[Objective] To investigate and summarize the clinicopathological features, diagnosis, treatment and prognosis of adrenocortical carcinoma with rhabdoid features. [Methods] The clinical diagnosis and treatment of a case of adrenocortical carcinoma with rhabdoid features admitled to Department of Urology, Weifang People's Hospital were reported.The clinical manifestations, pathological features, diagnosis and prognosis of the disease were analyzed in combination with relevant literature. [Results] A 34-year-old male patient was admitted due to scrotal distension and pain that had persisted for 6 months.Imaging examination showed a huge soft tissue tumor in the left adrenal region of the retroperitoneum with compression displacement of the left kidney, leading to obstruction of venous return in the left spermatic vein, which in turn caused varicose veins.The levels of serum renin, angiotensin, aldosterone, cortisol, and catecholamine were within normal ranges.Surgical resection of the tumor was performed, and postoperative pathological examination revealed that the tumor tissue was predominantly composed of rhabdoid cells, exhibiting positive immunohistochemical staining for INI 1, Syn, Calretinin and Vimentin.Genetic testing did not identify any deletion of SMARCB1 and SMARCA4 mutations.Therefore, the diagnosis was adrenocortical carcinoma with rhabdoid features.At the current 20-month follow-up, no recurrence or metastasis was observed.A review of the literature found that only 7 cases of this disease had been reported. [Conclusion] Adrenocortical carcinoma with rhabdoid features is a rare disease, and a definitive diagnosis is dependent upon pathological examination.Surgical resection remains the primary treatment.Long-term follow-up is essential, and further research is needed to evaluate the impact of adjuvant therapy.

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*

OBJECTIVE: To summarize the early clinical results and safety of Stand-alone OLIF application of lumbar lesions, and explored its surgical indications. METHODS: Total of 92 cases of lumbar spine lesions treated with Stand-alone OLIF at two medical centers from October 2014 to December 2018 were retrospectively analyzed, including 30 males and 62 females with an average age of (61.20±12.94) years old ranged from 32 to 83 years old. There were 20 cases of lumbar spinal stenosis, 15 cases of lumbar disc degeneration, 11 cases of lumbar degenerative spondylolisthesis, 6 cases of discogenic low back pain, 7 cases of giant lumbar disc herniation, 13 cases of primary lumbar discitis, 6 cases of adjacent vertebral disease after lumbar internal fixation surgery, and 14 cases of degenerative lumbar scoliosis. Pre-operative dual energy X-ray bone density examination 31 cases' T-values ranged from -1 to -2.4, 8 cases' T-values ranged from -2.5 to -3.5, and the rest had normal bone density. The number of fusion segments: 68 cases of single segment, 9 cases of two segment, 12 cases of three segment , and 3 cases of four segment. Fusion site:L_1,2 1 case, L_2,3 4 cases, L_3,4 10 cases, L_4,5 53 cases, L_2,3-L_3,4 3 cases, L_3,4-L_4,5 6 cases, L_1,2L_2,3L_3,4 1 case, L_1,2L_3,4L_4,5 1 case, L_2,3L_3,4L_4,5 10 cases, L_1,2L_2,3L_3,4L_4,5 3 cases. The clinical results and imaging results of this group of cases were observed, as well as the complications. RESULTS: The surgical time ranged from 40 to 140 minutes with an average of (60.92±27.40) minutes. The intraoperative bleeding volume was 20 to 720 ml with an average of (68.22±141.60) ml. The patients had a follow-up period of 6 to 84 months with an average of (38.50±12.75) months. The height of the intervertebral space recovered from (9.23±1.94) mm in preoperative to (12.68±2.01) mm in postoperative, and (9.11±1.72) mm at the last follow-up, there was a statistically significant difference(F=6.641, P=0.008);there was also a statistically significant difference between the postoperative and preoperative height of the intervertebral space(t=9.27, P<0.000 1);and there was also a statistically significant difference (t=10.06, P<0.000 1) between the last follow-up and postoperative height of the intervertebral space. At the last follow-up, cage subsidence grading was as follows:level 0 in 69 cases (76 segments), levelⅠin 17 cases (43 segments), level Ⅱin 5 cases (14 segments), and level Ⅲ in 1 case (1 segment);according to the number of segments, normal subsidence accounts for 56.72%, abnormal subsidence accounts for 43.28%. Bone mineral desity of normal subsidence groups was -0.50±0.07 whinch was better than that the abnormal subsidence groups -2.10±0.43, and the difference was statistically significant(χ²=2.275, P=0.014). As well as there was a statistically significant difference in the patient's VAS of backache from (6.28±2.11) in preoperative to (1.48±0.59) in last follow-up(t=8.56, P<0.05). The ODI recovered from (36.30±7.52)% before surgery to (10.20±2.50)% at the last follow-up, with a statistically significant difference (t=7.79, P<0.000 1). Complications involved 4 cases of intraoperative vascular injury, 21 cases of endplate injury, and 4 cases of combined vertebral fractures. The incision skin has no necrosis or infection. There were 4 cases of left sympathetic chain injury, 4 cases of transient left hip flexion weakness, 2 cases of left thigh anterolateral numbness with quadriceps femoris weakness, and 1 case of incomplete intestinal obstruction;8 cases were treated with posterior pedicle screw fixation due to fusion cage settlement accompanied by stubborn lower back pain, and 6 cases were treated with fusion cage settlement and lateral displacement. According to the actual number of cases, there were 38 complications, with an incidence rate of 41.3%. CONCLUSION The application of Stand alone OLIF in lumbar spine disease fusion has achieved good early results, with obvious clinical advantages, but also there are high probability of complications. It is recommended to choose carefully. It is necessary to continuously summarize and gradually clarify and complete the surgical indications and specific case selection criteria.
Humans ; Male ; Female ; Middle Aged ; Spinal Fusion/methods* ; Lumbar Vertebrae/injuries* ; Aged ; Adult ; Retrospective Studies ; Aged, 80 and over

This study investigated the impact of metabolic syndrome (MetS) and its components on prostate volume (PV) in the general Chinese population. In total, 43 455 participants in The First Medical Center of the Chinese PLA General Hospital (Beijing, China) from January 1, 2012, to December 31, 2022, undergoing health examinations were included in the study. Participants were categorized into four groups according to PV quartiles: Q1 (PV ≤24.94 ml), Q2 (PV >24.94 ml and ≤28.78 ml), Q3 (PV >28.78 ml and ≤34.07 ml), and Q4 (PV >34.07 ml), with Q1 serving as the reference group. Logistic regression analyses were used to examine the association between MetS and PV, with subgroup analyses conducted by age. Among the participants, 18 787 (43.2%) were diagnosed with MetS. In the multivariate analysis model, a significant correlation between MetS and PV was observed, with odds ratios (ORs) increasing as PV increased (Q2, OR = 1.203, 95% confidence interval [CI]: 1.139-1.271; Q3, OR = 1.300, 95% CI: 1.230-1.373; and Q4, OR = 1.556, 95% CI: 1.469-1.648). Analysis of MetS components revealed that all components were positively associated with PV, with abdominal obesity showing the most significant effect. The number of MetS components was identified as a dose-dependent risk factor for elevated PV. The impact of MetS, its components, and component count on PV exhibited a decreasing trend with advancing age. Overall, the influence of MetS, its components, and component count on PV was predominantly observed in the age groups of 40-49 years and 50-59 years. Early intervention targeting MetS can significantly alleviate the increase in PV, particularly benefiting individuals aged 40-59 years who have abdominal obesity.
Humans ; Male ; Metabolic Syndrome/complications* ; Middle Aged ; Cross-Sectional Studies ; Aged ; Prostate/diagnostic imaging* ; Adult ; Age Factors ; Organ Size ; China/epidemiology* ; Obesity, Abdominal ; Risk Factors

Cytotoxicity, usually represented by cell viability, is a crucial parameter for evaluating drug safety in vitro. Accurate prediction of cell viability/cytotoxicity could accelerate drug development in the early stage. In this study, by integrating cellular transcriptome and cell viability data using four machine learning algorithms (support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM)) and two ensemble algorithms (voting and stacking), highly accurate prediction models of 50% and 80% cell viability were developed with area under the receiver operating characteristic curve (AUROC) of 0.90 and 0.84, respectively; these models also showed good performance when utilized for diverse cell lines. Concerning the characterization of the employed Feature Genes, the models were interpreted, and the mechanisms of bioactive compounds with a narrow therapeutic index (NTI) can also be analyzed. In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. Moreover, for the first time, Cytotoxicity Signature (CTS) genes were identified, which could provide additional clues for further study of mechanisms of action (MOA), especially for NTI compounds.

The precise and rapid monitoring of multiple organ dysfunction is crucial in drug discovery. Traditional methods, such as pathological analysis, are often time-consuming and inefficient. Here, we developed a multiplexed near-infrared window two (NIR-II) fluorescent bioimaging method that allows for real-time, rapid, and quantitative assessment of multiple organ dysfunctions. Given that existing probes did not fully meet requirements, we synthesized a range of NIR-II hemicyanine dyes (HDs) with varying absorption and emission wavelengths. By modifying these dyes, we achieved high spatial and temporal resolution imaging of the liver, kidneys, stomach, and intestines. This method was further applied to investigate disorders induced by cisplatin, a drug known to cause gastric emptying issues along with liver and kidney injuries. By monitoring the metabolic rate of the dyes in these organs, we accurately quantified multi-organ dysfunction, which was also confirmed by gold-standard pathological analysis. Additionally, we evaluated the effects of five aristolochic acids (AAs) on multiple organ dysfunction. For the first time, we identified that AA-I and AA-II could cause gastric emptying disorders, which was further validated through transcriptomics analysis. Our study introduces a novel approach for the simultaneous monitoring of multi-organ dysfunction, which may significantly enhance the evaluation of drug side effects.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks