Diagnosis and management of vaginal leiomyoma: A case report and literature review

Objectives: Leiomyomas are benign mesenchymal tumors that consist of smooth muscle cells and varying amounts of fibrous stroma. Uterine leiomyomas are the most common, affecting 20% to 30% of reproductive-age women, but vaginal leiomyomas are rare. Treatments gradually diversify with increased awareness of vaginal leiomyoma, but transvaginal fibroid resection remains the commonly used scheme. Case report: Herein, we present the case of a 50-year-old asymptomatic woman who had a mass in the left anterior wall of the vagina discovered by gynecological examination and ultrasound. We used oxytocin diluent injection during surgery to create a water pad in the tissue space and then performed a transvaginal myomectomy. There was little or negligible intraoperative bleeding and no peripheral tissue injury, early or late postoperative complications, incision dehiscence, and no surgical site infection. Conclusions: Transvaginal ultrasonography is the preferred examination for vaginal leiomyomas, and transvaginal myomectomy is the classic treatment method. The formation of a water pad with oxytocin dilution can effectively reduce intraoperative bleeding and shorten surgery time

Xiaoqinglong granules as add-on therapy for asthma: latent class analysis of symptom predictors of response.

Xiaoqinglong granules (XQLG) has been shown to be an effective therapy in asthma animal models. We reviewed the literature and conducted this study to assess the impact of XQLG as an add-on therapy to treatment with fluticasone/salmeterol (seretide) in adult patients with mild-to-moderate, persistent asthma. A total of 178 patients were randomly assigned to receive XQLG and seretide or seretide plus placebo for 90 days. Asthma control was assessed by asthma control test (ACT), symptoms scores, FEV(1), and PEF. Baseline patient-reported Chinese medicine (CM)-specific symptoms were analyzed to determine whether the symptoms may be possible indicators of treatment response by conducting latent class analysis (LCA). There was no statistically significant difference in ACT score between two groups. In the subset of 70 patients with symptoms defined by CM criteria, XQLG add-on therapy was found to significantly increase the levels of asthma control according to global initiative for asthma (GINA) guidelines (P = 0.0329). There was no significant difference in another subset of 100 patients with relatively low levels of the above-mentioned symptoms (P = 0.1291). Results of LCA suggest that patients with the six typical symptoms defined in CM may benefit from XQLG

Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model

BackgroundPancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications.MethodsIn this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method.ResultsOur analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age.ConclusionOur study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease

Predicting Housekeeping Genes Based on Fourier Analysis

Housekeeping genes (HKGs) generally have fundamental functions in basic biochemical processes in organisms, and usually have relatively steady expression levels across various tissues. They play an important role in the normalization of microarray technology. Using Fourier analysis we transformed gene expression time-series from a Hela cell cycle gene expression dataset into Fourier spectra, and designed an effective computational method for discriminating between HKGs and non-HKGs using the support vector machine (SVM) supervised learning algorithm which can extract significant features of the spectra, providing a basis for identifying specific gene expression patterns. Using our method we identified 510 human HKGs, and then validated them by comparison with two independent sets of tissue expression profiles. Results showed that our predicted HKG set is more reliable than three previously identified sets of HKGs

Influence of Variable Rigidity Design of Piled Raft Foundation on Seismic Performance of Buildings

In order to reduce the costs and improve the overall performance of building systems, the static optimized design with variable rigidity of piled raft foundations has been widely used in recent years. Variable rigidity design of piled raft foundations that support midrise buildings in high-risk seismic zones can alter the dynamic characteristics of the soil-pile-structure system during an earthquake due to soil-pile-structure interaction. To investigate these aspects, a nuclear power plant sitting on multilayered soil is simulated numerically. The paper describes a numerical modeling technique for the simulation of complex seismic soil-pile-structure interaction phenomena. It was observed that the total shear force on top of the piles and the rocking of the raft are reduced after optimization, whereas the displacement of the superstructure is nearly unaffected. The findings of this study can help engineers select a correct pile arrangement when considering the seismic performance of a building sitting on soft soil

Software diversity evaluation method based on the properties of ROP/JOP gadgets

In order to reduce the risk of rapid spread of homogeneous attacks in network systems, and enhance network and software security, software diversification technologies are applied widely nowadays.Software diversification aims to generate functionally equivalent but internally changed program variants, thereby alter a single operating environment and mitigating homogenization attacks.The existing diversified technical evaluation index ROP gadgets survival rate is difficult to directly reflect the safety impact and the evaluation method is single.In order to evaluate the effectiveness of the diversification method more comprehensively and effectively, a software diversification evaluation method based on the properties of ROP/JOP gadgets is proposed, by analyzing common code reuse attacks, and turns abstract quantification into concrete indicators evaluates the security gain and effect of diversified methods from three aspects of space, time and quality.The method first discusses how diversification techniques affect ROP/JOP attacks according to the three properties of gadgets similarity, damage degree and availability.Nine kinds of diversification methods, such as instruction replacement, NOP insertion, and control flow flattening, are used to diversify the GNU coreutils assembly to generate diversification assembly.Experiments based on the property of gadgets are carried out on the diverse assemblies, and the effectiveness of different diversification methods and the impact on attacks are evaluated according to the experimental results.The experimental results show that this method can accurately evaluate the security gain of software diversification methods, the diversification technology will lead to the increase of the attack chain space required by the ROP/JOP attack, the longer time to construct the attack chain and the lower the attack success rate.The effects of different diversification methods are different, it has a guiding role for the follow-up research on diversified technologies with higher safety gains

The complete chloroplast genome of Caroxylon passerinum (Chenopodiaceae), an annual desert plant

Caroxylon passerinum is an important constructive species, which is widely distributed in both desert and desert steppe in north-western China. C. passerinum is one of hosts of holoparasitic Cistanche species. In this study, we report the complete chloroplast genome sequence of C. passerinum, which is 150,925 bp in length and comprises a large single-copy region (83,057 bp), a small single-copy region (18,180 bp), and a pair of inverted repeats (24,844 bp). It encodes 132 unique genes, including 89 protein-coding genes (PCGs), 35 tRNAs, and eight rRNAs. The overall GC content of this chloroplast genome is 36.8%. Maximum likelihood (ML) phylogenetic tree strongly supports that C. passerinum is closely related to the hosts of Cistanche deserticola, Haloxylon persicum and Haloxylon ammodendron

Evaluation of nonionic surfactant modified montmorillonite as mycotoxins adsorbent for aflatoxin B1 and zearalenone

This work aims at exploring the potential of nonionic surfactant octylphenol polyoxyethylene ether (OP-10) modified montmorillonites (NMts) as mycotoxins adsorbent. The resulting NMts has different structural configurations, organic carbon contents, surface hydrophobicity and textural properties at different surfactant loadings. The prepared NMts were used for adsorption of polar aflatoxin B1 (AFB1) and weak polar zearalenone (ZER) in both single and binary-contaminate systems by simulating conditions of gastrointestinal tract. The adsorption capacities of NMts to AFB1 and ZER increased up to 2.78 and 8.54 mg/g respectively from 0.51 and 0.00 mg/g of raw montmorillonite (Mt). High adsorption capacities of NMts to AFB1 and ZER could be reached at low surfactant loadings. There was little decrease from pH of 3.5 to 6.5 but became negligible with increasing the surfactant loadings. In binary-contaminate adsorption system, the adsorption of ZER was obviously affected by the existence of AFB1, while ZER had little effect on the adsorption process of AFB1 due to different adsorption mechanism. This study demonstrates that NMts could be a promising adsorbent for simultaneous detoxification of polar and non-polar mycotoxins