Water-Soluble Lipophilic Near-Infrared Region II Fluorophores for High-Brightness Lipid Layer and Lipid Droplets Imaging Applications.

Fluorescence imaging in the second near-infrared region (NIR-II, 1000-1700 nm) has garnered considerable attention for displaying the biological information of deep tissues. However, the lack of biocompatible contrast agents with bright NIR-II emission has hampered the precise clinical application of deep tissue imaging. Here, a lipophilic enhancement strategy employing donor-acceptor-donor (D-A-D) molecules, introducing long alkoxy chains and quaternary ammonium salts for the development of highly bright water-soluble NIR-II fluorophores (BBTD-2C-N), is described. Notably, liposome-encapsulated BBTD-2C-N nanoparticles (B-2C-N/DMPC) in aqueous solution exhibit a 1.8-fold increase in NIR-II fluorescence brightness compared to free BBTD-2C-N in methanol. Avoidance of the aggregation-caused quenching effect and enhanced NIR-II fluorescence are attributed to significantly attenuated π-π stacking interactions and maintained monodisperses in the hydrophobic liposome shell. Moreover, BBTD-2C-N demonstrates superior performance in visualizing lipid droplet-rich HeLa cells in vitro, as well as precise monitoring of adipose tissue and fatty liver in vivo. This study reveals a new avenue for the development of bright NIR-II fluorophores and precise in vivo imaging.

Photo-Amplified Plasma Membrane Rupture by Membrane-Anchoring NIR-II Small Molecule Design for Improved Cancer Photoimmunotherapy.

Immunotherapy is a promising cancer treatment method for eradicating tumor cells by enhancing the immune response. However, there are several major obstacles to conventional phototherapy-mediated immune responses, including inadequate immunogenicity and immunosuppressive environment. Here, we present a novel photoimmunotherapy modality-the development of membrane-anchoring small molecule inducing plasma membrane rupture (PMR) by NIR-II photo-stimulation, thus evoking cell necrotic death and enhancing antitumor immunotherapy. Our top-performing membrane-anchoring small molecule (CBT-3) exhibits temperature-tunable PMR efficiency, allowing rapid necrotic death in cancer cells at 50 µM dose by using exogenous NIR-II light-mediated mild photothermal effect (1064 nm, 0.6 W cm-2). Further evidence indicated that this gentle therapeutic approach activated inflammatory signaling pathways in cells, enhanced immunogenic cell death, and reshaped the immunosuppressive tumor microenvironment, ultimately promoting systemic antitumor immune responses in vivo. This study represents the first instance of utilizing NIR-II photo-amplified PMR effect based on membrane-anchoring small molecule, providing a novel avenue for advancing cancer photoimmunotherapy.

Clinical study on conversion therapy of hepatocellular carcinoma - summary and comparison of clinical data from a single center of consecutive four years.

AIM: The purpose of this study was to interpret real-world clinical data to analyze the surgical safety and survival outcomes of patients with initial unresectable hepatocellular carcinoma (uHCC) after conversion therapy. METHODS: A retrospective analysis was performed on 2984 hepatocellular carcinoma (HCC) patients hospitalized in Shandong Cancer Hospital Affiliated to Shandong First Medical University from June 1st, 2019 to June 1st, 2023. Clinicopathological features, response to systemic and/or loco-regional treatments, surgical resection rate after conversion therapy, surgical safety, and postoperative recurrence were analyzed. RESULTS: A total of 38 patients were successfully converted to obtain surgical resection. 35 patients underwent radical resection. A high objective response rate (ORR) (52.6% under RECIST v1.1 and 78.9% under mRECIST criteria) was observed in patients under conversion therapy, and the disease control rate (DCR) was 100%. Pathologic complete response (pCR) was 42.9%. Treatment-related adverse events (TRAEs) of any grade were observed in 37 patients (97.4%). Safety of conversion or direct surgery continues to improve. The median follow-up time was 19.3 months. The 1-year Disease-free survival (DFS) rate of patients with direct surgery and patients with conversion surgery were 91.4% and 86.8%, respectively. CONCLUSIONS: With conversion therapy, a small percentage (1.81%) of uHCC patients are likely to be converted to radical resection. Local combined systemic therapy is a relatively safe and effective conversion therapy, and the safety of surgery is gradually improved after successful conversion. Preliminary follow-up data showed satisfactory survival benefits for patients undergoing conversion surgery. TRIAL REGISTRATION: This was a retrospective study and it did not interfere with treatment decisions.

Occurrence, Source Apportionment, and Risk Assessment of Antibiotics in Mangrove Sediments from the Lianzhou Bay, China.

In recent years, the widespread application of antibiotics has raised global concerns, posing a severe threat to ecological health. In this study, the occurrence, source, and ecological risks of 39 antibiotics belonging to 5 classes in mangrove sediments from Lianzhou Bay, China, were assessed. The total concentrations of the antibiotics (∑39 antibiotics) ranged from 65.45 to 202.24 ng/g dry weight (dw), with an average of 142.73 ± 36.76 ng/g dw. The concentrations of these five classes of antibiotics were as follows: Sulfonamides (SAs) > Tetracyclines (TCs) > Fluoroquinolones (QUs) > Penicillin (PCs) > Macrolides (MLs). The spatial distribution of antibiotics varied as high tidal zone > middle tidal zone > low tidal zone. The total organic carbon (TOC), pH, nitrate (NO3--N), and nitrite (NO2--N) of the sediment significantly influenced the distribution of antibiotics (p < 0.05). A source analysis identified untreated sewage from aquaculture as the primary source of antibiotics in the local mangrove. A risk assessment revealed that ciprofloxacin, norfloxacin, ofloxacin of QUs, and tetracycline of TCs exhibited medium risks to algae in certain sampling sites, while other antibiotics exhibited low or no risks to all organisms. Nevertheless, the total risk of all the detected antibiotics to algae was medium in 95% of the sites. The overall ecological risk level of antibiotics in the middle tidal zone was slightly lower than in the high tidal zone and the lowest in the low tidal zone. In summary, the experimental results provided insights into the fate and transport behaviors of antibiotics in mangrove sediments from Lianzhou Bay.

Delay learning based on temporal coding in Spiking Neural Networks.

Spiking Neural Networks (SNNs) hold great potential for mimicking the brain's efficient processing of information. Although biological evidence suggests that precise spike timing is crucial for effective information encoding, contemporary SNN research mainly concentrates on adjusting connection weights. In this work, we introduce Delay Learning based on Temporal Coding (DLTC), an innovative approach that integrates delay learning with a temporal coding strategy to optimize spike timing in SNNs. DLTC utilizes a learnable delay shift, which assigns varying levels of importance to different informational elements. This is complemented by an adjustable threshold that regulates firing times, allowing for earlier or later neuron activation as needed. We have tested DLTC's effectiveness in various contexts, including vision and auditory classification tasks, where it consistently outperformed traditional weight-only SNNs. The results indicate that DLTC achieves remarkable improvements in accuracy and computational efficiency, marking a step forward in advancing SNNs towards real-world applications. Our codes are accessible at https://github.com/sunpengfei1122/DLTC.

Hepatic arterial infusion chemotherapy enhances the efficacy of lenvatinib plus PD-1 inhibitors in hepatocellular carcinoma patients with tumor thrombosis in the inferior vena cava and/or right atrium.

RATIONALE AND OBJECTIVES: Hepatocellular carcinoma (HCC) with invasion into the inferior vena cava (IVC) or the right atrium (RA) presents significant therapeutic challenges due to its rapid progression and limited available treatments. MATERIALS AND METHODS: This retrospective study evaluated the effectiveness of hepatic arterial infusion chemotherapy alongside lenvatinib and PD-1 inhibitors (HAIC-Len-PD1) compared to treatment with only lenvatinib and PD-1 inhibitors (Len-PD1). A total of 115 patients with HCC and IVC or RA invasion were included. We analyzed groups for median overall survival (OS) and progression-free survival (PFS) through the Kaplan-Meier method, along with tumor response rates, disease control rates, and adverse event frequencies. RESULTS: The HAIC-Len-PD1 treatment showed a marked improvement in median OS (22.2 vs. 14.4 months; P = 0.007) and median PFS (13.8 vs. 5.1 months; P = 0.001) over the Len-PD1 regimen. There was also a higher overall response rate (68.7% vs. 37.5%; P < 0.05) and disease control rate (92.5% vs. 75%; P < 0.05) observed in the HAIC-Len-PD1 group. A subgroup analysis demonstrated consistent survival benefits across diverse patient demographics. Although the incidence of adverse events was higher in the HAIC-Len-PD1 group, these were generally manageable and well-tolerated. CONCLUSION: The combined regimen of HAIC, lenvatinib, and PD-1 inhibitors may improve survival and tumor management in HCC patients with IVC or RA invasion, suggesting a potential therapeutic option for this critically at-risk group. Further research in the form of randomized controlled trials are needed to verify these findings for advanced-stage HCC with vascular compromise.

Ultrasound Spectral Combined With Clinical Pathological Parameters in Prediction of Axillary Lymph Node Metastatic in Breast Cancer.

OBJECTIVES: To explore the clinical value of the nomogram based on ultrasound spectral combined with clinical pathological parameter in predicting axillary lymph node metastasis in breast cancer. METHODS: We prospectively gathered clinicopathologic and ultrasonic data from 240 patients confirmed breast cancer. The risk factors of axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression, and the prediction model was established. The model calibration, predictive ability, and diagnostic efficiency in the training set and the testing set were analyzed by receiver operating characteristic curve and calibration curve analysis, respectively. RESULTS: Univariate analysis showed that lymph node metastasis was related with tumor size, Ki-67, axillary ultrasound, ultrasound spectral quantitative parameter, internal echo, and calcification (P < .05). Multivariate logistic regression analysis showed that the Ki-67, axillary ultrasound, quantitative parameter (the mean of the mid-band fit in tumor and posterior tumor) were independent risk factors of axillary lymph node metastasis (P < .05). The models developed using Ki-67, axillary ultrasound, and quantitative parameters for predicting axillary lymph node metastasis demonstrated an area under the receiver operating characteristic curve of 0.83. Additionally, the prediction model exhibited outstanding predictability for axillary lymph node metastasis, as evidenced by a Harrell C-index of 0.83 (95% confidence interval 0.73-0.93). CONCLUSION: Axillary ultrasound combined with Ki-67 and ultrasound spectral parameters has the potential to predict axillary lymph node metastasis in breast cancer, which is superior to axillary ultrasound alone.

Preliminary experiments on interpretable ChatGPT-assisted diagnosis for breast ultrasound radiologists.

Background: Ultrasound is essential for detecting breast lesions. The American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) classification system is widely used, but its subjectivity can lead to inconsistency in diagnostic outcomes. Artificial intelligence (AI) models, such as ChatGPT-3.5, may potentially enhance diagnostic accuracy and efficiency in medical settings. This study aimed to assess the utility of the ChatGPT-3.5 model in generating BI-RADS classifications for breast ultrasound reports and its ability to replicate the "chain of thought" (CoT) in clinical decision-making to improve model interpretability. Methods: Breast ultrasound reports were collected, and ChatGPT-3.5 was used to generate diagnoses and treatment plans. We evaluated GPT-4's performance by comparing its generated reports to those from doctors with various levels of experience. We also conducted a Turing test and a consistency analysis. To enhance the interpretability of the model, we applied the CoT method to deconstruct the decision-making chain of the GPT model. Results: A total of 131 patients were evaluated, with 57 doctors participating in the experiment. ChatGPT-3.5 showed promising performance in structure and organization (S&O), professional terminology and expression (PTE), treatment recommendations (TR), and clarity and comprehensibility (C&C). However, improvements are needed in BI-RADS classification, malignancy diagnosis (MD), likelihood of being written by a physician (LWBP), and ultrasound doctor artificial intelligence acceptance (UDAIA). Turing test results indicated that AI-generated reports convincingly resembled human-authored reports. Reproducibility experiments displayed consistent performance. Erroneous report analysis revealed issues related to incorrect diagnosis, inconsistencies, and overdiagnosis. The CoT investigation supports the potential of ChatGPT to replicate the clinical decision-making process and offers insights into AI interpretability. Conclusions: The ChatGPT-3.5 model holds potential as a valuable tool for assisting in the efficient determination of BI-RADS classifications and enhancing diagnostic performance.

Predicting axillary lymph node metastasis in breast cancer based on ultrasound radiofrequency time-series analysis.

BACKGROUND: The status of axillary lymph nodes (ALN) plays a critical role in the management of patients with breast cancer. It is an urgent demand to develop highly accurate, non-invasive methods for predicting ALN status. PURPOSE: To evaluate the efficacy of ultrasound radiofrequency (URF) time-series parameters, in combination with clinical data, in predicting ALN metastasis in patients with breast cancer. MATERIAL AND METHODS: We prospectively gathered clinicopathologic and ultrasonic data from patients diagnosed with breast cancer. Various machine-learning (ML) models were developed using all available features to determine the most efficient diagnostic model. Subsequently, distinct prediction models were created using the optimal ML model, and their diagnostic performances were evaluated and compared. RESULTS: The study encompassed 240 patients, of whom 88 had lymph node metastases. A leave-one-out cross-validation (LOOCV) method was used to split the entire dataset into training and testing subsets. The random forest ML model outperformed the other algorithms, with an area under the curve (AUC) of 0.92. Prediction models based on clinical, ultrasonic, URF parameters, clinical + ultrasonic, clinical + URF, and ultrasonic + URF parameters had AUCs of 0.56, 0.79, 0.78, 0.90, 0.80, and 0.84, respectively, in the testing set. The comprehensive diagnostic model (clinical + ultrasonic + URF parameters) demonstrated strong diagnostic capability, with an AUC of 0.94 in the testing set, exceeding any single prediction model. CONCLUSION: The combined model (clinical + ultrasonic + URF parameters) could be used preoperatively to predict lymph node status, offering valuable input for the design of individualized surgical approaches.

Genetic variation in CCDC93 is associated with elevated central systolic blood pressure, impaired arterial relaxation, and mitochondrial dysfunction.

Genetic studies of blood pressure (BP) traits to date have been performed on conventional measures by brachial cuff sphygmomanometer for systolic BP (SBP) and diastolic BP, integrating several physiologic occurrences. Genetic associations with central SBP (cSBP) have not been well-studied. Genetic discovery studies of BP have been most often performed in European-ancestry samples. Here, we investigated genetic associations with cSBP in a Chinese population and functionally validated the impact of a novel associated coiled-coil domain containing 93 (CCDC93) gene on BP regulation. An exome-wide association study (EWAS) was performed using a mixed linear model of non-invasive cSBP and peripheral BP traits in a Han Chinese population (N = 5,954) from Beijing, China genotyped with a customized Illumina ExomeChip array. We identified four SNP-trait associations with three SNPs, including two novel associations (rs2165468-SBP and rs33975708-cSBP). rs33975708 is a coding variant in the CCDC93 gene, c.535C>T, p.Arg179Cys (MAF = 0.15%), and was associated with increased cSBP (ß = 29.3 mmHg, P = 1.23x10-7). CRISPR/Cas9 genome editing was used to model the effect of Ccdc93 loss in mice. Homozygous Ccdc93 deletion was lethal prior to day 10.5 of embryonic development. Ccdc93+/- heterozygous mice were viable and morphologically normal, with 1.3-fold lower aortic Ccdc93 protein expression (P = 0.0041) and elevated SBP as compared to littermate Ccdc93+/+ controls (110±8 mmHg vs 125±10 mmHg, P = 0.016). Wire myography of Ccdc93+/- aortae showed impaired acetylcholine-induced relaxation and enhanced phenylephrine-induced contraction. RNA-Seq transcriptome analysis of Ccdc93+/- mouse thoracic aortae identified significantly enriched pathways altered in fatty acid metabolism and mitochondrial metabolism. Plasma free fatty acid levels were elevated in Ccdc93+/- mice (96±7mM vs 124±13mM, P = 0.0031) and aortic mitochondrial dysfunction was observed through aberrant Parkin and Nix protein expression. Together, our genetic and functional studies support a novel role of CCDC93 in the regulation of BP through its effects on vascular mitochondrial function and endothelial function.

Unlocking epoxy thermal management capability via hierarchical Ce-MOF@MoS2 hybrid constructed by in-situ growth method.

This study demonstrates the preparation of needle-like Ce-MOF crystals on molybdenum disulfide (MoS2) nanosheets using in-situ growth technology. This hybrid structure significantly enhances the thermal management and mechanical properties of thermosetting epoxy resin (EP). Specifically, EP/Ce-MOF@MoS2-3 exhibits a notable increase in tensile strength (TS) to 50.87 MPa and elongation at break (EB) to 10.84 %. Moreover, Ce-MOF@MoS2 provides synergistic flame retardant benefits, reducing the peak heat release rate (pHRR) and total heat release (THR) of EP/Ce-MOF@MoS2-3 by 38 % and 12.64 %, respectively, compared to EP-0. Additionally, Ce-MOF@MoS2 suppresses smoke and reduces toxic emissions; at a 3 % loading, it decreases CO and CO2 production in EP nanocomposites by 48.8 % and 38.7 %, respectively. Thus, this Ce-MOF@MoS2 hybrid, synthesized via in-situ growth, offers a novel approach for developing EP nanocomposites with superior thermal management and mechanical properties, along with effective flame retardancy and reduced hazardous emissions during thermal events.

Analysis of efficacy and safety for the combination of tislelizumab and regorafenib in advanced hepatocellular carcinoma: A prospective clinical study.

BACKGROUNDS: Programmed death receptor 1 (PD-1) monoclonal antibody has been approved for the first and second-line treatments of hepatocellular carcinoma (HCC). This study aimed to evaluate the efficacy and safety of tislelizumab + regorafenib as a second-line treatment option for advanced HCC. METHODS: Treatment-related adverse events (TRAEs) were the primary endpoints in this clinical trial comprising 28 patients with advanced HCC. The secondary endpoints included objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). RESULTS: According to the mRECIST 1.1 evaluation criteria, the ORR was 28.6%. Complete and partial response were observed in 3 and 5 patients, respectively; stable disease was observed in 12 patients (DCR, 71.4%). The median PFS was 6.4 months. The incidence of grade 1-2 and 3-4 TRAEs was 57.1% and 39.3%, respectively. CONCLUSION: This study suggests that tislelizumab + regorafenib can be used as a second-line treatment for advanced HCC.

A universal optical aptasensor for antibiotics determination based on a new high-efficiency Förster resonance energy transfer pair.

A novel "turn-on" aptasensor for kanamycin (Kana) detection based on a new Förster resonance energy transfer (FRET) pair is reported. A new organic small molecule was employed as a high-efficiency quencher for fluorophore. Based on specific interactions between ssDNA and the quencher, an ingenious and amplified strategy was designed. In the absence of the target, the fluorescence of the fluorophore labeled at the end of the aptamer was quenched. After the binding of the aptamer to the target, the fluorescence was recovered and amplified. The proposed aptasensor showed high specificity, selectivity, and stability in complicated systems. With the P3-based strategy, the limit of detection for Kana is estimated to be 10 nM, which is much lower than the maximum allowable concentration in milk. The recoveries of spiked Kana in milk were in the range 99.8 ~ 105.3% (n = 3). Fortunately, this novel method can be easily extended to other antibiotics such as tobramycin by simply replacing the aptamer, showing great potential as a universal platform for selective, sensitive, and rapid detection of hazardous analytes in food samples.

Accumulated temperature dictates the regional structural variation of prokaryotic periphyton at soil-water interface in paddy fields.

As a pervasive microbial aggregate found at the water-soil interface in paddy fields, periphyton plays crucial roles in modulating nutrient biogeochemical cycling. Consequently, it effectively mitigates non-point source pollution due to its diverse composition. Despite its significance, the mechanisms governing periphyton diversity across different rice planting regions remain poorly understood. To bridge this gap, we investigated periphyton grown in 200 paddy fields spanning 25° of latitude. Initially, we analyzed local diversity and latitudinal variations in prokaryotic communities within paddy field periphyton, identifying 7 abundant taxa, 42 moderate taxa, and 39 rare taxa as the fundamental prokaryotic framework. Subsequently, to elucidate the mechanisms governing periphyton diversity across large scales, we constructed interaction models illustrating triangular relationships among local richness, assembly, and regional variation of prokaryotic subcommunities. Our findings suggest that accumulated temperature-driven environmental filtering partially influences the assembly process of prokaryotes, thereby impacting local species richness and ultimately governing regional structural variations in periphyton. Furthermore, we determined that a latitude of 39° represents the critical threshold maximizing local species richness of periphyton in paddy fields. This study advances our understanding of the factors shaping periphyton geo-imprints and provides valuable insights into predicting their responses to environmental changes, potentially influencing rice production outcomes.

Fabrication of conjugated polymers with aggregation-induced near-infrared-II emission for efficient phototheranostics.

Conjugated polymers (CPs), which emit in the second near-infrared window (NIR-II, 1000-1700 nm), are used as biomaterials for NIR-II fluorescence imaging because of their adjustable photophysical properties and high optical stability. However, the fluorescence signal of conventional CPs is quenched in an aggregated state due to strong π-π stacking, which results in the closure of the radiation attenuation pathway. To solve this problem, the aggregation-induced emission effect is considered a reasonable strategy for enhancing the aggregative fluorescence of IR-II emitters. We herein report NIR-II conjugated polymers with typical AIE characteristics (αAIE > 3) by changing the side chain structure of receptor units and the conjugation degree of donors. Conjugated polymer nanoparticles (PoBVT NPs) exhibit outstanding performance in NIR-II fluorescence imaging (QY = 1.94%) and highly effective photothermal therapy (η = 45%). In vivo studies have shown that the location of tumors can be accurately obtained by NIR-II FL/NIR-II PA imaging, and there is a significant anti-tumor effect after laser irradiation. This work offers prospects for the design of multifunctional conjugated polymers for NIR-II FL/PA imaging to guide NIR-II PTT applications.

Revealing and reconstructing the 3D Li-ion transportation network for superionic poly(ethylene) oxide conductor.

Understanding the Li-ions conduction network and transport dynamics in polymer electrolyte is crucial for developing reliable all-solid-state batteries. In this work, advanced nano- X-ray computed tomography combined with Raman spectroscopy and solid state nuclear magnetic resonance are used to multi-scale qualitatively and quantitatively reveal ion conduction network of poly(ethylene) oxide (PEO)-based electrolyte (from atomic, nano to macroscopic level). With the clear mapping of the microstructural heterogeneities of the polymer segments, aluminium-oxo molecular clusters (AlOC) are used to reconstruct a high-efficient conducting network with high available Li-ions (76.7%) and continuous amorphous domains via the strong supramolecular interactions. Such superionic PEO conductor (PEO-LiTFSI-AlOC) exhibites a molten-like Li-ion conduction behaviour among the whole temperature range and delivers an ionic conductivity of 1.87 × 10-4 S cm-1 at 35 °Ï¹. This further endows Li electrochemical plating/stripping stability under 50 µA cm-2 and 50 µAh cm-2 over 2000 h. The as-built Li|PEO-LiTFSI-AlOC|LiFePO4 full batteries show a high rate performance and a capacity retention more than 90% over 200 cycling at 250 µA cm-2, even enabling a high-loading LiFePO4 cathode of 16.8 mg cm-2 with a specific capacity of 150 mAh g-1 at 50 °Ï¹.

Association Between Serine Concentration and Coronary Heart Disease: A Case-Control Study.

Purpose: Early identification of new residual risk factors for coronary heart disease (CHD) is warranted. In this study, we aim to investigate the association between the serine concentration, an important amino acid in one-carbon metabolism, and CHD in Chinese hospitalized patients. Patients and Methods: This case-control study included 428 case-control pairs comprising patients with CHD with a maximum coronary artery stenosis degree of >70% and controls with stenosis of <30%. The individuals were matched by age, sex, and date of coronary angiography at Peking University First Hospital from January 1, 2016, to December 31, 2019. Conditional logistic regression was used to investigate the associations between the serine concentration and CHD. Results: Patients with CHD were aged 63.48 ± 10.38 years, and 43.73% were male. Compared with controls, patients with CHD had a slightly lower serine concentration (13.35 ± 4.20 vs 13.77 ± 4.08 µg/mL), but the difference was not significant. In the multivariable conditional logistic regression analysis, for every 1 µg/mL increase in serine concentration, the odds of CHD decreased by 6% (95% confidence interval [CI] 0.90-0.99; P = 0.010). Patients with a serine concentration of ≥13.41 µg/mL had a lower CHD risk than those with a serine concentration of <13.41 µg/mL (odds ratio [OR] 0.57, 95% CI 0.39-0.84; P = 0.004). Subgroup analyses showed that sex interacted with the relationship between serine concentration and CHD (P interaction = 0.039), which was more significant in males (OR 0.93, 95% CI 0.87-0.98; P = 0.013) than in females. Conclusion: This study observed an inverse association between the serine concentration and CHD prevalence in Chinese hospitalized patients, which revealed that serine might play a protective role in CHD.

Cationic conjugated polymer coupled non-conjugated segments for dually enhanced NIR-II fluorescence and lower-temperature photothermal-gas therapy.

The lack of a simple design strategy to obtain ideal conjugated polymers (CPs) with high absorbance and fluorescence (FL) in the near-infrared-II (NIR-II; 1000-1700 nm) region still hampers the success of NIR-II light-triggered phototheranostics. Herein, novel phototheranostic nanoparticles (PPN-NO NPs) were successfully prepared by coloading a cationic NIR-II CPs (PBC-co-PBF-NMe3) and a NO donor (S-nitroso-N-acetylpenicillamine, SNAP) onto a 1:1 mixture of DSPE-PEG5000 and dimyristoylphosphatidylcholine (DMPC) for NIR-II FL and NIR-II photoacoustic (PA) imaging-guided low-temperature NIR-II photothermal therapy (PTT) and gas combination therapy for cancer treatment. A precise NIR-II FL dually enhanced design tactic was proposed herein by integrating flexible nonconjugated segments (C6) into the CPs backbone and incorporating quaternary ammonium salt cationic units into the CPs side chain, which considerably increased the radiative decay pathway, resulting in desirable NIR-II FL intensity and balanced NIR-II absorption and NIR PTT properties. The phototheranostic PPN-NO NPs exhibited distinguished NIR-II FL and PA imaging performance in tumor-bearing mice models. Furthermore, the low-temperature photothermal effect of PPN-NO NPs could initiate NO release upon 980 nm laser irradiation, efficiently suppressing tumor growth owing to the combination of low-temperature NIR-II PTT and NO gas therapy in vitro and in vivo.

Spectral analysis enhanced net (SAE-Net) to classify breast lesions with BI-RADS category 4 or higher.

Early ultrasound screening for breast cancer reduces mortality significantly. The main evaluation criterion for breast ultrasound screening is the Breast Imaging-Reporting and Data System (BI-RADS), which categorizes breast lesions into categories 0-6 based on ultrasound grayscale images. Due to the limitations of ultrasound grayscale imaging, lesions with categories 4 and 5 necessitate additional biopsy for the confirmation of benign or malignant status. In this paper, the SAE-Net was proposed to combine the tissue microstructure information with the morphological information, thus improving the identification of high-grade breast lesions. The SAE-Net consists of a grayscale image branch and a spectral pattern branch. The grayscale image branch used the classical deep learning backbone model to learn the image morphological features from grayscale images, while the spectral pattern branch is designed to learn the microstructure features from ultrasound radio frequency (RF) signals. Our experimental results show that the best SAE-Net model has an area under the receiver operating characteristic curve (AUROC) of 12% higher and a Youden index of 19% higher than the single backbone model. These results demonstrate the effectiveness of our method, which potentially optimizes biopsy exemption and diagnostic efficiency.

Preoperative prediction of high-grade osteosarcoma response to neoadjuvant therapy based on a plain CT radiomics model: A dual-center study.

Objective: To develop a model combining clinical and radiomics features from CT scans for a preoperative noninvasive evaluation of Huvos grading of neoadjuvant chemotherapy in patients with HOS. Methods: 183 patients from center A and 42 from center B were categorized into training and validation sets. Features derived from radiomics were obtained from unenhanced CT scans.Following dimensionality reduction, the most optimal features were selected and utilized in creating a radiomics model through logistic regression analysis. Integrating clinical features, a composite clinical radiomics model was developed, and a nomogram was constructed. Predictive performance of the model was evaluated using ROC curves and calibration curves. Additionally, decision curve analysis was conducted to assess practical utility of nomogram in clinical settings. Results: LASSO LR analysis was performed, and finally, three selected image omics features were obtained.Radiomics model yielded AUC values with a good diagnostic effect for both patient sets (AUCs: 0.69 and 0.68, respectively). Clinical models (including sex, age, pre-chemotherapy ALP and LDH levels, new lung metastases within 1 year after surgery, and incidence) performed well in terms of Huvos grade prediction, with an AUC of 0.74 for training set. The AUC for independent validation set stood at 0.70. Notably, the amalgamation of radiomics and clinical features exhibited commendable predictive prowess in training set, registering an AUC of 0.78. This robust performance was subsequently validated in the independent validation set, where the AUC remained high at 0.75. Calibration curves of nomogram showed that the predictions were in good agreement with actual observations. Conclusion: Combined model can be used for Huvos grading in patients with HOS after preoperative chemotherapy, which is helpful for adjuvant treatment decisions.