Bioactive metabolite profiles and quality of Rosa rugosa during its growing and flower-drying process.

Rosa rugosa is extensively cultivated in China for its remarkable fragrance and flavor, however, the metabolic changes in roses during growth and drying remain unclear. Our results revealed significant variations in phenol and flavonoid contents and antioxidant capacity in roses (Rosa rugosa f. plena (Regel) Byhouwer) under different conditions. Phenol contents were positively correlated with antioxidant capacity, with phytochemicals being most prominent in unfolded petals. The highest antioxidant capacity and phenol and flavonoid contents were observed in April. Considering their greater consumption value, whole flowers were more suitable than petals alone. Furthermore, considerable sensory and nutritional differences were observed in dried roses. Different drying methods increased their total phenol content of roses by 4.2-5.4 times and the antioxidant capacity by 2.9 times. Metabolomics revealed the altered contents of flavonoids, anthocyanins, lipids, amino acids, and saccharides. This study provides baseline data for the potential of roses as a natural source of antioxidants in the food and pharmaceutical industries.

Increased Prostate-Specific Membrane Antigen Uptake in a Gallbladder Stone.

ABSTRACT: An Al 18F-prostate-specific membrane antigen (PSMA) Q PET/CT scan was performed in a 67-year-old man to identify any potential recurrent prostate cancer lesions, which revealed no recurrent or metastatic lesions. However, a large gallbladder stone with increased PSMA uptake was incidentally detected, which could be a potential pitfall in the interpretation of PSMA PET imaging.

An isothermal CRISPR- based lateral flow assay for detection of Neisseria meningitidis.

BACKGROUND: Neisseria meningitidis can cause life-threatening meningococcal meningitis and meningococcemia. Old standard microbiological results from CSF/blood cultures are time consuming. This study aimed to combine the sensitivity of loop-mediated isothermal nucleic acid amplification (LAMP) with the specificity of CRISPR/Cas12a cleavage to demonstrate a reliable diagnostic assay for rapid detection of N. meningitidis. METHODS: A total of n = 139 samples were collected from patients with suspected meningococcal disease and were used for evaluation. The extracted DNA was subjected to qualitative real-time PCR, targeting capsular transporter gene (ctrA) of N. meningitidis. LAMP-specific primer pairs, also targeting the ctrA, were designed and the LAMP products were subjected to CRISPR/Cas12 cleavage reaction. the readout was on a lateral flow strip. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of LAMP-CRISPR/Cas was compared with real-time PCR assays. The limit of detection (LOD) was established with serial dilutions of the target N. meningitidis DNA and calculated by Probit regression analysis. RESULTS: Six LAMP assay-specific primers were developed targeting the ctrA gene of N. meningitidis, which is conserved in all meningococcal serogroups. The LAMP primers did not amplify DNA from other bacterial DNA tested, showing 100% specificity. The use of 0.4 M betaine increased the sensitivity and stability of the reaction. LAMP-CRISPR/Cas detected meningococcal serogroups (B, C, W). The assay showed no cross-reactivity and was specific for N. meningitidis. The LOD was 74 (95% CI: 47-311) N. meningitidis copies. The LAMP-CRISPR/Cas performed well compared to the gold standard. In the 139 samples from suspected patients, the sensitivity and specificity of the test were 91% and 99% respectively. CONCLUSION: This developed and optimized method can complement for the available gold standard for the timely diagnosis of meningococcal meningitis and meningococcemia.

Supercritical CO2 fluid extract from Stellariae Radix ameliorates 2,4-dinitrochlorobenzene-induced atopic dermatitis by inhibit M1 macrophages polarization via AMPK activation.

Yin chai hu (Radix Stellariae) is a root medicine that is frequently used in Chinese traditional medicine to treat fever and malnutrition. In modern medicine, it has been discovered to have anti-inflammatory, anti-allergic, and anticancer properties. In a previous study, we were able to extract lipids from Stellariae Radix using supercritical CO2 extraction (SRE), and these sterol lipids accounted for up to 88.29% of the extract. However, the impact of SRE on the development of atopic dermatitis (AD) has not yet been investigated. This study investigates the inhibitory effects of SRE on AD development using a 2,4-dinitrochlorobenzene (DNCB)-induced AD mouse model. Treatment with SRE significantly reduced the dermatitis score and histopathological changes compared with the DNCB group. The study found that treatment with SRE resulted in a decrease of pro-inflammatory cytokines TNF-α, CXC-10, IL-12, and IL-1ß in skin lesions. Additionally, immunohistochemical analysis revealed that SRE effectively suppressed M1 macrophage infiltration into the AD lesion. Furthermore, the anti-inflammatory effect of SRE was evaluated in LPS + INF-γ induced bone marrow-derived macrophages (BMDMs) M1 polarization, SRE inhibited the production of TNF-α, CXC-10, IL-12, and IL-1ß and decreased the expression of NLRP3. Additionally, SRE was found to increase p-AMPKT172, but had no effect on total AMPK expression, after administration of the AMPK inhibitor Compound C, the inhibitory effect of SRE on M1 macrophages was partially reversed. The results indicate that SRE has an inhibitory effect on AD, making it a potential therapeutic agent for this atopic disorder.

Efficacy and safety of Ruxolitinib, Crisaborole, and Tapinarof for mild-to-moderate atopic dermatitis: a Bayesian network analysis of RCTs.

Given the lack of head-to-head studies of novel non-steroidal molecule topical therapies in mild-to-moderate atopic dermatitis (AD), network meta-analyses (NMAs) can provide comparative efficacy and safety data for clinical decision-making. In this NMA, we performed a literature search until 01 March 2023 for eligible studies written in English using databases, including PubMed, EMBASE, Cochrane Library, and ClinicalTrials.gov. Only double-blind randomized clinical trials (RCTs) with topical Ruxolitinib, Crisaborole, or Tapinarof versus vehicle for patients with mild-to-moderate AD were included. Baseline and follow-up data were extracted. Efficacy was evaluated using Investigator's Global Assessment (IGA) achieving "clear" or "almost clear," with 2 points or more improvement from baseline at the end of treatment, referred to as "IGA success." For binary outcomes, we analyzed in random-effects Bayesian NMA consistency models to compare the efficacy of these 3 topical therapies by odds ratio (OR) with 95% credibility interval (CrI). Overall, 10 phase 2 or phase 3 RCTs were identified, which included 4010 patients with mild to moderate AD. Compared with the topical vehicle control, all these 3 treatments had higher response rate of "IGA success" at the end of trial (Ruxolitinib 1.5% b.i.d: OR, 11.94; 95%CrI, 6.28-23.15; Crisaborole 2% b.i.d: OR, 2.08; 95%CrI, 1.46-3.52; Tapinarof 1% b.i.d: OR, 2.64; 95%CrI, 0.75-9.70). Notably, Ruxolitinib 1.5% b.i.d. had the highest probability of achieving "IGA success" in ranking analysis (Rank 1, SUCRA = 0.75) and lower risk of AE (Rank 8, SUCRA = 0.22). Besides, there was no difference in treatment-related adverse events between 3 therapies. Heterogeneity was not significant across studies.

On the Number of Linear Regions of Convolutional Neural Networks with Piecewise Linear Activations.

One fundamental problem in deep learning is understanding the excellent performance of deep Neural Networks (NNs) in practice. An explanation for the superiority of NNs is that they can realize a large family of complicated functions, i.e., they have powerful expressivity. The expressivity of a Neural Network with Piecewise Linear activations (PLNN) can be quantified by the maximal number of linear regions it can separate its input space into. In this paper, we provide several mathematical results needed for studying the linear regions of Convolutional Neural Networks with Piecewise Linear activations (PLCNNs), and use them to derive the maximal and average numbers of linear regions for one-layer PLCNNs. Furthermore, we obtain upper and lower bounds for the number of linear regions of multi-layer PLCNNs. Our results suggest that deeper PLCNNs have more powerful expressivity than shallow PLCNNs, while PLCNNs have more expressivity than fully-connected PLNNs per parameter, in terms of the number of linear regions.

Protein Multiple Conformation Prediction Using Multi-Objective Evolution Algorithm.

The breakthrough of AlphaFold2 and the publication of AlphaFold DB represent a significant advance in the field of predicting static protein structures. However, AlphaFold2 models tend to represent a single static structure, and multiple-conformation prediction remains a challenge. In this work, we proposed a method named MultiSFold, which uses a distance-based multi-objective evolutionary algorithm to predict multiple conformations. To begin, multiple energy landscapes are constructed using different competing constraints generated by deep learning. Subsequently, an iterative modal exploration and exploitation strategy is designed to sample conformations, incorporating multi-objective optimization, geometric optimization and structural similarity clustering. Finally, the final population is generated using a loop-specific sampling strategy to adjust the spatial orientations. MultiSFold was evaluated against state-of-the-art methods using a benchmark set containing 80 protein targets, each characterized by two representative conformational states. Based on the proposed metric, MultiSFold achieves a remarkable success ratio of 56.25% in predicting multiple conformations, while AlphaFold2 only achieves 10.00%, which may indicate that conformational sampling combined with knowledge gained through deep learning has the potential to generate conformations spanning the range between different conformational states. In addition, MultiSFold was tested on 244 human proteins with low structural accuracy in AlphaFold DB to test whether it could further improve the accuracy of static structures. The experimental results demonstrate the performance of MultiSFold, with a TM-score better than that of AlphaFold2 by 2.97% and RoseTTAFold by 7.72%. The online server is at http://zhanglab-bioinf.com/MultiSFold .

Markers of prolonged hospitalisation in severe dengue.

BACKGROUND: Dengue is one of the most common diseases in the tropics and subtropics. Whilst mortality is a rare event when adequate supportive care can be provided, a large number of patients get hospitalised with dengue every year that places a heavy burden on local health systems. A better understanding of the support required at the time of hospitalisation is therefore of critical importance for healthcare planning, especially when resources are limited during major outbreaks. METHODS: Here we performed a retrospective analysis of clinical data from over 1500 individuals hospitalised with dengue in Vietnam between 2017 and 2019. Using a broad panel of potential biomarkers, we sought to evaluate robust predictors of prolonged hospitalisation periods. RESULTS: Our analyses revealed a lead-time bias, whereby early admission to hospital correlates with longer hospital stays - irrespective of disease severity. Importantly, taking into account the symptom duration prior to hospitalisation significantly affects observed associations between hospitalisation length and previously reported risk markers of prolonged stays, which themselves showed marked inter-annual variations. Once corrected for symptom duration, age, temperature at admission and elevated neutrophil-to-lymphocyte ratio were found predictive of longer hospitalisation periods. CONCLUSION: This study demonstrates that the time since dengue symptom onset is one of the most significant predictors for the length of hospital stays, independent of the assigned severity score. Pre-hospital symptom durations need to be accounted for to evaluate clinically relevant biomarkers of dengue hospitalisation trajectories.

Exploration of Sweeping Effect: Droplet Coalescence Jumping of a Rolling and Static Droplet.

The sweeping effect of merged droplets plays a key role in enhancing application performance due to the continuing coalescence caused by the horizontal jumping velocity. Most studies focused on static droplet coalescence jumping, while moving droplet coalescence is poorly understood. In this work, we experimentally and numerically study the coalescence of a rolling droplet and a static one. When the droplet radius ratio is larger than 0.8, as the dimensionless initial velocity increases and the vertical jumping velocity first decreases and then increases. The critical dimensionless initial velocity Vc* corresponding to the minimum vertical jumping velocity could be estimated as 0.9(rs2rm2). When the droplet radius ratio is smaller than 0.8, the dimensionless initial velocity has a positive effect on the vertical jumping velocity. The mechanism of the vertical jumping velocity can be attributed to two parts: liquid bridge impact and retraction of the merged droplet. The squeezing effect generated by the initial velocity between the two droplets promotes the growth of the liquid bridge and enhances the impact effect of the liquid bridge but weakens the upward velocity accumulation caused by the retraction of the merged droplets. However, different from the vertical jumping velocity, the horizontal jumping velocity is approximately proportional to the dimensionless initial velocity. The outcome of our work elucidates a fundamental understanding of a rolling droplet coalescing with a static one.

The clinical characteristics and prognosis of patients with SAPHO syndrome--a real-world cohort study.

OBJECTIVES: We aimed to analyze the clinical characteristics and outcomes of patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. METHODS: The clinical records of 64 patients with SAPHO syndrome were collected, and the treatment and outcomes of 27 patients were followed up. The patients were divided into three groups according to the site of bone lesions: only anterior chest wall (ACW) involvement, only spinal involvement, and bone lesion involvement at both sites. The clinical characteristics and outcomes were compared. The clinical characteristics of the patients with and without peripheral joint involvement were compared. RESULTS: Among all patients, 31.25% (20/64) had only ACW involvement, 15.63% (10/64) had only spinal involvement, and 53.12% (34/64) had both ACW and spinal involvement. Peripheral joint involvement was observed in 25.00% (16/64) of the patients. Patients with only spinal involvement were older than those with only ACW involvement (p = 0.006). Patients with both ACW and spinal involvement were older than those with only ACW involvement (p = 0.002) and had a longer diagnosis delay (p = 0.015). Patients with peripheral joint involvement were younger than those without peripheral joint involvement (p = 0.028). During follow-up, 88.89% (24/27) of patients had good outcomes. Twenty-two patients were treated with non-steroidal anti-inflammatory drugs + Iguratimod (IGU), and the outcomes of 90.91% (20/22) improved. CONCLUSIONS: A relationship may exist between the sites of bone lesions and clinical characteristics of patients with SAPHO syndrome. The clinical outcomes of these patients may be good, and IGU may be effective in treating SAPHO syndrome. Key Points • This study is the first long-term follow-up on the effectiveness of iguratimod in treating patients with SAPHO. • This study revealed that patients with SAPHO and different bone lesion sites may present with different clinical characteristics.

Exploring the Effects of Liquid Marbles' Deformation on Their Rolling Resistance.

Liquid marbles (LMs) are nonwetting droplets manufactured by encapsulating droplets with micro- or nanoscale particles. These marbles are widely used as transport carriers for digital microfluidics due to their rapid displacement velocity and leak-free transport. An improved understanding of the resistance mechanism of rolling LMs is crucial for their transport and manipulation. In this study, we investigated the rolling resistance of LMs obtained with different powders and volumes using a high-speed camera. Our findings suggest that the deformation of liquid marbles would hinder their rolling by a resistance torque. To depict this resistance effect, we propose a theoretical model (f∼λ(ε-12Bo1/2ε2+14Boε3)), where f is the rolling resistance of marbles, λ is the deflection coefficient, Bo is the Bond number, and (ε is the contact surface deformation) that accurately predicts the relationship between deformation and rolling resistance, which is supported by our experimental results. To further validate our theoretical model, we conducted three independent experiments: shape detection of prepared LMs, measuring the elastic force of LMs, and detecting the diffusive motion of the encapsulating particles. Furthermore, we discuss three factors that affect the rolling resistance: the volume of the marbles, the type and size of the encapsulating particles, and the substrate roughness. This comprehensive study not only generalizes the mechanism of deformation hindering the rolling of liquid marbles but also provides a theoretical framework to predict the relationship between the deformation and rolling resistance. These findings have practical implications for improving the manipulation efficiency and advancing the use of LMs as microfluidic carriers.

Identification of Pla a 7 as a novel pollen allergen group in Platanus acerifolia pollen.

BACKGROUND: Platanus acerifolia is recognized as a source of allergenic pollen worldwide. Currently, five Platanus acerifolia pollen allergens belonging to different protein families have been identified, in which profilin and enolase were characterized by our group recently. Besides, we also screened and identified a novel allergen candidate as triosephosphate isomerase, which was different from already known types of pollen allergens. However, the role of this novel allergen group in Platanus acerifolia pollen allergy was unclear. Therefore, we further investigated the allergenicity and clarify its clinical relevance in this study. METHODS: The natural triosephosphate isomerase from Platanus acerifolia pollen was purified by three steps of chromatography and identified by mass spectrometry. The cDNA sequence of this protein was matched from in-house transcripts based on internal peptide sequences, which was further confirmed by PCR cloning. The recombinant triosephosphate isomerase was expressed and purified from E. coli. Allergenicity analysis of this protein was carried out by enzyme linked immunosorbent assay, immunoblot, and basophil activation test. RESULTS: A novel allergen group belonging to triosephosphate isomerase was firstly identified in Platanus acerifolia pollen and named as Pla a 7. The cDNA of Pla a 7 contained an open reading frame of 762 bp encoding 253 amino acids. The natural Pla a 7 displayed 41.4% IgE reactivity with the patients' sera by ELISA, in which the absorbance value showed correlation to the serum sIgE against Platanus acerifolia pollen extract. Inhibition of IgE-binding to pollen extracts reached 26%-94% in different Pla a 7-positive sera. The recombinant Pla a 7 exhibited weaker IgE-reactivity in ELISA than its natural form, but showed comparable activity in immunoblot. The allergenicity was further confirmed by basophil activation test. CONCLUSIONS: Triosephosphate isomerase (Pla a 7) was first recognized as pollen allergen in Platanus acerifolia pollen, which is a completely different type of pollen allergen from those previously reported. This finding is essential to enrich information on allergen components and pave the way for molecular diagnosis or treatment strategies for Platanus acerifolia pollen allergy.

Assessing protein model quality based on deep graph coupled networks using protein language model.

Model quality evaluation is a crucial part of protein structural biology. How to distinguish high-quality models from low-quality models, and to assess which high-quality models have relatively incorrect regions for improvement, are remain a challenge. More importantly, the quality assessment of multimer models is a hot topic for structure prediction. In this study, we propose GraphCPLMQA, a novel approach for evaluating residue-level model quality that combines graph coupled networks and embeddings from protein language models. The GraphCPLMQA consists of a graph encoding module and a transform-based convolutional decoding module. In encoding module, the underlying relational representations of sequence and high-dimensional geometry structure are extracted by protein language models with Evolutionary Scale Modeling. In decoding module, the mapping connection between structure and quality is inferred by the representations and low-dimensional features. Specifically, the triangular location and residue level contact order features are designed to enhance the association between the local structure and the overall topology. Experimental results demonstrate that GraphCPLMQA using single-sequence embedding achieves the best performance compared with the CASP15 residue-level interface evaluation methods among 9108 models in the local residue interface test set of CASP15 multimers. In CAMEO blind test (20 May 2022 to 13 August 2022), GraphCPLMQA ranked first compared with other servers (https://www.cameo3d.org/quality-estimation). GraphCPLMQA also outperforms state-of-the-art methods on 19, 035 models in CASP13 and CASP14 monomer test set.

High Hepatitis E Virus (HEV) Seroprevalence and No Evidence of HEV Viraemia in Vietnamese Blood Donors.

The prevalence of hepatitis E virus (HEV) in the Vietnamese population remains underestimated. The aim of the present study was to investigate the seroprevalence of HEV IgG/IgM antibodies and the presence of HEV RNA in blood donors as a part of epidemiological surveillance for transfusion-transmitted viruses. Serum samples from blood donors (n = 553) were analysed for markers of past (anti-HEV IgG) and recent/ongoing (anti-HEV IgM) HEV infections. In addition, all serum samples were subsequently tested for HEV RNA positivity. The overall prevalence of anti-HEV IgG was 26.8% (n = 148/553), while the seroprevalence of anti-HEV IgM was 0.5% (n = 3/553). Anti-HEV IgG seroprevalence in male and female donors was similar (27.1% and 25.5%, respectively). A higher risk of hepatitis E exposure was observed with increasing age. None of the blood donors were HEV RNA positive, and there was no evidence of HEV viraemia. Although the absence of HEV viraemia in blood donors from Northern Vietnam is encouraging, further epidemiological surveillance in other geographical regions is warranted to rule out transfusion-transmitted HEV.

Proteomic Identification and Characterization of Collagen from Bactrian Camel (Camelus bactrianus) Hoof.

With the development of camel-derived food and pharmaceutical cosmetics, camel hoof, as a unique by-product of the camel industry, has gradually attracted the attention of scientific researchers in the fields of nutrition, health care, and biomaterial development. In this study, the protein composition and collagen type of Bactrian camel hoof collagen extract (CHC) were analyzed by LC-MS/MS, and the functional properties of CHC were further investigated, including its rheological characteristics, emulsification and emulsion stability, and hygroscopicity and humectancy. Proteomic identification confirmed that CHC had 13 collagen subunits, dominated by type I collagen (α1, α2), with molecular weights mainly in the 100-200 KDa range and a pI of 7.48. An amino acid study of CHC revealed that it carried the standard amino acid profile of type I collagen and was abundant in Gly, Pro, Glu, Ala, and Arg. Additionally, studies using circular dichroism spectroscopy and Fourier transform infrared spectroscopy revealed that CHC contains a collagen-like triple helix structure that is stable and intact. Different concentrations of CHC solutions showed shear-thinning flow behavior. Its tan δ did not differ much with increasing concentration. The CHC has good emulsifying ability and stability, humectancy, and hygroscopicity. This study provides a basis for utilizing and developing Bactrian camel hoof collagen as a functional ingredient.

Combined Doxorubicin Mesoporous Carbon Nanospheres for Effective Tumor Lymphatic Metastasis by Multi-Modal Chemo-Photothermal Treatment in vivo.

Introduction: Sentinel lymph node (SLN) is the first regional lymph node where tumor cells metastasize, and its identification and treatment are of great significance for the prevention of tumor metastasis. However, the current clinical modalities for identification and treatment of SLN are still far from satisfactory owing to their high cost, invasiveness and low accuracy. We aim to design a novel nanomedicine system for SLN imaging and treatment with high efficacy. Methods: We designed and prepared hollow mesoporous carbon spheres (HMCS) and loaded with the chemotherapeutic drug doxorubicin (DOX), which is then modified with polyvinyl pyrrolidone (PVP) to obtain nanomedicine: HMCS-PVP-DOX. Results: HMCS-PVP with a size of about 150 nm could retain in the lymph nodes for a long time and stain the lymph nodes, which could be easily observed by the naked eye. At the same time, HMCS-PVP exhibited excellent photoacoustic and photothermal imaging capabilities, realizing multimodal imaging to locate lymph nodes precisely. Due to its high specific surface area, HMCS could be largely loaded with the chemotherapeutic drug doxorubicin (DOX). HMCS-PVP-DOX displayed highly efficient synergistic chemotherapy-photothermal therapy for lymphatic metastases in both cellular and animal experiments due to its significant photothermal effect under 1064 nm laser irradiation. HMCS-PVP-DOX also displayed great stability and biosafety. Discussion: Multifunctional nanomedicine HMCS-PVP-DOX is expected to provide a novel paradigm for designing nanomedicine to the diagnosis and treatment of lymphatic metastases because of its good stability and safety.

Scientific discovery in the age of artificial intelligence.

Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment and accelerate research, helping scientists to generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone. Here we examine breakthroughs over the past decade that include self-supervised learning, which allows models to be trained on vast amounts of unlabelled data, and geometric deep learning, which leverages knowledge about the structure of scientific data to enhance model accuracy and efficiency. Generative AI methods can create designs, such as small-molecule drugs and proteins, by analysing diverse data modalities, including images and sequences. We discuss how these methods can help scientists throughout the scientific process and the central issues that remain despite such advances. Both developers and users of AI toolsneed a better understanding of when such approaches need improvement, and challenges posed by poor data quality and stewardship remain. These issues cut across scientific disciplines and require developing foundational algorithmic approaches that can contribute to scientific understanding or acquire it autonomously, making them critical areas of focus for AI innovation.

Berberine suppressed sarcopenia insulin resistance through SIRT1-mediated mitophagy.

Abnormal mitochondrial function resulting in inadequate energy supply leads to sarcopenia and IR, suggesting that maintaining mitochondrial homeostasis by regulating mitophagy may be a promising strategy for sarcopenia IR therapy. Herein, we constructed sarcopenia mice model, which was treated with berberine and/or SIRT1/mitophagy inhibitors, and the activity of SIRT1/mitophagy signaling pathway was identified. Then, muscle tissue, blood biochemical index, inflammatory factors, GTT, and ITT were detected. We found that berberine treatment increased the body weight and alleviated d-galactose-induced weight loss in mice. SIRT1/mitophagy inhibitors suppressed the effects of berberine in the treatment of sarcopenia. The effect of berberine on the increase of muscle tissue, improving metabolic disorders, reducing the expression of inflammatory factors, and suppressing sarcopenia insulin resistance (IR) were reversed by SIRT1/mitophagy inhibitors. Our study establishes proof-of-concept to distinct the effect of berberine in sarcopenia IR, and provides strong evidence to support the hypothesis that berberine-induced SIRT1 triggers mitochondrial autophagy pathway and suppresses IR in sarcopenia.