Non-invasive prediction nomogram for predicting significant fibrosis in patients with metabolic-associated fatty liver disease: a cross-sectional study

BACKGROUND AND AIM

This study aims to validate the efficacy of the conventional non-invasive score in predicting significant fibrosis in metabolic-associated fatty liver disease (MAFLD) and to develop a non-invasive prediction model for MAFLD.

METHODS

This cross-sectional study was conducted among 7701 participants with MAFLD from August 2018 to December 2023. All participants were divided into a training cohort and a validation cohort. The study compared different subgroups' demographic, anthropometric, and laboratory examination indicators and conducted logistic regression analysis to assess the correlation between independent variables and liver fibrosis. Nomograms were created using the logistic regression model. The predictive values of noninvasive models and nomograms were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA).

RESULTS

Four nomograms were developed for the quantitative analysis of significant liver fibrosis risk based on the multivariate logistic regression analysis results. The nomogram's area under ROC curves (AUC) was 0.710, 0.714, 0.748, and 0.715 in overall MAFLD, OW-MAFLD, Lean-MAFLD, and T2DM-MAFLD, respectively. The nomogram had a higher AUC in all MAFLD participants and OW-MAFLD than the other non-invasive scores. The DCA curve showed that the net benefit of each nomogram was higher than that of APRI and FIB-4. In the validation cohort, the AUCs of the nomograms were 0.722, 0.750, 0.719, and 0.705, respectively.

CONCLUSION

APRI, FIB-4, and NFS performed poorly predicting significant fibrosis in patients with MAFLD. The new model demonstrated improved diagnostic accuracy and clinical applicability in identifying significant fibrosis in MAFLD.

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis

The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the body, including the brain and spine. Developing a single drug can take several decades, making drug discovery costly and time-consuming. Machine learning algorithms like support vector machines (SVM), k-nearest neighbor (k-NN), random forest (RF) and Gaussian naive base (GNB) are fast and effective and are commonly used in drug discovery. These algorithms are ideal for the virtual screening of large compound libraries to classify molecules as active or inactive. For the training of the models, a dataset of 307 was downloaded from BindingDB. Among 307 compounds, 85 compounds were labeled as active, having an IC50 below 58 mM, while 222 compounds were labeled inactive against thymidylate kinase, with 87.2% accuracy. The developed models were subjected to an external ZINC dataset of 136,564 compounds. Furthermore, we performed the 100-ns dynamic simulation and post trajectories analysis of compounds having good interaction and score in molecular docking. As compared to the standard reference compound, the top three hits revealed greater stability and compactness. In conclusion, our predicted hits can inhibit thymidylate kinase overexpression to combat Mycobacterium tuberculosis.Communicated by Ramaswamy H. Sarma.

Unraveling the mechanisms of Sofosbuvir resistance in HCV NS3/4A protease: Structural and molecular simulation-based insights

Current management of HCV infection is based on Direct-Acting Antiviral Drugs (DAAs). However, resistance-associated mutations, especially in the NS3 and NS5B regions are gradually decreasing the efficacy of DAAs. Among the most effective HCV NS3/4A protease drugs, Sofosbuvir also develops resistance due to mutations in the NS3 and NS5B regions. Four mutations at positions A156Y, L36P, Q41H, and Q80K are classified as high-level resistance mutations. The resistance mechanism of HCV NS3/4A protease toward Sofosbuvir caused by these mutations is still unclear, as there is less information available regarding the structural and functional effects of the mutations against Sofosbuvir. In this work, we combined molecular dynamics simulation, molecular mechanics/Generalized-Born surface area calculation, principal component analysis, and free energy landscape analysis to explore the resistance mechanism of HCV NS3/4A protease due to these mutations, as well as compare interaction changes in wild-type. Subsequently, we identified that the mutant form of HCV NS3/4A protease affects the activity of Sofosbuvir. In this study, the resistance mechanism of Sofosbuvir at the atomic level is proposed. The proposed drug-resistance mechanism will provide valuable guidance for the design of HCV drugs.

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

Comparative investigation of transport and deposition of nebulized particles in nasal airways following various middle turbinectomy

BACKGROUND

Topical intranasal medication is required following functional endoscopic sinus surgery (FESS). The optimal particle size of transnasal nebulization aimed at the sinonasal cavities is not conclusive. The current study aims to evaluate the effect of particle size and various surgery scope of middle turbinectomy (MT) on post-full FESS drug delivery to the sinonasal cavities.

METHODS

Sinonasal reconstructions were performed from post-full FESS CT scans in 6 chronic rhinosinusitis with nasal polyps (CRSwNP) patients. Four additional models representing alternative surgery scopes of MT were established from each post-FESS reconstruction for simulation data comparison. Airflow and particle deposition of nebulized delivery were simulated via computational fluid dynamics (CFD) and validated through in vitro experiments. The optimal particle sizes reaching a deposition of at least 75% of the maximum in the targeted regions were identified.

RESULTS

The drug deposition rate onto the targeted regions increased following MT, with the greatest deposition following posterior MT (P-MT). Droplets in the range of 18-26 μm reached a deposition of larger than 75% of the maximum onto the targeted regions. Drug delivery rate in the sinonasal cavities varied significantly among individuals and across different types of MT with varying surgical scopes.

CONCLUSIONS

This study is the first to investigate the effect of various surgery scope on drug delivery by transnasal nebulization to the sinonasal cavities. The findings strongly affirm the vast potential of transnasal nebulization as an effective post-FESS treatment option. Moreover, it emphasizes that the drug delivery process via atomizers to the nasal cavity and paranasal sinuses is highly sensitive to the particle size.

Targeting human progesterone receptor (PR), through pharmacophore-based screening and molecular simulation revealed potent inhibitors against breast cancer

Breast cancer, the prevailing malignant tumor among women, is linked to progesterone and its receptor (PR) in both tumorigenesis and treatment responsiveness. Despite thorough investigation, the precise molecular mechanisms of progesterone in breast cancer remain unclear. The human progesterone receptor (PR) serves as an essential therapeutic target for breast cancer treatment, warranting the rapid design of small molecule therapeutics that can effectively inhibit HPR. By employing cutting-edge computational techniques like molecular screening, simulation, and free energy calculation, the process of identifying potential lead molecules from natural products has been significantly expedited. In this study, we employed pharmacophore-based virtual screening and molecular simulations to identify natural product-based inhibitors of human progesterone receptor (PR) in breast cancer treatment. High-throughput molecular screening of traditional Chinese medicine (TCM) and zinc databases was performed, leading to the identification of potential lead compounds. The analysis of binding modes for the top five compounds from both database provides valuable structural insights into the inhibition of HPR for breast cancer treatment. The top five hits exhibited enhanced stability and compactness compared to the reference compound. In conclusion, our study provides valuable insights for identifying and refining lead compounds as HPR inhibitors.

Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction

The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response. In conclusion, the immunogenic construct shows promise in providing protection against NPV, However, further experimental validation is required before moving to clinical trials.

Pharmacokinetics of Ziyuglycoside I and Ziyuglycoside II in Rat Plasma by UPLC-MS/MS

Ziyuglycoside I and ziyuglycoside II are important active components of Sanguisorba officinalis L., which have excellent pharmacological effects, such as antioxidant and anticancer effects. However, the bioavailability of ziyuglycoside I and ziyuglycoside II has not been reported. This work aims to establish a UPLC-MS/MS method to study the pharmacokinetics of ziyuglycoside I and ziyuglycoside II in rats under different administration routes (intragastric and intravenous administration) and to calculate the bioavailability. The concentration of ziyuglycoside I and ziyuglycoside II in rat plasma in the range of 2-2000 ng/mL showed a good linear relationship (r > 0.99). The intra-day accuracies of ziyuglycoside I and ziyuglycoside II ranged from 87% to 110%, and the inter-day accuracies ranged from 97% to 109%. The intra-day precision was less than 15% and the inter-day precision was less than 14%. The matrix effects ranged from 88% to 113%. The recoveries were all above 84%. The developed UPLC-MS/MS method for the determination of ziyuglycoside I and ziyuglycoside II in rat plasma was applied to pharmacokinetics. The bioavailability of ziyuglycoside I and ziyuglycoside II was measured at 2.6% and 4.6%, respectively.

Gender Differences in the Incidence of Nephropathy and Changes in Renal Function in Patients with Type 2 Diabetes Mellitus: A Retrospective Cohort Study

Purpose

This research aims to examine and scrutinize gender variations in the incidence of diabetic nephropathy (DN) and the trajectory of renal function in type 2 diabetes mellitus (T2DM) patients.

Patients and Methods

We conducted a retrospective cohort study that enrolled 1549 patients diagnosed with T2DM from May 2015 to July 2023. We separately compared the clinical characteristics of male and female participants with and without DN. We utilized the Kaplan-Meier method to examine the cumulative incidence of DN among T2DM patients of varying genders. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using univariable and multivariable Cox proportional hazards regression analysis to evaluate the correlation between various factors and the risk of DN incidence. Multiple linear regression was utilized to investigate the relationship between ΔeGFR% and each factor. Logistic regression with cubic spline function and smooth curve fitting was employed to analyze the nonlinear link between ΔeGFR% and the risk of DN among participants of different genders.

Results

The prevalence of DN was higher in female participants (17.31%) than in male participants (12.62%), with a significant cumulative risk ratio (1.33 [1.02-1.73], P = 0.034). Multiple linear regression analysis revealed that creatinine, female gender, blood urea nitrogen, alkaline phosphatase, and total cholesterol had a significant impact on ΔeGFR% in T2DM patients, with standardized β coefficients of -0.325, -0.219, -0.164, -0.084, and 0.071, respectively. The restricted cubic spline analysis demonstrated a strong negative association between ΔeGFR% and the risk of developing DN (P < 0.001).

Conclusion

Both male and female patients with T2DM had a higher prevalence of DN over the 5-year follow-up period. However, women had a greater risk of developing DN and a faster decline in renal function compared to men.

Machine learning and molecular simulation-based protocols to identify novel potential inhibitors for reverse transcriptase against HIV infections

Acquired immunodeficiency syndrome (AIDS) is a potentially fatal condition affecting the human immune system, which is attributed to the human immunodeficiency virus (HIV). The suppression of reverse transcriptase activity is a promising and feasible strategy for the therapeutic management of AIDS. In this study, we employed machine learning algorithms, such as support vector machines (SVM), k-nearest neighbor (k-NN), random forest (RF), and Gaussian naive base (GNB), which are fast and effective tools commonly used in drug design. For model training, we initially obtained a dataset of 5,159 compounds from BindingDB. The models were assessed using tenfold cross-validation to ensure their accuracy and reliability. Among these compounds, 1,645 compounds were labeled as active, having an IC50 below 0.49 µM, while 3,514 compounds were labeled "inactive against reverse transcriptase. Random forest achieved 86% accuracy on the train and test set among the different machine learning algorithms. Random forest model was then applied to an external ZINC dataset. Subsequently, only three hits-ZINC1359750464, ZINC1435357562, and ZINC1545719422-were selected based on the Lipinski Rule, docking score, and good interaction. The stability of these molecules was further evaluated by deploying molecular dynamics simulation and MM/GBSA, which were found to be -38.6013 ± 0.1103 kcal/mol for the Zidovudine/RT complex, -59.1761 ± 2.2926 kcal/mol for the ZINC1359750464/RT complex, -47.6292 ± 2.4206 kcal/mol for the ZINC1435357562/RT complex, and -50.7334 ± 2.5713 kcal/mol for the ZINC1545719422/RT complex.Communicated by Ramaswamy H. Sarma.

Design and Synthesis of Immunoadjuvant QS-21 Analogs and Their Biological Evaluation

A series of novel immunoadjuvant QS-21 analogs were synthesized, and their effects on the in vitro hemolysis of red blood cells were evaluated using QS-21 as a control and hemolytic properties as an index. Our results show that all the QS-21 analogs had lower hemolytic effects than QS-21, and their concentrations exhibited a certain quantitative effect relationship with the hemolysis rate. Notably, saponin compounds L1-L8 produced minimal hemolysis and showed lower hemolytic effects, warranting further investigation.

In silico exploration of the potential inhibitory activities of in-house and ZINC database lead compounds against alpha-glucosidase using structure-based virtual screening and molecular dynamics simulation approach

Inhibitors of α-glucosidase have been used to treat type-2 diabetes (T2DM) by preventing the breakdown of carbohydrates into glucose and prevent enhancing glucose conversion. Structure-based virtual screening (SBVS) was used to generate novel chemical scaffold-ligand α-glucosidase inhibitors. The databases were screened against the receptor α-glucosidase using SBVS and molecular dynamics simulation (MDS) techniques in this study. Based on molecular docking studies, three and two compounds of α-glucosidase inhibitors were chosen from a commercial database (ZINC) and an In-house database for this study respectively. The mode of binding interactions of the selected compounds later predicted their α-glucosidase inhibitory potential. Finally, one out of three lead compound from ZINC and one out of two lead compound from In-house database were shortlisted based on interactions. Furthermore, MDS and post-MDS strategies were used to refine and validate the shortlisted leads along with the reference acarbose/α-glucosidase. The Hits' ability to inhibit α-glucosidase was predicted by SBVS, indicating that these compounds have good inhibitory activities. The lead inhibitor's structure may serve as templates for the design of novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is necessary. These insights can help rationally design new effective anti-diabetic drugs.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-based potential multi-peptide vaccine designing against Jamestown Canyon Virus (JCV) capable of eliciting cellular and humoral immune responses

Jamestown Canyon virus (JCV) is a deadly viral infection transmitted by various mosquito species. This mosquito-borne virus belongs to Bunyaviridae family, posing a high public health threat in the in tropical regions of the United States causing encephalitis in humans. Common symptoms of JCV include fever, headache, stiff neck, photophobia, nausea, vomiting, and seizures. Despite the availability of resources, there is currently no vaccine or drug available to combat JCV. The purpose of this study was to develop an epitope-based vaccine using immunoinformatics approaches. The vaccine aimed to be secure, efficient, bio-compatible, and capable of stimulating both innate and adaptive immune responses. In this study, the protein sequence of JCV was obtained from the NCBI database. Various bioinformatics methods, including toxicity evaluation, antigenicity testing, conservancy analysis, and allergenicity assessment were utilized to identify the most promising epitopes. Suitable linkers and adjuvant sequences were used in the design of vaccine construct. 50s ribosomal protein sequence was used as an adjuvant at the N-terminus of the construct. A total of 5 CTL, 5 HTL, and 5 linear B cell epitopes were selected based on non-allergenicity, immunological potential, and antigenicity scores to design a highly immunogenic multi-peptide vaccine construct. Strong interactions between the proposed vaccine and human immune receptors, i.e., TLR-2 and TLR-4, were revealed in a docking study using ClusPro software, suggesting their possible relevance in the immunological response to the vaccine. Immunological and physicochemical properties assessment ensured that the proposed vaccine demonstrated high immunogenicity, solubility and thermostability. Molecular dynamics simulations confirmed the strong binding affinities, as well as dynamic and structural stability of the proposed vaccine. Immune simulation suggest that the vaccine has the potential to effectively stimulate cellular and humoral immune responses to combat JCV infection. Experimental and clinical assays are required to validate the results of this study.

Exploring potent aldose reductase inhibitors for anti-diabetic (anti-hyperglycemic) therapy: integrating structure-based drug design, and MMGBSA approaches

Aldose reductase (AR) is an important target in the development of therapeutics against hyper-glycemia-induced health complications such as retinopathy, etc. In this study, we employed a combination of structure-based drug design, molecular simulation, and free energy calculation approaches to identify potential hit molecules against anti-diabetic (anti-hyperglycemic)-induced health complications. The 3D structure of aldoreductase was screened for multiple compound libraries (1,00,000 compounds) and identified as ZINC35671852, ZINC78774792 from the ZINC database, Diamino-di nitro-methyl dioctyl phthalate, and Penta-o-galloyl-glucose from the South African natural compounds database, and Bisindolylmethane thiosemi-carbazides and Bisindolylme-thane-hydrazone from the Inhouse database for this study. The mode of binding interactions of the selected compounds later predicted their aldose reductase inhibitory potential. These com-pounds interact with the key active site residues through hydrogen bonds, salt bridges, and π-π interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. The structures of the lead inhibitors can serve as templates for developing novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is warranted. The current study is the first to design small molecule inhibitors for the aldoreductase protein that can be used in the development of therapeutic agents to treat diabetes.

Design of a novel multiple epitope-based vaccine: an immunoinformatics approach to combat monkeypox

Monkeypox virus is an infectious agent that causes fever, Pneumonitis encephalitis, rash, lymphadenopathy and bacterial infection. The current outbreak of monkeypox has reawakened the global health concern. In the current situation of increasing viral infection, no vaccine or drug is available for monkeypox. Thus, there is an urgent need for viable vaccine development to prevent viral transmission by boosting human immunity. Herein, using immunoinformatics approaches, a multi-epitope vaccine was constructed for the Monkeypox virus. In this connection, B-Cell and T-cell epitopes were identified and joined with the help of adjutants and linkers. The vaccine construct was selected based on promising vaccine candidates and immunogenic potential. Further epitopes were selected based on antigenicity score, non-allergenicity and good immunological properties. Molecular docking reveals strong interactions between TLR-9 and the predicted vaccine construct. Finally, molecular dynamics simulations were performed to evaluate the stability and compactness of the constructed vaccine. The MD simulation results demonstrated the significant stability of the polypeptide vaccine construct. The predicted vaccine represented good stability, expression, immunostimulatory capabilities and significant solubility. Design vaccine was verified as efficient in different computer-based immune response investigations. Additionally, the constructed vaccine also represents a good population coverage in computer base analysis.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening, molecular simulation and free energy calculations of traditional Chinese medicine, ZINC database revealed potent inhibitors of estrogen-receptor α (ERα)

Breast Cancer, a heterogeneous disease at the molecular level, is the most common cause of woman mortality worldwide. We used molecular screening and simulation approaches to target nuclear receptor protein-estrogen receptor alpha (Erα) protein to design and develop of specific and compelling drugs from traditional Chinese medicine (TCM), and ZINC database against pathophysiology of breast cancer. Using virtual screening, only six hits TCM22717, TCM23524, TCM31953, while ZINC05632920, ZINC05773243, and ZINC12780336 demonstrated better pharmacological potential than the 4-hydroxytamoxifen (OHT) taken as control. Binding mode of each of the top hit revealed that these compounds could block the main active site residues and block the function of Erα protein. Moreover, molecular simulation revealed that the identified compounds exhibit stable dynamics and may induce stronger therapeutic effects in experimental setup. All the complexes reported tighter structural packing and less flexible behaviour. We found that the average hydrogen bonds in the identified complexes remained higher than the control drug. Finally, the total binding free energy demonstrated the best hits among the all. The BF energy results revealed -30.4525 ± 3.3565 for the 4-hydroxytamoxifen (OHT)/Erα complex, for the TCM22717/Erα -57.0597 ± 3.4852 kcal/mol, for the TCM23524/Erα complex the BF energy was -56.9084 ± 3.3737 kcal/mol, for the TCM31953/Erα the BF energy was -32.4191 ± 3.8864 kcal/mol while for the ZINC05632920/Erα complex -46.3182 ± 2.7380, ZINC05773243/Erα complex -38.3690 ± 2.8240, and ZINC12780336/Erα complex the BF energy was calculated to be -35.8048 ± 4.1571 kcal/mol.Communicated by Ramaswamy H. Sarma.

Napthyridine-derived compounds as promising inhibitors for Staphylococcus aureus CrtM: a primer for the discovery of potential anti-Staphylococcus aureus agents

The disease-free existence of humans is constantly under attack by a variety of infections caused by a variety of organisms including bacteria. Notable among the bacteria is Staphylococcus aureus which is an etiological organism for infections including impetigo, folliculitis, and furuncles. The response of the human immune system against this disease is often neutralized by the production of a pigment called Staphyloxanthin (STX) via a series of reactions mediated by several enzymes. Among these enzymes, dehydrosqualene synthase, also known as CrtM, has emerged as a viable drug target due to its role in mediating the first step of the pathway. Consequently, this study employs molecular modeling approaches including molecular docking, quantum mechanical calculations, and molecular dynamics (MD) simulations among others to investigate the potential of napthyridine derivatives to serve as inhibitors of the CrtM. The results of the study revealed the high binding affinities of the compounds for the target as demonstrated by their docking scores, while further subjection to screening pipeline aimed at determining their fitness for development into drugs revealed just one compound namely 6-[[1-[(2-fluorophenyl) methyl]triazol-4-yl]methoxy]-4-oxo-1H-1,5-naphthyridine-3-carboxylic acid as the compound with good drug-like, pharmacokinetics, and toxicity properties profiles. A 100 ns-long MD simulation of the complexes formed after molecular docking revealed the stable interaction of the compound with the target. Ultimately, this study can be a promising outlet to discover a weapon to fight against clinically resistant bacteria, however, further experimental studies are suggested to carry out in the wet lab, pre-clinical, and clinical levels.

Suppressed Concentration Quenching Brightens Short-Wave Infrared Emitters

The brightness of doped luminescent materials is usually limited by the ubiquitous concentration quenching phenomenon resulting in an intractable tradeoff between internal quantum efficiency and excitation efficiency. Here, an intrinsic suppression of concentration quenching in sensitized luminescent systems, by exploiting the competitive relationship between light emitters and quenchers in trapping excitation energies from sensitizers, is reported. Although Cr3+ sensitizers and trivalent lanthanide (Ln3+ , Ln = Yb, Nd, and Er) emitters themselves are highly susceptible to concentration quenching, the unprecedentedly high-brightness luminescence of Cr3+ -Ln3+ systems is demonstrated in the short-wave infrared (SWIR) range employing high concentrations of Cr3+ , whereby a record photoelectric efficiency of 23% is achieved for SWIR phosphor-converted light-emitting diodes, which is about twice as high as those previously reported. The results underscore the beneficial role of emitters in terminating excitation energies, opening up a new dimension for developing efficient sensitized luminescent materials.

Structure based virtual screening and molecular simulation study of FDA-approved drugs to inhibit human HDAC6 and VISTA as dual cancer immunotherapy

Cancer immunotherapy has significantly contributed to the treatment of various types of cancers mainly by targeting immune checkpoint inhibitors (ICI). Among them, V-domain immunoglobulin suppressor of T cell activation (VISTA) has been explored as a promising therapeutic target. Besides, histone deacetylase 6 (HDAC6) has been demonstrated to be efficacious target for several cancers. The current theoretical work was performed to explore the virtual repurposing of the FDA-approved drugs as inhibitors against these two (VISTA and HDAC6) cancers therapeutic targets. The crystal structure of the two proteins were downloaded from PDB and subjected to virtual screening by DrugRep webserver while using FDA-approved drugs library as ligands database. Our study revealed that Oxymorphone and Bexarotene are the top-ranked inhibitors of VISTA and HDAC6, respectively. The docking score of Bexarotene was predicted as - 10 kcal/mol while the docking score of Oxymorphone was predicted as - 6.2 kcal/mol. Furthermore, a total of 100 ns MD simulation revealed that the two drugs Oxymorphone and Bexarotene formed stable complexes with VISTA and HDAC6 drug targets. As compared to the standard drug the two drugs Oxymorphone and Bexarotene revealed great stability during the whole 100 ns MD simulation. The binding free energy calculation further supported the Root Mean Square Deviation (RMSD) result which stated that as compared to the ref/HDAC6 (- 18.0253 ± 2.6218) the binding free energy score of the Bexarotene/HDAC6 was good (- 51.9698 ± 3.1572 kcal/mol). The binding free energy score of Oxymorphone/VISTA and Ref/VISTA were calculated as - 36.8323 ± 3.4565, and - 21.5611 ± 4.8581 respectively. In conclusion, the two drugs deserve further consideration as cancer treatment option.

Machine Learning-Based Virtual Screening and Molecular Simulation Approaches Identified Novel Potential Inhibitors for Cancer Therapy

Cyclin-dependent kinase 2 (CDK2) is a promising target for cancer treatment, developing new effective CDK2 inhibitors is of great significance in anticancer therapy. The involvement of CDK2 in tumorigenesis has been debated, but recent evidence suggests that specifically inhibiting CDK2 could be beneficial in treating certain tumors. This approach remains attractive in the development of anticancer drugs. Several small-molecule inhibitors targeting CDK2 have reached clinical trials, but a selective inhibitor for CDK2 is yet to be discovered. In this study, we conducted machine learning-based drug designing to search for a drug candidate for CDK2. Machine learning models, including k-NN, SVM, RF, and GNB, were created to detect active and inactive inhibitors for a CDK2 drug target. The models were assessed using 10-fold cross-validation to ensure their accuracy and reliability. These methods are highly suitable for classifying compounds as either active or inactive through the virtual screening of extensive compound libraries. Subsequently, machine learning techniques were employed to analyze the test dataset obtained from the zinc database. A total of 25 compounds with 98% accuracy were predicted as active against CDK2. These compounds were docked into CDK2's active site. Finally, three compounds were selected based on good docking score, and, along with a reference compound, underwent MD simulation. The Gaussian naïve Bayes model yielded superior results compared to other models. The top three hits exhibited enhanced stability and compactness compared to the reference compound. In conclusion, our study provides valuable insights for identifying and refining lead compounds as CDK2 inhibitors.

In silico mutagenesis-based designing of oncogenic SHP2 peptide to inhibit cancer progression

Cancer is among the top causes of death, accounting for an estimated 9.6 million deaths in 2018, it appeared that approximately 500,000 people die from cancer in the United States alone annually. The SHP2 plays a major role in regulation of cell growth, proliferation, and differentiation, and functional upregulation of this enzyme is linked to oncogenesis and developmental disorders. SHP2 activity has been linked to several cancer types for which no drugs are currently available. In our study, we aimed to design peptide inhibitors against the SHP2 mutant. The crystal structure of the human Src SH2-PQpYEEIPI peptide mutant was downloaded from the protein databank. We generated several peptides from the native wild peptide using an in silico mutagenesis method, which showed that changes (P302W, Y304F, E306Q, and Q303A) might boost the peptide's affinity for binding to SHP2. Furthermore, the dynamical stability and binding affinities of the mutated peptide were confirmed using Molecular dynamics simulation and Molecular Mechanics with Generalized Born and Surface Area Solvation free energy calculations. The proposed substitution greatly enhanced the binding affinity at the residue level, according to a study that decomposed energy into its component residues. Our proposed peptide may prevent the spread of cancer by inhibiting SHP2, according to our detailed analyses of binding affinities.

Computational design of medicinal compounds to inhibit RBD-hACE2 interaction in the Omicron variant: unveiling a vulnerable target site

The COVID-19 pandemic, caused by SARS-CoV-2, has globally affected both human health and economy. Several variants with a high potential for reinfection and the ability to evade immunity were detected shortly after the initial reported case of COVID-19. A total of 30 mutations in the spike protein (S) have been reported in the SARS-CoV-2 (BA.2) variant in India and South Africa, while half of these mutations are in the receptor-binding domain and have spread rapidly throughout the world. Drug repurposing offers potential advantages over the discovery of novel drugs, and one is that it can be delivered quickly without lengthy assessments and time-consuming clinical trials. In this study, computational drug design, such as pharmacophore-based virtual screening and MD simulation has been concentrated, in order to find a novel small molecular inhibitor that prevents hACE2 from binding to the receptor binding domain (RBD). three medicinal compound databases: North-East African, North African, and East African were screened and carried out a multi-step screening approach that identified three compounds, which are thymoquinol 2-O-beta-glucopyranoside (C1), lanneaflavonol (C2), and naringenin-4'-methoxy-7-O-Alpha-L-rhamnoside (C3), with excellent anti-viral properties against the RBD of the omicron variant. Furthermore, PAIN assay interference, computation bioactivity prediction, binding free energy, and dissociation constant were used to validate the top hits, which indicated good antiviral activity. The three compounds that were found may be useful against COVID-19, though more research is required. These findings could aid the development of novel therapeutic drugs against the emerging Omicron variant of SARS-CoV-2.

[Efficacy of Hintermann calcaneal lengthening osteotomy for flexible flatfoot]

Objective: To investigate the clinical efficacy of Hintermann osteotomy (H-LCL) for flexible flatfoot. Methods: A follow-up study. Clinical data of 30 patients with flexible flatfoot treated with H-LCL operation from January 2020 to December 2021 in Sports Medical Center of the First Affiliated Hospital of Army Medical University were retrospectively analyzed. There were 8 males and 22 females, with a mean age of (39.0±15.2) years. The mean time from symptom onset to the diagnosis［M（Q₁，Q₃）］was 24.0 (5.5, 102.0) months. The functional and imaging scores of the patients before and after the last follow-up were compared to evaluate the clinical efficacy of the operation. The functional scores included American Orthopedic Foot and Ankle Society (AOFAS) score, visual analogue scale (VAS) of pain, pain interference (PI) and physical function (PF) index in Patient-Reported Outcomes Measurement Information System (PROMIS). And the imaging scores included Meary's angle, calcaneal pitch angle, calcaneal valgus angle and talonavicular coverage angle. Results: The mean operation time was (82.3±24.4) min, and the follow-up periods was (17.9±6.9) months. At the last follow-up, VAS of pain [M(Q₁, Q₃)] decreased from 5 (4, 6) to 2 (1, 2); PI decreased from 59.8±5.0 to 44.6±5.7; AOFAS increased from 65.2±10.0 to 85.8±3.3; PF increased from 50 (48.5,51.0) to 58.5 (54.0, 66.0); Meary's angle (antero-posterior image) decreased from 15.7° (10.1°, 29.2°) to 3.9° (2.6°, 5.3°); Meary's angle (lateral image) decreased from 13.5°±6.8° to 4.4°±2.6°; calcaneal pitch angle increased from 14.0°±3.3° to 18.6°±4.2°; calcaneal valgus angle decreased from 12.6°±7.3° to 4.3°±2.5°; and talonavicular coverage angle decreased from 20.9°±10.7° to 7.7°±5.2°. The up-mentioned parameters were all improved statistically significant at the last follow-up when compared with those before the operation (all P<0.05). Conclusion: H-LCL brings a significant improvement of clinical outcome scores and good radiological correction of flatfoot deformities in correcting flexible flatfoot, it conforms to the anatomical characteristics of the subtalar joint.

Design of a Novel and Potent Multi-Epitope Chimeric Vaccine against Human Papillomavirus (HPV): An Immunoinformatics Approach

In the current era, our experience is full of pandemic infectious agents that no longer threaten the major local source but the whole globe. One such infectious agent is HPV, a sexually transmitted disease that can cause various clinical disorders, including benign lesions and cervical cancer. Since available vaccines still need further improvements in order to enhance efficacy, our goal was to design a chimeric vaccine against HPV using an immunoinformatics approach. For designing the vaccine, the sequence of HPV was retrieved, and then phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes were all predicted using bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for vaccine construction, and then physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking and dynamics simulation techniques were used to explore the interactions between the Toll-like receptor 2 and the modeled vaccine construct. To ensure the vaccine protein was expressed at a higher level, the construct was computationally cloned into the pET28a (+) plasmid. The molecular docking and simulation results showed that our designed vaccine is stable, of immunogenic quality, and has considerable solubility. Through in silico immune simulation, it was predicted that the designed polypeptide vaccine construct would trigger both humoral and cellular immune responses. The developed vaccine showed significant affinity for the TLR2 receptor molecule. However, additional laboratory research is required to evaluate its safety and efficacy.

A surface molecularly imprinted electrochemical biosensor for the detection of SARS-CoV-2 spike protein by using Cu7S4-Au as built-in probe

Sensitive detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein (S protein) is of significant clinical importance in the diagnosis of COVID-19 pandemic. In this work, a surface molecularly imprinted (SMI) electrochemical biosensor is fabricated for the detection of SARS-CoV-2 S protein. Cu₇S₄-Au is used as the built-in probe and modified on the surface of a screen-printed carbon electrode (SPCE). 4-Mercaptophenylboric acid (4-MPBA) is anchored to the surface of the Cu₇S₄-Au through Au-SH bonds, which can be used for the immobilization of the SARS-CoV-2 S protein template through boronate ester bonds. After that, 3-aminophenylboronic acid (3-APBA) is electropolymerized on the electrode surface and used as the molecularly imprinted polymers (MIPs). The SMI electrochemical biosensor is obtained after the elution of the SARS-CoV-2 S protein template with an acidic solution by the dissociation of the boronate ester bonds, which can be utilized for sensitive detection of the SARS-CoV-2 S protein. The developed SMI electrochemical biosensor displays high specificity, reproducibility and stability, which might be a potential and promising candidate for the clinical diagnosis of COVID-19.

Immunoinformatics and Reverse Vaccinology Driven Predication of a Multi-Epitope Vaccine Against Borrelia burgdorferi and Validation Through in silico Cloning and Immune Simulation

Borrelia burgdorferi is regarded as an extremely dangerous bacteria causing infectious disease in humans, resulting in musculoskeletal pain, fatigue, fever and cardiac symptom. Because of all alarming concerns, no such prophylaxis setup has been available against Borrelia burgdorferi till now. In fact, vaccine construction using traditional methods is so expensive and time-consuming. Therefore, considering all concerns, we designed a multi-epitope-based vaccine design against Borrelia burgdorferi using in silico approaches.

METHOD

The present study utilized different computational methodologies, covering different ideas and elements in bioinformatics tools. The protein sequence of Borrelia burgdorferi was retrieved from the NCBI database. Different B and T cell epitopes were predicated using the IEDB tool. Efficient B and T cell epitopes were further assessed for vaccine construction using linkers AAY, EAAAK and GPGPG, respectively. Furthermore, the tertiary structure of constructed vaccine was predicated, and its interaction was determined with TLR9 using ClusPro software. In addition, further atomic level detail of docked complex and their immune response were further determined by MD simulation and C-ImmSim tool, respectively.

RESULT

A protein with immunogenic potential and good vaccine properties (candidate) was identified based on high binding scores, low percentile rank, non-allergenicity and good immunological properties, which were further used to calculate epitopes. Additionally, molecular docking possesses strong interaction; seventeen H- bonds interactions were reported, such as THR101-GLU264, THR185-THR270, ARG 257-ASP210, ARG 257-ASP 210, ASP259-LYS 174, ASN263-GLU237, CYS 265- GLU 233, CYS 265-TYR 197, GLU267-THR202, GLN 270- THR202, TYR345-ASP 210, TYR345-THR 213, ARG 346-ASN209, SER350-GLU141, SER350-GLU141, ASP 424-ARG220 and ARG426-THR216 with TLR-9. Finally, high expression was determined in E. coli (CAI = (0.9045), and GC content = (72%). Using the IMOD server, all-atom MD simulations of docked complex affirmed its significant stability. The outcomes of immune simulation indicate that both T and B cells represent a strong response to the vaccination component.

CONCLUSION

This type of in-silico technique may precisely decrease valuable time and expenses in vaccine designing against Borrelia burgdorferi for experimental planning in laboratories. Currently, scientists frequently utilize bioinformatics approaches that speed up their vaccine-based lab work.

In silico Mutagenesis and Modeling of Decoy Peptides Targeting CIB1 to Obscure its Role in Triple-negative Breast Cancer Progression

BACKGROUND

Cancer is recognized globally as the second-most dominating and leading cause of morbidities. Breast cancer is the most often diagnosed disease in women and one of the leading causes of cancer mortality. In women, 287,850, and in males, 2710 cases were reported in 2022. Approximately 10-20% of all new cases of breast cancer diagnosed in the United States in 2017 were triple-negative breast cancers (TNBCs), which lack the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).

OBJECTIVE

This study aims to adopt different strategies for targeting calcium integrin-binding protein 1 by computer- aided drug design methods. Our results showed that the top four selected peptides interact with CIB1 more strongly than the reference peptide and restore normal cell function by engaging CIB1. Our binding affinity analyses explore an innovative approach to planning a new peptide to inhibit triple-negative breast cancer.

METHODS

Molecular dynamic simulation of the CIB1-UNC10245092 interaction highlights the potential peptide inhibitors through in-silico mutagenesis and designs novel peptide inhibitors from the reference peptide (UNC10245092) through residue scan methodology.

RESULTS

The top four designed peptides (based on binding free energy) were subjected to molecular dynamics simulations using AMBER to evaluate stability.

CONCLUSION

Our results indicate that among the top five selected peptides, the mutant 2nd mutants have more potential to inhibit CIB1 than the reference peptide (UNC10245092) and have the potency to prevent or restore the tumor suppressor function of UNC10245092.

Fabrication of Super-Sized Metal Inorganic-Organic Hybrid Glass with Supramolecular Network via Crystallization-Suppressing Approach

Metal coordination compound (MCC) glasses [e.g., metal-organic framework (MOF) glass, coordination polymer glass, and metal inorganic-organic complex (MIOC) glass] are emerging members of the hybrid glass family. So far, a limited number of crystalline MCCs can be converted into glasses by melt-quenching. Here, we report a universal wet-chemistry method, by which the super-sized supramolecular MIOC glasses can be synthesized from non-meltable MOFs. Alcohol and acid were used as agents to inhibit crystallization. The MIOC glasses demonstrate unique features including high transparency, shaping capability, and anisotropic network. Directional photoluminescence with a large polarization ratio (≈47 %) was observed from samples doped with organic dyes. This crystallization-suppressing approach enables fabrication of super-sized MCC glasses, which cannot be achieved by conventional vitrification methods, and thus allows for exploring new MCC glasses possessing photonic functionalities.

In Silico Identification of Lead Compounds for Pseudomonas Aeruginosa PqsA Enzyme: Computational Study to Block Biofilm Formation

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium implicated in acute and chronic nosocomial infections and a leading cause of patient mortality. Pseudomonas aeruginosa infections are frequently associated with the development of biofilms, which give the bacteria additional drug resistance and increase their virulence. The goal of this study was to find strong compounds that block the Anthranilate-CoA ligase enzyme made by the pqsA gene. This would stop the P. aeruginosa quorum signaling system. This enzyme plays a crucial role in the pathogenicity of P. aeruginosa by producing autoinducers for cell-to-cell communication that lead to the production of biofilms. Pharmacophore-based virtual screening was carried out utilizing a library of commercially accessible enzyme inhibitors. The most promising hits obtained during virtual screening were put through molecular docking with the help of MOE. The virtual screening yielded 7/160 and 10/249 hits (ZINC and Chembridge). Finally, 2/7 ZINC hits and 2/10 ChemBridge hits were selected as potent lead compounds employing diverse scaffolds due to their high pqsA enzyme binding affinity. The results of the pharmacophore-based virtual screening were subsequently verified using a molecular dynamic simulation-based study (MDS). Using MDS and post-MDS, the stability of the complexes was evaluated. The most promising lead compounds exhibited a high binding affinity towards protein-binding pocket and interacted with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

[Correlation analysis and benchmark dose study on bone metabolic biochemical index of low doses of exposed hydrogen fluoride workers]

Objective: To analyze correlation of occupational hydrogen fluoride exposure to low doses of bone metabolism index through occupational epidemiological investigation and benchmark dose calculation. Methods: In May 2021, using cluster sampling method, 237 workers exposed to hydrogen fluoride in a company were selected as the contact group, and 83 workers not exposed to hydrogen fluoride in an electronics production company were selected as the control group. The external exposure dose and urinary fluoride concentration, blood and urine biochemical indicators of the workers was measured.The relationship between external dose and internal dose of hydrogen fluoride was analyzed. The external dose, urinary fluoride was used as exposure biomarkers, while serum osteocalcin (BGP), serum alkaline phosphatase (AKP) and urinary hydroxyproline (HYP) were used as effect biomarkers for bone metabolism of hydrogen fluoride exposure. The benchmark dose calculation software (BMDS1.3.2) was used to calculate benchmark dose (BMD) . Results: Urine fluoride concentration in the contact group was correlated with creatinine-adjusted urine fluoride concentration (r=0.69, P=0.001). There was no significant correlation between the external dose of hydrogen fluoride and urine fluoride in the contact group (r=0.03, P=0.132). The concentrations of urine fluoride in the contact group and the control group were (0.81±0.61) and (0.45±0.14) mg/L, respectively, and the difference between the two groups was statistically significant (t=5.01, P=0.025). Using BGP, AKP and HYP as effect indexes, the urinary BMDL-05 values were 1.28, 1.47 and 1.08 mg/L, respectively. Conclusion: Urinary fluoride can sensitively reflect the changes in the effect indexes of biochemical indexes of bone metabolism. BGP and HYP can be used as early sensitive effect indexes of occupational hydrogen fluoride exposure.

Biocatalytic synthesis of chiral five-membered carbasugars intermediates utilizing CV2025 ω-transaminase from Chromobacterium violaceum

(S)-4-(Hydroxymethyl)cyclopent-2-enone is a key intermediate in the synthesis of chiral five-membered carbasugars, which can be used to synthesize a large number of pharmacologically relevant carbocyclic nucleosides. Herein, CV2025 ω-transaminase from Chromobacterium violaceum was selected based on substrate similarity to convert ((1S,4R)-4-aminocyclopent-2-enyl)methanol to (S)-4-(hydroxymethyl)cyclopent-2-enone. The enzyme was successfully cloned, expressed in Escherichia coli, purified and characterized. We show that it has R configuration preference in contrast with the conventional S preference. The highest activity was obtained below 60 °C and at pH 7.5. Cations Ca²⁺ and K⁺ enhanced activity by 21% and 13%, respectively. The conversion rate reached 72.4% within 60 min at 50 °C, pH 7.5, using 0.5 mM pyridoxal-5'-phosphate, 0.6 μM CV2025, and 10 mM substrate. The present study provides a promising strategy for preparing five-membered carbasugars economically and efficiently.

Molecularly imprinted miniature electrochemical biosensor for SARS-CoV-2 spike protein based on Au nanoparticles and reduced graphene oxide modified acupuncture needle

Accurate detection of SARS-CoV-2 spike (SARS-CoV-2-S) protein is of clinical significance for early diagnosis and timely treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, a surface molecularly imprinted miniature biosensor was fabricated. Au nanoparticles (AuNPs), reduced graphene oxide (rGO), poly(methylene blue)/poly(ionic liquids) and poly(ionic liquids) were successively electrodeposited onto the pinpoint of an acupuncture needle (AN). The molecularly imprinted miniature biosensor was obtained after the template of SARS-CoV-2-S protein was removed, which could be used for sensitive detection of SARS-CoV-2-S protein. The linear range and limit of detection (LOD) were 0.1 ∼ 1000 ng mL^-1 and 38 pg mL^-1, respectively, which were superior to other molecularly imprinted biosensors previously reported. The developed miniature biosensor also exhibited high specificity and stability. The reliability of the biosensor was evaluated by the detection of SARS-CoV-2-S protein in clinical serum samples.

The association between dietary selenium intake and Hashimoto's thyroiditis among US adults: National Health and Nutrition Examination Survey (NHANES), 2007-2012

BACKGROUND

Selenium has been shown to influence the pathological processes and physiological functions of thyroid. Although growing evidence has shown that selenium can improve the treatment of Hashimoto's thyroiditis (HT), there is a need to evaluate the association between dietary selenium intake and HT in a large cross-sectional study. This study explored the association between dietary selenium intake and HT based on the National Health reand Nutrition Examination Survey (NHANES) database (2007-2012).

METHODS

A total of 8756 of 30,442 participants were included in the study. Dietary selenium intake was the independent variable, while HT was the dependent variable. In addition, the relative importance of the selected variables was determined using the XGBoost model. A smooth curve was constructed based on the fully adjusted model to investigate the potential linear relationship between dietary selenium intake and HT. Smooth curves were also constructed to explore the linear/non-linear relationship between dietary selenium intake and thyroid peroxidase antibody (TPOAb)/ thyroglobulin antibody (TgAb).

RESULTS

The mean age of the enrolled participants was 44.35 years (± 20.92). The risk of HT was significantly reduced by a 35% per-unit increase in dietary selenium intake after fully adjusting for covariates according to the model (log2-transformed data; OR 0.65; 95% CI 0.51, 0.83). The XGBoost model revealed that dietary selenium intake was the most important variable associated with Hashimoto's thyroiditis. Dietary selenium intake (Log2-transformed) was negatively correlated with TPOAb levels [- 16.42 (- 22.18, - 10.65), P < 0.0001], while a non-linear relationship was observed between dietary selenium intake and TgAb with an inflection point of 6.58 (95.67 μg, Log2-transformed).

CONCLUSION

Dietary selenium intake is independently and inversely associated with HT risk. Moreover, dietary selenium intake is negatively correlated with TPOAb levels and non-linearly correlated with TGAb levels. Therefore, dietary selenium intake may be a safe and low-cost alternative for the prevention and treatment of HT.

Fabrication of manganese-coordinated polyphenol carbon dots for photothermal therapy and immune activation

Background

Nanoparticle-based photothermal therapy (PTT) is capable of inducing immunogenic cell death (ICD) and eradicating local tumor via hyperthermia. However, it can hardly prevent tumor recurrence and metastasis owing to inadequate immune activation.

Results

To this end, manganese-coordinated polyphenol carbon dots (MP-CDs) were synthesized by hydrothermal carbonization and metal–polyphenol coordination. This prepared MP-CDs had ultra-small particle size of 5 nm, excellent optical performance, good dispersibility in water and favorable biocompatibility. Under 808 nm near-infrared laser irradiation, the MP-CDs with high photothermal conversion efficiency could kill tumor cells and induce the release of damage-associated molecular patterns (DAMPs) from tumor cells. Notably, the MP-CDs can promote the maturation and antigen presentation ability of dendritic cells (DCs) via manganese-mediated immune activation.

Conclusion

The present work offers a versatile strategy to integrate functional metal into CDs via metal–polyphenol coordination for photothermal/immune therapy.

[A multicenter epidemiological study of acute bacterial meningitis in children]

Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ²=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.

Biosynthesis of plant hemostatic dencichine in Escherichia coli

Dencichine is a plant-derived nature product that has found various pharmacological applications. Currently, its natural biosynthetic pathway is still elusive, posing challenge to its heterologous biosynthesis. In this work, we design artificial pathways through retro-biosynthesis approaches and achieve de novo production of dencichine. First, biosynthesis of the two direct precursors L-2, 3-diaminopropionate and oxalyl-CoA is achieved by screening and integrating microbial enzymes. Second, the solubility of dencichine synthase, which is the last and only plant-derived pathway enzyme, is significantly improved by introducing 28 synonymous rare codons into the codon-optimized gene to slow down its translation rate. Last, the metabolic network is systematically engineered to direct the carbon flux to dencichine production, and the final titer reaches 1.29 g L-1 with a yield of 0.28 g g-1 glycerol. This work lays the foundation for sustainable production of dencichine and represents an example of how synthetic biology can be harnessed to generate unnatural pathways to produce a desired molecule.

Dual-template molecularly imprinted electrochemical biosensor for IgG-IgM combined assay based on a dual-signal strategy

Detection of immunoglobulins (Igs) is of clinical significance for early diagnosis and timely treatment of diseases. Herein, a dual-template molecularly imprinted (DTMI) electrochemical biosensor was developed for IgG-IgM combined assay. In this DTMI electrochemical biosensor, Prussian blue (PB) and thionine (TH) decorated on graphene oxide (GO) and multi-walled carbon nanotubes (MWCNTs), respectively, were utilized as the dual-signal probes, and Au nanoparticles (AuNPs) were used for Igs anchoring and signal amplification. Polypyrrole (PPy) was electrodeposited on the biosensor surface and acted as the molecularly imprinted polymers (MIPs). After the removal of the IgG and IgM templates, the resultant DTMI electrochemical biosensor was used for IgG-IgM combined assay, and the concentrations of IgG and IgM could be indicated by the changes in the peak currents of PB (ΔI_PB) and TH (ΔI_TH), respectively. The DTMI electrochemical biosensor displayed a wide linear range and a low limit of detection (LOD) for both IgG (28.80 pg mL^-1) and IgM (0.58 pg mL^-1). Finally, the developed DTMI biosensor was used for IgG-IgM combined assay in clinical serum samples, and the results were comparable to those obtained by conventional immunoturbidimetry, implying its great potential in clinical diagnosis.

Construction and validation of a predictive model for hepatocellular carcinoma based on serum markers

Background

Early hepatocellular carcinoma (HCC) detection with non-invasive biomarkers remains an unmet clinical need. We aimed to construct a predictive model based on the pre-diagnostic levels of serum markers to predict the early-stage onset of HCC.

Methods

A total of 339 HCC patients (including 157 patients from Changzhou cohort and 182 patients from Wuxi cohort) were enrolled in our retrospective study. Levels of 25 baseline serum markers were collected. Propensity score matching (PSM) analysis was conducted to balance the distributions of patients’ gender, age, and the surveillance time between HCC group and control group. Then, Receiver operating characteristic (ROC) and Logistic regression analysis were performed to screen the independent predictive variables and construct a non-invasive predictive model. Subsequently, ROC curve and Kaplan–Meier (K–M) curve were used to evaluate the predictive values of the model. Clinical net benefit of the model was demonstrated by decision curve analysis (DCA) and clinical impact curve.

Results

Five independent predictive variables for HCC onset and two general characteristics of patients (age and gender) were incorporated into the score model. ROC and DCA curves showed that the score model had better predictive performance in discrimination and clinical net benefit compared with single variable or other score systems, with the area under the curve (AUC) of 0.890 (95% CI 0.856–0.925) in Changzhou cohort and 0.799 (95% CI 0.751–0.849) in Wuxi cohort. Meanwhile, stratification analysis indicated that the score model had good predictive values for patients with early tumor stage (AJCC stage I) or small tumors (< 2 cm). Moreover, the score of HCC patient began to increase at 30 months before clinical diagnosis and reach a peak at 6 months.

Conclusion

Based on this model, we could optimize the current risk stratification at an early stage and consider further intensive surveillance programs for high-risk patients. It could also help clinicians to evaluate the progression and predict the prognosis of HCC patients.

SARS-CoV-2 omicron variant clearance delayed in breakthrough cases with elevated fasting blood glucose

Background

Omicron variant (B.1.1.529) is a dominant variant worldwide. However, the risk factors for Omicron variant clearance are yet unknown. The present study aimed to investigate the risk factors for early viral clearance of Omicron variant in patients with a history of inactivated vaccine injection.

Methods

Demographic, clinical, and epidemiological data from 187 patients were collected retrospectively during the Omicron variant wave.

Results

73/187 and 114/187 patients were administered two and three doses of vaccine, respectively. The median duration of SARS-CoV-2 RNA positivity was 9 days, and the difference between patients with two and three vaccine injections was insignificant (P = 0.722). Fever was the most common symptom (125/187), and most patients (98.4%) had a fever for < 7 days. The RNA was undetectable in 65/187 patients on day 7. Univariable logistic analysis showed that baseline glucose, uric acid, lymphocytes count, platelet count, and CD4⁺ T lymphocyte count were associated with SARS-CoV-2 RNA-positivity on day 7. Multivariable analysis showed that glucose ≥ 6.1 mmol/L and CD4⁺T lymphocytes count were independent risk factors for RNA positivity on day 7. 163/187 patients had an undetectable RNA test on day 14, and uric acid was the only independent risk factor for RNA positivity. Moreover, baseline glucose was negatively correlated with uric acid and CD4⁺ and CD8⁺ T cell count, while uric acid was positively correlated with CD4⁺ and CD8⁺ T cell count.

Conclusions

Omicron variant clearance was delayed in breakthrough cases with elevated fasting blood glucose, irrespective of the doses of inactivated vaccine.

Efficient Synthesis of the Key Intermediate of Scopolamine by [4+3] Cycloaddition Reaction

Abstract:

Scopolamine, as an anticholinergic agent, plays a regulatory role in the peripheral nervous system. In this paper, 6,7-dehydrotropinone which is the key intermediate of scopolamine was synthesized in moderate yield through [4+3] cyclization reaction and Barton deoxygenation reaction. This route has good application prospects with mild reaction conditions, moderate yield and simple operation procedures.

[Analysis of the effectiveness of coracoid osteotomy and concentric coaxial reconstruction of the glenoid cavity in the treatment of recurrent anterior dislocation of the shoulder joint]

Objective: To investigate the clinical efficacy of the modified Latarjet procedure in the treatment of recurrent anterior subluxation of the shoulder by "coaxial co-arc" reconstruction of the glenoid cavity. Methods: The clinical data of 103 cases (106 shoulders) of recurrent anterior dislocation of the shoulder admitted to the First Affiliated Hospital of the Army Military Medical University from January 2005 to December 2020 were retrospectively studied. Out of these cases, 84 were males and 19 were females; 31 with left-sided injuries while 75 with right-sided injuries, with a mean age of (29.4±11.5) years (16-61 years). The preoperative anterior fear test was positive, and a modified Latarjet procedure was used to reconstruct the shoulder glenoid defect through a "coaxial co-arc". The Rowe score, simple shoulder test (SST) score, and Visual analogue scale (VAS) score of pain were used to assess the shoulder's function. Parameters such as the postoperative shoulder recurrent dislocation rate, shoulder body external rotation angle, and subscapularis muscle strength changes were recorded postoperatively. Moreover, radiographs and CT scans were used to check for the incidence of osteoarthritis (Samson-Prieto score). Results: After a mean follow-up of 9.0 years (1 to 16 years), bony healing occurred 3 to 6 months postoperatively. The Rowe score improved from 40.4±6.5 preoperatively to 93.2±2.5 (P<0.001), the SST score improved from 5.2±1.3 preoperatively to 10.1±1.5 (P<0.001), and the VAS pain score decreased from 3.5±1.9 preoperatively to 1.1±1.2 (P<0.001) at the final follow-up. The angle of lateral external rotation of the shoulder joint was 58.8°±15.6° preoperatively and 57.6°±14.5° postoperatively with no statistically significant difference (P>0.05). There was no statistically significant difference in the measurement of subscapularis muscle strength between the healthy side and the affected side (P>0.05). In 89.6% of patients after surgery, coaxial co-arc reconstruction of the shoulder glenoid was obtained, and the shoulder glenoid defect and postoperative inclusion angle were significantly improved compared with those before surgery (P<0.001). Postoperatively, new-onset osteoarthritis developed in 7 cases (7/98), arthritis progressed in 2 cases (2/8), incisional healing was poor in 2 cases (2/98), and revision surgery was performed in 2 cases (2/98) due to bone mass detachment. Conclusion: Coracoid osteotomy and concentric coaxial reconstruction of the glenoid cavity elicits adequate good clinical efficacy for cases of recurrent anterior shoulder dislocation, with low recurrence rates, low revision rates and low incidence of osteoarthritis.

Strategies for targeting CIB1, a challenging drug target

Breast cancer is common malignancy in women which is diverse disease. In women, 287,850 and in male 2710 cases are reported in 2022 reported by WHO. Triple negative breast cancer (TNBC), a subtype of breast cancer that lacks expression of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), accounted for 10-20% of all new cases discovered in the United States in 2017. Because calcium integrin-binding protein1 lacks a suitable pocket that could be used to create a chemical inhibitor, and because the breast cancer-causing protein is nearly identical to its necessary wild-type counterpart, it was thought to be druggable. The structure and function of the newly discovered calcium integrin-binding protein1 have been improved, paving the way for the designing of several therapeutic candidates. Currently, no FDA-approved drugs are available for CIB1-driven cancer. CIB1 has proven to challenging drug target due to several factors, including the fact that the CIB1 protein is highly resistant to small inhibitors. This study aimed to present various ways for targeting calcium integrin-binding protein1, which is an important target that could be useful to scientists.

In silico designing of a multi-epitope vaccine against Burkholderia pseudomallei: reverse vaccinology and immunoinformatics

BACKGROUND

Burkholderia pseudomallei is an infectious agent causing severe disease melioidosis resulting in pneumonia, fever, and acute septicemia in humans. B. pseudomallei show resistance to drugs. No such FDA-approved vaccine is available against B. pseudomallei, and treatment is limited to therapy. Therefore, the scientific study was designed to develop a vaccine for B. pseudomallei. The protein sequence of B. pseudomallei was retrieved from NCBI. B-cell and T-cell epitopes were identified and further screened for allergenicity, antigenicity docking, and simulation.

RESULTS

Here, in this study, in silico approach was applied to design a multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of proteins considered to be potential novel vaccine candidates. Peptide epitopes were joined by adjuvant and EAAAK, CPGPG, and AAY linkers. This constructed vaccine was subjected to in silico immune simulations by C-ImmSim. The protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using SnapGene.

CONCLUSION

The designed multi-epitope vaccine was analyzed for its physicochemical, structural, and immunological characteristics, and it was found to be antigenic, soluble, stable, nonallergenic, and have a high affinity to its target receptor. The immune simulation studies were carried out on the C-ImmSim showing increased production of cellular and humoral responses indicating that the constructed vaccine proved effective and able to provoke humoral and cell-mediated response immune responses. In silico study could be a breakthrough in designing effective vaccines to eradicate B. pseudomallei globally.

Design and synthesis of cinnamic acid triptolide ester derivatives as potent antitumor agents and their biological evaluation

A series of novel cinnamic acid triptolide ester derivatives were synthesized, and their growth inhibitory properties against human hepatoma HepG2 cells were assessed as the measure of cytotoxicity with triptolide as the positive control. One of the phenolic hydroxyl phosphorylated products, CL20 was found to possess the best cytotoxicity and surpassed the parent natural triptolide, suggesting that compound CL20 is a promising antitumor lead compound and deserves further research of pharmacological activity. In addition, the structure-activity relationship for these compounds was also investigated.

Design, synthesis, and bioactivity evaluation of macrocyclic benzo[b]pyrido[4,3-e][1,4]oxazine derivatives as novel Pim-1 kinase inhibitors

Pim-1 kinase is a serine/threonine kinase which is vital in many tumors. The Pim-1 inhibitor 10-DEBC and its derivatives discovered in our previous work were modified through macrocyclization strategy. A series of benzo[b]pyridine[4,3-e][1,4]oxazine macrocyclic compounds were designed, synthesized, and evaluated as novel Pim-1 kinase inhibitors. Among these compounds, compound H5 exhibited the highest activity with an IC₅₀ value of 35 nM. In addition, the crystal complex structure of Pim-1 kinase bound with compound H3 was determined, and the structure-activity relationship of these macrocyclic compounds was analyzed, which provides the structural basis of further optimization of novel macrocyclic Pim-1 kinase inhibitors..

Discovery and Characterization of Rubrinodin Provide Clues into the Evolution of Lasso Peptides

Lasso peptides are unique natural products that comprise a class of ribosomally synthesized and post-translationally modified peptides. Their defining three-dimensional structure is a lariat knot, in which the C-terminal tail is threaded through a macrolactam ring formed between the N-terminal amino group and an Asp or Glu side chain (i.e., an isopeptide bond). Recent genome mining strategies have revealed various types of lasso peptide biosynthetic gene clusters and have thus redefined the known chemical space of lasso peptides. To date, over 20 different types of these gene clusters have been discovered, including several different clades from Proteobacteria. Despite the diverse architectures of these gene clusters, which may or may not encode various tailoring enzymes, most currently known lasso peptides are synthesized by two discrete clades defined by the presence of an ATP-binding cassette transporter or its absence and (sometimes) concurrent appearance of an isopeptidase, raising questions about their evolutionary history. Herein, we discovered and characterized the lasso peptide rubrinodin, which is assembled by a gene cluster encoding both an ATP-binding cassette transporter and an isopeptidase. Our bioinformatics analyses of this and other representative cluster types provided new clues into the evolutionary history of lasso peptides. Furthermore, our structural and biochemical investigations of rubrinodin permitted the conversion of this thermolabile lasso peptide into a more thermostable scaffold.

Glass-Crystallized Luminescence Translucent Ceramics toward High-Performance Broadband NIR LEDs

Near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) are newly emergent broadband light sources for miniaturizing optical systems like spectrometers. However, traditional converters with NIR phosphors encapsulated by organic resins suffer from low external quantum efficiency (EQE), strong thermal quenching as well as low thermal conductivity, thus limiting the device efficiency and output power. Through pressureless crystallization from the designed aluminosilicate glasses, here broadband Near-infrared (NIR) emitting translucent ceramics are developed with high EQE (59.5%) and excellent thermal stability (<10% intensity loss and negligible variation of emission profile at 150 °C) to serve as all-inorganic visible-to-NIR converters. A high-performance NIR phosphor-converted light emitting diodes is further demonstrated with a record NIR photoelectric efficiency (output power) of 21.2% (62.6 mW) at 100 mA and a luminescence saturation threshold up to 184 W cm^-2 . The results can substantially expand the applications of pc-LEDs, and may open up new opportunity to design efficient broadband emitting materials.

Boosting Continuous-Wave Laser-Driven Nonlinear Photothermal White Light Generation by Nanoscale Porosity

The irradiation of an optically absorptive medium by a continuous-wave (CW) near-infrared (NIR) laser can result in a spectral continuum emission covering both the visible and NIR regions, which is attractive for applications as continuum light sources in diverse fields. It is shown here that this NIR-laser-driven light emission can be effectively modulated with nanoscale architecture in the medium. By using porous silica as the model matrix and Yb³⁺ ions as the photothermally active centers, up to 100 folds increment in NIR-laser-induced emission intensity and dramatic decrease in threshold excitation density are demonstrated. It is observed that the emission intensity exhibits a strong nonlinear dependence on the power of the NIR excitation laser, featuring clear excitation power thresholds. Based on combined numerical simulation and spectral and temperature measurements, the improved broadband emission and photothermal nonlinearity are interpreted by enhanced optical energy localization around the laser spot that results in boosting the photon-to-photon conversion efficiency. The use of the nonlinear photothermal emission process as a broadband NIR light source, which could be exploited for applications including NIR spectroscopy, imaging, and sensing, is further demonstrated as a proof-of-concept.