Twin drug design, synthesis and evaluation of diosgenin derivatives as multitargeted agents for the treatment of vascular dementia.

A novel series of multitargeted molecules were designed and synthesized by combining the pharmacological role of cholinesterase inhibitor and antioxidant of steroid as potential ligands for the treatment of Vascular Dementia (VD). The oxygen-glucose deprivation (OGD) model was used to evaluate these molecules, among which the most potent compound ML5 showed the highest activity. Firstly, ML5 showed appropriate inhibition of cholinesterases (ChEs) at orally 15 mg/kg in vivo. The further test revealed that ML5 promoted the nuclear translocation of Nrf2. Furthermore, ML5 has significant neuroprotective effect in vivo model of bilateral common carotid artery occlusion (BCCAO), significantly increasing the expression of Nrf2 protein in the cerebral cortex. In the molecular docking research, we predicted the ML5 combined with hAChE and Keap1. Finally, compound ML5 displayed normal oral absorption and it was nontoxic at 500 mg/kg, po, dose. We can draw the conclusion that ML5 could be considered as a new potential compound for VD treatment.

A low-cost and portable fluorometer based on an optical pick-up unit for chlorophyll-a detection.

Chlorophyll-a (Chl-a) fluorescence detection is an important technique for monitoring water quality. In this work, we proposed an approach that employs the mass-produced low-cost optical pick-up unit (OPU) extracted from the high-definition digital versatile disc (HD-DVD) drive as the key optical component for our chlorophyll-a fluorometer. The built-in blue-violet 405 nm laser diode of the OPU acts as the excitation light to perform laser-induced fluorescence (LIF). The laser driver and a series of intrinsic lenses within the OPU, such as an objective lens with a numerical aperture (NA) of 0.65 and a collimating lens, help reduce the size, cost, and system complexity of the fluorometer. By integrating off-the-shelf electronic components, miniaturized optical setups, and 3D-printed assemblies, we have developed a low-cost, easy-to-make, standalone, and portable fluorometer. Finally, we validated the performance of the device for chlorophyll-a fluorescence detection under laboratory and on-site conditions, which demonstrated its great potential in water monitoring applications. The limit of detection (LOD) for chlorophyll-a is 0.35 µg/L, the size of the device is 151 × 100 × 80 mm3, and the total cost of the proposed fluorometer is as low as 137.5 USD. © 2023 Elsevier Science. All rights reserved.

Serum sex hormones correlate with pathological features of papillary thyroid cancer.

PURPOSE: Sex hormones are thought to be responsible for the unique gender differences in papillary thyroid cancer(PTC). Most previous studies on these have focused on the expression of estrogen receptors, or have been limited to animal studies. The aim of our study was to explore the relationship between serum sex hormones and the pathological features of PTC in the clinical setting, as further evidence of the role of sex hormones in PTC. METHODS: Retrospective data analysis of patients who underwent thyroid surgery at the Department of Thyroid Surgery, Nanjing Drum Tower Hospital from January 2022 to September 2022 Correlation between serum sex hormone and pathological features was analyzed in male patients and in menopausal female patients. Serum sex hormones include luteinizing hormone(LH), follicle stimulating hormone(FSH), estradiol(E2), total testosterone(TT), progesterone(P), and prolactin(PRL). Tumor pathological characteristics include the number and size of tumor, presence of extrathyroidal extension(ETE), presence of lymph node metastasis(LNM). RESULTS: Preoperative serum E2 in male patients was positively correlated with tumor size in PTC, LH was negatively correlated with LNM, while TT and P were negatively correlated with ETE. Similar findings were not observed in menopausal female patients. CONCLUSION: We observed that serum sex hormones correlate with the pathological features of PTC in male patients, for the first time in a clinical study. High serum estrogens may be a risk factor for PTC, while androgens are the opposite. This somewhat corroborates previous research and provides new variables for future PTC prediction models.

The development and application of pediatric complicated appendicitis prediction model.

BACKGROUND: Acute appendicitis in children refers to the acute inflammation of the appendix, which accounts for 20% ∼ 30% of cases of acute abdomen in pediatric surgery. OBJECTIVE: This study aimed to establish a decision tree model of complicated appendicitis in children using appendiceal ultrasound combined with an inflammatory index and evaluated its clinical efficacy in pediatric patients. METHODS: A total of 395 children admitted to the Emergency Department of the Shanghai Children's Hospital from January 2018 to December 2021 and diagnosed with appendicitis by postoperative pathology were retrospectively analyzed. According to the postoperative pathology, the children were divided into a complicated and non-complicated appendicitis group, respectively. Routine laboratory inflammatory indicators, including white blood cell count, N(%), neutrophil (Neu) count, Neu/lymphocyte ratio (NLR), C-reactive protein (CRP), and procalcitonin were collected from the two groups. Collecting data on ultrasound examination of the appendix includes whether the appendix diameter is thickened, whether the echogenicity of the mesenteric rim surrounding the appendix is enhanced, whether there is rich blood supply in the appendix, and whether there are fecaliths in the appendix lumen. The risk factors for complicated appendicitis were screened out by univariate and multivariate logistic regression analyses, the binary logistic regression prediction and decision tree models were established, respectively, and the receiver operating characteristic (ROC) curve was used to verify the accuracy of the two prediction models. RESULTS: Binary logistic regression analysis showed that CRP, NLR, the presence of an appendicolith, and peripheral retina echo enhancement were independent risk factors for complicated appendicitis in children (P< 0.05). The decision tree model had an overall accuracy of 79%, an area under the ROC curve (AUC) of 0.809 (95% confidence interval [CI] 0.780-0.865), and sensitivity and specificity of 71.3% and 77.7%, respectively. The logistic regression model had an overall accuracy of 74.9%, an AUC value of 0.823 (95% CI, 0.765-0.853), a sensitivity value of 80.3%, and a specificity of 71.8%. CONCLUSION: This predictive model, based on ultrasound of the appendix combined with inflammatory markers, provides a useful method to assist pediatric emergency physicians in diagnosing childhood appendicitis. The decision tree model reflected the interaction of various indexes, and the model was simple, intuitive, and effective.

Design, synthesis, and biological evaluation of diosgenin-indole derivatives as dual-functional agents for the treatment of Alzheimer's disease.

The complex pathogenesis of Alzheimer's disease (AD) has become a major obstacle in its treatment. An effective approach is to develop multifunctional agents that simultaneously target multiple pathological processes. Here, a series of diosgenin-indole compounds were designed, synthesized and evaluated for their neuroprotective effects against H2O2 (hydrogen peroxide), 6-OHDA (6-hydroxydopamine) and Aß (beta amyloid) damages. Preliminary structure-activities relationship revealed that the introduction of indole fragment and electron-donating group at C-5 on ring indole could be beneficial for neuroprotective activities. Results indicated that compound 5b was the most promising candidate against cellular damage induced by H2O2 (52.9 ± 1.9%), 6-OHDA (38.4 ± 2.4%) and Aß1-42 (54.4 ± 2.7%). Molecular docking study suggested the affinity for 5b bound to Aß1-42 was -40.59 kcal/mol, which revealed the strong binding affinity of 5b to Aß1-42. The predicted values of brain/blood partition coefficient (-0.733) and polar surface area (85.118 Å2) indicated the favorable abilities of BBB permeation and absorption of 5b. In addition, 5b significantly decreased ROS (reactive oxygen species) production induced by H2O2. In the following in vivo experiment, 5b obviously attenuated memory and learning impairments of Aß-injected mice. In summary, compound 5b could be considered as a promising dual-functional neuroprotective agent against AD.

Design, synthesis and evaluation of diosgenin carbamate derivatives as multitarget anti-Alzheimer's disease agents.

In order to produce an effective and multi-targeted clinical drug that could prevent progressive neurodegeneration, a series of diosgenin carbamate derivatives were designed, synthesized and tested for their anti-inflammatory, antioxidant and anti-Aß activities. The results demonstrated that compound M15 was the most promising derivative against inflammatory (NO inhibition 22.7 ± 2.2%,10 µM) and cellular damage induced by H2O2 (SH-SY5Y cell protection = 75.3 ± 3.4%, 10 µM) or Aß (astrocytes protection = 70.2 ± 6.5%, 10 µM). Molecular docking studies revealed the strong binding affinity of M15 to the active site of nNOS, Aß42 and pro-inflammatory proteins. Western blot demonstrated that M15 decreased IL-1ß, IL-6 and TNF-α level, which may contribute to its anti-inflammatory effects. In addition, M15 maintained mitochondrial function as well as cell viability through reducing H2O2-induced ROS production. The results indicated that oral administration of M15 attenuated memory deficits and played a neuroprotective effect on subcutaneous (s.c.) D-gal aging mice. In summary, M15 could be considered as a potential multifunctional neuroprotective agent due to the effects of anti-inflammatory, antioxidant and anti-Aß activities.

[Genetic diversity of starch synthesis genes of Chinese maize (Zea mays L.) with SNAPs].

Analysis of genetic diversity in maize populations is a very important step for understanding genetic structure and subsequently for genetic manipulations in maize breeding. Sh2, Bt2, Sh1, Wx1, Ae1 and Su1 involved in starch biosynthesis are important genes associated with yield and quality traits in maize breeding programs. In this study, genetic diversity of these six genes in 67 Chinese elite maize inbred lines was measured using single-nucleotide amplified polymorphisms (SNAPs). The results indicated that the number of haplotypes of each gene and population was far less than theoretically expected 2(n) (n = the number of the SNAPs). Phenetic clustering analysis showed that the kernel phonetic (semi-) dent and (semi-) flint lines were belong to distinct subclusters based on haplotypes of SNAPs, with a few exceptions. In addition, the genetic origin of these maize inbred lines was associated with the clustered subgroups. Intragenic linkage disequilibrium (LD) was observed in some of the SNAPs in Bt2, Sh1 and Ae1, while intergenic LD was observed in some of the SNAPs in Bt2, Sh1 and Su1. Association study of kernel phenotypes and SNAP haplotypes showed that the (semi-) dent and (semi-) flint lines had the common haplotype of TA and CC at two SNAP sites in Bt2 (Bt2-2 and Bt2-5), respectively. Two haplotypes of ATGT and GTGC at four SNAP sites in Sh1 (Sh1-2, Sh1-3, Sh1-4 and Sh1-5) were associated with temperature and tropical origin of the maize inbred lines, respectively.

MALAT1 promotes angiogenesis of breast cancer.

Metastasis­associated lung adenocarcinoma transcript 1 (MALAT1) is a long non­coding RNA (lncRNA) that has an oncogenic role in some types of cancers, uncluding breast cancer (BC). To investigate the role of MALAT1 in human BC progression, we detected MALAT1 expression levels based on tissue samples from 20 BC cases and 20 healthy controls and found MALAT1 expression levels to be significantly high (P<0.05). Then, we knocked down endogenous MALAT1 in MCF­7 cells using MALAT1 short hairpin RNA (shRNA). The results revealed that MALAT1 knockdown could significantly inhibit proliferation, migration, and tube formation in vitro. In addition, miR­145 expression inversely changed in BC tissue cases. Furthermore, knockdown of endogenous MALAT1 significantly increased miR­145 levels in MCF­7 cells. This finding indicated an interaction between MALAT1 and miR­145. In addition, knockdown of MALAT1 significantly reduced the expression of vascular endothelial growth factor in MCF­7 cells. This outcome revealed that MALAT1 promoted angiogenesis in BC, which may be related to the expression of miR­145.

Microfluidics for rapid detection of isocitrate dehydrogenase 1 mutation for intraoperative application.

OBJECT Conventional methods for isocitrate dehydrogenase 1 (IDH1) detection, such as DNA sequencing and immunohistochemistry, are time- and labor-consuming and cannot be applied for intraoperative analysis. To develop a new approach for rapid analysis of IDH1 mutation from tiny tumor samples, this study used microfluidics as a method for IDH1 mutation detection. METHODS Forty-seven glioma tumor samples were used; IDH1 mutation status was investigated by immunohistochemistry and DNA sequencing. The microfluidic device was fabricated from polydimethylsiloxane following standard soft lithography. The immunoanalysis was conducted in the microfluidic chip. Fluorescence images of the on-chip microcolumn taken by the charge-coupled device camera were collected as the analytical results readout. Fluorescence signals were analyzed by NIS-Elements software to gather detailed information about the IDH1 concentration in the tissue samples. RESULTS DNA sequencing identified IDH1 R132H mutation in 33 of 47 tumor samples. The fluorescence signal for IDH1-mutant samples was 5.49 ± 1.87 compared with 3.90 ± 1.33 for wild type (p = 0.005). Thus, microfluidics was capable of distinguishing IDH1-mutant tumor samples from wild-type samples. When the cutoff value was 4.11, the sensitivity of microfluidics was 87.9% and the specificity was 64.3%. CONCLUSIONS This new approach was capable of analyzing IDH1 mutation status of tiny tissue samples within 30 minutes using intraoperative microsampling. This approach might also be applied for rapid pathological diagnosis of diffuse gliomas, thus guiding personalized resection.

The domain landscape of virus-host interactomes.

Viral infections result in millions of deaths in the world today. A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies. In this study, we presented a landscape of virus-host interactomes based on protein domain interaction. Compared to the analysis at protein level, this domain-domain interactome provided a unique abstraction of protein-protein interactome. Through comparisons among DNA, RNA, and retrotranscribing viruses, we identified a core of human domains, that viruses used to hijack the cellular machinery and evade the immune system, which might be promising antiviral drug targets. We showed that viruses preferentially interacted with host hub and bottleneck domains, and the degree and betweenness centrality among three categories of viruses are significantly different. Further analysis at functional level highlighted that different viruses perturbed the host cellular molecular network by common and unique strategies. Most importantly, we creatively proposed a viral disease network among viral domains, human domains and the corresponding diseases, which uncovered several unknown virus-disease relationships that needed further verification. Overall, it is expected that the findings will help to deeply understand the viral infection and contribute to the development of antiviral therapy.

A comparison of computational methods for identifying virulence factors.

Bacterial pathogens continue to threaten public health worldwide today. Identification of bacterial virulence factors can help to find novel drug/vaccine targets against pathogenicity. It can also help to reveal the mechanisms of the related diseases at the molecular level. With the explosive growth in protein sequences generated in the postgenomic age, it is highly desired to develop computational methods for rapidly and effectively identifying virulence factors according to their sequence information alone. In this study, based on the protein-protein interaction networks from the STRING database, a novel network-based method was proposed for identifying the virulence factors in the proteomes of UPEC 536, UPEC CFT073, P. aeruginosa PAO1, L. pneumophila Philadelphia 1, C. jejuni NCTC 11168 and M. tuberculosis H37Rv. Evaluated on the same benchmark datasets derived from the aforementioned species, the identification accuracies achieved by the network-based method were around 0.9, significantly higher than those by the sequence-based methods such as BLAST, feature selection and VirulentPred. Further analysis showed that the functional associations such as the gene neighborhood and co-occurrence were the primary associations between these virulence factors in the STRING database. The high success rates indicate that the network-based method is quite promising. The novel approach holds high potential for identifying virulence factors in many other various organisms as well because it can be easily extended to identify the virulence factors in many other bacterial species, as long as the relevant significant statistical data are available for them.

Predicting protein oxidation sites with feature selection and analysis approach.

Protein oxidation is a ubiquitous post-translational modification that plays important roles in various physiological and pathological processes. Owing to the fact that protein oxidation can also take place as an experimental artifact or caused by oxygen in the air during the process of sample collection and analysis, and that it is both time-consuming and expensive to determine the protein oxidation sites purely by biochemical experiments, it would be of great benefit to develop in silico methods for rapidly and effectively identifying protein oxidation sites. In this study, we developed a computational method to address this problem. Our method was based on the nearest neighbor algorithm in which, however, the maximum relevance minimum redundancy and incremental feature selection approaches were incorporated. From the initial 735 features, 16 features were selected as the optimal feature set. Of such 16 optimized features, 10 features were associated with the position-specific scoring matrix conservation scores, three with the amino acid factors, one with the propensity of conservation of residues on protein surface, one with the side chain count of carbon atom deviation from mean, and one with the solvent accessibility. It was observed that our prediction model achieved an overall success rate of 75.82%, indicating that it is quite encouraging and promising for practical applications. Also, the 16 optimal features obtained through this study may provide useful clues and insights for in-depth understanding the action mechanism of protein oxidation.

Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.