Genetic association and causal relationship between multiple modifiable risk factors and autoimmune liver disease: a two-sample mendelian randomization study.

BACKGROUND: The intricate etiology of autoimmune liver disease (AILD) involves genetic, environmental, and other factors that yet to be completely elucidated. This study comprehensively assessed the causal association between genetically predicted modifiable risk factors and AILD by employing Mendelian randomization. METHODS: Genetic variants associated with 29 exposure factors were obtained from genome-wide association studies (GWAS). Genetic association data with autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) were also obtained from publicly available GWAS. Univariate and multivariate Mendelian randomization analyses were performed to identify potential risk factors for AILD. RESULTS: Genetically predicted rheumatoid arthritis (RA) (OR = 1.620, 95%CI 1.423-1.843, P = 2.506 × 10- 13) was significantly associated with an increased risk of AIH. Genetically predicted smoking initiation (OR = 1.637, 95%CI 1.055-2.540, P = 0.028), lower coffee intake (OR = 0.359, 95%CI 0.131-0.985, P = 0.047), cholelithiasis (OR = 1.134, 95%CI 1.023-1.257, P = 0.017) and higher C-reactive protein (CRP) (OR = 1.397, 95%CI 1.094-1.784, P = 0.007) were suggestively associated with an increased risk of AIH. Genetically predicted inflammatory bowel disease (IBD) (OR = 1.212, 95%CI 1.127-1.303, P = 2.015 × 10- 7) and RA (OR = 1.417, 95%CI 1.193-1.683, P = 7.193 × 10- 5) were significantly associated with increased risk of PBC. Genetically predicted smoking initiation (OR = 1.167, 95%CI 1.005-1.355, P = 0.043), systemic lupus erythematosus (SLE) (OR = 1.086, 95%CI 1.017-1.160, P = 0.014) and higher CRP (OR = 1.199, 95%CI 1.019-1.410, P = 0.028) were suggestively associated with an increased risk of PBC. Higher vitamin D3 (OR = 0.741, 95%CI 0.560-0.980, P = 0.036) and calcium (OR = 0.834, 95%CI 0.699-0.995, P = 0.044) levels were suggestive protective factors for PBC. Genetically predicted smoking initiation (OR = 0.630, 95%CI 0.462-0.860, P = 0.004) was suggestively associated with a decreased risk of PSC. Genetically predicted IBD (OR = 1.252, 95%CI 1.164-1.346, P = 1.394 × 10- 9), RA (OR = 1.543, 95%CI 1.279-1.861, P = 5.728 × 10- 6) and lower glycosylated hemoglobin (HbA1c) (OR = 0.268, 95%CI 0.141-0.510, P = 6.172 × 10- 5) were positively associated with an increased risk of PSC. CONCLUSIONS: Evidence on the causal relationship between 29 genetically predicted modifiable risk factors and the risk of AIH, PBC, and PSC is provided by this study. These findings provide fresh perspectives on the management and prevention strategies for AILD.

The predictive value of PFKFB3 in bladder cancer prognosis.

6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3 (PFKFB3) influences cancer progression via participating in tumor aerobic glycolysis. In this study, we aimed to evaluate the prognostic significance of PFKFB3 in bladder cancer (BLCA) patients by analyzing a combination of publicly available databases, clinical patient data, and bladder tumor samples from our hospital. Single-cell and bulk RNA-seq data of bladder cancer, obtained from ENA, GEO, and TCGA databases, were utilized for our analysis. The results indicated that PFKFB3 mRNA expression was markedly elevated in bladder cancer compared to paired normal tissue. Furthermore, BLCA patients with high PFKFB3 expression exhibited a significantly worse prognosis (P < 0.05). To validate these findings, clinical data and immunohistochemistry staining were performed on specimens obtained from 89 BLCA patients who underwent radical cystectomy at either Qingdao University Affiliated Hospital or Peking Union Medical College Hospital. The findings from this verification process confirmed that high expression of PFKFB3 serves as a biomarker for predicting worse prognosis in BLCA patients (OR: 2.462, 95 % CI: 1.202-5.042, P = 0.012). To facilitate clinical application, we developed a nomogram based on four variables, including PFKFB3 expression, to predict the survival of BLCA patients. Importantly, this nomogram demonstrated a low mean prediction error of 0.03. Taken together, our findings suggest that PFKFB3 has the potential to serve as both a prognostic biomarker and a therapeutic target for BLCA patients.

Proteomics appending a complementary dimension to precision oncotherapy.

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Clinical Effect Analysis of Wearable Sensor Technology-Based Gait Function Analysis in Post-Transcranial Magnetic Stimulation Stroke Patients.

(1) Background: This study evaluates the effectiveness of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) in improving gait in post-stroke hemiplegic patients, using wearable sensor technology for objective gait analysis. (2) Methods: A total of 72 stroke patients were randomized into control, sham stimulation, and LF-rTMS groups, with all receiving standard medical treatment. The LF-rTMS group underwent stimulation on the unaffected hemisphere for 6 weeks. Key metrics including the Fugl-Meyer Assessment Lower Extremity (FMA-LE), Berg Balance Scale (BBS), Modified Barthel Index (MBI), and gait parameters were measured before and after treatment. (3) Results: The LF-rTMS group showed significant improvements in the FMA-LE, BBS, MBI, and various gait parameters compared to the control and sham groups (p < 0.05). Specifically, the FMA-LE scores improved by an average of 5 points (from 15 ± 3 to 20 ± 2), the BBS scores increased by 8 points (from 35 ± 5 to 43 ± 4), the MBI scores rose by 10 points (from 50 ± 8 to 60 ± 7), and notable enhancements in gait parameters were observed: the gait cycle time was reduced from 2.05 ± 0.51 s to 1.02 ± 0.11 s, the stride length increased from 0.56 ± 0.04 m to 0.97 ± 0.08 m, and the walking speed improved from 35.95 ± 7.14 cm/s to 75.03 ± 11.36 cm/s (all p < 0.001). No adverse events were reported. The control and sham groups exhibited improvements but were not as significant. (4) Conclusions: LF-rTMS on the unaffected hemisphere significantly enhances lower-limb function, balance, and daily living activities in subacute stroke patients, with the gait parameters showing a notable improvement. Wearable sensor technology proves effective in providing detailed, objective gait analysis, offering valuable insights for clinical applications in stroke rehabilitation.

A Single-Step Method for Harvesting Influenza Viral Particles from MDCK Cell Culture Supernatant with High Yield and Effective Impurity Removal.

Influenza vaccines, which are recommended by the World Health Organization (WHO), are the most effective preventive measure against influenza virus infection. Madin-Darby canine kidney (MDCK) cell culture is an emerging technology used to produce influenza vaccines. One challenge when purifying influenza vaccines using this cell culture system is to efficiently remove impurities, especially host cell double-stranded DNA (dsDNA) and host cell proteins (HCPs), for safety assurance. In this study, we optimized ion-exchange chromatography methods to harvest influenza viruses from an MDCK cell culture broth, the first step in influenza vaccine purification. Bind/elute was chosen as the mode of operation for simplicity. The anion-exchange Q chromatography method was able to efficiently remove dsDNA and HCPs, but the recovery rate for influenza viruses was low. However, the cation-exchange SP process was able to simultaneously achieve high dsDNA and HCP removal and high influenza virus recovery. For the SP process to work, the clarified cell culture broth needed to be diluted to reduce its ionic strength, and the optimal dilution rate was determined to be 1:2 with purified water. The SP process yielded a virus recovery rate exceeding 90%, as measured using a hemagglutination units (HAUs) assay, with removal efficiencies over 97% for HCPs and over 99% for dsDNA. Furthermore, the general applicability of the SP chromatography method was demonstrated with seven strains of influenza viruses recommended for seasonal influenza vaccine production, including H1N1, H3N2, B (Victoria), and B (Yamagata) strains, indicating that the SP process could be utilized as a platform process. The SP process developed in this study showed four advantages: (1) simple operation, (2) a high recovery rate for influenza viruses, (3) a high removal rate for major impurities, and (4) general applicability.

Clinical treatment patterns, molecular characteristics and survival outcomes of ROS1-rearranged non-small cell lung cancer: A large multicenter retrospective study.

BACKGROUND: Non-small cell lung cancer (NSCLC) harboring ROS1 rearrangements is a molecular subset that exhibits favorable responses to tyrosine kinase inhibitor (TKI) treatment than chemotherapy. This study investigated real-world treatment patterns and survival outcomes among patients with ROS1-rearranged advanced NSCLC. METHODS: We conducted a retrospective analysis of patients with ROS1-rearranged advanced NSCLC treated in four different hospitals in China from August 2018 to March 2022. The study analyzed gene fusion distribution, resistance patterns, and survival outcomes. RESULTS: ROS1 rearrangement occurs in 1.8 % (550/31,225) of our study cohort. CD74 was the most common ROS1 fusion partner, accounting for 45.8 %. Crizotinib was used in 73.9 % of patients in the first-line treatment, and an increased use of chemotherapy, ceritinib, and lorlatinib was seen in the second-line setting. Lung (43.2 %) and brain (27.6 %) were the most common sites of progression in first-line setting, while brain progression (39.2 %) was the most common site of progression in second-line. Median overall survival was 46 months (95 % confidence intervals: 39.6-52.4). First-line crizotinib use yielded significantly superior survival outcomes over chemotherapy in terms of progression-free (18.5 vs. 6.0; p < 0.001) and overall survival (49.8 vs. 37; p = 0.024). The choice of treatment in the latter line also had survival implications, wherein survival outcomes were better when first-line crizotinib was followed by sequential TKI therapy than first-line chemotherapy followed by TKI therapy. CONCLUSIONS: Our study provided insights into the real-world treatment, drug resistance patterns, and survival outcomes among patients with ROS1-rearranged NSCLC. This information serves as a valuable reference for guiding the treatment of this molecular subset of NSCLC.

The synergistic evolution of supply-demand composite system for airport green development: A case study in Guangzhou Baiyun International Airport, China.

Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development.

Research and Application Progress of Laser-Processing Technology in Diamond Micro-Fabrication.

Laser-processing technology has been widely used in the ultra-precision machining of diamond materials. It has the advantages of high precision and high efficiency, especially in the field of super-hard materials and high-precision parts manufacturing. This paper explains the fundamental principles of diamond laser processing, introduces the interaction mechanisms between various types of lasers and diamond materials, focuses on analyzing the current development status of various modes of laser processing of diamond, briefly discusses the relevant applications in diamond cutting, micro-hole forming, and micro-groove machining, etc., and finally discusses the issues, challenges, and potential future advancements of laser technology in the field of diamond processing at this point.

Planned expansion of transportation infrastructure in Brazil has implications for the pattern of agricultural production and carbon emissions.

High transportation costs have been a barrier to the expansion of agriculture in the interior of Brazil. To reduce transportation costs, Brazil launched the National Logistics Plan, aiming to expand its railway network by up to 91 % by 2035. Such a large-scale infrastructure investment raises concerns about its economic and environmental consequences. By combining geospatial estimation of transportation cost with a grid-resolving, multi-scale economic model that bridges fine-scale crop production with its trade and demand from national and global perspectives, we explore impacts of transportation infrastructure expansion on agricultural production, land use changes, and carbon emissions both locally and nationally in Brazil. We find that globally, the impacts on output and land use changes are small. However, within Brazil, the plan's primary impacts are impressive. PNL2035 results in the reduction of transportation costs by 8-23 % across states (depending on expansion's extent) in the interior Cerrado biome. This results in cropland expansion and increases in terrestrial carbon emissions in the Cerrado region. However, the increase in terrestrial carbon emissions in the Cerrado is offset by spillover effects elsewhere in Brazil, as crop production shifts away from the Southeast-South regions and accompanying change in the mix of transportation mode for farm products from roadway to more emission-efficient railway. Furthermore, we argue that the transportation infrastructure's impact on the enhanced mobility of labor and other agricultural inputs would further accentuate the regional shift in agricultural production and contribute to carbon emission mitigation. Upon its completion, PNL2035 is expected to result in the reduction of net national emissions by 1.8-30.7 million metric ton of CO2-equivalent, depending on the impacts on labor and purchased input mobility. We conclude that the omission of spillover effects due to infrastructure expansion can lead to misleading assessments of transport policies.

Thickness- and Field-Dependent Magnetic Domain Evolution in van der Waals Fe3GaTe2.

The discovery of room-temperature ferromagnetism in van der Waals (vdW) materials opens new avenues for exploring low-dimensional magnetism and its applications in spintronics. Recently, the observation of the room-temperature topological Hall effect in the vdW ferromagnet Fe3GaTe2 suggests the possible existence of room-temperature skyrmions, yet skyrmions have not been directly observed. In this study, real-space imaging was employed to investigate the domain evolution of the labyrinth and skyrmion structure. First, Néel-type skyrmions can be created at room temperature. In addition, the influence of flake thickness and external magnetic field (during field cooling) on both labyrinth domains and the skyrmion lattice is unveiled. Due to the competition between magnetic anisotropy and dipole interactions, the specimen thickness significantly influences the density of skyrmions. These findings demonstrate that Fe3GaTe2 can host room-temperature skyrmions of various sizes, opening up avenues for further study of magnetic topological textures at room temperature.

Experimental observation of current-driven antiskyrmion sliding in stripe domains.

Magnetic skyrmions are promising as next-generation information units. Their antiparticle-the antiskyrmion-has also been discovered in chiral magnets. Here we experimentally demonstrate antiskyrmion sliding in response to a pulsed electric current at room temperature without the requirement of an external magnetic field. This is realized by embedding antiskyrmions in helical stripe domains, which naturally provide one-dimensional straight tracks along which antiskyrmion sliding can be easily launched with low current density and without transverse deflection from the antiskyrmion Hall effect. The higher mobility of the antiskyrmions in the background of helical stripes in contrast to the typical ferromagnetic state is a result of intrinsic material parameters and elastic energy of the stripe domain, thereby smearing out the random pinning potential, as supported by micromagnetic simulations. The demonstration and comprehensive understanding of antiskyrmion movement along naturally straight tracks offers a new perspective for (anti)skyrmion application in spintronics.

Incorporating machine learning and PPI networks to identify mitochondrial fission-related immune markers in abdominal aortic aneurysms.

Purpose: The aim of this study is to investigate abdominal aortic aneurysm (AAA), a disease characterised by inflammation and progressive vasodilatation, for novel gene-targeted therapeutic loci. Methods: To do this, we used weighted co-expression network analysis (WGCNA) and differential gene analysis on samples from the GEO database. Additionally, we carried out enrichment analysis and determined that the blue module was of interest. Additionally, we performed an investigation of immune infiltration and discovered genes linked to immune evasion and mitochondrial fission. In order to screen for feature genes, we used two PPI network gene selection methods and five machine learning methods. This allowed us to identify the most featrue genes (MFGs). The expression of the MFGs in various cell subgroups was then evaluated by analysis of single cell samples from AAA. Additionally, we looked at the expression levels of the MFGs as well as the levels of inflammatory immune-related markers in cellular and animal models of AAA. Finally, we predicted potential drugs that could be targeted for the treatment of AAA. Results: Our research identified 1249 up-regulated differential genes and 3653 down-regulated differential genes. Through WGCNA, we also discovered 44 genes in the blue module. By taking the point where several strategies for gene selection overlap, the MFG (ITGAL and SELL) was produced. We discovered through single cell research that the MFG were specifically expressed in T regulatory cells, NK cells, B lineage, and lymphocytes. In both animal and cellular models of AAA, the MFGs' mRNA levels rose. Conclusion: We searched for the AAA novel targeted gene (ITGAL and SELL), which most likely function through lymphocytes of the B lineage, NK cells, T regulatory cells, and B lineage. This analysis gave AAA a brand-new goal to treat or prevent the disease.

Correlation between acoustic characteristics and sensory evaluation of puffed-grain food based on energy analysis.

Puffed-grain food is a crispy snack whose consumer satisfaction depends on snack crispness and crunchiness, which can be characterized by the sound and the acoustic signals of food breaking. This study aimed to evaluate whether acoustic characteristics can be used to predict the crispness of various puffed-grain food. Sensory evaluation was performed on puffed-grain products with varying hygroscopic durations and different types. The relation between sensory evaluation and acoustic characteristics of nine different types of food was examined. The Hilbert-Huang transform was used to perform energy segmentation of the acoustic signal of puffed-grain food and observe its energy migration process. The results showed that energy release was more concentrated in the low-frequency range for grain-puffed foods with different hygroscopic durations. No notable correlation was observed between the low-frequency interval and sensory crispness for the different types of puffed-grain foods. However, the acoustic features extracted from their inherent low-frequency intervals showed a significantly improved correlation with sensory crispness. Therefore, it provides a theoretical reference for applying acoustic characteristics to describe food texture.

Structural Characterization and Physiological Role of Bombyx mori Fibroinase in the Silk Gland Development.

Silkworm is a highly valuable insect that produces silk through secretion by a silk gland. Within this gland, a type of cathepsin L protease called Fibroinase was identified as an enzyme for hydrolyzing the primary components of silk, including fibroin and sericin. Here, we determined the crystal structure of Fibroinase fromBombyx mori at a resolution of 1.56 Å. Comparative structural analysis revealed that Fibroinase adopted a similar structural pattern with papain-type cathepsin, consisting of an N-terminal domain and a C-terminal domain. The interface between the domains forms a substrate-binding cleft, where the E64 inhibitor noncovalently binds in a novel manner. Additionally, computational simulations combined with biochemical analysis allowed us to define the binding mode and inhibition mechanism of physiological inhibitor Bombyx cysteine protease inhibitor (BCPI) with Fibroinase. Moreover, the expression profiles and RNA interference of Fibroinase indicated its critical role in removing silk proteins in the silk gland lumen and the destruction of silk gland tissue during the larval-pupal metamorphosis. These findings enhance our understanding of the structural and biochemical features of Fibroinase and its inhibitors, while also providing evidence for the physiological role of Fibroinase in silk gland development.

Mycobacterium tuberculosis Infection in School Contacts of Tuberculosis Cases: A Systematic Review and Meta-Analysis.

Substantial tuberculosis transmission occurs outside of households, and tuberculosis surveillance in schools has recently been proposed. However, the yield of tuberculosis outcomes from school contacts is not well characterized. We assessed the prevalence of Mycobacterium tuberculosis infection among close school contacts by performing a systematic review. We searched PubMed, Elsevier, China National Knowledge Infrastructure, and Wanfang databases. Studies reporting the number of children who were tested overall and who tested positive were included. Subgroup analyses were performed by study location, index case bacteriological status, type of school, and other relevant factors. In total, 28 studies including 54,707 school contacts screened for M. tuberculosis infection were eligible and included in the analysis. Overall, the prevalence of M. tuberculosis infection determined by the QuantiFERON Gold in-tube test was 33.2% (95% CI, 0.0-73.0%). The prevalences of M. tuberculosis infection based on the tuberculin skin test (TST) using 5 mm, 10 mm, and 15 mm as cutoffs were 27.2% (95% CI, 15.1-39.3%), 24.3% (95% CI, 15.3-33.4%), and 12.7% (95% CI, 6.3-19.0%), respectively. The pooled prevalence of M. tuberculosis infection (using a TST ≥5-mm cutoff) was lower in studies from China (22.8%; 95% CI, 16.8-28.8%) than other regions (36.7%; 95% CI, 18.1-55.2%). The pooled prevalence of M. tuberculosis infection was higher when the index was bacteriologically positive (43.6% [95% CI, 16.5-70.8%] versus 23.8% [95% CI, 16.2-31.4%]). These results suggest that contact investigation and general surveillance in schools from high-burden settings merit consideration as means to improve early case detection in children.

[Energy-saving and Emission Reduction Path for Road Traffic in Key Coastal Cities of Guangdong, Fujian and Zhejiang].

The rapid development of society and economy has resulted in a substantial increase in energy consumption, consequently exacerbating pollution issues. Current research predominantly focuses on energy-saving and emission reduction in road transportation within individual cities or the three major economic regions of China:the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Region. However, there is a dearth of studies addressing the southeastern coastal economic region. Located at the heart of China's southeastern coastal economic development, the provinces of Guangdong, Fujian, and Zhejiang unavoidably face challenges associated with energy consumption and emissions while pursuing economic growth. To address these challenges, this study employed a LEAP model to construct various scenarios for road transportation in the key coastal cities of Guangdong, Fujian, and Zhejiang from 2015 to 2035. These scenarios included a baseline scenario (BAU), an existing policy scenario (EPS), and an improved policy scenario (MPS). The MPS and EPS encompassed vehicle structure optimization (VSO), improved fuel economy (IFE), and reduced annual average mileage (RDM). By simulating and evaluating these scenarios, the energy-saving and emission reduction potentials of road transportation in the key coastal cities were assessed. The results indicated that, in the primary scenario, the MPS exhibited the most significant improvements in energy-saving, carbon reduction, and pollutant reduction effects. By 2035, the MPS achieved a remarkable 75% energy-saving rate compared to that in the baseline scenario, accompanied by reductions of 68%, 59%, 66%, 70%, and 64% in CO2, CO, NOx, PM2.5, and SO2 emissions, respectively. In the secondary scenario, the improved scenario of enhancing fuel economy achieved a notable 30% reduction in energy consumption. Additionally, the scenarios involving vehicle structure adjustment (yielding reductions of 36%, 30%, 36%, 26%, and 40%) and annual average mileage reduction (resulting in reductions of 37%, 37%, 36%, 37%, and 36%) demonstrated significant reductions in CO2, CO, NOx, PM2.5, and SO2 emissions.

Erratum: Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration - CORRIGENDUM.

[This corrects the article DOI: 10.1017/cts.2024.2.].

First-in-human phase I study of BEBT-109 in previously treated EGFR exon 20 insertion-mutated advanced non-small cell lung cancer.

BACKGROUND: BEBT-109 is an oral pan-mutant-selective inhibitor of epidermal growth factor receptor (EGFR) that demonstrated promising antitumor potency in preclinical models. METHODS: This first-in-human study was a single-arm, open-label, two-stage study. Phase Ia dose-escalation study evaluated the safety and pharmacokinetics of BEBT-109 in 11 patients with EGFR T790M-mutated advanced non-small cell lung cancer (aNSCLC). Phase Ib dose-expansion study evaluated the safety and efficacy of BEBT-109 in 18 patients with EGFR exon 20 insertion (ex20ins)-mutated treatment-refractory aNSCLC. The primary outcomes were adverse events and antitumor activity. Clinical trial registration number CTR20192575. FINDINGS: The phase Ia study demonstrated no dose-limiting toxicity, no observation of the maximum tolerated dose, and no new safety signals with BEBT-109 in the dose range of 20-180 mg/d, suggesting that BEBT-109 had an acceptable safety profile among patients with EGFR T790M-mutated aNSCLC. Plasma pharmacokinetics of BEBT-109 showed a dose-proportional increase in the area under the curve and maximal concentration, with no significant drug accumulation. The dose-expansion study demonstrated that BEBT-109 treatment was tolerable across the three dose levels. The three most common treatment-related adverse events were diarrhea (100%; 22.2% ≥Grade 3), rash (66.7%; 5.6% ≥Grade 3), and anemia (61.1%; 0% ≥Grade 3). The objective response rate was 44.4% (8 of 18). Median progression-free survival was 8.0 months (95% confidence intervals, 1.33-14.67). CONCLUSION: Preliminary findings showed that BEBT-109 had an acceptable safety profile and favorable antitumor activity in patients with refractory EGFR ex20ins-mutated aNSCLC. FUNDING: National Natural Science Foundation of China.

New clinical trial design in precision medicine: discovery, development and direction.

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Research on predicting the driving forces of digital transformation in Chinese media companies based on machine learning.

Chinese media companies are facing opportunities and challenges brought about by digital transformation. Media economics takes the evaluation of the business results of media companies as the main research topic. However, overcoming the internal differences in the industry and comprehensively predicting the digital transformation of Chinese media companies from multiple dimensions has become an important issue to be understood. Based on the "TOE-I" theoretical framework, this study innovatively uses machine learning methods to predict the digital transformation of Chinese media companies and to analyze specific modes of the main driving factors affecting the digital transformation, using data from China's A-share-listed media companies from 2010 to 2020. The study found that environmental drivers can most effectively and accurately predict the digital transformation of Chinese media companies. Therefore, under sustained and stable economic and financial policies, guiding inter-industry competition and providing balanced digital infrastructure conditions are keys to bridging internal barriers in the media industry and promoting digital transformation. In the process of transformation from traditional content to digital production, media companies should focus on policy changes, economic benefits, the decision-making role of core managers, and the training and preservation of digital technology talent.