ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Apurinic/apyrimidinic endonuclease 1(APE 1)is a multifunctional protein that plays important roles in DNA repair and regulation of gene expression.Because APE 1 is overexpressed in various cancers,it can serve as a cancer biomarker for aiding clinical diagnosis,guiding therapy,and monitoring prognosis.On this basis,a label-free fluorescent probe was designed based on the primer exchange reaction(PER)strategy for highly sensitive detection of APE 1 activity.In the absence of APE 1,the structure of catalytic hairpin(HP)was stable and could not form G-quadruplex.Therefore,the background fluorescence of this sensing system was very low due to the dissociation of thioflavin T(ThT).In the presence of APE 1,the apurinic/apyrimidinic(AP)site of HP was cleaved by APE 1 and a short nucleic acid fragment that acted as a primer to initiate PER was generated.After PER reaction,a large number of G-quadruplex were produced,which could specifically bind with ThT and resulted in significant increase of fluorescence signal.The combination of low background design of HP and PER amplification made this biosensor had high sensitivity with a detection limit(3σ)of 0.0008 U/mL.Furthermore,the primer sequence was directly generated by the cleavage of APE 1 without additional addition,which not only increased the specificity of the reaction,but also simplified the experiment procedure.Moreover,the use of label-free fluorescence signal reduced the cost of the experiment,and realized rapid detection of APE 1.Finally,this sensor was used to detect APE 1 in human serum samples with spiked recoveries of 91%-104%,proving great potential in study of biological enzyme.

Objective To establish a laser diffraction method for determining globule size distribution in medium and long chain fat emulsion injection(C8～24Ve).Methods The Mastersizer 3000 laser particle size analyzer and Hydro EV wet sampling device were used,with water as the dispersion medium.Critical parameters,including refractive index,absorption coefficient,obscuration,measurement duration,stirring speed,and sonication parameters,were systematically optimized.Comparative evaluations were conducted across different computational models(Mie vs.Fraunhofer theories)and instrument platforms.Results The optimized optical parameters for particle size distribution analysis of medium and long chain fat emulsion injection(C8～24Ve)were determined as follows:absorption rate 0.001,refractive index 1.52,measurement duration 10 s,stirring speed 1 200 r·min-1,with no sonication applied.Under these conditions,the method demonstrated satisfactory precision,repeatability,and robustness.Conclusions This method demonstrates operational simplicity,high accuracy,and excellent reproducibility,making it suitable for particle size distribution analysis of medium and long chain fat emulsion injection(C8～24Ve).The established protocol provides a valuable reference for the development of particle size determination methods for emulsion formulations.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Transfer-RNA derived small RNA(tsRNA),a re-cently discovered class of non-coding RNA,is produced by ma-ture tRNA or tRNA precursor through the mediation of specific endonucleases.By regulating gene expression at the transcrip-tional and post transcriptional levels and acting as an epigenetic regulator,tsRNA plays an important role in the physiological and pathological processes of many organisms.Therefore,it has gradually become a research hotspot in biomedicine and attracted widespread attention.Moreover,there is increasing evidence that tsRNA is involved in the occurrence and development of many neuropsychiatric diseases through participating in stress re-sponse,cell proliferation and apoptosis,neural development,synaptic plasticity,neuroinflammation and immune regulation,epigenetic regulation,RNA processing,and protein translation regulation.This article mainly discusses the generation,classifi-cation and biological functions of tsRNA,and elaborates on the role and possible mechanisms of tsRNA in neurodevelopment and neuropsychiatric disorders,thereby further revealing the poten-tial of tsRNA as a reliable biomarker and therapeutic target for neuropsychiatric disorders.