stages were comparable but much higher than those of other imaging parameters (0.954, 92.46, 91.85 for T1ρ; 0.949, 92.52, 91.24 for MD). The model combining T1ρ and MD exhibited better diagnostic performance with higher AUC values than any individual method for staging liver fibrosis (≥ F1: 1.000 (0.884-1.000); ≥ F2: 0.935 (0.782-0.992); ≥ F3: 0.982 (0.852-1.000); F4: 0.986 (0.859-1.000)). CONCLUSION: Among the evaluated imaging parameters, T1ρ and MD were superior for differentiating varying liver fibrosis stages. The model combining T1ρ and MD was promising to be a credible diagnostic biomarker to detect and accurately stage liver fibrosis.

Isthmin-1 promotes growth and progression of colorectal cancer through the interaction with EGFR and YBX-1.

While previous studies have indicated the involvement of Isthmin 1 (ISM1), a secreted protein, in cancer development, the precise mechanisms have remained elusive. In this study, we unveiled that ISM1 is significantly overexpressed in both the blood and tissue samples of colorectal cancer (CRC) patients, correlating with their poor prognosis. Functional experiments demonstrated that enforced ISM1 expression significantly enhances CRC proliferation, migration, invasion and tumor growth. Notably, our investigation reveals an interaction of ISM1 with epidermal growth factor receptor (EGFR), a member of the receptor tyrosine kinase (RTK) family of CRC cells. The binding of ISM1 triggered EGFR activation and initiate downstream signaling pathways. Meanwhile, intracellular ISM1 interacted with Y-box binding protein 1 (YBX1), enhancing its transcriptional regulation on EGFR. Furthermore, our research uncovered the regulation of ISM1 expression by the hypoxia-inducible transcription factor HIF-1α in CRC cells. Mechanistically, we identified HIF-1α as a direct regulator of ISM1, binding to a hypoxia response element on its promoter. This novel mechanism illuminated potential therapeutic targets, offering insights into restraining HIF-1α/ISM1/EGFR-driven CRC progression and metastasis.

Effects of the ZrO2 Crystalline Phase and Morphology on the Thermocatalytic Decomposition of Dimethyl Methylphosphonate.

Thermocatalytic decomposition is an efficient purification technology that is potentially applicable to degrading chemical warfare agents and industrial toxic gases. In particular, ZrO2 has attracted attention as a catalyst for the thermocatalytic decomposition of dimethyl methylphosphonate (DMMP), which is a simulant of the nerve gas sarin. However, the influence of the crystal phase and morphology on the catalytic performance of ZrO2 requires further exploration. In this study, monoclinic- and tetragonal-phase ZrO2 (m- and t-ZrO2, respectively) with nanoparticle, flower-like shape and hollow microsphere morphologies were prepared via hydrothermal and solvothermal methods, and their thermocatalytic decomposition of DMMP was systematically investigated. For a given morphology, m-ZrO2 performed better than t-ZrO2. For a given crystalline phase, the morphology of hollow microspheres resulted in the longest protection time. The exhaust gases generated by the thermocatalytic decomposition of DMMP mainly comprised H2, CO2, H2O and CH3OH, and the by-products were phosphorus oxide species. Thus, the deactivation of ZrO2 was attributed to the deposition of these phosphorous oxide species on the catalyst surface. These results are expected to help guide the development of catalysts for the safe disposal of chemical warfare agents.

Neutrophil to albumin ratio: a biomarker in non-alcoholic fatty liver disease and with liver fibrosis.

Objective: Given the high prevalence of non-alcoholic fatty liver disease (NAFLD) and its potential to progress to liver fibrosis, it is crucial to identify the presence of NAFLD in patients to guide their subsequent management. However, the current availability of non-invasive biomarkers for NAFLD remains limited. Therefore, further investigation is needed to identify and develop non-invasive biomarkers for NAFLD. Methods: A retrospective analysis was conducted on 11,883 patients admitted to the Healthcare Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2016 to December 2019 and divided into NAFLD and non-NAFLD groups. Anthropometric and laboratory examination data were collected. The correlations between variables and NAFLD were evaluated using the student's t-test or Mann-Whitney U test and binary logistic regression analysis. The predictive ability of these variables for NAFLD was assessed using the areas under the curves (AUCs) of receiver operating characteristics. Results: Among the included patients, 3,872 (32.58%) were diagnosed with NAFLD, with 386 (9.97%) individuals having liver fibrosis. Patients with NAFLD exhibited a higher proportion of males, elevated body mass index (BMI), and increased likelihood of hypertension, diabetes mellitus, and atherosclerosis. Logistic regression analysis identified the neutrophil to albumin ratio (NAR) as the most promising novel inflammation biomarkers, with the highest AUC value of 0.701, a cut-off value of 0.797, sensitivity of 69.40%, and specificity of 66.00% in identifying the risk of NAFLD. Moreover, NAR demonstrated superior predictive value in identifying NAFLD patients at risk of liver fibrosis, with an AUC value of 0.795, sensitivity of 71.30%, and specificity of 73.60% when NAR reached 1.285. Conclusion: These findings highlight that the novel inflammatory biomarker, NAR, is a convenient and easily accessible non-invasive predictor for NAFLD and NAFLD with liver fibrosis.

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study.

PURPOSE: This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model. METHOD: Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes. RESULTS: Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities. CONCLUSION: The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

New full-counts phase-matched data-driven gated (DDG) PET/CT.

BACKGROUND: Data-driven gated (DDG) PET has gained clinical acceptance and has been shown to match or outperform external-device gated (EDG) PET. However, in most clinical applications, DDG PET is matched with helical CT acquired in free breathing (FB) at a random respiratory phase, leaving registration, and optimal attenuation correction (AC) to chance. Furthermore, DDG PET requires additional scan time to reduce image noise as it only preserves 35%-50% of the PET data at or near the end-expiratory phase of the breathing cycle. PURPOSE: A new full-counts, phase-matched (FCPM) DDG PET/CT was developed based on a low-dose cine CT to improve registration between DDG PET and DDG CT, to reduce image noise, and to avoid increasing acquisition times in DDG PET. METHODS: A new DDG CT was developed for three respiratory phases of CT images from a low dose cine CT acquisition of 1.35 mSv for a coverage of about 15.4 cm: end-inspiration (EI), average (AVG), and end-expiration (EE) to match with the three corresponding phases of DDG PET data: -10% to 15%; 15% to 30%, and 80% to 90%; and 30% to 80%, respectively. The EI and EE phases of DDG CT were selected based on the physiological changes in lung density and body outlines reflected in the dynamic cine CT images. The AVG phase was derived from averaging of all phases of the cine CT images. The cine CT was acquired over the lower lungs and/or upper abdomen for correction of misregistration between PET and FB CT as well as DDG PET and FB CT. The three phases of DDG CT were used for AC of the corresponding phases of PET. After phase-matched AC of each PET dataset, the EI and AVG PET data were registered to the EE PET data with deformable image registration. The final result was FCPM DDG PET/CT which accounts for all PET data registered at the EE phase. We applied this approach to 14 18F-FDG lung cancer patient studies acquired at 2 min/bed position on the GE Discovery MI (25-cm axial FOV) and evaluated its efficacy in improved quantification and noise reduction. RESULTS: Relative to static PET/CT, the SUVmax increases for the EI, AVG, EE, and FCPM DDG PET/CT were 1.67 ± 0.40, 1.50 ± 0.28, 1.64 ± 0.36, and 1.49 ± 0.28, respectively. There were 10.8% and 9.1% average decreases in SUVmax from EI and EE to FCPM DDG PET/CT, respectively. EI, AVG, and EE DDG PET/CT all maintained increased image noise relative to static PET/CT. However, the noise levels of FCPM and static PET were statistically equivalent, suggesting the inclusion of all counts was able to decrease the image noise relative to EI and EE DDG PET/CT. CONCLUSIONS: A new FCPM DDG PET/CT has been developed to account for 100% of collected PET data in DDG PET applications. Image noise in FCPM is comparable to static PET, while small decreases in SUVmax were also observed in FCPM when compared to either EI or EE DDG PET/CT.