Maternal immune activation induces sex-dependent behavioral differences in a rat model of schizophrenia.

Background: Maternal immune activation (MIA) is a mature means to construct a schizophrenia model. However, some preclinical studies have reported that a MIA-induced schizophrenia model seemed to have gender heterogeneity in behavioral phenotype. On the other hand, the MIA's paradigms were diverse in different studies, and many details could affect the effect of MIA. To some extent, it is not credible and scientific to directly compare the gender differences of different MIA programs. Therefore, it is necessary to study whether the sex of the exposed offspring leads to behavioral differences on the premise of maintaining a consistent MIA mode. Methods: An animal model of schizophrenia was established by the administration of 10 mg/kg Poly (I: C) when dams were on day 9 of gestation. Then, a number of female and male offspring completed a series of behavioral tests during postnatal days 61-75. Results: Compared with the female control group (n = 14), female MIA offspring (n = 12) showed a longer movement distance (d = 1.07, p < 0.05) and higher average speed (d = 1.08, p < 0.05) in the open field test (OFT). In the Y maze test, the percentage of entering the novel arm of female MIA offspring was lower (d = 0.92, p < 0.05). Compared with the male control group (n = 14), male MIA offspring (n = 13) displayed less movement distance (d = 0.93, p < 0.05) and a lower average speed (d = 0.94, p < 0.05) in the OFT. In the Y maze test, the proportion of exploration time in the novel arm of male MIA offspring was lower (d = 0.96, p < 0.05). In the EPM, male MIA offspring showed less time (d = 0.85, p < 0.05) and a lower percentage of time spent in the open arms (d = 0.85, p < 0.05). Male MIA offspring also had a lower PPI index (76 dB + 120 dB, d = 0.81, p < 0.05; 80 dB + 120 dB, d = 1.45, p < 0.01). Conclusions: Our results showed that the behavioral phenotypes induced by prenatal immune activation were highly dependent on the sex of the offspring.

Highly Active and Sintering-Resistant Pt Clusters Supported on FeOx-Hydroxyapatite Achieved by Tailoring Strong Metal-Support Interactions.

The catalytic performance of supported metal catalysts is closely related to their structure. While Pt-based catalysts are widely used in many catalytic reactions because of their exceptional intrinsic activity, they tend to deactivate in high-temperature reactions, requiring a tedious and expensive regeneration process. The strong metal-support interaction (SMSI) is a promising strategy to improve the stability of supported metal nanoparticles, but often at the price of the activity due to either the coverage of the active sites by support overlay and/or the too-strong metal-support bonding. Herein, we newly constructed a supported Pt cluster catalyst by introducing FeOx into hydroxyapatite (HAP) support to fine-tune the SMSIs. The catalyst exhibited not only high catalytic activity but also sintering resistance, without deactivation in a 100 h test for catalytic CO oxidation. Detailed characterizations reveal that FeOx introduced into HAP weaken the strong covalent metal-support interaction (CMSI) between Pt and FeOx while simultaneously inhibiting the oxidative strong metal-support interaction (OMSI) between Pt and HAP, giving rise to both high activity and thermal stability of the supported Pt clusters.

Effect of the AADE7 Self-Care Behaviors Framework on Diabetes Education Management in a Shared Care Model.

Background: Diabetes self-management education (DSME) provides diabetic patients with knowledge of diabetes, requires attention and recording of dietary habits, and increases the frequency and accuracy of blood glucose monitoring. DSME also achieves better blood glucose control, thus benefiting diabetic patients and reducing the risk of diabetes complications. However, few studies have systematically examined whether DSME follows AADE 7 Self-Care Behaviors (AADE7™). Therefore, this study aimed to investigate the control effect of AADE7™-based management on laboratory test indicators of diabetic patients. Methods: The patients with diabetes who received shared care management in our hospital between June 2014 and April 2022 were analyzed retrospectively. According to the process of outpatient consultation, each patient received health education provided by diabetes education nurses and dietitians after consultation. Health education was a process from assessment to health guidance. The basic information of all patients was recorded, and AADE7™ behavior assessment and health education session were conducted through interviews. A total of 13,650 were given shared care management, requiring more than 6 follow-up visits per year, as well as health education. It was reassessed annually according to AADE standards. The impact of the patients' behavior change after the AADE7™-based management on the relevant test indicators was observed. Results: After eight years of intervention, a total of 8319 samples were obtained after excluding the outliers. Stepwise regression analysis was performed, and the results showed that, with other conditions held constant, a greater number of days per week to follow a healthy diet, to take hypoglycemic medication as prescribed, to monitor blood glucose, and to exercise and higher education level were associated with lower levels of glycosylated hemoglobin. The change from drinking to nondrinking was associated with lower triglycerides. If low blood glucose was monitored, patients who reviewed and took immediate action showed lower levels of low-density lipoprotein, urine microalbumin, and urine microalbumin/creatinine ratio compared with those without review and immediate action. Significance tests for each term showed P value <0.05. Conclusions: The AADE7™ framework is a tool supporting patient-centered self-management and education. In the AADE7™ standards, successful self-management is considered as a key outcome in the care of patients with diabetes and related diseases. This tool can effectively improve patient compliance and increase the rate of blood glucose compliance rates in patients with diabetes and therefore is worthy of clinical promotion.

First-Line Anlotinib Treatment for Soft Tissue Sarcoma in Chemotherapy-Ineligible Patients: An Open-label, Single-arm, Phase 2 Clinical Trial.

PURPOSE: Standard treatment for patients with unresectable locally advanced or metastatic soft-tissue sarcoma (LA/M STS) is chemotherapy based on anthracyclines, but patient tolerance of chemotherapy is limited. The present trial (NCT03792542) investigated the use of anlotinib as first-line treatment for patients with advanced STS, in particular liposarcoma (LPS). PATIENTS AND METHODS: Eligible patients were previously untreated, pathologically confirmed, unresectable LA/M STS cases. Anlotinib was given orally at a dose of 12 mg once daily from day 1 to day 14 every 3 weeks until disease progression or intolerable adverse events (AEs) occurred. The primary endpoint was progression-free survival (PFS) and the secondary endpoints overall survival (OS), the objective response rate and the disease control rate (DCR). The safety profile was also evaluated. RESULTS: Forty patients were enrolled from April 2019 to Jun 2022 and are included in the intention-to-treat analysis. The median PFS was 6.83 months [95% confidence interval (CI): 4.17-8.71] and the median OS 27.40 months (95% CI: 16.43-not evaluable); 1 patient reached partial response and 26 attained stable disease, with a DCR of 67.5% (27/40). Median PFS and OS times for LPS patients were 8.71 and 16.23 months, respectively. Ten (25.0%) patients had treatment-related AEs ≥ grade 3, with in particular a higher incidence of hypertension (15.0%) and proteinuria (7.5%). CONCLUSIONS: The findings suggest a potential benefit in employing front-line anlotinib to treat patients with STS, who are not eligible for cytotoxic chemotherapy. Of note, the clinical outcomes for the LPS subgroup of patients were encouraging.

Targeting DNMT3A-mediated oxidative phosphorylation to overcome ibrutinib resistance in mantle cell lymphoma.

The use of Bruton tyrosine kinase (BTK) inhibitors such as ibrutinib achieves a remarkable clinical response in mantle cell lymphoma (MCL). Acquired drug resistance, however, is significant and affects long-term survival of MCL patients. Here, we demonstrate that DNA methyltransferase 3A (DNMT3A) is involved in ibrutinib resistance. We find that DNMT3A expression is upregulated upon ibrutinib treatment in ibrutinib-resistant MCL cells. Genetic and pharmacological analyses reveal that DNMT3A mediates ibrutinib resistance independent of its DNA-methylation function. Mechanistically, DNMT3A induces the expression of MYC target genes through interaction with the transcription factors MEF2B and MYC, thus mediating metabolic reprogramming to oxidative phosphorylation (OXPHOS). Targeting DNMT3A with low-dose decitabine inhibits the growth of ibrutinib-resistant lymphoma cells both in vitro and in a patient-derived xenograft mouse model. These findings suggest that targeting DNMT3A-mediated metabolic reprogramming to OXPHOS with decitabine provides a potential therapeutic strategy to overcome ibrutinib resistance in relapsed/refractory MCL.

Independent Validation of the BRENDA-Score Breast Cancer Prognosis Prediction Tool In Chinese Patients.

BACKGROUND: The BRENDA-Score was developed and used to predict the prognosis of patients with breast cancer (BC). This study was performed to validate the use of this tool in Chinese patients with primary invasive BC patients. METHODS: Patients underwent surgery for BC from January 2009 to December 2016. Discrimination was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Calibrations were assessed by comparing predicted and observed 5-year and 10-year metastasis-free survival (MFS) in the overall cohort and patient subgroups. RESULTS: A total of 2029 BC patients were enrolled. Kaplan-Meier analysis revealed significant differences in MFS risk groups (log-rank test P < .01). ROC analysis showed good accuracy for 5-year MFS (AUC 0.779) and fair accuracy for 10-year MFS (AUC 0.728). The BRENDA-Score accurately predicted 5-year and 10-year MFS in the entire cohort and in all other predefined subgroups, except for the 5-year MFS in the subgroup aged<40 years, which was overestimated (differences between the predicted and observed MFS were 6.7%, P < .05). The 5-year MFS rates of ER- positive and ER-negative patients were 90.9% and 80.6%, respectively (P < .05). The 10-year MFS rates of ER-positive and ER-negative patients were 78.0% and 73.7%, respectively (P = .25). CONCLUSIONS: The BRENDA-Score accurately predicted 5-year and 10-year MFS. The results showed good validity, transportability, and potential clinical value. However, the results for 5-years MFS should be interpreted carefully in patients aged <40 years. After 10 years the value of the ER as a prognostic factor was less important.

A lightweight CNN for multi-source infrared ship detection from unmanned marine vehicles.

Infrared ship detection is of great significance due to its broad applicability in maritime surveillance, traffic safety and security. Multiple infrared sensors with different spectral sensitivity provide enhanced sensing capabilities, facilitating ship detection in complex environments. Nevertheless, current researches lack discussion and exploration of infrared imagers in different spectral ranges for marine objects detection. Furthermore, for unmanned marine vehicles (UMVs), e.g., unmanned surface vehicles (USVs) and unmanned ship (USs), detection and perception are usually performed in embedded devices with limited memory and computation resource, which makes traditional convolutional neural network (CNN)-based detection methods struggle to leverage their advantages. Aimed at the task of sea surface object detection on USVs, this paper provides lightweight CNNs with high inference speed that can be deployed on embedded devices. It also discusses the advantages and disadvantages of using different sensors in marine object detection, providing a reference for the perception and decision-making modules of USVs. The proposed method can detect ships in short-wave infrared (SWIR), long-wave infrared (LWIR) and fused images with high-performance and high-inference speed on an embedded device. Specifically, the backbone is built from bottleneck depth-separable convolution with residuals. Generating redundant feature maps by using cheap linear operation in neck and head networks. The learning and representation capacities of the network are promoted by introducing the channel and spatial attention, redesigning the sizes of anchor boxes. Comparative experiments are conducted on the infrared ship dataset that we have released which contains SWIR, LWIR and the fused images. The results indicate that the proposed method can achieve high accuracy but with fewer parameters, and the inference speed is nearly 60 frames per second (FPS) on an embedded device.

Modification effects of long-term air pollution levels on the relationship between short-term exposure to meteorological factors and hand, foot, and mouth disease: A distributed lag non-linear model-based study in Shandong Province, China.

The occurrence of hand, foot, and mouth disease (HFMD) is closely related to meteorological factors. However, location-specific characteristics, such as persistent air pollution, may increase the complexity of the impact of meteorological factors on HFMD, and studies across different areas and populations are largely lacking. In this study, a two-stage multisite time-series analysis was conducted using data from 16 cities in Shandong Province from 2015 to 2019. In the first stage, we obtained the cumulative exposure-response curves of meteorological factors and the number of HFMD cases for each city. In the second stage, we merged the estimations from the first stage and included city-specific air pollution variables to identify significant effect modifiers and how they modified the short-term relationship between HFMD and meteorological factors. High concentrations of air pollutants may reduce the risk effects of high average temperature on HFMD and lead to a distinct peak in the cumulative exposure-response curve, while lower concentrations may increase the risk effects of high relative humidity. Furthermore, the effects of average wind speed on HFMD were different at different levels of air pollution. The differences in modification effects between subgroups were mainly manifested in the diversity and quantity of significant modifiers. The modification effects of long-term air pollution levels on the relationship between sunshine hours and HFMD may vary significantly depending on geographical location. The people in age＜3 and male groups were more susceptible to long-term air pollution. These findings contribute to a deepening understanding of the relationship between meteorological factors and HFMD and provide evidence for relevant public health decision-making.

Preparation of ß-galacto-oligosaccharides using a novel endo-1,4-ß-galactanase from Penicillium oxalicum.

Endo-1,4-ß-galactanase is an indispensable tool for preparing prebiotic ß-galacto-oligosaccharides (ß-GOS) from pectic galactan resources. In the present study, a novel endo-1,4-ß-galactanase (PoßGal53) belonging to glycoside hydrolase family 53 from Penicillium oxalicum sp. 68 was cloned and expressed in Pichia pastoris GS115. Upon purification by affinity chromatography, recombinant PoßGal53 exhibited a single band on SDS-PAGE with a molecular weight of 45.0 kDa. Using potato galactan as substrate, PoßGal53 showed optimal reaction conditions of pH 4.0, 40 °C, and was thermostable, retaining >80 % activity after incubating below 45 °C for 12 h. Significantly, PoßGal53 exhibited relatively conserved substrate specificity for (1 â†’ 4)-ß-D-galactan with an activity of 6244 ± 282 U/mg. In this regard, the enzyme is in effect the most efficient endo-1,4-ß-galactanase identified to date. By using PoßGal53, ß-GOS monomers were prepared from potato galactan and separated using medium pressure liquid chromatography. HPAEC-PAD, MALDI-TOF-MS and ESI-MS/MS analyses demonstrated that these ß-GOS species ranged from 1,4-ß-D-galactobiose to 1,4-ß-D-galactooctaose (DP 2-8) with high purity. This work provides not only a highly active tool for enzymatic degradation of pectic galactan, but an efficient protocol for preparing ß-GOS.

Perovskite Oxide as A New Platform for Efficient Electrocatalytic Nitrogen Oxidation.

Electrocatalytic nitrogen oxidation reaction (NOR) offers an efficient and sustainable approach for conversion of widespread nitrogen (N2 ) into high-value-added nitrate (NO3 - ) under mild conditions, representing a promising alternative to the traditional approach that involves harsh Haber-Bosch and Ostwald oxidation processes. Unfortunately, due to the weak absorption/activation of N2 and the competitive oxygen evolution reaction, the kinetics of NOR process is extremely sluggish accompanied with low Faradaic efficiencies and NO3 - yield rates. In this work, an oxygen-vacancy-enriched perovskite oxide with nonstoichiometric ratio of strontium and ruthenium (denoted as Sr0.9 RuO3 ) was synthesized and explored as NOR electrocatalyst, which can exhibit a high Faradaic efficiency (38.6 %) with a high NO3 - yield rate (17.9 µmol mg-1 h-1 ). The experimental results show that the amount of oxygen vacancies in Sr0.9 RuO3 is greatly higher than that of SrRuO3 , following the same trend as their NOR performance. Theoretical simulations unravel that the presence of oxygen vacancies in the Sr0.9 RuO3 can render a decreased thermodynamic barrier toward the oxidation of *N2 to *N2 OH at the rate-determining step, leading to its enhanced NOR performance.

Dynamical graph neural network with attention mechanism for epilepsy detection using single channel EEG.

Epilepsy is a chronic brain disease, and identifying seizures based on electroencephalogram (EEG) signals would be conducive to implement interventions to help patients reduce impairment and improve quality of life. In this paper, we propose a classification algorithm to apply dynamical graph neural network with attention mechanism to single channel EEG signals. Empirical mode decomposition (EMD) are adopted to construct graphs and the optimal adjacency matrix is obtained by model optimization. A multilayer dynamic graph neural network with attention mechanism is proposed to learn more discriminative graph features. The MLP-pooling structure is proposed to fuse graph features. We performed 12 classification tasks on the epileptic EEG database of the University of Bonn, and experimental results showed that using 25 runs of ten-fold cross-validation produced the best classification results with an average of 99.83[Formula: see text] accuracy, 99.91[Formula: see text] specificity, 99.78[Formula: see text] sensitivity, 99.87[Formula: see text] precision, and 99.47[Formula: see text] [Formula: see text] score for the 12 classification tasks.

Morphologically transformable peptide nanocarriers coloaded with doxorubicin and curcumin inhibit the growth and metastasis of hepatocellular carcinoma.

In tumor treatment, the highly disordered vascular system and lack of accumulation of chemotherapeutic drugs in tumors severely limit the therapeutic role of nanocarriers. Smaller drug-containing nanoparticles (NPs) can better penetrate the tumor but are easily removed, which severely limits the tumor-killing properties of the drug. The chemotherapeutic medication doxorubicin (DOX) is highly toxic to the heart, but this toxicity can be effectively mitigated and the combined anticancer effect can be enhanced by clinically incorporating curcumin (CUR) as part of the dual therapy. We designed a small-molecule peptide, Pep1, containing a targeting peptide (CREKA) and a pH-responsive moiety. These NPs can target the blood vessels in tumor microthrombi and undergo a morphological shift in the tumor microenvironment. This process enhances the penetration and accumulation of drugs, ultimately improving the effectiveness of cancer treatment. In vitro and in vivo experiments demonstrated that this morphological transformation allowed rapid and effective drug release into tumors, the effective inhibition of tumor angiogenesis, and the promotion of tumor cell apoptosis, thus effectively killing tumor cells. Our findings provide a novel and simple approach to nhibit the growth and metastasis of hepatocellular carcinoma.

A pan-cancer analysis of the MAPK family gene and their association with prognosis, tumor microenvironment, and therapeutic targets.

The mitogen-activated protein kinases family of genes plays a crucial role in a wide range of inflammatory responses in the human body. The MAPK family of genes includes ERK, ERK5, JNK, P-38 mitogen-activated protein kinases. However, the correlation between MAPK family gene expression and pan-cancer prognosis, as well as the tumor microenvironment, has not been extensively studied. This study integrated multiple bioinformatics analysis methods to assess the expression and prognostic value of MAPK family genes, as well as their relationship with tumor microenvironment in patients with pan-cancer. The results showed that ERK, JNK, and P-38 MAPK expression were found to be significantly upregulated in rectum adenocarcinoma (READ), colon adenocarcinoma/rectum adenocarcinoma esophageal carcinoma (COADREAD), and kidney renal clear cell carcinoma (KIRC), and significantly downregulated in acute myeloid leukemia. And the results revealed good prognostic results for ERK, JNK, and P-38 MAPK in READ, COADREAD, and KIRC. We observed significant positive correlation between MAPK family gene expression and immune scores especially dendritic cells in READ, COADREAD, and KIRC. And we observed that the expression levels of MAPK family genes were significantly correlated with the expression of immune-related genes, such as CXCL1, CXCL2, CXCL8, CXCR1, CXCR2, CTLA-4, CD80, CD86, and CD28, suggesting their important role in regulating immune infiltrates and tumor progression. Therefore, our study suggested that MAPK family gene plays an important role in regulating immune infiltrates and tumor progression.

Artificial intelligence versus radiologist in the accuracy of fracture detection based on computed tomography images: a multi-dimensional, multi-region analysis.

Background: Extremities fractures are a leading cause of death and disability, especially in the elderly. Avulsion fracture are also the most commonly missed diagnosis, and delayed diagnosis leads to higher litigation rates. Therefore, this study evaluates the diagnostic efficiency of the artificial intelligence (AI) model before and after optimization based on computed tomography (CT) images and then compares it with that of radiologists, especially for avulsion fractures. Methods: The digital X-ray photography [digital radiography (DR)] and CT images of adult limb trauma in our hospital from 2017 to 2020 were retrospectively collected, with or without 1 or more fractures of the shoulder, elbow, wrist, hand, hip, knee, ankle, and foot. Labeling of the fracture referred to the visualization of the fracture on the corresponding CT images. After training the pre-optimized AI model, the diagnostic performance of the pre-optimized AI, optimized AI model, and the initial radiological reports were evaluated. For the lesion level, the detection rate of avulsion and non-avulsion fractures was analyzed, whereas for the case level, the accuracy, sensitivity, and specificity were compared among them. Results: The total datasets (1,035 cases) were divided into a training set (n=675), a validation set (n=169), and a test set (n=191) in a balanced joint distribution. At the lesion level, the detection rates of avulsion fracture (57.89% vs. 35.09%, P=0.004) and non-avulsion fracture (85.64% vs. 71.29%, P<0.001) by the optimized AI were significantly higher than that by pre-optimized AI. The average precision (AP) of the optimized AI model for all lesions was higher than that of pre-optimized AI model (0.582 vs. 0.425). The detection rate of avulsion fracture by the optimized AI model was significantly higher than that by radiologists (57.89% vs. 29.82%, P=0.002). For the non-avulsion fracture, there was no significant difference of detection rate between the optimized AI model and radiologists (P=0.853). At the case level, the accuracy (86.40% vs. 71.93%, P<0.001) and sensitivity (87.29% vs. 73.48%, P<0.001) of the optimized AI were significantly higher than those of the pre-optimized AI model. There was no statistical difference in accuracy, sensitivity, and specificity between the optimized AI model and the radiologists (P>0.05). Conclusions: The optimized AI model improves the diagnostic efficacy in detecting extremity fractures on radiographs, and the optimized AI model is significantly better than radiologists in detecting avulsion fractures, which may be helpful in the clinical practice of orthopedic emergency.

Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma.

BACKGROUND: Gallbladder carcinoma (GBC) is a highly malignant tumor with a poor overall prognosis. This study aimed to identify the characteristic microRNAs (miRNAs) of GBC and the competing endogenous RNA (ceRNA) regulatory mechanisms. METHODS: The microarray data of GBC tissue samples and normal gallbladder (NGB) tissue samples from the Gene Expression Omnibus (GEO) database was downloaded. GBC-related differentially expressed miRNAs (DE-miRNAs) were identified by inter-group differential expression analysis and weighted gene co-expression network analysis (WGCNA). Machine learning algorithms were used to screen the characteristic miRNA based on the intersect between least absolute shrinkage and selection operator (LASSO) and Support vector machine-recursive feature elimination (SVM-RFE). Based on the differential expression analysis of GEO database, the ceRNA network of characteristic miRNA was predicted and constructed. The biological functions of the ceRNA network were revealed by carrying out the gene enrichment analysis was implemented. We further screened the key genes of ceRNA network and constructed a protein-protein interaction (PPI) network, and predicted and generated the transcription factors (TFs) network of signature miRNAs. The expression of characteristic miRNA in clinical samples was verified by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: A total of 131 GBC-related DE-miRNAs were obtained. The hsa-miR-4770 was defined as characteristic miRNA for GBC. The ceRNA network containing 211 mRNAs, one miRNA, two lncRNAs, and 48 circRNAs was created. Gene enrichment analysis suggested that the downstream genes were mainly involved in actin filament organization, cell-substrate adhesion, cell-matrix adhesion, reactive oxygen species metabolic process, glutamine metabolic process and extracellular matrix (ECM)-receptor interaction pathway. 10 key genes in the network were found to be most correlated with disease, and involved in cell cycle-related processes, p53, and extrinsic apoptotic signaling pathways. The qRT-PCR result demonstrated that hsa-miR-4770 is down-regulated in GBC, and the expression trend is consistent with the public database. CONCLUSIONS: We identified hsa-miR-4770 as the characteristic miRNA for GBC. The ceRNA network of hsa-miR-4770 may play key roles in GBC. This study provided some basis for potential pathogenesis of GBC.

An Online Structured Diabetes Self-Management Education and Support Programme Improves Glycaemic Control in Young Adults with Type 1 Diabetes.

Objective: We explore the effect of a structured online DSMES program on glycaemic control and the self-management behaviour of adolescents and young adults with T1DM. Methods: We used a pre-post uncontrolled intervention design over a period of 6 months. A total of 37 youths with T1DM aged 10-45 years were enrolled. The intervention comprised 11 structured online DSMES course sessions; these were video-based and delivered by a diabetes specialist, nurses and a dietitian. The primary outcome was a change in (glycated hemoglobin) HbA1c. The secondary outcomes were changes in hypoglycaemia frequency, time in target range (TIR) among patients using a continuous glucose monitoring (CGM) system and self-management behaviour; the latter was measured using a T1DM self-management scale for Chinese adults (SMOD-CA) and the Chinese version of the diabetic behaviour rating scale in adolescents with T1DM (DBRS). Results: Twenty-three (85.2%) participants attended ≥8 of the online sessions. There was a significant reduction in HbA1c (from 6.92% to 6.47%, P = 0.002), hypoglycaemic episodes (from 6.0 to 4.0 during the preceding month, P = 0.026) and a significant increase in TIR (from 74.0% to 80.5%, P = 0.027) and an increase in the SMOD-CA score (from 79.6 to 84.6, P = 0.026) in young adults. No significant change in glucose control, hypoglycaemic events or DBRS score were found among children and adolescents. The score of the 12-item version of the Barrett-Lennard Relationship Inventory (B-L RI:mini) indicated that more than half of the participants experienced congruence, positive regard, and an empathic understanding in this programme. Conclusion: The online structured DSMES programme was effective in improving the glycaemic control and self-management behaviour of young adults with T1DM; however, integrating offline visits or appointments with online consultations may be necessary for youth patients.

EGR1-mediated metabolic reprogramming to oxidative phosphorylation contributes to ibrutinib resistance in B-cell lymphoma.

The use of Bruton tyrosine kinase inhibitors, such as ibrutinib, to block B-cell receptor signaling has achieved a remarkable clinical response in several B-cell malignancies, including mantle cell lymphoma (MCL) and diffuse large B-cell lymphoma (DLBCL). Acquired drug resistance, however, is significant and affects the long-term survival of these patients. Here, we demonstrate that the transcription factor early growth response gene 1 (EGR1) is involved in ibrutinib resistance. We found that EGR1 expression is elevated in ibrutinib-resistant activated B-cell-like subtype DLBCL and MCL cells and can be further upregulated upon ibrutinib treatment. Genetic and pharmacological analyses revealed that overexpressed EGR1 mediates ibrutinib resistance. Mechanistically, TCF4 and EGR1 self-regulation induce EGR1 overexpression that mediates metabolic reprogramming to oxidative phosphorylation (OXPHOS) through the transcriptional activation of PDP1, a phosphatase that dephosphorylates and activates the E1 component of the large pyruvate dehydrogenase complex. Therefore, EGR1-mediated PDP1 activation increases intracellular adenosine triphosphate production, leading to sufficient energy to enhance the proliferation and survival of ibrutinib-resistant lymphoma cells. Finally, we demonstrate that targeting OXPHOS with metformin or IM156, a newly developed OXPHOS inhibitor, inhibits the growth of ibrutinib-resistant lymphoma cells both in vitro and in a patient-derived xenograft mouse model. These findings suggest that targeting EGR1-mediated metabolic reprogramming to OXPHOS with metformin or IM156 provides a potential therapeutic strategy to overcome ibrutinib resistance in relapsed/refractory DLBCL or MCL.

High Valence State Sites as Favorable Reductive Centers for High-Current-Density Water Splitting.

Electrochemical water splitting is a promising approach for producing sustainable and clean hydrogen. Typically, high valence state sites are favorable for oxidation evolution reaction (OER), while low valence states can facilitate hydrogen evolution reaction (HER). However, here we proposed a high valence state of Co3+ in Ni9.5 Co0.5 -S-FeOx hybrid as the favorable center for efficient and stable HER, while structural analogues with low chemical states showed much worse performance. As a result, the Ni9.5 Co0.5 -S-FeOx catalyst could drive alkaline HER with an ultra-low overpotential of 22 mV for 10 mA cm-2 , and 175 mV for 1000 mA cm-2 at the industrial temperature of 60 °C, with an excellent stability over 300 h. Moreover, this material could work for both OER and HER, with a low cell voltage being 1.730 V to achieve 1000 mA cm-2 for overall water splitting at 60 °C. X-ray absorption spectroscopy (XAS) clearly identified the high valence Co3+ sites, while in situ XAS during HER and theoretical calculations revealed the favorable electron capture at Co3+ and suitable H adsorption/desorption energy around Co3+ , which could accelerate the HER. The understanding of high valence states to drive reductive reactions may pave the way for the rational design of energy-related catalysts.

Sterol Regulatory Element-Binding Protein, BbSre1, Controls Oxidative Stress Response, Peroxisome Division, and Lipid Homeostasis in an Insect Fungal Pathogen.

Sterol regulatory element-binding protein, Sre1, regulates sterol biosynthesis, lipid metabolism, hypoxia adaptation, and virulence in some fungi, even though its roles are varied in fungal species. However, few studies report its other functions in fungi. Here, we report novel roles of Sre1 homolog, BbSre1, in the insect fungal pathogen, Beauveria bassiana, that regulates oxidative stress response, peroxisome division, and redox homeostasis. The gene disruption stain showed increased sensitivity to oxidative stress, which was in line with oxidative stress-induced-BbSre1 nuclear import and control of antioxidant and detoxification-involved genes. The gene mutation also inhibited peroxisome division, affected redox homeostasis, and impaired lipid/fatty acid metabolism and sterol biosynthesis, which was verified by downregulation of their associated genes. These data broaden our understanding of role of Sre1, which regulates peroxisome division, antioxidant, and detoxification-involved genes for control of redox homeostasis and oxidative stress response that links to lipid/fatty acid metabolism and sterol biosynthesis.