[Effect analysis of facial nerve decompression surgery in the treatment of Bell's palsy and Hunt syndrome].

Objective:To summarize and analyze the effect of facial nerve decompression surgery for the treatment of Bell's palsy and Hunt syndrome. Methods:The clinical data of 65 patients with facial nerve palsy who underwent facial nerve decompression in our center from October 2015 to October 2022 were retrospectively analyzed, including 54 patients with Bell's palsy and 11 patients with Hunter syndrome. The degree of facial paralysis（HB grade） was evaluated before surgery, and ENoG, pure tone audiometry, temporal bone CT and other examinations were completed. All patients had facial palsy with HB grade V or above after conservative treatment for at least 1 month, and ENoG decreased by more than 90%. All patients underwent facial nerve decompression surgery through the transmastoid approach within 3 months after onset of symptoms. The recovery effect of facial nerve function after surgery in patients with Bell's palsy and Hunter syndrome was summarized and analyzed. In addition, 15 cases in group A（operated within 30-60 days after onset） and 50 cases in group B（operated within 61-90 days after onset） were grouped according to the course of the disease（the interval between onset of symptoms and surgery） to explore the effect of surgical timing on postoperative effect. Results:There was no significant difference between the two groups of patients with Chi-square test（P=0.54） in 42 patients（77.8%, 42/54） with Bell's palsy and 7 patients（63.6%, 7/11） in patients with Hunter syndrome who recovered to grade Ⅰ-Ⅱ. According to the course of the disease, 10 cases（66.7%, 10/15） in group A recovered to grade Ⅰ-Ⅱ after surgery. In group B, 39 patients（78.0%, 39/50） recovered to grade Ⅰ-Ⅱ after surgery, and there was no statistically significant difference between the two groups by Chi-square test（P=0.58）. Conclusion:Patients with Bell's palsy and Hunter syndrome can achieve good results after facial nerve decompression within 3 months of onset, and there is no significant difference in the surgical effect between the two types of patients.

KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data.

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped. In this study, we propose a computational framework KinPred-RNA to derive kinase activities from bulk RNA-sequencing data in cancer samples. KinPred-RNA framework, using the extreme gradient boosting (XGBoost) regression model, outperforms random forest regression, multiple linear regression, and support vector machine regression models in predicting kinase activities from cancer-related RNA sequencing data. Efficient gene signatures from the LINCS-L1000 dataset were used as inputs for KinPred-RNA. The results highlight its potential to be related to biological function. In conclusion, KinPred RNA constitutes a significant advance in cancer research by potentially facilitating the identification of cancer.

p53-regulated lncRNAs in cancers: from proliferation and metastasis to therapy.

Long non-coding RNAs (lncRNAs) have been identified as master gene regulators through various mechanisms such as transcription, translation, protein modification and RNA-protein complexes. LncRNA dysregulation is frequently associated with a variety of biological functions and human diseases including cancer. The p53 network is a key tumor-suppressive mechanism that transcriptionally activates target genes to suppress cellular proliferation in human malignancies. Recent research indicates that lncRNAs play an important role in the p53 signaling pathway. In this review, we summarize the current knowledge of lncRNAs in p53-relevant functions and provide an overview of how these altered lncRNAs contribute to tumor initiation and progression. We also discuss the association between lncRNA and up- or downstream genes of p53. These findings imply that lncRNAs can help identify cellular vulnerabilities that may prove to be promising potential biomarkers and therapeutic targets for cancer treatment.

DeepAFP: An effective computational framework for identifying antifungal peptides based on deep learning.

Fungal infections have become a significant global health issue, affecting millions worldwide. Antifungal peptides (AFPs) have emerged as a promising alternative to conventional antifungal drugs due to their low toxicity and low propensity for inducing resistance. In this study, we developed a deep learning-based framework called DeepAFP to efficiently identify AFPs. DeepAFP fully leverages and mines composition information, evolutionary information, and physicochemical properties of peptides by employing combined kernels from multiple branches of convolutional neural network with bi-directional long short-term memory layers. In addition, DeepAFP integrates a transfer learning strategy to obtain efficient representations of peptides for improving model performance. DeepAFP demonstrates strong predictive ability on carefully curated datasets, yielding an accuracy of 93.29% and an F1-score of 93.45% on the DeepAFP-Main dataset. The experimental results show that DeepAFP outperforms existing AFP prediction tools, achieving state-of-the-art performance. Finally, we provide a downloadable AFP prediction tool to meet the demands of large-scale prediction and facilitate the usage of our framework by the public or other researchers. Our framework can accurately identify AFPs in a short time without requiring significant human and material resources, and hence can accelerate the development of AFPs as well as contribute to the treatment of fungal infections. Furthermore, our method can provide new perspectives for other biological sequence analysis tasks.

[Diagnosis and treatment of rare malignant temporal bone tumors].

Objective:To analyze the diagnosis, treatment and prognosis of patients with rare malignant tumors of the temporal bone. Methods:Four cases of rare temporal bone malignant tumors in our hospital between March 2014 and December 2020 were reviewed, including two cases of chondrosarcoma, one case of fibrosarcoma and one case of endolymphatic cystic papillary adenocarcinoma. There were three males and one female, ages between 28 and 56 years at the time of surgery. Common symptoms included hearing loss, facioplegia, tinnitus, and headache. All patients underwent imaging examinations to evaluate the extent of the lesions. Tumors were removed by subtotal temporal bone resection or infratemporal fossa approach, and postoperative adjuvant radiotherapy was applied if necessary. Results:One of the two chondrosarcoma patients was cured by complete resection of the tumor for 75 months, the other one recurred after the first excision of the tumor and underwent infratemporal fossa approach resection of skull base mass again with no recurrence found yet for 112 months. One patient with fibrosarcoma survived for 28 months after surgery with a positive margin and post-operative radiotherapy. One patient with endolymphatic cystic papillary adenocarcinoma recurred 12 months after subtotal lithotomy, and underwent subtotal temporal bone resection again, combined with radiotherapy. No recurrence was found for 63 months. Conclusion:The incidence of rare temporal bone malignant tumors is extremely low, the location is hidden, and the symptoms are atypical. Attention should be paid for early detection and early treatment. Surgical resection is the main treatment, and radiotherapy can be supplemented in the advanced stage or with a positive margin.

Long non-coding RNA HIF1A-As2 and MYC form a double-positive feedback loop to promote cell proliferation and metastasis in KRAS-driven non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the main oncogenic driver in lung cancer that can be activated by gene mutation or amplification, but whether long non-coding RNAs (lncRNAs) regulate its activation remains unknown. Through gain and loss of function approaches, we identified that lncRNA HIF1A-As2, a KRAS-induced lncRNA, is required for cell proliferation, epithelial-mesenchymal transition (EMT) and tumor propagation in non-small cell lung cancer (NSCLC) in vitro and in vivo. Integrative analysis of HIF1A-As2 transcriptomic profiling reveals that HIF1A-As2 modulates gene expression in trans, particularly regulating transcriptional factor genes including MYC. Mechanistically, HIF1A-As2 epigenetically activates MYC by recruiting DHX9 on MYC promoter, consequently stimulating the transcription of MYC and its target genes. In addition, KRAS promotes HIF1A-As2 expression via the induction of MYC, suggesting HIF1A-As2 and MYC form a double-regulatory loop to strengthen cell proliferation and tumor metastasis in lung cancer. Inhibition of HIF1A-As2 by LNA GapmeR antisense oligonucleotides (ASO) significantly improves sensitization to 10058-F4 (a MYC-specific inhibitor) and cisplatin treatment in PDX and KRASLSLG12D-driven lung tumors, respectively.

Environmentally Friendly and Broad-Spectrum Antibacterial Poly(hexamethylene guanidine)-Modified Polypropylene and Its Antifouling Application.

Biological fouling is one of the main reasons that limits the application of traditional polypropylene (PP) fishing nets in aquaculture. Here, a new environmentally friendly and broad-spectrum antibacterial agent called cationic poly(hexamethylene guanidine) (PHMG) was grafted onto PP molecular chains via permanent chemical bonding to inhibit the biological fouling. The antibacterial monofilaments were obtained by blending different contents of PP-g-PHMG with PP by melt spinning. FTIR results found PHMG to be stably present in the mixed monofilaments after high-temperature melt spinning molding. The crystallinity, relaxation behavior, mechanical properties, water absorptivity, and antibacterial and antifouling efficiencies of the PP-g-PHMG/PP blends were strongly dependent on PP-g-PHMG. The crystallinity increased with increasing PP-g-PHMG content. Adding PP-g-PHMG improved the breaking strength, knotting strength, and elongation at the break for all ratios of PP-g-PHMG/PP blends. However, the water absorption caused by PHMG is low, ranging between 2.48% and 3.45% for the PP-g-PHMG/PP monofilaments. The monofilaments showed excellent nonleaching antimicrobial activities against Staphylococcus aureus and Escherichia coli. The electrostatic adsorption of the negatively charged bacteria and the destruction of their cell membrane allowed the growth inhibition to reach 99.69% with a PP-g-PHMG content of 40%. The marine fish farming experiment also showed a long-term antifouling effect.

Effects of Surgical Timing of Facial Nerve Decompression for Patients With Severe Bell's Palsy.

Context: Bell's palsy is a form of idiopathic, facial nerve palsy. Initial treatment includes the use of oral corticosteroids and/or antiviral agents, but facial paralysis may persist. Some surgeons suggest that surgical decompression of the facial nerve can be a beneficial, but the optimal surgical approach, extent of nerve decompression, and timing of surgery remain unclear. Objective: This study intended to evaluate the efficacy of delayed, facial nerve decompression for severe Bell's palsy (BP) and to explore the relationship of opportunity timing for operations, with postoperative recovery for facial nerve function. Design: The research team performed a retrospective study. Setting: The study took place at Beijing Tiantan Hospital of Capital Medical University in Beijing, China. Participants: Participants were 45 patients who had been diagnosed with BP between 2015 and 2021 and who had undergone facial nerve decompression using the transmastoid approach, between 30 and 180 days after the onset of BP. According to the operation's timing, the research team divided the participants into three groups, consisting of participants who underwent surgery: (1) at 30-60-days after BP onset-19 participants, (2) at 61-90 days after BP onset-18 participants, and (3) at more than 90 days after BP onset-8 participants. Outcome Measures: The research team: (1) analyzed participants' demographic and preoperative and postoperative clinical characteristics, (2) compared the surgical outcomes with participants' House-Brackmann (HB) scales, and (3) analyzed the factors affecting the recovery of facial nerve function using logistic regression. Results: Decompression surgery was effective for 29 participants (64.4%), with similar rates for participants who underwent surgery after 30-60 days (73.7%) and 61-90 days (77.8%), but the surgery' success was significantly higher for those groups than for participants who underwent surgery after >90 days (12.5%), with P = .008 and P = .003, respectively. Multivariate logistic regression analysis showed that disease duration was the only factor significantly associated with the effectiveness of surgery (odds ratio = 120.337; 95% confidence interval 2.997-4832.267, P = .011). Conclusions: For patients with severe Bell's palsy with ineffective conservative treatment, surgery performed 30 to 90 days after the onset of paralysis can have therapeutic benefits, whereas surgery performed after 3 months is relatively ineffective.

Multikink quantile regression for longitudinal data with application to progesterone data analysis.

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multikink quantile regression model for longitudinal data analysis. It relaxes the linearity condition and assumes different regression forms in different regions of the domain of the threshold covariate. In this paper, we first propose a multikink quantile regression for longitudinal data. Two estimation procedures are proposed to estimate the regression coefficients and the kink points locations: one is a computationally efficient profile estimator under the working independence framework while the other one considers the within-subject correlations by using the unbiased generalized estimation equation approach. The selection consistency of the number of kink points and the asymptotic normality of two proposed estimators are established. Second, we construct a rank score test based on partial subgradients for the existence of the kink effect in longitudinal studies. Both the null distribution and the local alternative distribution of the test statistic have been derived. Simulation studies show that the proposed methods have excellent finite sample performance. In the application to the longitudinal progesterone data, we identify two kink points in the progesterone curves over different quantiles and observe that the progesterone level remains stable before the day of ovulation, then increases quickly in 5 to 6 days after ovulation and then changes to stable again or drops slightly.

A volatile basic nitrogens-responsive tag based on aggregation-induced emission luminogen for real-time monitoring and in situ visualization of salmon freshness.

Given the ever-growing food safety issues, the establishment of efficient approaches for monitoring food freshness attracts increasing attention. Volatile basic nitrogens (VBNs), including biogenic amines and ammonia, serve as an important biomarker for monitoring food freshness. In this study, a novel VBNs-responsive tag using glutathione capped copper nanoclusters (GSH-CuNCs) aggregates was developed as a fluorescent probe for in situ and real-time visual monitoring of salmon freshness, and the prepared GSH-CuNCs aggregates were characterized and their sensitivity for detecting VBNs using biogenic amines and ammonium hydroxide as the model targets was evaluated. Based on their remarkable response in liquid status, the GSH-CuNCs aggregates-based tag as a gas indicator was then fabricated, which exhibited visible colour changes under UV light as a function of ammonia vapour concentrations. More importantly, through exploring the sensing mechanism of GSH-CuNCs aggregates in VBNs detection, the existence of ligand exchange between the GSH-CuNCs and VBNs was observed and verified for the first time, confirming the effect of hydrogen bonding reported in the literature. Moreover, the GSH-CuNCs aggregates-based tag was applied for quantitative analysis of salmon freshness during different storage periods, which was validated by the standard method for detection of total VBNs in salmon. In addition, a colour card was developed and its feasibility for application in monitoring salmon freshness was validated, which could be used for consumers to obtain the freshness level directly with the naked eye, demonstrating the feasibility of the fabricated tag for real-time and visual monitoring of salmon freshness, thus showing great potentials for its practical applications in the food industry.

Influence of TIG and Laser Welding Processes of Fe-10Cr-4Al-RE Alloy Cracks Overlayed on 316L Steel Plate.

In this paper, the possibility of applying different welding strategies to overlay an FeCrAl layer against corrosion from heavy liquid metal on a plain plate made of 316L austenitic stainless steel was investigated. This technology could be used in manufacturing the main vessel of CiADS, which may be considered as a more economic and feasible solution than production with the corrosion-resistant FeCrAl alloy directly. The main operational parameters of the laser welding process, including laser power, weld wire feeding speed, diameter of the welding wire, etc., were adjusted correspondingly to the optimized mechanical properties of the welded plate. After performing the standard nuclear-grade bending tests, it can be preliminarily confirmed that the low-power pulse laser with specific operational parameters and an enhanced cooling strategy will be suitable to surface an Fe-10Cr-4Al-RE layer with a thickness of approximately 1 mm on a 40 mm-thick 316L stainless steel plate, thanks to the upgraded mechanical properties incurred by refined grains with a maximum size of around 300 µm in the welded layer.

Rapid structural discrimination of IgG antibodies by multicharge-state collision-induced unfolding.

Immunoglobulin G (IgG) antibodies are an important class of biotherapeutics that target various diseases, such as cancers, neurodegenerative disorders, and autoimmune diseases, yet rapid discrimination of IgG antibodies remains a great challenge due to heterogeneity, flexibility, and large size. Herein, we demonstrate a simplified multicharge-state collision-induced unfolding (CIU) method for rapid differentiation of four IgG isotypes that differ in terms of the numbers and patterns of disulfide bonds, bypassing tedious single charge-state selection in advance. The results presented herein reveal that gas-phase unfolding behaviors have a strong dependence on charge states outside IgG surfaces; therefore, multicharge-state CIU analysis of IgG subtypes could offer a great opportunity to gain deeper insights into their gas-phase structural differentiation. The full discrimination of IgG antibody isoforms that possess different disulfide bond numbers and even subtle disulfide bonding patterns can be achieved based on their charge-dependent gas-phase unfolding behaviors and root-mean square deviation in CIU difference spectra. Taken together, the incorporation of all charge states observed in a native ion mobility-mass spectrometry (IM-MS) experiment to CIU analysis could make this strategy sensitive to more subtle structural discrepancies, facilitating the rapid discrimination and evaluation of innovative structurally similar biotherapeutic candidates with unexplored functions.

The transotic approach for vestibular schwannoma: indications and results.

To analyze retrospectively the indications and the results obtained with the transotic approach in a series of patients with vestibular schwannoma. The study included 36 patients from 2007 to 2013 with a vestibular schwannoma that was removed with a transotic approach. All patients underwent preoperative pure tone audiometry, evaluation of facial function and CT and MR imaging. All patients having (1) a hearing loss of more than 50 dB, (2) an average tumor size of 2.7 cm (range 0.5-5.0 cm) and (3) signs of a contracted mastoid (high jugular bulb, anteriorly located sigmoid sinus, low middle cranial fossa, or reduced pneumatization) were selected. The tumor was totally removed in 34 and near-totally removed in 2 patients. The facial nerve was preserved in all patients. The postoperative facial function after 6 weeks was House-Brackmann grade I in 7, grade II in 27, and grade III in 2 patients. All patients presented postoperatively with unilateral total deafness. Seven patients experienced transitory postoperative imbalance. There were two patients who required revision surgery, one with intracranial hemorrhage and another with a CSF leak. There were no deaths and no severe complications such as hemiplegia or intracranial infections. The transotic approach has proven to be of value for the removal of vestibular schwannomas up to 5.0 cm in the presence of temporal bone contraction. Hearing was not preserved; however, other clinical outcomes were very favorable, including high rates of total tumor removal and facial nerve preservation, and low rates of complications.

Mass spectrometric analysis of mono- and multi-phosphopeptides by selective binding with NiZnFe2O4 magnetic nanoparticles.

Selective isolation of mono- and multi-phosphorylated peptides is important for understanding how a graded protein kinase or phosphatase signal can precisely modulate the on and off states of signal transduction pathways. Here we report that metal ions at exposed octahedral sites of nano-ferrites, including Fe3O4, NiFe2O4, ZnFe2O4 and NiZnFe2O4, have distinctly selective coordination abilities with mono- and multi- phosphopeptides. Due to their intrinsic magnetic properties and high surface area to volume ratios, these nanoparticles enable the rapid isolation of mono- and multi-phosphopeptides by an external magnetic field. Model phosphoprotein α-casein and two synthesized mono- and di-phosphopeptides have been chosen for proof-of-principle demonstrations, and these nanoparticles have also been applied to phosphoproteome profiling of zebrafish eggs. It is shown that NiZnFe2O4 is highly selective for multi-phosphopeptides. In contrast, Fe3O4, NiFe2O4 and ZnFe2O4 can bind with both mono- and multi-phosphopeptides with relatively stronger affinity towards mono-phosphopeptides.

Comparison of Bayesian model averaging and stepwise methods for model selection in logistic regression.

Logistic regression is the standard method for assessing predictors of diseases. In logistic regression analyses, a stepwise strategy is often adopted to choose a subset of variables. Inference about the predictors is then made based on the chosen model constructed of only those variables retained in that model. This method subsequently ignores both the variables not selected by the procedure, and the uncertainty due to the variable selection procedure. This limitation may be addressed by adopting a Bayesian model averaging approach, which selects a number of all possible such models, and uses the posterior probabilities of these models to perform all inferences and predictions. This study compares the Bayesian model averaging approach with the stepwise procedures for selection of predictor variables in logistic regression using simulated data sets and the Framingham Heart Study data. The results show that in most cases Bayesian model averaging selects the correct model and out-performs stepwise approaches at predicting an event of interest.