Triple-negative breast cancer (TNBC) represents a distinctive subtype, characterized by the absence of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2 (HER2). Due to its high inter-tumor and intra-tumor heterogeneity, TNBC poses significant chanllenges for personalized diagnosis and treatment. The advant of clustered regular interspaced short palindromic repeats (CRISPR) technology has profoundly enhanced our understanding of the structure and function of the TNBC genome, providing a powerful tool for investigating the occurrence and development of diseases. This review focuses on the application of CRISPR/Cas technology in the personalized diagnosis and treatment of TNBC. We begin by discussing the unique attributes of TNBC and the limitations of current diagnostic and treatment approaches: conventional diagnostic methods provide limited insights into TNBC, while traditional chemotherapy drugs are often associated with low efficacy and severe side effects. The CRISPR/Cas system, which activates Cas enzymes through complementary guide RNAs (gRNAs) to selectively degrade specific nucleic acids, has emerged as a robust tool for TNBC research. This technology enables precise gene editing, allowing for a deeper understanding of TNBC heterogeneity by marking and tracking diverse cell clones. Additionally, CRISPR facilitates high-throughput screening to promptly identify genes involved in TNBC growth, metastasis, and drug resistance, thus revealing new therapeutic targets and strategies. In TNBC diagnostics, CRISPR/Cas was applied to develop molecular diagnostic systems based on Cas9, Cas12, and Cas13, each employing distinct detection principles. These systems can sensitively and specifically detect a variety of TNBC biomarkers, including cell-specific DNA/RNA and circulating tumor DNA (ctDNA). In the realm of precision therapy, CRISPR/Cas has been utilized to identify key genes implicated in TNBC progression and treatment resistance. CRISPR-based screening has uncovered potential therapeutic targets, while its gene-editing capabilities have facilitated the development of combination therapies with traditional chemotherapy drugs, enhancing their efficacy. Despite its promise, the clinical translation of CRISPR/Cas technology remains in its early stages. Several clinical trials are underway to assess its safety and efficacy in the treatment of various genetic diseases and cancers. Challenges such as off-target effects, editing efficiency, and delivery methods remain to be addressed. The integration of CRISPR/Cas with other technologies, such as 3D cell culture systems, human induced pluripotent stem cells (hiPSCs), and artificial intelligence (AI), is expected to further advance precision medicine for TNBC. These technological convergences can offer deeper insights into disease mechanisms and facilitate the development of personalized treatment strategies. In conclusion, the CRISPR/Cas system holds immense potential in the precise diagnosis and treatment of TNBC. As the technology progresses and becomes more costs-effective, its clinical relevance will grow, and the translation of CRISPR/Cas system data into clinical applications will pave the way for optimal diagnosis and treatment strategies for TNBC patients. However, technical hurdles and ethical considerations require ongoing research and regulation to ensure safety and efficacy.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Lung cancer is one of the most common cancers worldwide, and its mortality rate remains high. In addition to conventional surgery, radiotherapy, and chemotherapy, immunotherapy methods have been developed and used in recent years for the treatment of non-small cell lung cancer (NSCLC). However, only a small number of patients with NSCLC can benefit from immunotherapy strategies, and some patients even have hyperprogression after receiving immunotherapy. Therefore, precision immunotherapy requires effective biomarkers to guide it. In this paper, tissue samples, blood samples, intestinal microbiota, and other biomarkers are reviewed according to different sample sources. Blood samples, including TCR immune repertoire, Tregs cells, cytokines, lactate dehydrogenase, and other markers, are summarized and analyzed to provide reference for clinicians' diagnosis and treatment decisions.

Humans ; Infant ; Child ; Infant, Newborn ; Developmental Disabilities ; Bronchopulmonary Dysplasia

Aim To investigate the role and potential mechanism of methyltransferase-like 5 (METTL5) in triple-negative breast cancer (TNBC) . Methods The expression of METTL5 in TNBC tumor tissues and cell lines was detected by immunohistochemistry and Western blot. After shRNA targeting METTL5 (shRNAMETTL5) was transfected into TNBC cells, cell proliferation, migration and invasion were detected by CCK-8, colony formation, wound healing and Transwell assays, respectively. Western blot was used to detect the expression of Wnt/p-catenin signaling-related key proteins. A xenograft tumor model was constructed to verify the effect of METTL5 knockdown on the growth of TNBC cells and Wnt/p-catenin signaling activity in vivo. Results The expression of METTL5 was up-regulated in TNBC tumor tissues and cell lines (P < 0. 01) . Knockdown of METTL5 significantly inhibited the proliferation, migration and invasion of TNBC cells and reduced the expression of Wnt/p-catenin signaling molecules (3-catenin, cyclin Dl, matrix metalloproteinase (MMP) -2 and MMP-7 (all P < 0. 01) . Knockdown of METTL5 reduced tumor growth and Wnt/pcatenin signaling activity in vivo. Conclusions Knockdown of METTL5 can inhibit the proliferation, migration and invasion of TNBC cells, which may be related to the inhibition of Wnt/p-catenin signaling pathway.

Idiosyncratic drug-induced liver injury (IDILI) has long posed a challenging and pivotal concern in pharmaceutical research. The complex composition of traditional Chinese medicine (TCM) has introduced a bottleneck in current research, hindering the elucidation of the component basis associated with IDILI in TCM. Using Epimedii Folium (EF) and Psoraleae Fructus (PF) as illustrative examples, this study endeavors to establish an in vitro evaluation model, providing a high-throughput and preliminary assessment method for screening components related to TCM-induced IDILI. A TNF-α-mediated HepG2 susceptible model was first established in this study, with the focus on the index components present in EF and PF. The release of lactate dehydrogenase (LDH) in the cell supernatant served as the detection index. A concentration-toxicity response curve was constructed, and the hepatotoxic components of EF and PF were identified utilizing the synergistic toxicity index. The LDH results unveiled the hepatotoxic effects of bavachin, backuchiol, isobavachin, neobavaisoflavone, psoralidin, isobavachalcone, icarisid I, and icarisid II on both normal and susceptible cells, categorizing these 8 components as both direct hepatotoxicity components and idiosyncratic hepatotoxicity components. Bavachin and neobavaisoflavone exhibited no hepatotoxicity on normal cells but demonstrated significant effects on susceptible cells, designating them as potential idiosyncratic susceptible hepatotoxicity components. The study further delineated that 10 EF components and 3 PF components were direct immune-promoting hepatotoxicity components. Additionally, 14 idiosyncratic immune-promoting hepatotoxicity components were identified, encompassing 10 EF components and 4 PF components, with neobavaisoflavone, bavachinin, and isobavachin being potential idiosyncratic susceptible immune-promoting hepatotoxicity components. Synergistic toxicity index results indicated that 13 idiosyncratic immune-promoting hepatotoxicity components (except anhydroicaritin) combined with bavachin demonstrated synergistic hepatotoxicity on susceptible cells. Notably, 3 idiosyncratic susceptible immune-promoting hepatotoxicity components combined with bavachin exhibited synergistic hepatotoxicity, with neobavaisoflavone displaying the highest synergistic toxicity index and bavachinin the lowest. In summary, this methodology successfully screens hepatotoxic and immune-promoting hepatotoxic components in EF and PF, distinguishing the types of components inducing hepatotoxicity, evaluating the hepatotoxicity degree of each component, and elucidating the synergistic relationships among them. Importantly, these findings align with the characteristics of IDILI. The method provides an effective model tool for the fundamental research of TCM-related IDILI components.

Based on the interaction between supramolecule of traditional Chinese medicine and enterobacteria, the material basis of Rhei Radix et Rhizoma and Coptidis Rhizoma was explored. Scanning electron microscopy (SEM) and dynamic light scattering (DLS) were used to characterize the morphological differences of Rhubarb single decoction, Coptis single decoction and Rhubarb and Coptis co-decoction. An in vitro antibacterial model (E. coli, E. faecium and B. subtilis) was established to evaluate the damage effect of the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma on enterobacteria. Ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to analyze the changes of chemical components of single decoctions and co-decoctions. The co-decoction of Rhei Radix et Rhizoma and Coptidis Rhizoma was turbid after decocting. The spherical particles of 300-400 nm were observed under SEM, and the co-decoction was more uniform and stable than that of single decoction. The interaction between supramolecules formed after the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma and enterobacteria was significantly different from that of single decoction. In the process of interaction between supramolecules and enterobacteria, the spherical state was maintained, and the medicinal ingredients in Coptidis Rhizoma or Rhei Radix et Rhizoma were blocked, which could effectively alleviate the damage to enterobacteria. This study provided a reference for subsequent studies on the regulation of intestinal flora homeostasis by the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma.

ObjectiveTo analyze the prevalence of myopia among the primary school students in Shanghai, and to explore its relationship with sleep duration and sleep quality, providing references for precise myopia prevention. MethodsA cross-sectional survey and random sampling were employed. Between April and May 2023, a total of 1 889 students from grades 1 to 5 in Jiading District, Shanghai, were selected for vision testing and a questionnaire on children’s sleeping habits and relevant factors were conducted using the Children’s Sleep Habits Questionnaire (CSHQ) in Chinese. The relationship between myopia and sleep patterns was analyzed using chi-square tests and a multivariate logistic regression model. ResultsThe overall myopia rate among the primary school students in Jiading District, Shanghai, was 35.6%. The results of univariate analysis showed that in the myopia group, the incidences of sleep disturbance and sleep anxiety were lower compared to children without myopia, while the incidences of sleep continuity and parasomnias were higher than there in the non-myopia group (χ²=12.816, 10.292, 10.971, 3.917, all P<0.05). Additionally, among the elementary school students with an average daily sleep duration of less than 10 hours, the prevalence of myopia was higher. The multivariate logistic regression analysis revealed that factors such as being female (OR=1.291, 95%CI: 1.044‒1.597), higher grade levels (2^nd grade: OR=2.174, 95%CI: 1.471‒3.212; 3^rd grade:OR=3.850, 95%CI: 2.648‒5.598; 4^th grade: OR=8.906, 95%CI: 6.154‒12.890; 5^th grade: OR=12.299, 95%CI: 8.433‒17.937), having one parent (OR=2.250, 95%CI: 1.757‒2.881) or both parents(OR=3.623, 95%CI: 2.719‒4.827) with myopia, and parasomnias (OR=1.518, 95%CI: 1.065‒2.163) were associated with a higher detection rate of myopia. ConclusionThe prevalence of myopia is notably high among the primary school students in Jiading District, Shanghai, and there is an association between the occurrence of myopia and parasomnias.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective To compare the pharmacokinetic profiles of the two teriflunomide tablets in healthy Chinese subjects under fasting and fed conditions and to evaluate their bioequivalence and safety.Methods A randomized,open,single-dose,parallel trial design was used to enroll 31 and 32 healthy Chinese male subjects in the fasting and fed groups,who were randomized to a single oral dose of 14 mg of either reference or test preparation of teriflunomide tablets.The plasma concentrations of teriflunomide were determined using liquid chromatography-tandem mass spectrometry method,and Phoenix WinNonlin 8.1 software was used to calculate pharmacokinetic parameters and perform bioequivalence analysis.Results Subjects received a single oral dose of the reference and test formulations of teriflunomide.The main pharmacokinetic parameters of teriflunomide in the fasting group were as follows:Cmax were(2.14±0.27)and(2.27±0.33)μg·mL-1,AUC0-72h were(105.70±11.20)and(107.72±11.77)μg·mL-1·h,tmax was 1.49 and 0.99 h;the main pharmacokinetic parameters of teriflunomide in the fed group were as follows:Cmaxwere(1.83±0.17)and(1.75±0.22)μg·mL-1,AUC0-72h were(102.66±9.18)and(101.57±13.01)μg·mL-1·h,tmax was 4.01 and 4.99 h.The 90％confidence intervals for the geometric means of Cmax and AUC0-72h for reference and test preparations in the fasting and fed groups were in the range of 80％to 125％.Conclusion The pharmacokinetic characteristics of the 2 formulations were similar under fasting and fed administration conditions,with good bioequivalence and safety;Postprandial administration may delay the time to peak of the drug.