Effect of grayscale threshold on X-ray computed tomography reconstruction of gas diffusion layers in polymer electrolyte membrane fuel cells.

In X-ray computed tomography (CT) reconstructions of gas diffusion layers (GDLs), grayscale threshold selection is a critical issue. Although various selection methods exist, they all have their own drawbacks. This study investigates the influence of grayscale threshold on GDL properties and compares Otsu and porosity-adaptive thresholds. We utilized X-ray CT to reconstruct a Toray carbon paper sample (TGP-H-060) at a resolution of 2 µm. Using reconstructed 3D models generated under different grayscale thresholds, we performed structural analysis, computational fluid dynamics simulation, and compression simulation. We subsequently calculated porosity, tortuosity, permeability, and macroscopic stress-strain relationships, quantitatively analyzing the sensitivity of these parameters to the change of grayscale threshold. The results indicated that small change in the grayscale threshold can significantly impact the transport and mechanical properties of reconstructed GDLs. The difference between Otsu and porosity-adaptive thresholds is notable, and the porosity-adaptive threshold appears to be less accurate than the Otsu threshold.

Synthesis and structure-activity optimization of azepane-containing derivatives as PTPN2/PTPN1 inhibitors.

Protein tyrosine phosphatases PTPN2 and PTPN1 (also known as PTP1B) have been implicated in a number of intracellular signaling pathways of immune cells. The inhibition of PTPN2 and PTPN1 has emerged as an attractive approach to sensitize T cell anti-tumor immunity. Two small molecule inhibitors have been entered the clinic. Here we report the design and development of compound 4, a novel small molecule PTPN2/N1 inhibitor demonstrating nanomolar inhibitory potency, good in vivo oral bioavailability, and robust in vivo antitumor efficacy.

Parathyroid Hormone is Negatively Correlated with Glycated Hemoglobin in Newly Diagnosed Type 2 Diabetic Patients.

Objective: The growing evidence shows that parathyroid hormone (PTH) may affect glucose metabolism. However, the relationship between them is still controversial among diabetic patients. The current study aimed to investigate the relationship between PTH and glucose metabolism in the patients with newly diagnosed type 2 diabetes (T2D). Methods: A total of 532 participants, including 387 patients with newly diagnosed T2D and 145 healthy controls, were recruited in the present study. PTH and metabolic parameters were measured in all participants. Results: The PTH levels were significantly lower in the newly diagnosed T2D patients compared with the control group (35.10 (25.90, 47.20) vs. 47.15 (35.83, 58.65) pg/ml, P < 0.001). The T2D patients with a higher glycated hemoglobin (HbA1c) tertile had lower PTH levels than the patients with a lower HbA1c tertile (32.90 (24.85, 41.40) vs. 37.50 (26.10, 54.55) pg/ml, P < 0.001). Spearman correlation analysis showed that PTH was positively correlated with the body mass index (BMI), fasting insulin (FINS), homeostasis model assessment of ß-cell function (HOMA-ß), and homeostasis model assessment of insulin resistance (HOMA-IR) and negatively correlated with HbA1c, blood calcium (Ca), blood phosphorus (P), and 25-hydroxyvitamin D3 (25-OH-D3). Multiple linear regression analysis demonstrated that PTH was significantly associated with HbA1c (ß = -1.475, P=0.003) and HOMA-ß (ß = 0.090, P=0.001) after adjusting for age, sex, BMI, season, 25-OH-D3, Ca, and P. Conclusion: PTH was negatively correlated with HbA1c in the newly diagnosed T2D patients. Our results suggested that the PTH level within the reference range is related to islet ß-cell function and hyperglycemia.

Discovery of novel MAT2A inhibitors by an allosteric site-compatible fragment growing approach.

The methionine adenosyltransferase MAT2A catalyzes the synthesis ofthe methyl donor S-adenosylmethionine (SAM) and thereby regulates critical aspects of metabolism and transcription. Aberrant MAT2A function can lead to metabolic and transcriptional reprogramming of cancer cells, and MAT2A has been shown to promote survival of MTAP-deficient tumors, a genetic alteration that occurs in âˆ¼ 13 % of all tumors. Thus, MAT2A holds great promise as a novel anticancer target. Here, we report a novel series of MAT2A inhibitors generated by a fragment growing approach from AZ-28, a low-molecular weight MAT2A inhibitor with promising pre-clinical properties. X-ray co-crystal structure revealed that compound 7 fully occupies the allosteric pocket of MAT2A as a single molecule mimicking MAT2B. By introducing additional backbone interactions and rigidifying the requisite linker extensions, we generated compound 8, which exhibited single digit nanomolar enzymatic and sub-micromolar cellular inhibitory potency for MAT2A.

Application of ensemble learning for predicting GABAA receptor agonists.

BACKGROUND: Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists. METHODS: 306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method. RESULTS: The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given. CONCLUSION: Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.

Study on Microstructure and High Temperature Stability of WTaVTiZrx Refractory High Entropy Alloy Prepared by Laser Cladding.

The extremely harsh environment of the high temperature plasma imposes strict requirements on the construction materials of the first wall in a fusion reactor. In this work, a refractory alloy system, WTaVTiZrx, with low activation and high entropy, was theoretically designed based on semi-empirical formula and produced using a laser cladding method. The effects of Zr proportions on the metallographic microstructure, phase composition, and alloy chemistry of a high-entropy alloy cladding layer were investigated using a metallographic microscope, XRD (X-ray diffraction), SEM (scanning electron microscope), and EDS (energy dispersive spectrometer), respectively. The high-entropy alloys have a single-phase BCC structure, and the cladding layers exhibit a typical dendritic microstructure feature. The evolution of microstructure and mechanical properties of the high-entropy alloys, with respect to annealing temperature, was studied to reveal the performance stability of the alloy at a high temperature. The microstructure of the annealed samples at 900 °C for 5-10 h did not show significant changes compared to the as-cast samples, and the microhardness increased to 988.52 HV, which was higher than that of the as-cast samples (725.08 HV). When annealed at 1100 °C for 5 h, the microstructure remained unchanged, and the microhardness increased. However, after annealing for 10 h, black substances appeared in the microstructure, and the microhardness decreased, but it was still higher than the matrix. When annealed at 1200 °C for 5-10 h, the microhardness did not increase significantly compared to the as-cast samples, and after annealing for 10 h, the microhardness was even lower than that of the as-cast samples. The phase of the high entropy alloy did not change significantly after high-temperature annealing, indicating good phase stability at high temperatures. After annealing for 10 h, the microhardness was lower than that of the as-cast samples. The phase of the high entropy alloy remained unchanged after high-temperature annealing, demonstrating good phase stability at high temperatures.

Discovery of Novel and Potent Prolyl Hydroxylase Domain-Containing Protein (PHD) Inhibitors for The Treatment of Anemia.

Stabilization of hypoxia-inducible factor (HIF) by inhibiting prolyl hydroxylase domain enzymes (PHDs) represents a breakthrough in treating anemia associated with chronic kidney disease. Here, we identified a novel scaffold for noncarboxylic PHD inhibitors by utilizing structure-based drug design (SBDD) and generative models. Iterative optimization of potency and solubility resulted in compound 15 which potently inhibits PHD thus stabilizing HIF-α in vitro. X-ray cocrystal structure confirmed the binding model was distinct from previously reported carboxylic acid PHD inhibitors by pushing away the R383 and Y303 residues resulting in a larger inner subpocket. Furthermore, compound 15 demonstrated a favorable in vitro/in vivo absorption, distribution, metabolism, and excretion (ADME) profile, low drug-drug interaction risk, and clean early safety profiling. Functionally, oral administration of compound 15 at 10 mg/kg every day (QD) mitigated anemia in a 5/6 nephrectomy rat disease model.

Urinary-derived extracellular vesicle microRNAs as non-invasive diagnostic biomarkers for early-stage renal cell carcinoma.

BACKGROUND AND AIMS: The potential of urinary-derived extracellular vesicle (uEV) microRNAs (miRNAs) as noninvasive molecular biomarkers for identifying early-stage renal cell carcinoma (RCC) patients is rarely explored. The present study aims to explore the possibility of uEV miRNAs as novel molecular biomarkers for distinguishing early-stage RCC. MATERIALS AND METHODS: uEVs were extracted by ExoQuick-TC™ kit and miRNA concentrations were measured by RT-qPCR. ROC curves and bioinformatics analysis were employed to predict the diagnostic efficacy and regulatory mechanisms of dysregulated miRNAs. RESULTS: Through a multiphase case-control study on uEV miRNAs screening, training, and validation in RCC cells (ACHN, Caki-1) and control cells (HK-2) and in uEVs of 125 RCC patients and 128 age- and sex-matched controls, we successfully identified four uEVs miRNAs (miR-135b-5p, miR-196b-5p, miR-200c-3p, and miR-203a-3p) were significantly and stably upregulated in RCC in vitro and in vivo. When adjusted with estimated glomerular filtration rate (eGFR), the AUC of the three-uEV miRNA panel (miR-135b-5p, miR-200c-3p, and miR-203a-3p) was 0.785 (95 % CI = 0.729-0.842, P < 0.0001) for discriminating RCC patients from controls. Notably, this panel exhibited similar performance in distinguishing early-stage (stage Ⅰ) RCC patients, with an AUC of 0.786 (95 %CI = 0.727-0.844, P < 0.0001). Bioinformatics analysis predicted that candidate miRNAs were involved in cancer progressing. CONCLUSION: Our study identified a four uEV miRNAs panel (miR-135b-5p, miR-196b-5p, miR-200c-3p, and miR-203a-3p) may serve as an auxiliary noninvasive indication of early-stage RCC.

Effect of dapagliflozin on proteomics and metabolomics of serum from patients with type 2 diabetes.

BACKGROUND: Sodium-glucose co-transporter 2 (SGLT2) inhibitors reduced the risk of cardiovascular and renal outcomes in patients with type 2 diabetes (T2D), but the underlying mechanism has not been well elucidated. The circulating levels of proteins and metabolites reflect the overall state of the human body. This study aimed to evaluate the effect of dapagliflozin on the proteome and metabolome in patients with newly diagnosed T2D. METHODS: A total of 57 newly diagnosed T2D patients were enrolled, and received 12 weeks of dapagliflozin treatment (10 mg/d, AstraZeneca). Serum proteome and metabolome were investigated at the baseline and after dapagliflozin treatment. RESULTS: Dapagliflozin significantly decreased HbA1c, BMI, and HOMA-IR in T2D patients (all p < 0.01). Multivariate models indicated clear separations of proteomics and metabolomics data between the baseline and after dapagliflozin treatment. A total of 38 differentially abundant proteins including 23 increased and 15 decreased proteins, and 35 differentially abundant metabolites including 17 increased and 18 decreased metabolites, were identified. In addition to influencing glucose metabolism (glycolysis/gluconeogenesis and pentose phosphate pathway), dapagliflozin significantly increased sex hormone-binding globulin, transferrin receptor protein 1, disintegrin, and metalloprotease-like decysin-1 and apolipoprotein A-IV levels, and decreased complement C3, fibronectin, afamin, attractin, xanthine, and uric acid levels. CONCLUSIONS: The circulating proteome and metabolome in newly diagnosed T2D patients were significantly changed after dapagliflozin treatment. These changes in proteins and metabolites might be associated with the beneficial effect of dapagliflozin on cardiovascular and renal outcomes.

Genome-wide identification and expression analysis of growth-regulating factors in Dendrobium officinale and Dendrobium chrysotoxum.

Background: Dendrobium, one of the largest genera in Orchidaceae, is popular not only for its aesthetic appeal but for its significant medicinal value. Growth-regulating factors (GRFs) play an essential role in plant growth and development. However, there is still a lack of information about the evolution and biological function analysis of the GRF gene family among Dendrobiumspecies. Methods: Growth-regulating factors from Dendrobium officinale Kimura et Migo and Dendrobium chrysotoxum Lindl. were identified by HMMER and BLAST. Detailed bioinformatics analysis was conducted to explore the evolution and function of GRF gene family in D. officinale and D. chrysotoxum using genomic data, transcriptome data and qRT-PCR technology. Results: Here, we evaluated the evolution of the GRF gene family based on the genome sequences of D. officinale and D. chrysotoxum. Inferred from phylogenetic trees, the GRF genes were classified into two clades, and each clade contains three subclades. Sequence comparison analysis revealed relatively conserved gene structures and motifs among members of the same subfamily, indicating a conserved evolution of GRF genes within Dendrobiumspecies. However, considering the distribution of orthologous DoGRFs and DcGRFs, and the differences in the number of GRFs among species, we suggest that the GRF gene family has undergone different evolutionary processes. A total of 361 cis-elements were detected, with 33, 141, and 187 related to plant growth and development, stress, and hormones, respectively. The tissue-specific expression of GRFs showed that DoGRF8 may have a significant function in the stem elongation of D. officinale. Moreover, four genes were up-regulated under Methyl-jasmonic acid/methyl jasmonate (MeJA) treatment, showing that DoGRFs and DcGRFs play a crucial role in stress response. These findings provide valuable information for further investigations into the evolution and function of GRF genes in D. officinale and D. chrysotoxum.

Mitochondrial genome comparison and phylogenetic analysis of Dendrobium (Orchidaceae) based on whole mitogenomes.

BACKGROUND: Mitochondrial genomes are essential for deciphering the unique evolutionary history of seed plants. However, the rules of their extreme variation in genomic size, multi-chromosomal structure, and foreign sequences remain unresolved in most plant lineages, which further hindered the application of mitogenomes in phylogenetic analyses. RESULTS: Here, we took Dendrobium (Orchidaceae) which shows the great divergence of morphology and difficulty in species taxonomy as the study focus. We first de novo assembled two complete mitogenomes of Dendrobium wilsonii and Dendrobium henanense that were 763,005 bp and 807,551 bp long with multichromosomal structures. To understand the evolution of Dendrobium mitogenomes, we compared them with those of four other orchid species. The results showed great variations of repetitive and chloroplast-derived sequences in Dendrobium mitogenomes. Moreover, the intergenic content of Dendrobium mitogenomes has undergone expansion during evolution. We also newly sequenced mitogenomes of 26 Dendrobium species and reconstructed phylogenetic relationships of Dendrobium based on genomic mitochondrial and plastid data. The results indicated that the existence of chloroplast-derived sequences made the mitochondrial phylogeny display partial characteristics of the plastid phylogeny. Additionally, the mitochondrial phylogeny provided new insights into the phylogenetic relationships of Dendrobium species. CONCLUSIONS: Our study revealed the evolution of Dendrobium mitogenomes and the potential of mitogenomes in deciphering phylogenetic relationships at low taxonomic levels.

Genome-Wide Identification and Analysis of TCP Gene Family among Three Dendrobium Species.

Dendrobium orchids, which are among the most well-known species of orchids, are appreciated for their aesthetic appeal across the globe. Furthermore, due to their strict living conditions, they have accumulated high levels of active ingredients, resulting not only in their medicinal value but also in their strong ability to respond to harsh environments. The TCP gene family plays an important role in plant growth and development, and signal transduction. However, these genes have not been systematically investigated in Dendrobium species. In this study, we detected a total of 24, 23, and 14 candidate TCP members in the genome sequences of D. officinale, D. nobile, and D. chrysotoxum, respectively. These genes were classified into three clades on the basis of a phylogenetic analysis. The TCP gene numbers among Dendrobium species were still highly variable due to the independent loss of genes in the CIN clade. However, only three gene duplication events were detected, with only one tandem duplication event (DcTCP9/DcTCP10) in D. chrysotoxum and two pairs of paralogous DoTCP gene duplication events (DoTCP1/DoTCP23 and DoTCP16/DoTCP24) in D. officinale. A total of 25 cis-acting elements of TCPs related to hormone/stress and light responses were detected. Among them, the proportions of hormone response, light response, and stress response elements in D. officinale (100/421, 127/421, and 171/421) were similar to those in D. nobile (83/352, 87/352, and 161/352). Using qRT-PCR to determine their expression patterns under MeJA treatment, four DoTCPs (DoTCP2, DoTCP4, DoTCP6, and DoTCP14) were significantly upregulated under MeJA treatment, which indicates that TCP genes may play important roles in responding to stress. Under ABA treatment, seven DoTCPs (DoTCP3, DoTCP7, DoTCP9, DoTCP11, DoTCP14, DoTCP15, and DoTCP21) were significantly upregulated, indicating that TCP genes may also play an important role in hormone response. Therefore, these results can provide useful information for studying the evolution and function of TCP genes in Dendrobium species.

Detecting local communities in complex network via the optimization of interaction relationship between node and community.

The goal of local community detection algorithms is to explore the optimal community with a reference to a given node. Such algorithms typically include two primary processes: seed selection and community expansion. This study develops and tests a novel local community detection algorithm called OIRLCD that is based on the optimization of interaction relationships between nodes and the community. First, we introduce an improved seed selection method to solve the seed deviation problem. Second, this study uses a series of similarity indices to measure the interaction relationship between nodes and community. Third, this study uses a series of algorithms based on different similarity indices, and designs experiments to reveal the role of the similarity index in algorithms based on relationship optimization. The proposed algorithm was compared with five existing local community algorithms in both real-world networks and artificial networks. Experimental results show that the optimization of interaction relationship algorithms based on node similarity can detect communities accurately and efficiently. In addition, a good similarity index can highlight the advantages of the proposed algorithm based on interaction optimization.

The serum concentration and activity of DPP4 is positively related with the severity of hyperthyroidism in patients with Graves' disease.

OBJECTIVE: Graves' disease (GD) is an organ-specific autoimmune disease. The production of anti-thyrotropin receptor antibodies (TRAb) is associated with a loss of immune tolerance. Dipeptidyl peptidase-4 (DPP-4) is expressed on multiple immune cells. This study aimed to investigate the relationship between serum concentration/activity of DPP4 and the severity of hyperthyroidism in GD patients. METHODS: A total of 82 newly diagnosed drug-naive patients with GD hyperthyroidism, 20 patients with non-autoimmune thyrotoxicosis and 122 age- and sex- matched healthy controls were enrolled. The clinical parameters and serum concentration and activity of DPP4 were measured. RESULTS: The GD group had increased serum concentration and activity of DPP4 than the healthy controls and patients with non-autoimmune thyrotoxicosis, while no significant difference was observed in the latter two groups. Multivariate linear regression indicated that the serum concentration/activity of DPP4 were positively associated with FT3, FT4 and TRAb levels in the GD patients. And the positive association between serum concentration/activity of DPP4 and TRAb was remained even after adjustment for confounding factors (all p < 0.05). CONCLUSIONS: The GD patients had significantly increased serum concentration/activity of DPP4. And the serum concentration/activity of DPP4 was positively associated with the severity of hyperthyroidism in GD patients.Key messagesThe activity and concentration of DPP4 in patients with Graves' disease were higher than those in healthy controls.There was a significant positive correlation between serum DPP4 concentration and TRAb levels in patients with Graves' disease.In patients with Graves 'disease, serum DPP4 activity was positively correlated with TRAb levels.

Hepatic glucuronyl C5-epimerase combats obesity by stabilising GDF15.

BACKGROUND & AIMS: Disturbed hepatic metabolism frequently results in excessive lipid accumulation in the adipose tissue. However, the specific role of the liver-adipose axis in maintaining lipid homeostasis, as well as the underlying mechanism, has not yet been fully elucidated. In this study, we investigated the role of hepatic glucuronyl C5-epimerase (Glce) in the progression of obesity. METHODS: We determined the association between the expression of hepatic Glce and body mass index (BMI) in obese patients. Obesity models were established in hepatic Glce-knockout and wild-type mice fed a high-fat diet (HFD) to understand the effect of Glce on obesity development. The role of Glce in the progression of disrupted hepatokine secretion was examined via secretome analysis. RESULTS: Hepatic Glce expression was inversely correlated with BMI in obese patients. Moreover, Glce level was found to be decreased in the liver of a HFD murine model. Hepatic Glce deficiency led to impaired thermogenesis in adipose tissue and exacerbated HFD-induced obesity. Interestingly, decreased level of growth differentiation factor 15 (GDF15) was observed in the culture medium of Glce-knockout mouse hepatocytes. Treatment with recombinant GDF15 obstructed obesity progression derived from the absence of hepatic Glce, similar to the effect of Glce or its inactive mutant overexpressed both in vitro and in vivo. Furthermore, liver Glce deficiency led to diminished production and increased degradation of mature GDF15, resulting in reduced hepatic GDF15 secretion. CONCLUSIONS: Hepatic Glce deficiency facilitated obesity development, and decreased Glce expression further reduced hepatic secretion of GDF15, thereby perturbing lipid homeostasis in vivo. Therefore, the novel Glce-GDF15 axis plays an important role in maintaining energy balance and may act as a potential target for combating obesity. IMPACT AND IMPLICATIONS: Evidence suggests that GDF15 plays a key role in hepatic metabolism; however, the molecular mechanism for regulating its expression and secretion is largely unknown. Our work observes that hepatic Glce, as a key Golgi-localised epimerase, may work on the maturation and post-translational regulation of GDF15. Hepatic Glce deficiency reduces the production of mature GDF15 protein and facilitates its ubiquitination, resulting in the aggravation of obesity development. This study sheds light on the new function and mechanism of the Glce-GDF15 axis in lipid metabolism and provides a potential therapeutic target against obesity.

The climate changes promoted the chloroplast genomic evolution of Dendrobium orchids among multiple photosynthetic pathways.

Dendrobium orchids have multiple photosynthetic pathways, which can be used as a model system for studying the evolution of crassulacean acid metabolism (CAM). In this study, based on the results of the net photosynthetic rates (Pn), we classified Dendrobium species into three photosynthetic pathways, then employed and compared their chloroplast genomes. The Dendrobium chloroplast genomes have typical quartile structures, ranging from 150,841-153,038 bp. The apparent differences in GC content, sequence variability, and IR junctions of SSC/IRB junctions (JSBs) were measured within chloroplast genomes among different photosynthetic pathways. The phylogenetic analysis has revealed multiple independent CAM origins among the selected Dendrobium species. After counting insertions and deletions (InDels), we found that the occurrence rates and distribution densities among different photosynthetic pathways were inconsistent. Moreover, the evolution patterns of chloroplast genes in Dendrobium among three photosynthetic pathways were also diversified. Considering the diversified genome structure variations and the evolution patterns of protein-coding genes among Dendrobium species, we proposed that the evolution of the chloroplast genomes was disproportional among different photosynthetic pathways. Furthermore, climatic correlation revealed that temperature and precipitation have influenced the distribution among different photosynthetic pathways and promoted the foundation of CAM pathway in Dendrobium orchids. Based on our study, we provided not only new insights into the CAM evolution of Dendrobium but also provided beneficial genetic data resources for the further systematical study of Dendrobium.

Longitudinal changes in serum adropin levels and liver fat content during liraglutide treatment in newly diagnosed patients with type 2 diabetes mellitus and metabolic dysfunction-associated fatty liver disease.

AIMS: To explore the effect of liraglutide treatment on serum adropin and its relationship to the liver fat content in newly diagnosed patients with type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated fatty liver disease (MAFLD). METHODS: Serum adropin level and liver fat content were assessed in patients with T2DM and MAFLD (n = 22), along with healthy controls (n = 22). Afterward, the patients received liraglutide treatment for 12 weeks. Serum adropin levels were examined by a competitive enzyme-linked immunosorbent assay. Liver fat content was quantified via magnetic resonance imaging-estimated proton density fat fraction (MRI-PDFF). RESULTS: We found that patients with newly diagnosed T2DM and MAFLD had lower serum adropin levels [2.79 ± 0.47 vs. 3.27 ± 0.79 ng/mL, P < 0.05] and higher liver fat content [19.12 ± 9.46 vs. 4.67 ± 0.61%, P < 0.001], compared to healthy controls. Following 12-week liraglutide treatment, serum adropin levels increased from 2.83(2.44, 3.24) to 3.65(3.20, 3.85) ng/mL (P < 0.001), and liver fat content decreased from 18.04(11.08, 27.65) to 7.74(6.42, 13.49) % (P < 0.001) in patients with T2DM and MAFLD. Furthermore, increases in serum adropin were strongly associated with decreases in liver fat content (ß = - 5.933, P < 0.001), liver enzyme and glucolipid metabolism parameters. CONCLUSION: The increase in serum adropin level following liraglutide treatment was strongly correlated with the reduction in liver fat content and glucolipid metabolism. Hence, adropin might be a potential marker for the beneficial effects of liraglutide on treating T2DM and MAFLD.

Carbon-Based Nanomaterials as Drug Delivery Agents for Colorectal Cancer: Clinical Preface to Colorectal Cancer Citing Their Markers and Existing Theranostic Approaches.

Colorectal cancer (CRC) is one of the universally established cancers with a higher incidence rate. Novel progression toward cancer prevention and cancer care among countries in transition should be considered seriously for controlling CRC. Hence, several cutting edge technologies are ongoing for high performance cancer therapeutics over the past few decades. Several drug-delivery systems of the nanoregime are relatively new in this arena compared to the previous treatment modes such as chemo- or radiotherapy to mitigate cancer. Based on this background, the epidemiology, pathophysiology, clinical presentation, treatment possibilities, and theragnostic markers for CRC were revealed. Since the use of carbon nanotubes (CNTs) for the management of CRC has been less studied, the present review analyzes the preclinical studies on the application of carbon nanotubes for drug delivery and CRC therapy owing to their inherent properties. It also investigates the toxicity of CNTs on normal cells for safety testing and the clinical use of carbon nanoparticles (CNPs) for tumor localization. To conclude, this review recommends the clinical application of carbon-based nanomaterials further for the management of CRC in diagnosis and as carriers or therapeutic adjuvants.

Celastrol suppresses colorectal cancer via covalent targeting peroxiredoxin 1.

As a terpenoids natural product isolated from the plant Thunder God Vine, Celastrol is widely studied for its pharmacological activities, including anti-tumor activities. The clinical application of Celastrol is strictly limited due to its severe side effects, whereas previously revealed targets and mechanism of Celastrol seldom reduce its in vivo toxicity via structural optimization. Target identification has a far-reaching influence on the development of innovative drugs, and omics data has been widely used for unbiased target prediction. However, it is difficult to enrich target of specific phenotype from thousands of genes or proteins, especially for natural products with broad promising activities. Here, we developed a text-mining-based web-server tool to enrich targets from omics data of inquired compounds. Then peroxiredoxin 1 (PRDX1) was identified as the ROS-manipulating target protein of Celastrol in colorectal cancer. Our solved high-resolution crystal structure revealed the unique covalent binding mode of Celastrol with PRDX1. New derivative compound 19-048 with improved potency against PRDX1 and selectivity towards PRDX2~PRDX6 were synthesized based on crystal structure analysis. Both Celastrol and 19-048 effectively suppressed the proliferation of colorectal cancer cells. The anti-tumor efficacy of Celastrol and 19-048 was significantly diminished on xenograft nude mice bearing PRDX1 knock-down colorectal cancer cells. Several downstream genes of p53 signaling pathway were dramatically up-regulated with Celastrol or 19-048 treatment. Our findings reveal that the side effects of Celastrol could be reduced via structural modification, and PRDX1 inhibition is promising for the treatment of colorectal cancer.

Association between Intrapancreatic Fat Deposition and Lower High-Density Lipoprotein Cholesterol in Individuals with Newly Diagnosed T2DM.

Background: Intrapancreatic fat deposition (IPFD) usually occurs in individuals with type 2 diabetes mellitus (T2DM), but its physiopathological influence remains controversial. The present study aimed to investigate IPFD and its associations with various aspects of glucose and lipid metabolism in individuals with newly diagnosed T2DM. Methods: A total of 100 individuals were included, consisting of 80 patients with newly diagnosed T2DM and 20 age- and sex-matched healthy controls. Then, we assessed IPFD using magnetic resonance imaging (MRI) and various parameters of glucose and lipid metabolism. Results: Individuals with newly diagnosed T2DM had a significantly higher IPFD (median: 12.34%; IQR, 9.19-16.60%) compared with healthy controls (median: 6.35%; IQR, 5.12-8.96%) (p < 0.001). In individuals with newly diagnosed T2DM, IPFD was significantly associated with FINS and HOMA-IR in unadjusted model (ß = 0.239, p=0.022; ß = 0.578, p=0.007, respectively) and adjusted model for age and sex (ß = 0.241, p=0.022; ß = 0.535, p=0.014, respectively), but these associations vanished after adjustment for age, sex, and BMI. The OR of lower HDL-C for the prevalence of high IPFD was 4.22 (95% CI, 1.41 to 12.69; p=0.010) after adjustment for age, sex, BMI, and HbA1c. Conclusions: Lower HDL-C was an independent predictor for a high degree of IPFD.