Evaluating and Enhancing Large Language Models' Performance in Domain-specific Medicine: Explainable LLM with DocOA.

BACKGROUND: Evaluating and Enhancing Large Language Models' Performance in Domain-specific Medicine: Explainable LLM with DocOA. OBJECTIVE: This study focused on evaluating and enhancing the clinical capabilities and explainability of LLMs in specific domains, using osteoarthritis (OA) management as a case study. METHODS: A domain specific benchmark framework was developed, which evaluate LLMs across a spectrum from domain-specific knowledge to clinical applications in real-world clinical scenarios. DocOA, a specialized LLM designed for OA management integrating retrieval-augmented generation (RAG) and instructional prompts, was developed. It can identify the clinical evidence upon which its answers are based through RAG, thereby demonstrating the explainability of those answers. The study compared the performance of GPT-3.5, GPT-4, and a specialized assistant, DocOA, using objective and human evaluations. RESULTS: Results showed that general LLMs like GPT-3.5 and GPT-4 were less effective in the specialized domain of OA management, particularly in providing personalized treatment recommendations. However, DocOA showed significant improvements. CONCLUSIONS: This study introduces a novel benchmark framework which assesses the domain-specific abilities of LLMs in multiple aspects, highlights the limitations of generalized LLMs in clinical contexts, and demonstrates the potential of tailored approaches for developing domain-specific medical LLMs.

Association of depressive symptoms and sleep disturbances with survival among US adult cancer survivors.

BACKGROUND: Depression and sleep disturbances are associated with increased risks of various diseases and mortality, but their impacts on mortality in cancer survivors remain unclear. The objective of this study was to characterize the independent and joint associations of depressive symptoms and sleep disturbances with mortality outcomes in cancer survivors. METHODS: This population-based prospective cohort study included cancer survivors aged ≥ 20 years (n = 2947; weighted population, 21,003,811) from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 cycles. Depressive symptoms and sleep disturbances were self-reported. Depressive symptoms were assessed using the Patient Health Questionnaire 9 (PHQ-9). Death outcomes were determined by correlation with National Death Index records through December 31, 2019. Primary outcomes included all-cause, cancer-specific, and noncancer mortality. RESULTS: During the median follow-up of 69 months (interquartile range, 37-109 months), 686 deaths occurred: 240 participants died from cancer, 146 from heart disease, and 300 from other causes. Separate analyses revealed that compared with a PHQ-9 score (0-4), a PHQ-9 score (5-9) was associated with a greater risk of all-cause mortality (hazard ratio [HR], 1.28; 95% CI, 1.03-1.59), and a PHQ-9 score (≥ 10) was associated with greater risk of all-cause mortality (HR, 1.37; 95% CI, 1.04-1.80) and noncancer mortality (HR, 1.45; 95% CI, 1.01-2.10). Single sleep disturbances were not associated with mortality risk. In joint analyses, the combination of a PHQ-9 score ≥ 5 and no sleep disturbances, but not sleep disturbances, was associated with increased risks of all-cause mortality, cancer-specific mortality, and noncancer mortality. Specifically, compared with individuals with a PHQ-9 score of 0-4 and no sleep disturbances, HRs for all-cause mortality and noncancer mortality in individuals with a PHQ-9 score of 5-9 and no sleep disturbances were 1.72 (1.21-2.44) and 1.69 (1.10-2.61), respectively, and 2.61 (1.43-4.78) and 2.77 (1.27-6.07), respectively, in individuals with a PHQ-9 score ≥ 10 and no sleep disturbances; HRs for cancer-specific mortality in individuals with a PHQ-9 score ≥ 5 and no sleep disturbances were 1.95 (1.16-3.27). CONCLUSIONS: Depressive symptoms were linked to a high risk of mortality in cancer survivors. The combination of a PHQ-9 score (≥ 5) and an absence of self-perceived sleep disturbances was associated with greater all-cause mortality, cancer-specific mortality, and noncancer mortality risks, particularly in individuals with a PHQ-9 score (≥ 10).

Identification of an HLA-A*11:01-restricted neoepitope of mutant PIK3CA and its specific T cell receptors for cancer immunotherapy targeting hotspot driver mutations.

Hotspot driver mutations presented by human leukocyte antigens might be recognized by anti-tumor T cells. Based on their advantages of tumor-specificity and immunogenicity, neoantigens derived from hotspot mutations, such as PIK3CAH1047L, may serve as emerging targets for cancer immunotherapies. NetMHCpan V4.1 was utilized for predicting neoepitopes of PIK3CA hotspot mutation. Using in vitro stimulation, antigen-specific T cells targeting the HLA-A*11:01-restricted PIK3CA mutation were isolated from healthy donor-derived peripheral blood mononuclear cells. T cell receptors (TCRs) were cloned using single-cell PCR and sequencing. Their functionality was assessed through T cell activation markers, cytokine production and cytotoxic response to cancer cell lines pulsed with peptides or transduced genes of mutant PIK3CA. Immunogenic mutant antigens from PIK3CA and their corresponding CD8+ T cells were identified. These PIK3CA mutation-specific CD8+ T cells were subsequently enriched, and their TCRs were isolated. The TCR clones exhibited mutation-specific and HLA-restricted reactivity, demonstrating varying degrees of functional avidity. Identified TCR genes were transferred into CD8+ Jurkat cells and primary T cells deficient of endogenous TCRs. TCR-expressing cells demonstrated specific recognition and reactivity against the PIK3CAH1047L peptide presented by HLA-A*11:01-expressing K562 cells. Furthermore, mutation-specific TCR-T cells demonstrated an elevation in cytokine production and profound cytotoxic effects against HLA-A*11:01+ malignant cell lines harboring PIK3CAH1047L. Our data demonstrate the immunogenicity of an HLA-A*11:01-restricted PIK3CA hotspot mutation and its targeting therapeutic potential, together with promising candidates of TCR-T cell therapy.

Meiotic transcriptional reprogramming mediated by cell-cell communications in humans and mice revealed by scATAC-seq and scRNA-seq.

Meiosis is a highly complex process significantly influenced by transcriptional regulation. However, studies on the mechanisms that govern transcriptomic changes during meiosis, especially in prophase I, are limited. Here, we performed single-cell ATAC-seq of human testis tissues and observed reprogramming during the transition from zygotene to pachytene spermatocytes. This event, conserved in mice, involved the deactivation of genes associated with meiosis after reprogramming and the activation of those related to spermatogenesis before their functional onset. Furthermore, we identified 282 transcriptional regulators (TRs) that underwent activation or deactivation subsequent to this process. Evidence suggested that physical contact signals from Sertoli cells may regulate these TRs in spermatocytes, while secreted ENHO signals may alter metabolic patterns in these cells. Our results further indicated that defective transcriptional reprogramming may be associated with non-obstructive azoospermia (NOA). This study revealed the importance of both physical contact and secreted signals between Sertoli cells and germ cells in meiotic progression.

Selective bioaccumulation of polystyrene nanoplastics in fetal rat brain and damage to myelin development.

Micro(nano)plastic, as a new type of environmental pollutant, have become a potential threat to the life and health of various stages of biology. However, it is not yet clear whether they will affect brain development in the fetal stage. Therefore, this study aims to explore the potential effects of nanoplastics on the development of fetal rat brains. To assess the allocation of NPs (25 nm and 50 nm) in various regions of the fetal brain, pregnant rats were exposed to concentrations (50, 10, 2.5, and 0.5 mg/kg) of PS-NPs. Our results provided evidence of the transplacental transfer of PS-NPs to the fetal brain, with a prominent presence observed in several cerebral regions, notably the cerebellum, hippocampus, striatum, and prefrontal cortex. This distribution bias might be linked to the developmental sequence of each brain region. Additionally, we explored the influence of prenatal exposure on the myelin development of the cerebellum, given its the highest PS-NP accumulation in offspring. Compared with control rats, PS-NPs exposure caused a significant reduction in myelin basic protein (MBP) and myelin oligodendrocyte glycoprotein (MOG) expression, a decrease in myelin thickness, an increase in cell apoptosis, and a decline in the oligodendrocyte population. These effects gave rise to motor deficits. In conclusion, our results identified the specific distribution of NPs in the fetal brain following prenatal exposure and revealed that prenatal exposure to PS-NPs can suppress myelin formation in the cerebellum of the fetus.

Ultraconformal Skin-Interfaced Sensing Platform for Motion Artifact-Free Monitoring.

Capable of directly capturing various physiological signals from human skin, skin-interfaced bioelectronics has emerged as a promising option for human health monitoring. However, the accuracy and reliability of the measured signals can be greatly affected by body movements or skin deformations (e.g., stretching, wrinkling, and compression). This study presents an ultraconformal, motion artifact-free, and multifunctional skin bioelectronic sensing platform fabricated by a simple and user-friendly laser patterning approach for sensing high-quality human physiological data. The highly conductive membrane based on the room-temperature coalesced Ag/Cu@Cu core-shell nanoparticles in a mixed solution of polymers can partially dissolve and locally deform in the presence of water to form conformal contact with the skin. The resulting sensors to capture improved electrophysiological signals upon various skin deformations and other biophysical signals provide an effective means to monitor health conditions and create human-machine interfaces. The highly conductive and stretchable membrane can also be used as interconnects to connect commercial off-the-shelf chips to allow extended functionalities, and the proof-of-concept demonstration is highlighted in an integrated pulse oximeter. The easy-to-remove feature of the resulting device with water further allows the device to be applied on delicate skin, such as the infant and elderly.

Histology and transcriptomic analysis reveal the inflammation and affected pathways under 2-methylisoborneol (2-MIB) exposure on grass carp.

2-Methylisoborneol (2-MIB) is a common and widely distributed off-flavor compound in water. However, the toxic mechanisms of 2-MIB on aquatic organisms remain largely unexplored. In this study, grass carp larvae were exposed to different concentrations (0, 5, and 20 µg L-1) of 2-MIB for 96 h. The accumulation of 2-MIB in the dorsal muscle was measured. Histological analysis, ultrastructure observations, and transcriptomic sequencing were conducted on the liver tissues. The results showed that 2-MIB accumulated significantly in the fish muscle, with the accumulation increasing as the exposure concentration increased through gas chromatography-mass spectrometry (GC-MS) detection. Histological and ultrastructure observations indicated that 2-MIB caused concentration-dependent inflammatory infiltration and mitochondrial damage in the liver. Transcriptomic analysis revealed lipid metabolism disorders induced by exposure to 2-MIB in grass carp. Additionally, 5 µg L-1 2-MIB affected the neurodevelopment and cardiovascular system of grass carp larvae through extracellular matrix (ECM)-receptor interaction and focal adhesion pathway. Furthermore, several pathways related to the digestive system were significantly enriched, implying that 2-MIB may impact pancreatic secretion function, protein digestion and absorption processes. These findings provide new insights into the potential toxicological mechanisms of 2-MIB.

Morphology and Composition of Lumbar Intervertebral Discs: Comparative Analyses of Manual Measurement and Computer-Assisted Algorithms.

BACKGROUND: The morphology and internal composition, particularly the nucleus-to-cross sectional area (NP-to-CSA) ratio of the lumbar intervertebral discs (IVDs), is important information for finite element models (FEMs) of spinal loadings and biomechanical behaviors, and, yet, this has not been well investigated and reported. METHODS: Anonymized MRI scans were retrieved from a previously established database, including a total of 400 lumbar IVDs from 123 subjects (58 F and 65 M). Measurements were conducted manually by a spine surgeon and using two computer-assisted segmentation algorithms, i.e., fuzzy C-means (FCM) and region growing (RG). The respective results were compared. The influence of gender and spinal level was also investigated. RESULTS: Ratios derived from manual measurements and the two computer-assisted algorithms (FCM and RG) were 46%, 39%, and 38%, respectively. Ratios derived manually were significantly larger. CONCLUSIONS: Computer-assisted methods provide reliable outcomes that are traditionally difficult for the manual measurement of internal composition. FEMs should consider the variability of NP-to-CSA ratios when studying the biomechanical behavior of the spine.

Photoperiod-Dependent Nutrient Accumulation in Rice Cultivated in Plant Factories: A Comparative Metabolomic Analysis.

Plant factories offer a promising solution to some of the challenges facing traditional agriculture, allowing for year-round rapid production of plant-derived foods. However, the effects of conditions in plant factories on metabolic nutrients remain to be explored. In this study, we used three rice accessions (KongYu131, HuangHuaZhan, and Kam Sweet Rice) as objectives, which were planted in a plant factory with strict photoperiods that are long-day (12 h light/12 h dark) or short-day (8 h light/16 h dark). A total of 438 metabolites were detected in the harvested rice grains. The difference in photoperiod leads to a different accumulation of metabolites in rice grains. Most metabolites accumulated significantly higher levels under the short-day condition than the long-day condition. Differentially accumulated metabolites were enriched in the amino acids and vitamin B6 pathway. Asparagine, pyridoxamine, and pyridoxine are key metabolites that accumulate at higher levels in rice grains harvested from the short-day photoperiod. This study reveals the photoperiod-dependent metabolomic differences in rice cultivated in plant factories, especially the metabolic profiling of taste- and nutrition-related compounds.

Nomogram Predicts Prognostic Factors for Head and Neck Cutaneous Melanoma: A Population-Based Analysis.

BACKGROUND: The head and neck cutaneous melanoma (HNCM) accounts for 20% of newly diagnosed melanoma. Research on prognostic models for their survival yet remains largely unexplored. This study employed a nomogram approach to develop and validate a predictive model for both overall survival (OS) and disease-specific survival (DSS) in patients with HNCM. METHODS: This study analyzed the HNCM patients diagnosed between 2004 and 2014 from Surveillance, Epidemiology, and End Results database. To identify independent prognostic factors for HNCM, we integrated results from univariate Cox regression analysis, random survival forests, and LASSO regression with cross-validation. A nomogram was designed and validated based on the identified characteristics to predict the 3-, 5-, and 8-year OS and DSS of patients with HNCM. RESULTS: Age, Stage, Ulceration, Thickness, Chemotherapy, lymph node metastasis, and Radiation were identified as independent prognostic factors. The nomogram achieved a satisfactory performance with C-indices of 0.824(DSS) and 0.757(OS) in the training cohort and 0.827(DSS) and 0.749(OS) in the validation cohort, respectively. The area under the curves for the OS at 3, 5, and 8 years were 0.789, 0.788, and 0.794 for the training cohort, and 0.778, 0.776, and 0.795 for the validation cohort, respectively. For DSS, the area under the curves at 3, 5, and 8 years were 0.859, 0.842, and 0.828 in the training cohort, and 0.864, 0.844, and 0.834 in the validation cohort, respectively. The calibration curve showed that there was a strong correlation between the observed outcomes and the predicted survival probability. CONCLUSIONS: This study established and validated predictive nomograms for HNCM patients with robust predictive performance.

Establishing a machine learning model based on dual-energy CT enterography to evaluate Crohn's disease activity.

OBJECTIVES: The simplified endoscopic score of Crohn's disease (SES-CD) is the gold standard for quantitatively evaluating Crohn's disease (CD) activity but is invasive. This study aimed to develop and validate a machine learning (ML) model based on dual-energy CT enterography (DECTE) to noninvasively evaluate CD activity. METHODS: We evaluated the activity in 202 bowel segments of 46 CD patients according to the SES-CD score and divided the segments randomly into training set and testing set at a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) was used for feature selection, and three models based on significant parameters were established based on logistic regression. Model performance was evaluated using receiver operating characteristic (ROC), calibration, and clinical decision curves. RESULTS: There were 110 active and 92 inactive bowel segments. In univariate analysis, the slope of spectral curve in the venous phases (λHU-V) has the best diagnostic performance, with an area under the ROC curve (AUC) of 0.81 and an optimal threshold of 1.975. In the testing set, the AUC of the three models established by the 7 variables to differentiate CD activity was 0.81-0.87 (DeLong test p value was 0.071-0.766, p > 0.05), and the combined model had the highest AUC of 0.87 (95% confidence interval (CI): 0.779-0.959). CONCLUSIONS: The ML model based the DECTE can feasibly evaluate CD activity, and DECTE parameters provide a quantitative analysis basis for evaluating specific bowel activities in CD patients. CRITICAL RELEVANCE STATEMENT: The machine learning model based on dual-energy computed tomography enterography can be used for evaluating Crohn's disease activity noninvasively and quantitatively. KEY POINTS: Dual-energy CT parameters are related to Crohn's disease activity. Three machine learning models effectively evaluated Crohn's disease activity. Combined models based on conventional and dual-energy CT have the best performance.

Optimization Method for Space-Based Target Detection System Based on Background-Oriented Schlieren.

Currently, the visual detection of a target's shock flow field through background schlieren technology is a novel detection system. However, there are very few studies on the long-distance background schlieren imaging mechanism and its application in system design in the field of target detection. This paper proposes a design optimization method for space-based BOS detection system metrics. By establishing sensitivity evaluation models and image signal-to-noise ratio evaluation models for BOS detection systems, the influence of the different flight parameters and key parameters of BOS systems (detection spectral bands and spatial resolution) on target detection efficiency is explored. Furthermore, an optimization method based on the image signal-to-noise ratio of the BOS system and the overall metrics for specific scenarios are provided. The simulation results demonstrate that under satellite background images and speckle background images, the system metrics can detect and identify the schlieren of high-speed targets, with better applicability to disordered and complex real background images. This research contributes to advancing the development of high-speed target detection technology based on BOS.

Online Detection of Hydrogen Fluoride under Corona Discharge in Gas-Insulated Switchgear Based on Photoacoustic Spectroscopy.

Internal discharge and overheating faults in sulfur hexafluoride (SF6) gas-insulated electrical equipment will generate a series of characteristic gas products. Hydrogen fluoride (HF) is one of the main decomposition gases under discharge failure. Because of its extremely corrosive nature, it can react with other materials in gas-insulated switchgear (GIS), resulting in a short existence time, so it needs to be detected online. Resonant gas photoacoustic spectroscopy has the advantage of high sensitivity, fast response, and no sample gas consumption, and can be used for the online detection of flowing gas. In this paper, a simulated GIS corona discharge experimental platform was built, and the HF generated in the discharge was detected online by gas photoacoustic spectroscopy. The absorption peak of HF molecule near 1312.59 nm was selected as the absorption spectral line, and a resonant photoacoustic cell was designed. To improve the detection sensitivity of HF, wavelength modulation and second-harmonic detection technology were used. The online monitoring of HF in the simulated GIS corona discharge fault was successfully realized. The experimental results show that the sensitivity of the designed photoacoustic spectroscopy detection system for HF is 0.445 µV/(µL/L), and the limit of detection (LOD) is 0.611 µL/L.

The hepatocellular carcinoma risk in patients with HBV-related cirrhosis: a competing risk nomogram based on a 4-year retrospective cohort study.

Objective: The study aimed to build and validate a competitive risk nomogram to predict the cumulative incidence of hepatocellular carcinoma (HCC) for patients with hepatitis B virus (HBV)-related cirrhosis. Methods: A total of 1401 HBV-related cirrhosis patients were retrospectively enrolled from January 1, 2011 to December 31, 2014. Application of 20 times imputation dealt with missing data using multiple imputation by chained equations (MICE). The patients were randomly divided into a training set (n = 1017) and a validation set (n = 384) at a ratio of 3:1. A prediction study was carried out using a competing risk model, where the event of interest was HCC and the competing events were death and liver transplantation, and subdistribution hazard ratios (sHRs) with 95% CIs were reported. The multivariate competing risk model was constructed and validated. Results: There was a negligible difference between the original database and the 20 imputed datasets. At the end of follow-up, the median follow-up time was 69.9 months (interquartile range: 43.8-86.6). There were 31.5% (442/1401) of the patients who developed HCC, with a 5-year cumulative incidence of 22.9 (95%CI, 20.8%-25.2%). The univariate and multivariate competing risk regression and construction of the nomogram were performed in 20 imputed training datasets. Age, sex, antiviral therapy history, hepatitis B e antigen, alcohol drinking history, and alpha-fetoprotein levels were included in the nomogram. The area under receiver operating characteristic curve values at 12, 24, 36, 60, and 96 months were 0.68, 0.69, 0.70, 0.68, and 0.80, and the Brier scores were 0.30, 0.25, 0.23, 0.21, and 0.20 in the validation set. According to the cumulative incidence function, the nomogram effectively screened out high-risk HCC patients from low-risk patients in the presence of competing events (Fine-Gray test p < 0.001). Conclusion: The competitive risk nomogram was allowed to be used for predicting HCC risk in individual patients with liver cirrhosis, taking into account both the association between risk factors and HCC and the modifying effect of competition events on this association.

Hyperosmotic Stress Induces Inflammation and Excessive Th17 Response to Blunt T-Cell Immunity in Tilapia.

Despite the advances in study on osmotic physiology in bony fish, the mechanism by which the immune system, especially T-cell immunity, adapts and responds to osmotic stress remains unknown. In the current study, we investigated the response of T cells to hyperosmotic stress in the bony fish Nile tilapia (Oreochromis niloticus). As a euryhaline fish, tilapia was able to adapt to a wide range of salinities; however, hypertonic stress caused inflammation and excessive T-cell activation. Furthermore, hypertonic stress increased the expression of IL-17A in T cells, upregulated the transcription factor RORα, and activated STAT3 signaling, along with IL-6- and TGF-ß1-mediated pathways, revealing an enhanced Th17 response in this early vertebrate. These hypertonic stress-induced events collectively resulted in an impaired antibacterial immune response in tilapia. Hypertonic stress elevated the intracellular ROS level, which in turn activated the p38-MK2 signaling pathway to promote IL-17A production by T cells. Both ROS elimination and the p38-MK2 axis blockade diminished the increased IL-17A production in T cells under hypertonic conditions. Moreover, the produced proinflammatory cytokines further amplified the hypertonic stress signaling via the MKK6-p38-MK2 axis-mediated positive feedback loop. To our knowledge, these findings represent the first description of the mechanism by which T-cell immunity responds to hypertonic stress in early vertebrates, thus providing a novel perspective for understanding the adaptive evolution of T cells under environmental stress.

Effects of flowing water stimulation on hormone regulation during the maturation process of Conger myriaster ovaries.

Conger eel (Conger myriaster) is an economically important species in China. Due to the complex life history of the conger eel, achieving artificial reproduction has remained elusive. This study aimed to explore the effect of water stimulation on hormonal regulation during the artificial reproduction of conger eel. The experiment was divided into four groups: A1 (no hormone injection, still water), A2 (no hormone injection, flowing water), B1 (hormone injection, still water), and B2 (hormone injection, flowing water). The flowing water group maintained a flow velocity of 0.4 ± 0.05 m/s for 12 h daily throughout the 60-day period. Steroid hormone levels in the serum and ovaries of conger eels were analyzed using UPLC-MS/MS and ELISA on the 30th and 60th days of the experiment. The relative expression levels of follicle-stimulating hormone (FSHß) and luteinizing hormone (LHß) in the pituitary were determined by quantitative PCR. The results showed a significantly lower gonadosomatic index (GSI) in B2 compared to B1 (p < 0.05) on the 30th day. FSH was found to act only in the early stages of ovarian development, with water stimulation significantly enhancing FSH synthesis (p < 0.05), while FSHß gene was not expressed after hormone injection. Conversely, LH was highly expressed in late ovarian development, with flowing water stimulation significantly promoting LH synthesis (p < 0.05). Serum cortisol (COR) levels were significantly higher in the flowing water group than in the still water group (p < 0.05). Furthermore, estradiol (E2) content of B2 was significantly lower than that of B1 on the 30th and 60th day. Overall, flowing water stimulation enhanced the synthesis of FSH in early ovarian development and LH in late ovarian development, while reducing E2 accumulation in the ovaries. In this study, the effect of flowing water stimulation on hormone regulation during the artificial reproduction of conger eel was initially investigated to provide a theoretical basis for optimizing artificial reproduction techniques.

Treatment Strategy for Splenic Artery Aneurysms and Novel Classification Based on Imaging.

OBJECTIVE: The incidence of splenic artery aneurysms (SAAs) has increased with advancements in imaging techniques, necessitating a comprehensive classification to guide treatment strategies. This study aims to propose a novel classification system for SAAs based on aneurysm characteristics and to review treatment outcomes at our center. METHODS: This retrospective study included 113 SAAs patients admitted at Peking Union Medical College Hospital from January 2019 to December 2023, assessed using computed tomography angiography (CTA) or digital subtraction angiography (DSA). A new classification system was devised based on the aneurysms' location, morphology, integrity, and parent artery anatomy. Treatment strategies were determined based on these characteristics, with interventions ranging from endovascular therapy to laparoscopic and open surgery. Patients were followed up post-intervention to assess mortality, complications, reinterventions, and aneurysm-related outcomes. RESULTS: The study cohort of 113 patients with 127 SAAs had a predominance of female patients (63.7%) and a mean age of 52.7 years. The SAAs were classified into five types, with Type I being the most common. The intervention techniques varied across types, with sac embolization, covered stent implantation, and artery embolization being the most frequently employed. The overall technical success rate was 94.7%, with perioperative complication and reintervention rates of 25% and 0.9%, respectively, and no deaths within 30 days post-intervention. The median follow-up duration was 21 months, with overall complications rate of 3.5% and no aneurysm-related complications or deaths. CONCLUSIONS: The proposed classification system effectively guides the selection of treatment strategies for SAAs, incorporating key anatomical and morphological features. This system facilitated high technical success and low complication rates, underscoring the importance of tailored techniques in managing SAAs. Further research is necessary to validate this classification system and optimize treatment algorithms.

The Effect of Low HBV-DNA Viral Load on Recurrence in Hepatocellular Carcinoma Patients Who Underwent Primary Locoregional Treatment and the Development of a Nomogram Prediction Model.

(1) Background: HBV-DNA is an essential clinical indicator of primary hepatocellular carcinoma (HCC) prognosis. Our study aimed to investigate the prognostic implication of a low load of HBV-DNA in HCC patients who underwent local treatment. Additionally, we developed and validated a nomogram to predict the recurrence of patients with low (20-100 IU/mL) viral loads (L-VL). (2) Methods: A total of 475 HBV-HCC patients were enrolled, including 403 L-VL patients and 72 patients with very low (<20 IU/mL) viral loads (VL-VL). L-VL HCC patients were randomly divided into a training set (N = 282) and a validation set (N = 121) at a ratio of 7:3. Utilizing the Lasso-Cox regression analysis, we identified independent risk factors for constructing a nomogram. (3) Results: L-VL patients had significantly shorter RFS than VL-VL patients (38.2 m vs. 23.4 m, p = 0.024). The content of the nomogram included gender, BCLC stage, Glob, and MLR. The C-index (0.682 vs. 0.609); 1-, 3-, and 5-year AUCs (0.729, 0.784, and 0.783, vs. 0.631, 0.634, the 0.665); calibration curves; and decision curve analysis (DCA) curves of the training and validation cohorts proved the excellent predictive performance of the nomogram. There was a statistically significant difference in RFS between the low-, immediate-, and high-risk groups both in the training and validation cohorts (p < 0.001); (4) Conclusions: Patients with L-VL had a worse prognosis. The nomogram developed and validated in this study has the advantage of predicting patients with L-VL.

FPL+: Filtered Pseudo Label-based Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation.

Adapting a medical image segmentation model to a new domain is important for improving its cross-domain transferability, and due to the expensive annotation process, Unsupervised Domain Adaptation (UDA) is appealing where only unlabeled images are needed for the adaptation. Existing UDA methods are mainly based on image or feature alignment with adversarial training for regularization, and they are limited by insufficient supervision in the target domain. In this paper, we propose an enhanced Filtered Pseudo Label (FPL+)-based UDA method for 3D medical image segmentation. It first uses cross-domain data augmentation to translate labeled images in the source domain to a dual-domain training set consisting of a pseudo source-domain set and a pseudo target-domain set. To leverage the dual-domain augmented images to train a pseudo label generator, domain-specific batch normalization layers are used to deal with the domain shift while learn the domain-invariant structure features, generating high-quality pseudo labels for target-domain images. We then combine labeled source-domain images and target-domain images with pseudo labels to train a final segmentor, where image-level weighting based on uncertainty estimation and pixel-level weighting based on dual-domain consensus are proposed to mitigate the adverse effect of noisy pseudo labels. Experiments on three public multi-modal datasets for Vestibular Schwannoma, brain tumor and whole heart segmentation show that our method surpassed ten state-of-the-art UDA methods, and it even achieved better results than fully supervised learning in the target domain in some cases.

Present situation of minimally invasive surgical treatment for early gastric cancer.

Minimally invasive surgery is a kind of surgical operation, which is performed by using professional surgical instruments and equipment to inactivate, resect, repair or reconstruct the pathological changes, deformities and wounds in human body through micro-trauma or micro-approach, in order to achieve the goal of treatment, its surgical effect is equivalent to the traditional open surgery, while avoiding the morbidity of conventional surgical wounds. In addition, it also has the advantages of less trauma, less blood loss during operation, less psychological burden and quick recovery on patients, and these minimally invasive techniques provide unique value for the examination and treatment of gastric cancer patients. Surgical minimally invasive surgical techniques have developed rapidly and offer numerous options for the treatment of early gastric cancer (EGC): endoscopic mucosal resection (EMR), underwater EMR (UEMR), endoscopic submucosal dissection (ESD), endoscopic full-thickness resection (EFTR), endoscopic submucosal excavation (ESE), submucosal tunnel endoscopic resection), laparoscopic and endoscopic cooperative surgery (LECS); Among them, EMR, EFTR and LECS technologies have a wide range of applications and different modifications have been derived from their respective surgical operations, such as band-assisted EMR (BA-EMR), conventional EMR (CEMR), over-the-scope clip-assisted EFTR, no-touch EFTR, the inverted LECS, closed LECS, and so on. These new and improved minimally invasive surgeries are more precise, specific and effective in treating different types of EGC.