Acute toxicity and responses of antioxidant systems to dibutyl phthalate in neonate and adult Daphnia magna

Dibutyl phthalate (DBP) poses a severe threat to aquatic ecosystems, introducing hazards to both aquatic species and human health. The ecotoxic effects of DBP on aquatic organisms have not been fully investigated. This study investigates acute toxicity, oxidative damage, and antioxidant enzyme parameters in neonate and adult Daphnia magna exposed to DBP. The obtained results show comparable DBP toxic responses in neonates and adults. The median lethal concentrations (LC50) of DBP in neonates exposed for 24 and 48 h were 3.48 and 2.83 mg/L, respectively. The LC50 of adults for the same DBP exposure durations were 4.92 and 4.31 mg/L, respectively. Increased hydrogen peroxide and malondialdehyde were found in neonates and adults at both 24 and 48 h, while the total antioxidant capacity decreased. Superoxide dismutase activity increased significantly in neonates and adults exposed to 0.5 mg/L DBP, and subsequently diminished at higher DBP concentrations and prolonged exposure. Catalase and glutathione S-transferases activities both decreased markedly in neonates and adults. The changes observed were found to be time and concentration dependent. Overall, these data indicated that the acute toxic effects of DBP exposure on neonates were more pronounced than in adults, and oxidative injury may be the main mechanism of DBP toxicity. These results provide a functional link for lipid peroxidation, antioxidant capacity, and antioxidant enzyme levels in the Daphnia magna response to DBP exposure

A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method

Recurrent renal secondary hyperparathyroidism caused by supernumerary mediastinal parathyroid gland and parathyromatosis: A case report

BackgroundSurgical parathyroidectomy (PTX) is necessary for patients with severe and progressive secondary hyperparathyroidism (SHPT) refractory to medical treatment. Recurrence of SHPT after PTX is a serious clinical problem. Both supernumerary mediastinal parathyroid gland and parathyromatosis are the rare causes of recurrent renal SHPT. We report a rare case of recurrent renal SHPT due to supernumerary mediastinal parathyroid gland and parathyromatosis.Case presentationA 53-year-old man underwent total parathyroidectomy with autotransplantation due to the drug-refractory SHPT 17 years ago. In the last 11 months, the patient experienced symptoms including bone pain and skin itch, and the serum intact parathyroid hormone (iPTH) level elevated to 1,587 pg/ml. Ultrasound detected two hypoechoic lesions located at the dorsal area of right lobe of the thyroid gland, and both lesions presented as characteristics of hyperparathyroidism in contrast-enhanced ultrasound. 99mTc-MIBI/SPECT detected a nodule in the mediastinum. A reoperation involved a cervicotomy for excising parathyromatosis lesions and the surrounding tissue and a thoracoscopic surgery for resecting a mediastinal parathyroid gland. According to a histological examination, two lesions behind the right thyroid lobe and one lesion in the central region had been defined as parathyromatosis. A nodule in the mediastinum was consistent with hyperplastic parathyroid. The patient remained well for 10 months with alleviated symptoms and stabilized iPTH levels in the range of 123–201 pg/ml.ConclusionAlthough rare, recurrent SHPT may be caused by a coexistence of both supernumerary parathyroid glands and parathyromatosis, which should receive more attention. The combination of imaging modalities is important for reoperative locations of parathyroid lesions. To successfully treat parathyromatosis, all the lesions and the surrounding tissue must be excised. Thoracoscopic surgery is a reliable and safe approach for the resection of ectopic mediastinal parathyroid glands

DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

We propose DISC-LawLLM, an intelligent legal system utilizing large language models (LLMs) to provide a wide range of legal services. We adopt legal syllogism prompting strategies to construct supervised fine-tuning datasets in the Chinese Judicial domain and fine-tune LLMs with legal reasoning capability. We augment LLMs with a retrieval module to enhance models' ability to access and utilize external legal knowledge. A comprehensive legal benchmark, DISC-Law-Eval, is presented to evaluate intelligent legal systems from both objective and subjective dimensions. Quantitative and qualitative results on DISC-Law-Eval demonstrate the effectiveness of our system in serving various users across diverse legal scenarios. The detailed resources are available at https://github.com/FudanDISC/DISC-LawLLM

Development of Inflammatory Immune Response-Related Drugs Based on G Protein-Coupled Receptor Kinase 2

G protein-coupled receptor kinase 2 (GRK2), as a vital Ser/Thr kinase, is an important regulatory protein in the inflammatory immune response (IIR) by maintaining the balance between the function of inflammatory immune cells and non-conventional inflammatory immune cells and regulating inflammatory immune cell infiltration, inflammatory cytokine secretion, and the signaling associated with endothelial function. However, the imbalance of GRK2 expression and activity plays an important role in the development of IIR-related diseases, such as hypertension, heart failure, Alzheimer’s disease, type 2 diabetes mellitus, insulin resistance, rheumatoid arthritis, thyroid cancer, multiple sclerosis, and liver cancer. Small molecule GRK2 inhibitors, including balanol, Takeda inhibitors, paroxetine and derivatives, M119 and gallein, peptides, RNA aptamers, Raf kinase inhibitory protein, and microRNAs, that can directly inhibit GRK2 kinase activity have been identified by different strategies. This review discusses recent progress in one of the hallmark molecular abnormalities of GRK2 in IIR-related diseases and explores the soft regulation of IIR by innovative drugs reducing the excessive activity of GRK2 to basal levels, without damaging normal physiological function, to ameliorate inflammatory disorders

StaPep: an open-source tool for the structure prediction and feature extraction of hydrocarbon-stapled peptides

Many tools exist for extracting structural and physiochemical descriptors from linear peptides to predict their properties, but similar tools for hydrocarbon-stapled peptides are lacking.Here, we present StaPep, a Python-based toolkit designed for generating 2D/3D structures and calculating 21 distinct features for hydrocarbon-stapled peptides.The current version supports hydrocarbon-stapled peptides containing 2 non-standard amino acids (norleucine and 2-aminoisobutyric acid) and 6 nonnatural anchoring residues (S3, S5, S8, R3, R5 and R8).Then we established a hand-curated dataset of 201 hydrocarbon-stapled peptides and 384 linear peptides with sequence information and experimental membrane permeability, to showcase StaPep's application in artificial intelligence projects.A machine learning-based predictor utilizing above calculated features was developed with AUC of 0.85, for identifying cell-penetrating hydrocarbon-stapled peptides.StaPep's pipeline spans data retrieval, cleaning, structure generation, molecular feature calculation, and machine learning model construction for hydrocarbon-stapled peptides.The source codes and dataset are freely available on Github: https://github.com/dahuilangda/stapep_package.Comment: 26 pages, 6 figure

Genetic identification and expression optimization of a novel protease HapR from Bacillus velezensis

Due to the broad application and substantial market demand for proteases, it was vital to explore the novel and efficient protease resources. The aim of this study was to identify the novel protease for tobacco protein degradation and optimize the expression levels. Firstly, the tobacco protein was used as the sole nitrogen resource for isolation of protease-producing strains, and a strain with high protease production ability was obtained, identified as Bacillus velezensis WH-7. Then, the whole genome sequencing was conducted on the strain B. velezensis WH-7, and 7 proteases genes were mined by gene annotation analysis. By further heterologous expression of the 7 protease genes, the key protease HapR was identified with the highest protease activity (144.19 U/mL). Moreover, the catalysis mechanism of HapR was explained by amino acid sequence analysis. The expression levels of protease HapR were further improved through optimization of promoter, signal peptide and host strain, and the maximum protease activity reaced 384.27 U/mL in WX-02/pHY-P43-SPyfkD-hapR, increased by 167% than that of initial recombinant strain HZ/pHY-P43-SPhapR-hapR. This study identified a novel protease HapR and the expression level was significantly improved, which provided an important enzyme resource for the development of enzyme preparations in tobacco protein degradation

Comparative studies of salinomycin-loaded nanoparticles prepared by nanoprecipitation and single emulsion method

To establish a satisfactory delivery system for the delivery of salinomycin (Sal), a novel, selective cancer stem cell inhibitor with prominent toxicity, gelatinase-responsive core-shell nanoparticles (NPs), were prepared by nanoprecipitation method (NR-NPs) and single emulsion method (SE-NPs). The gelatinase-responsive copolymer was prepared by carboxylation and double amination method. We studied the stability of NPs prepared by nanoprecipitation method with different proportions of F68 in aqueous phase to determine the best proportion used in our study. Then, the NPs were prepared by nanoprecipitation method with the best proportion of F68 and single emulsion method, and their physiochemical traits including morphology, particle size, zeta potential, drug loading content, stability, and in vitro release profiles were studied. The SE-NPs showed significant differences in particle size, drug loading content, stability, and in vitro release profiles compared to NR-NPs. The SE-NPs presented higher drug entrapment efficiency and superior stability than the NR-NPs. The drug release rate of SE-NPs was more sustainable than that of the NR-NPs, and in vivo experiment indicated that NPs could prominently reduce the toxicity of Sal. Our study demonstrates that the SE-NPs could be a satisfactory method for the preparation of gelatinase-responsive NPs for intelligent delivery of Sal