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

Photodynamic immunotherapy is a promising strategy for cancer treatment. However, the dysfunctional tumor vasculature results in tumor hypoxia and the low efficiency of drug delivery, which in turn restricts the anticancer effect of photodynamic immunotherapy. In this study, we designed photosensitive lipid nanoparticles. The synthesized PFBT@Rox Lip nanoparticles could produce type I/II reactive oxygen species (ROS) by electron or energy transfer through PFBT under light irradiation. Moreover, this nanosystem could alleviate tumor hypoxia and promote vascular normalization through Roxadustat. Upon irradiation with white light, the ROS produced by PFBT@Rox Lip nanoparticles in situ dysregulated calcium homeostasis and triggered endoplasmic reticulum stress, which further promoted the release of damage-associated molecular patterns, enhanced antigen presentation, and stimulated an effective adaptive immune response, ultimately priming the tumor microenvironment (TME) together with the hypoxia alleviation and vessel normalization by Roxadustat. Indeed, in vivo results indicated that PFBT@Rox Lip nanoparticles promoted M1 polarization of tumor-associated macrophages, recruited more natural killer cells, and augmented infiltration of T cells, thereby leading to efficient photodynamic immunotherapy and potentiating the anti-primary and metastatic tumor efficacy of PD-1 antibody. Collectively, photodynamic immunotherapy with PFBT@Rox Lip nanoparticles efficiently program TME through the induction of immunogenicity and oxygenation, and effectively suppress tumor growth through immunogenic cell death and enhanced anti-tumor immunity.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

ObjectiveDirected differentiation of human induced pluripotent stem cells （hiPSCs） into spinal cord γ-aminobutyric acid （GABA）-ergic progenitor cells were implanted into an decellularized optical nerve （DON） bioscaffold to construct a hiPSC-derived inhibitory neural network tissue with synaptic activities. This study aimed to provide a novel stem cell-based tissue engineering product for the study and the repair of central nervous system injury. MethodsThe combination of stepwise directional induction and tissue engineering technology was applied in this study. After hiPSCs were directionally induced into human neural progenitor cells （hNPCs） in vitro， they were seeded into a DON for three-dimensional culture， allowing further differentiation into inhibitory GABAergic neurons under the specific neuronal induction environment. Transmission electron microscopy and whole cell patch clamp technique were used to detect whether the hiPSCs differentiated neurons could form synapse-like structures and whether these neurons had spontaneous inhibitory postsynaptic currents， respectively， in order to validate that the hiPSC-derived neurons would form neural networks with synaptic transmission potentials from a structural and functional perspective. ResultsThe inhibitory neurons of GABAergic phenotype were successfully induced from hiPSCs in vitro， and maintained good viability after 28 days of culture. With the transmission electron microscopy， it was observed that many cell junctions were formed between hiPSC-derived neural cells in the three-dimensional materials， some of which presented a synapse- like structure， manifested as the slight thickness of cell membrane and a small number of vesicles within one side of the cell junctions， the typical structure of a presynatic component， and focal thickness of the membrane of the other side of the cell junctions， a typical structure of a postsynaptic component. According to whole-cell patch-clamp recording， the hiPSC-derived neurons had the capability to generate action potentials and spontaneous inhibitory postsynaptic currents were recorded in this biotissue. ConclusionsThe results of this study indicated that hiPSCs can be induced to differentiate into GABAergic progenitor cells in vitro and can successfully construct iPSC-derived inhibitory neural network tissue with synaptic transmission after implanted into a DON for three-dimensional culture. This study would provide a novel neural network tissue for future research and treatment of central nervous system injury by stem cell tissue engineering technology.

ObjectiveTo identify acute phase features associated with the prognosis of traumatic brain injury （TBI）. MethodsThrough two traditional strategies， correlation analysis and prediction model， and one innovative research strategy based on feature deconstruction， a retrospective analysis was conducted using demographic， acute phase and chronic phase features of 354 TBI patients to identify acute phase features associated with activities of daily living （ADL） in chronic phase of TBI. For feature deconstruction strategy， the LASSO （Least Absolute Shrinkage and Selection Operator） algorithm was used to build a prediction model that could effectively predict ADL based on non-ADL chronic phase features. The model could indicate the key chronic phase dimensions determining the ADL in TBI patients. We then identified demographic and acute phase variables that were significantly associated with these key chronic phase features. ResultsThe feature deconstruction strategy revealed that ADL could be deconstructed into chronic phase dimensions such as weak limbs in TBI population. Importantly， to the best of our knowledge， this strategy revealed for the first time the association of these important acute phase features with specific chronic phase impairment features. For example， TBI patients had a higher risk for chronic phase recent memory impairment if they had a prolonged coma time and low GCS scores at acute phase ［scaled coma time OR95%CI = 94.288 （35.095， 273.231）； scaled GCS OR95%CI = 0.068 （0.030， 0.147）］； the patients had a higher risk for insight impairment and disorientation at chronic phase if they had hydrocephalus at acute phase ［insight impairment OR95%CI = 6.760 （3.653，12.855） ； disorientation OR95%CI = 6.538 （3.530， 12.490）］. All strategies showed that the strongest risk factors for ADL damage in the chronic phase included prolonged coma time and low GCS scores as well as hydrocephalus. ConclusionThis study provides an innovative research strategy to establish the association between acute injury features and chronic recovery features， and to identify demographic and acute phase features associated with the prognosis of TBI.

ObjectiveTo construct a neural network-like tissue with the potential of synaptic formation in vitro by seeding human induced pluripotent stem cell-derived neural precursor cells （hiPSC-NPCs） on decellularized optic nerve （DON）， so as to provide a promising approach for repair of nerve tissue injury. MethodsThrough directional induction and tissue engineering technology， human induced pluripotent stem cells （hiPSCs） and 3D DON scaffolds were combined to construct neural network-like tissues. Then the hiPSCs were directionally induced into human neural precursor cells （hNPCs） and neurons. Immunofluorescence staining was used to identify cell differentiation efficiency. 3D DON scaffolds were prepared. Morphology and cytocompatibility of scaffolds were identified by scanning electron microscopy and Tunnel staining. Induced hiPSC-NPCs were seeded on DON scaffolds. Immunofluorescence staining， scanning electron microscopy， transmission electron microscopy and patch clamp were used to observe the morphology and functional identification of constructed neural network tissues. Results①The results of immunofluorescence staining suggested that most of hiPSC-NPCs differentiated into neurons in vitro. We had successfully constructed a neural network dominated by neurons. ② The results of scanning electron microscopy and immunohistochemistry suggested that a neural network-like tissue with predominating excitatory neurons in vitro was successfully constructed. ③The results of immunohistochemical staining， transmission electron microscopy and patch clamp indicated that the neural network-like tissue had synaptic transmission function. ConclusionA neural network-like tissue mainly composed of excitatory neurons has been constructed by the combination of natural uniform-channel DON scaffold and hiPSC-NPCs， which has the function of synaptic transmission. This neural network plays a significant role in stem cell derived replacement therapy， and offers a promising prospect for repair of spinal cord injury （SCI） and other neural tissue injuries.

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens

Blau syndrome is a rare genetic disorder characterized by the a mix of granulomatous arthritis, uveitis, and dermatitis. Patients typically manifest multisystem involvement, including ocular, skin, and skeletal abnormalities. Blau syndrome is extremely rare, with a global incidence of less than one in a million among children. In this multidisciplinary consultation, we present a case of a 21-year-old young female patient having multisystemic involvement since early childhood. She was presented with multiple joint swelling, skin lesions, increased eye discharge, and accompanied by hypertension and arterial abnormalities, and received a diagnosis of uveitis. The patient had been receiving steroid treatment since the age of 6 and has tried various medications, with some improvement in joint swelling and ocular symptoms. Through this rare disease multidisciplinary consultation, we aim to provide guidance in the molecular diagnosis of the patient, multisystem assessment, and the selection and formulation of treatment plans. Additionally, we hope that by reporting this case, clinical physicians can gain a better understanding of the diagnosis and comprehensive treatment strategies for Blau syndrome, thereby improving the management and treatment of rare diseases.

Entinostat plus exemestane in hormone receptor-positive (HR+) advanced breast cancer (ABC) previously showed encouraging outcomes. This multicenter phase 3 trial evaluated the efficacy and safety of entinostat plus exemestane in Chinese patients with HR + ABC that relapsed/progressed after ≥1 endocrine therapy. Patients were randomized (2:1) to oral exemestane 25 mg/day plus entinostat (n = 235) or placebo (n = 119) 5 mg/week in 28-day cycles. The primary endpoint was the independent radiographic committee (IRC)-assessed progression-free survival (PFS). The median age was 52 (range, 28-75) years and 222 (62.7%) patients were postmenopausal. CDK4/6 inhibitors and fulvestrant were previously used in 23 (6.5%) and 92 (26.0%) patients, respectively. The baseline characteristics were comparable between the entinostat and placebo groups. The median PFS was 6.32 (95% CI, 5.30-9.11) and 3.72 (95% CI, 1.91-5.49) months in the entinostat and placebo groups (HR, 0.76; 95% CI, 0.58-0.98; P = 0.046), respectively. Grade ≥3 adverse events (AEs) occurred in 154 (65.5%) patients in the entinostat group versus 23 (19.3%) in the placebo group, and the most common grade ≥3 treatment-related AEs were neutropenia [103 (43.8%)], thrombocytopenia [20 (8.5%)], and leucopenia [15 (6.4%)]. Entinostat plus exemestane significantly improved PFS compared with exemestane, with generally manageable toxicities in HR + ABC (ClinicalTrials.gov #NCT03538171).