In a healthy human, the airway mucus forms a thin, protective liquid layer covering the surface of the respiratory tract. It comprises a complex blend of mucin, multiple antibacterial proteins, metabolic substances, water, and electrolytes. This mucus plays a pivotal role in the lungs' innate immune system by maintaining airway hydration and capturing airborne particles and pathogens. However, heightened mucus secretion in the airway can compromise ciliary clearance, obstruct the respiratory tract, and increase the risk of pathogen colonization and recurrent infections. Consequently, a thorough exploration of the mechanisms driving excessive airway mucus secretion is crucial for establishing a theoretical foundation for the eventual development of targeted drugs designed to reduce mucus production. Across a range of lung diseases, excessive airway mucus secretion manifests with unique characteristics and regulatory mechanisms, all intricately linked to mucin. This article provides a comprehensive overview of the characteristics and regulatory mechanisms associated with excessive airway mucus secretion in several prevalent lung diseases.
Humans ; Mucus/metabolism* ; Mucins/physiology* ; Lung Diseases/metabolism* ; Respiratory Mucosa/metabolism* ; Pulmonary Disease, Chronic Obstructive/physiopathology* ; Asthma/physiopathology* ; Cystic Fibrosis/physiopathology* ; Mucociliary Clearance/physiology*

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

Objective To develop a melanoma diagnosis framework based on large-scale vision-language models,and to explore the feasibility and accuracy of the framework for melanoma diagnosis.Methods The publicly available Derm7pt dataset,which was divided into a training set(346 cases),a validation set(161 cases),and a test set(320 cases)was utilized.A melanoma diagnosis framework based on large-scale vision-language models was proposed,comprising two text branches and one visual branch.In the text branches,one branch processed fixed clinical prompts,while the other handled learnable prompts.This design aimed to optimize the effectiveness of learnable prompts through guidance from fixed clinical prompts.The visual branch processed dermoscopic images and enhanced melanoma feature recognition through fine-tuning the image encoder.Results On the Derm7pt dataset,our method outperformd other existing method.It achieved an area under the receiver operating characteristic curve(AUC)of 87.35％,an accuracy of 84.17％,and an F1-score of 84.01％.Conclusion The study demonstrates that with appropriate fine-tuning strategies,methods based on large-scale vision-language pre-trained models can effectively adapt to melanoma diagnosis tasks.This approach can serve as a powerful auxiliary tool for doctors,helping them make more accurate diagnostic decisions.

Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.

Objective:To explore the prognostic factors of seroma after endoscopic thyroidectomy by breast ap-proach,and construct a nomogram to predict the possibility of cervical seroma.Methods:Data of patients undergoing endoscopic thyroid surgery in Dongguan Tungwah Hospital from January 2022 to May 2024 and Dongguan Songshan Lake Tungwah Hospital from May 2023 to August 2024 were retrospectively analyzed,and 1493 patients meeting the in-clusion criteria were selected.Among them,there were 1048 patients in Dongguan Tungwah Hospital as the training co-hort,1015 patients without seroma group and 33 patients with seroma group.There were 445 patients in Dongguan Songshan Lake Tungwah Hospital as the verification cohort,including 424 patients without seroma and 21 patients with seroma.Multivariate logistic regression analysis was used to obtain relevant independent prognostic factors,and R soft-ware established a nomogram model.Calibration curves,Hosmer-Lemeshow goodness of fit,ROC curves were used to evaluate the calibrability of the nomogram model,and clinical utility was assessed by clinical decision curves.Results:Multivariate logistic regression analysis showed that central lymph node dissection,diabetes,hyperthyroidism,and nod-ule size were independent prognostic factors related to seroma.Based on the prognostic factors,the nomogram of se-roma after ETBA was constructed.The calibration curves of the training and the verification group were in good agree-ment with the observed results,and the Hosmer-Lemeshow goodness of fit test was good,with the training cohort P=0.244 and the verification cohort P=0.803.The ROC curve of the training cohort showed that the area under the curve was 0.810(95%CI:0.740～0.879),and the ROC curve of the verification cohort showed that the area under the curve was 0.815(95%CI:0.722～0.909).Conclusion:The nomogram model based on the relevant prognostic factors ob-tained by multivariate logistic regression analysis has a good prediction effect on the seroma after ETBA,and can provide reasonable and individualized treatment plan for patients.

The patent data in the key technology field of capsule endoscopy industry was retrieved in IncoPat Global Patent Database from January 1,2003 to December 31,2022,and the development trend of key technologies and patent competition in the global capsule endoscopy industry were analyzed in terms of the applicant,concentration of China's patent applications and regional layout.It's pointed out Japan's Olympus company gained advantages in the key technology field,the enterprise played a main role in the innovation of the key technology field,the main exporters and target markets included the United States,South Korea,Japan and China and China became more and more important for the innovation of the key technology field.References were provided for the technology development of capsule endoscopy industry in China.[Chinese Medical Equipment Journal,2025,46(5):60-65]

The patent data in the key technology field of capsule endoscopy industry was retrieved in IncoPat Global Patent Database from January 1,2003 to December 31,2022,and the development trend of key technologies and patent competition in the global capsule endoscopy industry were analyzed in terms of the applicant,concentration of China's patent applications and regional layout.It's pointed out Japan's Olympus company gained advantages in the key technology field,the enterprise played a main role in the innovation of the key technology field,the main exporters and target markets included the United States,South Korea,Japan and China and China became more and more important for the innovation of the key technology field.References were provided for the technology development of capsule endoscopy industry in China.[Chinese Medical Equipment Journal,2025,46(5):60-65]

Objective:To explore the prognostic factors of seroma after endoscopic thyroidectomy by breast ap-proach,and construct a nomogram to predict the possibility of cervical seroma.Methods:Data of patients undergoing endoscopic thyroid surgery in Dongguan Tungwah Hospital from January 2022 to May 2024 and Dongguan Songshan Lake Tungwah Hospital from May 2023 to August 2024 were retrospectively analyzed,and 1493 patients meeting the in-clusion criteria were selected.Among them,there were 1048 patients in Dongguan Tungwah Hospital as the training co-hort,1015 patients without seroma group and 33 patients with seroma group.There were 445 patients in Dongguan Songshan Lake Tungwah Hospital as the verification cohort,including 424 patients without seroma and 21 patients with seroma.Multivariate logistic regression analysis was used to obtain relevant independent prognostic factors,and R soft-ware established a nomogram model.Calibration curves,Hosmer-Lemeshow goodness of fit,ROC curves were used to evaluate the calibrability of the nomogram model,and clinical utility was assessed by clinical decision curves.Results:Multivariate logistic regression analysis showed that central lymph node dissection,diabetes,hyperthyroidism,and nod-ule size were independent prognostic factors related to seroma.Based on the prognostic factors,the nomogram of se-roma after ETBA was constructed.The calibration curves of the training and the verification group were in good agree-ment with the observed results,and the Hosmer-Lemeshow goodness of fit test was good,with the training cohort P=0.244 and the verification cohort P=0.803.The ROC curve of the training cohort showed that the area under the curve was 0.810(95%CI:0.740～0.879),and the ROC curve of the verification cohort showed that the area under the curve was 0.815(95%CI:0.722～0.909).Conclusion:The nomogram model based on the relevant prognostic factors ob-tained by multivariate logistic regression analysis has a good prediction effect on the seroma after ETBA,and can provide reasonable and individualized treatment plan for patients.

Platycodonis Radix is the dry root of Platycodon grandiflorum of Campanulaceae, which has a variety of pharmacological effects and is a commonly used bulk Chinese medicine. In this study, the chloroplast genome sequences of six P. grandiflorum from different producing areas has been sequenced with Illumina HiSeq X Ten platform. The specific DNA barcodes were screened, and the germplasm resources and genetic diversity were analyzed according to the specific barcodes. The total length of the chloroplast genome of 6 P. grandiflorum samples was 172 260-172 275 bp, and all chloroplast genomes showed a typical circular tetrad structure and encoded 141 genes. The comparative genomics analysis and results of amplification efficiency demonstrated that trnG-UCC and ndhG_ndhF were the potential specific DNA barcodes for identification the germplasm resources of P. grandiflorum. A total of 305 P. grandiflorum samples were collected from 15 production areas in 9 provinces, for which the fragments of trnG-UCC and ndhG_ndhF were amplificated and the sequences were analyzed. The results showed that trnG-UCC and ndhG_ndhF have 5 and 11 mutation sites, respectively, and 5 and 7 haplotypes were identified, respectively. The combined analysis of the two sequences formed 13 haplotypes (named Hap1-Hap13), and Hap4 is the main genotype, followed by Hap1. The unique haplotypes possessed by the three producing areas can be used as DNA molecular tags in this area to distinguish from the germplasm resources of P. grandiflorum from other areas. The haplotype diversity, nucleotide diversity and genetic distance were 0.94, 4.79×10^-3 and 0.000 0-0.020 3, respectively, suggesting that the genetic diversity was abundant and intraspecific kinship was relatively close. This study laid a foundation for the identification of P. grandiflorum, the protection and utilization of germplasm resources, and molecular breeding.