With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveTo investigate the current awareness and optimization recommendations on pneumonia with unknown etiology (PUE) surveillance among Shanghai healthcare professionals, and to provide evidence for the improvement of the surveillance system. MethodsIn December 2024, healthcare professional participants from diverse medical and health institutions were randomly selected within each stratum using a stratified cluster sampling method in all 16 districts of Shanghai for questionnaire surveys on their knowledge and suggestions for optimization of the PUE surveillance system. Descriptive statistics analyses, multivariate logistic regressions, and content analyses were used for data analyses. ResultsA total of 385 survey subjects were involved in the study, including 119 professional staffs from disease prevention and control centers and 266 from medical institutions. Those who understood the case definition for PUE correctly accounted for 67.01% (258/385). Multivariate regression model analyses showed that female gender (aOR=2.22, 95%CI: 1.36‒3.66), professionals from disease control institutions (aOR=2.02, 95%CI: 1.12‒3.72), and those who self-assessed as being familiar with the monitoring system (aOR=2.18, 95%CI:1.23‒3.89) had better understanding of the definition. Overall, 89.61% (345/385) of the survey subjects acknowledged the necessity of the surveillance system. Small number of cases meeting the case definition (54.46%, 214/379), insufficient diagnostic awareness (39.84%, 151/379), and lack of incentives for case reporting (29.29%, 111/379) were major problems for the current surveillance system, with variations observed across different types of institutions. Suggested segments for optimizing the surveillance system included monitoring purpose, case definition, form of monitoring and reporting procedure, organization mechanism, and epidemiological investigation and response. ConclusionThe necessity of PUE surveillance is commonly recognized among healthcare workers. However, the existing system falls short in terms of mastery of case definition and overall surveillance adaptability. There is an urgent need for optimization and improvement to enhance the capacity for preventing and controlling emerging and sudden respiratory infectious diseases.

Objective To establish a highly sensitive and specific method for detecting human DNA based on real time quantitative PCR(qPCR)technique for the rapid detection of potential DNA con-tamination sources in DNA laboratories.Methods Primers and probes were designed with Primer Ex-pressTM software using the reference sequence of human 18S rRNA gene as a template,and the opti-mal prime-probe combination was screened by matrix method.The PCR products of the target se-quence of human 18S rRNA gene were used to construct the plasmid,and a plasmid standard was used to draw the standard curve of the qPCR system.According to the Minimum Information for Pub-lication of Quantitative Real-time PCR Experiments(MIQE)guidelines,the specificity,sensitivity,re-peatability and application effect of the qPCR system were evaluated.Results The sensitivity of the qPCR system established in this study was 5.3×10-5 ng/μL,which showed good specificity for human DNA samples.The correlation coefficient of the qPCR system was-0.999,and amplification efficiency was 100％.Both the intra-batch and inter-batch variation coefficients were less than 2％.Conclusion The established human DNA detection method based on qPCR technique has good specificity,high sen-sitivity,and robust stability.It can be used for rapid detection of DNA contamination and daily moni-toring of the accumulated human DNA in the laboratory environment.

Objective To explore the value of combining apparent diffusion coefficient(ADC)heterogeneity with morphological indicators in assessing the pathological grading of non-muscle invasive bladder cancer(NMIBC).Methods The MRI images of 86 patients confirmed with NMIBC by surgical pathology were analyzed retrospectively.All patients underwent T2WI,diffusion weighted ima-ging(DWI),and dynamic contrast enhancement(DCE)examinations.Two radiologists independently measured tumor largest diam-eter(LD),actual tumor-wall contact length(ACTCL),ADCmean,ADCmin,and ADCmax values.ADC heterogeneity was calculated using the formula(ADCmax-ADCmin)/ADCmean.Differences in quantitative parameters between low-and high-grade NMIBC were compared using the Mann-Whitney U test,while differences in qualitative parameters were compared using the chi-square test.Univariate and multivariate logistic regression analyses were used to identify independent predictors of high-grade NMIBC,and receiver operating characteristic(ROC)curves were drawn to evaluate the performance of ADC heterogeneity combined with morphological indicators in assessing high-grade NMIBC.Results ADC heterogeneity and ACTCL were independent predictors for preoperative assessment of NMIBC pathological grading.The area under the curve(AUC)of ADC heterogeneity and ACTCL in assessing high-grade NMIBC were 0.843 and 0.744,respectively.The combined AUC was 0.902.The difference was statistically significant(P<0.05).Conclusion The combination of ADC heterogeneity with ACTCL can effectively improve the efficiency of preoperative assessment of NMIBC pathological grading,and providing more precise clinical decision-making and prognosis monitoring.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Antibiotic adjuvants offer a promising strategy for restoring antibiotic sensitivity, expanding antibacterial spectra, and reducing required dosages. Previously, compound 15 was identified as a potential adjuvant for Polymyxin B (PB) against multidrug-resistant (MDR) Pseudomonas aeruginosa DK2; however, its clinical utility was hindered by high cytotoxicity, uncertain in vivo efficacy, and an unclear synergetic mechanism. To address these challenges, we synthesized and evaluated a series of novel benzamide derivatives, with A22 emerging as a particularly promising candidate. A22 demonstrated potent synergistic activity to PB, minimal cytotoxicity, improved water solubility, and broad-spectrum synergism of polymyxins against various clinically isolated MDR Gram-negative strains. In vivo studies using Caenorhabditis elegans and mouse models further confirmed the efficacy of A22. Moreover, A22 effectively suppressed the development of PB resistance in Pseudomonas aeruginosa DK2. Mechanistic investigations revealed that A22 enhances polymyxins activity by inducing reactive oxygen species production, reducing ATP levels, increasing NOX activity, and inhibiting biofilm formation, leading to bacterial death. These findings position A22 as a highly promising candidate for the development of polymyxin adjuvants, offering a robust approach to combating MDR Gram-negative bacterial infections.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Accurate timing of myelination is crucial for the proper functioning of the central nervous system. Here, we identified a de novo heterozygous mutation in TMEM63A (c.1894G>A; p. Ala632Thr) in a 7-year-old boy exhibiting hypomyelination. A Ca²⁺ influx assay suggested that this is a loss-of-function mutation. To explore how TMEM63A deficiency causes hypomyelination, we generated Tmem63a knockout mice. Genetic deletion of TMEM63A resulted in hypomyelination at postnatal day 14 (P14) arising from impaired differentiation of oligodendrocyte precursor cells (OPCs). Notably, the myelin dysplasia was transient, returning to normal levels by P28. Primary cultures of Tmem63a^-/- OPCs presented delayed differentiation. Lentivirus-based expression of TMEM63A but not TMEM63A_A632T rescued the differentiation of Tmem63a^-/- OPCs in vitro and myelination in Tmem63a^-/- mice. These data thus support the conclusion that the mutation in TMEM63A is the pathogenesis of the hypomyelination in the patient. Our study further demonstrated that TMEM63A-mediated Ca²⁺ influx plays critical roles in the early development of myelin and oligodendrocyte differentiation.
Animals ; Cell Differentiation/physiology* ; Oligodendroglia/metabolism* ; Mice, Knockout ; Mice ; Male ; Myelin Sheath/metabolism* ; Humans ; Child ; Cells, Cultured ; Oligodendrocyte Precursor Cells/metabolism*

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins