The Naples prognostic score serves as a predictor and prognostic indicator for cancer survivors in the community.

OBJECTIVE: Inflammation, malnutrition, and cancer are intricately interconnected. Despite this, only a few studies have delved into the relationship between inflammatory malnutrition and the risk of death among cancer survivors. This study aimed to specifically investigate the association between the categorically defined Naples prognostic score (NPS) and the prognosis of cancer survivors. METHODS: Data from 42,582 participants in the National Health and Nutrition Examination Survey (NHANES, 1999-2018) were subjected to analysis. Naples prognostic scores (NPS) were computed based on serum albumin (ALB), total cholesterol (TC), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR), and participants were stratified into three groups accordingly. Cancer status was ascertained through a self-administered questionnaire, while mortality data were sourced from the National Death Index up to December 31, 2019. Multiple logistic regression was employed to estimate the odds ratio (OR) with a 95% confidence interval (CI) between NPS and cancer prevalence within the U.S. community population. Kaplan-Meier survival analysis and the Log-rank test were utilized to compare survival disparities among the three groups. Additionally, Cox proportional regression was utilized to estimate the hazard ratio (HR) with a 95% CI. RESULTS: The incidence of cancers was 9.86%. Among the participants, 8140 individuals (19.1%) were classified into Group 0 (NPS 0), 29,433 participants (69.1%) into Group 1 (NPS 1 or 2), and 5009 participants (11.8%) into Group 2 (NPS 3 or 4). After adjusting for confounding factors, the cancer prevalence for the highest NPS score yielded an odds ratio (OR) of 1.64 (95% CI: 1.36, 1.97) (P(for trend) < 0.05). In comparison to cancer survivors in Group 0, those with the highest NPS had adjusted hazard ratios (HRs) of 2.57 (95% CI: 1.73, 3.84) for all-cause mortality, 3.44 (95% CI: 1.64, 7.21) for cardiovascular mortality, 1.60 (95% CI: 1.01, 2.56) for cancer mortality, and 3.15 (95% CI: 1.74, 5.69) for other causes of mortality (All P(for trend) < 0.05). These associations remained consistent when stratified by age, sex, race, and body mass index. CONCLUSIONS: This study indicates that the Naples prognostic score (NPS), serving as a novel prognostic metric integrating inflammation and nutritional status, is closely linked to cancer prognosis within the general population.

Genome mining integrating semi-rational protein engineering and nanoreactor design: roadmap for a robust biocatalyst for industrial resolution of Vince lactam.

Biomanufacturing of chemicals using biocatalysts is an attractive strategy for the production of valuable pharmaceuticals since it is usually more economical and has a much-reduced environmental impact. However, there are often challenges such as their thermal instability that should be overcome before a newly discovered enzyme is eventually translated into industrial processes. In this work, we describe a roadmap for the development of a robust catalyst for industrial resolution of Vince lactam, a key intermediate for the synthesis of carbocyclic-nucleoside-related pharmaceuticals. By a genome mining strategy, a new (+)-γ-lactamase (MiteL) from Microbacterium testaceum was successfully discovered and biochemically characterized. In vitro studies showed that the enzyme exhibited high activity but poor enantioselectivity (E = 6.3 ± 0.2) toward racemic Vince lactam, and thus, it is not suitable for industrial applications. Based on structural modeling and docking studies, a semi-rational engineering strategy combined with an efficient screening method was then applied to improve the enantioselectivity of MiteL. Several mutants with significant shifting stereoselectivity toward (-)-γ-lactam were obtained by site-saturation mutagenesis. Synergy effects led to the final mutant F14D/Q114R/M117L, which enabled efficient acquisition of (-)-γ-lactam with a high E value (> 200). The mutant was biochemically characterized, and the docking studies suggested a plausible mechanism for its improved selectivity. Finally, a sunflower-like nanoreactor was successfully constructed to improve the mutant's robustness via protein supramolecular self-assembly. Thus, the synergism between semi-rational protein engineering and self-assembling immobilization enabled construction of a nanoreactor with superior properties, which can be used for resolution of Vince lactam in large scale.

In search of underlying mechanisms and potential drugs of melphalan-induced vascular toxicity through retinal endothelial cells using bioinformatics approach.

We aimed to explore molecular mechanism and drug candidates of vascular toxicities associated with melphalan after treating human retinal endothelial cells (RECs). GSE34381 microarray data was firstly downloaded and used to identify the differentially expressed genes (DEGs) in human REC treated with melphalan vs. untreated cells by limma package in R language. The transcription network was constructed based on TRANSFAC database and the top five transcription factors (TFs) were select with a measure of regulatory impact factor, followed by the construction of function modules. Gene ontology enrichment analyses were performed to explore the enriched functions. Connectivity Map analysis was conducted to predict the potential drugs overcoming the melphalan's actions on REC. Totally, 75 DEGs were identified, including 70 up-regulated and five down-regulated genes. Transcription network with 1311 nodes and 1875 edges was constructed and the top five TFs were CREM, MYC, FLI1, NF-κB1, and JUN. Functional modules indicated that NF-κB1 and MYC were the important nodes. The upregulated genes as well as the genes involved in the modules mainly participated in biological process of immune response, cell proliferation, and cell motion. Five small molecules were predicted to be potential drug candidates, including doxorubicin, fipexide, daunorubicin, tiabendazole, and GW-8510. Based on these results, we speculate that NF-κB1 and MYC might involve in the molecular mechanism of vascular toxicity induced by melphalan through regulating their target genes. Five small molecules might be drug candidates to overcome the melphalan-induced vascular toxicity via targeting to MYC and JUN.

Crucial microRNAs and genes of human primary breast cancer explored by microRNA-mRNA integrated analysis.

This study aimed to screen potential microRNAs (miRNAs) and genes related to human primary breast cancer. The gene and miRNA expression profile data of GSE19783 was obtained from Gene Expression Omnibus. The matched messenger RNA (mRNA) and miRNA expression profiles of 100 human primary breast cancer samples were chosen for further analysis. The miRNA-gene regulatory modules were screened via iterative multiplicative updating algorithm. The potential functions of genes in modules were predicted by functional and pathway enrichment analysis; meanwhile, the potential functions of miRNAs were predicted by functional enrichment analysis. Furthermore, miRNA-miRNA functional synergistic network and miRNA-miRNA co-regulatory network were constructed. Totally, 16 miRNA-gene modules were screened, containing 222 miRNA-gene interactions. The genes in these modules were mainly related to breast cancer. Genes in module 6 (e.g., SFRP1) were enriched in cell junction assembly; genes in module 8 and 12 (e.g., ESR1 and ERBB4) were significantly implicated in mammary gland alveolus and lobule development. Meanwhile, genes in module 12 (e.g., ERBB4) were enriched in the pathway of endocytosis. Besides, several miRNAs (e.g., miR-375) were enriched in inflammatory cell apoptotic process; some other miRNAs (e.g., miR-139-5p and miR-9) were enriched in response to vitamin D. Additionally, miR-139-5p with several other miRNAs (e.g., miR-9) co-regulated SFRP1; miR-375, miR-592, and miR-135a co-regulated ESR1 and ERBB4. Some miRNAs (e.g., miR-139-5p and miR-9) and their target gene SFRP1, as well as several other miRNAs (e.g., miR-375, miR-592, and miR-135a) and their target genes (e.g., ESR1 and ERBB4), might be crucial in the pathogenesis of primary breast cancer.

Chemoenzymatic synthesis of (1R,3R)-3-hydroxycyclopentanemethanol: An intermediate of carbocyclic-ddA.

The synthesis of carbocyclic-ddA, a potent antiviral agent against hepatitis B, relies significantly on (1R,3R)-3-hydroxycyclopentanemethanol as a key intermediate. To effectively produce this intermediate, our study employed a chemoenzymatic approach. The selection of appropriate biocatalysts was based on substrate similarity, leading us to adopt the CrS enoate reductase derived from Thermus scotoductus SA-01. Additionally, we developed an enzymatic system for NADH regeneration, utilising formate dehydrogenase from Candida boidinii. This system facilitated the efficient catalysis of (S)-4-(hydroxymethyl)cyclopent-2-enone, resulting in the formation of (3R)-3-(hydroxymethyl) cyclopentanone. Furthermore, we successfully cloned, expressed, purified, and characterized the CrS enzyme in Escherichia coli. Optimal reaction conditions were determined, revealing that the highest activity occurred at 45 °C and pH 8.0. By employing 5 mM (S)-4-(hydroxymethyl)cyclopent-2-enone, 0.05 mM FMN, 0.2 mM NADH, 10 µM CrS, 40 µM formic acid dehydrogenase, and 40 mM sodium formate, complete conversion was achieved within 45 min at 35 °C and pH 7.0. Subsequently, (1R,3R)-3-hydroxycyclopentanemethanol was obtained through a simple three-step chemical conversion process. This study not only presents an effective method for synthesizing the crucial intermediate but also highlights the importance of biocatalysts and enzymatic systems in chemoenzymatic synthesis approaches.

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.

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.

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.

Immunoinformatics and Reverse Vaccinology Driven Predication of a Multi-epitope Vaccine against Borrelia burgdorferi and Validation through in silico Cloning and Immune Simulation.

BACKGROUND: 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. OBJECTIVE: To design an effective and safe vaccine that can activate cell-mediated and humoral immunity against Borrelia burgdorferi by using various bioinformatics tools. METHODS: 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. RESULTS: 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.

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.

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.

Comparison of Different Therapeutic Effects of T-MIST for Chronic Idiopathic Tinnitus.

Objective: Tinnitus, as a common clinical symptom, has the characteristics of high incidence and great heterogeneity among different patients. As one of the common treatment strategies for tinnitus, this study is aimed at exploring the factors influencing tinnitus sound therapy and the correlation between different tinnitus acoustic characteristics. Methods: 315 patients with chronic tinnitus were enrolled and divided into three groups according to the tinnitus multielement integration sound therapy (T-MIST): (1) vanishing, (2) remission, and (3) unchanged. The general characteristics, psychoacoustic scores (tinnitus handicap inventory (THI) and visual analog scale (VAS)), residual inhibition (RI), degree of hearing loss, and tinnitus characteristics of each group were compared. Finally, we analyze the predictive significance of different features for acoustic effects. Results: The frequency of tinnitus in the vanishing group was higher than that in the remission and unchanged groups (P < 0.05). There were no differences in age, initial onset time, course of the disease, and VSAD between the vanishing group and the unchanged group (P > 0.05). High-frequency tinnitus may predict the vanishing of tinnitus after treatment (P < 0.05), but the degree of hearing loss, tinnitus characteristics (loudness and frequency), and psychoacoustic score (THI and VAS) were only weakly correlated (P < 0.05). Residual inhibition test (RI) was an independent risk factor for the efficacy of acoustic therapy (P < 0.001). Conclusion: The patients were divided into three groups by T-MIST treatment effect; Kruskal-Wallis test and chi-square test were used to compare the baseline information of each group. Then, we analyzed the correlation between patient characteristics and psychoacoustic scores. Finally, logistic regression was performed to explore predictors that might influence the treatment effect. High-frequency tinnitus may have a better therapeutic effect; age, disease course, and other factors can not be stable explanation factors for a poor therapeutic effect of tinnitus. The residual inhibition (RI) test was an independent factor in predicting the efficacy of T-MIST.

Vulnerable frequency as an independent prognostic factor for sudden sensorineural hearing loss.

Objectives: Sudden sensorineural hearing loss (SSNHL) is a common otology emergency in the practice. Its severe hearing impairment and prognosis impair the quality of life. Given that cochlear hair cell vulnerability is not consistent across frequencies, this study aims to investigate the impact of frequency-specific hearing loss on prognosis in SSNHL. Methods: The study included 255 patients with full-frequency SSNHL. The baseline, clinical, and hearing characteristics, as well as possible cardiovascular predictors in blood, were collected for analysis. Results: The 4,000 and 8,000 Hz hearing levels in the responder group were significantly lower than those in the non-responder group (p = 0.008, p < 0.001), while the average hearing was not (p = 0.081). Logistic regression showed that only vertigo (OR, 95% CI, 0.265, 0.102-0.684, p = 0.006) and 8,000 Hz hearing level (OR, 95% CI, 0.943, 0.916-0.971, p < 0.001) were strongly associated with treatment outcome. Conclusions: Compared with other frequencies, 8,000 Hz hearing level was closely related to prognosis in SSNHL. In an adjusted model, our study did not find an effect of mean hearing on prognosis in SSNHL. However, further multicenter prospective studies are needed for validation.

Calmodulin Bidirectionally Regulates Evoked and Spontaneous Neurotransmitter Release at Retinal Ribbon Synapses.

For decades, a role for the Ca2+-binding protein calmodulin (CaM) in Ca2+-dependent presynaptic modulation of synaptic transmission has been recognized. Here, we investigated the influence of CaM on evoked and spontaneous neurotransmission at rod bipolar (RB) cell→AII amacrine cell synapses in the mouse retina. Our work was motivated by the observations that expression of CaM in RB axon terminals is extremely high and that [Ca2+] in RB terminals normally rises sufficiently to saturate endogenous buffers, making tonic CaM activation likely. Taking advantage of a model in which RBs can be stimulated by expressed channelrhodopsin-2 (ChR2) to avoid dialysis of the presynaptic terminal, we found that inhibition of CaM dramatically decreased evoked release by inhibition of presynaptic Ca channels while at the same time potentiating both Ca2+-dependent and Ca2+-independent spontaneous release. Remarkably, inhibition of myosin light chain kinase (MLCK), but not other CaM-dependent targets, mimicked the effects of CaM inhibition on evoked and spontaneous release. Importantly, initial antagonism of CaM occluded the effect of subsequent inhibition of MLCK on spontaneous release. We conclude that CaM, by acting through MLCK, bidirectionally regulates evoked and spontaneous release at retinal ribbon synapses.

An examination of the regulatory mechanism of Pxdn mutation-induced eye disorders using microarray analysis.

The present study aimed to identify biomarkers for peroxidasin (Pxdn) mutation-induced eye disorders and study the underlying mechanisms involved in this process. The microarray dataset GSE49704 was used, which encompasses 4 mouse samples from embryos with Pxdn mutation and 4 samples from normal tissues. After data preprocessing, the differentially expressed genes (DEGs) between Pxdn mutation and normal tissues were identified using the t-test in the limma package, followed by functional enrichment analysis. The protein-protein interaction (PPI) network was constructed based on the STRING database, and the transcriptional regulatory (TR) network was established using the GeneCodis database. Subsequently, the overlapping DEGs with high degrees in two networks were identified, as well as the sub-network extracted from the TR network. In total, 121 (75 upregulated and 46 downregulated) DEGs were identified, and these DEGs play important roles in biological processes (BPs), including neuron development and differentiation. A PPI network containing 25 nodes such as actin, alpha 1, skeletal muscle (Acta1) and troponin C type 2 (fast) (Tnnc2), and a TR network including 120 nodes were built. By comparing the two networks, seven crucial genes which overlapped were identified, including cyclin­dependent kinase inhibitor 1B (Cdkn1b), Acta1 and troponin T type 3 (Tnnt3). In the sub-network, Cdkn1b was predicted as the target of miRNAs such as mmu-miR-24 and transcription factors (TFs) including forkhead box O4 (FOXO4) and activating enhancer binding protein 4 (AP4). Thus, we suggest that seven crucial genes, including Cdkn1b, Acta1 and Tnnt3, play important roles in the progression of eye disorders such as glaucoma. We suggest that Cdkn1b exert its effects via the inhibition of proliferation and is mediated by mmu-miR-24 and targeted by the TFs FOXO4 and AP4.