Extravascular administration of IGF1R antagonists protects against aortic aneurysm in rodent and porcine models.

An abdominal aortic aneurysm (AAA) is a life-threatening cardiovascular disease. We identified plasma insulin-like growth factor 1 (IGF1) as an independent risk factor in patients with AAA by correlating plasma IGF1 with risk. Smooth muscle cell- or fibroblast-specific knockout of Igf1r, the gene encoding the IGF1 receptor (IGF1R), attenuated AAA formation in two mouse models of AAA induced by angiotensin II infusion or CaCl2 treatment. IGF1R was activated in aortic aneurysm samples from human patients and mice with AAA. Systemic administration of IGF1C, a peptide fragment of IGF1, 2 weeks after disease development inhibited AAA progression in mice. Decreased AAA formation was linked to competitive inhibition of IGF1 binding to its receptor by IGF1C and modulation of downstream alpha serine/threonine protein kinase (AKT)/mammalian target of rapamycin signaling. Localized application of an IGF1C-loaded hydrogel was developed to reduce the side effects observed after systemic administration of IGF1C or IGF1R antagonists in the CaCl2-induced AAA mouse model. The inhibitory effect of the IGF1C-loaded hydrogel administered at disease onset on AAA formation was further evaluated in a guinea pig-to-rat xenograft model and in a sheep-to-minipig xenograft model of AAA formation. The therapeutic efficacy of IGF1C for treating AAA was tested through extravascular delivery in the sheep-to-minipig model with AAA established for 2 weeks. Percutaneous injection of the IGF1C-loaded hydrogel around the AAA resulted in improved vessel flow dynamics in the minipig aorta. These findings suggest that extravascular administration of IGF1R antagonists may have translational potential for treating AAA.

A kinetic-assisted growth curve prediction method for Chlamydomonas reinhardtii incorporating transfer learning.

Traditional predictions of microalgal growth states rely on empirical or easily implementable kinetic models, leading to significant biases and elevated cost. This study proposes a kinetic-assisted machine learning method for predicting the growth curve of microalgal biomass under small sample conditions. Firstly, a microalgae growth kinetic model is constructed based on the logistic model. A two-stage kinetic fitting strategy is specified to account for the light-dark ratio. The Box-Behnken method is employed for experimental design. Then, using Two-stage TrAdaboost.R2 algorithm, the kinetic model is utilized as the source domain, and the experimental design data serves as the target domain for training machine learning models. The results indicate that the proposed method outperforms a single machine learning model in terms of prediction and has the potential to rapidly estimate microalgal growth trends under different conditions and accurately predict harvested biomass, potentially reducing the need for laborious, expensive, and time-consuming laboratory trials.

ALDOC promotes non-small cell lung cancer through affecting MYC-mediated UBE2N transcription and regulating Wnt/ß-catenin pathway.

Despite advancements in therapeutic options, the overall prognosis for non-small cell lung cancer (NSCLC) remains poor. Therefore, it is crucial to further explore the etiology and targets for novel treatments to effectively manage NSCLC. In this study, immunohistochemistry was used to analyze the expression of aldolase, fructose-bisphosphate C (ALDOC) protein in tumor tissues and adjacent non-malignant tissues from 79 NSCLC patients. Our findings revealed that ALDOC was overexpressed in NSCLC tissues. ALDOC expression was associated with lymph node metastasis, lymphatic metastasis and pathological stage. In addition, Kaplan-Meier analysis showed that higher ALDOC levels were indicative of a poorer prognosis. Additionally, we observed elevated ALDOC mRNA levels in NSCLC cell lines relative to normal cells. To investigate the functional roles of ALDOC, we infected cells with small interfering RNA against ALDOC, which led to attenuated proliferation and migration, as well as ameliorated apoptosis. Furthermore, through our investigations, we discovered that ubiquitin-conjugating enzyme E2N (UBE2N) acts as a downstream factor of ALDOC. ALDOC promoted NSCLC through affecting MYC-mediated UBE2N transcription and regulating the Wnt pathway. More importantly, we found that downregulation of UBE2N or the use of Wnt pathway inhibitor could reverse the promoting effects of ALDOC elevation on NSCLC development in vitro and in vivo. Based on these findings, our study highlights the potential of ALDOC as a future therapeutic target for NSCLC.

Anti-Sca-1 antibody-functionalized vascular grafts improve vascular regeneration via selective capture of endogenous vascular stem/progenitor cells.

Small-diameter vascular grafts fabricated from synthetic biodegradable polymers exhibit beneficial mechanical properties but often face poor regenerative potential. Different tissue engineering approaches have been employed to improve tissue regeneration in vascular grafts, but there remains a requirement for a new generation of synthetic grafts that can orchestrate the host response to achieve robust vascular regeneration. Vascular stem/progenitor cells (SPCs) are mostly found in quiescent niches but can be activated in response to injury and participate in endothelium and smooth muscle regeneration during neo-artery formation. Here, we developed a functional vascular graft by surface immobilization of stem cell antigen-1 (Sca-1) antibody on an electrospun poly(ε-caprolactone) graft (PCL-Sca-1 Ab). PCL-Sca-1 Ab promoted capture and retainment of Sca-1+ SPCs in vitro. In rat abdominal aorta replacement models, PCL-Sca-1 Ab stimulated in vivo recruitment of Sca-1+ SPCs, and drove SPCs differentiation towards vascular cell lineages. The origin of infiltrated Sca-1+ SPCs was further investigated using a bone marrow transplantation mouse model, which revealed that Sca-1+ SPCs originating from the resident tissues and bone marrow contributed to rapid vascular regeneration of vascular grafts. Our data indicated that PCL-Sca-1 Ab vascular grafts may serve as a useful strategy to develop next generation cell-free vascular grafts.

The Specific Changes of Urine Raman Spectra Can Serve as Novel Diagnostic Tools for Disease Characteristics in Patients with Crohn's Disease.

PURPOSE: Crohn's disease (CD) is a chronic recurrent intestinal inflammatory disease that requires repeated invasive examinations. Convenient and noninvasive diagnostic tools for CD are lacking. Surface-enhanced Raman spectroscopy (SERS) can rapidly provide specific metabolite information in various samples. Our previous study has showed urine Raman spectrum can distinguish CD patients from healthy controls noninvasively. In this study, we further investigated the value of urine Raman spectra on identifying the disease characterizations in patients with CD. PATIENTS AND METHODS: Urine samples were analyzed by SERS to acquire specific changes of the spectra from 100 active CD (aCD) patients and 88 inactive CD (iCD) patients. The accuracy of classifier models yielded by SERS was assessed by principal component analysis and support vector machine (PCA-SVM) to investigate spectral differences and disease characterizations. RESULTS: Given a panel of 16 specific Raman spectra, the classifier model was established to predict disease activity between patients with aCD and iCD and achieved higher efficacy than fecal calprotectin (AUC value, 0.864 vs 0.596, P=0.02). After leave-one-patient-out cross-validation, the classifier model still obtained 75.5% of accuracy. The correlation analysis showed it had negative correlation with endoscopic results (r=-0.616, P<0.0001). We further established the classifier model in identifying disease location to discriminate colonic-type from ileal-type CD with 63.6% of accuracy with the significantly increased intensity of 1643 cm-1 band, and the model to predict the spectra changes of before and after treatment in tumor necrosis factor inhibitor responders with 91.2% of accuracy with a panel of 11 specific spectra. The metabolic changes of amino acids, proteins, lipids, and other compounds in urine levels were noted by SERS in patients with CD. CONCLUSION: The specific changes of urine Raman spectra can reflect changes in urine metabolism. It has the potential value on being the promising diagnostic tool for disease characterizations in CD patients by a convenient and noninvasive way.

Non-invasive diagnosis of Crohn's disease based on SERS combined with PCA-SVM.

Crohn's disease (CD) is an idiopathic chronic inflammatory bowel disease without a cure. Most of the CD patients are firstly diagnosed by invasive endoscopy, and clinical and pathological examinations are further required to confirm the diagnosis. Hence, the development of a non-invasive, rapid and accurate diagnosis method for CD patients is essential. In this study, urine samples from 95 CD patients (including 58 active CD (aCD) patients and 37 inactive CD (iCD) patients) and 48 healthy controls (HC) were investigated by surface-enhanced Raman spectroscopy (SERS). The statistical analysis of the three groups (i.e., CD/HC, aCD/HC and iCD/HC) was performed on the measured data. Principal component analysis (PCA)-support vector machine (SVM) and PCA-linear discriminant analysis (LDA) were then employed to establish classification models to distinguish between patients and HC. For the average SERS spectra of patients and HC, the Raman peaks belonging to lipids, proteins and nucleic acids were stronger in patients than those in HC. It showed that the classification accuracy of CD/HC based on PCA-SVM was higher than that of PCA-LDA (82.5% vs. 69.9%). And the classification accuracy of aCD/HC based on PCA-SVM was higher than that of iCD/HC (86.8% vs. 76.5%). The classification model we established distinguished between aCD and HC with 86.2% sensitivity and 87.5% specificity. It indicates that the metabolic change of patients could be identified by measuring urine with SERS, and aCD and HC could be distinguished more effectively. Our findings are helpful for clinicians to diagnose CD patients and monitor the progress and recurrence of the disease.

Quantitative analysis of direct oral anticoagulant rivaroxaban by terahertz spectroscopy.

Rivaroxaban, as a direct oral anticoagulant, has been widely used in the treatment and prevention of thrombosis disease (TD). However, even if the same dose of rivaroxaban is taken, different pathophysiological characteristics of TD patients determine the differences in plasma concentrations between individuals, leading to the difficulties of dosage selection and plasma concentration control. Conventional rivaroxaban detection methods, including prothrombin time method, anti-Xa assay and liquid chromatography-tandem mass spectrometry (LC-MS/MS), are not widely used in clinical practice due to the limitations of accuracy, speed and cost. Here, we present a simple quantitative detection method for rivaroxaban by terahertz (THz) spectroscopy. Combining density functional theory (DFT) method and THz spectroscopy, the THz absorption peaks of rivaroxaban and the corresponding low-frequency vibrational modes are studied theoretically and experimentally. We find linear relationships between the amplitudes of these characteristic peaks and the concentrations of rivaroxaban. Based on these linear functions, we can analyse the rivaroxaban concentration with a detection time of 1 minute per test and the lowest detection limit of 2 µmol mL-1. As compared to Raman spectroscopy method (its detection limit is about 80 µmol mL-1), our method has more potential and is practical for the clinical quantitative detection of rivaroxaban as well as other direct oral anticoagulants.

[A review on multi-modal human motion representation recognition and its application in orthopedic rehabilitation training].

Human motion recognition (HAR) is the technological base of intelligent medical treatment, sports training, video monitoring and many other fields, and it has been widely concerned by all walks of life. This paper summarized the progress and significance of HAR research, which includes two processes: action capture and action classification based on deep learning. Firstly, the paper introduced in detail three mainstream methods of action capture: video-based, depth camera-based and inertial sensor-based. The commonly used action data sets were also listed. Secondly, the realization of HAR based on deep learning was described in two aspects, including automatic feature extraction and multi-modal feature fusion. The realization of training monitoring and simulative training with HAR in orthopedic rehabilitation training was also introduced. Finally, it discussed precise motion capture and multi-modal feature fusion of HAR, as well as the key points and difficulties of HAR application in orthopedic rehabilitation training. This article summarized the above contents to quickly guide researchers to understand the current status of HAR research and its application in orthopedic rehabilitation training.

A multi-feature image retrieval scheme for pulmonary nodule diagnosis.

Deep analysis of radiographic images can quantify the extent of intra-tumoral heterogeneity for personalized medicine.In this paper, we propose a novel content-based multi-feature image retrieval (CBMFIR) scheme to discriminate pulmonary nodules benign or malignant. Two types of features are applied to represent the pulmonary nodules. With each type of features, a single-feature distance metric model is proposed to measure the similarity of pulmonary nodules. And then, multiple single-feature distance metric models learned from different types of features are combined to a multi-feature distance metric model. Finally, the learned multi-feature distance metric is used to construct a content-based image retrieval (CBIR) scheme to assist the doctors in diagnosis of pulmonary nodules. The classification accuracy and retrieval accuracy are used to evaluate the performance of the scheme.The classification accuracy is 0.955 ±â€Š0.010, and the retrieval accuracies outperform the comparison methods.The proposed CBMFIR scheme is effective in diagnosis of pulmonary nodules. Our method can better integrate multiple types of features from pulmonary nodules.

Metabolomics and Lipidomics Profiling Reveals Hypocholesterolemic and Hypolipidemic Effects of Arabinoxylan on Type 2 Diabetic Rats.

Type 2 diabetes (T2D) is a pandemic disease chiefly characterized by hyperglycemia. In this study, the combination of serum lipidomic and metabolomic approach was employed to investigate the effect of arabinoxylan on type 2 diabetic rats and identify the critical biomarkers of T2D. Metabolomics analysis revealed that branched-chain amino acids, 12α-hydroxylated bile acids, ketone bodies, and several short- and long-chain acylcarnitines were significantly increased in T2D, whereas lysophosphatidylcholines (LPCs) were significantly decreased. Lipidomics analysis indicated T2D-related dyslipidemia was mainly associated with the increased levels of acetylcarnitine, free fatty acids (FFA), diacylglycerols, triacylglycerols, and cholesteryl esters and the decreased levels of some unsaturated phosphatidylcholines (less than 22 carbons). These variations indicated the disturbed amino acid and lipid metabolism in T2D, and the accumulation of incompletely oxidized lipid species might eventually contribute to impaired insulin action and glucose homeostasis. Arabinoxylan treatment decreased the concentrations of 12α-hydroxylated bile acids, carnitines, and FFAs and increased the levels of LPCs. The improved bile acid and lipid metabolism by arabinoxylan might be involved in the alleviation of hypercholesterolemia and hyperlipidemia in T2D.

Effectiveness of Aromatherapy Massage and Inhalation on Symptoms of Depression in Chinese Community-Dwelling Older Adults.

OBJECTIVES: Geriatric depression is a major public health problem in China. The study compared the intervention and follow-up effects of aromatherapy massage and inhalation on symptoms of depression in community-dwelling older adults after an 8-week intervention. DESIGN: A prospective, randomized controlled trial was conducted on community-dwelling adults ≥60 years old, with symptoms of depression. Participants were randomly assigned, by Latin Square, to aromatherapy massage, inhalation, or control groups (each n = 20). INTERVENTIONS: The aromatherapy massage group received 30 min of aromatherapy massage with 5 mL oil, twice weekly for 8 weeks. The oil contained 50 µL (one drop) of compound essential oils (lavender [Lavandula angustifolia], sweet orange [Citrus sinensis], and bergamot (Citrus bergamia in a 2:1:1 ratio)], diluted in sweet almond oil to a concentration of 1%. The aromatherapy inhalation group received 30 min of nasal inhalation of 50 µL of the compound essential oils blended in 10 mL of purified water, twice weekly for 8 weeks. The control group received no intervention. OUTCOME MEASURES: The Geriatric Depression Scale Short Form (GDS-SF) and Patient Health Questionnaire-9 (PHQ-9) were used for assessment at pretest, posttest, and 6- and 10-week follow-ups in all groups. 5-Hydroxytryptamine (5-HT) concentration was assessed pretest and posttest. RESULTS: Postintervention, the aromatherapy massage and inhalation groups demonstrated significantly lower GDS-SF and PHQ-9 scores than control participants. Compared with the pretest, the GDS-SF and PHQ-9 scores for depressive symptoms in both experimental groups remained lower at posttest (8 weeks), 6-week (14 weeks), and 10-week (18 weeks) follow-ups. However, the GDS-SF and PHQ-9 scores did not differ among the four time points in the control group. The posttest 5-HT concentrations in the aromatherapy massage and inhalation groups were increased over pretest values. CONCLUSIONS: Both aromatherapy massage and aromatherapy inhalation may have important implications for intervening depression in older adults.

Metabolism and health effects of phyto-estrogens.

Phyto-estrogens are plant-derived compounds that can exert various estrogenic and anti-estrogenic effects, and are usually used as a natural alternative to estrogen replacement due to their health benefits, including a lowered risk of osteoporosis, heart disease, breast cancer, and menopausal symptoms. Phyto-estrogens are also considered as endocrine disruptors due to their structure similar to human female hormone 17-ß oestradiol. However, the issue of whether phyto-estrogens are beneficial or harmful to human health remains unknown, as this may depend on the dose, form, level and duration of administration of phyto-estrogens, and influence by genetics, metabolism, gut physiology, age, diet, and the health status of individuals. Clarification on this issue is necessary for the sake of their two-side effects on human health and rapidly increasing global consumption of phyto-estrogens. This review mainly includes the metabolism of phyto-estrogens and weighs the evidence for and against the purported health benefits and adverse effects of phyto-estrogens.

A newly identified polysaccharide from Ganoderma atrum attenuates hyperglycemia and hyperlipidemia.

A polysaccharide from Ganoderma atrum (PSG-1) was purified and characterized, and its hypoglycemic and hypolipidemic effects were investigated in high fat diet- and streptozotocin-induced type 2 diabetic rats. Oral administration of PSG-1 at 200 or 400 mg/kg body weight significantly reduced fasting blood glucose and serum insulin levels. PSG-1 significantly decreased the levels of serum total cholesterol, triglyceride, low-density lipoprotein cholesterol, free fatty acid and insulin resistance, and increased high-density lipoprotein cholesterol level and insulin sensitivity. In addition, PSG-1 inhibited the expression of pro-apoptotic protein, Bax and increased the expression of anti-apoptotic protein, Bcl-2 in pancreatic cells, suggesting that PSG-1 exerted a protective role in the pancreas of diabetic rats. These results indicated that PSG-1 may have a potential for the treatment of hyperglycemia, hyperlipidemia, hyperinsulinemia and insulin resistance in type 2 diabetes.