Application of Natural Medicinal Plants Active Ingredients in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common malignant cancer of the head and neck, with high morbidity and mortality, ranking as the sixth most common cancer in the world. The treatment of OSCC is mainly radiotherapy, chemotherapy and surgery, however, the prognosis of patients is still poor and the recurrence rate is high. This paper reviews the range of effects of natural medicinal plant active ingredients (NMPAIs) on OSCC cancer, including the types of NMPAIs, anti-cancer mechanisms, involved signaling pathways, and clinical trials. The NMPAIs include terpenoids, phenols, flavonoids, glycosides, alkaloids, coumarins, and volatile oils. These active ingredients inhibit proliferation, induce apoptosis and autophagy, inhibit migration and invasion of OSCC cells, and regulate cancer immunity to exert anti-cancer effects. The mechanism involves signaling pathways such as mitogen-activated protein kinase, phosphatidylinositol 3 kinase/protein kinase B, nuclear factor kappa B, miR-22/WNT1/ß-catenin and Nrf2/Keap1. Clinically, NMPAIs can inhibit the growth of OSCC, and the combined drug is more effective. Natural medicinal plants are promising candidates for the treatment of OSCC.

Radiomics on spatial-temporal manifolds via Fokker-Planck dynamics.

BACKGROUND: Delta radiomics is a high-throughput computational technique used to describe quantitative changes in serial, time-series imaging by considering the relative change in radiomic features of images extracted at two distinct time points. Recent work has demonstrated a lack of prognostic signal of radiomic features extracted using this technique. We hypothesize that this lack of signal is due to the fundamental assumptions made when extracting features via delta radiomics, and that other methods should be investigated. PURPOSE: The purpose of this work was to show a proof-of-concept of a new radiomics paradigm for sparse, time-series imaging data, where features are extracted from a spatial-temporal manifold modeling the time evolution between images, and to assess the prognostic value on patients with oropharyngeal cancer (OPC). METHODS: To accomplish this, we developed an algorithm to mathematically describe the relationship between two images acquired at time t = 0 $t = 0$ and t > 0 $t > 0$ . These images serve as boundary conditions of a partial differential equation describing the transition from one image to the other. To solve this equation, we propagate the position and momentum of each voxel according to Fokker-Planck dynamics (i.e., a technique common in statistical mechanics). This transformation is driven by an underlying potential force uniquely determined by the equilibrium image. The solution generates a spatial-temporal manifold (3 spatial dimensions + time) from which we define dynamic radiomic features. First, our approach was numerically verified by stochastically sampling dynamic Gaussian processes of monotonically decreasing noise. The transformation from high to low noise was compared between our Fokker-Planck estimation and simulated ground-truth. To demonstrate feasibility and clinical impact, we applied our approach to 18F-FDG-PET images to estimate early metabolic response of patients (n = 57) undergoing definitive (chemo)radiation for OPC. Images were acquired pre-treatment and 2-weeks intra-treatment (after 20 Gy). Dynamic radiomic features capturing changes in texture and morphology were then extracted. Patients were partitioned into two groups based on similar dynamic radiomic feature expression via k-means clustering and compared by Kaplan-Meier analyses with log-rank tests (p < 0.05). These results were compared to conventional delta radiomics to test the added value of our approach. RESULTS: Numerical results confirmed our technique can recover image noise characteristics given sparse input data as boundary conditions. Our technique was able to model tumor shrinkage and metabolic response. While no delta radiomics features proved prognostic, Kaplan-Meier analyses identified nine significant dynamic radiomic features. The most significant feature was Gray-Level-Size-Zone-Matrix gray-level variance (p = 0.011), which demonstrated prognostic improvement over its corresponding delta radiomic feature (p = 0.722). CONCLUSIONS: We developed, verified, and demonstrated the prognostic value of a novel, physics-based radiomics approach over conventional delta radiomics via data assimilation of quantitative imaging and differential equations.

Propagation of lump-type waves in nonlinear shallow water wave.

In this work, a new extended shallow water wave equation in (3+1) dimensions was studied, which represents abundant physical meaning in a nonlinear shallow water wave. We discussed the interaction between a lump wave and a single solitary wave, which is an inelastic collision. Further, the interaction between a lump wave and two solitary waves and the interaction between a lump wave and a periodic wave was also studied using the Hirota bilinear method. Finally, the interaction among lump, periodic and one solitary wave was investigated. The dynamic properties of the obtained results are shown and analyzed by some three-dimensional images.

MiR-1a-3p Inhibits Apoptosis in Fluoride-exposed LS8 Cells by Targeting Map3k1.

Dental fluorosis is a common chemical disease. It is currently unclear how fluorosis occurs at the molecular level. We used miRNA-seq to look at the differences between miRNAs in the cell line of ameloblasts LS8 that had been treated with 3.2 mmol/L NaF. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. miR-1a-3p levels were significantly lower in mouse LS8 cells treated with 3.2 mmol/L NaF, and miR-1a-3p-targeted genes were significantly enriched in the MAPK pathway. LS8 cells were divided into four groups: control, NaF, NaF+miR-1a-3p mimics, and NaF+miR-1a-3p mimics normal control groups. Cellular morphology was observed by an inverted microscope, and the proliferation activity of LS8 cells was assessed by Cell Counting Kit-8 (CCK-8). Using the real-time quantitative polymerase chain reaction (RT-qPCR), transcription levels of miR-1a-3p and Map3k1 were detected. The expressions of Bax, Bcl-2, Map3k1, p38MAPK, ERK1/2, p-p38MAPK, and p-ERK1/2 were measured by Western blot. After bioinformatics analysis, we used a luciferase reporter assay (LRA) to validate the target of miR-1a-3p, showing that miR-1a-3p could inhibit apoptosis while increasing proliferation in fluoride-exposed LS8 cells. Generally, miR-1a-3p might directly inhibit Map3k1, reduce MAPK signal pathway activation, and promote phosphorylation. Thus, our findings revealed that the interaction of miR-1a-3p with its target gene Map3k1 and MAPK signal pathway might decrease the apoptosis of LS8 cells treated with 3.2 mmol/L NaF.

High-order moment closure models with random batch method for efficient computation of multiscale turbulent systems.

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment equations are closed by a precise calibration of the high-order feedbacks using ensemble solutions of the consistent stochastic equations, suitable for modeling complex phenomena including non-Gaussian statistics and extreme events. To address challenges associated with closely coupled spatiotemporal scales in turbulent states and expensive large ensemble simulation for high-dimensional systems, we introduce efficient computational strategies using the random batch method (RBM). This approach significantly reduces the required ensemble size while accurately capturing essential high-order structures. Only a small batch of small-scale fluctuation modes is used for each time update of the samples, and exact convergence to the full model statistics is ensured through frequent resampling of the batches during time evolution. Furthermore, we develop a reduced-order model to handle systems with really high dimensions by linking the large number of small-scale fluctuation modes to ensemble samples of dominant leading modes. The effectiveness of the proposed models is validated by numerical experiments on the one-layer and two-layer Lorenz '96 systems, which exhibit representative chaotic features and various statistical regimes. The full and reduced-order RBM models demonstrate uniformly high skill in capturing the time evolution of crucial leading-order statistics, non-Gaussian probability distributions, while achieving significantly lower computational cost compared to direct Monte-Carlo approaches. The models provide effective tools for a wide range of real-world applications in prediction, uncertainty quantification, and data assimilation.

Effects of epigallocatechin-3-gallate on oxidative stress, inflammation, and bone loss in a rat periodontitis model.

Background/purpose: Epigallocatechin-3-gallate (EGCG) is playing an increasingly important role in the treatment of oral diseases. However, its mechanisms remain to be clarified. This study aimed to investigate the effect of EGCG on oxidative and inflammatory stress and bone loss in experimental periodontitis. Materials and methods: Periodontitis was induced in rats, followed by gavage using different concentrations of EGCG for 5 weeks. The levels of interleukin-1ß (IL-1ß), interleukin-18 (IL-18), tumor necrosis factor-α (TNF-α), superoxide dismutase (SOD) and malondialdehyde (MDA) in rats were measured. The degree of alveolar bone loss and the number of inflammatory cells were detected. The integrated optical density of nuclear factor erythroid 2-related factor (Nrf2), heme oxygenase-1 (HO-1), NLR pyrin domain-containing 3 (NLRP3) and nuclear factor-kappaB p65 (NF-κB p65) was measured. Results: EGCG (200 mg/kg) significantly reduced alveolar bone loss in the ligated maxillary molars and the number of inflammatory cells in the EGCG-200 group compared with the periodontitis, EGCG-100 and EGCG-400 groups. 200 mg/kg was the optimal dose of EGCG and was used in subsequent experiments. The expression levels of IL-1ß, IL-18, TNF-α and MDA were significantly lower and the expression level of SOD was significantly higher in the EGCG-200 group compared with the periodontitis group. The expression of NLRP3 and NF-κB p65 was significantly decreased, while the expression of Nrf2 and HO-1 was significantly increased in the EGCG-200 group compared with the periodontitis group. Conclusion: These results suggest that EGCG inhibits oxidative stress and inflammatory responses in the periodontitis model by modulating the Nrf2/HO-1/NLRP3/NF-κB p65 signaling pathway, thereby decreasing alveolar bone loss.

Endoscopic Ruler for varix size measurement: A multicenter pilot study.

BACKGROUND: We invented Endoscopic Ruler, a new endoscopic device to measure the size of varices in patients with cirrhosis and portal hypertension. AIM: To assess the feasibility and safety of Endoscopic Ruler, and evaluate the agreement on identifying large oesophageal varices (OV) between Endoscopic Ruler and the endoscopists, as well as the interobserver agreement on diagnosing large OV using Endoscopic Ruler. METHODS: We prospectively and consecutively enrolled patients with cirrhosis from 11 hospitals, all of whom got esophagogastroduodenoscopy (EGD) with Endoscopic Ruler. The primary study outcome was a successful measurement of the size of varices using Endoscopic Ruler. The secondary outcomes included adverse events, operation time, the agreement of identifying large OV between the objective measurement of Endoscopic Ruler and the empirical reading of endoscopists, together with the interobserver agreement on diagnosing large OV by Endoscopic Ruler. RESULTS: From November 2020 to April 2022, a total of 120 eligible patients with cirrhosis were recruited and all of them underwent EGD examinations with Endoscopic Ruler successfully without any adverse event. The median operation time of Endoscopic Ruler was 3.00 min [interquartile range (IQR): 3.00 min]. The kappa value between Endoscopic Ruler and the endoscopists while detecting large OV was 0.52, demonstrating a moderate agreement. The kappa value for diagnosing large OV using Endoscopic Ruler among the six independent observers was 0.77, demonstrating a substantial agreement. CONCLUSION: The data demonstrates that Endoscopic Ruler is feasible and safe for measuring the size of varices in patients with cirrhosis and portal hypertension. Endoscopic Ruler is potential to promote the clinical practice of the two-grade classification system of OV.

Heel bone mineral density and various oral diseases: a bidirectional Mendelian randomization.

INTRODUCTION: Observational studies demonstrated that the relationship between bone mineral density and oral diseases is mixed. To access the association between heel bone mineral density and various oral diseases, we conducted the Mendelian randomization analysis to explore the association. MATERIALS AND METHODS: Two-sample bidirectional Mendelian analysis was used to explore the relationship between heel bone mineral density and various oral diseases. The inverse-variance weighted (IVW) was used as the primary effect estimate, and various methods were applied to test the reliability and stability of the results, namely MR-Egger, weighted median, simple mode, and weighted mode. RESULTS: This study showed that there was a negative relationship between heel BMD and periodontitis when heel BMD was used as an exposure factor and periodontitis as an outcome factor (IVW OR = 0.85; 95% CI, 0.75-0.95; p = 0.005). Bidirectional Mendelian randomization showed that there was no statistically significant association between periodontitis and heel bone mineral density when chronic periodontitis was the exposure factor (p > 0.05). And there was no significant relationship between heel bone mineral density and other oral diseases (dental caries, diseases of pulp and periapical tissues, impacted teeth, cleft lip, and cleft palate, oral and oropharyngeal cancer) (p > 0.05). CONCLUSION: This study showed that there was a negative relationship between heel bone density and periodontitis, and the decrease in heel bone density could promote the occurrence of periodontitis. In addition, there was no statistically significant relationship between heel bone density and other oral diseases.

[Research Status and Trend Analysis of Environmental and Health Risk and Control of Persistent, Mobile, and Toxic Chemicals].

Persistent, mobile, and toxic or very persistent and very mobile (PMT/vPvM) chemicals have been widely detected in surface water, groundwater, and drinking water around the world and are important emerging contaminants that may significantly affect human health and the environment in the future. According to the identification criteria proposed by the European Union, there are thousands of PMT/vPvM substances in existing chemicals, covering a wide range of applications, including dozens of high-yield industrial chemicals such as melamine. PMT/vPvM chemicals can be discharged into the environment through farmland runoff, industrial wastewater, and domestic sewage, and sewage treatment plants are currently considered to be their main discharge route. It is difficult to effectively remove PMT/vPvM chemicals through the current conventional water treatment technology; they can exist in the water circulation system of the urban human settlement environment for a long time, endangering the safety of drinking water and the ecosystem. The European Union has taken the lead in introducing PMT/vPvM chemicals specifically into the priority areas of the current chemical risk management system. At present, there are still many potential PMT/vPvM chemicals in the environment, and their monitoring methods need to be further improved. It will take time for the identification of substances, the scope of categories, and the establishment of lists. Studies on the environmental fate and exposure of PMT/vPvM in various regions of the world are still very limited, and research on the potential, long-term ecotoxicity, and human health hazard effects remains scarce. At the same time, the research and development of substitute or alternative technologies, as well as environmental engineering treatment technologies such as sewage treatment and contaminated site remediation, will become an urgent need for future PMT/vPvM risk scientific research and management decisions.

Identification of immunological bioprocesses involved in peri-implantitis using weighted gene co-expression network analysis.

BACKGROUND: Peri-implantitis is an irreversible infectious disease that occurs with high incidence. Exploring the immune responses of peri-implantitis is key to developing targeted treatment strategies. However, there is limited research on the immune response of peri-implantitis. METHODS: This study performed a weighted gene co-expression network analysis to identify the peri-implantitis related gene network and conducted a functional enrichment analysis of the gene network. Thereafter, the candidate hub genes were selected by constructing a protein-protein interaction network and drawing an upset plot. The hub genes were identified through their significant associations with disease condition and validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. Using the gene set variation analysis, the hub genes were further used to explore infiltrating immunocytes and immune factors in peri-implantitis. Finally, the immunocytes and immune factor related hub genes were intersected to obtain the therapeutic target, which was validated using histological staining. RESULTS: The peri-implantitis related gene network was enriched in innate and adaptive immune response. Subsequently, interleukin (IL)1B, IL10, ITGAM, ITGB1, STAT3, and TLR4 were identified as hub genes. Plasmacytoid dendritic cells, macrophages, myeloid-derived suppressor cells, natural killer T cells, and immature B cells were positively and significantly related to the hub genes IL1B, TLR4, ITGAM, and ITGB1 (correlation coefficient > 0.80). While immune factors CXCL10, IL6, and CXCL12 and hub genes IL10 and IL1B held the highest degree in the immune factors network. IL1B may be a promising therapeutic target. CONCLUSION: This study provides new insights into the hub genes, immunocytes, and immune factors underlying peri-implantitis immunological bioprocess.

A random batch method for efficient ensemble forecasts of multiscale turbulent systems.

A new efficient ensemble prediction strategy is developed for a multiscale turbulent model framework with emphasis on the nonlinear interactions between large and small-scale variables. The high computational cost in running large ensemble simulations of high-dimensional equations is effectively avoided by adopting a random batch decomposition of the wide spectrum of the fluctuation states, which is a characteristic feature of the multiscale turbulent systems. The time update of each ensemble sample is then only subject to a small portion of the small-scale fluctuation modes in one batch, while the true model dynamics with multiscale coupling is respected by frequent random resampling of the batches at each time updating step. We investigate both theoretical and numerical properties of the proposed method. First, the convergence of statistical errors in the random batch model approximation is shown rigorously independent of the sample size and full dimension of the system. Next, the forecast skill of the computational algorithm is tested on two representative models of turbulent flows exhibiting many key statistical phenomena with a direct link to realistic turbulent systems. The random batch method displays robust performance in capturing a series of crucial statistical features with general interests, including highly non-Gaussian fat-tailed probability distributions and intermittent bursts of instability, while requires a much lower computational cost than the direct ensemble approach. The efficient random batch method also facilitates the development of new strategies in uncertainty quantification and data assimilation for a wide variety of general complex turbulent systems in science and engineering.

Anticancer Activity of Diosgenin and Its Molecular Mechanism.

Diosgenin, a steroidal sapogenin, obtained from Trigonella foenum-graecum, Dioscorea, and Rhizoma polgonati, has shown high potential and interest in the treatment of various cancers such as oral squamous cell carcinoma, laryngeal cancer, esophageal cancer, liver cancer, gastric cancer, lung cancer, cervical cancer, prostate cancer, glioma, and leukemia. This article aims to provide an overview of the in vivo, in vitro, and clinical studies reporting the diosgenin's anticancer effects. Preclinical studies have shown promising effects of diosgenin on inhibiting tumor cell proliferation and growth, promoting apoptosis, inducing differentiation and autophagy, inhibiting tumor cell metastasis and invasion, blocking cell cycle, regulating immunity and improving gut microbiome. Clinical investigations have revealed clinical dosage and safety property of diosgenin. Furthermore, in order to improve the biological activity and bioavailability of diosgenin, this review focuses on the development of diosgenin nano drug carriers, combined drugs and the diosgenin derivatives. However, further designed trials are needed to unravel the diosgenin's deficiencies in clinical application.

Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality.

BACKGROUND: Due to intrinsic differences in data formatting, data structure, and underlying semantic information, the integration of imaging data with clinical data can be non-trivial. Optimal integration requires robust data fusion, that is, the process of integrating multiple data sources to produce more useful information than captured by individual data sources. Here, we introduce the concept of fusion quality for deep learning problems involving imaging and clinical data. We first provide a general theoretical framework and numerical validation of our technique. To demonstrate real-world applicability, we then apply our technique to optimize the fusion of CT imaging and hepatic blood markers to estimate portal venous hypertension, which is linked to prognosis in patients with cirrhosis of the liver. PURPOSE: To develop a measurement method of optimal data fusion quality deep learning problems utilizing both imaging data and clinical data. METHODS: Our approach is based on modeling the fully connected layer (FCL) of a convolutional neural network (CNN) as a potential function, whose distribution takes the form of the classical Gibbs measure. The features of the FCL are then modeled as random variables governed by state functions, which are interpreted as the different data sources to be fused. The probability density of each source, relative to the probability density of the FCL, represents a quantitative measure of source-bias. To minimize this source-bias and optimize CNN performance, we implement a vector-growing encoding scheme called positional encoding, where low-dimensional clinical data are transcribed into a rich feature space that complements high-dimensional imaging features. We first provide a numerical validation of our approach based on simulated Gaussian processes. We then applied our approach to patient data, where we optimized the fusion of CT images with blood markers to predict portal venous hypertension in patients with cirrhosis of the liver. This patient study was based on a modified ResNet-152 model that incorporates both images and blood markers as input. These two data sources were processed in parallel, fused into a single FCL, and optimized based on our fusion quality framework. RESULTS: Numerical validation of our approach confirmed that the probability density function of a fused feature space converges to a source-specific probability density function when source data are improperly fused. Our numerical results demonstrate that this phenomenon can be quantified as a measure of fusion quality. On patient data, the fused model consisting of both imaging data and positionally encoded blood markers at the theoretically optimal fusion quality metric achieved an AUC of 0.74 and an accuracy of 0.71. This model was statistically better than the imaging-only model (AUC = 0.60; accuracy = 0.62), the blood marker-only model (AUC = 0.58; accuracy = 0.60), and a variety of purposely sub-optimized fusion models (AUC = 0.61-0.70; accuracy = 0.58-0.69). CONCLUSIONS: We introduced the concept of data fusion quality for multi-source deep learning problems involving both imaging and clinical data. We provided a theoretical framework, numerical validation, and real-world application in abdominal radiology. Our data suggests that CT imaging and hepatic blood markers provide complementary diagnostic information when appropriately fused.

[Experimental study of APB-DOCK8 transgenic tomato vaccine for caries prevention].

PURPOSE: To observe the anti-caries effect of transgenic tomato anti-caries vaccine after immunization with SD rats by gavage and to explore its immunity mechanism initially. METHODS: SD rats were used to establish an experimental caries model. The transgenic anti-caries tomatoes expressing the target protein were cultivated and identified. The SIgA and IgG contents of specific anti-PAcA in saliva and blood samples of SD rats were detected by ELISA. Then, the SD rats were sacrificed, the maxillary and mandibular bones were taken for Keyes dental caries score, and spleens were taken for the analysis of RNA-seq. Statistical analysis was performed with SPSS 18.0 software package. RESULTS: The target protein concentration in the transgenic tomato anti-caries vaccine was 36.28 µg/mL. After vaccine immunization of SD rats, group D (8 mL/kg) produced the highest levels of specific SIgA and IgG antibodies at week 6 and was significantly different from the other groups(P＜0.05), and caries counting score was also significantly different than the other groups (P＜0.05). The spleen mRNA of SD rats in group D was extracted and sequenced by RNA-seq, and 40 genes with significant differences in mRNA expression were obtained(P-adjust＜0.05, |Fold Change|≥1.5). 26 genes were significantly upregulated, including IGFBP6 and COL15A1. The upregulated gene GO enrichment was enriched to humoral immune response, B-cell activation, and immunoglobulin receptor binding; KEGG enrichment was enriched to 56 signaling pathways, including PI3K-AKT and NF-κB, and F＜0.001. Fourteen genes were significantly downregulated, but the analysis of downregulated gene GO and KEGG enrichment was not statistically significant(F＞0.1). CONCLUSIONS: Transgenic tomato anti-caries vaccine may reduce caries occurrence by upregulating the activation of PI3K-AKT signaling pathway mediated by IGFBP6 in SD rats.

Effects of different doses of vancomycin powder in total knee and hip arthroplasty on the periprosthetic joint infection rate: a systematic review and meta-analysis.

BACKGROUND: Periprosthetic joint infection (PJI) following total joint arthroplasty (TJA) is a serious complication for patients. Some joint surgeons have tried to use vancomycin powder (VP) in total knee and total hip arthroplasty to prevent postoperative PJI, but its effect is still not clear. At present, there is no meta-analysis that specifically analyses the effect of different doses of vancomycin powder on the incidence of PJI. METHODS: We carried out a search based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and identified the studies we needed. Review Manager (RevMan) 5.3 software was employed for statistical analysis. RESULTS: The analysis of primary TKA (PTKA) showed that using 1 g (RR 0.38, 95% CI 0.22-0.67 [P = 0.0008]) and 2 g (RR 0.48, 95% CI 0.31-0.74 [P = 0.0008]) of vancomycin powder in primary TKA (PTKA) could all significantly prevent PJI. The analysis of primary THA (PTHA) showed that using 1 g (RR 0.37, 95% CI 0.17-0.80 [P = 0.01]) of vancomycin powder effectively decreased the incidence of PJI, while using 2 g (RR 1.02, 95% CI 0.53-1.97 [P = 0.94]) of vancomycin powder had no significant effect on preventing PJI. Because the data were abnormal, we believed the conclusion that using 2 g of vancomycin powder in primary THA had no effect on preventing PJI was doubtful. Using vancomycin powder in revision TKA (RTKA) significantly reduced the PJI rate (RR 0.33, 95% CI 0.14-0.77 [P = 0.01]), similar to revision THA (RTHA) (RR 0.37, 95% CI 0.14-0.96 [P = 0.04]). CONCLUSIONS: In primary TKA, both 1 g and 2 g of vancomycin powder can effectively prevent PJI. In primary THA, using 1 g of vancomycin powder is a better choice, while the effect of using 2 g of vancomycin powder is not clear, and a more prospective randomized controlled trial should be done to verify it. In revision TKA and revision THA, vancomycin powder is a good choice to prevent PJI.

Rhodium-Catalyzed Asymmetric 1,4-Addition of α/ß-(N-Indolyl) Acrylates.

A rhodium-catalyzed asymmetric 1,4-addition of α/ß-(N-indolyl) acrylates to access highly enantioenriched chiral N-alkylindoles promoted by chiral diene or sulfur-olefin ligands under mild reaction conditions has been developed, which provides an efficient and practical approach for constructing carbon stereocenters adjacent to the indole nitrogen. The reaction can be applied to various N-indolyl-substituted α,ß-unstaturated esters and arylboron reagents, providing access to a wide range of α- and ß-(N-indolyl) propionate derivatives in high yields with excellent enantioselectivities (≤99% ee).

Age-dependent aneuploidy in mammalian oocytes instigated at the second meiotic division.

Ageing severely affects the chromosome segregation process in human oocytes resulting in aneuploidy, infertility and developmental disorders. A considerable amount of segregation errors in humans are introduced at the second meiotic division. We have here compared the chromosome segregation process in young adult and aged female mice during the second meiotic division. More than half of the oocytes in aged mice displayed chromosome segregation irregularities at anaphase II, resulting in dramatically increased level of aneuploidy in haploid gametes, from 4% in young adult mice to 30% in aged mice. We find that the post-metaphase II process that efficiently corrects aberrant kinetochore-microtubule attachments in oocytes in young adult mice is approximately 10-fold less efficient in aged mice, in particular affecting chromosomes that show small inter-centromere distances at the metaphase II stage in aged mice. Our results reveal that post-metaphase II processes have critical impact on age-dependent aneuploidy in mammalian eggs.

Reconstructing community structure of online social network via user opinions.

User opinion affects the performance of network reconstruction greatly since it plays a crucial role in the network structure. In this paper, we present a novel model for reconstructing the social network with community structure by taking into account the Hegselmann-Krause bounded confidence model of opinion dynamic and compressive sensing method of network reconstruction. Three types of user opinion, including the random opinion, the polarity opinion, and the overlap opinion, are constructed. First, in Zachary's karate club network, the reconstruction accuracies are compared among three types of opinions. Second, the synthetic networks, generated by the Stochastic Block Model, are further examined. The experimental results show that the user opinions play a more important role than the community structure for the network reconstruction. Moreover, the polarity of opinions can increase the accuracy of inter-community and the overlap of opinions can improve the reconstruction accuracy of intra-community. This work helps reveal the mechanism between information propagation and social relation prediction.

Prediction of clinical efficacy of subcutaneous immunotherapy for Artemisia sieversiana pollen allergic rhinitis by serum metabolomics.

BACKGROUND/PURPOSE: Specific immunotherapy is the only effective etiological treatment for allergic rhinitis, but subcutaneous immunotherapy has a slow onset and poor compliance. Predicting the clinical efficacy of subcutaneous immunotherapy in advance can reduce unnecessary medical costs and resource waste. This study aimed to identify metabolites that could predict the efficacy of subcutaneous immunotherapy on seasonal allergic rhinitis by serum metabolomics. METHODS: Patients (n = 43) with Artemisia sieversiana pollen allergic rhinitis were enrolled and treated with subcutaneous immunotherapy for one year. Patients were divided into the ineffective group (n = 10) and effective group (n = 33) according to the therapeutic index. Serum samples were collected before treatment. Metabolomics was determined by liquid chromatography-mass spectrometry combined with gas chromatography-mass spectrometry and analyzed differential compounds and related metabolic pathways. RESULTS: A total of 129 differential metabolites (P < 0.05) were identified and 4 metabolic pathways, namely taurine and hypotaurine metabolism, pentose and glucuronate interconversions, pentose phosphate pathway, and alanine, aspartate, and glutamate metabolism, were involved. CONCLUSION: Some metabolites, such as hypotaurine, taurine, and l-alanine, have the potential to become predictive biomarkers for effective subcutaneous immunotherapy.

Efficacy and safety of letrozole or anastrozole in the treatment of male infertility with low testosterone-estradiol ratio: A meta-analysis and systematic review.

BACKGROUND: Aromatase inhibitors (AIs) have been used to treat male infertility for decades. However, due to the lack of large-scale randomized controlled studies and basic research, the efficacy and safety of AIs in the treatment of male infertility remain controversial. Therefore, it is necessary to conduct an evidence-based preliminary evaluation of the existing clinical trials of AIs in the treatment of male infertility. METHOD: A comprehensive literature search was performed in the PubMed, Embase, Cochrane, CNKI, VIP, CBM, and Wanfang databases through August 2021 for all studies. We conducted a systematic review with a meta-analysis of all available studies reporting sperm conventional parameters, gonadotropin and testosterone levels, and/or the pregnancy rate. RESULTS: A total of 10 studies involving 666 patients were included. Letrozole (LE) or anastrozole (AZ) administration significantly increased sperm concentration, total sperm count, serum luteinizing hormone (LH), follicle-stimulating hormone (FSH), testosterone (T) levels, and the testosterone-to-estradiol ratio (T/E2), but E2 levels were significantly reduced compared with baseline values. Compared with the control group, which included selective estrogen receptor modulators (SEMRs) or human chorionic gonadotropin (HCG), LE, or AZ did not have any significant effect on sperm concentration, motility, and morphology, except that AIs had less effect on sperm motility than the control group (weighted mean difference [WMD]: -2.55; 95% CI: -4.11 to -1.00; p = 0.001). CONCLUSION: AIs may be effective in the treatment of male infertility. For infertile male patients planning assisted reproduction, discontinuation of AIs for 2-7 days prior to sperm retrieval may increase the success rate of fertilization. Further studies with larger sample sizes are needed to validate these findings.