Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

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.

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

This study aims to explore the medication rules and mechanisms of treating chronic renal failure(CRF) by Jinling medical school based on data mining, network pharmacology, and experimental validation systematically and deeply. Firstly, the study selected the papers published by the inherited clinicians in Jinling medical school in Chinese journals using the subject headings named "traditional Chinese medicine(TCM) + chronic renal failure", "TCM + chronic renal inefficiency", or "TCM + consumptive disease" in China National Knowledge Infrastructure, Wanfang, and VIP Chinese Science and Technology Periodical Database and screened TCM formulas for treating CRF according to inclusion and exclusion criteria. The study analyzed the frequency of use of single TCM and the four properties, five tastes, channel tropism, and efficacy of TCM used with high frequency and performed association rule and clustering analysis, respectively. As a result, a total of 215 TCM formulas and 235 different single TCM were screened, respectively. The TCM used with high frequency included Astragali Radix, Rhei Radix et Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma, Poria, and Atractylodis Macrocephalae Rhizoma(top 5). The single TCM characterized by "cold properties, sweet flavor, and restoring spleen channel" and the TCM with the efficacy of tonifying deficiency had the highest frequency of use, respectively. Then, the TCM with the rules of "blood-activating and stasis-removing" and "diuretic and dampness-penetrating" appeared. In addition, the core combination of TCM [(Hexin Formula, HXF)] included "Astragali Radix, Rhei Radix et Rhizoma, Poria, Salviae Miltiorrhizae Radix, and Angelicae Sinensis Radix". The network pharmacology analysis showed that HXF had 91 active compounds and 250 corresponding protein targets including prostaglandin-endoperoxide synthase 2(PTGS2), PTGS1, sodium voltage-gated channel alpha subunit 5(SCN5A), cholinergic receptor muscarinic 1(CHRM1), and heat shock protein 90 alpha family class A member 1(HSP90AA1)(top 5). Gene Ontology(GO) function analysis revealed that the core targets of HXF predominantly affected biological processes, cellular components, and molecular functions such as positive regulation of transcription by ribonucleic acid polymerase Ⅱ and DNA template transcription, formation of cytosol, nucleus, and plasma membrane, and identical protein binding and enzyme binding. Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis revealed that CRF-related genes were involved in a variety of signaling pathways and cellular metabolic pathways, primarily involving "phosphatidylinositol 3-kinase(PI3K)-protein kinase B(Akt) pathway" and "advanced glycation end products-receptor for advanced glycation end products". Molecular docking results showed that the active components in HXF such as isomucronulatol 7-O-glucoside, betulinic acid, sitosterol, and przewaquinone B might be crucial in the treatment of CRF. Finally, a modified rat model with renal failure induced by adenine was used, and the in vivo experimental confirmation was performed based on the above-mentioned predictions. The results verify that HXF can regulate mitochondrial autophagy in the kidneys and the PI3K-Akt-mammalian target of rapamycin(mTOR) signaling pathway activation at upstream, so as to alleviate renal tubulointerstitial fibrosis and then delay the progression of CRF.
Data Mining ; Drugs, Chinese Herbal/chemistry* ; Network Pharmacology ; Humans ; Kidney Failure, Chronic/metabolism* ; Medicine, Chinese Traditional ; China

OBJECTIVE: To explore the efficacy and adverse reactions of CAG regimen combined with venetoclax, chidamide, and azacitidine in the treatment of elderly patients with acute myeloid leukemia (AML). METHODS: 15 elderly AML patients aged≥60 years old who were admitted to the Hematology Department of our hospital from May 2022 to October 2023 were treated with the CAG regimen combined with venetoclax, chidamide and azacitidine, and the efficacy, treatment-related adverse events, overall survival (OS) and event-free survival (EFS) were analyzed. RESULTS: After one course of treatment, 11 out of 15 patients achieved complete response (CR), 3 patients achieved CR with incomplete hematologic recovery (CRi), and 1 patient died due to prior infection before efficacy evaluation, and the overall response rate (ORR) was 93.3% (14/15). The median follow-up time was 131 (19-275) days, with median OS and EFS both remaining unreached. Next-generation sequencing (NGS) analysis showed that among the 15 patients, 13 were detected with gene mutations, and there were 7 genes with mutation frequencies of more than 10%, including ASXL1 (4 cases), RUNX1 (4 cases), BCOR (3 cases), DNMT3A (3 cases), STAG2 (2 cases), IDH1/2 (2 cases), and TET (2 cases). Among the 13 patients with detectable mutations, 12 patients achieved composite response (CR+CRi). The average recovery time of white blood cell count was 14.6 days after chemotherapy, and the average recovery time of platelets was 7.7 days after chemotherapy. The main adverse event was myelosuppression, with 10 patients accompanied by infection. Except for 1 patient who died due to septic shock during chemotherapy, no patients experienced serious complications such as heart, liver, or kidney damage during the treatment process. CONCLUSION The CACAG+V regimen, which combines the CAG regimen with venetoclax, chidamide, and azacitidine, can be applied in the treatment of elderly AML patients, demonstrating good safety and induction remission rate.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Bridged Bicyclo Compounds, Heterocyclic/therapeutic use* ; Sulfonamides/therapeutic use* ; Aminopyridines/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Azacitidine/therapeutic use* ; Aged ; Benzamides/therapeutic use* ; Male ; Female ; Treatment Outcome ; Middle Aged ; Cytarabine ; Aclarubicin ; Granulocyte Colony-Stimulating Factor

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged