Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students.

ChatGPT (OpenAI), a cutting-edge natural language processing model, holds immense promise for revolutionizing medical education. With its remarkable performance in language-related tasks, ChatGPT offers personalized and efficient learning experiences for medical students and doctors. Through training, it enhances clinical reasoning and decision-making skills, leading to improved case analysis and diagnosis. The model facilitates simulated dialogues, intelligent tutoring, and automated question-answering, enabling the practical application of medical knowledge. However, integrating ChatGPT into medical education raises ethical and legal concerns. Safeguarding patient data and adhering to data protection regulations are critical. Transparent communication with students, physicians, and patients is essential to ensure their understanding of the technology's purpose and implications, as well as the potential risks and benefits. Maintaining a balance between personalized learning and face-to-face interactions is crucial to avoid hindering critical thinking and communication skills. Despite challenges, ChatGPT offers transformative opportunities. Integrating it with problem-based learning, team-based learning, and case-based learning methodologies can further enhance medical education. With proper regulation and supervision, ChatGPT can contribute to a well-rounded learning environment, nurturing skilled and knowledgeable medical professionals ready to tackle health care challenges. By emphasizing ethical considerations and human-centric approaches, ChatGPT's potential can be fully harnessed in medical education, benefiting both students and patients alike.

Tubulin alpha-1b chain was identified as a prognosis and immune biomarker in pan-cancer combing with experimental validation in breast cancer.

The α-tubulin subtype, Tubulin α-1b chain (TUBA1B), has been shown to influence immune cell infiltration, cancer growth, and survival across various malignancies. However, a comprehensive study has not yet been undertaken examining the immunological and predictive effects of TUBA1B in a pan-carcinoma context. Using data from TCGA, GEO, and other databases, we analyzed TUBA1B expression across various carcinoma types using transcriptional profiling, prognostic implications, genetic and epigenetic alterations, methylation patterns, and immunological significance. To validate our findings, we conducted Western blot analysis to assess TUBA1B protein levels in matched breast cancer tissue samples and performed CCK-8 proliferation assay, flow cytometry, transwell invasion, and migration assays to comprehensively examine the functional impact of TUBA1B on breast cancer cells. Our pan-cancer analysis found TUBA1B upregulation across most tumor types, with varying expression patterns in distinct immune and molecular subtypes. High TUBA1B expression was an independent risk factor and associated with poor prognoses in several cancers, including BRCA, KICH, LGG, LUAD, and MESO. TUBA1B also demonstrates moderate to high diagnostic accuracy in most tumor types. Increased m6A methylation levels were observed in the TUBA1B gene, while its promoter region displayed low methylation levels. TUBA1B's expression impacted some cancers by elevating tumor mutation burden, microsatellite instability, neoantigen formation, immune cell infiltration, and the modulation of immune checkpoints. Functional enrichment analysis highlights TUBA1B's involvement in important cellular processes such as the cell cycle, p53 signaling, cell senescence, programmed cell death, and the regulation of immune-related pathways. Moreover, our study reveals higher TUBA1B protein expression in breast cancer tissues compared to adjacent tissues. In vitro experiments confirm that TUBA1B deletion reduces breast cancer cell proliferation, invasion, and migration while increasing apoptosis. In conclusion, our study suggests that TUBA1B could potentially serve as a diagnostic marker for predicting cancer immunological profiles and survival outcomes and shed light on the expression and role of TUBA1B in breast cancer, providing a solid foundation for considering it as a promising therapeutic target for breast cancer patient treatment.

MiR-132-3p suppresses peritoneal fibrosis induced by peritoneal dialysis via targeting TGF-ß1/Smad2/3 signaling pathway.

BACKGROUND: Peritoneal fibrosis (PF) is the main complication of peritoneal dialysis (PD) and the most common cause of cessation from PD. There is still no effective therapeutic approach to reserve PF. We aimed to investigate the role of miR-132-3p and underlying potential mechanisms in PF. METHODS: A total of 18 Sprague-Dawley (SD) rats were divided randomly into three groups (n = 6): (i)Control group (ii)PF group (iii)PF+Losartan group; Rats in the PF group and PF+Losartan group received daily intraperitoneal injections of 3 mg/kg chlorhexidine for 14 days, and rats in the PF+Losartan group simultaneously received daily intraperitoneal injections of 2 mg/kg losartan for 14 days. The control group was injected with saline in the same volume. Met-5A cells were treated for 24h with TGF-ß1 dissolved in recombinant buffered saline at a concentration of 10 ng/ml, meanwhile, PBS solution as a negative control. The human peritoneal solution was collected for the detection of miR-132-3p. RESULTS: In vivo, SD rats were infused with chlorhexidine to establish PF model, and we found that miR-132-3p significantly decreased and the expressions of transforming growth factor-ß1 (TGF-ß1), and Smad2/3 were up-regulated in PF. In vitro, miR-132-3p mimics suppressed TGF-ß1/Smad2/3 activity, whereas miR-132-3p inhibition activated the pathway. In human peritoneal solution, we found that the expression of miR-132-3p decreased in a time-dependent model and its effect became more pronounced with longer PD duration. CONCLUSION: MiR-132-3p ameliorated PF by suppressing TGF-ß1/Smad2/3 activity, suggesting that miR-132-3p represented a potential therapeutic approach for PF.

Bioactive Layered Double Hydroxides for Synergistic Sonodynamic/Cuproptosis Anticancer Therapy with Elicitation of the Immune Response.

Sonodynamic therapy (SDT) has promising application prospects in tumor therapy. However, SDT does not eradicate metastatic tumors. Herein, Cu-substituted ZnAl ternary layered double hydroxide nanosheets (ZCA NSs) were developed as both sonosensitizers and copper nanocarriers for synergistic SDT/cuproptosis cancer therapy. An optimized electronic structure more conducive to the sonodynamic process was obtained from ZCA NSs via the Jahn-Teller effect induced by the introduction of Cu2+, and the synthesized ZCA NSs regulated the intricate tumor microenvironment (TME) by depleting endogenous glutathione (GSH) to amplify oxidative stress for further enhanced SDT performance. Furthermore, cuproptosis was evoked by intracellular overload of Cu2+ and amplified by SDT, leading to irreversible proteotoxicity. In vitro results showed that such synergetic SDT/cuproptosis triggered immunogenic cell death (ICD) and promoted the maturation of dendritic cells (DCs). Furthermore, the as-synthesized ZCA NS-mediated SDT/cuproptosis thoroughly eradicated the in vivo solid tumors and simultaneously elicited antitumor immunity to suppress lung and liver metastasis. Overall, this work established a nanoplatform for synergistic SDT/cuproptosis with a satisfactory antitumor immunity.

Refining the taxonomy of the order Hyphomicrobiales (Rhizobiales) based on whole genome comparisons of over 130 type strains.

The alphaproteobacterial order Hyphomicrobiales consists of 38 families comprising at least 152 validly published genera as of January 2024. The order Hyphomicrobiales was first described in 1957 and underwent important revisions in 2020. However, we show that several inconsistencies in the taxonomy of this order remain and we argue that there is a need for a consistent framework for defining families within the order. We propose a common genome-based framework for defining families within the order Hyphomicrobiales, suggesting that families represent monophyletic groups in core-genome phylogenies that share pairwise average amino acid identity values above ~75 % when calculated from a core set of 59 proteins. Applying this framework, we propose the formation of four new families and to reassign the genera Salaquimonas, Rhodoblastus, and Rhodoligotrophos into Salaquimonadaceae fam. nov., Rhodoblastaceae fam. nov., and Rhodoligotrophaceae fam. nov., respectively, and the genera Albibacter, Chenggangzhangella, Hansschlegelia, and Methylopila into Methylopilaceae fam. nov. We further propose to unify the families Bartonellaceae, Brucellaceae, Phyllobacteriaceae, and Notoacmeibacteraceae as Bartonellaceae; the families Segnochrobactraceae and Pseudoxanthobacteraceae as Segnochrobactraceae; the families Lichenihabitantaceae and Lichenibacteriaceae as Lichenihabitantaceae; and the families Breoghaniaceae and Stappiaceae as Stappiaceae. Lastly, we propose to reassign several genera to existing families. Specifically, we propose to reassign the genus Pseudohoeflea to the family Rhizobiaceae; the genera Oricola, Roseitalea, and Oceaniradius to the family Ahrensiaceae; the genus Limoniibacter to the emended family Bartonellaceae; the genus Faunimonas to the family Afifellaceae; and the genus Pseudochelatococcus to the family Chelatococcaceae. Our data also support the recent proposal to reassign the genus Prosthecomicrobium to the family Kaistiaceae.

Abnormal biochemical indicators of neonatal inherited metabolic disease in carriers.

BACKGROUND: Traditional biochemical screening for neonatal inherited metabolic diseases has high false-positive rates and low positive predictive values, which are not conducive to early diagnosis and increase parents' anxiety. This study analysed the relationship between gene variant carriers and their biochemical indicators in traditional biochemical screening, aiming to find explanations for false positives in newborns. RESULTS: This retrospective study included 962 newborns. Newborns underwent traditional biochemical screening at birth using blood staining and genomic sequencing of their stored blood staining using the NeoSeq Pro panel, which was able to detect 154 pathogenic genes and 86 diseases. A total of 632 newborns were carriers of gene variants. 56% of congenital hypothyroidism carriers had higher thyroid-stimulating hormone levels than normal newborns. Abnormal biochemical indices were detected in 71% of carriers of organic acid metabolic diseases, 69% of carriers of amino acid metabolic diseases, and 85% of carriers of fatty acid ß oxidation disorders. In carriers associated with organic acid metabolic diseases, the propionylcarnitine (C3), C3/acetylcarnitine (C2), and methylmalonylcarnitine (C4DC) + 3-hydroxyisovalerylcarnitine (C5OH) levels were higher than those in non-carriers (C3: 4.12 vs. 1.66 µmol/L; C3/C2: 0.15 vs. 0.09; C4DC + C5OH: 0.22 vs. 0.19 µmol/L). In carriers associated with amino acid metabolic diseases, phenylalanine levels were higher than those in non-carriers (68.00 vs. 52.05 µmol/L). For carriers of fatty acid ß oxidation disorders, butyrylcarnitine levels were higher than those in non-carriers (0.31 vs. 0.21 µmol/L), while the free carnitine levels were lower than those in non-carriers (14.65 vs. 21.87 µmol/L). There was a higher occurrence of carriers among newborns who received false-positive results for amino acid metabolic diseases compared to those who received negative results (15.52% vs. 6.71%). Similarly, there was a higher occurrence of carriers among newborns who received false-positive results for fatty acid ß oxidation disorders compared to those who received negative results (28.30% vs. 7.29%). CONCLUSIONS: This study showed that the carriers comprised a large number of newborns. Carriers had abnormal biochemical indicators compared with non-carriers, which could explain the false-positive rate for newborns using traditional newborn biochemical screening, especially in amino acid metabolic and fatty acid ß oxidation disorders.

Manganese-Doped Potassium Chloride Nanoelectrodes to Potentiate Electrochemical Immunotherapy.

Hypochlorous acid (HClO), as a powerful oxidizer, is obtained from the oxidation of Cl- ions during the electrochemical therapy (EChT) process for cancer therapy. However, the extracellular generated HClO is inadequate to inhibit effective tumor cell death. Herein, manganese-doped potassium chloride nanocubes (MPC NCs) fabricated and modified with amphipathic polymer PEG (PMPC NCs) to function as massive three-dimensional nanoelectrodes (NEs) were developed to enhance the generation of HClO for electrochemical immunotherapy under an alternating electric field. Under an square-wave alternating current (AC) electric field, the generation of HClO was boosted by PMPC NEs due to the enlarged active surface area, enhanced mass transfer rate, and improved electrocatalytic activity. Notably, PMPC NEs upregulated the intracellular HClO concentration to induce robust immunogenic cell death (ICD) under an AC electric field. Meanwhile, the electric-triggered release of Mn2+ effectively stimulated dendritic cells (DCs) maturation. In vivo results illustrated that PMPC-mediated EChT inhibited tumor growth and triggered the promotion of the immune response to regulate the tumor immune microenvironment. Based on the potent antitumor immunity, PMPC-mediated EChT was further combined with an immune checkpoint inhibitor (αCTLA-4) to realize combined EChT-immunotherapy, which demonstrated enhanced tumor inhibition of the primary tumors and an abscopal effect on distant tumors. To summarize, our work highlights the application of electrochemical-immunotherapy technology in tumor therapy.

Effects of the Glucocorticoid-Mediated Mitochondrial Translocation of Glucocorticoid Receptors on Oxidative Stress and Pyroptosis in BV-2 Microglia.

Microglia are resident macrophages within the central nervous system, serving as the first responders to neuroinflammation. Glucocorticoids (GCs) may cause damage to brain tissue, but the specific mechanism remains unclear. This study was divided into two parts: a glucocorticoid receptor (GR) mitochondrial translocation intervention experiment and a mitochondrial oxidative stress inhibition experiment. BV-2 microglia were stimulated with dexamethasone (DEX) and treated with either tubastatin-A or mitoquinone (MitoQ) for 24 h. Our results showed that DEX increased the translocation of GRs to mitochondria, and this effect was accompanied by decreases in the expression of mitochondrially encoded cytochrome c oxidase 1 (MT-CO1) and mitochondrially encoded cytochrome c oxidase 3 (MT-CO3) and increases in the expression of NOD-like receptor thermal protein domain-associated protein 3 (NLRP3), caspase-1, and Gasdermin D (GSDMD). The level of mitochondrial respiratory chain complex IV (MRCC IV) and adenosine triphosphate (ATP) was decreased. An elevation in the level of mitochondrial oxidative stress and the opening of the mitochondrial permeability transition pore (mPTP) was also observed. Mechanistically, tubastatin-A significantly suppressed the mitochondrial translocation of GRs, improved the expression of mitochondrial genes, promoted the restoration of mitochondrial function, and inhibited pyroptosis. MitoQ significantly prevented mitochondrial oxidative stress, improved mitochondrial function, and reduced apoptosis and pyroptosis. Both tubastatin-A and MitoQ suppressed DEX-induced pyroptosis. This study substantiates that the increase in the mitochondrial translocation of GRs mediated by GCs exacerbates oxidative stress and pyroptosis in microglia, which indicates that the regulation of mitochondrial pathways by GCs is pathogenic to microglia.

Transformation risk and associated survival outcome of marginal zone lymphoma: A nationwide study.

Histological transformation into an aggressive B-cell lymphoma indicates a poor survival outcome for patients with indolent marginal zone lymphoma (MZL), which has been less studied. Large-scale data with long-term follow-up to investigate MZL transformation is limited. Here, by reporting a US-Nationwide cohort of 30,619 MZL patients diagnosed between 2000 and 2019, we found that transformation occurred in 2.08% (N = 624) of MZL cases, with the transformation incidence of 3.1 per 1,000 person-years. Advanced Ann Arbor stage, nodal MZL (NMZL) and splenic MZL (SMZL) were associated with an elevated risk of transformation. Certain subtype-specific characteristics, such as non-gastric extra-nodal MZL (vs. gastric, HR, 1.51, 95%CI 1.13-2.04; p = 0.006), and receiving splenectomy for SMZL (HR, 2.04, 95%CI 1.28-3.26; p = 0.003), also indicated a higher risk of transformation. Besides, transformation independently increased the overall mortality risk (HR, 1.38, 95%CI 1.24-1.53, p < 0.001), especially the higher lymphoma-caused mortality risk (HR, 3.21, 95%CI 2.81-3.67, p < 0.001). Transformation was also associated with a higher percentage of lymphoma-caused deaths. The post-transformation prognostic analyses demonstrated that female gender and age ≥ 65 years independently affected patients' mortalities. These findings, based on the largest cohort to date, contribute to a better understanding of transformed MZL, and provide valuable reference points for guidelines and patient counseling.

Comparative genomic analysis of the Growth-Regulating Factors-Interacting Factors (GIFs) in six Salicaceae species and functional analysis of PeGIF3 reveals their regulatory role in Populus heteromorphic leaves.

BACKGROUND: The growth-regulating factor-interacting factor (GIF) gene family plays a vital role in regulating plant growth and development, particularly in controlling leaf, seed, and root meristem homeostasis. However, the regulatory mechanism of heteromorphic leaves by GIF genes in Populus euphratica as an important adaptative trait of heteromorphic leaves in response to desert environment remains unknown. RESULTS: This study aimed to identify and characterize the GIF genes in P. euphratica and other five Salicaceae species to investigate their role in regulating heteromorphic leaf development. A total of 27 GIF genes were identified and characterized across six Salicaceae species (P. euphratica, Populus pruinose, Populus deltoides, Populus trichocarpa, Salix sinopurpurea, and Salix suchowensis) at the genome-wide level. Comparative genomic analysis among these species suggested that the expansion of GIFs may be derived from the specific Salicaceae whole-genome duplication event after their divergence from Arabidopsis thaliana. Furthermore, the expression data of PeGIFs in heteromorphic leaves, combined with functional information on GIF genes in Arabidopsis, indicated the role of PeGIFs in regulating the leaf development of P. euphratica, especially PeGIFs containing several cis-acting elements associated with plant growth and development. By heterologous expression of the PeGIF3 gene in wild-type plants (Col-0) and atgif1 mutant of A. thaliana, a significant difference in leaf expansion along the medial-lateral axis, and an increased number of leaf cells, were observed between the overexpressed plants and the wild type. CONCLUSION: PeGIF3 enhances leaf cell proliferation, thereby resulting in the expansion of the central-lateral region of the leaf. The findings not only provide global insights into the evolutionary features of Salicaceae GIFs but also reveal the regulatory mechanism of PeGIF3 in heteromorphic leaves of P. euphratica.

Development and validation of a model for predicting the risk of cardiovascular events in maintenance hemodialysis patients.

The mortality rates for patients undergoing hemodialysis (HD) remain unacceptably high compared to the general population, and more specific information about the causes of death is not known. The study aimed to develop and validate a risk prediction model that uses common clinical factors to predict the probability of cardiovascular events in maintenance hemodialysis (MHD) patients. The study involved 3488 adult patients who received regular scheduled hemodialysis treatment at 20 hemodialysis centers in southwest China between June 2015 and August 2020, with follow-up until August 2021. The optimal parameter set was identified by multivariable Cox regression analyses and Cross-LASSO regression analyses and was used to establish a nomogram for predicting the risk of cardiovascular events in maintenance hemodialysis patients at 3 and 5 years. The performance of the model was evaluated using the consistency index (Harrell's C-index), the area under the receiver operating characteristic (ROC) curve, and calibration plots. The model was validated by tenfold cross-validation and bootstrapping with 1000 resamples. In the derivation cohort, the model yields an AUC of 0.764 [95% confidence interval (CI), 0.737-0.790] and 0.793 [CI, 0.757-0.829] for predicting the risk of cardiovascular events of MHD patients at 3 and 5 years. In the internal validation cohort AUC of 0.803 [95% CI, 0.756-0.849], AUC of 0.766 [95% CI, 0.686-0.846], and the external validation cohort AUC of 0.826 [95% CI, 0.765-0.888], AUC of 0.817 [95% CI, 0.745-0.889] at 3 and 5 years. The model's calibration curve is close to the ideal diagonal. By tenfold cross-validation analyses, the 3- and 5-year risk of cardiovascular events (AUC 0.732 and 0.771, respectively). By the bootstrap resampling method, the derivation cohort and validation cohort (Harrell's C-index 0.695 and 0.667, respectively) showed good uniformity with the model. The constructed model accurately predicted cardiovascular events of MHD patients in the 3rd and 5th years after dialysis. And the further research is needed to determine whether use of the risk prediction tool improves clinical outcomes.

Overexpression of ABCC1 and ABCG2 confers resistance to talazoparib, a poly (ADP-Ribose) polymerase inhibitor.

AIMS: The overexpression of ABC transporters on cancer cell membranes is one of the most common causes of multidrug resistance (MDR). This study investigates the impact of ABCC1 and ABCG2 on the resistance to talazoparib (BMN-673), a potent poly (ADP-ribose) polymerase (PARP) inhibitor, in ovarian cancer treatment. METHODS: The cell viability test was used to indicate the effect of talazoparib in different cell lines. Computational molecular docking analysis was conducted to simulate the interaction between talazoparib and ABCC1 or ABCG2. The mechanism of talazoparib resistance was investigated by constructing talazoparib-resistant subline A2780/T4 from A2780 through drug selection with gradually increasing talazoparib concentration. RESULTS: Talazoparib cytotoxicity decreased in drug-selected or gene-transfected cell lines overexpressing ABCC1 or ABCG2 but can be restored by ABCC1 or ABCG2 inhibitors. Talazoparib competitively inhibited substrate drug efflux activity of ABCC1 or ABCG2. Upregulated ABCC1 and ABCG2 protein expression on the plasma membrane of A2780/T4 cells enhances resistance to other substrate drugs, which could be overcome by the knockout of either gene. In vivo experiments confirmed the retention of drug-resistant characteristics in tumor xenograft mouse models. CONCLUSIONS: The therapeutic efficacy of talazoparib in cancer may be compromised by its susceptibility to MDR, which is attributed to its interactions with the ABCC1 or ABCG2 transporters. The overexpression of these transporters can potentially diminish the therapeutic impact of talazoparib in cancer treatment.

Diffusion Tensor and Kurtosis MRI-Based Radiomics Analysis of Kidney Injury in Type 2 Diabetes.

BACKGROUND: Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) can provide quantitative parameters that show promise for evaluation of diabetic kidney disease (DKD). The combination of radiomics with DTI and DKI may hold potential clinical value in detecting DKD. PURPOSE: To investigate radiomics models of DKI and DTI for predicting DKD in type 2 diabetes mellitus (T2DM) and evaluate their performance in automated renal parenchyma segmentation. STUDY TYPE: Prospective. POPULATION: One hundred and sixty-three T2DM patients (87 DKD; 63 females; 27-80 years), randomly divided into training cohort (N = 114) and validation cohort (N = 49). FIELD STRENGTH/SEQUENCE: 1.5-T, diffusion spectrum imaging (DSI) with 9 different b-values. ASSESSMENT: The images of DSI were processed to generate DKI and DTI parameter maps, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). The Swin UNETR model was trained with 5-fold cross-validation using 100 samples for renal parenchyma segmentation. Subsequently, radiomics features were automatically extracted from each parameter map. The performance of the radiomics models on the validation cohort was evaluated by utilizing the receiver operating characteristic (ROC) curve. STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Pearson correlation coefficient, least absolute shrinkage and selection operator (LASSO), dice similarity coefficient (DSC), decision curve analysis (DCA), area under the curve (AUC), and DeLong's test. The threshold for statistical significance was set at P < 0.05. RESULTS: The DKI_MD achieved the best segmentation performance (DSC, 0.925 ± 0.011). A combined radiomics model (DTI_FA, DTI_MD, DKI_FA, DKI_MD, and DKI_RD) showed the best performance (AUC, 0.918; 95% confidence interval [CI]: 0.820-0.991). When the threshold probability was greater than 20%, the combined model provided the greatest net benefit. Among the single parameter maps, the DTI_FA exhibited superior diagnostic performance (AUC, 887; 95% CI: 0.779-0.972). DATA CONCLUSION: The radiomics signature constructed based on DKI and DTI may be used as an accurate and non-invasive tool to identify T2DM and DKD. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Tumorous IRE1α facilitates CD8+T cells-dependent anti-tumor immunity and improves immunotherapy efficacy in melanoma.

BACKGROUND: Tumor cells frequently suffer from endoplasmic reticulum (ER) stress. Previous studies have extensively elucidated the role of tumorous unfolded protein response in melanoma cells, whereas the effect on tumor immunology and the underlying mechanism remain elusive. METHODS: Bioinformatics, biochemical assays and pre-clinical mice model were employed to demonstrate the role of tumorous inositol-requiring transmembrane kinase/endoribonuclease 1α (IRE1α) in anti-tumor immunity and the underlying mechanism. RESULTS: We firstly found that IRE1α signaling activation was positively associated with the feature of tumor-infiltrating lymphocytes. Then, pharmacological ER stress induction by HA15 exerted prominent anti-tumor effect in immunocompetent mice and was highly dependent on CD8+T cells, paralleled with the reshape of immune cells in tumor microenvironment via tumorous IRE1α-XBP1 signal. Subsequently, tumorous IRE1α facilitated the expression and secretion of multiple chemokines and cytokines via XBP1-NF-κB axis, leading to increased infiltration and anti-tumor capacity of CD8+T cells. Ultimately, pharmacological induction of tumorous ER stress by HA15 brought potentiated therapeutic effect along with anti-PD-1 antibody on melanoma in vivo. CONCLUSIONS: Tumorous IRE1α facilitates CD8+T cells-dependent anti-tumor immunity and improves immunotherapy efficacy by regulating chemokines and cytokines via XBP1-NF-κB axis. The combination of ER stress inducer and anti-PD-1 antibody could be promising for increasing the efficacy of melanoma immunotherapy.

Amorphous MnO2 Lamellae Encapsulated Covalent Triazine Polymer-Derived Multi-Heteroatoms-Doped Carbon for ORR/OER Bifunctional Electrocatalysis.

The intelligent construction of non-noble metal materials that exhibit reversible oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with bifunctional electrocatalytic performance is greatly coveted in the realm of zinc-air batteries (ZABs). Herein, a crafted structure-amorphous MnO2 lamellae encapsulated covalent triazine polymer-derived N, S, P co-doped carbon sphere (A-MnO2 /NSPC) is designed using a self-doped pyrolysis coupled with an in situ encapsulation strategy. The customized A-MnO2 /NSPC-2 demonstrates a superior bifunctional electrocatalytic performance, confirmed by a small ΔE index of 0.64 V for ORR/OER. Experimental investigations, along with density functional theory calculations validate that predesigned amorphous MnO2 surface defects and abundant heteroatom catalytic active sites collectively enhance the oxygen electrocatalytic performance. Impressively, the A-MnO2 /NSPC-based rechargeable liquid ZABs show a large open-circuit potential of 1.54 V, an ultrahigh peak power density of 181 mW cm-2 , an enormous capacity of 816 mAh g-1 , and a remarkable stability for more than 1720 discharging/charging cycles. Additionally, the assembled flexible all-solid-state ZABs also demonstrate outstanding cycle stability, surpassing 140 discharging/charging cycles. Therefore, this highly operable synthetic strategy offers substantial understanding in the development of magnificent bifunctional electrocatalysts for various sustainable energy conversions and beyond.

Civic Utilisation based on meta-ethnography willingness of government to open data Modeling of Influential factors.

[Purpose/Significance]Government open data has been in China for 10 years, however, the actual use of it has been criticised. This study analyses citizens' willingness to use government open data from their perspectives and constructs a model, aiming to promote in-depth research on citizens' use of government open data. [Methodology/Process] Meta-ethnographic qualitative research method was adopted to synthesise and integrate the 25 original studies. [Results/Conclusions] The study finally constructed a model of factors influencing citizens' willingness to use government open data, and identified four dimensions: "citizen", "platform", "government" and "environment". The four dimensions of "citizen", "platform", "government" and "environment" were identified, of which "citizen" involves "intrinsic motivation", "behavioural attitude", "information attitude" and "information security". The four dimensions of "Citizen" include "Intrinsic Motivation", "Behavioural Attitude", "Information Literacy", and "Demographic Characteristics", while the four dimensions of "Platform" include "Data Quality", "Information Literacy", and "Demographic Characteristics". platform" involves the sub-dimensions of "data quality" and "platform quality", "government" involves the sub-dimensions of "organisational conditions" and "policies and regulations", and "government" involves the sub-dimensions of "organisational conditions" and "policies and regulations". government" involves two sub-dimensions, "organisational conditions" and "policies and regulations", and "environment" involves two sub-dimensions, "social environment" and "type of context", with each sub-dimension having a different impact on the use of open government data by citizens. The different factors under each sub-dimension have different degrees of influence on citizens' use of open government data. Finally, suggestions are made to enhance citizens' willingness to use open government data.

The Underlying Structure of Preventive Behaviors and Related Factors During the COVID-19 Pandemic: A Comprehensive Network Analysis.

BACKGROUND: Various strategies against COVID-19 have been adopted in different countries, with vaccination and mask-wearing being widely used as self-preventive interventions. However, the underlying structure of these behaviors and related factors remain unclear. PURPOSE: In this study, we aimed to explore the network structure of preventive behaviors during the COVID-19 pandemic and their underlying factors, incorporating age and sex in the network. METHODS: We used a multi-center sample of 20,863 adults who were vaccinated against COVID-19 in China between April 1, 2021, and June 1, 2021. Networks were estimated using unregularized partial correlation models. We also estimated the accuracy and stability of the network. RESULTS: The preventive behaviors related to network factors revealed that self-initiated vaccination was more connected with cognition factors, and mask-wearing was more connected with personal profiles. The two clusters were linked through information-seeking and political beliefs. Moreover, self-initiated vaccination was negatively connected with vaccine hesitancy and concerns about COVID-19 vaccines and positively connected with trust in the vaccines, pandemic-related altruism, political beliefs, and being married. Mask-wearing was negatively connected with being a professional/white collar worker and higher education level and positively connected with regular physical examination, self-rated health, migration, being married, and better family relationships. Incorporation of age and sex into the network revealed relevant associations between age and mask-wearing and age and self-initiated vaccination. The network was highly accurately estimated. The subset bootstrap showed that the order of node strength centrality, betweenness, and closeness were all stable. The correlation stability coefficient (CS-coefficient) also showed the stability of this estimate, with 0.75 for node strength, 0.75 for betweenness, and 0.67 for closeness. CONCLUSIONS: The internal structures of vaccination and mask-wearing behaviors were quite different, the latter of which were mainly affected by socioeconomic status and health-related behaviors and the former by knowledge about vaccines and political beliefs. Information-seeking and family relationships were the bridge factors connecting these two self-preventive behavior clusters, suggesting the direction of future efforts.

Rare and complex diseases in focus: ChatGPT's role in improving diagnosis and treatment.

Rare and complex diseases pose significant challenges to both patients and healthcare providers. These conditions often present with atypical symptoms, making diagnosis and treatment a formidable task. In recent years, artificial intelligence and natural language processing technologies have shown great promise in assisting medical professionals in diagnosing and managing such conditions. This paper explores the role of ChatGPT, an advanced artificial intelligence model, in improving the diagnosis and treatment of rare and complex diseases. By analyzing its potential applications, limitations, and ethical considerations, we demonstrate how ChatGPT can contribute to better patient outcomes and enhance the healthcare system's overall effectiveness.

Dual-Signal Chemical Exchange Saturation Transfer (Dusi-CEST): An Efficient Strategy for Visualizing Drug Delivery Monitoring in Living Cells.

We report a dual-signal chemical exchange saturation transfer (Dusi-CEST) strategy for drug delivery and detection in living cells. The two signals can be detected by operators in complex environments. This strategy is demonstrated on a cucurbit[6]uril (CB[6]) nanoparticle probe, as an example. The CB[6] probe is equipped with two kinds of hydrophobic cavities: one is found inside CB[6] itself, whereas the other exists inside the nanoparticle. When the probe is dispersed in aqueous solution as part of a hyperpolarized 129Xe NMR experiment, two signals appear at two different chemical shifts (100 and 200 ppm). These two resonances correspond to the NMR signals of 129Xe in the two different cavities. Upon loading with hydrophobic drugs, such as paclitaxel, for intracellular drug delivery, the two resonances undergo significant changes upon drug loading and cargo release, giving rise to a metric enabling the assessment of drug delivery success. The simultaneous change of Dusi-CEST likes a mobile phone that can receive both LTE and Wi-Fi signals, which can help reduce the occurrence of false positives and false negatives in complex biological environments and help improve the accuracy and sensitivity of single-shot detection.