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Surface-enhanced Raman scattering (SERS) is a promising analytical technique with applications in environmental monitoring, healthcare, and the biopharmaceutical industry. While SERS has been successfully applied to molecules such as 4-mercaptobenzoic acid and other thiol- and amine-containing compounds, there is limited research on its detection capabilities for molecules rich in carboxyl groups or unsaturated bonds, such as citric acid. This study investigates the SERS enhancement of Au@Ag core-shell nanoparticles in response to citric acid and other molecules with carboxyl and unsaturated bonds. We compare the SERS behavior of nanoparticles in freshly prepared and aged sodium citrate solutions to identify differences in Raman peak enhancement. Our findings show that the Au@Ag core-shell nanoparticles exhibit significant SERS enhancement when exposed to citric acid and other related compounds. The enhancement varies based on the age of the sodium citrate solution, which influences the structural properties of the nanoparticles. This work opens avenues for further research and applications in biological monitoring, environmental testing, and the pharmaceutical industry.

IntroductionThe frequent occurrence of mutations in the SARS-CoV-2 Spike (S) protein, with up to dozens of mutations, poses a severe threat to the current efficacy of authorized COVID-19 vaccines. Membrane (M) protein, which is the most abundant viral structural protein, exhibits a high level of amino acid sequence conservation. M protein ectodomain could be recognized by specific antibodies; however, the extent to which it is immunogenic and provides protection remains unclear.MethodsWe designed and synthesized multiple peptides derived from coronavirus M protein ectodomains, and determined the secondary structure of specific peptides using circular dichroism (CD) spectroscopy. Enzyme-linked immunosorbent assay (ELISA) was utilized to detect IgG responses against the synthesized peptides in clinical samples. To evaluate the immunogenicity of peptide vaccines, BALB/c mice were intraperitoneally immunized with peptide-keyhole limpet hemocyanin (KLH) conjugates adjuvanted with incomplete Freund’s adjuvant (IFA). The humoral and T-cell immune responses induced by peptide-KLH conjugates were assessed using ELISA and ELISpot assays, respectively. The efficacy of the S2M2-30-KLH vaccine against SARS-CoV-2 variants was evaluated in vivo using the K18-hACE2 transgenic mouse model. The inhibitory effect of mouse immune serum on SARS-CoV-2 virus replication in vitro was evaluated using microneutralization assays. The subcellular localization of the M protein was evaluated using an immunofluorescent staining method, and the Fc-mediated antibody-dependent cellular cytotoxicity (ADCC) activity of the S2M2-30-specific monoclonal antibody (mAb) was measured using an ADCC reporter assay.ResultsSeroconversion rates for ectodomain-specific IgG were observed to be high in both SARS-CoV-2 convalescent patients and individuals immunized with inactivated vaccines. To assess the protective efficacy of the M protein ectodomain-based vaccine, we initially identified a highly immunogenic peptide derived from this ectodomain, named S2M2-30. The mouse serum specific to S2M2-30 showed inhibitory effects on the replication of SARS-CoV-2 variants in vitro. Immunizations of K18-hACE2-transgenic mice with the S2M2-30-keyhole limpet hemocyanin (KLH) vaccine significantly reduced the lung viral load caused by B.1.1.7/Alpha (UK) infection. Further mechanism investigations reveal that serum neutralizing activity, specific T-cell response and Fc-mediated antibody-dependent cellular cytotoxicity (ADCC) correlate with the specific immuno-protection conferred by S2M2-30.DiscussionThe findings of this study suggest that the antibody responses against M protein ectodomain in the population most likely exert a beneficial effect on preventing various SARS-CoV-2 infections.

Coronavirus disease 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently spreading rapidly around the world. Since SARS-CoV-2 seriously threatens human life and health as well as the development of the world economy, it is very urgent to identify effective drugs against this virus. However, traditional methods to develop new drugs are costly and time-consuming, which makes drug repositioning a promising exploration direction for this purpose. In this study, we collected known antiviral drugs to form five virus-drug association datasets, and then explored drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization (VDA-GKSBMF). By the 5-fold cross-validation, we found that VDA-GKSBMF has an area under curve (AUC) value of 0.8851, 0.8594, 0.8807, 0.8824, and 0.8804, respectively, on the five datasets, which are higher than those of other state-of-art algorithms in four datasets. Based on known virus-drug association data, we used VDA-GKSBMF to prioritize the top-k candidate antiviral drugs that are most likely to be effective against SARS-CoV-2. We confirmed that the top-10 drugs can be molecularly docked with virus spikes protein/human ACE2 by AutoDock on five datasets. Among them, four antiviral drugs ribavirin, remdesivir, oseltamivir, and zidovudine have been under clinical trials or supported in recent literatures. The results suggest that VDA-GKSBMF is an effective algorithm for identifying potential antiviral drugs against SARS-CoV-2.

BackgroundThe association between hematologic parameters and anti-programmed death-1 (PD-1) inhibitors was generally examined without considering therapy lines and medicine types. The study was aimed to identify potential hematologic biomarkers associated with clinical outcome in patients with non-small cell lung cancer (NSCLC) treated with first-line pembrolizumab and subsequent-line nivolumab.Materials and methods161 NSCLC patients were categorized into first-line pembrolizumab group (pembrolizumab group) and subsequent-line nivolumab group (nivolumab group). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic value of hematologic parameters for clinical outcomes.ResultsThe median progression-free survival (mPFS) was 9.6 months in the pembrolizumab group and 4.1 months in the nivolumab group (HR =1.61; P = 0.012); the median overall survival (mOS) was not reached in the pembrolizumab group and 17.7 months in the nivolumab group (HR =1.37; P = 0.23). Of the 79 patients in the pembrolizumab group, baseline PD-L1 tumor proportion score (TPS)≥1% was an independent factor of longer PFS and OS. Age≥60 years, absolute platelet count (APC)≥220×109/L and platelet-to-lymphocyte ratio (PLR)≥120 were associated with inferior PFS. Of the 82 patients in the nivolumab group, absolute neutrophil count (ANC)≥3×109/L was associated with longer PFS, while LDH (lactate dehydrogenase)≥160 U/L was associated with inferior PFS and derived neutrophil-to-lymphocyte ratio (dNLR)≥1.2 was associated with longer OS.ConclusionOur study identified multiple clinically accessible prognostic biomarkers in the peripheral blood in both the pembrolizumab and nivolumab subgroups.

Obesity has become an increasingly serious public health problem. Pancreatic lipase (PL) is identified as a ideal target for the prevention and treatment of obesity. Orlistat, the only approved PL inhibitor (PLI), is a powerful weight loss drug but has many side effects. Therefore, there is an urgent need to discover powerful PLIs with high safety. Protein hydrolysate has been demonstrated to be a treasure trove of PLIs, but recognizing responsible functional peptides from them is like looking for a needle in a haystack. In this work, we synthesized and optimized a PL ligand fishing model (PLLFM) using magnetic nanoparticles (MNPs), then PLLFM was used to quickly fish out potential PLIs from the Cod meat hydrolysate (CMH). Finally, two new PLIs, GSPPPSG and KLEGDLK were identified with IC50 of 0.60 and 1.08 mg/mL, respectively. The Lineweaver-Burk diagram showed that GSPPPSG is a non-competitively dominant mixed-type PLI, whereas KLEGDLK is a competitive inhibitory-type PLI. Moreover, molecular docking suggested that both peptides can stably bind to the key amino acid residues of the PL active site, mainly through hydrogen bonding, hydrophobic, and electrostatic interactions. In general, we not only established a method to rapidly fish out potential PLIs from protein hydrolysate, but also provided safe and efficient lead compounds for the development of novel diet foods or drugs.

The coordinated relationship between urban population–land spatial patterns (UPLSPs) and ecological efficiency (EE) is conducive not only to the rational utilization of resources and environment and the sustainable development of society, but also to the provision of a living environment that benefits public health. Identifying the coupling relationship of urban development and EE can provide critical information for urban planning. Previous studies have mainly focused on the coupling relationship between urban population and land, urbanization, and ecological development, while ignoring that between UPLSPs and EE. This study integrates several models to construct a novel framework for coupling UPLSPs and EE. Taking Hubei Province as the research area, we calculate the UPLSPs, EE, and their coupling coordination degree for 12 cities from 2000 to 2019. The paper offers several conclusions. (1) the urban population–land spatial matching degree increased, but the overall matching level was not high; the average value of EE showed an “N”-shaped change trajectory, and its overall level was low, with small changes and obvious regional differences. (2) The average value of the coupling coordination degree between UPLSPs and EE was a slow upward trend, with a radial distribution high in the middle and low in the periphery. There was conflict between the spatial patterns and EE, and the former restricted the development of the latter. (3) There were strong correlations between coordination degree and various indicators of UPLSPs and EE. While we should revitalize the stock of construction land and optimize the upgrading of the industrial structure, we also must coordinate human and land resources and the ecological environment, and narrow regional development differences. This study provides a new framework for urban environmental assessment and urban planning decision-making.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with an extremely low 5-year survival rate. Accumulating evidence has unveiled that inflammatory response promotes tumor progression, enhances angiogenesis, and causes local immunosuppression. Herein, we aim to develop an inflammatory related prognostic signature, and found it could be used to predict gemcitabine response in PDAC.Methods: PDAC cohorts with mRNA expression profiles and clinical information were systematically collected from the four public databases. An inflammatory response related genes (IRRGs) prognostic signature was constructed by LASSO regression analysis. Kaplan–Meier survival analysis, receiver operating characteristic analysis, principal component analysis, and univariate and multivariate Cox analyses were carried out to evaluate effectiveness, and reliability of the signature. The correlation between gemcitabine response and risk score was evaluated in the TCGA-PAAD cohort. The GDSC database, pRRophetic algorithm, and connectivity map analysis were used to predict gemcitabine sensitivity and identify potential drugs for the treatment of PDAC. Finally, we analyzed differences in frequencies of gene mutations, infiltration of immune cells, as well as biological functions between different subgroups divided by the prognostic signature.Results: We established a seven IRRGs (ADM, DCBLD2, EREG, ITGA5, MIF, TREM1, and BTG2) signature which divided the PDAC patients into low- and high-risk groups. Prognostic value of the signature was validated in 11 PDAC cohorts consisting of 1337 PDAC patients from 6 countries. A nomogram that integrated the IRRGs signature and clinicopathologic factors of PDAC patients was constructed. The risk score showed positive correlation with gemcitabine resistance. Two drugs (BMS-536924 and dasatinib) might have potential therapeutic implications in high-risk PDAC patients. We found that the high-risk group had higher frequencies of KRAS, TP53, and CDKN2A mutations, increased infiltration of macrophages M0, neutrophils, and macrophages M2 cells, as well as upregulated hypoxia and glycolysis pathways, while the low-risk group had increased infiltration of CD8+ T, naïve B, and plasma and macrophages M1 cells.Conclusion: We constructed and validated an IRRGs signature that could be used to predict the prognosis and gemcitabine response of patients with PDAC, as well as two drugs (BMS-536924 and dasatinib) may contribute to PDAC treatment.

Diffuse gliomas are the most common malignant primary brain tumors. Identification of isocitrate dehydrogenase 1 (IDH1) mutations aids the diagnostic classification of these tumors and the prediction of their clinical outcomes. While histology continues to play a key role in frozen section diagnosis, as a diagnostic reference and as a method for monitoring disease progression, recent research has demonstrated the ability of multi-parametric magnetic resonance imaging (MRI) sequences for predicting IDH genotypes. In this paper, we aim to improve the prediction accuracy of IDH1 genotypes by integrating multi-modal imaging information from digitized histopathological data derived from routine histological slide scans and the MRI sequences including T1-contrast (T1) and Fluid-attenuated inversion recovery imaging (T2-FLAIR). In this research, we have established an automated framework to process, analyze and integrate the histopathological and radiological information from high-resolution pathology slides and multi-sequence MRI scans. Our machine-learning framework comprehensively computed multi-level information including molecular level, cellular level, and texture level information to reflect predictive IDH genotypes. Firstly, an automated pre-processing was developed to select the regions of interest (ROIs) from pathology slides. Secondly, to interactively fuse the multimodal complementary information, comprehensive feature information was extracted from the pathology ROIs and segmented tumor regions (enhanced tumor, edema and non-enhanced tumor) from MRI sequences. Thirdly, a Random Forest (RF)-based algorithm was employed to identify and quantitatively characterize histopathological and radiological imaging origins, respectively. Finally, we integrated multi-modal imaging features with a machine-learning algorithm and tested the performance of the framework for IDH1 genotyping, we also provided visual and statistical explanation to support the understanding on prediction outcomes. The training and testing experiments on 217 pathologically verified IDH1 genotyped glioma cases from multi-resource validated that our fully automated machine-learning model predicted IDH1 genotypes with greater accuracy and reliability than models that were based on radiological imaging data only. The accuracy of IDH1 genotype prediction was 0.90 compared to 0.82 for radiomic result. Thus, the integration of multi-parametric imaging features for automated analysis of cross-modal biomedical data improved the prediction accuracy of glioma IDH1 genotypes.

Lymphomatoid granulomatosis (LYG) is an infrequent lymphoproliferative disease that typically involves the lungs, but may also affect the central nervous system (CNS). Isolated CNS involvement is very rare, and its clinicopathological features have not been fully elucidated. Here, we systematically reviewed the English literature through PubMed to collect all relevant case reports and small case series with pathologically confirmed primary CNS-LYG. A total of 29 relevant articles with 40 cases were included in this systemic review. In cases where T cells and B cells were compared, T cells were predominant in 19 (79.2%), and B cells were predominant in 5 (20.8%). The overall infection rate of EBV was 48.1% (13/27), among which the infection rate was 40.9% (9/22) in immunocompetent patients and 80% (4/5) in immunodeficient (HIV-infected) patients. Among the patients who underwent pathological grading, 35.7% (5/14) were at grade I, 42.9% (6/14) were at grade II, and 21.4% were at grade III. In conclusion, primary CNS-LYG is closely related to EBV infection and some cases may be predominantly T-cell phenotype. Surgical resection may be effective for mass-like lesions, although there is still a lack of standard therapeutic regimen. Accurate grading of lesions is essential for treatment selection and prognosis evaluation.

Background: The association between hematologic parameters and antiprogrammed death-1 (PD-1) inhibitors was generally examined without considering therapy lines and medicine types. The study was aimed to identify potential hematologic biomarkers associated with clinical outcome in patients with non-small cell lung cancer (NSCLC) treated with first-line pembrolizumab and subsequent-line nivolumab. Materials and methods: 161 NSCLC patients were categorized into first-line pembrolizumab group (pembrolizumab group) and subsequent-line nivolumab group (nivolumab group). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic value of hematologic parameters for clinical outcomes. Results: The median progression-free survival (mPFS) was 9.6 months in the pembrolizumab group and 4.1 months in the nivolumab group (HR =1.61; P = 0.012); the median overall survival (mOS) was not reached in the pembrolizumab group and 17.7 months in the nivolumab group (HR =1.37; P = 0.23). Of the 79 patients in the pembrolizumab group, baseline PD-L1 tumor proportion score (TPS)=1% was an independent factor of longer PFS and OS. Age=60 years, absolute platelet count (APC)=220×109/L and platelet-tolymphocyte ratio (PLR)=120 were associated with inferior PFS. Of the 82 patients in the nivolumab group, absolute neutrophil count (ANC)=3×109/L was associated with longer PFS, while LDH (lactate dehydrogenase)=160 U/L was associated with inferior PFS and derived neutrophil-to-lymphocyte ratio (dNLR)=1.2 was associated with longer OS. Conclusion: Our study identified multiple clinically accessible prognostic biomarkers in the peripheral blood in both the pembrolizumab and nivolumab subgroups. [ABSTRACT FROM AUTHOR]