[Determination of the derivatization reactivity between α/ß-dicarbonyl compounds and standard citrullinated peptides based on matrix-assisted laser desorption ionization-time-of-flight mass spectrometry].

Protein citrullination is an irreversible post-translational modification process regulated by peptidylarginine deiminases (PADs) in the presence of Ca2+. This process is closely related to the occurrence and development of autoimmune diseases, cancers, neurological disorders, cardiovascular and cerebrovascular diseases, and other major diseases. The analysis of protein citrullination by biomass spectrometry confronts great challenges owing to its low abundance, lack of affinity tags, small mass-to-charge ratio change, and susceptibility to isotopic and deamidation interferences. The methods commonly used to study the protein citrullination mainly involve the chemical derivatization of the urea group of the guanine side chain of the peptide to increase the mass-to-charge ratio difference of the citrullinated peptide. Affinity-enriched labels are then introduced to effectively improve the sensitivity and accuracy of protein citrullination by mass spectrometry. 2,3-Butanedione or phenylglyoxal compounds are often used as derivatization reagents to increase the mass-to-charge ratio difference of the citrullinated peptide, and the resulting derivatives have been observed to contain α-dicarbonyl structures. To date, however, no relevant studies on the reactivity of dicarbonyl compounds with citrullinated peptides have been reported. In this study, we determined whether six α-dicarbonyl and two ß-dicarbonyl compounds undergo derivatization reactions with standard citrullinated peptides using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Among the α-dicarbonyl compounds, 2,3-butanedione and glyoxal reacted efficiently with several standard citrullinated peptides, but yielded a series of by-products. Phenylglyoxal, methylglyoxal, 1,2-cyclohexanedione, and 1,10-phenanthroline-5,6-dione also derivated efficiently with standard citrullinated peptides, generating a single derivative. Thus, a new derivatization method that could yield a single derivative was identified. Among the ß-dicarbonyl compounds, 1,3-cyclohexanedione and 2,4-pentanedione successfully reacted with the standard citrullinated peptides, and generated a single derivative. However, their reaction efficiency was very low, indicating that the ß-dicarbonyl compounds are unsuitable for the chemical derivatization of citrullinated peptides. The above results indicate that the α-dicarbonyl structure is necessary for realizing the efficient and specific chemical derivatization of citrullinated peptides. Moreover, the side chains of the α-dicarbonyl structure determine the structure of the derivatives, derivatization efficiency, and generation (or otherwise) of by-products. Therefore, the specific enrichment and precise identification of citrullinated peptides can be achieved by synthesizing α-dicarbonyl structured compounds containing affinity tags. The proposed method enables the identification of citrullinated proteins and their modified sites by MS, thereby providing a better understanding of the distribution of citrullinated proteins in different tissues. The findings will be beneficial for studies on the mechanism of action of citrullinated proteins in a variety of diseases.

Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.

PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status. METHODS: Ultrasound images from 528 cases of female breast cancer at the Affiliated Hospital of Xiangnan University and 232 cases of female breast cancer at the Affiliated Rehabilitation Hospital of Xiangnan University were selected for this study. We utilized deep learning methods to automatically outline the gross tumor volume and perform habitat clustering. Subsequently, habitat sub-regions were extracted to identify radiomics features and underwent feature engineering using the L1,2-norm. A prediction model for the Ki-67 status of breast cancer patients was then developed using a FCNN. The model's performance was evaluated using accuracy, area under the curve (AUC), specificity (Spe), positive predictive value (PPV), negative predictive value (NPV), Recall, and F1. In addition, calibration curves and clinical decision curves were plotted for the test set to visually assess the predictive accuracy and clinical benefit of the models. RESULT: Based on the feature engineering using the L1,2-norm, a total of 9 core features were identified. The predictive model, constructed by the FCNN model based on these 9 features, achieved the following scores: ACC 0.856, AUC 0.915, Spe 0.843, PPV 0.920, NPV 0.747, Recall 0.974, and F1 0.890. Furthermore, calibration curves and clinical decision curves of the validation set demonstrated a high level of confidence in the model's performance and its clinical benefit. CONCLUSION: Habitat clustering of ultrasound images of breast cancer is effectively supported by the combined implementation of the L1,2-norm and FCNN algorithms, allowing for the accurate classification of the Ki-67 status in breast cancer patients.

Facile Access to Branched Multispecific Proteins.

Approaches that leverage orthogonal chemical reactions to generate protein-protein conjugates have expanded access to bespoke chimeras. Although the literature is replete with examples of the semisynthesis of bispecific proteins, few methods exist for the semisynthesis of protein conjugates of higher complexity (i.e., greater than two-protein fusions). The recent emergence of trispecific cell engagers for immune cell redirection therapies necessitates the development of chemical methods for the construction of trispecific proteins that would otherwise be inaccessible via natural protein synthesis. Here, we demonstrate that 3-bromo-5-methylene pyrrolone (3Br-5MP) can be used to effect the facile chemical synthesis of trispecific peptides and proteins with exquisite control over the addition of each monomer. The multimeric complexes maintain epitope functionality both in human cells and upon immobilization. We anticipate that facile access to trispecific proteins using this 3Br-5MP will have broad utility in basic science research and will quicken the pace of research to establish novel, multimeric immune cell redirection therapies.

Automatic breast ultrasound (ABUS) tumor segmentation based on global and local feature fusion.

Accurate segmentation of tumor regions in automated breast ultrasound (ABUS) images is of paramount importance in computer-aided diagnosis system. However, the inherent diversity of tumors and the imaging interference pose great challenges to ABUS tumor segmentation. In this paper, we propose a global and local feature interaction model combined with graph fusion (GLGM), for 3D ABUS tumor segmentation. In GLGM, we construct a dual branch encoder-decoder, where both local and global features can be extracted. Besides, a global and local feature fusion module is designed, which employs the deepest semantic interaction to facilitate information exchange between local and global features. Additionally, to improve the segmentation performance for small tumors, a graph convolution-based shallow feature fusion module is designed. It exploits the shallow feature to enhance the feature expression of small tumors in both local and global domains. The proposed method is evaluated on a private ABUS dataset and a public ABUS dataset. For the private ABUS dataset, the small tumors (volume smaller than 1 cm3) account for over 50% of the entire dataset. Experimental results show that the proposed GLGM model outperforms several state-of-the-art segmentation models in 3D ABUS tumor segmentation, particularly in segmenting small tumors.

Attention decoupled contrastive learning for semi-supervised segmentation method based on data augmentation.

Objective.Deep learning algorithms have demonstrated impressive performance by leveraging large labeled data. However, acquiring pixel-level annotations for medical image analysis, especially in segmentation tasks, is both costly and time-consuming, posing challenges for supervised learning techniques. Existing semi-supervised methods tend to underutilize representations of unlabeled data and handle labeled and unlabeled data separately, neglecting their interdependencies.Approach.To address this issue, we introduce the Data-Augmented Attention-Decoupled Contrastive model (DADC). This model incorporates an attention decoupling module and utilizes contrastive learning to effectively distinguish foreground and background, significantly improving segmentation accuracy. Our approach integrates an augmentation technique that merges information from both labeled and unlabeled data, notably boosting network performance, especially in scenarios with limited labeled data.Main results.We conducted comprehensive experiments on the automated breast ultrasound (ABUS) dataset and the results demonstrate that DADC outperforms existing segmentation methods in terms of segmentation performance.

The role of Testis-Specific Protein Y-encoded-Like 2 in kidney injury.

Renal ischemia-reperfusion injury (IRI) is a major cause of acute kidney injury (AKI). Recent findings suggest that Testis-Specific Protein Y-encoded-Like 2 (TSPYL2) plays a fibrogenic role in diabetes-associated renal injury. However, the role of TSPYL2 in IRI-induced kidney damage is not entirely clear. In this study, we found that the expression of TSPYL2 was upregulated in a mouse model of AKI and in the hypoxia/reoxygenation (H/R) cell model. Knockdown of TSPYL2 attenuated kidney injury after IRI. More specifically, the knockdown of TSPYL2 or aminocarboxymuconate-semialdehyde decarboxylase (ACMSD) alleviated renal IRI-induced mitochondrial dysfunction and oxidative stress in vitro and in vivo. Further investigation showed that TSPYL2 regulated SREBP-2 acetylation by inhibiting SIRT1 and promoting p300 activity, thereby promoting the transcriptional activity of ACMSD. In conclusion, TSPYL2 was identified as a pivotal regulator of IRI-induced kidney damage by activating ACMSD, which may lead to NAD+ content and the damaging response in the kidney.

Microscopic Electric Rotary Grinding of Plaques Combined with Graft Repair in the Management of Peyronie's Disease.

Peyronie's Disease (PD) is clinically characterized by the development of localized fibrous plaques, primarily on the tunica albuginea, especially on the dorsal area of the penis. These plaques are the hallmark feature of this condition, resulting in penile curvature, deformity, and painful erections for affected individuals. Although various nonsurgical treatment options exist, their overall effectiveness is limited. As a result, surgical intervention has become the ultimate choice for patients with severe penile curvature deformities and associated erectile dysfunction. Our research team has successfully employed a combined approach involving microscopic electric rotary grinding of the fibrous plaques and the use of tunica vaginalis or bovine pericardium as graft materials for the repairing of the defects of tunica albuginea in the treatment of PD. This approach has consistently yielded highly satisfactory results regarding the restoration of penile shape, with excellent cosmetic results and significantly improved sexual satisfaction. This protocol aims to present a comprehensive surgical management strategy utilizing electric rotary grinding of the plaques and repairing the defects of tunica albuginea by using the tunica vaginalis, which represents an optimal surgical strategy for treating PD.

Large-scale Prospective Validation Study of a Multiplex RNA Urine Test for Noninvasive Detection of Upper Tract Urothelial Carcinoma.

BACKGROUND: Current approaches for diagnosis and monitoring of upper tract urothelial carcinoma (UTUC) are often invasive, costly, and not efficient for early-stage and low-grade tumors. OBJECTIVE: To validate a noninvasive urine-based RNA test for accurate UTUC diagnosis. DESIGN, SETTING, AND PARTICIPANTS: Urine samples were prospectively collected from 61 patients with UTUC and 99 controls without urothelial carcinomas, in five clinical centers between October 2022 and August 2023 prior to any invasive test (cystoscope or ureteroscope) or treatment. All samples were analyzed with a urine-based RNA test composed of eight genes (CA9, CCL18, ERBB2, IGF2, MMP12, PPP1R14D, SGK2, and SWINGN). The test results were presented with a risk score for each participant, which was applied to categorize patients into low- or high-risk groups. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The diagnosis of UTUC was based mainly on preoperative radiological examination criteria and confirmed by postoperative pathological results. The recursive feature elimination and support vector machine algorithms, χ2, and Student t test were used. RESULTS AND LIMITATIONS: The eight-gene urine test accurately detected UTUC patients and controls with an area under the curve (AUC) of 0.901 in a single-center testing cohort (n = 93) and an AUC of 0.926 in a multicenter clinical validation cohort (n = 66). In the merged validation cohort, the eight-gene urine test achieved high sensitivity of 90.16%, specificity of 88.89%, and overall accuracy of 89.38%. Remarkably, excellent performance was achieved in 11 low-grade UTUC patients with accuracy of 100%. However, this study collected the urine of UTUC patients only at a single preoperative time point and did not perform continuous tests during the pathological process of UTUC in the surveillance population. CONCLUSIONS: Our results demonstrated that the eight-gene urine test can differentiate accurately between UTUC and other urological diseases with high sensitivity and specificity. In clinical practice, it may be used for identifying UTUC patients effectively, leading to reduced reliance on ureteroscopy and blind surgery. PATIENT SUMMARY: In this study, we investigated a multiplex RNA urine test for noninvasive upper tract urothelial carcinoma (UTUC) diagnosis before treatment. We found that the risk scores derived from the multiplex RNA urine test differed significantly between UTUC patients and corresponding controls.

Extraction, purification, structural characteristics and biological properties of the polysaccharides from Armillaria mellea (Vahl) P. Kumm.: A review.

Armillaria mellea (Vahl) P. Kumm. is a well-known homoeopathic plant with medicinal and culinary uses. Modern phytochemical researchers have successfully extracted and purified over 40 types of A. mellea polysaccharides (AMPs) from the fruiting bodies, hyphae and fermentation broth of A. mellea, and some of them have been analyzed and identified by their chemical structures. The impressive biological activity of these polysaccharides has been recognized by scientists worldwide. Many studies show that AMPs have remarkable antioxidant, anti-diabetic, anti-tumor, anti-inflammatory, immunoregulatory, hypolipidemic, thrombectomy, anti-aging, pulmonary protective, hepatic protective, anti-Alzheimer's properties, etc. However, the current understanding of the relationships between their chemical structure and biological activity, toxicological effects and pharmacokinetics remains limited. This article provides a systematic review of the research conducted over the past decades on the extraction and purification methods, structural characteristics, biological activity and mechanism of action of AMPs. The aim is to provide a research base that will benefit the future application of AMPs as therapeutic drugs and functional foods, and also provide insights for the further development of AMPs.

ABUS tumor segmentation via decouple contrastive knowledge distillation.

Objective.In recent years, deep learning-based methods have become the mainstream for medical image segmentation. Accurate segmentation of automated breast ultrasound (ABUS) tumor plays an essential role in computer-aided diagnosis. Existing deep learning models typically require a large number of computations and parameters.Approach. Aiming at this problem, we propose a novel knowledge distillation method for ABUS tumor segmentation. The tumor or non-tumor regions from different cases tend to have similar representations in the feature space. Based on this, we propose to decouple features into positive (tumor) and negative (non-tumor) pairs and design a decoupled contrastive learning method. The contrastive loss is utilized to force the student network to mimic the tumor or non-tumor features of the teacher network. In addition, we designed a ranking loss function based on ranking the distance metric in the feature space to address the problem of hard-negative mining in medical image segmentation.Main results. The effectiveness of our knowledge distillation method is evaluated on the private ABUS dataset and a public hippocampus dataset. The experimental results demonstrate that our proposed method achieves state-of-the-art performance in ABUS tumor segmentation. Notably, after distilling knowledge from the teacher network (3D U-Net), the Dice similarity coefficient (DSC) of the student network (small 3D U-Net) is improved by 7%. Moreover, the DSC of the student network (3D HR-Net) reaches 0.780, which is very close to that of the teacher network, while their parameters are only 6.8% and 12.1% of 3D U-Net, respectively.Significance. This research introduces a novel knowledge distillation method for ABUS tumor segmentation, significantly reducing computational demands while achieving state-of-the-art performance. The method promises enhanced accuracy and feasibility for computer-aided diagnosis in diverse imaging scenarios.

Feasibility and accuracy of a task-autonomous robot for zygomatic implant placement.

STATEMENT OF PROBLEM: Zygomatic implants (ZIs) should be placed accurately as planned preoperatively to minimize complications and maximize the use of the remaining bone. Current digital techniques such as static guides and dynamic navigation are affected by human error; therefore, new techniques are required to improve the accuracy of ZI placement. PURPOSE: The purpose of this clinical study was to assess the feasibility and accuracy of a task-autonomous robot for ZI placement. MATERIAL AND METHODS: Patients indicated for ZI placement were enrolled, and an appropriate surgical positioning piece was selected based on the presence of natural teeth in the maxilla. Preoperative cone beam computed tomography (CBCT) scanning was performed with the surgical positioning piece, and virtual implant design and socket preparation procedures were initiated. Implant socket preparation and placement were automatically performed by the robot according to the preoperative plan under the supervision of the surgeon. Postoperative CBCT scanning was performed to evaluate deviations between the virtual and actual implants. All quantitative data were expressed as standardized descriptive statistics (mean, standard deviation, minimum, maximum, and 95% confidence interval [CI]). The Shapiro-Wilk test was used to assess the normal distribution of all variables (α=.05). RESULTS: Six participants were enrolled, and 8 ZIs were inserted. No intraoperative or postoperative complications were observed. Robotic ZI placement showed a global coronal deviation of 0.97 mm (95% CI: 0.55 to 1.39 mm), a global apical deviation of 1.27 mm (95% CI: 0.71 to 1.83 mm), and an angular deviation of 1.48 degrees (95% CI: 0.97 to 2.00 degrees). CONCLUSIONS: Task-autonomous robots can be used for ZI placement with satisfactory accuracy. Robotic ZI surgery can be an alternative to static guidance and dynamic navigation to improve the accuracy of implant placement.

Semi-autonomous two-stage dental robotic technique for zygomatic implants: An in vitro study.

OBJECTIVE: To assess the feasibility and accuracy of a semi-autonomous two-stage dental robotic technique for zygomatic implants. METHODS: Twenty-six zygomatic implants were designed and randomly divided into two groups using 10 three-dimensionally printed resin models with severe maxillary atrophy. In one group, the conventional drilling technique was used, in the other group, the drilling process for the alveolar ridge section (first stage) was completed, after which drilling for the zygoma section (second stage) was done. Based on preoperative planning combined with postoperative cone-beam computed tomography (CBCT), coronal, apical, depth, and angle deviations were measured. Zygomatic implant placement technique-related deviations (sinus slot, intrasinus, and extrasinus) were also recorded and analyzed. RESULTS: The two-stage technical group's coronal, apical, depth, and angle deviations were 0.57 ± 0.19 mm, 1.07 ± 0.48 mm, 0.30 ± 0.38 mm, and 0.91 ± 0.51°, respectively. The accuracy of the two-stage technique was significantly higher than that of the conventional one-stage technique (p < 0.05). The apical deviation in the intrasinus group was 1.12 ± 0.56 mm, which was significantly better than that in the other two groups (p < 0.05). The angle deviation in the sinus slot group was 1.96 ± 0.83°, which was significantly worse than that in the other two groups (p < 0.05). CONCLUSION: Using the semi-autonomous two-stage dental robotic technique for zygomatic implants is feasible and is more accurate than using the conventional one-stage technique. CLINICAL SIGNIFICANCE: The two-stage technique enabled the semi-autonomous robot to overcome the mouth-opening restriction for zygomatic implants and improved accuracy.

Efficient TNBC immunotherapy by dual reprogramming tumor-infiltrating dendritic cells and tumor-associated macrophages with stimulus-responsive miR155 nanocomplexes.

Triple negative breast cancer (TNBC) remains to be a formidable adversary with high mortality and unfavorable prognosis. Tumor microenvironment comprises of various constituents, among them, tumor infiltrating dendritic cells (TIDCs) and tumor-associated macrophages (TAMs) which have been recognized as pivotal factors responsible for mediating immune responses. Overcoming the refractory properties of TIDCs and TAMs is critical for inducing a robust and sustained immune response against cancer cells. In this study, pH/ROS-responsive microRNA-155 (miR155) nanocomplexes (MiR@PCPmP NPs) were developed to reprogram TIDCs and TAMs for efficient TNBC immunotherapy. This nanoplatform was based on a pH/ROS cleavable copolymer of poly(ethylene glycol)-carboxydimethyl maleate-poly(ethyleneimine)-peroxalate ester-poly(ε-caprolactone) grafted with mannose moieties (PEG-CDM-PEI[Man]-ox-PCL) which self-assembled with miRNA to form nanocomplexes. In the tumor microenvironment, the nanocomplexes showed selective cellular uptake by TIDCs and TAMs through PEG detachment and mannose exposure, followed by efficient endosomal escape, cytosolic miR155 release, and the dual-reprogramming of TIDCs and TAMs. Our results showed that MiR@PCPmP NPs significantly improved antitumor immune responses with highly infiltrating CD8+ T cells while restraining immunosuppressive components in 4T1 tumor-bearing mice. Furthermore, the nanoparticles effectively suppressed both primary tumors and pulmonary metastatic nodules without obvious systemic toxicity. This research highlights the potential of dual-reprogramming of TIDCs and TAMs with the miR155 nanocomplexes as a promising strategy for TNBC immunotherapy, with potential for translation to other cancers with a similar microenvironment.

Autonomous dental robotic surgery for zygomatic implants: A two-stage technique.

Zygomatic implants (ZIs) can be a treatment option for patients with severe atrophy in the maxilla, but deviation during ZI placement could lead to serious complications. Surgical guides and dynamic navigation have been used to improve the accuracy of ZI placement, but both techniques are subject to human error. A 2-stage technique is described that enabled an autonomous dental robot to overcome mouth-opening restrictions for ZI placement. The technique enables the complete digitalization of ZI placement, further improving the accuracy of the drilling process.

Immune responses and disease biomarker long-term changes following COVID-19 mRNA vaccination in a cohort of rheumatic disease patients.

Introduction: The longitudinal responses towards multiple doses of COVID-19 mRNA vaccines in patients with systemic autoimmune diseases remain incompletely understood. While observational studies suggested the safety of COVID-19 mRNA vaccines in rheumatic disease patients, laboratory evidence is lacking. Methods: Here we evaluated seroreactivity, clinical manifestions, and multiple disease biomarkers after 2 or 3 doses of COVID-19 mRNA vaccines in a cohort of patients with rheumatic diseases. Results: Most patients generated high SARS-CoV-2 spike-specific neutralizing antibodies comparable to those in healthy controls after 2 doses of mRNA vaccines. The antibody level declined over time but recovered after the third dose of the vaccine. Patients with systemic lupus erythematosus (SLE) or psoriatic arthritis (PsA) remained without significant flares post-vaccination. The changes in anti-dsDNA antibody concentration and expression of type I interferon (IFN) signature genes were highly variable but did not show consistent or significant increases. Frequency of double negative 2 (DN2) B cells remained largely stable. Discussion: Our data provide experimental evidences indicating the efficacy and safety of repeated COVID-19 mRNA vaccination in rheumatic disease patients.

Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation.

Background: Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosis of BLCA accurately, we evaluated the prognostic value of anoikis-associated genes in BLCA and constructed the best model to predict prognosis. Method: The BLCA transcriptome data were downloaded from TCGA and GEO databases, and genes with differential expression were selected and then clustered using non-negative matrix factorization (NMF). The genes with the most correlation with anoikis were screened and identified using univariate Cox regression, lasso regression, and multivariate Cox regression. The GEO dataset was used for external validation. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with receiver operating characteristic (ROC) curves. The immunotherapeutic significance of this risk score was assessed using the immune phenomenon score (IPS). IC50 values of predictive chemotherapeutic agents were calculated. Finally, we used RT-qPCR to determine the mRNA expression of four genes, CALR, FASN, CASP6, and RAD9A. Result: We screened 406 tumor samples and 19 normal tissue samples from the TCGA database. Based on anoikis-associated genes, we classified patients into two subtypes (C1 and C2) using NMF method. Subsequently, nine core genes were screened by multiple methods after analysis, which were used to construct risk profiles. The design of nomograms based on risk profiles and clinical variables, ROC, and calibration curves confirmed that the model could well have the ability to predict the survival of BLCA patients at 1, 3, and 5 years. By predicting the IC50 values of chemotherapeutic drugs, it was learned that the high-risk group (HRG) was more susceptible to paclitaxel, gemcitabine, and cisplatin, and the low-risk group (LRG) was more susceptible to veriparib and afatinib. Conclusion: In summary, the risk score of anoikis-associated genes can be applied as a predictor to predict the prognosis of BLCA in clinical practice.

In vitro knockdown of TsDNase II-7 suppresses Trichinella spiralis invasion into the host's intestinal epithelial cells.

Trichinella spiralis (T. spiralis) adult-specific deoxyribonuclease II-7 (TsDNase II-7), a member of the DNase II-like nuclease family with no DNase II activity, was identified in the excretory-secretory (ES) products of adult worms (AWs). However, its biological functions are still unclear. Our previous study revealed that TsDNase II-7 is located around the infection site in the intestinal tissue, speculating that it was involved in the T. spiralis invasion of host intestinal epithelial cells (IECs). This study aimed to use RNA interference to verify our speculation that TsDNase II-7 in 3-day old adult T. spiralis (Ad3) plays a role in intestinal invasion. TsDNase II-7-specific small interfering RNAs (siRNAs) were delivered into muscle larvae (MLs) to knockdown TsDNase II-7 expression by electroporation. Twenty-four hours later, the MLs transfected with 2 µM siRNA-841 exhibited decreased in TsDNase II-7 transcription and expression as compared to the control MLs. The knockdown of TsDNase II-7 expression did not affect ML viability, and the low expression of TsDNase II-7 still maintained in Ad3 recovered from TsDNase II-7-RNAi-ML infected mice, resulting in a weakened ability of Ad3 to invade intestinal epithelial cells (IECs). These results indicated that knockdown of TsDNase II-7 gene expression via RNA interference (RNAi) suppressed adult worm invasion and confirmed that TsDNase II-7 plays a crucial role during the intestinal phase of T. spiralis infections, which provided new candidate for vaccine development of T. spiralis.

Myd88 Signaling Is Involved in the Inflammatory Response in LPS-Induced Mouse Epididymitis and Bone-Marrow-Derived Dendritic Cells.

Epididymitis is an epididymal inflammation that may lead to male infertility. Dendritic cells (DCs) and myeloid differentiation primary response gene 88 (Myd88) were associated with epididymitis in rodents. However, the functions of Myd88 on epididymal DCs remain unclear. This study investigated the role of Myd88 in DCs for epididymitis. The Myd88 signaling pathway, phenotypes of DC subsets, and cytokines were investigated in lipopolysaccharide (LPS)-induced epididymitis in mice. CRISPR-Cas9 was used to knockout Myd88 in bone-marrow-derived dendritic cells (BMDCs) and immortalized mouse epididymal (DC2) cell line. In the vivo experiments, levels of the proinflammatory cytokines IL-1α, IL-6, IL-17A, TNF-α, IL-1ß, MCP-1, and GM-CSF, mRNA for MyD88 related genes, and the percentages of monocyte-derived DCs (Mo-DCs) were significantly elevated in mice with epididymitis. In the vitro experiments, LPS significantly promoted the apoptosis of BMDCs. In addition, the concentration of inflammatory cytokines in BMDCs and DC2s were increased in the LPS group, while decreasing after the knockout of Myd88. These findings indicate that Myd88 on DCs is involved in the inflammation of epididymitis in mice, which may be a potential target for better strategies regarding the treatment of immunological male infertility.

Autonomous robotic surgery for zygomatic implant placement and immediately loaded implant-supported full-arch prosthesis: a preliminary research.

OBJECTIVES: A patient with extensive atrophy of the alveolar ridge in the posterior portion of the maxilla was selected to complete an experimental and clinical case of the robotic zygomatic implant to investigate the viability of an implant robotic system in clinical use. METHODS: The preoperative digital information was collected, and the implantation position and personalized optimization marks needed for robot surgery were designed in advance in a repair-oriented way. The resin models and marks of the patient's maxilla and mandible are all printed in 3D. Custom-made special precision drills and handpiece holders for robotic zygomatic implants were used to perform model experiments and compare the accuracy of the robotic zygomatic implant group (implant length = 52.5 mm, n = 10) with the alveolar implant group (implant length = 18 mm, n = 20). Based on the results of extraoral experiments, a clinical case of robotic surgery for zygomatic implant placement and immediate loading of implant-supported full arch prosthesis was carried out. RESULTS: In the model experiment, the zygomatic implant group reported an entry point error of 0.78 ± 0.34 mm, an exit point error of 0.80 ± 0.25 mm, and an angle error of 1.33 ± 0.41degrees. In comparison, the alveolar implant group (control group) reported an entry point error of 0.81 ± 0.24 mm, an exit point error of 0.86 ± 0.32 mm, and an angle error of 1.71 ± 0.71 degrees. There was no significant difference between the two groups (p > 0.05). In clinical cases, the average entry point error of two zygomatic implants is 0.83 mm, the average exit point error is 1.10 mm and the angle error is 1.46 degrees. CONCLUSIONS: The preoperative planning and surgical procedures developed in this study provide enough accuracy for robotic zygomatic implant surgery, and the overall deviation is small, which is not affected by the lateral wall deviation of maxillary sinus.