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Obesity is associated with biological dysfunction in skeletal muscle. As a condition of obesity accompanied by muscle mass loss and physical dysfunction, sarcopenic obesity (SO) has become a novel public health problem. Human fibroblast growth factor 19 (FGF19) plays a therapeutic role in metabolic diseases. However, the protective effects of FGF19 on skeletal muscle in obesity and SO are still not completely understood. Our results showed that FGF19 administration improved muscle loss and grip strength in young and aged mice fed a high‐fat diet (HFD). Increases in muscle atrophy markers (FOXO‐3, Atrogin‐1, MuRF‐1) were abrogated by FGF19 in palmitic acid (PA)‐treated C2C12 myotubes and in the skeletal muscle of HFD‐fed mice. FGF19 not only reduced HFD‐induced body weight gain, excessive lipid accumulation and hyperlipidaemia but also promoted energy expenditure (PGC‐1α, UCP‐1, PPAR‐γ) in brown adipose tissue (BAT). FGF19 treatment restored PA‐ and HFD‐induced hyperglycaemia, impaired glucose tolerance and insulin resistance (IRS‐1, GLUT‐4) and mitigated the PA‐ and HFD‐induced decrease in FNDC‐5/irisin expression. However, these beneficial effects of FGF19 on skeletal muscle were abolished by inhibiting AMPK, SIRT‐1 and PGC‐1α expression. Taken together, this study suggests that FGF19 protects skeletal muscle against obesity‐induced muscle atrophy, metabolic derangement and abnormal irisin secretion partially through the AMPK/SIRT‐1/PGC‐α signalling pathway, which might be a potential therapeutic target for obesity and SO.

Solasonine, a steroidal glycoalkaloid isolated from the herbal plant Solanum nigrum Linn., has shown active against multiple human cancers; however, there is little knowledge on the activity of solasonine against gastric cancer until now. This study aimed to examine the effect of solasonine on the biological behaviours of human gastric cancer SGC‐7901 cells. The results showed that solasonine suppressed SGC‐7901 cell proliferation in a dose‐dependent manner. Solasonine treatment mainly induced the cell cycle arrest at G2 phase in SGC‐7901 cells. Treatment with solasonine resulted in significant down‐regulation of Bcl‐2 and Caspase‐3 protein expression and reduced Bax and Bcl‐xL protein expression in SGC‐7901 cells. Solasonine shows a comparable inhibitory effect on the proliferation of human gastric cancer SGC‐7901 cells with cisplatin, and solasonine induces of SGC‐7901 cell apoptosis through triggering the endoplasmic reticulum stress pathway and the mitochondrial pathway. Our data indicate that solasonine may be a promising agent for the treatment of gastric cancer.

Graphitic electrode is commonly used in electrochemical reactions owing to its excellent in-plane conductivity, structural robustness and cost efficiency 1 , 2 . It serves as prime electrocatalyst support as well as a layered intercalation matrix 2 , 3 , with wide applications in energy conversion and storage 1 , 4 . Being the two-dimensional building block of graphite, graphene shares similar chemical properties with graphite 1 , 2 , and its unique physical and chemical properties offer more varieties and tunability for developing state-of-the-art graphitic devices 5 – 7 . Hence it serves as an ideal platform to investigate the microscopic structure and reaction kinetics at the graphitic-electrode interfaces. Unfortunately, graphene is susceptible to various extrinsic factors, such as substrate effect 8 – 10 , causing much confusion and controversy 7 , 8 , 10 , 11 . Hereby we have obtained centimetre-sized substrate-free monolayer graphene suspended on aqueous electrolyte surface with gate tunability. Using sum-frequency spectroscopy, here we show the structural evolution versus the gate voltage at the graphene–water interface. The hydrogen-bond network of water in the Stern layer is barely changed within the water-electrolysis window but undergoes notable change when switching on the electrochemical reactions. The dangling O–H bond protruding at the graphene–water interface disappears at the onset of the hydrogen evolution reaction, signifying a marked structural change on the topmost layer owing to excess intermediate species next to the electrode. The large-size suspended pristine graphene offers a new platform to unravel the microscopic processes at the graphitic-electrode interfaces. Using centimetre-sized substrate-free monolayer graphene suspended on aqueous electrolyte surface, the structural evolution versus gate voltage at the graphene–water interface is shown, demonstrating minimal influence of extrinsic factors.

To determine the living regions of individuals based on amino acids in fingermark residues and to establish a rapid and accurate regional classification method using machine learning. Methods: A total of 71 fingermark donors from six different provinces in various regions of China were selected. The content of 18 amino acids in their fingermarks was detected using UHPLC-QQQ-MS/MS. Classification models were established using various machine learning algorithms, and the cross-validation accuracy of 72 combinations, including feature engineering, classification algorithms, and optimization algorithms, was compared. Results: UHPLC-QQQ-MS/MS successfully quantified 16 amino acids. Significant differences in the relative content of amino acids were found between the fingermarks from the eastern and western regions of China, as well as among neighboring provinces. The combination of SFS+SVM+BO was identified as the optimal classification model, achieving an accuracy of 90.14 %. Conclusion: The study found regional differences in the relative content of amino acids in fingermarks and established a regional classification method combining UHPLC-QQQ-MS/MS and machine learning. The method developed in this study can be applied to incomplete or distorted fingermarks, and the experimental results can be directly used in police investigations. This research uncovers the multidimensional information carried by fingerprint substances, demonstrating innovation and application value. It not only saves and shortens investigation time and provides investigative leads, but also enables previously unusable physical evidence to play a role again, enhancing the profiling of suspects. •Established a fingermark amino acid testing method using UHPLC-QQQ-MS/MS.•Relative amino acid contents in fingermarks show significant differences across populations from six provinces.•Compared 72 algorithm combinations, with SFS+SVM+BO achieving a classification accuracy of 90.14 %.

Associations between gut microbiota and colorectal cancer (CRC) have been widely investigated. However, the replicable markers for early-stage adenoma diagnosis across multiple populations remain elusive. Here, we perform an integrated analysis on 1056 public fecal samples, to identify adenoma-associated microbial markers for early detection of CRC. After adjusting for potential confounders, Random Forest classifiers are constructed with 11 markers to discriminate adenoma from control (area under the ROC curve (AUC) = 0.80), and 26 markers to discriminate adenoma from CRC (AUC = 0.89), respectively. Moreover, we validate the classifiers in two independent cohorts achieving AUCs of 0.78 and 0.84, respectively. Functional analysis reveals that the altered microbiome is characterized with increased ADP- l -glycero-beta- d -manno-heptose biosynthesis in adenoma and elevated menaquinone-10 biosynthesis in CRC. These findings are validated in a newly-collected cohort of 43 samples using quantitative real-time PCR. This work proves the validity of adenoma-specific markers across multi-populations, which would contribute to the early diagnosis and treatment of CRC. The gut microbiome plays an important role in colorectal carcinogenesis and predictive microbiome signatures have been proposed for colorectal cancer (CRC) diagnosis. Here the authors perform a meta-analysis of 16S rRNA-based profiles to identify microbial markers able to discriminate patients with adenoma from control and CRC, building a model that can be applied for the early detection of CRC.

In the V2X environment, intelligent connected vehicles can obtain multi-dimensional traffic flow data in real time through the vehicle–road collaborative cyber–physical fusion system. Based on this, this study proposes a multi-lane traffic flow lattice model integrating optimal traffic flow difference estimation information to effectively suppress traffic congestion. The linear stability criterion of the system is derived through linear stability analysis, proving that the optimal traffic flow difference estimation can significantly expand the stable region and suppress traffic fluctuations caused by small disturbances. Furthermore, the perturbation method is used to derive the mKdV equation near the critical stability point of the system, revealing the nonlinear characteristics of traffic congestion propagating in the form of kink solitary waves, and indicating that the new consideration effect can effectively slow down the congestion propagation speed by adjusting the parameters of solitary waves (such as wave speed and amplitude). The numerical simulation results show that compared to the traditional model, the improved model exhibits enhanced traffic flow stability and robustness. Meanwhile, it reveals the nonlinear relationship between the increase of the number of lanes and the alleviation of congestion, and there is an optimal lane configuration threshold. The research results not only provide theoretical support for the optimization of traffic flow efficiency in intelligent transportation systems, but also provide a decision-making basis for dynamic lane management strategies in the V2X environment.

The traffic flow difference factor is of great significance for traffic flow stability and congestion mitigation. However, its role has not been studied in existing curved-road traffic flow models. To fill this gap, this study proposes an improved lattice traffic flow model for curved roads based on lattice hydrodynamic theory, which comprehensively considers the synergistic influence of curve geometric characteristics and the flow difference factor on traffic dynamics. Meanwhile, the new model adopts a modified optimal speed function regarding the symmetric characteristics of density. Through linear stability analysis, the stability criterion of the new model is derived. Via nonlinear analysis, the mKdV equation describing the propagation mechanism of traffic congestion near the critical point, along with its density wave solution, is obtained. The results show that introducing the traffic flow difference factor can significantly suppress the propagation speed and fluctuation amplitude of density waves and reduce the driver’s critical sensitivity coefficient, thereby effectively enhancing the stability and robustness of traffic flow on curved roads. Moreover, the model’s stability gradually improves as the curve curvature increases. Under the same curve conditions, compared with the classical Zhou model, the critical sensitivity and density wave propagation speed of the new model are reduced by approximately 16.67% and 19.48%, respectively, with favorable traffic congestion suppression effects.

Osteoarthritis (OA) is the most common chronic joint disease worldwide. Chondrocyte, as the only resident cell type in cartilage, its apoptosis is of pathogenetic significance in OA. Mesenchymal stem cell (MSC)-based-therapy has been proved effective in OA in animals and clinical studies. Nowadays, the regenerative potential of MSC-based therapy is mostly attributed to its paracrine secretion, in which exosomes may play an important role. In the present study, we aimed to find out the significance of MSC-derived exosomes (MSC-Exos) on the viability of chondrocytes under normal and inflammatory conditions. Bone marrow MSCs (BMSCs) and chondrocytes from rabbits were cultured in vitro. BMSC-Exos were isolated by an ultracentrifugation method. Transmission electron microscopy and Western blot were used to identify exosomes. The internalization of BMSC-Exos into chondrocytes was observed by fluorescent microscope. The viability and apoptosis of chondrocytes induced by IL-1β were tested through MTT method, Hoechst33324 dying, and mitochondrial damage measurement. Phosphorylation of p38, ERK, and Akt were evaluated by Western blot. The results showed that BMSC-Exos were round-shaped. Co-culturing BMSC-Exos with chondrocytes could observe the uptake of BMSC-Exos by chondrocytes. The viability decreased, apoptosis occurred, and the mitochondrial membrane potential of chondrocytes changed a lot when IL-1β were given, but all the changes were almost abolished when BMSC-Exos was added. Furthermore, the phosphorylation of p38 and ERK were inhibited, and phosphorylation of Akt was promoted by BMSC-Exos compared with IL-1β group. The present study demonstrated that BMSC-Exos inhibited mitochondrial-induced apoptosis in response to IL-1β, and p38, ERK, and Akt pathways were involved. BMSC-Exo might represent a novel cell-free therapeutic approach for the treatment of OA.

Background Subtribe Orchidinae (Orchidaceae, Orchidoideae) are a nearly cosmopolitan taxon of terrestrial orchids, comprising about 1800 species in 47 to 60 genera. Although much progress has been made in recent years of phylogenetics of Orchidinae, considerable problems remain to be addressed. Based on molecular phylogenetics, we attempt to illustrate the phylogenetic relationships and discuss generic delimitation within Orchidinae. Seven DNA markers (five plastid and two nuclear), a broad sampling of Orchidinae (400 species in 52 genera) and three methods of phylogenetic analysis (maximum likelihood, maximum parsimony and Bayesian inference) were used. Results Orchidinae s.l. are monophyletic. Satyrium is sister to the rest of Orchidinae s.l. Brachycorythis and Schizochilus are successive sister to Asian-European Orchidinae s.s. Sirindhornia and Shizhenia are successive sister to clade formed by Tsaiorchis - Hemipilia - Ponerorchis alliance. Stenoglottis is sister to the Habenaria-Herminium-Peristylus alliance. Habenaria , currently the largest genus in Orchidinae, is polyphyletic and split into two distant clades: one Asian-Australian and the other African–American–Asian. Diplomeris is sister to Herminium s.l. plus Asian-Australian Habenaria . Conclusions We propose to recognize five genera in the Ponerorchis alliance: Hemipilia , Ponerorchis s.l., Sirindhornia , Shizhenia and Tsaiorchis . Splitting Habenaria into two genera based on morphological characters and geographical distribution may be the least disruptive approach, and it is reasonable to keep Satyrium in Orchidinae.