Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disorder primarily caused by pathogenic variants in the TSC1 or TSC2 genes. It is characterized by multisystem hamartomatous lesions and neuropsychiatric manifestations. Here we report a young male patient with TSC involving multiple organs, caused by a heterozygous frameshift mutation in TSC2 (c.2071delC, p.Arg691Alafs^*7). The patient initially presented with classic facial angiofibromas and hypomelanotic macules, and subsequently developed psychiatric and behavioral disturbances with auditory hallucinations. Neuroimaging revealed an intracranial mass lesion, which was confirmed as a subependymal giant cell astrocytoma on postoperative histopathology following surgery performed at an outside institution. After admission, the patient underwent a comprehensive diagnostic workup, and multidisciplinary treatment evaluation revealed extensive multisystem involve-ment, including the nervous system, skin, kidneys, lungs, heart, eyes, pancreas, liver and bones. Combined with relevant literature, this article discusses the molecular mechanisms, clinical phenotypes, and comprehensive management of TSC, in order to provide a reference for the standardized and individualized management of this disease.

ObjectiveTo explore the value of a multimodal MRI-based radiomics nomogram for differentiating human epidermal growth factor receptor-2 （HER-2） negative breast cancer molecular subtypes.MethodsA retrospective analysis was conducted on 190 patients with HER-2 negative breast cancer who underwent multimodal MRI examination， and the patients were divided into two molecular subtype groups： a HER-2 low expression group （n=108） and a HER-2 zero expression group （n=82）. The cases were randomly stratified and sampled at a ratio of 7∶3 and divided into a training set of 133 cases and a testing set of 57 cases. The clinical and radiological features of the patients were collected， the radiomics features based on T2-weighted imaging （T2WI）， diffusion-weighted imaging （DWI）， and dynamic contrast-enhanced （DCE）-MRI were extracted， and the clinical-radiological model， unimodal radiomics model， multimodal radiomics model， and combined model were constructed respectively. Then the nomogram combined multimodal radiomics signature （radsocre） with clinical-radiological features was used to construct a visualized predictive model， and the area under the curve （AUC） was used to compare the effectiveness of different models in distinguishing HER-2 low expression and zero expression subtypes.ResultsA significant difference in radscore was demonstrated between the HER-2 low and HER-2 zero expression groups in both the training （P<0.000 1） and testing sets （P<0.01）. The AUC of the multimodal radiomics model in the training set and the testing set were 0.914 and 0.836， respectively， which was superior to any unimodal radiomics model. The nomogram demonstrated great diagnostic efficacy （AUC=0.930 in training set； AUC=0.865 in testing set）.ConclusionA multimodal MRI-based nomogram incorporating radsocre and clinical-radiological features can accurately distinguish the subtypes of HER-2 negative breast cancer.

Objective:To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（NPC） and nasopharyngeal lymphoma（NPL）. Methods:The retrospective study included 142 patients with NPL and 292 patients with NPC who underwent conventional MRI at Renmin Hospital of Wuhan University from June 2012 to February 2023. MRI from 80 patients were manually segmented to train the segmentation model. The automatically segmented regions of interest（ROIs） formed four datasets: T1 weighted images（T1WI）, T2 weighted images（T2WI）, T1 weighted contrast-enhanced images（T1CE）, and a combination of T1WI and T2WI. The ImageNet-pretrained ResNet101 model was fine-tuned for the classification task. Statistical analysis was conducted using SPSS 22.0. The Dice coefficient loss was used to evaluate performance of segmentation task. Diagnostic performance was assessed using receiver operating characteristic（ROC） curves. Gradient-weighted class activation mapping（Grad-CAM） was imported to visualize the model's function. Results:The DICE score of the segmentation model reached 0.876 in the testing set. The AUC values of classification models in testing set were as follows: T1WI: 0.78（95%CI 0.67-0.81）, T2WI: 0.75（95%CI 0.72-0.86）, T1CE: 0.84（95%CI 0.76-0.87）, and T1WI+T2WI: 0.93（95%CI 0.85-0.94）. The AUC values for the two clinicians were 0.77（95%CI 0.72-0.82） for the junior, and 0.84（95%CI 0.80-0.89） for the senior. Grad-CAM analysis revealed that the central region of the tumor was highly correlated with the model's classification decisions, while the correlation was lower in the peripheral regions. Conclusion:The deep learning model performed well in differentiating NPC from NPL based on conventional MRI. The T1WI+T2WI combination model exhibited the best performance. The model can assist in the early diagnosis of NPC and NPL, facilitating timely and standardized treatment, which may improve patient prognosis.
Humans ; Nasopharyngeal Carcinoma/diagnostic imaging* ; Deep Learning ; Magnetic Resonance Imaging ; Retrospective Studies ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Lymphoma/diagnostic imaging* ; Diagnosis, Differential ; ROC Curve ; Male ; Female ; Middle Aged ; Adult

BACKGROUND: Electroacupuncture (EA) treatment is efficacious in patients with respiratory disorders, although the mechanisms of its action in lung-function protection are poorly understood. This study aimed to explore the neuroanatomical mechanisms of EA stimulation at the BL13 acupoint (Feishu, EA-BL13) improvement in asthma. METHODS: Allergic asthma was induced by intranasal 2.0% ovalbumin (OVA) instillation combined with intraperitoneal injection of the 10.0% OVA. The levels of interleukin (IL)-4 and IL-5 were detected by enzyme-linked immunosorbent assay. Hematoxylin and eosin and periodic acid-schiff stain were used to evaluate inflammatory cell infiltration and mucus secretion. Cellular oncogene fos induction in neurons after EA stimulation was detected by immunofluorescent staining. The messenger RNA expression levels of adrenergic receptors were quantified with real-time polymerase chain reaction. RESULTS: EA improved airway inflammation and mucus secretion mainly by activating somatosensory-sympathetic pathways ( P <0.001). Briefly, the intermediolateral (IML) nuclei of the spinal cord received signals from somatic EA stimulation and then delivered the information via the sympathetic trunk to the lung. Excited sympathetic nerve endings in lung tissue released large amounts of catecholamines that specifically activated the β2 adrenergic receptor (β2AR) on T cells ( P <0.01) and further decreased the levels of IL-4 and IL-5 ( P <0.001) through the cyclic adenosine monophosphate/protein kinase A signaling pathway. CONCLUSION This study provided a new explanation and clinical basis for the use of EA-BL13 as a treatment for allergic asthma in both the attack and remission stages and other respiratory disorders related to airway inflammation.
Electroacupuncture/methods* ; Animals ; Asthma/immunology* ; Rats ; Rats, Sprague-Dawley ; Male ; Inflammation/therapy* ; Interleukin-4/metabolism* ; Interleukin-5/metabolism*

Objective: To explore the value of nomogram based on DCE-MRI radiomics combined with clinical-ra- diological features in predicting HR status in breast cancer with Her-2 low expression． Methods: A total of 198 pa- tients of Her-2 low expression breast cancer who underwent standardized breast MRI in our hospital from January 2019 to February 2025 were retrospectively analyzed．Patients were divided into HR ( + ) group ( n = 137) and HR ( －) group ( n = 61) ．The cases were divided into a training set ( 138 cases) and a testing set ( 60 cases) in a 7 ∶ 3 ratio．Clinical-radiological model was based on clinical and traditional radiological features，radiomics model was based on DCE-MRI，and combined model was constructed，respectively．The nomogram was drawn，and re- ceiver operating characteristic curve was used to compare the performance of different models in predicting HR sta- tus． Results: The DCE-MRI radiomics score ( Radscore) between the HR ( + ) group and the HR ( －) group showed statistical differences in both the training and testing sets ( both P＜0. 001) ．The AUC of the clinical-radio- logical model based on lesion mobility，Ki67，TIC type，enhancement pattern and maximum diameter for predicting HR status in the training set and testing set were 0. 643 and 0. 616，respectively．The AUC of the DEC-MRI ra- diomics model in the training set and testing set were 0. 897 and 0. 860，respectively．The nomogram drawn by combining clinical-radiological features and Radscore showed better predictive performance in both the training set ( AUC = 0. 913) and testing set ( AUC = 0. 898) than the clinical-radiological model ( all P＜0. 05) ． Conclusion The nomogram combined by DCE-MRI radiomics and clinical-radiological features can effectively predict HR sta-tus of breast cancer with low Her-2 expression，which is helpful to the building of individualized treatment plan for breast cancer patients．

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

OBJECTIVE: To develop a digital intelligent multimodal shift handover system for the intensive care unit (ICU) and evaluate its application effect in ICU shift handovers. METHODS: A research and development team was established, consisting of 1 department director, 1 head nurse, 3 information technology engineers, 3 nurses, and 2 doctors. Team members were assigned responsibilities including overall coordination and planning, platform design and maintenance, pre-application training, collection and organization of clinical feedback, and research investigation respectively. A digital intelligent multimodal shift handover system was developed for ICU based on the Shannon-Weaver linear transmission model. This innovative system integrated automated data collection, intelligent dynamic monitoring, multidimensional condition analysis and visual reporting functions. A cloud platform was used to gather data from multi-parameter vital signs monitors, infusion pumps, ventilators and other devices. Artificial intelligence algorithms were employed to standardize and analyze the data, providing personalized recommendations for healthcare professionals. A self-controlled before-after method was adopted. Before the application of the ICU digital intelligent multimodal shift handover system (from December 2023 to March 2024), the traditional verbal bedside handover was used; from June 2024 to March 2025, the ICU digital intelligent multimodal shift handover system was applied for shift handovers. Questionnaires before the application of the shift handover system were collected in April 2024, and those after the application were collected in April 2025. The shift handover time, handover quality (scored by the nursing handover evaluation scale), satisfaction with doctor-nurse communication (scored by the ICU doctor-nurse scale) before and after the application of the handover system were compared, and nurses' satisfaction with the shift handover system (scored by the clinical nursing information system effectiveness evaluation scale) was investigated. RESULTS: After the application of the ICU digital intelligent multimodal shift handover system, the shift handover time was significantly shorter than that before the application [minutes: 20 (15, 25) vs. 30 (22, 40)], the handover quality was significantly higher than that before the application [score: 84.0 (78.0, 88.5) vs. 71.0 (55.0, 79.0)], and the satisfaction with doctor-nurse communication was also significantly higher than that before the application (score: 84.58±6.79 vs. 74.50±11.30). All differences were statistically significant (all P < 0.05). In addition, the nurses' system effectiveness evaluation scale score was 102.30±10.56, which indicated that nurses had a very high level of satisfaction with the ICU digital intelligent multimodal shift handover system. CONCLUSIONS The application of the ICU digital intelligent multimodal shift handover system can shorten the shift handover time, improve the handover quality, and enhance the satisfaction with doctor-nurse communication. Nurses have a high level of satisfaction with this system.
Intensive Care Units ; Humans ; Patient Handoff ; Artificial Intelligence ; Algorithms

Objective To investigate the influence of different embryo development rates on the clinical outcomes of assisted reproductive technology(ART).Methods The clinical data of female patients who underwent in vitro fertilization and intracytoplasmic sperm injection embryo transfer in Reproductive Medicine Center of The First Affiliated Hospital of Naval Medical University from Jan.1,2015 to Dec.31,2023 were retrospectively analyzed.A total of 1 556 cycles were included.Group A was transferred on day 3,and they were assigned to subgroups according to the embryo development rates until day 3:subgroup A1(≤6 cell stages),subgroup A2(7-9 cell cleavage stages),or subgroup A3(≥10 cell cleavage stages).Group B was transferred on day 4,and they were assigned to subgroups according to the embryo development rates until day 4:subgroup B1(cleavage stages),subgroup B2(1st or 2nd period blastocyst or morula stages),or subgroup B3(3rd period blastocyst or higher stages).Group C was transferred on day 5,and they were assigned to subgroups according to the embryo development rates until day 5:subgroup C1(1st or 2nd period blastocyst or morula stages),subgroup C2(4th or 5th period blastocyst stages),or subgroup C3(6th period blastocyst stages).Group D was transferred on day 6,and they were assigned to subgroups according to the embryo development rates until day 6:subgroup D1(morula or 1st or 2nd period blastocyst stages),or subgroup D2(5th or 6th period blastocyst stages).The clinical pregnancy and live birth rates were calculated for each group.Results Pairwise comparisons of the subgroups A1,B1,C1 and D1,all with relatively slow development rates,showed that the clinical pregnancy rates were 23.7%,37.3%,26.9%and 35.9%,respectively(P＜0.05),the live birth rates were 16.4%,28.4%,19.2%and 26.9%,respectively(P＜0.05),and the clinical pregnancy rate and live birth rate were both the highest in the B1 group.Pairwise comparisons of the subgroups A2,B2,C2 and D2 with normal development rates,the clinical pregnancy rates were 58.0%,59.4%,62.2%and 61.5%,respectively(P＜0.05),the live birth rates were 47.5%,49.4%,53.8%and 52.3%,respectively(P＜0.05),and the clinical pregnancy rate and live birth rate were both the highest in the subgroup C2.Pairwise comparisons of the subgroups A3,B3 and C3 with relatively fast development rates showed that the clinical pregnancy rates were 62.2%,64.6%and 63.5%,respectively(P＜0.05),the live birth rates were 52.2%,56.9%and 54.1%,respectively(P＜0.05),and the clinical pregnancy rate and live birth rate were both the highest in the subgroup B3.Conclusion The 4th day fast-developing blastocysts have better development potential and clinical outcomes.Embryos with slower development rate should be transferred on the 4th day,and embryos with normal development rate are recommended to be cultured and transferred to the 5th day.

Objective To systematically identify the key genes regulating the exit from na?ve pluripotency in embryonic stem cells(ESCs)in order to provide novel targets and theoretical insights into the mechanisms for pluripotency transition and early cell fate determination.Methods Nanog-green fluorescent protein(Nanog-GFP)reporter-labeled ESCs were infected with a genome-wide Brie knockout library,and further cultured under leukemia inhibitory factor/serum(LIF/S)conditions for 14 d.Flow cytometry was used to sort Nanog-GFP?(na?ve-state)and Nanog-GFP-(primed state)cell populations,followed by genomic DNA extraction and high-throughput sequencing.Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout(MAGeCK)was applied to identify differential genes between GFP?/Input,GFP?/Input,and GFP?/GFP? groups.Metascape and Gene Set Enrichment Analysis(GSEA)were conducted for functional enrichment analysis.Then the obtained candidate genes were employed to construct knockout models,and their roles were assessed through cell morphology observation,Nanog-positive rate detection,colony formation assays,and pluripotency gene expression analysis.Results The GFP?/Input screening revealed 2 921 negatively regulated genes(mainly enriched in basic life processes,such as RNA metabolism and cell cycle)and 1 393 positively regulated genes(enriched in the processes of nervous system development,carbohydrate metabolism,and vascular system development).In the GFP?/Input screening,2 765 negatively regulated genes(enriched in RNA metabolism,cell cycle,and other fundamental processes)and 1 303 positively regulated genes(enriched in neural development,cell survival,and endothelial migration)were identified.The GFP?/GFP? comparison identified 1 001 negatively regulated genes[involved in stress response and inhibition of mitogen-activated protein kinase(MAPK)signaling]and 983 positively regulated genes[related to fibroblast growth factor/extracellular signal-regulated kinase(FGF/ERK)signaling pathway and glucose metabolism).These genes,were not only known pluripotency regulators(e.g.,Nanog,Nr5a2,Klf2,Klf4)and exit-associated genes(e.g.,Gata6,Grb2,Zeb1,Fgfr1),but also some novel candidates(e.g.,Dmrt1,Rxra,Zbtb14 and Tmem41b).Functional validation showed that transient knockout of Dmrt1,Tmem41b,and Hic2 significantly increased the proportion of Nanog? cells(P<0.01),suggesting their role in suppressing ground-state exit.ESCs with stable Dmrt1 knockout exhibited a more na?ve-state phenotype,presenting compact,dome-shaped colonies,with increased ratio of undifferentiated colonies(P<0.01),up-regulation of ground-state markers(Nanog,Nr5a2,Dppa3,P<0.01),and down-regulation of primed-state markers(Fgf5,Lefty1,Dnmt3b,P<0.01).Rescue experiments for Dmrt1 expression reversed these above phenotypes.Conclusion A candidate gene set regulating exit from na?ve pluripotency in ESC is screened out and identified with genome-wide CRISPR.Our findings implicate Dmrt1 plays a critical role in promoting the exit.