Chinese medicinal retention enemas have gradually attracted the attention of clinicians as an alternative approach for tubal obstructive infertility. The purpose of this study was to investigate the ...efficacy and safety of conventional surgery combined with traditional Chinese medicinal retention enemas for the treatment of tubal obstructive infertility.
Eight electronic databases were searched from their inception to November 30, 2022. To assess the efficacy and safety of different treatments, following outcomes were measured: clinical pregnancy rate, clinical total effective rate, incidence of ectopic pregnancy, the improvement of Traditional Chinese Medicinal (TCM) symptoms, the improvement of the signs of obstructive tubal infertility and side effects.
A total of 23 Randomized Controlled Trials (RCTs) with 1909 patients met the inclusion criteria. The pooled results showed a higher pregnancy rate in the experimental group than in the control group (RR 1.75, 95% CI 1.58, 1.94, Z = 10.55, P<0.00001). The clinical total effective rate in the experimental group was higher than that in the control group (RR 1.28, 95% CI 1.23, 1.34, Z = 11.07, P<0.00001). The incidence of ectopic pregnancy in the experimental group was lower than that in the control group (RR 0.40, 95% CI 0.20, 0.77, Z = -2.73, P = 0.01).
Based on current evidence, we concluded that conventional surgery combined with traditional Chinese medicinal retention enema for tubal obstructive infertility was superior to conventional surgery alone in improving the clinical pregnancy rate, improving clinical total effective rate, improving TCM symptoms, improving the signs of obstructive tubal infertility and lowering the incidence of ectopic pregnancy. However, further clinical trials with high-quality methodologies need to be conducted.
The purpose of this study is to explore whether LncRNA PICSAR binds to miR-485-5p and thereby activates TGF-β1/Smad signaling pathway, influencing the abnormal proliferation of fibroblasts and ...excessive deposition of ECM in hypertrophic scar formation. PICSAR and miR-485-5p expressions were detected by qPCR. Cell proliferation was examined by CCK-8. Protein expressions were determined by western blot. Immunofluorescence detected the Ki-67 expression. Dual-luciferase followed by immunoprecipitation was performed to verify the interaction between PICSAR and miR-485-5p. Interference with PICSAR inhibited the abnormal proliferation of hypertrophic scar fibroblasts (HSFs) and the excessive deposition of ECM. It was also confirmed in our study that MiR-485-5p is a direct target of PICSAR in HSFs. Additionally, inhibition of miR-485-5p reversed the effect of PICSAR knockdown in HSFs. LncRNA PICSAR binds to miR-485-5p and thereby activates TGF-β1/Smad signaling pathway, promoting the abnormal proliferation of fibroblasts and excessive deposition of ECM in hypertrophic scar formation.
Human-sensitive mechanosensation depends on ionic currents controlled by skin mechanoreceptors. Inspired by the sensory behavior of skin, we investigate zwitterionic hydrogels that generate ions ...under an applied force in a mobile-ion-free system. Within this system, water dissociates as the distance between zwitterions reduces under an applied pressure. Meanwhile, zwitterionic segments can provide migration channels for the generated ions, significantly facilitating ion transport. These combined effects endow a mobile-ion-free zwitterionic skin sensor with sensitive transduction of pressure into ionic currents, achieving a sensitivity up to five times that of nonionic hydrogels. The signal response time, which relies on the crosslinking degree of the zwitterionic hydrogel, was ~38 ms, comparable to that of natural skin. The skin sensor was incorporated into a universal throat-worn silent-speech recognition system that transforms the tiny signals of laryngeal mechanical vibrations into silent speech.
Ideal hydrogel fibers with high toughness and environmental tolerance are indispensable for their long-term application in flexible electronics as actuating and sensing elements. However, current ...hydrogel fibers exhibit poor mechanical properties and environmental instability due to their intrinsically weak molecular (chain) interactions. Inspired by the multilevel adjustment of spider silk network structure by ions, bionic hydrogel fibers with elaborated ionic crosslinking and crystalline domains are constructed. Bionic hydrogel fibers show a toughness of 162.25 ± 21.99 megajoules per cubic meter, comparable to that of spider silks. The demonstrated bionic structural engineering strategy can be generalized to other polymers and inorganic salts for fabricating hydrogel fibers with broadly tunable mechanical properties. In addition, the introduction of inorganic salt/glycerol/water ternary solvent during constructing bionic structures endows hydrogel fibers with anti-freezing, water retention, and self-regeneration properties. This work provides ideas to fabricate hydrogel fibers with high mechanical properties and stability for flexible electronics.
African swine fever virus (ASFV) is a complex nucleocytoplasmic large DNA virus (NCLDV) that causes a lethal hemorrhagic disease that is currently threatening the global pig industry. ASFV structural ...protein p30 is a membrane phosphoprotein that suggests it may play a regulatory role, possibly in signal transduction. Despite its significance in internalization into host cells, the interaction between p30 and host proteins is relatively unknown. In this study, we describe the application of a DUALmembrane yeast two-hybrid assay to screen a primary porcine alveolar macrophages cDNA library and analyze the interactome of p30 protein. Our data identify seven host cellular proteins (DAB2, RPSA, OAS1, PARP9, CAPG, ARPC5, and VBP1) that putatively interact with the p30. We further verified the interaction between p30 and host proteins by laser confocal microscopy, co-immunoprecipitation, and GST-pulldown assay. To further understand the relationship between host proteins and p30, we drew the interaction network diagram and analyzed the functional enrichment of each host protein. Enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes indicated that host proteins were mainly related to endocytosis, actin cytoskeleton regulation, and innate immunity. Collectively, we identified the interaction between p30 and host cell protein using a membrane protein yeast two-hybrid system, which increases our knowledge of the interaction between ASFV and the host and informs future research on antiviral strategies.
Familial hypercholesterolemia is an inherited disorder that remains underdiagnosed. Conventional genetic testing methods such as next-generation sequencing (NGS) or target PCR are based on the ...amplification process. Due to the efficiency limits of polymerase and ligase enzymes, these methods usually target short regions and do not detect large mutations straightforwardly. This study combined the long-read nanopore sequencing and CRISPR-Cas9 system to sequence the target DNA molecules without amplification. We originally designed and optimized the CRISPR-RNA panel to target the low-density lipoprotein receptor gene (LDLR) and proprotein convertase subtilisin/kexin type 9 gene (PCSK9) from human genomic DNA followed by nanopore sequencing. The average coverages for LDLR and PCSK9 were 106× and 420×, versus 1.2× for the background genome. Among them, continuous reads were 52x and 307x, respectively, and spanned the entire length of LDLR and PCSK9. We identified pathogenic mutations in both coding and splicing donor regions in LDLR. We also detected an 11,029 bp large deletion in another case. Furthermore, using continuous long reads generated from the benchmark experiment, we demonstrated how a false-positive 670 bp deletion caused by PCR amplification errors was easily eliminated.
In network edge computing scenarios, close monitoring of network data and anomaly detection is critical for Internet services. Although a variety of anomaly detectors have been proposed by many ...scholars, few of these take into account the anomalies of the data in business logic. Expert labeling of business logic exceptions is also very important for detection. Most exception detection algorithms focus on problems, such as numerical exceptions, missed exceptions and false exceptions, but they ignore the existence of business logic exceptions, which brings a whole new challenge to exception detection. Moreover, anomaly detection in the context of big data is limited to the need to manually adjust detector parameters and thresholds, which is constrained by the physiological limits of operators. In this paper, a neural network algorithm based on the combination of Labeling Neural Network and Relevant Long Short-Term Memory Neural Network is proposed. This is a semi-supervised exception detection algorithm that can be readily extended with business logic exception types. The self-learning performance of this multi-network is better adapted to the big data anomaly detection scenario, which further improves the efficiency and accuracy of network data anomaly detection and considers business scenario-based anomaly data detection. The results show that the algorithm achieves 96% detection accuracy and 97% recall rate, which are consistent with the business logic anomaly fragments marked by experts. Both theoretical analysis and simulation experiments verify its effectiveness.
In the field of financial investment, accurate prediction of financial market values can increase investor profits. Investor personality affects specific portfolio solutions, which keeps them ...symmetrical in the process of investment competition. However, information is often asymmetric in financial markets, and this information bias often results in different future returns for investors. Nowadays, machine learning algorithms are widely used in the field of financial investment. Many advanced machine learning algorithms can effectively predict future market changes and provide a scientific basis for investor decisions. The purpose of this paper is to study the problem of optimal matching of financial investment by using machine learning algorithms combined with finance and to reduce the impact of information asymmetry for investors effectively. Moreover, based on the model results, we study the effects of different investor personalities on factors such as expected investment returns and the number of transactions. Based on the time-series characteristics of price data, through multi-model comparison, we select the ARIMA model combined with particle swarm algorithm to determine the optimal prediction model and introduce the concepts of mean-variance model, Sharpe ratio, and efficient frontier to find the balance point of risk and return. In this study, we use gold and bitcoin price data from 2016–2021 to develop optimal investment strategies and study the impact of investor behavior on trading strategies.
Abstract
Toxoplasma gondii
is an obligate parasitic protozoon that transmits to animals and humans via ingested food. Cats that act as
T. gondii’
s final hosts play a critical role in
T. gondii
...transmission by shedding millions of oocysts. Timely diagnosis of infected cats is essential for preventing toxoplasmosis because oocysts are a putative
T. gondii
source in epidemiology. We developed a new visual LAMP assay targeting the B1 gene to analyze single oocysts in cat feces in this study. The amplification result could be visually estimated based on the color change. LAMP assay analytical sensitivity was 10
1
copies/µL for the B1 gene plasmid, which was tenfold better than the PCR reaction. There were no cross-reactions with other parasites. The LAMP assay can detect a single
T. gondii
oocyst in 200 mg of cat feces. The LAMP assay detected a single oocyst in 200 mg cat feces at a higher rate than the PCR assay (83.3% vs. 50.0%).
With a high prevalence of noise-induced hearing loss (NIHL), the noise survey tools for identifying individuals with high risk of NIHL are still limited. This study was aimed to translate and develop ...a Chinese version of noise exposure questionnaire (C-NEQ), and validate its reliability and reproducibility.
This study was conducted from May 2020 to March 2021 in China. The questionnaire was translated from the original NEQ and adapted into Chinese culture using the method according to the International Test Committee. Content validity was evaluated by our expert group. Construct validity and reliability of the C-NEQ was determined through estimating the confirmatory factor analysis and Cronbach's alpha in a cross-sectional analysis among 641 Chinese speaking adults, respectively. The retest reproducibility of the C-NEQ was analyzed by using the intra-group correlation coefficient (ICC) in a follow-up analysis among 151 participants.
The C-NEQ comprises ten items covering four domains: occupational, housework, transport and recreational noise exposure. The annual noise exposure (ANE) was calculated as the protocol of original NEQ. A total of 641 adult participants (aged 26.9 ± 10.1 years, 53.4% males) completed the C-NEQ. The average time for completing the C-NEQ was 4.4 ± 3.0 min. Content validity indicated high relevance of the C-NEQ. The confirmatory factor analysis indices illustrated that the items of the C-NEQ were suitable with the data in the study. For the internal reliability, the Cronbach's α coefficients of the total items and four domains (occupational, housework, transport, and recreational noise exposure) were 0.799, 0.959, 0.837, 0.825, and 0.803, respectively. Among them, 151 participants (aged 36.1 ± 11.1 years, 65.6% males) completed the retest of the C-NEQ 1 month after the first test. The ICC value of total ANEs between the first test and the second test was 0.911 (P < 0.001).
In this study, we have validated the C-NEQ with adequate reliability and reproducibility for quantifying an individual's annual daily noise exposure, which provides an effective fast-screen tool for researches and clinics to identify those individuals with high risks of NIHL within the short time duration (no more than five minutes) among Chinese population.
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