Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer.

Depending on the source of the blastophore, there are various subtypes of laryngeal cancer, each with a unique metastatic risk and prognosis. The forecasting of their prognosis is a pressing issue that needs to be resolved. This study comprised 5953 patients with glottic carcinoma and 4465 individuals with non-glottic type (supraglottic and subglottic). Five clinicopathological characteristics of glottic and non-glottic carcinoma were screened using univariate and multivariate regression for CoxPH (Cox proportional hazards); for other models, 10 (glottic) and 11 (non-glottic) clinicopathological characteristics were selected using least absolute shrinkage and selection operator (LASSO) regression analysis, respectively; the corresponding survival models were established; and the best model was evaluated. We discovered that RSF (Random survival forest) was a superior model for both glottic and non-glottic carcinoma, with a projected concordance index (C-index) of 0.687 for glottic and 0.657 for non-glottic, respectively. The integrated Brier score (IBS) of their 1-year, 3-year, and 5-year time points is, respectively, 0.116, 0.182, 0.195 (glottic), and 0.130, 0.215, 0.220 (non-glottic), demonstrating the model's effective correction. We represented significant variables in a Shapley Additive Explanations (SHAP) plot. The two models are then combined to predict the prognosis for two distinct individuals, which has some effectiveness in predicting prognosis. For our investigation, we established separate models for glottic carcinoma and non-glottic carcinoma that were most effective at predicting survival. RSF is used to evaluate both glottic and non-glottic cancer, and it has a considerable impact on patient prognosis and risk factor prediction.

Cause of Death in Patients with Oropharyngeal Carcinoma by Human Papillomavirus Status: Comparative Data Analysis.

BACKGROUND: The incidence of oropharyngeal squamous cell carcinomas (OPSCC) has increased in recent decades, and human papillomavirus (HPV) infection is the main cause of OPSCC. The data regarding causes of death (CODs) are vitally important in informing follow-up strategies and revising treatment strategies to deal with any possible preventable treatment-related COD. However, limited studies have assessed the competing COD by HPV status in patients with OPSCC. OBJECTIVE: We aimed to analyze the distribution of the competing COD according to HPV status in OPSCC. METHODS: We retrospectively included stage I-IVB patients with OPSCC from the Surveillance, Epidemiology, and End Results database between 2010 and 2015. The association between HPV status and head and neck cancer-specific mortality (HNCSM), second primary cancer mortality (SPCM), and noncancer-caused mortality (NCCM) were analyzed. The chi-square test, Kaplan-Meier analysis, and Fine and Gray model were used for statistical analysis. RESULTS: We included 5852 patients in this study and 73.2% (n=4283) of them had HPV-related tumors. A total of 1537 (26.3%) patients died, including 789 (51.3%), 333 (21.7%), and 415 (27%) patients who died from head and neck cancer, second cancer, and noncancer causes, respectively. The 5-year HNCSM, SPCM, NCCM, and overall mortality were 14.7%, 6.5%, 7.7%, and 26.4%, respectively. Those with HPV-positive disease had a lower cumulative incidence of HNCSM (subdistribution hazard ratio [sHR] 0.362, 95% CI 0.315-0.417; P<.001), SPCM (sHR 0.400, 95% CI 0.321-0.496; P<.001), and NCCM (sHR 0.460, 95% CI 0.378-0.560; P<.001) than those with HPV-negative disease. The 5-year risk of HNCSM was 26.9% and 10.7% in those with HPV-negative and HPV-positive disease, respectively (P<.001). The 5-year risk of SPCM was 12.4% and 4.6% in those with HPV-negative and HPV-positive disease, respectively (P<.001). The 5-year risk of NCCM of death was 13.7% and 5.8% in those with HPV-negative and HPV-positive disease, respectively (P<.001). Using the Fine and Gray competing-risks model, our results show that those with HPV-negative tumors had a significantly higher risk of HNCSM (P<.001), SPCM (P<.001), and NCCM (P<.001) than those with HPV-negative tumors. CONCLUSIONS: HPV-positive OPSCC has a lower NCSM, SPCM, and NCCM as compared to those with HPV-negative OPSCC. HPV positivity is a favorable prognostic factor in the context of overcoming cancer as well as in terms of reducing the risk of other CODs in OPSCC. Our finding supports the need to tailor patient follow-up based on the HPV status of patients with OPSCC.

Biological Nitrogen Removal Database: A Manually Curated Data Resource.

Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research.

Explore the effect of LLY-283 on the ototoxicity of auditory cells caused by cisplatin: A bioinformatic analysis based on RNA-seq.

BACKGROUND: Cisplatin is a commonly used chemotherapeutic drug in clinics, and long-term application will lead to hearing impairment. LLY-283, an inhibitor of PRMT5, has not been reported in deafness. Our study aimed to explore the mechanism of LLY-283 in hearing impairment. MATERIALS AND METHODS: First, we performed RNA-seq (cisplatin in the experimental group and DMSO in the control group) to obtain the biological processes mainly involved in differentially expressed genes (DEGs). CCK-8 and LDH experiments were used to observe the effect of LLY-283 on cisplatin-induced auditory cell injury. ROS experiment was used to monitor the impact of LLY-283 on oxidative damage of auditory cells. Effect of LLY-283 on apoptosis of auditory cells detected by TUNEL experiment. PCR and Western blotting were used to detect the expression of genes and proteins related to auditory cell apoptosis in LLY-283 cells. Meanwhile, we explored the effect of LLY-283 on the expression of PRMT5 in cisplatin-induced hearing impaired cells at RNA and protein levels. RESULTS: Biological process analysis showed that DEGs were mainly enriched in the apoptotic process involved in morphogenesis (-Log10 P = 3.71). CCK-8 and LDH experiments confirmed that LLY-283 could save cisplatin-induced auditory cell injury. ROS experiments confirmed that LLY-283 could rescue cisplatin-induced oxidative damage to auditory cells. TUNEL experiments confirmed that LLY-283 could protect cisplatin-induced apoptosis of auditory cells. Meanwhile, LLY-283 could inhibit the expression of PRMT5 in auditory cells induced by cisplatin. CONCLUSION: LLY-283 can rescue cisplatin-induced auditory cell apoptosis injury. LLY-283 can inhibit the increase in PRMT5 expression induced by cisplatin.

mibPOPdb: An online database for microbial biodegradation of persistent organic pollutants.

Microbial biodegradation of persistent organic pollutants (POPs) is an attractive, ecofriendly, and cost-efficient clean-up technique for reclaiming POP-contaminated environments. In the last few decades, the number of publications documenting POP-degrading microbes, enzymes, and experimental data sets has continuously increased, necessitating the development of a dedicated web resource that catalogs consolidated information on POP-degrading microbes and tools to facilitate integrative analysis of POP degradation data sets. To address this knowledge gap, we developed the Microbial Biodegradation of Persistent Organic Pollutants Database (mibPOPdb) by accumulating microbial POP degradation information from the public domain and manually curating published scientific literature. Currently, in mibPOPdb, there are 9215 microbial strain entries, including 184 gene (sub)families, 100 enzymes, 48 biodegradation pathways, and 593 intermediate compounds identified in POP-biodegradation processes, and information on 32 toxic compounds listed under the Stockholm Convention environmental treaty. Besides the standard database functionalities, which include data searching, browsing, and retrieval of database entries, we provide a suite of bioinformatics services to facilitate comparative analysis of users' own data sets against mibPOPdb entries. Additionally, we built a Graph Neural Network-based prediction model for the biodegradability classification of chemicals. The predictive model exhibited a good biodegradability classification performance and high prediction accuracy. mibPOPdb is a free data-sharing platform designated to promote research in microbial-based biodegradation of POPs and fills a long-standing gap in environmental protection research. Database URL: http://mibpop.genome-mining.cn/.

Toxicological Effects of Artificial Fine Particulate Matter in Rats through Induction of Oxidative Stress and Inflammation.

Airborne fine particulate matter with an aerodynamic diameter equal to or smaller than 2.5 µm (abbreviated as PM2.5) increases the risk of nasal lesions, but the underlying molecular mechanism has not been fully elucidated. In the atmosphere, the composition of PM2.5 collected varies in physical and chemical properties, which affects its damage to human health. Thus, we constructed artificial PM2.5 particles based on actual PM2.5 and investigated the in vivo effects of artificial PM2.5 exposure on the oxidative stress, inflammatory response, and nasal mucosa morphology of rats. The results showed that artificial PM2.5 is comparable in composition ratio, size, and morphology to actual PM2.5. This in vivo study indicated that artificial PM2.5 exposure reduces total superoxide dismutase and glutathione peroxidase activities, elevates malondialdehyde content in the nasal mucosa, and induces increased levels of pro-inflammatory mediators, including interleukin-1, interleukin-6 and tumor necrosis factor-α. Our data shows that artificial PM2.5 particles could be used for experimental study of PM2.5 toxicology, ensuring that the physical and chemical properties of experimental PM2.5 are relatively constant and allowing for repeatability of this research. Oxidative damage and inflammatory response may be the toxic mechanisms that cause nasal lesions after exposure to artificial PM2.5.

[Study on the relationship between benign paroxysmal positional vertigo and sleep disturbance].

Objective:To explore the relationship between benign paroxysmal positional vertigo （BPPV） and sleep disorders through the analysis of subjective and objective sleep conditions. Methods:Forty-five patients with BPPV and fifty controls who met the inclusion and exclusion criteria were selected for Pittsburgh sleep quality index （PSQI） questionnaire survey and polysomnography （PSG） check, and SPSS 23.0 was used to compare and analyze the results. Results:Compared with the control group, patients with BPPV had changes in sleep structure, high apnea hypopnea index （AHI） and significantly decreased subjective sleep quality （P<0.05）, and there were significant differences in the PQSI scores of patients with BPPV before and after treatment （P<0.05）.Binary logistic regression analysis of BPPV and AHI showed that for every 1 increase in AHI index, the probability of BPPV increased by 1.8 times （OR=2.80, 95%CI=2.25-3.66）.After grouping AHI and performing regression analysis, it was found that the risk of BPPV in patients with AHI≥5 was 3.94 times that of patients with AHI <5（OR=3.94，95%CI=1.63-9.48）. Conclusion:Patients with BPPV have decreased sleep quality and altered sleep structure, and in this study, AHI is found to be a risk indicator for BPPV.