A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts.

Predicting interactions between microbes and hosts plays critical roles in microbiome population genetics and microbial ecology and evolution. How to systematically characterize the sophisticated mechanisms and signal interplay between microbes and hosts is a significant challenge for global health risks. Identifying microbe-host interactions (MHIs) can not only provide helpful insights into their fundamental regulatory mechanisms, but also facilitate the development of targeted therapies for microbial infections. In recent years, computational methods have become an appealing alternative due to the high risk and cost of wet-lab experiments. Therefore, in this study, we utilized rich microbial metagenomic information to construct a novel heterogeneous microbial network (HMN)-based model named KGVHI to predict candidate microbes for target hosts. Specifically, KGVHI first built a HMN by integrating human proteins, viruses and pathogenic bacteria with their biological attributes. Then KGVHI adopted a knowledge graph embedding strategy to capture the global topological structure information of the whole network. A natural language processing algorithm is used to extract the local biological attribute information from the nodes in HMN. Finally, we combined the local and global information and fed it into a blended deep neural network (DNN) for training and prediction. Compared to state-of-the-art methods, the comprehensive experimental results show that our model can obtain excellent results on the corresponding three MHI datasets. Furthermore, we also conducted two pathogenic bacteria case studies to further indicate that KGVHI has excellent predictive capabilities for potential MHI pairs.

Predictive Value of Jugulo-omohyoid Lymph Nodes in Lateral Lymph Node Metastasis of Papillary Thyroid Cancer.

BACKGROUND: Jugulo-omohyoid lymph nodes (JOHLN) metastasis has proven to be associated with lateral lymph node metastasis (LLNM). This study aimed to reveal the clinical features and evaluate the predictive value of JOHLN in PTC to guide the extent of surgery. METHODS: A total of 550 patients pathologically diagnosed with PTC between October 2015 and January 2020, all of whom underwent thyroidectomy and lateral lymph node dissection, were included in this study. RESULTS: Thyroiditis, tumor location, tumor size, extra-thyroidal extension, extra-nodal extension, central lymph node metastasis (CLNM), and LLMM were associated with JOHLN. Male, upper lobe tumor, multifocality, extra-nodal extension, CLNM, and JOHLN metastasis were independent risk factors from LLNM. A nomogram based on predictors performed well. Nerve invasion contributed the most to the prediction model, followed by JOHLN metastasis. The area under the curve (AUC) was 0.855, and the p-value of the Hosmer-Lemeshow goodness of fit test was 0.18. Decision curve analysis showed that the nomogram was clinically helpful. CONCLUSION: JOLHN metastasis could be a clinically sensitive predictor of further LLM. A high-performance nomogram was established, which can provide an individual risk assessment of LNM and guide treatment decisions for patients.

Distinct risk factors of lateral lymph node metastasis in patients with papillary thyroid cancer based on age stratification.

INTRODUCTION: Studies have revealed that age is associated with the risk of lateral lymph node metastasis (LLNM) in papillary thyroid cancer (PTC). This study aimed to identify the optimal cut point of age for a more precise prediction model of LLNM and to reveal differences in risk factors between patients of distinct age stages. METHODS: A total of 499 patients who had undergone thyroidectomy and lateral neck dissection (LND) for PTC were enrolled. The locally weighted scatterplot smoothing (LOWESS) curve and the 'changepoint' package were used to identify the optimal age cut point using R. Multivariate logistic regression analysis was performed to identify independent risk factors of LLNM in each group divided by age. RESULTS: Younger patients were more likely to have LLNM, and the optimal cut points of age to stratify the risk of LLNM were 30 and 45 years old. Central lymph node metastasis (CLNM) was a prominent risk factor for further LNM in all patients. Apart from CLNM, sex(p = 0.033), tumor size(p = 0.027), and tumor location(p = 0.020) were independent predictors for patients younger than 30 years old; tumor location(p = 0.013), extra-thyroidal extension(p < 0.001), and extra-nodal extension(p = 0.042) were independent risk factors for patients older than 45 years old. CONCLUSIONS: Our study could be interpreted as an implication for a change in surgical management. LND should be more actively performed when CLNM is confirmed; for younger patients with tumors in the upper lobe and older patients with extra-thyroidal extension tumors, more aggressive detection of the lateral neck might be considered.

HMGB1 mediates synaptic loss and cognitive impairment in an animal model of sepsis-associated encephalopathy.

BACKGROUND: Microglial activation-mediated neuroinflammation is one of the essential pathogenic mechanisms of sepsis-associated encephalopathy (SAE). Mounting evidence suggests that high mobility group box-1 protein (HMGB1) plays a pivotal role in neuroinflammation and SAE, yet the mechanism by which HMGB1 induces cognitive impairment in SAE remains unclear. Therefore, this study aimed to investigate the mechanism of HMGB1 underlying cognitive impairment in SAE. METHODS: An SAE model was established by cecal ligation and puncture (CLP); animals in the sham group underwent cecum exposure alone without ligation and perforation. Mice in the inflachromene (ICM) group were continuously injected with ICM intraperitoneally at a daily dose of 10 mg/kg for 9 days starting 1 h before the CLP operation. The open field, novel object recognition, and Y maze tests were performed on days 14-18 after surgery to assess locomotor activity and cognitive function. HMGB1 secretion, the state of microglia, and neuronal activity were measured by immunofluorescence. Golgi staining was performed to detect changes in neuronal morphology and dendritic spine density. In vitro electrophysiology was performed to detect changes in long-term potentiation (LTP) in the CA1 of the hippocampus. In vivo electrophysiology was performed to detect the changes in neural oscillation of the hippocampus. RESULTS: CLP-induced cognitive impairment was accompanied by increased HMGB1 secretion and microglial activation. The phagocytic capacity of microglia was enhanced, resulting in aberrant pruning of excitatory synapses in the hippocampus. The loss of excitatory synapses reduced neuronal activity, impaired LTP, and decreased theta oscillation in the hippocampus. Inhibiting HMGB1 secretion by ICM treatment reversed these changes. CONCLUSIONS: HMGB1 induces microglial activation, aberrant synaptic pruning, and neuron dysfunction in an animal model of SAE, leading to cognitive impairment. These results suggest that HMGB1 might be a target for SAE treatment.

The Optimal Age Threshold for Stratifying the Risks of Disease Progression in Patients with Highly Suspicious Sub-centimeter Thyroid Nodules.

PURPOSE: The study aimed to identify the value and optimal age cutoff to predict the progression of highly suspicious thyroid nodules ≤ 10 mm during active surveillance (AS), and to reveal distinct risk factors in patients of different ages. METHODS: A total of 779 patients with highly suspicious thyroid nodules were enrolled and followed up by ultrasonography. Locally weighted scatterplot smoothing (LOWESS) and the package 'changepoint' were used to identify the optimal age cutoffs using R. Multivariate Cox regression was performed to identify independent prognostic factors in each patient group divided according to age. RESULTS: Age was an independent predictor of nodule progression (P = 0.038). The optimal age cutoff to stratify the risk of nodule progression was 30 years. Younger patients were more likely to have progression of nodules during AS (P < 0.001), including enlargement of nodule size (P = 0.011) and new lesion occurrence (P < 0.001). Nodule size was identified as a risk factor for disease progression in patients younger than 30 years old (P = 0.008, OR 7.946, 95% CI 1.715-36.820), while multifocality (P = 0.018, OR 2.315, 95% CI 1.155-4.639) and thyroiditis (P = 0.028, OR 2.265, 95% CI 1.092-4.699) were independent predictors in patients over 30 years old. CONCLUSIONS: Highly suspicious thyroid nodules ≤ 10 mm in young patients tended to be more progressive. The predictors of disease progression were distinct in patients of different ages.

Evaluation of serum B7-H3 expression, ultrasound and clinical characteristics to predict the risk of cervical lymph node metastases in papillary thyroid carcinoma by nomogram.

BACKGROUND: Improving the preoperative diagnosis of cervical lymph node metastasis (LNM) will help improve the clinical outcomes of papillary thyroid carcinoma (PTC) patients. B7-H3, as an immune checkpoint of the B7 family, is highly expressed in PTC tissues and related to LNM and prognosis. We aimed to explore the clinical values of serum B7-H3 (sB7-H3) in predicting LNM in PTC by a nomogram prediction model. METHODS: From September 2019 to May 2021, a total of 344 PTC patients with primary surgery in our hospital were enrolled in this research. Enzyme-linked Immunosorbent Assay (ELISA) was used to detect sB7-H3 from the peripheral blood of PTC patients and normal controls. We created a nomogram prediction model in combination with sB7-H3 expression, clinical and ultrasound characteristics to predict LNM in the early stage. RESULTS: Gender (p = 0.001), age (p = 0.015), tumor size (p < 0.001), number of tumors (p = 0.021) and sB7-H3 expression (p = 0.003) were independent risk factors for LNM in PTC. All the factors were included in the nomogram. The area under the curve (AUC) was 73.9% (95% CI, 68.12%-79.69%). CONCLUSION: The nomogram is helpful in assessing the risk of LNM in PTC. sB7-H3 has excellent potential in predicting LNM in patients with PTC as an adjunctive ultrasound tool.

Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-driven intelligent laryngoscopy monitoring assistant (ILMA) for landmark anatomical sites identification on laryngoscopic images and videos based on a convolutional neural network (CNN). MATERIALS AND METHODS: The laryngoscopic images taken from January to December 2018 were retrospectively collected, and ILMA was developed using the CNN model of Inception-ResNet-v2 + Squeeze-and-Excitation Networks (SENet). A total of 16,000 laryngoscopic images were used for training. These were assigned to 20 landmark anatomical sites covering six major head and neck regions. In addition, the performance of ILMA in identifying anatomical sites was validated using 4000 laryngoscopic images and 25 videos provided by five other tertiary hospitals. RESULTS: ILMA identified the 20 anatomical sites on the laryngoscopic images with a total accuracy of 97.60 %, and the average sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 100 %, 99.87 %, 97.65 %, and 99.87 %, respectively. In addition, multicenter clinical verification displayed that the accuracy of ILMA in identifying the 20 targeted anatomical sites in 25 laryngoscopic videos from five hospitals was ≥95 %. CONCLUSION: The proposed CNN-based ILMA model can rapidly and accurately identify the anatomical sites on laryngoscopic images. The model can reflect the coverage of anatomical regions of the head and neck by laryngoscopy, showing application potential in improving the quality of laryngoscopy.

The Leap of Inulin Fructans from Food Industry to Medical Application.

As a dietary supplement, the efficacy of prebiotics has become a hot issue in recent years. Inulin is one of internationally recognized prebiotics and belongs to a group of non-digestible and fermentable carbohydrates. Currently, the food industry is increasingly using prebiotic inulin as a health-promoting substrate, not just as food supplement. In addition, inulin has also shown great promise in the treatment of various diseases. This article reviews the application of inulin in the food industry and summarizes physiological function of inulin. Through the review and prospect of the research on obesity, diabetes and mental illness, it provides the theoretical basis for the joint development of inulin in food industry and medical application.

Genetic polymorphisms and phylogenetic characteristics of Tibeto-Burman-speaking Lahu population from southwest China based on 41 Y-STR loci.

BACKGROUND: Male sex-linked Y-chromosome short tandem repeats (Y-STRs) have been widely used in forensic cases and population genetics research. At present, the forensic-related Y-STR data in the Chinese Lahu population are still poorly understood. AIM: To enrich the available Y-STR data of this Chinese minority population and investigate its phylogenetic relationships with other reported populations. SUBJECTS AND METHODS: The genetic polymorphisms of 41 Y-STR loci were analysed in 299 unrelated healthy Lahu male individuals from Southwest China. Phylogenetic analyses were performed by multidimensional scaling analysis and neighbor-joining phylogenetic tree construction. RESULTS: A total of 379 alleles were observed at the 41 Y-STR loci. The allele frequencies ranged from 0.0033 to 0.9666. The genetic diversity values ranged from 0.0653 to 0.9072. A total of 254 different haplotypes of the 41 Y-STR loci were observed in 299 individuals. The values of haplotype diversity, haplotype match probability, and discrimination capacity were 0.9987, 0.0047, and 0.8495, respectively. The phylogenetic analysis indicated that the Tibeto-Burman-speaking Lahu population showed a close genetic relationship with the Yunnan Yi population. CONCLUSIONS: The haplotype data of the present study can enrich the forensic databases of this Chinese minority population and will be useful for population genetics and forensic DNA application.

Predictors of Occult Lymph Node Metastasis and Prognosis in Patients with cN0 T1-T2 Supraglottic Laryngeal Carcinoma: A Retrospective Study.

BACKGROUND: This work aimed to explore the predictors of lymph node metastasis (LNM) and analyze the prognosis of patients with clinically node-negative (cN0) T1-T2 supraglottic laryngeal carcinoma (SGLC). METHODS: Data for 130 patients with cN0 T1-T2 SGLC who initially underwent surgery were retrospectively reviewed. Occult LNM incidence, relevant factors, and prognosis were analyzed. RESULTS: Of the 130 patients with cN0 T1-T2 SGLC, 21 (16.2%) had occult LNM. Based on univariate and multivariable regression analyses, male sex and poor tumor differentiation predicted the incidence of occult LNM. The incidence of occult LNM was 20.9% in males and 5.1% in females (p = 0.035). Patients with poorly differentiated tumors had a higher incidence of occult LNM (42.9%) than patients with well-differentiated (10.3%) and moderately differentiated tumors (14.3%; p < 0.05). Thirteen patients (10%) had cervical recurrence, and all had T2 tumors (p = 0.02). The 5-year disease-specific survival rates were 70 and 90% for patients with and without LNM, respectively (p = 0.000). CONCLUSIONS: Sex and tumor differentiation are potential predictors of occult nodal disease. Female patients with cN0 T1-T2 SGLC are less likely than male patients to have neck metastasis. Poorly differentiated tumors are associated with the frequency of neck metastasis, and selective neck dissection is strongly recommended for these tumors.

Efficacy of Superselective Neck Dissection in Detecting Metastasis in Patients with cN0 Papillary Thyroid Carcinoma at High Risk of Lateral Neck Metastasis.

Background Material and Methods Results Conclusions.

Bionic dual-scale structured films for efficient passive radiative cooling accompanied by robust durability.

Passive radiative cooling (PRC), as an energy-free cooling approach, is ingeniously harnessed for certain natural organisms to withstand extreme high-temperature climates, which has inspired numerous bionic designs. However, it is a great challenge to enhance the durability of the designed materials in practical scenarios while inheriting the natural biological principles. We demonstrate bionic dual-scale structured (BDSS) films for efficient passive radiative cooling accompanied by robust durability after discovering the excellent thermoregulatory properties of the inner surface of Hawaiian scallop shell. We found that the inner surface of the shell consists of large-scale triangular ridges scattered with small-scale terrace steps. This dual-scale structure can enhance the reflectivity of sunlight by efficient Mie scattering and increase the emissivity in the mid-infrared range by lengthening the propagation of photons, thereby decreasing the surface temperature. Underpinned by this finding, we developed a BDSS film that features a strong solar spectrum reflectivity of 0.95 and a high mid-infrared emissivity of 0.98, achieving a sub-ambient cooling of 10.8 °C under direct sunlight. Additionally, the designed films possess robust durability including excellent self-cleaning, flexibility, mechanical strength, chemical stability, and anti-ultraviolet radiation, which is promising for thermal thermoregulation in various harsh scenarios.

The Detection of Nasopharyngeal Carcinomas Using a Neural Network Based on Nasopharyngoscopic Images.

OBJECTIVE: To construct and validate a deep convolutional neural network (DCNN)-based artificial intelligence (AI) system for the detection of nasopharyngeal carcinoma (NPC) using archived nasopharyngoscopic images. METHODS: We retrospectively collected 14107 nasopharyngoscopic images (7108 NPCs and 6999 noncancers) to construct a DCNN model and prepared a validation dataset containing 3501 images (1744 NPCs and 1757 noncancers) from a single center between January 2009 and December 2020. The DCNN model was established using the You Only Look Once (YOLOv5) architecture. Four otolaryngologists were asked to review the images of the validation set to benchmark the DCNN model performance. RESULTS: The DCNN model analyzed the 3501 images in 69.35 s. For the validation dataset, the precision, recall, accuracy, and F1 score of the DCNN model in the detection of NPCs on white light imaging (WLI) and narrow band imaging (NBI) were 0.845 ± 0.038, 0.942 ± 0.021, 0.920 ± 0.024, and 0.890 ± 0.045, and 0.895 ± 0.045, 0.941 ± 0.018, and 0.975 ± 0.013, 0.918 ± 0.036, respectively. The diagnostic outcome of the DCNN model on WLI and NBI images was significantly higher than that of two junior otolaryngologists (p < 0.05). CONCLUSION: The DCNN model showed better diagnostic outcomes for NPCs than those of junior otolaryngologists. Therefore, it could assist them in improving their diagnostic level and reducing missed diagnoses. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:127-135, 2024.

Recombinant human collagen I/carboxymethyl chitosan hydrogel loaded with long-term released hUCMSCs derived exosomes promotes skin wound repair.

BACKGROUND: Stem cell exosomes are beneficial in accelerating wound repair. However, the therapeutic function is limited due to its rapid clearance in vivo. To improve the functionality of exosomes in cutaneous wound healing, a novel hydrogel was designed and fabricated by recombinant human collagen I and carboxymethyl chitosan loaded with exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSCs), named as the rhCol I/CMC-Exos hydrogel. METHODS: Exosomes were extracted from hUCMSCs and were characterizated by TEM (Transmission Electron Microscopy), and biomarker detection. The rhCol I hydrogel, rhCol I/carboxymethyl chitosan (rhCol I/CMC) hydrogel and the rhCol I/CMC-Exos hydrogel composites were cross-linked by genipin. These materials were assessed and compared for their physical characteristics, including cross-sectional morphology, porosity, pore distribution, and hydrophilicity. Cell biocompatibility on biomaterials was investigated using scanning electron microscopy and CFDA staining, as well as assessed in vivo through histological examination of major organs in mice. Effects of the hydrogel composite on wound healing were further evaluated by using the full-thickness skin defect mice model. RESULTS: Successful extraction of hUCMSCs-derived exosomes was confirmed by TEM，Western Blotting and flow cytometry. The synthesized rhCol I/CMC-Exos hydrogel composite exhibited cytocompatibility and promoted cell growth in vitro. The rhCol I/CMC-Exos hydrogel showed sustained release of exosomes. In the mice full skin-defects model, the rhCol I/CMC-Exos-treated group showed superior wound healing efficiency, with 15 % faster wound closure compared to controls. Histological examinations revealed thicker dermis formation and more balanced collagen deposition in wounds treated with rhCol I/CMC-Exos hydrogel. Mechanistically, the application of rhCol I/CMC-Exos hydrogel increased fibroblasts proliferation, alleviated inflammation responses as well as promoted angiogenesis, thereby was beneficial in promoting skin wound healing and regeneration. CONCLUSION: Our study, for the first time, introduced recombinant human Collagen I in fabricating a novel hydrogel loaded with hUCMSCs-derived exosomes, which effectively promoted skin wound closure and regeneration, demonstrating a great potential in severe skin wound healing treatment.

The minimal number of examined lymph nodes for accurate nodal staging and favorable prognosis in T1-2 supraglottic laryngeal squamous cell carcinoma.

OBJECTIVE: The study aimed to investigate the minimal number of examined lymph nodes (ELNs) for accurate assessment of lymph node status and favorable prognosis in patients with stage T1-2 supraglottic laryngeal squamous cell carcinoma (LSCC) who received radical resection. METHODS: Patients with stage T1-2 supraglottic LSCC from the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese Academy of Medical Sciences, Cancer Hospital/National Cancer Center (NCC) were reviewed. The association of the ELN count with the identification of nodal metastasis and overall survival (OS) was analyzed using a multivariate regression model. Locally weighted scatterplot smoothing fitting curve and the 'changepoint' package were adopted to identify the optimal cut points using R. RESULTS: A total of 429 patients from the SEER database and 53 patients from NCC were enrolled. The probability of identifying nodal metastasis was positively related to the ELN count. For patients diagnosed with pathological stage N0 (pN0) disease, the mortality risks rapidly decreased when the amount of ELNs exceeded ten, and those with ELNs >10 had better OS. CONCLUSION: An adequate amount of ELNs benefits precise nodal staging in patients with stage T1-2 supraglottic LSCC. Ten lymph nodes are the minimum number of ELNs. For pN0 patients, an ELN count ≤10 is an unfavorable prognostic factor.

The optimal number of examined lymph nodes for accurate nodal staging and favorable prognosis of oral tongue squamous cell carcinoma.

OBJECTIVE: The study aimed to determine the optimal count of examined lymph nodes (ELN) for accurate assessment of lymph node status and favorable long-term survival in patients with oral tongue squamous cell carcinoma (OTSCC) who received radical resection. METHODS: Patients with OTSCC who received radical resection between 2004 and 2015 were enrolled from the Surveillance, Epidemiology, and End Results database (SEER) and were randomly divided into two cohorts. The association of ELN count with nodal migration and overall survival (OS) was analyzed using a multivariate regression model with the adjustment of relevant factors. Locally weighted scatterplot smoothing (LOWESS) and 'strucchange' package were adopted to identify the optimal cut points using R. RESULTS: A total of 2077 patients were included in this study. The optimal cut points of ELN count for accurate nodal staging and favorable OS were 19 and 15, respectively. The probability of detecting positive lymph nodes (PLN) significantly increased in patients with ELN count ≥ 19 in comparison to those with ELN count < 19 (training set, P < 0.001; validation set, P = 0.012). A better postoperative prognosis was observed in patients with ELN count ≥ 15 than those with fewer ELN (training set, P = 0.001, OR: 0.765; validation set, P = 0.016, OR: 0.678). CONCLUSION: The optimal cut point of ELN count to ensure the accuracy of nodal staging and to achieve a favorable postoperative prognosis were 19 and 15, respectively. The ELN count beyond the cutoff values might improve the accuracy of cancer staging and OS.

[Automatic anatomical site recognition of laryngoscopic images using convolutional neural network].

Objective:To explore the automatic recognition and classification of 20 anatomical sites in laryngoscopy by an artificial intelligence（AI） quality control system using convolutional neural network（CNN）. Methods: Laryngoscopic image data archived from laryngoscopy examinations at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences from January to December 2018 were collected retrospectively, and a CNN model was constructed using Inception-ResNet-V2+SENet. Using 14000 electronic laryngoscope images as the training set, these images were classified into 20 specific anatomical sites including the whole head and neck, and their performance was tested by 2000 laryngoscope images and 10 laryngoscope videos. Results:The average time of the trained CNN model for recognition of each laryngoscopic image was（20.59 ± 1.55） ms, and the overall accuracy of recognition of 20 anatomical sites in laryngoscopic images was 97.75%（1955/2000）, with average sensitivity, specificity, positive predictive value, and negative predictive value of 100%, 99.88%, 97.76%, and 99.88%, respectively. The model had an accuracy of ≥ 99% for the identification of 20 anatomical sites in laryngoscopic videos. Conclusion:This study confirms that the CNN-based AI system can perform accurate and fast classification and identification of anatomical sites in laryngoscopic pictures and videos, which can be used for quality control of photo documentation in laryngoscopy and shows potential application in monitoring the performance of laryngoscopy.

Survival and long-term quality-of-life of concurrent chemoradiotherapy versus surgery followed by radiotherapy with or without concurrent chemotherapy for the treatment of resectable stage III/IV hypopharyngeal carcinoma.

OBJECTIVE: We evaluated the utility of concurrent chemoradiotherapy (CCRT) compared to surgery followed by adjuvant radiotherapy (with or without concurrent chemotherapy) (SRT) in terms of improving the life expectancy and quality-of-life (QOL) of patients with stage III/IV hypopharyngeal squamous cell carcinomas (HPSCCs). METHODS: From January 2010 to July 2018, a total of 299 patients with stage III/IV HPSCC who received surgery followed by adjuvant radiotherapy (with or without concurrent chemotherapy) (SRT, n = 111), or concurrent chemoradiotherapy (CCRT, n = 188) in our hospital were included. We measured overall survival (OS) and disease-free survival (DFS). We used the EORTC QLQ-C30, QLQ-H&N35, and Voice handicap index-30 (VHI-30) instruments to assess the long-term QOL. RESULTS: The OS and DFS afforded by SRT were significantly better than those associated with CCRT (p = 0.039; p = 0.048 respectively), especially for stage N2-N3 patients. CCRT patients experienced better speech outcomes. CONCLUSION: For resectable stage III/IV HPSCC patients, appropriate treatment plans should be selected comprehensively considering survival rate, QOL, patient preference and multidisciplinary treatment.

Suppression of NF-κB signaling by Pseudorabies virus DNA polymerase processivity factor UL42 via recruiting SOCS1 to promote the ubiquitination degradation of p65.

The NF-κB pathway is a critical signaling involved in the regulation of the inflammatory and innate immune responses. Previous studies have shown that Pseudorabies Virus (PRV), a porcine alpha herpesvirus, could lead to the phosphorylation and nucleus translocation of p65 while inhibiting the expression of NF-κB-dependent inflammatory cytokines, which indicated that there may be unknown mechanisms downstream of p65 that downregulate the activation of NF-κB signaling. Here, we found that PRV DNA polymerase factor UL42 inhibited TNFα-, LPS-, IKKα-, IKKß-, and p65-mediated transactivation of NF-κB signaling, which demonstrated UL42 worked either at or downstream of p65. In addition, it was found that the DNA-binding activity of UL42 was required for inhibition of NF-κB signaling. Importantly, it was revealed that UL42 could induce the ubiquitination degradation of p65 by upregulating the suppressor of cytokine signaling 1 (SOCS1). Additionally, it was found that UL42 could promote the K6/K29-linked ubiquitination of p65. Finally, knockdown of SOCS1 attenuated the replication of PRV and led to a significant increase of the inflammatory cytokines. Taken together, our findings uncovered a novel mechanism that PRV-UL42 could upregulated SOCS1 to promote the ubiquitination degradation of p65 to prevent excessive inflammatory response during PRV infection.