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.

Tunable and switchable multifunctional terahertz meta-mirror based on graphene and vanadium dioxide.

We design a multifunctional THz polarization modulation meta-mirror integrated with polarization conversion and dichroism functions switched by temperature and voltage. The meta-mirror is composed of two-layered graphene metasurfaces and a layer of vanadium dioxide (VO2) on a gold film substrate. Linear-to-linear polarization conversion and linear dichroism (LD) can be switched by temperature control in the VO2 film and Fermi level adjustments in the graphene metasurfaces, where the polarization conversion ratio (PCR) is higher than 0.9 in the range of 2.89 THz to 4.02 THz, LD value reached a maximum of 0.6 at 3.84 THz, and linear-to-circular polarization conversion and circular dichroism (CD) can also be tuned with ellipticity higher than 0.9 in the range of 2.32 THz to 2.69 THz and CD value as high as 0.71 at 2.45 THz. The proposed meta-mirror is the first THz metamaterial device integrating four switchable functions, including linear-to-linear polarization conversion, linear-to-circular polarization conversion, linear dichroism and circular dichroism. The meta-mirror is a promising design for compact system integration in THz imaging, sensing and biological detection applications.

Inhibition of OGFOD1 by FG4592 confers neuroprotection by activating unfolded protein response and autophagy after ischemic stroke.

BACKGROUND: Acute ischemic stroke is a common neurological disease with a significant financial burden but lacks effective drugs. Hypoxia-inducible factor (HIF) and prolyl hydroxylases (PHDs) participate in the pathophysiological process of ischemia. However, whether FG4592, the first clinically approved PHDs inhibitor, can alleviate ischemic brain injury remains unclear. METHODS: The infarct volumes and behaviour tests were first analyzed in mice after ischemic stroke with systemic administration of FG4592. The knockdown of HIF-1α and pretreatments of HIF-1/2α inhibitors were then used to verify whether the neuroprotection of FG4592 is HIF-dependent. The targets predicting and molecular docking methods were applied to find other targets of FG4592. Molecular, cell biological and gene knockdown methods were finally conducted to explore the potential neuroprotective mechanisms of FG4592. RESULTS: We found that the systemic administration of FG4592 decreased infarct volume and improved neurological defects of mice after transient or permanent ischemia. Meanwhile, FG4592 also activated autophagy and inhibited apoptosis in peri-infarct tissue of mice brains. However, in vitro and in vivo results suggested that the neuroprotection of FG4592 was not classical HIF-dependent. 2-oxoglutarate and iron-dependent oxygenase domain-containing protein 1 (OGFOD1) was found to be a novel target of FG4592 and regulated the Pro-62 hydroxylation in the small ribosomal protein s23 (Rps23) with the help of target predicting and molecular docking methods. Subsequently, the knockdown of OGFOD1 protected the cell against ischemia/reperfusion injury and activated unfolded protein response (UPR) and autophagy. Moreover, FG4592 was also found to activate UPR and autophagic flux in HIF-1α independent manner. Blocking UPR attenuated the neuroprotection, pro-autophagy effect and anti-apoptosis ability of FG4592. CONCLUSION: This study demonstrated that FG4592 could be a candidate drug for treating ischemic stroke. The neuroprotection of FG4592 might be mediated by inhibiting alternative target OGFOD1, which activated the UPR and autophagy and inhibited apoptosis after ischemic injury. The inhibition of OGFOD1 is a novel therapy for ischemic stroke.

Random forest model in tax risk identification of real estate enterprise income tax.

The text describes improvements made to the random forest model to enhance its distinctiveness in addressing tax risks within the real estate industry, thereby tackling issues related to tax losses. Firstly, the paper introduces the potential application of the random forest model in identifying tax risks. Subsequently, the experimental analysis focuses on the selection of indicators for tax risk. Finally, the paper develops and utilizes actual taxpayer data to test a risk identification model, confirming its effectiveness. The experimental results indicate that the model's output report includes basic taxpayer information, a summary of tax compliance risks, value-added tax refund situations, directions of suspicious items, and detailed information on common indicators. This paper comprehensively presents detailed taxpayer data, providing an intuitive understanding of tax-related risks. Additionally, the paper reveals the level of enterprise risk registration assessment, risk probability, risk value, and risk assessment ranking. Further analysis shows that enterprise risk points primarily exist in operating income, selling expenses, financial expenses, and total profit. Additionally, the results indicate significant differences between the model's judgment values and declared values, especially in the high-risk probability of total operating income and profit. This implies a significant underreporting issue concerning corporate income tax for real estate enterprises. Therefore, this paper contributes to enhancing the identification of tax risks for real estate enterprises. Using the optimized random forest model makes it possible to accurately assess enterprises' tax compliance risks and identify specific risk points.

Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study.

OBJECTIVE: This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients. MATERIALS AND METHODS: The study cohort consisted of 90 patients from the Fudan University Shanghai Cancer Center and 59 patients from the Affiliated Hospital of Jiangnan University. Occurrences of RP were used as the endpoint event. A total of 512 3D DL-derived features were extracted from two regions of interest (lung-PTV and PTV-GTV) delineated on the pre-radiotherapy planning CT. Feature selection was done using LASSO regression, and the classification models were built using the multilayered perceptron method. Performances of the developed models were evaluated by receiver operating characteristic curve analysis. In addition, the developed models were supplemented with clinical variables and dose-volume metrics of relevance to search for increased predictive value. RESULTS: The predictive model using DL features derived from lung-PTV outperformed the one based on features extracted from PTV-GTV, with AUCs of 0.921 and 0.892, respectively, in the internal test dataset. Furthermore, incorporating the dose-volume metric V30Gy into the predictive model using features from lung-PTV resulted in an improvement of AUCs from 0.835 to 0.881 for the training data and from 0.690 to 0.746 for the validation data, respectively (DeLong p < 0.05). CONCLUSION: Imaging features extracted from pre-radiotherapy planning CT using 3D DL networks could predict radiation pneumonitis and may be of clinical value for risk stratification and toxicity management in LA-NSCLC patients. CLINICAL RELEVANCE STATEMENT: Integrating DL-derived features with dose-volume metrics provides a promising noninvasive method to predict radiation pneumonitis in LA-NSCLC lung cancer radiotherapy, thus improving individualized treatment and patient outcomes.

STEAP3 Affects Ovarian Cancer Progression by Regulating Ferroptosis through the p53/SLC7A11 Pathway.

Ovarian cancer (OC) is a common malignant cancer in women with a low overall survival rate, and ferroptosis may be a potential new strategy for treatment. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a gene closely related to ferroptosis, yet the role of STEAP3 in OC has not yet been thoroughly investigated. Using biological information analysis, we first found that STEAP3 was highly expressed in OC, which was significantly associated with poor prognosis of patients and was an independent prognostic factor. Through cloning, scratch, and transwell experiments, we subsequently found that knockdown of STEAP3 significantly reduced the proliferation and migration ability of OC cells. Furthermore, we found that knockdown of STEAP3 induced ferroptosis in OC cells by detecting ferroptosis indicators. Mechanistically, we also found that knockdown of STEAP3 induced ferroptosis through the p53/SLC7A11 signaling pathway. Through tumorigenic experiments in nude mice, we finally verified that the knockdown of STEAP3 could inhibit tumor growth in vivo by promoting ferroptosis through the p53 pathway. Overall, our study identified a novel therapeutic target for ferroptosis in OC and explored its specific mechanism of action.

Electrogenerated Chemiluminescence Imaging of Single-Atom Nanocatalysts.

Single-atom catalysts (SACs), distinguished by their maximum atom efficiency and precise control over the coordination and electronic properties of individual atoms, show great promise in electrocatalysis. Gaining a comprehensive understanding of the electrochemical performance of SACs requires the screening of electron transfer process at micro/nano scale. This research pioneers the use of electrogenerated chemiluminescence microscopy (ECLM) to observe the electrocatalytic reactions at individual SACs. It boasts sensitivity at the single photon level and temporal resolution down to 100 ms, enabling real-time capture of the electrochemical behavior of individual SACs during potential sweeping. Leveraging the direct correlation between ECL emission and heterogeneous electron transfer processes, we introduced photon flux density for quantitative analysis, unveiling the electrocatalytic efficiency of individual SACs. This approach systematically reveals the relationship between SACs based on different metal atoms and their peroxidase (POD)-like activity. The outcomes contribute to a fundamental understanding of SACs and pave the way for designing SACs with diverse technological and industrial applications.

Elevating sensing capability via dual-atom catalysts boosted luminol cathodic electrochemiluminescence.

BACKGROUND: The advancement of highly sensitive electrochemiluminescence (ECL) biosensors has garnered escalating interest over time. Owing to the distinctive physicochemical attributes, the signal amplification strategy facilitated by functional nanomaterials has achieved notable milestones. Single-atom catalysts (SACs), featuring atomically dispersed metal active sites, have garnered significant attention. SACs offer unprecedented control over active sites and surface structures at the atomic level. However, to fully harness their potential, ongoing efforts focus on strategies to enhance the catalytic performance of SACs, profoundly influencing both the sensitivity and selectivity of SACs-based sensing platforms. RESULTS: In this study, we focused on the synthesis and application of Fe-Co-PNC dual-atom catalysts (DACs) with the incorporation of phosphorus, aiming to enhance catalytic efficiency, particularly in the context of the oxygen reduction reaction (ORR) correlated cathodic luminol ECL. The synergistic effects arising from the combination of Fe and Co in DACs were explored by ECL emission. Comparative studies with Fe-PNC SACs highlighted the superior catalytic performance of Fe-Co-PNC DACs. The ECL sensing platform exhibited excellent sensitivity, which provided a fast detection of Trolox with a wide linear range (0.1 µM-1.0 mM) and a low detection limit (LOD) of 0.03 µM. The platform demonstrated remarkable reproducibility and long-term stability, showcasing its potential for practical biosensing applications. SIGNIFICANCE: This study introduced the novel concept of Fe-Co-PNC DACs. The demonstrated synergistic effects and enhanced catalytic efficiency of DACs offer new avenues for the rational design of advanced catalysts. The successful application in the sensitive detection of Trolox emphasizes their potential significance in biosensing. It not only expands our understanding of SACs but also opens doors for the development of efficient and stable catalysts with broader applications.

The direct binding of bioactive peptide Andersonin-W1 to TLR4 expedites the healing of diabetic skin wounds.

BACKGROUND: Chronic nonhealing wounds remain a considerable challenge in clinical treatment due to excessive inflammation and impeded reepithelialization and angiogenesis. Therefore, the discovery of novel prohealing agents for chronic skin wounds are urgent and important. Amphibian-derived prohealing peptides, especially immunomodulatory peptides, provide a promising strategy for the treatment of chronic skin trauma. However, the mechanism of immunomodulatory peptides accelerating the skin wound healing remains poorly understood. METHODS: The prohealing ability of peptide Andersonin-W1 (AW1) was assessed by cell scratch, cell proliferation, transwell, and tube formation. Next, full-thickness, deep second-degree burns and diabetic full-thickness skin wounds in mice were performed to detect the therapeutic effects of AW1. Moreover, the tissue regeneration and expression of inflammatory cytokines were evaluated by hematoxylin and eosin (H&E), enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry staining. Molecular docking, colocalization, and western blotting were used to explore the mechanism of AW1 in promoting wound healing. RESULTS: We provide solid evidence to display excellent prohealing effects of AW1, identified as a short antimicrobial peptide in our previous report. At relative low concentration of nM, AW1 promoted the proliferation, migration, and scratch repair of keratinocyte, macrophage proliferation, and tube formation of HUVEC. AW1 also facilitated reepithelialization, granulation regeneration, and angiogenesis, thus significantly boosting the healing of full-thickness, deep second-degree burns and diabetic skin wounds in mice. Mechanistically, in macrophages, AW1 directly bound to Toll-like receptor 4 (TLR4) in the extracellular region and regulated the downstream nuclear factor-κB (NF-κB) signaling pathway to facilitate the inflammatory factor secretion and suppress excessive inflammation induced by lipopolysaccharide (LPS). Moreover, AW1 regulated macrophage polarization to promote the transition from the inflammatory to the proliferative phase and then facilitated reepithelialization, granulation regeneration, and angiogenesis, thus exhibiting excellent therapeutic effects on diabetic skin wounds. CONCLUSIONS: AW1 modulates inflammation and the wound healing process by the TLR4/NF-κB molecular axis, thus facilitating reepithelialization, granulation regeneration, and angiogenesis. These findings not only provided a promising multifunctional prohealing drug candidate for chronic nonhealing skin wounds but also highlighted the unique roles of "small" peptides in the elucidation of "big" human disease mechanisms.

Association of preoperative muscle-adipose index measured by computed tomography with survival in patients with esophageal squamous cell carcinoma.

BACKGROUND: Conventional nutritional metrics are closely associated with the prognosis of patients with radically resected esophageal squamous cell carcinoma (ESCC). Nevertheless, the prognostic implications of muscle and adipose tissue composite indexes in ESCC remain unknown. METHODS: We retrospectively analyzed clinicopathological data of 304 patients who underwent resected ESCC. To obtain measurements of the muscle and adipose indexes, preoperative computed tomography (CT) images were used to quantify skeletal-muscle adipose tissue. The diagnostic threshold for muscle-adipose imbalance was determined using X-tile software and used to analyze the association between the muscle-adipose index (MAI) and survival. Instantaneous risk of recurrence was assessed using a hazard function. We constructed a nomogram based on the MAI and other clinical characteristics and established a novel predictive model with independent prognostic factors. The prognostic capabilities of these nomograms were evaluated using calibration curves, receiver operating characteristic (ROC) curves, and decision-curve analysis (DCA). RESULTS: The overall survival (OS) and disease-free survival (DFS) rates in the muscle-adipose-balanced group were significantly better than those in the muscle-adipose-imbalanced group. Multivariate analyses revealed that the MAI, prognostic nutritional index (PNI), tumor stage, and tumor differentiation were independent prognostic factors for OS and DFS in patients with resected ESCC (P < 0.05). The nuclear density curve indicated a lower risk of recurrence for patients in the muscle-adipose-balanced group than that for their imbalanced counterparts. Conversely, the nuclear density curve for PNI was confounded. Postoperative radiotherapy- (RT) benefit analysis demonstrated that patients with ESCC in the muscle-adipose-balanced group could benefit from adjuvant RT. CONCLUSION: This study confirmed that preoperative MAI could serve as a useful independent prognostic factor in patients with resected ESCC. A nomogram based on the MAI and other clinical characteristics could provide individualized survival prediction for patients receiving radical resection. Timely and appropriate nutritional supplements may improve treatment efficacy.

A rapid-floating natural polysaccharide gel-raft with double-effect for the treatment of gastroesophageal reflux disease.

Gastroesophageal reflux disease (GERD) is a prevalent gastrointestinal condition characterized by regurgitating stomach contents into the esophagus, causing mucosal damage or erosion. Clinical physical protection treatment mainly relies on the use of floating rafts. Bletilla striata (BS) is widely regarded as the first-choice drug for treating digestive tract injuries in Chinese Medicine. The rapid-floating gel-raft (B-R) was prepared via a one-step swelling method using natural BS polysaccharide and glyceryl monooleate. Panax notoginseng saponins (PNS) were loaded to further prepare P/B-R according to clinical experience. Possessing hydrophobic dense, stratified porous structure and stable rheological properties, an outperforming floating performance of P/B-R was proven compared with Gaviscon® (alginate-antacid formulation) in vitro. In vivo imaging results showed that P/B-R can retain and adhere to the gastric mucosa of rats for up to 90 min, protecting and repairing the mucosa. Besides physical protection in situ, the systemic effects of antioxidant and anti-inflammatory actions for treating GERD were achieved through the intestinal release of PNS. Acid-labile PNS was protected by P/B-R against gastric acid, attaining the desired release and permeability. A significantly effective mucosa injury protective effect of P/B-R was found in ethanol-induced gastric damage model on rats. Moreover, P/B-R exhibits excellent biosafety at the cellular level.

Low 18F-fluorodeoxyglucose dose positron emission tomography assisted by a deep-learning image-denoising technique in patients with lymphoma.

Background: Patients with lymphoma receive multiple positron emission tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic response. With PET imaging, a reduced level of injected fluorine-18 fluorodeoxyglucose ([18F]FDG) activity can be administered while maintaining the image quality. In this study, we investigated the efficacy of applying a deep learning (DL) denoising-technique on image quality and the quantification of metabolic parameters and Deauville score (DS) of a low [18F]FDG dose PET in patients with lymphoma. Methods: This study retrospectively enrolled 62 patients who underwent [18F]FDG PET scans. The low-dose (LD) data were simulated by taking a 50% duration of routine-dose (RD) PET list-mode data in the reconstruction, and a U-Net-based denoising neural network was applied to improve the images of LD PET. The visual image quality score (1 = undiagnostic, 5 = excellent) and DS were assessed in all patients by nuclear radiologists. The maximum, mean, and standard deviation (SD) of the standardized uptake value (SUV) in the liver and mediastinum were measured. In addition, lesions in some patients were segmented using a fixed threshold of 2.5, and their SUV, metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) were measured. The correlation coefficient and limits of agreement between the RD and LD group were analyzed. Results: The visual image quality of the LD group was improved compared with the RD group. The DS was similar between the RD and LD group, and the negative (DS 1-3) and positive (DS 4-5) results remained unchanged. The correlation coefficients of SUV in the liver, mediastinum, and lesions were all >0.85. The mean differences of SUVmax and SUVmean between the RD and LD groups, respectively, were 0.22 [95% confidence interval (CI): -0.19 to 0.64] and 0.02 (95% CI: -0.17 to 0.20) in the liver, 0.13 (95% CI: -0.17 to 0.42) and 0.02 (95% CI: -0.12 to 0.16) in the mediastinum, and -0.75 (95% CI: -3.42 to 1.91), and -0.13 (95% CI: -0.57 to 0.31) in lesions. The mean differences in MTV and TLG were 0.85 (95% CI: -2.27 to 3.98) and 4.06 (95% CI: -20.53 to 28.64) between the RD and LD groups. Conclusions: The DL denoising technique enables accurate tumor assessment and quantification with LD [18F]FDG PET imaging in patients with lymphoma.

Bridging therapy improves functional outcomes and reduces 90-day mortality compared with direct endovascular thrombectomy in patients with acute posterior ischemic stroke: a systematic review and meta-analysis.

BACKGROUND: It remains unclear whether bridging therapy can achieve better neurologic outcomes than direct endovascular thrombectomy (EVT) in patients with posterior ischemic stroke. METHODS: We systematically searched PubMed, EMBASE, and Cochrane databases with posterior artery occlusion treated with bridging therapy vs. EVT. Efficacy was assessed based on functional independence at 90 days and successful recanalization, whereas safety was assessed by mortality, rate of symptomatic intracranial hemorrhage (sICH), and occurrence of any hemorrhage. All data were analyzed with Review Manager software v5.3 and the risk of bias was determined using the Methodological Index for Non-randomized Studies. RESULTS: We included 17 studies with a total of 3278 patients (1211 in the bridging therapy group and 2067 in the EVT group). Patients in the bridging group had a better functional outcome at 90 days, as evidenced by a higher proportion with a Modified Rankin Scale (mRS) score of 0-2 compared with the EVT group (odds ratio (OR) = 1.83, 95% confidence interval (CI): 1.54-2.19, P < 0.01), while no difference in mRS score of 0-3 (OR = 1.18, 95% CI: 0.96-1.45, P = 0.11). Patients in the bridging therapy group also had lower 90-day mortality rate (OR = 0.75, 95% CI: 0.59-0.95, P = 0.02). There were no significant differences between groups in rates of successful recanalization (OR = 0.96, 95% CI: 0.74-1.25, P = 0.77), sICH (OR = 1.27, 95% CI: 0.86-1.89, P = 0.24), and hemorrhage (OR = 1.22, 95% CI: 0.60-2.50, P = 0.58). CONCLUSIONS: Among patients with posterior ischemic stroke, bridging therapy may be superior to EVT in achieving a good functional outcome and lowering the mortality without increasing the risks of hemorrhage.

Covalent organic frameworks with flexible side chains in hybrid PEMs enable highly efficient proton conductivity.

Electrochemical hydrogen compression (EHC) is an emerging energy conversion technology. Proton exchange membranes (PEMs) with high proton conductivity and high mechanical strength are highly required to meet the practical requirements of EHC. Herein, ionic covalent organic frameworks (iCOFs) with tunable side chains were synthesized and introduced into the sulfonated poly (ether ether ketone) (SPEEK) matrix to fabricate hybrid PEMs. In our membranes, the rigid iCOFs afford ordered proton conduction channels, whereas the flexible side chains on iCOFs afford abundant proton conduction sites, adaptive hydrogen bonding networks, and high local density short hydrogen bonds for highly efficient proton transport. Moreover, the hydrogen bond interactions between the side chains on iCOFs and the SPEEK matrix enhance the mechanical stability of membranes. As a result, the hybrid PEM acquires an enhanced proton conductivity of 540.4 mS cm-1 (80 °C, 100%RH), a high mechanical strength of 120.41 MPa, and a superior performance (2.3 MPa at 30 °C, 100%RH) in EHC applications.

Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image.

Inferring gene expressions from histopathological images has long been a fascinating yet challenging task, primarily due to the substantial disparities between the two modality. Existing strategies using local or global features of histological images are suffering model complexity, GPU consumption, low interpretability, insufficient encoding of local features, and over-smooth prediction of gene expressions among neighboring sites. In this paper, we develop TCGN (Transformer with Convolution and Graph-Node co-embedding method) for gene expression estimation from H&E-stained pathological slide images. TCGN comprises a combination of convolutional layers, transformer encoders, and graph neural networks, and is the first to integrate these blocks in a general and interpretable computer vision backbone. Notably, TCGN uniquely operates with just a single spot image as input for histopathological image analysis, simplifying the process while maintaining interpretability. We validate TCGN on three publicly available spatial transcriptomic datasets. TCGN consistently exhibited the best performance (with median PCC 0.232). TCGN offers superior accuracy while keeping parameters to a minimum (just 86.241 million), and it consumes minimal memory, allowing it to run smoothly even on personal computers. Moreover, TCGN can be extended to handle bulk RNA-seq data while providing the interpretability. Enhancing the accuracy of omics information prediction from pathological images not only establishes a connection between genotype and phenotype, enabling the prediction of costly-to-measure biomarkers from affordable histopathological images, but also lays the groundwork for future multi-modal data modeling. Our results confirm that TCGN is a powerful tool for inferring gene expressions from histopathological images in precision health applications.

Symptoms of post traumatic stress disorder and their relationship with the fear of COVID-19 and COVID-19 burden among health care workers after the full liberalization of COVID-19 prevention and control policy in China: a cross-sectional study.

BACKGROUND: Over the past three years, the COVID-19 pandemic has brought an overwhelming impact on China's hospital system and health care workers, which can lead to post traumatic stress disorder (PTSD) symptoms. Previous research has shown that the COVID-19 pandemic had long-term adverse effects on the mental health of health care workers. Indeed, PTSD symptoms have emerged as one of the significant mental health issues for health care workers arising from the COVID-19 pandemic. Therefore, we conducted this cross-sectional survey to investigate the prevalence of PTSD symptoms in health care workers and its relationship with the fear of COVID-19 and the COVID-19 burden after the full liberalization of COVID-19 prevention and control policy in China. METHODS: This study was conducted three years after the global COVID-19 pandemic (January 15 to January 16, 2023). This study was conducted via the Wenjuanxing platform and used the Chinese versions of the scales PC-PTSD-5, COVID-19 Anxiety Scale (FCV-19S), Social Support Scale, COVID-19 Stress Scale, GAD-2, and PHQ-2. RESULTS: The prevalence of PTSD symptoms in health care workers was 24.3% (232/955). depression(P < 0.001), anxiety(P < 0.05), the fear of COVID-19(P < 0.001), and COVID-19 burden(P < 0.001) were highly correlated with PTSD symptoms in health care workers. Social support(P < 0.05) was a protective factor of PTSD symptoms. CONCLUSIONS: This survey shows that PTSD symptoms were highly prevalent among Chinese health care workers after the COVID-19 pandemic. Governments and leaders of medical institutions should, through psychological interventions, address the current situation of PTSD symptoms among health care workers and develop targeted programs and strategies to reduce their psychological problems.

Sodium-dependent glucose transporter 2 inhibitor alleviates renal lipid deposition and improves renal oxygenation levels in newly diagnosed type 2 diabetes mellitus patients: a randomized controlled trial.

BACKGROUND: Sodium-dependent glucose transporter 2 inhibitor (SGLT2i) has the advantages of effectively lowering blood glucose levels and improving renal outcomes in diabetic patients. This study evaluated the effect of canagliflozin on intrarenal lipid content and oxygenation in newly diagnosed type 2 diabetes mellitus (T2DM) patients. METHODS: A total of 64 newly diagnosed T2DM patients with normal renal function were randomly divided into canagliflozin (n = 33) and glimepiride control (n = 31) groups. All patients underwent functional magnetic resonance imaging (fMRI) scanning to assay patients' intrarenal lipid content and oxygenation level before and after 24 weeks of treatment. Furthermore, the relationship between body mass index and intrarenal lipid content in T2DM patients was analyzed and the correlation between changes in intrarenal lipid content and improvements in renal hypoxia was further assessed. RESULTS: The canagliflozin group had a greater decrease in body weight and blood uric acid level than the glimepiride group (all P < 0.05). The intrarenal lipid content could be significantly reduced after canagliflozin treatment for 24 weeks. The R2* values, a parameter for quantifying the oxygen content in tissues and is inversely related to the oxygen content, of the renal cortex and medulla in the canagliflozin group decreased from the baseline by 6.40% (P < 0.01) and 12.09% (P = 0.000007), respectively. In addition, the degree of reduction of fat fraction (ΔFF) in the kidneys of the canagliflozin group was correlated with the degree of improvement of oxygenation level (ΔR2*) in the renal cortex (r = 0.422, P = 0.014). CONCLUSIONS: The early renal protective effect of SGLT2i in newly diagnosed T2DM patients may be partly attributed to the amelioration of renal hypoxia via the alleviation of ectopic lipid deposition in the kidneys. TRIAL REGISTRATION: Chu Hsien-I Memorial Hospital of Tianjin Medical University (ChiCTR2000037951).

Manipulation of Cationic Group Density in Covalent Organic Framework Membranes for Efficient Anion Transport.

Anion exchange membranes with high anion conductivity are highly desired for electrochemical applications. Increasing ion exchange capacity is a straightforward approach to enhancing anion conductivity but faces a challenge in dimensional stability. Herein, we report the design and preparation of three kinds of isoreticular covalent organic framework (COF) membranes bearing tunable quaternary ammonium group densities as anion conductors. Therein, the cationic groups are integrated into the backbones by flexible ether-bonded alkyl side chains. The highly quaternary ammonium-group-functionalized building units endow COF membranes with abundant cationic groups homogeneously distributed in the ordered channels. The flexible side chains alleviate electrostatic repulsion and steric hindrance caused by large cationic groups, ensuring a tight interlayer stacking and multiple interactions. As a result, our COF membranes achieve a high ion exchange capacity and exceptional dimensional stability simultaneously. Furthermore, the effect of the ionic group density on the ion conductivity in rigid COF channels is systematically explored. Experiments and simulations reveal that the ionic group concentration and side chain mobility jointly determine the ion transport behavior, resulting in the abnormal phenomenon that the anion conductivity is not positively correlated to the ionic group density. The optimal COF membrane achieves the ever-reported highest hydroxide ion conductivity over 300 mS cm-1 at 80 °C and 100% RH. This study offers insightful guidelines on the rational design and preparation of high-performance anion conductors.

Mitigating misalignment in MRI-to-CT synthesis for improved synthetic CT generation: an iterative refinement and knowledge distillation approach.

Objective.Deep learning has shown promise in generating synthetic CT (sCT) from magnetic resonance imaging (MRI). However, the misalignment between MRIs and CTs has not been adequately addressed, leading to reduced prediction accuracy and potential harm to patients due to the generative adversarial network (GAN)hallucination phenomenon. This work proposes a novel approach to mitigate misalignment and improve sCT generation.Approach.Our approach has two stages: iterative refinement and knowledge distillation. First, we iteratively refine registration and synthesis by leveraging their complementary nature. In each iteration, we register CT to the sCT from the previous iteration, generating a more aligned deformed CT (dCT). We train a new model on the refined 〈dCT, MRI〉 pairs to enhance synthesis. Second, we distill knowledge by creating a target CT (tCT) that combines sCT and dCT images from the previous iterations. This further improves alignment beyond the individual sCT and dCT images. We train a new model with the 〈tCT, MRI〉 pairs to transfer insights from multiple models into this final knowledgeable model.Main results.Our method outperformed conditional GANs on 48 head and neck cancer patients. It reduced hallucinations and improved accuracy in geometry (3% ↑ Dice), intensity (16.7% ↓ MAE), and dosimetry (1% ↑γ3%3mm). It also achieved <1% relative dose difference for specific dose volume histogram points.Significance.This pioneering approach for addressing misalignment shows promising performance in MRI-to-CT synthesis for MRI-only planning. It could be applied to other modalities like cone beam computed tomography and tasks such as organ contouring.