Genotype-dependent N-glycosylation and newly exposed O-glycosylation affect plasmin-induced cleavage of histidine-rich glycoprotein (HRG).

Histidine-rich glycoprotein (HRG) is an abundant plasma protein harboring at least three N-glycosylation sites. HRG integrates many biological processes, such as coagulation, antiangiogenic activity, and pathogen clearance. Importantly, HRG is known to exhibit five genetic variants with minor allele frequencies of more than 10%. Among them, Pro204Ser can induce a fourth N-glycosylation site (Asn202). Considerable efforts have been made to reveal the biological function of HRG, whereas data on HRG glycosylation are scarcer. To close this knowledge gap, we used C18-based LC-MS/MS to study the glycosylation characteristics of six HRG samples from different sources. We used endogenous HRG purified from human plasma and compared its glycosylation to that of the recombinant HRG produced in Chinese hamster ovary cells or human embryonic kidney 293 cells, targeting distinct genotypic isoforms. In endogenous plasma HRG, every N-glycosylation site was occupied predominantly with a sialylated diantennary complex-type glycan. In contrast, in the recombinant HRGs, all glycans showed different antennarities, sialylation, and core fucosylation, as well as the presence of oligomannose glycans, LacdiNAcs, and antennary fucosylation. Furthermore, we observed two previously unreported O-glycosylation sites in HRG on residues Thr273 and Thr274. These sites together showed more than 90% glycan occupancy in all HRG samples studied. To investigate the potential relevance of HRG glycosylation, we assessed the plasmin-induced cleavage of HRG under various conditions. These analyses revealed that the sialylation of the N- and O-glycans as well as the genotype-dependent N-glycosylation significantly influenced the kinetics and specificity of plasmin-induced cleavage of HRG.

Proteogenomic Features of the Highly Polymorphic Histidine-rich Glycoprotein Arose Late in Evolution.

Histidine-rich glycoprotein (HRG) is a liver-produced protein circulating in human serum at high concentrations of around 125 µg/ml. HRG belongs to the family of type-3 cystatins and has been implicated in a plethora of biological processes, albeit that its precise function is still not well understood. Human HRG is a highly polymorphic protein, with at least five variants with minor allele frequencies of more than 10%, variable in populations from different parts of the world. Considering these five mutations we can theoretically expect 35 = 243 possible genetic HRG variants in the population. Here, we purified HRG from serum of 44 individual donors and investigated by proteomics the occurrence of different allotypes, each being either homozygote or heterozygote for each of the five mutation sites. We observed that some mutational combinations in HRG were highly favored, while others were apparently missing, although they ought to be present based on the independent assembly of these five mutation sites. To further explore this behavior, we extracted data from the 1000 genome project (n ∼ 2500 genomes) and assessed the frequency of different HRG mutants in this larger dataset, observing a prevailing agreement with our proteomics data. From all the proteogenomic data we conclude that the five different mutation sites in HRG are not occurring independently, but several mutations at different sites are fully mutually exclusive, whereas others are highly intwined. Specific mutations do also affect HRG glycosylation. As the levels of HRG have been suggested as a protein biomarker in a variety of biological processes (e.g., aging, COVID-19 severity, severity of bacterial infections), we here conclude that the highly polymorphic nature of the protein needs to be considered in such proteomics evaluations, as these mutations may affect HRG's abundance, structure, posttranslational modifications, and function.

Oxonium Ion-Guided Optimization of Ion Mobility-Assisted Glycoproteomics on the timsTOF Pro.

Spatial separation of ions in the gas phase, providing information about their size as collisional cross-sections, can readily be achieved through ion mobility. The timsTOF Pro (Bruker Daltonics) series combines a trapped ion mobility device with a quadrupole, collision cell, and a time-of-flight analyzer to enable the analysis of ions at great speed. Here, we show that the timsTOF Pro is capable of physically separating N-glycopeptides from nonmodified peptides and producing high-quality fragmentation spectra, both beneficial for glycoproteomics analyses of complex samples. The glycan moieties enlarge the size of glycopeptides compared with nonmodified peptides, yielding a clear cluster in the mobilogram that, next to increased dynamic range from the physical separation of glycopeptides and nonmodified peptides, can be used to make an effective selection filter for directing the mass spectrometer to analytes of interest. We designed an approach where we (1) focused on a region of interest in the ion mobilogram and (2) applied stepped collision energies to obtain informative glycopeptide tandem mass spectra on the timsTOF Pro:glyco-polygon-stepped collision energy-parallel accumulation serial fragmentation. This method was applied to selected glycoproteins, human plasma- and neutrophil-derived glycopeptides. We show that the achieved physical separation in the region of interest allows for improved extraction of information from the samples, even at shorter liquid chromatography gradients of 15 min. We validated our approach on human neutrophil and plasma samples of known makeup, in which we captured the anticipated glycan heterogeneity (paucimannose, phosphomannose, high mannose, hybrid and complex glycans) from plasma and neutrophil samples at the expected abundances. As the method is compatible with off-the-shelve data acquisition routines and data analysis software, it can readily be applied by any laboratory with a timsTOF Pro and is reproducible as demonstrated by a comparison between two laboratories.

Echinococcus multilocularis serpin regulates macrophage polarization and reduces gut dysbiosis in colitis.

Helminths serve as principal regulators in modulating host immune responses, and their excretory-secretory proteins are recognized as potential therapeutic agents for inflammatory bowel disease. Nevertheless, our comprehension of the mechanisms underlying immunoregulation remains restricted. This investigation delves into the immunomodulatory role of a secretory protein serpin (Emu-serpin), within the larval stage of Echinococcus multilocularis. Our observations indicate that Emu-serpin effectively alleviates dextran sulfate sodium-induced colitis, yielding a substantial reduction in immunopathology and an augmentation of anti-inflammatory cytokines. Furthermore, this suppressive regulatory effect is concomitant with the reduction of gut microbiota dysbiosis linked to colitis, as evidenced by a marked impediment to the expansion of the pathobiont taxa Enterobacteriaceae. In vivo experiments demonstrate that Emu-serpin facilitates the expansion of M2 phenotype macrophages while concurrently diminishing M1 phenotype macrophages, alongside an elevation in anti-inflammatory cytokine levels. Subsequent in vitro investigations involving RAW264.7 and bone marrow macrophages reveal that Emu-serpin induces a conversion of M2 macrophage populations from a pro-inflammatory to an anti-inflammatory phenotype through direct inhibition. Adoptive transfer experiments reveal the peritoneal macrophages induced by Emu-serpin alleviate colitis and gut microbiota dysbiosis. In summary, these findings propose that Emu-serpin holds the potential to regulate macrophage polarization and maintain gut microbiota homeostasis in colitis, establishing it as a promising candidate for developing helminth therapy for preventing inflammatory diseases.

Whole-exome sequencing and functional validation reveal a rare missense variant in MMP7 that confers ovarian endometriosis risk.

Prior studies have shown that genetic factors play important roles in ovarian endometriosis. Herein, we first analyzed the whole-exome sequencing data from 158 patients with ovarian endometriosis and 385 local control women without endometriosis. Among which, a rare missense variant in the MMP7 (p.I79T, rs150338402) gene exhibited a significant frequency difference. This rare variant was screened in an additional 1176 patients and 600 control women via direct DNA sequencing. Meanwhile, a total of 38 available clinical characteristics were collected. Our results showed 45 out of 1334 (3.37%) patients, while 15 out of 985 control women (1.52%) (P = 0.0076) harbored this rare variant, respectively. This rare variant was associated with clinical features such as follicle-stimulating hormone (Padj = 0.0342), luteinizing hormone (Padj = 0.0038), progesterone (Padj = 1.4e-7), testosterone (Padj = 0.0923), total bilirubin (Padj = 0.0699), carcinoembryonic antigen (Padj = 0.0665) and squamous cell carcinoma antigen (Padj = 0.0817), respectively. Functional assays showed that this rare variant could promote cell migration, invasion, epithelial-mesenchymal transition (EMT) and increase the proteolytic protein activity of MMP7, implicating that the increased capacities of cell invasion, migration and EMT might be mediated by enhanced proteolytic activity of MMP7 mutant. These results showed that the MMP7 rare missense variant (p.I79T) played important roles in the pathogenesis of ovarian endometriosis. In conclusion, we identified, for the first time, a significantly enriched MMP7 rare variant in ovarian endometriosis; this rare variant was closely associated with certain clinical features in ovarian endometriosis; thus, it could be a promising early diagnostic biomarker for this disease.

Dual siRNA-Loaded Cell Membrane Functionalized Matrix Facilitates Bone Regeneration with Angiogenesis and Neurogenesis.

Vascularization and innervation play irreplaceable roles in bone regeneration and bone defect repair. However, the reconstruction of blood vessels and neural networks is often neglected in material design. This study aims to design a genetically functionalized matrix (GFM) and enable it to regulate angiogenesis and neurogenesis to accelerate the process of bone defect repair. The dual small interfering RNA (siRNA)-polyvinylimide (PEI) (siRP) complexes that locally knocked down soluble vascular endothelial growth factor receptor 1 (sFlt-1) and p75 neurotrophic factor receptor (p75NTR ) are prepared. The hybrid cell membrane (MM) loaded siRP is synthesized as siRNA@MMs to coat on polylactone (PCL) electrospun fibers for mimicking the natural bone matrix. The results indicates that siRNA@MMs could regulate the expression of vascular-related and neuro-related cytokines secreted by mesenchymal stem cells (MSCs). GFMs promote the expression of osteogenic differentiation through paracrine function in vitro. GFMs attenuates inflammation and promotes osseointegration by regulating the coupling of vascularization and innervation in vivo. This study uses the natural hybrid cell membrane to carry genetic material and assist in the vascularization and innervation function of two siRNA. The results present the significance of neuro-vascularized organoid bone and may provide a promising choice for the design of bone tissue engineering scaffold.

Acidified Nitrogen Self-Doped Porous Carbon with Superprotonic Conduction for Applications in Solid-State Proton Battery.

Solid proton electrolytes play a crucial role in various electrochemical energy storage and conversion devices. However, the development of fast proton conducting solid proton electrolytes at ambient conditions remains a significant challenge. In this study, a novel acidified nitrogen self-doped porous carbon material is presented that demonstrates exceptional superprotonic conduction for applications in solid-state proton battery. The material, designated as MSA@ZIF-8-C, is synthesized through the acidification of nitrogen-doped porous carbon, specifically by integrating methanesulfonic acid (MSA) into zeolitic imidazolate framework-derived nitrogen self-doped porous carbons (ZIF-8-C). This study reveals that MSA@ZIF-8-C achieves a record-high proton conductivity beyond 10-2  S cm-1 at ambient condition, along with good long-term stability, positioning it as a cutting-edge alternative solid proton electrolyte to the default aqueous H2 SO4 electrolyte in proton batteries.

Landscapes of gut bacterial and fecal metabolic signatures and their relationship in severe preeclampsia.

BACKGROUND: Preeclampsia is a pregnancy-specific disease leading to maternal and perinatal morbidity. Hypertension and inflammation are the main characteristics of preeclampsia. Many factors can lead to hypertension and inflammation, including gut microbiota which plays an important role in hypertension and inflammation in humans. However, alterations to the gut microbiome and fecal metabolome, and their relationships in severe preeclampsia are not well known. This study aims to identify biomarkers significantly associated with severe preeclampsia and provide a knowledge base for treatments regulating the gut microbiome. METHODS: In this study, fecal samples were collected from individuals with severe preeclampsia and healthy controls for shotgun metagenomic sequencing to evaluate changes in gut microbiota composition. Quantitative polymerase chain reaction analysis was used to validate the reliability of our shotgun metagenomic sequencing results. Additionally, untargeted metabolomics analysis was performed to measure fecal metabolome concentrations. RESULTS: We identified several Lactobacillaceae that were significantly enriched in the gut of healthy controls, including Limosilactobacillus fermentum, the key biomarker distinguishing severe preeclampsia from healthy controls. Limosilactobacillus fermentum was significantly associated with shifts in KEGG Orthology (KO) genes and KEGG pathways of the gut microbiome in severe preeclampsia, such as flagellar assembly. Untargeted fecal metabolome analysis found that severe preeclampsia had higher concentrations of Phenylpropanoate and Agmatine. Increased concentrations of Phenylpropanoate and Agmatine were associated with the abundance of Limosilactobacillus fermentum. Furthermore, all metabolites with higher abundances in healthy controls were enriched in the arginine and proline metabolism pathway. CONCLUSION: Our research indicates that changes in metabolites, possibly due to the gut microbe Limosilactobacillus fermentum, can contribute to the development of severe preeclampsia. This study provides insights into the interaction between gut microbiome and fecal metabolites and offers a basis for improving severe preeclampsia by modulating the gut microbiome.

Evaluation of the role of atherogenic index of plasma in the reversion from Prediabetes to normoglycemia or progression to Diabetes: a multi-center retrospective cohort study.

BACKGROUND: Atherosclerosis is closely linked with glucose metabolism. We aimed to investigate the role of the atherogenic index of plasma (AIP) in the reversal of prediabetes to normal blood glucose levels or its progression to diabetes. METHODS: This multi-center retrospective cohort study included 15,421 prediabetic participants from 32 regions across 11 cities in China, under the aegis of the Rich Healthcare Group's affiliated medical examination institutions. Throughout the follow-up period, we monitored changes in the glycemic status of these participants, including reversal to normal fasting glucose (NFG), persistence in the prediabetic state, or progression to diabetes. Segmented regression, stratified analysis, and restricted cubic spline (RCS) were performed based on the multivariable Cox regression model to evaluate the association between AIP and the reversal of prediabetes to NFG or progression to diabetes. RESULTS: During a median follow-up period of 2.9 years, we recorded 6,481 individuals (42.03%) reverting from prediabetes to NFG, and 2,424 individuals (15.72%) progressing to diabetes. After adjusting for confounders, AIP showed a positive correlation with the progression from prediabetes to diabetes [(Hazard ratio (HR) 1.42, 95% confidence interval (CI):1.24-1.64)] and a negative correlation with the reversion from prediabetes to NFG (HR 0.89, 95%CI:0.81-0.98); further RCS demonstrated a nonlinear relationship between AIP and the reversion from prediabetes to NFG/progression to diabetes, identifying a turning point of 0.04 for reversion to NFG and 0.17 for progression to diabetes. In addition, we observed significant differences in the association between AIP and reversion from prediabetes to NFG/progression to diabetes across age subgroups, specifically indicating that the risk associated with AIP for progression from prediabetes to diabetes was relatively higher in younger populations; likewise, a younger age within the adult group favored the reversion from prediabetes to NFG in relation to AIP. CONCLUSION: Our study, for the first time, reveals a negative correlation between AIP and the reversion from prediabetes to normoglycemia and validates the crucial role of AIP in the risk assessment of prediabetes progression. Based on threshold analysis, therapeutically, keeping the AIP below 0.04 was of paramount importance for individuals with prediabetes aiming for reversion to NFG; preventatively, maintaining AIP below 0.17 was vital to reduce the risk of diabetes onset for those with prediabetes.

Impact of non-Gaussian noise on GMI and LDPC performance in neural network equalized systems.

In this Letter, the impact of non-Gaussian noise caused by a nonlinear equalizer on low-density parity-check code (LDPC) performance is investigated in a 25-km 50-Gb/s pulse amplitude modulation4 (PAM4) direct detection system. The lookup table (LUT)-based log-likelihood ratio (LLR) calculation method is proposed to enhance the LDPC performance for the non-Gaussian noise case. Compared to the conventional LLR calculation method based on Gaussian distribution, the proposed method can improve 0.6-dB sensitivity in artificial neural network (ANN) equalizer systems. In addition, the conventional generalized mutual information (GMI) is proven to be an imperfect predictor of LDPC performance after nonlinear equalizers, such as decision feedback equalization (DFE) and ANN equalizer.

Wearable strain sensor integrating mechanoluminescent fiber with a flexible printed circuit.

This paper reports an optical strain sensor that integrates a self-powered mechanoluminescent (ML) elastic fiber with a flexible circuit. The inclusion of an alumina nanoparticle as the additive results in seven-fold enhancement of ML intensity while maintaining flexibility of 120% strain. The sensor facilitates the detection of strain and stretching speed. It attains a sensitivity of 0.0022 lx/(1% strain) and a resolution of 0.2% strain, respectively. We have successfully applied it to detect bending motions of the finger, wrist, and elbow. This wearable strain sensor holds promise for diverse applications in wearable technology.

Seamless rate adaptation for wide SNR range in FSO systems based on rate compatible modulation.

We propose and experimentally demonstrate a large-range and seamless rate-adaptive free-space optical (FSO) scheme based on rate compatible modulation (RCM). It utilizes a mapping method through weighted summation, enabling an even increase of bit energy. This allows the system to seamlessly adjust the throughput. In addition, the handover mechanism based on rate check and acknowledgment signals ensures a wide coverage of signal-to-noise ratio (SNR) fluctuation. It is worth noting that this scheme does not require any changes to the mapping matrix and decoding algorithm, making it easier to implement in real-world systems. Simulation proves the superiority of the proposed approach in terms of coding rate coverage by applying a fixed mapping matrix compared to a traditional adaptive modulation and coding scheme. Experimental demonstration over a 50 m FSO link verifies that the SNR dynamic range of this scheme is >15 dB with a seamless rate adjustment between 6.7 Gb/s and 53.6 Gb/s and the operability of RCM is not limited by the time scale of turbulence, revealing huge potential for the massive connections in future smart cities.

Neochlorogenic Acid Combined with Bone Marrow Mesenchymal Stem Cells Encapsulated into GelMA Hydrogel for Transplantation to Repair Intervertebral Disk Degeneration.

Intervertebral disk degeneration is a common disease with an unknown etiology. Currently, tissue engineering is considered to be an important method for intervertebral disk repair. Although transplanted stem cells may disrupt the repair process because of apoptosis caused by the oxidative microenvironment. Herein, bone marrow mesenchymal stem cell (BMSC) and Neochlorogenic acid (Ncg) were encapsulated into a GelMA hydrogel as a carrier to protect transplanted stem cells. Ncg effectively inhibited the oxidative stress process and reduced the apoptosis rate. A 5% GelMA hydrogel had a large pore size and porosity that provided an enhanced survival space for cells. An in vivo assessment showed that treatment with GelMA + BMSC + Ncg produced greater repair of degenerated intervertebral disks than that found in other model groups. Thus, this study may help contribute to improving stem cell transplantation for treating intervertebral disk degeneration.

Clinical and epidemiological features of imported loiasis in Beijing: a report from patients returned from Africa.

BACKGROUND: Loiasis is one of the significant filarial diseases for people living in West and Central Africa with wide endemic area but is not seen in China. As economy booms and international traveling increase, China faces more and more imported parasitic diseases that are not endemic locally. Loiasis is one of the parasitic diseases that enter China by travelers infected in Africa. The better understanding of the clinical and laboratory features of loa loa infection will facilitate the diagnosis and treatment of loiasis in China. METHODS: The study targeted travelers who were infected with L. loa in endemic Africa regions and returned to Beijing between 2014 and 2023. Epidemiological, clinical, and biological data as well as treatment of these patients were collected. RESULTS: Total 21 cases were identified as L. loa infection based on their typical clinical manifestations and parasite finding. All cases had a history of travel to Africa for more than 6 months, most of them are the construction workers dispatched to West Africa with outdoor activities. Calabar swelling (n = 19; 90.5%) and pruritus (n = 11; 52.4%) were among the most common clinical symptoms followed by muscle pain (n = 7; 33.3%) and skin rash (n = 2; 9.5%). The adult worms were observed in the eyelid or subconjunctiva (n = 2; 9.5%) and subcutaneous tissues (n = 2; 9.5%). Although all patients presented with a high eosinophil count (> 0.52 × 109/L), only two cases displayed microfilariae in fresh venous blood and positive for filarial antigen. A cut section of adult worm was observed through biopsy on a skin nodule surrounded by lymphocytes, plasma cells and eosinophils. All subjects were positive in PCR targeting L. loa ITS-1. The constructed phylogenetic tree based on the amplified ITS-1 sequences identified their genetical relation to the L. Loa from Africa. All patients treated with albendazole and diethylcarbamazine were recovered without relapse. CONCLUSION: This study provides useful information and guideline for physicians and researchers in non-endemic countries to diagnose and treat loiasis and L. loa infections acquired from endemic regions.

Association between weight-adjusted waist index and non-alcoholic fatty liver disease: a population-based study.

BACKGROUND: Obesity is the most important driver of non-alcoholic fatty liver disease (NAFLD); nevertheless, the relationship of weight-adjusted waist index (WWI), a new obesity index, with NAFLD is unclear. METHODS: This retrospective study used data from the NAGALA project from 1994 to 2016. WWI values were calculated using waist circumference (WC) and weight measurements of the participants. Three stepwise adjusted logistic regression models were developed to assess the relationship of WWI with NAFLD in the whole population and in both sexes. Additionally, we also conducted a series of exploratory analysis to test the potential impact of body mass index (BMI), age, smoking status and exercise habits on the association of WWI with NAFLD. Receiver operating characteristic (ROC) curves were used to estimate cut-off points for identifying NAFLD in the entire population and in both sexes. RESULTS: The current study included a population of 11,805 individuals who participated in health screenings, including 6,451 men and 5,354 women. After adjusting for all non-collinear variables in the multivariable logistic regression model, we found a significant positive correlation of WWI with NAFLD. For each unit increase in WWI, the risk of NAFLD increased by 72% in the entire population, by 84% in men, and by 63% in women. Furthermore, subgroup analyses revealed no significant discrepancies in the correlation of WWI with NAFLD across individuals with varying ages, exercise habits, and smoking status (all P-interaction > 0.05), except for different BMI groups (P-interaction < 0.05). Specifically, compared to the overweight/obese group, the relationship of WWI with NAFLD was significantly stronger in the non-obese group, especially in non-obese men. Finally, based on the results of ROC analysis, we determined that the WWI cut-off point used to identify NAFLD was 9.7675 in men and 9.9987 in women. CONCLUSIONS: This study is the first to establish a positive correlation between WWI and NAFLD. Moreover, assessing the influence of WWI on NAFLD in individuals without obesity may yield more valuable insights compared to those who are overweight or obese.

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort.

BACKGROUND: Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. METHODS: We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. RESULTS: Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. CONCLUSION: Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Prognostic value of geriatric nutritional risk index in patients with stable coronary artery disease undergoing percutaneous coronary intervention.

BACKGROUND: Malnutrition increases the risk of poor prognosis in patients with cardiovascular disease, and our current research was designed to assess the predictive performance of the Geriatric Nutrition Risk Index (GNRI) for the occurrence of poor prognosis after percutaneous coronary intervention (PCI) in patients with stable coronary artery disease (SCAD) and to explore possible thresholds for nutritional intervention. METHODS: This study retrospectively enrolled newly diagnosed SCAD patients treated with elective PCI from 2014 to 2017 at Shinonoi General Hospital, with all-cause death as the main follow-up endpoint. Cox regression analysis and restricted cubic spline (RCS) regression analysis were used to explore the association of GNRI with all-cause death risk and its shape. Receiver operating characteristic curve (ROC) analysis and piecewise linear regression analysis were used to evaluate the predictive performance of GNRI level at admission on all-cause death in SCAD patients after PCI and to explore possible nutritional intervention threshold points. RESULTS: The incidence of all-cause death was 40.47/1000 person-years after a mean follow-up of 2.18 years for 204 subjects. Kaplan-Meier curves revealed that subjects at risk of malnutrition had a higher all-cause death risk. In multivariate Cox regression analysis, each unit increase in GNRI reduced the all-cause death risk by 14% (HR 0.86, 95% CI 0.77, 0.95), and subjects in the GNRI > 98 group had a significantly lower risk of death compared to those in the GNRI < 98 group (HR 0.04, 95% CI 0.00, 0.89). ROC analysis showed that the baseline GNRI had a very high predictive performance for all-cause death (AUC = 0.8844), and the predictive threshold was 98.62; additionally, in the RCS regression analysis and piecewise linear regression analysis we found that the threshold point for the GNRI-related all-cause death risk was 98.28 and the risk will be significantly reduced when the subjects' baseline GNRI was greater than 98.28. CONCLUSIONS: GNRI level at admission was an independent predictor of all-cause death in SCAD patients after PCI, and GNRI equal to 98.28 may be a useful threshold for nutritional intervention in SCAD patients treated with PCI.

Relative importance of triglyceride glucose index combined with body mass index in predicting recovery from prediabetic state to normal fasting glucose: a cohort analysis based on a Chinese physical examination population.

BACKGROUND: Prediabetes is a high-risk state for diabetes, and numerous studies have shown that the body mass index (BMI) and triglyceride-glucose (TyG) index play significant roles in risk prediction for blood glucose metabolism. This study aims to evaluate the relative importance of BMI combination with TyG index (TyG-BMI) in predicting the recovery from prediabetic status to normal blood glucose levels. METHODS: A total of 25,397 prediabetic subjects recruited from 32 regions across China. Normal fasting glucose (NFG), prediabetes, and diabetes were defined referring to the American Diabetes Association (ADA) criteria. After normalizing the independent variables, the impact of TyG-BMI on the recovery or progression of prediabetes was analyzed through the Cox regression models. Receiver Operating Characteristic (ROC) curve analysis was utilized to visualize and compare the predictive value of TyG-BMI and its constituent components in prediabetes recovery/progression. RESULTS: During the average observation period of 2.96 years, 10,305 individuals (40.58%) remained in the prediabetic state, 11,278 individuals (44.41%) recovered to NFG, and 3,814 individuals (15.02%) progressed to diabetes. The results of multivariate Cox regression analysis demonstrated that TyG-BMI was negatively associated with recovery from prediabetes to NFG and positively associated with progression from prediabetes to diabetes. Further ROC analysis revealed that TyG-BMI had higher impact and predictive value in predicting prediabetes recovering to NFG or progressing to diabetes in comparison to the TyG index and BMI. Specifically, the TyG-BMI threshold for predicting prediabetes recovery was 214.68, while the threshold for predicting prediabetes progression was 220.27. Additionally, there were significant differences in the relationship of TyG-BMI with prediabetes recovering to NFG or progressing to diabetes within age subgroups. In summary, TyG-BMI is more suitable for assessing prediabetes recovery or progression in younger populations (< 45 years old). CONCLUSIONS: This study, for the first time, has revealed the significant impact and predictive value of the TyG index in combination with BMI on the recovery from prediabetic status to normal blood glucose levels. From the perspective of prediabetes intervention, maintaining TyG-BMI within the threshold of 214.68 holds crucial significance.

Object phase-valid region segmentation method for FPP-based three-dimensional measurement.

In most existing studies based on fringe projector profilometry (FPP), the whole scenario is reconstructed, or the ideal experimental settings are established to segment the object easily. However, in real industrial scenarios, automated object detection and segmentation are essential to perform object-level measurement. To address the problem, a dual-wavelet feature interaction network (DWFI-Net) is developed in this paper to perform object phase-valid region segmentation, where both the background and shadow are removed. In our work, the modulation and wrapped phase maps are considered as inputs innovatively. The modulation maps provide abundant structures and textures, while the wrapped phase maps complement and enhance shadows and edges. An adaptive wavelet feature interaction (AWFI) module is presented to learn and fuse the features, where discrete wavelet transformation (DWT) is applied to decompose the features. An edge-aware discrete cosine transformation (EDCT) module is developed as a decoder, where the discrete cosine transformation (DCT) is applied to interpret the fused features. Qualitative and quantitative experiments are performed to verify the superiority of our DWFI-Net and its effectiveness on object-level three-dimensional measurement based on FPP.

Antihyperuricemic activity and inhibition mechanism of xanthine oxidase inhibitory peptides derived from whey protein by virtual screening.

Xanthine oxidase (XO), a rate-limiting enzyme in uric acid production, is the pivotal therapeutic target for gout and hyperuricemia. In this study, 57 peptides from α-lactalbumin and ß-lactoglobulin were obtained via virtual enzymatic hydrolysis, and 10 XO inhibitory peptides were virtually screened using molecular docking. Then toxicity, allergenicity, solubility, and isoelectric point of the obtained 10 novel peptides were evaluated by in silico tools. The XO activity of these synthetic peptides was tested using an in vitro assay by high-performance liquid chromatography. Their inhibitory mechanism was further explored by molecular docking. The results showed that 4 peptides GL, PM, AL, and AM exhibited higher inhibitory activity, and their half maximal inhibitory concentration in vitro was 10.20 ± 0.89, 23.82 ± 0.94, 34.49 ± 0.89, and 40.45 ± 0.92 mM, respectively. The peptides fitted well with XO through hydrogen bond, hydrophobic interaction, and van der Waals forces, and amino acid residues Glu802, Leu873, Arg880, and Pro1076 played an important role in this process. Overall, this study indicated 4 novel peptides GL, PM, AL, and AM from whey protein exhibited XO inhibitory activity, and they might be useful and safe XO inhibitors for hyperuricemia prevention and treatment.