Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

A liquid chromatography-tandem mass spectrometry(LC-MS/MS)method was developed for determination of three kinds of β-agonists(Clenbuterol(CL),Ractopamine(RAC)and Salbutamol(SAL))residues in animal liver samples.The liver sample homogenates were extracted with organic solvent,followed by clean-up using the automatic magnetic solid-phase extraction(MSPE),and then analyzed using LC-MS/MS.The results showed that the magnetic mixed-mode cation exchange adsorbent(M-MCX)exhibited 34%higher adsorption capacity than the conventional mixed-mode cation exchange(MCX)column.Furthermore,the clean-up was conducted by using an automatic MSPE device,and 8 samples could be simultaneously treated within 30 min.The limits of detection(LOD)were 0.01-0.1 μg/kg,the average recoveries ranged from 88.2%to 110.5%,and the relative standard deviations(RSDs)were in range of 2.9%-10.3%at three spiked levels for the three kinds of β-agonists.Compared with the traditional SPE technique,the present method had many advantages such as simple operation,rapidity and high efficiency,which was suitable for high-throughput and automatic detection of residues in routine analysis.

Objective Recombinase-aided polymerase chain reaction(RAP)is a sensitive,single-tube,two-stage nucleic acid amplification method.This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus(SA),Pseudomonas aeruginosa(PA),and Acinetobacter baumannii(AB)in the bloodstream based on recombinant human mannan-binding lectin protein(M1 protein)-conjugated magnetic bead(M1 bead)enrichment of pathogens combined with RAP. Methods Recombinant plasmids were used to evaluate the assay sensitivity.Common blood influenza bacteria were used for the specific detection.Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR(M-RAP)and quantitative PCR(qPCR)assays.Kappa analysis was used to evaluate the consistency between the two assays. Results The M-RAP method had sensitivity rates of 1,10,and 1 copies/μL for the detection of SA,PA,and AB plasmids,respectively,without cross-reaction to other bacterial species.The M-RAP assay obtained results for<10 CFU/mL pathogens in the blood within 4 h,with higher sensitivity than qPCR.M-RAP and qPCR for SA,PA,and AB yielded Kappa values of 0.839,0.815,and 0.856,respectively(P<0.05). Conclusion An M-RAP assay for SA,PA,and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Objective:The purpose of this study was to examine the clinical features and initial treatment outcomes of elderly individuals with idiopathic membranous nephropathy.Methods:This study retrospectively analyzed the clinical characteristics and therapeutic effect of hospitalized patients aged 60 years or older with renal-biopsy-proven idiopathic membranous nephropathy for at least one year.Results:This study enrolled a total of 91 elderly patients with IMN, consisting of 51 males(56.0%)and 40 females(44.0%). The median age of the patients was 67 years.The urinary protein creatinine ratio(uPCR)and urinary albumin creatinine ratio(uACR)of the patients were 4 454.3 mg/g and 2 258.5 mg/g, respectively.The median 24-hour urinary protein and urinary albumin levels were 5 098.2 mg/24 h and 2 800.6 mg/24 h, respectively.The average estimated glomerular filtration rate(eGFR)was(60.5±20.4)ml·min -1·1.73 m -2.Out of the total of 61 patients, 67.0% achieved remission, including complete and partial remission, within a year of renal biopsy.The levels of uPCR and uACR were significantly higher in the non-remission group compared to the remission group(5 462.5 vs.2 271.1 mg/g, P<0.001; 2 774.4 vs.1 320.0 mg/g, P=0.001). Additionally, the levels of 24h urinary protein and urinary albumin were significantly higher in the non-remission group compared to the remission group(6 526.4 vs.3 210.4 mg/g, P=0.002; 3 067.7 vs.2 102.4 mg/g, P=0.007). The remission group had a higher proportion of patients receiving immunosuppressive therapy(85.2% vs.33.3%, P<0.001). The remission rates were higher in patients treated with glucocorticoid combined with cyclophosphamide, glucocorticoid combined with calcineurin inhibitors, or glucocorticoid combined with mycophenolate mofetil compared to those receiving conservative treatment(88.2% vs.31.0%, P=0.001; 80.0% vs.31.0%, P<0.001; 100.0% vs.31.0%, P=0.007). There was no significant difference in remission rate between the three immunosuppressive therapy groups( P>0.05). However, upon further analysis, it was found that the levels of uPCR, uACR, and serum cystatin C(CysC)were higher in the immunosuppressive therapy groups compared to conservative treatment.Additionally, serum total protein and albumin were lower in the immunosuppressive therapy groups, and these differences were statistically significant( P<0.05). Conclusions:The majority of elderly patients diagnosed with IMN have multiple comorbidities.For those at high risk with elevated urinary protein levels, early initiation of immunosuppressive therapy may lead to a higher initial urinary protein remission rate.Therefore, it is advisable to develop individualized treatment plans for elderly patients with IMN based on their clinical characteristics, as well as the risks and benefits associated with immunosuppressive therapy.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Adaptive immunity is a critical component of the human immune system, playing an essential role in identifying antigens and orchestrating a tailored immune response. This review delves into the significant strides made in the development of epitope prediction tools, their integration into vaccine design, and their pivotal role in enhancing immunotherapy strategies. The review emphasizes the transformative potential of these tools in refining our understanding and application of immune responses. Adaptive immunity distinguishes itself from innate immunity by its ability to recognize specific antigens and remember past infections, leading to quicker and more effective responses upon subsequent exposures. This facet of immunity involves complex interactions between various cell types, primarily B cells and T cells, which recognize distinct epitopes presented by antigens. Epitopes are small sequences or configurations on antigens that are recognized by the immune receptors on B cells and T cells, acting as the focal points of immune recognition and response. Epitopes can be broadly classified into two types: linear (or sequential) epitopes and conformational (or discontinuous) epitopes. Linear epitopes consist of a sequence of amino acids in a protein that are recognized by B cells and T cells in their primary structure form. Conformational epitopes, on the other hand, are formed by spatially distinct amino acids that come together in the tertiary structure of the protein, often recognized by the immune system only when the protein folds into its native conformation. The role of epitopes in the immune response is critical as they are the primary triggers for the activation of B cells and T cells. When an epitope is recognized, it can stimulate B cells to produce antibodies, mobilize helper T cells to secrete cytokines, or prompt cytotoxic T cells to kill infected cells. These actions form the basis of the adaptive immune response, tailored to eliminate specific pathogens or infected cells effectively. The prediction of B cell and T cell epitopes has evolved with advances in computational biology, leading to the development of several sophisticated tools that utilize a variety of algorithms to predict the likelihood of epitope regions on antigens. Tools employing machine learning methods, such as support vector machines (SVMs), XGBoost, random forest, analyze large datasets of known epitopes to classify new sequences as potential epitopes based on their similarity to known data. Moreover, deep learning has emerged as a powerful method in epitope prediction, leveraging neural networks capable of learning high-dimensional data from vast amounts of immunological inputs to identify patterns that may not be evident to other predictive models. Deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and ESM protein language model have demonstrated superior accuracy in mapping the nonlinear relationships inherent in protein structures and epitope interactions. The application of epitope prediction tools in vaccine design is transformative, enabling the development of epitope-based vaccines that can elicit targeted immune responses against specific parts of the pathogen. These vaccines, by focusing the immune response on highly specific regions of the pathogen, can offer high efficacy and reduced side effects. Similarly, in cancer immunotherapy, epitope prediction tools help identify tumor-specific antigens that can be targeted to develop personalized immunotherapeutic strategies, thereby enhancing the precision of cancer treatments. The future of epitope prediction technology appears promising, with ongoing advancements anticipated to enhance the precision and efficiency of these tools further. The integration of broader immunological data, such as patient-specific immune profiles and pathogen variability, along with advances in AI and machine learning, will likely drive the development of more adaptive, robust, and clinically relevant prediction models. This will not only improve the effectiveness of vaccines and immunotherapies but also contribute to our broader understanding of immune mechanisms, potentially leading to breakthroughs in the treatment and prevention of multiple diseases. In conclusion, the development and refinement of epitope prediction tools stand as a cornerstone in the advancement of immunological research and therapeutic design, highlighting a path toward more precise and personalized medicine. The ongoing integration of computational models with experimental immunology holds the promise of revolutionizing our approach to combating infectious diseases and cancer.

Macroporous adsorption resin, MCI, Toyopearl HW-40C and silica gel column chromatography combined with the semi-preparative HPLC were used to isolate and purify the water extract of Cornus officinalis. And the structures of compounds were identified by HRESIMS, NMR, IR, UV and ECD. A total of twelve compounds were isolated from the fruits of Cornus officinalis. They were identified as neolignan B (1), 2,3-dihydro-7-methoxy-2-(4′-hydroxy-3′-methoxyphenyl)-3a-O-β-D-xylopyranosyloxymethyl-5-benzofuranpropanol (2), cornucadinoside A (3), 3,4-dihydroxyacetophenone (4), n-butyl gallate (5), 3-hydroxybenzoic acid (6), n-butyl quininate (7), 5-hydroxymaltol (8), 2-furolic acid (9), 5-hydroxymethylfurfural (10), 5-(methoxycarbonyl)-2-pyrrolidone (11), and dimethyl malate (12). Compound 1 is a new biphenyl lignan, named as neolignan B. Compounds 2, 4, 5, 7-9 and 11 were isolated from Cornus officinalis for the first time.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

Naturally derived metabolites are valuable resources for drug research and development, and play an important role in the treatment of diseases. As the "second genome" of the body, gut microbiota is rich in metabolic enzymes, which interacts with external substances such as drugs, thus affecting the progression of diseases. This article summarizes the interaction between gut microbiota-producing enzymes and natural medicines, and focuses on the impact of this interaction on disease progression, hoping to provide new ideas for the development and pharmacological mechanism of natural medicines.