Background and aims Hepatocellular carcinoma (HCC) cells are metabolically reprogrammed for excessive uptake and metabolism of many nutrients. The tumor suppressive microRNA-148a-3p (miR-148a-3p) is downregulated in HCC, whereas its function in regulating HCC cell metabolism remains obscure. Herein we aimed to delineate the role of miR-148a-3p in HCC cell metabolism by using novel bioengineered miR-148a-3p (BioRNALeu/miR-148a-3p) agent produced in vivo. Methods BioRNALeu/miR-148a-3p was designed by using human leucyl transfer RNA fused hsa-pre-miR-34a carrier, overexpressed in Escherichia coli (E. coli), and purified to high homogeneity. After transfection into HCC cells, the released miR-148a-3p levels were assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cell proliferation was determined by CellTiter-Glo assays. Targets were validated by dual-luciferase reporter assays, immunoblotting, and immunofluorescence confocal imaging. Glycolysis capacity was evaluated by Seahorse XF assays, and glucose, lactate, and amino acid levels were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods. Results BioRNALeu/miR-148a-3p was efficiently processed into target miR-148a-3p in HCC cells to effectively inhibit cell proliferation in a dose- and time-dependent manner. Mechanistically, miR-148a-3p suppressed the protein levels of glucose transporter GLUT1/SLC2A1 and L-type amino acid transporter LAT1/SLC7A5 via acting on their 3′-untranslated regions, as well as amino acid transporter ASCT2/SLC1A5. These, in turn, led to a reduction of glucose uptake, lactate production, and glycolytic flux in HCC cells, and alteration of intracellular amino acid metabolome including glutamine, leucine, phenylalanine, tyrosine, and methionine. Conclusions Reintroduction of miR-148a-3p into HCC cells modulates glucose and amino acid metabolism via regulating multiple SLC transporters, thereby suppressing HCC cell viability. These findings highlight the role of miR-148a-3p in HCC cell metabolism and potential of bioengineered miRNA molecules for functional studies and therapeutic development.

This paper systematically elaborates on the key points of diagnosis and differential diagnosis of salivary gland tumors characterized by a substantial amount of extracellular mucus as a main or prominent feature, and clarifies the core differential features. The term "mucus-rich" specifically denotes that mucus is a major component of the tumor, rather than a focal or minor one. This phenomenon is associated with distinct histogenetic mechanisms: it may result from specific genetic mutations (e.g., AKT1 E17K in mucinous adenocarcinoma) that drive ductal epithelial differentiation into mucus-secreting cells, or from myoepithelial cells secreting glycosaminoglycans that form a myxoid stroma. Salivary gland tumors with abundant extracellular mucus include mucinous cystadenoma, sialadenoma papilliferum-like intraductal papillary tumors, mucinous myoepithelioma, pleomorphic adenoma with mucin-rich stroma, mucinous adenocarcinoma, low-grade mucoepidermoid carcinoma, mucin-rich salivary duct carcinoma and intestinal-type adenocarcinoma. The diagnosis of these tumors is complicated by the dual nature of extracellular mucus: while it is a defining feature of some entities, it can also obscure key diagnostic architectural features in others, leading to histological overlap and inconspicuous diagnostic areas. Given the frequent histological morphological overlap among these tumors, immunohistochemical findings and molecular characteristics have emerged as crucial differential diagnostic criteria. Core differential diagnostic points include the following: histologically, there must be meticulous identification of typical structures obscured by mucin (such as squamoid cells in mucoepidermoid carcinoma and apocrine features in salivary duct carcinoma); in immunohistochemical staining, CK20 is useful for distinguishing intestinal-type adenocarcinoma (positive) from mucinous adenocarcinoma (negative), while androgen receptor aids in differentiating salivary duct carcinoma (positive) from mucoepidermoid carcinoma (negative); and molecular testing plays a critical role in definitive diagnosis (e.g., the AKT1 E17K mutation for mucinous adenocarcinoma, MAML2 rearrangement for mucoepidermoid carcinoma, and MEF2C::SS18 fusion for microsecretory adenocarcinoma). This paper systematically summarizes the core pathological features and differential diagnostic points of mucin-rich salivary gland tumors, aiming to provide a practical reference for clinical pathological diagnosis.

Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

Objective In order to understand the current resistance status of Aedes albopictus(Ae. albopictus) adult population to commonly used insecticides and the resistance dynamics development in Zhejiang Province and provide a theoretical basis for the scientific and rational use of hygienic insecticides. Methods Resistance determination was carried out using the diagnostic dose method(GB/T 26347-2010)recommended by WHO in the adult mosquito contact cylinder method to monitor the resistance of Ae. albopictus field populations in 11 cities and districts in Zhejiang Province in 2024. Results The monitoring result showed that adult Ae. albopictus in 11 areas were resistant or suspected resistant populations to both cis-cypermethrin and permethrin; suspected and resistant populations to the organophosphate insecticide malathion were as high as 81.82%; while suspected resistance to the carbamate insecticide residual carbofuran accounted for 45.45%, and the rest of the monitoring sites were sensitive to it. Conclusions The result suggest that the generalized resistance of Ae. albopictus populations to pyrethroids and organophosphorus insecticides in the field in Zhejiang Province needs to be highly emphasized. In future mosquito vector and mosquito-borne disease control, insecticides should be selected based on the resistance monitoring information, while following scientific guidelines for insecticide use.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Gastric contrast-enhanced ultrasound includes oral contrast-enhanced ultrasound (OCUS) and double contrast-enhanced ultrasound (DCEUS),which can provide valuable clinical information about tumor morphology,vascular characteristics,and treatment responses.OCUS can clearly identify the gastric wall structure and the extent and depth of lesions by applying oral contrast agents.DCEUS,based on OCUS combined with venography,can display the anatomical and perfusion characteristics of lesions.In recent years,gastric contrast agents and imaging techniques have developed rapidly.However,the clinical application of gastric contrast-enhanced ultrasound is still in the developmental stage.This article reviews the clinical status of OCUS and DCEUS in the screening,diagnosis,staging,pathological typing,and treatment evaluation of gastric cancer.Studies have shown that gastric contrast-enhanced ultrasound has high sensitivity and specificity in the assessment of diagnosis and T-staging of gastric cancer.Furthermore,gastric contrast-enhanced ultrasound has the advantages of being cost-effective,convenient,non-invasive,free from radiation exposure,real-time,and easy to repeat.In the diagnosis and treatment of gastric cancer,it is expected to become one of the important imaging assessment tools.
Humans ; Stomach Neoplasms/diagnostic imaging* ; Contrast Media ; Ultrasonography/methods*

Immunotherapy has emerged as a revolutionary approach to treat immune-related diseases. Dendritic cells (DCs) play a pivotal role in orchestrating immune responses, making them an attractive target for immunotherapeutic interventions. Modulation of gene expression in DCs using genome editing techniques, such as the CRISPR-Cas system, is important for regulating DC functions. However, the precise delivery of CRISPR-based therapies to DCs has posed a significant challenge. While lipid nanoparticles (LNPs) have been extensively studied for gene editing in tumor cells, their potential application in DCs has remained relatively unexplored. This study investigates the important role of cholesterol in regulating the efficiency of BAMEA-O16B lipid-assisted nanoparticles (BLANs) as carriers of CRISPR/Cas9 for gene editing in DCs. Remarkably, BLANs with low cholesterol density exhibit exceptional mRNA uptake, improved endosomal escape, and efficient single-guide RNA release capabilities. Administration of BLAN_mCas9/gPD-L1 results in substantial PD-L1 gene knockout in conventional dendritic cells (cDCs), accompanied by heightened cDC1 activation, T cell stimulation, and significant suppression of tumor growth. The study underscores the pivotal role of cholesterol density within LNPs, revealing potent influence on gene editing efficacy within DCs. This strategy holds immense promise for the field of cancer immunotherapy, offering a novel avenue for treating immune-related diseases.

Objective To initially explore the possibility of applying the fluorescence micro-optical sectioning tomography(fMOST)high-resolution 3D reconstruction system to the morphological study of the intestinal nervous system and to preliminarily establish a method for studying the morphology of the intestinal nervous system using this system.Methods fMOST high-resolution 3D reconstruction system was used to study the intestinal nervous system of C57BL/6 mice in detail.Based on this method,a new morphological method of the visceral nervous system of small animal models was explored at the single-cell level.Results Compared with the large intestine,the small intestine lacked the typical myenteric plexus(Auerbach),deep mucosal plexus(Henley),and submucosal superficial plexus(Meissner).Conclusion The result of this paper provide a clearer and systematic display of the anatomical structure of the enteric nervous system in C57BL/6 mice,and further clarify the similarities and differences between the enteric nervous system of mice and human,and provide a theoretical basis for its rational application in the study of digestive system diseases.The morphological study of fMOST high-resolution 3D reconstruction system is not limited to the central nervous system,but can be extended to the morphological study of multiple visceral nervous systems.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.