Integrated Network Pharmacology Analysis and Experimental Validation to Elucidate the Mechanism of Acteoside in Treating Diabetic Kidney Disease.

Background: Acteoside, an active ingredient found in various medicinal herbs, is effective in the treatment of diabetic kidney disease (DKD); however, the intrinsic pharmacological mechanism of action of acteoside in the treatment of DKD remains unclear. This study utilizes a combined approach of network pharmacology and experimental validation to investigate the potential molecular mechanism systematically. Methods: First, acteoside potential targets and DKD-associated targets were aggregated from public databases. Subsequently, utilizing protein-protein interaction (PPI) networks, alongside GO and KEGG pathway enrichment analyses, we established target-pathway networks to identify core potential therapeutic targets and pathways. Further, molecular docking facilitated the confirmation of interactions between acteoside and central targets. Finally, the conjectured molecular mechanisms of acteoside against DKD were verified through experimentation on unilateral nephrectomy combined with streptozotocin (STZ) rat model. The underlying downstream mechanisms were further investigated. Results: Network pharmacology identified 129 potential intersected targets of acteoside for DKD treatment, including targets such as AKT1, TNF, Casp3, MMP9, SRC, IGF1, EGFR, HRAS, CASP8, and MAPK8. Enrichment analyses indicated the PI3K-Akt, MAPK, Metabolic, and Relaxin signaling pathways could be involved in this therapeutic context. Molecular docking revealed high-affinity binding of acteoside to PIK3R1, AKT1, and NF-κB1. In vivo studies validated the therapeutic efficacy of acteoside, demonstrating reduced blood glucose levels, improved serum Scr and BUN levels, decreased 24-hour urinary total protein (P<0.05), alongside mitigated podocyte injury (P<0.05) and ameliorated renal pathological lesions. Furthermore, this finding indicates that acteoside inhibits the expression of pyroptosis markers NLRP3, Caspase-1, IL-1ß, and IL-18 through the modulation of the PI3K/AKT/NF-κB pathway. Conclusion: Acteoside demonstrates renoprotective effects in DKD by regulating the PI3K/AKT/NF-κB signaling pathway and alleviating pyroptosis. This study explores the pharmacological mechanism underlying acteoside's efficacy in DKD treatment, providing a foundation for further basic and clinical research.

Transcriptomic analysis and experiments revealed that remimazolam promotes proliferation and G1/S transition in HCT8 cells.

Background: Remimazolam is a new ultrashort-acting benzodiazepine for sedation and anesthesia. The effects of remimazolam and the mechanism by which it functions in cancer cells have not been determined. This research aimed to explore the mechanism of remimazolam action in colon cancer treatment, using bioinformatics analysis and in vitro experiments. Methods: Cell cycle progression, colony formation, self-renewal capacity, and apoptosis detection were performed in HCT8 cells treated with or without remimazolam. Transcriptome sequencing, Gene Ontology, Kyoto Encyclopedia of Genes and Genome, Protein-Protein Interaction, Gene Set Enrichment Analysis, Western blotting, and qPCR were performed to investigate the mechanism of action of remimazolam in HCT8 colon cancer cells. Results: Remimazolam promoted proliferation and cell-cycle progression of HCT8 cells. After remimazolam treatment, a total of 1,096 differentially expressed genes (DEGs) were identified: 673 genes were downregulated, and 423 genes were upregulated. The DEGs were enriched mainly in "DNA replication", "cell cycle", and "G1/S transition" related pathways. There were 15 DEGs verified by qPCR, and representative biomarkers were detected by Western Bloting. The remimazolam-mediated promotion of cell proliferation and cell cycle was reversed by G1T28, a CDK4/6 inhibitor. Conclusion: Remimazolam promoted cell-cycle progression and proliferation in HCT8 colon cancer cells, indicating that the long-term use of remimazolam has potential adverse effects in the anesthesia of patients with colon cancer.

Diagnosis of Canine Tumours and the Value of Combined Detection of VEGF, P53, SF and NLRP3 for the Early Diagnosis of Canine Mammary Carcinoma.

The average life of a dog is generally maintained at ten to fifteen years, and tumours are the predominant reason that leads to the death of dogs, especially canine mammary carcinoma. Therefore, early diagnosis of tumours is very important. In this study, tumor size, morphology, and texture could be seen through general clinical examination, tumor metastasis could be seen through imaging examination, inflammatory reactions could be seen through hematological examination, and abnormal cell morphology could be seen through cytological and histopathological examination. In the 269 malignant cases and 179 benign cases, we randomly selected 30 cases each, and an additional 30 healthy dogs were selected for the experiment (healthy dogs: dogs in good physical condition without any tumor or other diseases). We used RT-qPCR and ELISA to determine the relative expression of vascular endothelial growth factor (VEGF), tumor protein P53 (P53), serum ferritin (SF), and NOD-like receptor protein 3 (NLRP3) in 30 healthy dogs, 30 dogs with benign mammary tumours, and 30 dogs with malignant mammary tumours. In the results, the same expression trend was obtained both in serum and tissues, and the expression of the four markers was the highest in malignant mammary tumours, with highly significant differences compared with the benign and healthy/paracancerous groups. By plotting the ROC curves, it was found that the results of combined tests were better than a single test and the combination of the four markers was the best for the early diagnosis. In conclusion, this can assist the clinical early diagnosis to a certain extent, and also provides some references and assistance for the development of tumor detection kits in clinical practice.

A domain knowledge-based interpretable deep learning system for improving clinical breast ultrasound diagnosis.

BACKGROUND: Though deep learning has consistently demonstrated advantages in the automatic interpretation of breast ultrasound images, its black-box nature hinders potential interactions with radiologists, posing obstacles for clinical deployment. METHODS: We proposed a domain knowledge-based interpretable deep learning system for improving breast cancer risk prediction via paired multimodal ultrasound images. The deep learning system was developed on 4320 multimodal breast ultrasound images of 1440 biopsy-confirmed lesions from 1348 prospectively enrolled patients across two hospitals between August 2019 and December 2022. The lesions were allocated to 70% training cohort, 10% validation cohort, and 20% test cohort based on case recruitment date. RESULTS: Here, we show that the interpretable deep learning system can predict breast cancer risk as accurately as experienced radiologists, with an area under the receiver operating characteristic curve of 0.902 (95% confidence interval = 0.882 - 0.921), sensitivity of 75.2%, and specificity of 91.8% on the test cohort. With the aid of the deep learning system, particularly its inherent explainable features, junior radiologists tend to achieve better clinical outcomes, while senior radiologists experience increased confidence levels. Multimodal ultrasound images augmented with domain knowledge-based reasoning cues enable an effective human-machine collaboration at a high level of prediction performance. CONCLUSIONS: Such a clinically applicable deep learning system may be incorporated into future breast cancer screening and support assisted or second-read workflows.

Breast cancer is one of the most common cancers, and finding it early can greatly improve patients' chances of survival and recovery. We create a tool based on artificial intelligence (AI)­whereby computer software learns to perform tasks that normally require human thinking­called MUP-Net. MUP-Net can analyze medical images to predict a patient's risk of having breast cancer. To make this AI tool usable in clinical practice, we enabled doctors to see the reasoning behind the AI's predictions by visualizing the key image features it analyzed. We showed that our AI tool not only makes doctors more confident in their diagnosis but also helps them make better decisions, especially for less experienced doctors. With further testing, our AI tool may help clinicians to diagnose breast cancer more accurately and quickly, potentially improving patient outcomes.

Emerging health disparities among college graduates: Understanding the health consequences of education-occupation mismatch.

This study examines the health consequences and underlying pathways of education-occupation mismatch. Using a longitudinal sample of college graduates from the Panel Studies of Income Dynamics (1984-2019) and employing longitudinal hybrid models, we found that contemporary vertical mismatch (between education level and educational requirements of occupation) was associated with poorer psychological well-being and bio-behaviors (obesity and smoking), but not physical health. In contrast, horizontal mismatch (between field of study and field required for occupation) did not show clear health consequences. Sequence analysis was employed to uncover the mismatch trajectories and revealed that persistent vertical mismatch over one's career had a greater impact on psychological distress and smoking than episodic mismatch experiences. Furthermore, the linkage between vertical mismatch and health outcomes was likely shaped by psychosocial processes rather than reduced material well-being. These findings imply that education-occupation vertical (mis)match produces health disparities between occupationally matched and mismatched college graduates.

Impaired synaptic plasticity and decreased glutamatergic neuron excitability induced by SIRT1/BDNF downregulation in the hippocampal CA1 region are involved in postoperative cognitive dysfunction.

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a common complication after anesthesia/surgery, especially among elderly patients, and poses a significant threat to their postoperative quality of life and overall well-being. While it is widely accepted that elderly patients may experience POCD following anesthesia/surgery, the exact mechanism behind this phenomenon remains unclear. Several studies have indicated that the interaction between silent mating type information regulation 2 homologue 1 (SIRT1) and brain-derived neurotrophic factor (BDNF) is crucial in controlling cognitive function and is strongly linked to neurodegenerative disorders. Hence, this research aims to explore how SIRT1/BDNF impacts cognitive decline caused by anesthesia/surgery in aged mice. METHODS: Open field test (OFT) was used to determine whether anesthesia/surgery affected the motor ability of mice, while the postoperative cognitive function of 18 months old mice was evaluated with Novel object recognition test (NORT), Object location test (OLT) and Fear condition test (FC). The expressions of SIRT1 and other molecules were analyzed by western blot and immunofluorescence staining. The hippocampal synaptic plasticity was detected by Golgi staining and Long-term potentiation (LTP). The effects of SIRT1 and BDNF overexpression as well as chemogenetic activation of glutamatergic neurons in hippocampal CA1 region of 18 months old vesicular glutamate transporter 1 (VGLUT1) mice on POCD were further investigated. RESULTS: The research results revealed that older mice exhibited cognitive impairment following intramedullary fixation of tibial fracture. Additionally, a notable decrease in the expression of SIRT1/BDNF and neuronal excitability in hippocampal CA1 glutamatergic neurons was observed. By increasing levels of SIRT1/BDNF or enhancing glutamatergic neuron excitability in the CA1 region, it was possible to effectively mitigate synaptic plasticity impairment and ameliorate postoperative cognitive dysfunction. CONCLUSIONS: The decline in SIRT1/BDNF levels leading to changes in synaptic plasticity and neuronal excitability in older mice could be a significant factor contributing to cognitive impairment after anesthesia/surgery.

Germ cell-specific gene 2 accelerates cell cycle in epithelial ovarian cancer by inhibiting GSK3α-p27 cascade.

Epithelial ovarian cancer (EOC) is one of the most common malignant gynecological tumors with rapid growth potential and poor prognosis, however, the molecular mechanism underlying its outgrowth remained elusive. Germ cell-specific gene 2 (GSG2) was previously reported to be highly expressed in ovarian cancer and was essential for the growth of EOC. In this study, GSG2-knockdown cells and GSG2-overexpress cells were established through lentivirus-mediated transfection with Human ovarian cancer cells HO8910 and SKOV3. Knockdown of GSG2 inhibited cell proliferation and induced G2/M phase arrest in EOC. Interestingly, the expression of p27, a well-known regulator of the cell cycle showed a most significant increase after GSG2 knockdown. Further phosphorylation-protein array demonstrated the phosphorylation of GSK3αSer21 decreased in GSG2-knockdown cells to the most extent. Notably, inhibiting GSK3α activity effectively rescued GSG2 knockdown's suppression on cell cycle as well as p27 expression in EOC. Our study substantiates that GSG2 is able to phosphorylate GSK3α at Ser21 and then leads to the reduction of p27 expression, resulting in cell cycle acceleration and cell proliferation promotion. Thus, GSG2 may have the potential to become a promising target in EOC.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Castleman Disease Presenting in the Neck: A Report of 3 Cases and a Literature Review.

BACKGROUND Castleman's disease (CD) is a reactive lymph node hyperplasia initially identified by Castleman in 1956. CD predominantly affects individuals 20-50 years of age, with low incidence in children. This case report describes 3 cases of CD treated in our hospital and reviews the relevant literature. The purpose of this case report was to enhance clinical understanding and treatment of CD in the head and neck in children. CASE REPORT To enhance clinical understanding and improve treatment of CD in the head and neck region in children, we present the cases of 3 patients who were admitted to the hospital, primarily presenting with a neck mass. Preoperatively, the patients collectively exhibited non-specific findings. Surgical interventions were performed with Cases 1 and 3 undergoing left functional (radical) neck lymph node dissection, in contrast to Case 2, in which bilateral functional (radical) neck lymph node dissection was executed. Pathological examination confirmed the diagnosis of CD in each of the 3 patients. Following surgery, a follow-up period ranging from 3 months to 1 year revealed that all patients had successfully recovered, with no recurrence. CONCLUSIONS Castleman disease is a rare disease in children and difficult clinical diagnosis. Some patients with unicentric Castleman disease (UCD) can be treated with surgery, and those with multicentric Castleman disease (MCD) need chemotherapy, but at present there is no widely accepted treatment plan.

Sex-Specific Expression of Histone Lysine Demethylases (KDMs) in Thyroid Cancer.

BACKGROUND: The incidence of thyroid cancer in women is 3-4-fold higher than in men. To characterize sex-specific molecular alterations in thyroid cancer, we examined the expression of sex-biased genes in normal thyroids and thyroid tumors. METHODS: Ingenuity pathways analysis was used to define sex-biased gene networks using data from the Cancer Genome Atlas (TCGA). Confirmatory studies were performed through the analysis of histone lysine demethylases (KDMs) expression by real-time PCR and immunostaining. RESULTS: In normal thyroids, 44 sex-biased genes were comparatively upregulated in male and 28 in female patients. The expressions of 37/72 (51%) sex-biased genes were affected in cancer tissues compared with normal thyroids. Gene network analyses revealed sex-specific patterns in the expressions of KDM5C, KDM5D, and KDM6A. In confirmatory studies, KDM5D mRNA and protein were detected only in males, whereas KDM5C and KDM6A were detected in samples from male and female patients. Nuclear staining with anti-KDMs was found in normal thyroids, but a loss of nuclear expression with a concomitant gain of cytoplasmic staining was observed in cancer tissues. CONCLUSIONS: Normal thyroids have a sex-specific molecular signature, and the development of thyroid cancer is associated with a differential expression of sex-biased genes. The sex-specific expression of KDMs, coupled with cancer-related alterations in their intracellular localization, may contribute to mechanisms underlying sex differences in thyroid tumorigenesis.

Enhancing malignancy prediction in thyroid nodules: A multimodal ultrasound radiomics approach in TI-RADS category 4 lesions.

PURPOSE: To explore the diagnostic value of intralesional and perilesional radiomics based on multimodal ultrasound (US) images in predicting the malignant ACR TIRADS 4 thyroid nodules (TNs). METHODS: A total of 297 cases of TNs in patients who underwent preoperative thyroid grayscale US and shear wave elastography (STE) were enrolled (training cohort: n = 150, internal validation cohort: n = 77, external validation cohort: n = 70). Regions of interests (ROIs) were delineated on grayscale US images and STE images, and then an isotropic expansion of 1.0, 1.5, 2.0, 2.5, and 3.0 mm was applied. Predictive models were established using recursive feature elimination-support vector machines (RFE-SVM) based on radiomics features calculated by random forest. RESULTS: The perilesional ROI1.5mm expansion achieved the highest area under curve (AUC) (AUC: 0.753 for grayscale US, 0.728 for STE; 95% confidence interval (CI): 0.664-0.743, 0.684-0.739, respectively). The joint model had the highest AUC values of 0.936 in the training dataset, 0.926 in internal dataset, and 0.893 in external dataset. The calibration curve showed good consistency and the decision curve indicated a greater clinical net benefit of the joint model. CONCLUSION: Joint model containing perilesional radiomics (1.5 mm) had significant value in predicting the malignant ACR TIRADS 4 TNs.

A rare germline BMP15 missense mutation causes hereditary ovarian immature teratoma in human.

Ovarian immature teratomas (OITs) are malignant tumors originating from the ovarian germ cells that mainly occur during the first 30 y of a female's life. Early age of onset strongly suggests the presence of susceptibility gene mutations for the disease yet to be discovered. Whole exon sequencing was used to screen pathogenic mutations from pedigrees with OITs. A rare missense germline mutation (C262T) in the first exon of the BMP15 gene was identified. In silico calculation suggested that the mutation could impair the formation of mature peptides. In vitro experiments on cell lines confirmed that the mutation caused an 84.7% reduction in the secretion of mature BMP15. Clinical samples from OIT patients also showed a similar pattern of decrease in the BMP15 expression. In the transgenic mouse model, the spontaneous parthenogenetic activation significantly increased in oocytes carrying the T allele. Remarkably, a mouse carrying the T allele developed the phenotype of OIT. Oocyte-specific RNA sequencing revealed that abnormal activation of the H-Ras/MAPK pathway might contribute to the development of OIT. BMP15 was identified as a pathogenic gene for OIT which improved our understanding of the etiology of OIT and provided a potential biomarker for genetic screening of this disorder.

Multiple mediation of the association between childhood emotional abuse and adult obesity by anxiety and bulimia - a sample from bariatric surgery candidates and healthy controls.

Bulimia, which means a person has episodes of eating a very large amount of food (bingeing) during which the person feels a loss of control over their eating, is the most primitive reason for being overweight and obese. The extended literature has indicated that childhood emotional abuse has a close relationship with adverse mood states, bulimia, and obesity. To comprehensively understand the potential links among these factors, we evaluated a multiple mediation model in which anxiety/depression and bulimia were mediators between childhood emotional abuse and body mass index (BMI). A set of self-report questionnaires, including the Childhood Trauma Questionnaire (CTQ), Beck Anxiety Inventory, Beck Depression Inventory (BDI), and Eating Disorder Inventory (EDI), was sent out. Clinical data from 37 obese patients (age: 29.65 ± 5.35, body mass index (BMI): 37.59 ± 6.34) and 37 demographically well-matched healthy people with normal body weight (age: 31.35 ± 10.84, BMI: 22.16 ± 3.69) were included in the investigation. We first performed an independent t-test to compare all scales or subscale scores between the two groups. Then, we conducted Pearson correlation analysis to test every two variables' pairwise correlation. Finally, multiple mediation analysis was performed with BMI as the outcome variable, and childhood emotional abuse as the predictive variable. Pairs of anxiety, bulimia, and depression, bulimia were selected as the mediating variables in different multiple mediation models separately. The results show that the obese group reported higher childhood emotional abuse (t = 2.157, p = 0.034), worse mood state (anxiety: t = 5.466, p < 0.001; depression: t = 2.220, p = 0.030), and higher bulimia (t = 3.400, p = 0.001) than the healthy control group. Positive correlations were found in every pairwise combination of BMI, childhood emotional abuse, anxiety, and bulimia. Multiple mediation analyses indicate that childhood emotional abuse is positively linked to BMI (ß = 1.312, 95% CI = 0.482-2.141). The model using anxiety and bulimia as the multiple mediating variables is attested to play roles in the relationship between childhood emotional abuse and obesity (indirect effect = 0.739, 95% CI = 0.261-1.608, 56.33% of the total effect). These findings confirm that childhood emotional abuse contributes to adulthood obesity through the multiple mediating effects of anxiety and bulimia. The present study adds another potential model to facilitate our understanding of the eating psychopathology of obesity.

Impact of the addition of dexmedetomidine to patient-controlled intravenous analgesia on postoperative pain-sleep interaction cycle and delirium: A systematic review and meta-analysis of randomized controlled trials.

Background: The reciprocal nexus between sleep and pain is well-documented, with the deleterious impact of operative trauma potentially playing a pivotal role in the dysregulation of this interplay, which could significantly contribute to the manifestation of postoperative delirium (POD). Studies have investigated the effect of adding dexmedetomidine (DEX) to patient-controlled intravenous analgesia (PCIA) pumps on postoperative pain-sleep interaction cycle and POD, but conclusions remained uncertain. The objective of this investigation is to perform a meta-analysis that thoroughly assesses the impact of integrating DEX into PCIA, focusing on analgesic effectiveness, sleep quality, and the incidence of delirium in postoperative patients. Methods: PubMed, Embase, Cochrane Library, SinoMed, and Wanfang Data Knowledge Service Platform were searched, for publications in any language, from database inception to September 2023. Our analysis encompassed randomized controlled trials (RCTs) that examine the therapeutic efficacy and risk profile of adding DEX to the PCIA on the postoperative pain-sleep interaction cycle, by focusing on changes in postoperative analgesia (Visual analog scale (VAS) score), sleep efficiency, sleep structure, subjective sleep score (Assen insomnia scale and numerical rating scale) and adverse event rate. Results: 34 RCTs (4324 patients) were analyzed. This study shows DEX improved analgesia and reduced VAS scores at 6, 12, and 24 h after surgery. Sleep efficiency was enhanced on the 1st and 2nd postoperative night. DEX improved sleep structure at the 1st postoperative night by reducing non-rapid eye movement stage 1 (N1) sleep and increasing non-rapid eye movement stage 2 (N2) and non-rapid eye movement stage 3 (N3) sleep. At the 2nd night, DEX reduced N1 sleep and increased N2 sleep, but not N3 sleep. Data from AIS and NRS showed improvement in subjective sleep scores on the 1st postoperative night and 2nd night. Additionally, DEX decreased the occurrence of POD on the 24 h and first-three days. Conclusion: This study shows that the typical DEX doses added to PCIA with sufentanil were 2-5 µg/kg or approximately 200-250 µg, and the addition of DEX to PCIA can improve pain-sleep interaction cycle from multiple perspectives, and further decrease the occurrence of POD.

The feasibility of dexmedetomidine-led anesthesia maintenance strategy during major abdominal surgery.

Background: Dexmedetomidine is known for its selective action on α2-adrenoceptor sites and is recognized for its neuroprotective capabilities. It can improve postoperative cognitive function. Commonly used anesthetics, such as sevoflurane and propofol, have been reported to affect postoperative cognitive function. Therefore, it could be valuable to explore dexmedetomidine-led anesthesia strategy. This study was designed to assess the performance, safety, and effective infusion rate in anesthesia maintenance, to explore a feasible dexmedetomidine-led anesthesia maintenance protocol, and to provide a foundation for potential combined anesthesia. Methods: Thirty patients aged 18-60 years, classified as ASA I or II, undergoing abdominal surgery were involved. The anesthesia maintenance was achieved with dexmedetomidine, remifentanil and rocuronium. Dixon up-and-down sequential methodology was utilized to ascertain the ED50 of dexmedetomidine for maintaining Patient State Index (PSI) 25-40 (depth of stage III anesthesia). Intraoperative HR, BP and depth of anesthesia were monitored and controlled. The wake-up time from anesthesia, the incidence of intraoperative awareness and postoperative delirium, and the patients' satisfaction were assessed. Results: The results indicated that dexmedetomidine-led anesthesia could maintain the depth of stage III anesthesia during abdominal surgery. The ED50 and ED95 of dexmedetomidine infusion rates during anesthesia maintenance were 2.298 µg/kg·h (95%CI: 2.190-2.404 µg/kg·h) and 3.765 µg/kg·h (95%CI: 3.550-4.050 µg/kg·h). Continuous infusion of dexmedetomidine and 0.1-0.3 µg/kg·min remifentanil could maintain PSI 25-40, and provide appropriate anesthesia depth for abdominal surgery. Perioperative bradycardia and hypertension could be rapidly corrected with atropine and nitroglycerin. The median wake-up time after anesthesia was 4.8 min, the perioperative maximum HR had significant correlation with wake-up time and intraoperative dexmedetomidine dose. No intraoperative awareness and postoperative delirium occurred; the patients were satisfied with dexmedetomidine-led anesthesia. Conclusions: dexmedetomidine-led strategy could maintain stable depth of anesthesia throughout surgery, and the ED50 of dexmedetomidine infusion rates was 2.298 µg/kg·h. Intraoperative HR, BP and depth of anesthesia require monitoring, the bradycardia and hypertension could be rapidly corrected.

Hypoxia promotes metastasis by relieving miR-598-3p-restricted glycolysis in gastric cancer.

The activation of glycolysis, particularly in the context of reprogrammed energy metabolism, is increasingly recognized as a significant characteristic of cancer. However, the precise mechanisms by which glycolysis is promoted in metastatic gastric cancer cells under normal oxygen conditions remain poorly understood. MicroRNAs (miRNAs) play a crucial role in the development of malignant phenotypes in gastric cancer. Nevertheless, our understanding of the specific involvement of miRNAs in hypoxia-induced metabolic shifting and the subsequent metastatic processes is limited. Hypoxia-induced downregulation of miR-598-3p mechanistically leads to the upregulation of RMP and IGF1r, thereby promoting glycolysis. Either overexpression of miR-598-3p or R406 treatment effectively suppresses the metastasis of gastric cancer cells both in vitro and in vivo. Collectively, the depletion of miR-598-3p alters glucose metabolism from oxidative phosphorylation to glycolysis, thereby exacerbating the malignancy of gastric cancer cells. The present findings indicate a potential target for the development of therapeutics against gastric cancers with increased miR-598-3p expression.

Robust miniature Cas-based transcriptional modulation by engineering Un1Cas12f1 and tethering Sso7d.

The miniature V-F CRISPR-Cas12f system has been repurposed for gene editing and transcription modulation. The small size of Cas12f satisfies the packaging capacity of adeno-associated virus (AAV) for gene therapy. However, the efficiency of Cas12f-mediated transcriptional activation varies among different target sites. Here, we developed a robust miniature Cas-based transcriptional activation or silencing system using Un1Cas12f1. We engineered Un1Cas12f1 and the cognate guide RNA and generated miniCRa, which led to a 1,319-fold increase in the activation of the ASCL1 gene. The activity can be further increased by tethering DNA-binding protein Sso7d to miniCRa and generating SminiCRa, which reached a 5,628-fold activation of the ASCL1 gene and at least hundreds-fold activation at other genes examined. We adopted these mutations of Un1Cas12f1 for transcriptional repression and generated miniCRi or SminiCRi, which led to the repression of ∼80% on average of eight genes. We generated an all-in-one AAV vector AIOminiCRi used to silence the disease-related gene SERPINA1. AIOminiCRi AAVs led to the 70% repression of the SERPINA1 gene in the Huh-7 cells. In summary, miniCRa, SminiCRa, miniCRi, and SminiCRi are robust miniature transcriptional modulators with high specificity that expand the toolbox for biomedical research and therapeutic applications.

CCNB1 may as a biomarker for the adipogenic differentiation of adipose-derived stem cells in the postoperative fat transplantation of breast cancer.

Background: Adipose-derived stem cells (ADSCs) are closely associated with the survival rate of transplanted fat in breast reconstruction after breast cancer surgery. Nevertheless, the intrinsic mechanisms regulating ADSCs adipogenic differentiation remain ambiguous. The aim of our study was to explore the relevant genes and pathways to elucidate the potential mechanisms of adipogenic differentiation in ADSCs. Methods: The Gene Expression Omnibus (GEO) dataset GSE61302 was downloaded and analyzed to identify differentially expressed genes (DEGs). Key genes and signaling pathways were obtained through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional and enrichment analysis. Protein-protein interaction (PPI) network and hub gene analyses were performed with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape software. Finally, the transcription levels of hub genes in the adipogenic differentiated group and undifferentiated group of ADSCs were compared via real-time quantitative polymerase chain reaction (RT-qPCR). Results: In total, 1,091 DEGs were identified through bioinformatics analysis of the adipogenic differentiated group and undifferentiated group. If was then found that the 10 downregulated key genes, CCNB1, NUSAP1, DLGAP5, TTK, CCNB2, KIF23, BUB1B, CDC20, CDCA8, and KIF11 may play important roles in the adipogenic differentiation of ADSCs. Subsequent in vitro experimental verification also revealed that the messenger RNA (mRNA) expression levels of cyclin B1 in adipogenic differentiated cells and undifferentiated cells were significantly different at the early stage (P<0.05), but there was no significant difference at the late stage (P>0.05). Conclusions: As a key gene, CCNB1 might be a potential biomarker in the adipogenic differentiation of ADSCs at the early stage.

A novel CSN5/CRT O-GlcNAc/ER stress regulatory axis in platinum resistance of epithelial ovarian cancer.

Background: High levels of COP9 signalosome subunit 5 (CSN5) in epithelial ovarian cancer (EOC) are associated with poor prognosis and are implicated in mediating platinum resistance in EOC cells. The underlying mechanisms, however, remained undefined. This study aimed to elucidate the molecular process and identify potential therapeutic targets. Methods: RNA-sequencing was used to investigate differentially expressed genes between platinum-resistant EOC cells with CSN5 knockdown and controls. O-GlcNAc proteomics were employed to identify critical modulators downstream of CSN5. The omics findings were confirmed through qRT-PCR and immunoblotting. In vitro and in vivo experiments assessed the sensitivity of resistant EOCs to platinum. Results: We demonstrated an involvement of aberrant O-GlcNAc and endoplasmic reticulum (ER) stress disequilibrium in CSN5-mediated platinum resistance of EOC. Genetic or pharmacologic inhibition of CSN5 led to tumor regression and surmounted the intrinsic EOC resistance to platinum both in vitro and in vivo. Integration of RNA-sequencing and O-GlcNAc proteomics pinpointed calreticulin (CRT) as a potential target of aberrant O-GlcNAc modification. CSN5 upregulated O-GlcNAc-CRT at T346 to inhibit ER stress-induced cell death. Blocking T346 O-GlcNAc-CRT through CSN5 deficiency or T346A mutation resulted in Ca2+ disturbances, followed by ER stress overactivation, mitochondrial dysfunction, and ultimately cell apoptosis. Conclusion: This study reveals that CSN5-mediated aberrant O-GlcNAc-CRT acts as a crucial ER stress checkpoint, governing cell fate response to stress, and emphasizes an unrecognized role for the CSN5/CRT O-GlcNAc/ER stress axis in platinum resistance of EOC.

A novel clinical nomogram for predicting cancer-specific survival in patients with non-serous epithelial ovarian cancer: A real-world analysis based on the Surveillance, Epidemiology, and End Results database and external validation in a tertiary center.

BACKGROUND: Currently, there is a lack of prognostic evaluation methods for non-serous epithelial ovarian cancer (EOC). METHOD: We collected patients with non-serous EOC diagnosed between 2010 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database into a training cohort (n = 2078) and an internal validation cohort (n = 891). Meanwhile, patients meeting the criteria were screened from the Fujian Provincial Maternal and Child Health Hospital from 2013 to 2022 as an external validation cohort (n = 56). Univariate and multivariable logistic regression were used to determine the independent prognostic factors of cancer-specific survival (CSS) to construct the nomogram. The nomogram was validated by the concordance index (C-index), receiver operating characteristics (ROC) curve and calibration curves. RESULT: Age, laterality, preoperative CA125 status, histologic type, tumor grade, AJCC stage, surgery lesion, number of lymph nodes examined, residual lesion size, and bone metastasis were identified as independent prognostic factors to construct the nomogram. The nomogram showed better predictive ability than FIGO stage through internal and external cohorts validation. The C-index of the nomogram in the training cohort, validation cohort, and external validation cohort were 0.831, 0.835 and 0.944 higher than those of the Federation International of Gynecology and Obstetric (FIGO) stage, P<0.05. The Area Under Curve (AUC) values results indicated great clinical usefulness of the nomogram. The calibration curve indicated good agreement between the nomogram prediction and actual survival. CONCLUSION: We developed a nomogram with high predictive accuracy to predict survival in patients with non-serous EOC.