Oxidized cellulose-filled double thermo/pH-sensitive hydrogel for local chemo-photothermal therapy in breast cancer

Lumpectomy plus radiation is a treatment option offering better survival than conventional mastectomy for patients with early-stage breast cancer. However, successive radioactive therapy remains tedious and unsafe with severe adverse reactions and secondary injury. Herein, a composite hydrogel with pH- and photothermal double-sensitive activity is developed via physical crosslinking. The composite hydrogel incorporated with tempo-oxidized cellulose nanofiber (TOCN), polyvinyl alcohol (PVA) and a polydopamine (PDA) coating for photothermal therapy (PTT) triggered in situ release of doxorubicin (DOX) drug was utilized to optimize postoperative strategies of malignant tumors inhibition. The incorporation of TOCN significantly affects the performance of composite hydrogels. The best-performing TOCN/PVA7 was selected for drug loading and polydopamine coating by rational design. In vitro studies have demonstrated that the composite hydrogel exhibited high NIR photothermal conversion efficiency, benign cytotoxicity to L929 cells, pH-dependent release profiles, and strong MCF-7 cell inhibitory effects. Then the TOCN/PVA7-PDA@DOX hydrogel is implanted into the tumor resection cavity for local in vivo chemo-photothermal synergistical therapy to ablate residue tumor tissues. Overall, this work suggests that such a chemo-photothermal hydrogel delivery system has great potential as a promising tool for the postsurgical management of breast cancer.

Unraveling the distinction between depression and anxiety: A machine learning exploration of causal relationships

OBJECTIVE

Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective healthcare interventions. This research addressed this gap by employing a streamlined Symptom Checklist 90 (SCL-90) designed to minimize patient response burden. Utilizing machine learning algorithms, the study sought to construct classification models capable of distinguishing between depression and anxiety.

METHODS

The study included 4262 individuals currently experiencing depression alone (n = 2998), anxiety alone (n = 716), or both depression and anxiety (n = 548). Counterfactual diagnosis was used to construct a causal network on the dataset. Employing a causal network, the SCL-90 was simplified. Items that have causality with only depression, only anxiety and both depression and anxiety were selected, and these streamlined items served as input features for four distinct machine learning algorithms, facilitating the creation of classification models for distinguishing depression and anxiety.

RESULTS

Cross-validation demonstrated the performance of the classification models with the following metrics: (1) K-nearest neighbors (AUC = 0.924, Acc = 92.81 %); (2) support vector machine (AUC = 0.937, Acc = 94.38 %); (3) random forest (AUC = 0.918, Acc = 94.38 %); and (4) adaptive boosting (AUC = 0.882, Acc = 94.38 %). Notably, the support vector machine excelled, with the highest AUC and superior accuracy.

CONCLUSION

Incorporating the simplified SCL-90 and machine learning presents a promising, efficient, and cost-effective tool for the precise identification of depression and anxiety.

Improving therapeutic outcomes in heart failure with reduced nonvalvular ejection fraction: A clinical study of heart failure education intervention

OBJECTIVE

The current study delves into the impact of heart failure education intervention on improving therapeutic outcomes for heart failure (HF) patients with reduced nonvalvular ejection fraction.

METHODS

There involved a total of 60 HF patients with non-valvular ejection fraction reduction who met the inclusion requirements. Patients enrolled were randomly distributed into an observation group and a control group. The observation group received heart failure education intervention, while the control group received conventional intervention. The therapeutic effect, changes in physical indicators, cardiac function indicators, coagulation function, self-management scale scores, and the incidence of adverse cardiovascular events were meticulously evaluated.

RESULTS

The total effective proportion in the observation group was 96.67%, which was significantly higher than the control group's proportion of 76.67% (p < .05). After treatment, several parameters in the observation group showed significant improvements compared to the control group: hs-CRP, IL-6, LVEDV value, LVESV value, PT value, APTT value, and TT value were all evidently lower in the observation group. Additionally, the cardiac index, LVEF value, and heart failure self-management scale fraction were significantly higher in the observation group compared to the control group (p < .05). Furthermore, the incidence of adverse cardiovascular events in the observation group was only 6.67%, which was significantly lower than the control group's incidence of 20.00% (p < .05).

CONCLUSION

Heart failure education intervention demonstrates effectiveness in improving the therapeutic outcomes for HF patients and reduced nonvalvular ejection fraction. Additionally, it enhances patients' self-management abilities. Given these positive results, it is highly recommended to promote and implement HF education intervention in clinical practice.

Preparation of pH-sensitive porous polylactic acid-based medical dressing with self-pumping function

Excessive exudation from the wound site and the difficulty of determining the state of wound healing can make medical management more difficult and, in extreme cases, lead to wound deterioration. In this study, we fabricated a pH-sensitive colorimetric chronic wound dressing with self-pumping function using electrostatic spinning technology. It consisted of three layers: a polylactic acid-curcumin (PCPLLA) hydrophobic layer, a hydrolyzed polyacrylonitrile (HPAN) transfer layer, and a polyacrylonitrile-purple kale anthocyanin (PAN-PCA) hydrophilic layer. The results showed that the preparation of porous PLLA fiber membrane loaded with 0.2 % Cur was achieved by adjusting the spinning-related parameters, which could ensure that the composite dressing had sufficient anti-inflammatory, antibacterial and antioxidant properties. The HPAN membrane treated with alkali for 30 min had significantly enhanced liquid wetting ability, and the unidirectional transport of liquid could be achieved by simple combination with the 20 um PCPLLA fiber membrane. In addition, the 4 % loaded PCA showed more obvious color difference than the colorimetric membrane. In vivo and ex vivo experiments have demonstrated the potential of multifunctional dressings for the treatment of chronic wounds.

Pyroptotic macrophages promote proliferation and chemotherapy resistance of peripheral T-cell lymphoma via TLR4 signaling pathway

Peripheral T-cell lymphoma (PTCL) is a highly aggressive type of non-Hodgkin's lymphoma with a poor prognosis. Pyroptosis is a newly discovered procedural cell death mode, which has been implicated to occur in both tumor cells and immune cells. However, the occurrence and effect of pyroptosis on PTCL remain unclear. Here, we found that pyroptosis occurred in interstitial macrophages of PTCL rather than in tumor cells. In clinical specimens, macrophage pyroptosis was associated with a poor prognosis of PTCL. In vitro experiments and gene sequencing results showed that pyroptotic macrophages could upregulate the expression of TLR4 through secreting inflammatory cytokines IL-18. Upregulated TLR4 activated its downstream NF-κB anti-apoptotic signaling pathway, thus leading to malignant proliferation and chemotherapy resistance of tumor cells. Moreover, the expression of factors such as XIAP in the NF-κB anti-apoptotic pathway was downregulated after the knockdown of TLR4, and the malignant promotion effect of pyroptotic macrophages on PTCL cells was also reversed. Our findings revealed the mechanism of pyroptotic macrophages promoting the malignant biological behavior of PTCL and elucidated the key role of TLR4 in this process. In-depth analysis of this mechanism will contribute to understanding the regulatory effect of PTCL by the tumor microenvironment and providing new ideas for the clinical treatment of PTCL.

Abnormal functional connectivity within the prefrontal cortex is associated with multiple plasma lipid species in major depressive disorder

BACKGROUND

Abnormalities in functional connectivity (FC) in major depressive disorder (MDD) have been widely reported. Analysis of the relationship between FC and plasma lipid profiles would be meaningful in the exploration of pathophysiological mechanisms and helpful for the identification of biomarkers for MDD.

METHODS

Patients with MDD (n = 49) and healthy controls (HC, n = 87) were recruited. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for FC construction. The plasma lipid profiles were acquired using ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS) analysis and clustered as co-expression modules. The differential FC and lipid modules between HCs and patients with MDD were identified, and then the association between FC and lipid co-expression modules was analyzed using correlation analysis. The modules associated molecular function was explored using metabolite set enrichment analysis (MSEA).

RESULTS

MDD-associated FC and lipid co-expression modules were identified. One module was associated with FC values between the right orbital part of the middle frontal gyrus and the opercular part of the left inferior frontal gyrus, which was enriched in lipid sets of diacylglycerols and fatty alcohols; another module was associated with FC values between the right middle frontal gyrus and the right anterior cingulate and paracingulate gyri, which was enriched in lipid sets of glycerophosphocholines and glycerophosphoethanolamines.

CONCLUSION

Our results indicated that abnormal FC in the prefrontal cortex is associated with multiple plasma lipid species, which may provide novel clues for exploring the pathophysiology of MDD.

AURKA emerges as a vulnerable target for KEAP1-deficient non-small cell lung cancer by activation of asparagine synthesis

AURKA is an established target for cancer therapy; however, the efficacy of its inhibitors in clinical trials is hindered by differential response rates across different tumor subtypes. In this study, we demonstrate AURKA regulates amino acid synthesis, rendering it a vulnerable target in KEAP1-deficient non-small cell lung cancer (NSCLC). Through CRISPR metabolic screens, we identified that KEAP1-knockdown cells showed the highest sensitivity to the AURKA inhibitor MLN8237. Subsequent investigations confirmed that KEAP1 deficiency heightens the susceptibility of NSCLC cells to AURKA inhibition both in vitro and in vivo, with the response depending on NRF2 activation. Mechanistically, AURKA interacts with the eIF2α kinase GCN2 and maintains its phosphorylation to regulate eIF2α-ATF4-mediated amino acid biosynthesis. AURKA inhibition restrains the expression of asparagine synthetase (ASNS), making KEAP1-deficient NSCLC cells vulnerable to AURKA inhibitors, in which ASNS is highly expressed. Our study unveils the pivotal role of AURKA in amino acid metabolism and identifies a specific metabolic indication for AURKA inhibitors. These findings also provide a novel clinical therapeutic target for KEAP1-mutant/deficient NSCLC, which is characterized by resistance to radiotherapy, chemotherapy, and targeted therapy.

Microbial bile acid metabolite ameliorates mycophenolate mofetil-induced gastrointestinal toxicity through vitamin D3 receptor

Mycophenolate mofetil (MMF) is one of the most used immunosuppressive drugs in organ transplantation, but frequent gastrointestinal (GI) side effects through unknown mechanisms limit its clinical use. Gut microbiota and its metabolites were recently reported to play a vital role in MMF-induced GI toxicity, but the specific mechanism of how they interact with the human body is still unclear. Here, we found that secondary bile acids (BAs), as bacterial metabolites, were significantly reduced by MMF administration in the gut of mice. Microbiome data and fecal microbiota transfer model supported a microbiota-dependent effect on the reduction of secondary BAs. Supplementation of the secondary BA lithocholic acid alleviated MMF-induced weight loss, colonic inflammation, and oxidative phosphorylation damage. Genetic deletion of the vitamin D3 receptor (VDR), which serves as a primary colonic BA receptor, in colonic epithelial cells (VDRΔIEC) abolished the therapeutic effect of lithocholic acid on MMF-induced GI toxicity. Impressively, we discovered that paricalcitol, a Food and Drug Administration-approved VDR agonist that has been used in clinics for years, could effectively alleviate MMF-induced GI toxicity. Our study reveals a previously unrecognized mechanism of gut microbiota, BAs, and VDR signaling in MMF-induced GI side effects, offering potential therapeutic strategies for clinics.

PC71BM as Morphology Regulator for Highly Efficient Ternary Organic Solar Cells with Bulk Heterojunction or Layer-by-Layer Configuration

The ternary strategy is one of the effective methods to regulate the morphology of the active layer in organic solar cells (OSCs). In this work, the ternary OSCs with bulk heterojunction (BHJ) or layer-by-layer (LbL) active layers are prepared by using the polymer donor PM6 and the non-fullerene acceptor L8-BO as the main system and the fullerene acceptor PC71BM as the third component. The power conversion efficiencies (PCEs) of BHJ OSCs and LbL OSCs are increased from 17.10% to 18.02% and from 17.20% to 18.20% by introducing PC71BM into the binary active layer, respectively. The in situ UV-vis absorption spectra indicate that the molecular aggregation and crystallization process can be prolonged by introducing PC71BM into the PM6:L8-BO or PM6/L8-BO active layer. The molecular orientation and molecular crystallinity in the active layer are optimized by introducing the PC71BM into the binary BHJ or LbL active layers, which can be confirmed by the experimental results of grazing incidence wide-angle X-ray scattering. This study demonstrates that the third component PC71BM can be used as a morphology regulator to regulate the morphology of BHJ or LbL active layers, thus effectively improving the performance of BHJ and LbL OSCs.

Dual consistency regularization with subjective logic for semi-supervised medical image segmentation

Semi-supervised learning plays a vital role in computer vision tasks, particularly in medical image analysis. It significantly reduces the time and cost involved in labeling data. Current methods primarily focus on consistency regularization and the generation of pseudo labels. However, due to the model's poor awareness of unlabeled data, aforementioned methods may misguide the model. To alleviate this problem, we propose a dual consistency regularization with subjective logic for semi-supervised medical image segmentation. Specifically, we introduce subjective logic into our semi-supervised medical image segmentation task to estimate uncertainty, and based on the consistency hypothesis, we construct dual consistency regularization under weak and strong perturbations to guide the model's learning from unlabeled data. To evaluate the performance of the proposed method, we performed experiments on three widely used datasets: ACDC, LA, and Pancreas. Experiments show that the proposed method achieved improvement compared with other state-of-the-art (SOTA) methods.

A novel antagonist of the CCL5/CCR5 axis suppresses the tumor growth and metastasis of triple-negative breast cancer by CCR5-YAP1 regulation

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC) with a high mortality rate, and few effective therapeutic strategies are available. CCL5/CCR5 is an appealing immunotherapeutic target for TNBC. However, its signaling mechanism is poorly understood and its direct antagonists have not been reported. Here, we developed a high-throughput screening (HTS) assay for discovering its antagonists. Verteporfin was identified as a more selective and potent antagonist than the known CCR5 antagonist maraviroc. Without photodynamic therapy, verteporfin demonstrated significant inhibition on TNBC tumor growth through immune regulation, remarkable suppression of lung metastasis by cell-intrinsic mechanism, and a significant extension of overall survival in vivo. Mechanistically, CCR5 was found to be essential for expression of the key hippo effector YAP1. It promoted YAP1 transcription via HIF-1α and exerted further control over the migration of CD8+ T, NK, and MDSC immune cells through chemokines CXCL16 and CXCL8 which were identified from RNA-seq. Moreover, the CCR5-YAP1 axis played a vital role in promoting metastasis by modulating β-catenin and core epithelial-mesenchymal transition transcription factors ZEB1 and ZEB2. It is noteworthy that the regulatory relationship between CCR5 and YAP1 was observed across various BC subtypes, TNBC patients, and showed potential relevance in fifteen additional cancer types. Overall, this study introduced an easy-to-use HTS assay that streamlines the discovery of CCL5/CCR5 axis antagonists. Verteporfin was identified as a specific molecular probe of this axis with great potentials as a therapeutic agent for treating sixteen malignant diseases characterized by heightened CCR5 and YAP1 levels.

Realization of all-band-flat photonic lattices

Flatbands play an important role in correlated quantum matter and have promising applications in photonic lattices. Synthetic magnetic fields and destructive interference in lattices are traditionally used to obtain flatbands. However, such methods can only obtain a few flatbands with most bands remaining dispersive. Here we realize all-band-flat photonic lattices of an arbitrary size by precisely controlling the coupling strengths between lattice sites to mimic those in Fock-state lattices. This allows us to go beyond the perturbative regime of strain engineering and group all eigenmodes in flatbands, which simultaneously achieves high band flatness and large usable bandwidth. We map out the distribution of each flatband in the lattices and selectively excite the eigenmodes with different chiralities. Our method paves a way in controlling band structure and topology of photonic lattices.

Effects of In Vitro Fermentation of Polysialic Acid and Sialic Acid on Gut Microbial Community Composition and Metabolites in Healthy Humans

The influence of polysialic acid (PSA) and sialic acid (SA) on the gut microbial community composition and metabolites in healthy humans was investigated using a bionic gastrointestinal reactor. The results indicated that PSA and SA significantly changed the gut microbiota and metabolites to different degrees. PSA can increase the relative abundances of Faecalibacterium and Allisonella, whereas SA can increase those of Bifidobacterium and Megamonas. Both can significantly increase the content of short-chain fatty acids. The results of metabolome analysis showed that PSA can upregulate ergosterol peroxide and gallic acid and downregulate the harmful metabolite N-acetylputrescine. SA can upregulate 4-pyridoxic acid and lipoic acid. PSA and SA affect gut microbiota and metabolites in different ways and have positive effects on human health. These results will provide a reference for the further development of PSA- and SA-related functional foods and health products.

Interferon-γ and its response are determinants of antibody-mediated rejection and clinical outcomes in patients after renal transplantation

Interferon-γ (IFN-γ) is an important cytokine in tissue homeostasis and immune response, while studies about it in antibody-mediated rejection (ABMR) are very limited. This study aims to comprehensively elucidate the role of IFN-γ in ABMR after renal transplantation. In six renal transplantation cohorts, the IFN-γ responses (IFNGR) biological process was consistently top up-regulated in ABMR compared to stable renal function or even T cell-mediated rejection in both allografts and peripheral blood. According to single-cell analysis, IFNGR levels were found to be broadly elevated in most cell types in allografts and peripheral blood with ABMR. In allografts with ABMR, M1 macrophages had the highest IFNGR levels and were heavily infiltrated, while kidney resident M2 macrophages were nearly absent. In peripheral blood, CD14+ monocytes had the top IFNGR level and were significantly increased in ABMR. Immunofluorescence assay showed that levels of IFN-γ and M1 macrophages were sharply elevated in allografts with ABMR than non-rejection. Importantly, the IFNGR level in allografts was identified as a strong risk factor for long-term renal graft survival. Together, this study systematically analyzed multi-omics from thirteen independent cohorts and identified IFN-γ and IFNGR as determinants of ABMR and clinical outcomes in patients after renal transplantation.

Aurora kinase A-mediated phosphorylation triggers structural alteration of Rab1A to enhance ER complexity during mitosis

Morphological rearrangement of the endoplasmic reticulum (ER) is critical for metazoan mitosis. Yet, how the ER is remodeled by the mitotic signaling remains unclear. Here, we report that mitotic Aurora kinase A (AURKA) employs a small GTPase, Rab1A, to direct ER remodeling. During mitosis, AURKA phosphorylates Rab1A at Thr75. Structural analysis demonstrates that Thr75 phosphorylation renders Rab1A in a constantly active state by preventing interaction with GDP-dissociation inhibitor (GDI). Activated Rab1A is retained on the ER and induces the oligomerization of ER-shaping protein RTNs and REEPs, eventually triggering an increase of ER complexity. In various models, from Caenorhabditis elegans and Drosophila to mammals, inhibition of Rab1AThr75 phosphorylation by genetic modifications disrupts ER remodeling. Thus, our study reveals an evolutionarily conserved mechanism explaining how mitotic kinase controls ER remodeling and uncovers a critical function of Rab GTPases in metaphase.

Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases

OBJECTIVES

Glioblastoma (GBM) and brain metastases (BMs) are the two most common malignant brain tumors in adults. Magnetic resonance imaging (MRI) is a commonly used method for screening and evaluating the prognosis of brain tumors, but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited. In recent years, deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system. This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases (SBMs), and to further explore the impact of multimodality data fusion on classification tasks.

METHODS

Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed. First, structural T1-weight, T1C-weight, and T2-weight were selected as 3 inputs to the entire model, regions of interest (ROIs) were manually delineated on the registered three modal MR images, and multimodality radiomics features were obtained, dimensions were reduced using a random forest (RF)-based feature selection method, and the importance of each feature was further analyzed. Secondly, we used the method of contrast disentangled to find the shared features and complementary features between different modal features. Finally, the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities.

RESULTS

The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs. Furthermore, compared with single-modal data, the multimodal fusion models using machine learning algorithms such as support vector machine (SVM), Logistic regression, RF, adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) achieved significant improvements, with area under the curve (AUC) values of 0.974, 0.978, 0.943, 0.938, and 0.947, respectively; our comparative disentangled multi-modal MR fusion method performs well, and the results of AUC, accuracy (ACC), sensitivity (SEN) and specificity(SPE) in the test set were 0.985, 0.984, 0.900, and 0.990, respectively. Compared with other multi-modal fusion methods, AUC, ACC, and SEN in this study all achieved the best performance. In the ablation experiment to verify the effects of each module component in this study, AUC, ACC, and SEN increased by 1.6%, 10.9% and 15.0%, respectively after 3 loss functions were used simultaneously.

CONCLUSIONS

A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

Z-Type Heterojunction MnO2@g-C3N4 Photocatalyst-Activated Peroxymonosulfate for the Removal of Tetracycline Hydrochloride in Water

A Z-type heterojunction MnO2@g-C3N4 photocatalyst with excellent performance was synthesized by an easy high-temperature thermal polymerization approach and combined with peroxymonosulfate (PMS) oxidation technology for highly efficient degrading of tetracycline hydrochloride (TC). Analysis of the morphological structural and photoelectric properties of the catalysts was achieved through different characterization approaches, showing that the addition of MnO2 heightened visible light absorption by g-C3N4. The Mn1-CN1/PMS system showed the best degradation of TC wastewater, with a TC degradation efficiency of 96.97% following 180 min of treatment. This was an approximate 38.65% increase over the g-C3N4/PMS system. Additionally, the Mn1-CN1 catalyst exhibited excellent stability and reusability. The active species trapping experiment indicated •OH and SO4•- remained the primary active species to degrade TC in the combined system. TC degradation pathways and intermediate products were determined. The Three-Dimensional Excitation-Emission Matrix (3DEEM) was employed for analyzing changes in the molecular structure in TC photocatalytic degradation. The biological toxicity of TC and its degradation intermediates were investigated via the Toxicity Estimation Software Test (T.E.S.T.). The research offers fresh thinking for water environment pollution treatment.

Construction of an economical xylose-utilizing Saccharomyces cerevisiae and its ethanol fermentation

Traditional industrial Saccharomyces cerevisiae could not metabolize xylose due to the lack of a specific enzyme system for the reaction from xylose to xylulose. This study aims to metabolically remould industrial S. cerevisiae for the purpose of utilizing both glucose and xylose with high efficiency. Heterologous gene xylA from Piromyces and homologous genes related to xylose utilization were selected to construct expression cassettes and integrated into genome. The engineered strain was domesticated with industrial material under optimizing conditions subsequently to further improve xylose utilization rates. The resulting S. cerevisiae strain ABX0928-0630 exhibits a rapid growth rate and possesses near 100% xylose utilization efficiency to produce ethanol with industrial material. Pilot-scale fermentation indicated the predominant feature of ABX0928-0630 for industrial application, with ethanol yield of 0.48 g/g sugars after 48 hours and volumetric xylose consumption rate of 0.87 g/l/h during the first 24 hours. Transcriptome analysis during the modification and domestication process revealed a significant increase in the expression level of pathways associated with sugar metabolism and sugar sensing. Meanwhile, genes related to glycerol lipid metabolism exhibited a pattern of initial increase followed by a subsequent decrease, providing a valuable reference for the construction of efficient xylose-fermenting strains.

Investigation on the Attainment of High-Density 316L Stainless Steel with Selective Laser Sintering

Due to the low density of the green part produced by selective laser sintering (SLS), previous reports mainly improve the sample's density through the infiltration of low-melting metals or using isostatic pressing technology. In this study, the feasibility of preparing high-density 316L stainless steel using 316L and epoxy resin E-12 as raw materials for SLS combined with debinding and sintering was investigated. The results indicated that in an argon atmosphere, high carbon and oxygen contents, along with the uneven distribution of oxygen, led to the formation of impurity phases such as metal oxides, including Cr2O3 and FeO, preventing the effective densification of the sintered samples. Hydrogen-sintered samples can achieve a high relative density exceeding 98% without losing their original design shape. This can be attributed to hydrogen's strong reducibility (effectively reducing the carbon and oxygen contents in the samples, improving their distribution uniformity, and eliminating impurity phases) and hydrogen's higher thermal conductivity (about 10 times that of argon, reducing temperature gradients in the sintered samples and promoting better sintering). The microstructure of the hydrogen-sintered samples consisted of equiaxed austenite and ferrite phases. The samples exhibited the highest values of tensile strength, yield strength, and elongation at 1440 °C, reaching 513.5 MPa, 187.4 MPa, and 76.1%, respectively.

The emergence of modern zoogeographic regions in Asia examined through climate-dental trait association patterns

The complex and contrasted distribution of terrestrial biota in Asia has been linked to active tectonics and dramatic climatic changes during the Neogene. However, the timings of the emergence of these distributional patterns and the underlying climatic and tectonic mechanisms remain disputed. Here, we apply a computational data analysis technique, called redescription mining, to track these spatiotemporal phenomena by studying the associations between the prevailing herbivore dental traits of mammalian communities and climatic conditions during the Neogene. Our results indicate that the modern latitudinal zoogeographic division emerged after the Middle Miocene climatic transition, and that the modern monsoonal zoogeographic pattern emerged during the late Late Miocene. Furthermore, the presence of a montane forest biodiversity hotspot in the Hengduan Mountains alongside Alpine fauna on the Tibetan Plateau suggests that the modern distribution patterns may have already existed since the Pliocene.

TCAD Simulation Studies on Ultra-Low-Power Non-Volatile Memory

Ultra-Low-Power Non-Volatile Memory (UltraRAM), as a promising storage device, has attracted wide research attention from the scientific community. Non-volatile data retention in combination with switching at ≤2.6 V is achieved through the use of the extraordinary 2.1 eV conduction band offsets of InAs/AlSb and a triple-barrier resonant tunnelling structure. Along these lines, in this work, the structure, storage mechanism, and improvement strategies of UltraRAM were systematically investigated to enhance storage window clarity and speed performance. First, the basic structure and working principle of UltraRAM were introduced, and its comparative advantages over traditional memory devices were highlighted. Furthermore, through the validation of the band structure and storage mechanism, the superior performance of UltraRAM, including its low operating voltage and excellent non-volatility, was further demonstrated. To address the issue of the small storage window, an improvement strategy was proposed by reducing the thickness of the channel layer to increase the storage window. The feasibility of this strategy was validated by performing a series of simulation-based experiments. From our analysis, a significant 80% increase in the storage window after thinning the channel layer was demonstrated, providing an important foundation for enhancing the performance of UltraRAM. Additionally, the data storage capability of this strategy was examined under the application of short pulse widths, and a data storage operation with a 10 ns pulse width was successfully achieved. In conclusion, valuable insights into the application of UltraRAM in the field of non-volatile storage were provided. Our work paves the way for further optimizing the memory performance and expanding the functionalities of UltraRAM.

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion

Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to severe complications such as bleeding and headache. Therefore, forecasting necrosis of the nasopharynx and initiating timely clinical intervention has important implications for reducing complications caused by re-irradiation. This research informs clinical decision-making by making predictions on re-irradiation of recurrent nasopharyngeal carcinoma using deep learning multi-modal information fusion between multi-sequence nuclear magnetic resonance imaging and plan dose. Specifically, we assume that the hidden variables of model data can be divided into two categories: task-consistency and task-inconsistency. The task-consistency variables are characteristic variables contributing to target tasks, while the task-inconsistency variables are not apparently helpful. These modal characteristics are adaptively fused when the relevant tasks are expressed through the construction of supervised classification loss and self-supervised reconstruction loss. The cooperation of supervised classification loss and self-supervised reconstruction loss simultaneously reserves the information of characteristic space and controls potential interference simultaneously. Finally, multi-modal fusion effectively fuses information through an adaptive linking module. We evaluated this method on a multi-center dataset. and found the prediction based on multi-modal features fusion outperformed predictions based on single-modal, partial modal fusion or traditional machine learning methods.

No need to integrate action information during coarse semantic processing of man-made tools

Action representation of man-made tools consists of two subtypes: structural action representation concerning how to grasp an object, and functional action representation concerning the skilled use of an object. Compared to structural action representation, functional action representation plays the dominant role in fine-grained (i.e., basic level) object recognition. However, it remains unclear whether the two types of action representation are involved differently in the coarse semantic processing in which the object is recognized at a superordinate level (i.e., living/non-living). Here we conducted three experiments using the priming paradigm, in which video clips displaying structural and functional action hand gestures were used as prime stimuli and grayscale photos of man-made tools were used as target stimuli. Participants recognized the target objects at the basic level in Experiment 1 (i.e., naming task) and at the superordinate level in Experiments 2 and 3 (i.e., categorization task). We observed a significant priming effect for functional action prime-target pairs only in the naming task. In contrast, no priming effect was found in either the naming or the categorization task for the structural action prime-target pairs (Experiment 2), even when the categorization task was preceded by a preliminary action imitation of the prime gestures (Experiment 3). Our results suggest that only functional action information is retrieved during fine-grained object processing. In contrast, coarse semantic processing does not require the integration of either structural or functional action information.

Direct inhibition of dioxygenases TET1 by the rheumatoid arthritis drug auranofin selectively induces cancer cell death in T-ALL

T-cell acute lymphoblastic leukemia (T-ALL) is a type of hematologic tumor with malignant proliferation of hematopoietic progenitor cells. However, traditional clinical treatment of T-ALL included chemotherapy and stem cell transplantation always lead to recurrence and poor prognosis, thus new therapeutic targets and drugs are urgently needed for T-ALL treatment. In this study, we showed that TET1 (ten-eleven translocation 1), a key participant of DNA epigenetic control, which catalyzes the conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) to modulate gene expression, was highly upregulated in human T-ALL and negatively correlated with the prognosis of patients. Knockdown of TET1 suppressed T-ALL growth and progression, suggesting that TET1 inhibition maybe an effective way to fight T-ALL via DNA epigenetic modulation. Combining structure-guided virtual screening and cell-based high-throughput screening of FDA-approved drug library, we discovered that auranofin, a gold-containing compound, is a potent TET1 inhibitor. Auranofin inhibited the catalytic activity of TET1 through competitive binding to its substrates binding pocket and thus downregulated the genomic level of 5hmC marks and particularly epigenetically reprogramed the expression of oncogene c-Myc in T-ALL in TET1-dependent manner and resulted in suppression of T-ALL in vitro and in vivo. These results revealed that TET1 is a potential therapeutic target in human T-ALL and elucidated the mechanism that TET1 inhibitor auranofin suppressed T-ALL through the TET1/5hmC/c-Myc signaling pathway. Our work thus not only provided mechanism insights for T-ALL treatment, but also discovered potential small molecule therapeutics for T-ALL.

JUN mediates glucocorticoid resistance by stabilizing HIF1a in T cell acute lymphoblastic leukemia

Dexamethasone (Dex) plays a critical role in T-ALL treatment, but the mechanisms of Dex resistance are poorly understood. Here, we demonstrated that the expression of JUN was regulated in Dex-resistant T-ALL cell lines and patient samples. JUN knockdown increased the sensitivity to Dex. Moreover, the survival data showed that high expression of JUN related to poor prognosis of T-ALL patients. Then, we generated dexamethasone-resistant clones and conducted RNA-seq and ATAC-seq. We demonstrated that the upregulation of JUN was most significant and regulated by JNK pathway in Dex-resistant cells. High-throughput screening showed that HIF1α inhibitors synergized with Dex could enhance Dex resistance cells death in vitro and in vivo. Additionally, JUN combined and stabilized HIF1α in Dex resistance cells. These results reveal a new mechanism of Dex resistance in T-ALL and provide experimental evidence for the potential therapeutic benefit of targeting the JNK-JUN-HIF1α axis for T-ALL treatment.

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

A Novel Role of ARA70 in Regulating Ferritinophagy of RGCs During Retinal Ischemia Reperfusion

Although the contribution of ferroptosis, an iron-dependent cell death, to ischemia reperfusion (IR)-induced retinal injury has been reported before, to optimize therapeutic strategy, there is still an urgent need to identify potential candidates involved in this process. Androgen Receptor-Associated Protein of 70 kDa (ARA70) is a cargo receptor for ferritinophagy, and its role in retinal ferroptosis has not been revealed yet. Herein, we explored the role of ARA70 in IR-associated retinal lesions by in vivo (C57BL/6 J mice with intraocular pressure of 90-100 mmHg) and in vitro (retinal ganglion cells (RGCs) stimulated with tert-butyl hydroperoxide (tBH)) experiments. It was found that IR upregulated ARA70 expression and accelerated lipid peroxidation in retinal tissues. We first confirmed that two ferroptosis inhibitors, deferiprone or ferrostatin-1 (Fer-1), suppressed ferritin degradation, restrained apoptosis and inflammation, and protected mouse retinas against IR stress. Next, primary mouse RGCs were treated with tBH to simulate IR environment in vitro. ARA70 expression was decreased at lower concentrations of tBH (5-20 μM), but increased at higher concentrations (40-80 μM). Interestingly, the expression of ferritin-related proteins (ferritin heavy chain, FTH; ferritin light chain, FTL) showed an opposite alteration. Knockdown of ARA70 protected RGCs from tBH-induced damage. It inhibited the delivery of ferritin to lysosomes for ferritinophagy and thus reducing cellular Fe2+ concentration. Besides, ARA70 knockdown suppressed autophagy and inflammation of tBH-treated RGCs. These findings provide novel insights into the pathogenesis of retinal IR, and may be helpful for treatment of retinal diseases.

LaenNet: Learning robust GCNs by propagating labels

Graph Convolutional Networks (GCNs) can be acknowledged as one of the most significant methodologies for graph representation learning, and the family of GCNs has recently achieved great success in the community. However, in real-world scenarios, the graph data may be imperfect, e.g., with noisy and sparse features or labels, which poses a great challenge to the robustness of GCNs. To meet this challenge, we propose a simple-yet-effective LAbel-ENhanced Networks (LaenNet) architecture for GCNs, where the basic spirit is to propagate labels together with features. Specifically, we add an extra LaenNet module at one hidden layer of GCNs, which propagates labels along the graph and then integrates them with the hidden representations as the inputs to the deeper layer. The proposed LaenNet can be directly generalized to the variants of GCNs. We conduct extensive experiments to verify LaenNet on semi-supervised node classification tasks under four noisy and sparse graph data scenarios, including the graphs with noisy features, sparse features, noisy labels, and sparse labels. Empirical results indicate the superiority and robustness of LaenNet compared to the state-of-the-art baseline models. The implementation code is available to ease reproducibility1.

CT-based dosiomics and radiomics model predicts radiation-induced lymphopenia in nasopharyngeal carcinoma patients

Purpose

This study aims to develop and validate a model predictive for the incidence of grade 4 radiation-induced lymphopenia (G4RIL), based on dosiomics features and radiomics features from the planning CT of nasopharyngeal carcinoma (NPC) treated by radiation therapy.

Methods

The dataset of 125 NPC patients treated with radiotherapy from August 2018 to March 2019 was randomly divided into two sets-an 85-sample training set and a 40-sample test set. Dosiomics features and radiomics features of the CT image within the skull bone and cervical vertebrae were extracted. A feature selection process of multiple steps was employed to identify the features that most accurately forecast the data and eliminate superfluous or insignificant ones. A support vector machine learning classifier with correction for imbalanced data was trained on the patient dataset for prediction of RIL (positive classifier for G4RIL, negative otherwise). The model's predictive capability was gauged by gauging its sensitivity (the likelihood of a positive test being administered to patients with G4RIL) and specificity in the test set. The area beneath the ROC curve (AUC) was utilized to explore the association of characteristics with the occurrence of G4RIL.

Results

Three clinical features, three dosiomics features, and three radiomics features exhibited significant correlations with G4RIL. Those features were then used for model construction. The combination model, based on nine robust features, yielded the most impressive results with an ACC value of 0.88 in the test set, while the dosiomics model, with three dosiomics features, had an ACC value of 0.82, the radiomics model, with three radiomics features, had an ACC value of 0.82, and the clinical model, with its initial features, had an ACC value of 0.6 for prediction performance.

Conclusion

The findings show that radiomics and dosiomics features are correlated with the G4RIL of NPC patients. The model incorporating radiomics features and dosiomics features from planning CT can predict the incidence of G4RIL in NPC patients.

Photodynamic Therapy Combined with Ferroptosis Is a Synergistic Antitumor Therapy Strategy

Ferroptosis is a programmed death mode that regulates redox homeostasis in cells, and recent studies suggest that it is a promising mode of tumor cell death. Ferroptosis is regulated by iron metabolism, lipid metabolism, and intracellular reducing substances, which is the mechanism basis of its combination with photodynamic therapy (PDT). PDT generates reactive oxygen species (ROS) and 1O2 through type I and type II photochemical reactions, and subsequently induces ferroptosis through the Fenton reaction and the peroxidation of cell membrane lipids. PDT kills tumor cells by generating excessive cytotoxic ROS. Due to the limited laser depth and photosensitizer enrichment, the systemic treatment effect of PDT is not good. Combining PDT with ferroptosis can compensate for these shortcomings. Nanoparticles constructed by photosensitizers and ferroptosis agonists are widely used in the field of combination therapy, and their targeting and biological safety can be improved through modification. These nanoparticles not only directly kill tumor cells but also further exert the synergistic effect of PDT and ferroptosis by activating antitumor immunity, improving the hypoxia microenvironment, and inhibiting the tumor angiogenesis. Ferroptosis-agonist-induced chemotherapy and PDT-induced ablation also have good clinical application prospects. In this review, we summarize the current research progress on PDT and ferroptosis and how PDT and ferroptosis promote each other.

[Application effects of 3D visualization reconstruction technique in pheochromocytoma/ paraganglioma surgery]

To investigate the value of 3D visualization reconstruction technology in pheochromocytoma/paraganglioma surgery.The clinical data of 87 patients with pheochromocytoma/paraganglioma admitted to the Department of Urology of Peking Union Medical College Hospital between January 2019 and December 2022 were retrospectively analyzed, and 3D visualization model reconstruction was performed preoperatively in 47 patients [Group A:males was 24 cases,the age M(Q1, Q3)42.00(30.00, 54.00)]. while the remaining 40 patients [Group B: males was 23 cases,the age M(Q1, Q3) 44.00(30.25, 53.75)] was not. The maximum tumor diameter, operation time, intraoperative bleeding, drain retention time and postoperative hospital stay were compared between the two groups. Surgery was successfully completed in both groups. 37 (78.7%) patients in group A underwent laparoscopic surgery, 7 (14.9%) patients underwent open surgery, and 3 (6.4%) patients underwent laparoscopic-to-open surgery. Thirty-one (77.5%) patients in group B underwent laparoscopic surgery, 5 (12.5%) patients underwent open surgery, and 4 (10.0%) patients underwent laparoscopic to open surgery. There was a difference in the maximum diameter of the tumor between the two groups [(6.09±3.02) cm vs (5.32±1.76) cm, P<0.05], the retention time of the drainage tube was significantly shorter in group A compared with group B [(3.20±1.38) d vs (4.02±1.98) d, P<0.05], and the length of the hospital stay after surgery was significantly shorter [(5.75±2.12) d vs (6.49±3.37) d, P<0.05]. Comparison of operation time and intraoperative bleeding between the two groups showed no statistically significant difference (P>0.05).Two cases of postoperative anemia and one case of pulmonary atelectasis in group B patients improved before discharge. Conclusion when the tumor diameter is>6 cm or has a close relationship with the surrounding organs and blood vessels, the use of 3D visual reconstruction technology can formulate and implement a more accurate and safe surgical plan, shorten the retention time of the drainage tube and postoperative hospitalization time, which is conducive to the patient's postoperative recovery and reduce postoperative complications.

Insight into the enhancement effect of amino functionalized carbon nanotubes on the H2S removal performance of nanofluid system

By constructing nanofluid system, trace functionalized nanoparticles can significantly enhance the absorption performance of basic liquid. In this work, amino functionalized carbon nanotubes (ACNTs) and carbon nanotubes (CNTs) were introduced into alkaline deep eutectic solvents to build nanofluid systems and used for the dynamic absorption of H2S. The experiment results showed that the introduction of nanoparticles can significantly enhance the H2S removal performance of original liquid. When performing H2S removal experiments, the optimal mass concentrations of ACNTs versus CNTs were 0.05 % and 0.01 %, respectively. The characterization showed that the surface morphology and structure of the nanoparticles unchanged significantly during the absorption-regeneration process. A double mixed gradientless gas-liquid reactor was used to explore the gas-liquid absorption kinetics characteristics of the nanofluid system. It was found that the gas-liquid mass transfer rate increased significantly after the addition of nanoparticles. The highest total mass transfer coefficient of the nanofluid system of ACNTs was increased to more than 400 % of the value before the addition of nanoparticles. The analysis showed that the shuttle effect and hydrodynamic effect of nanoparticles play important role in the process of enhancing gas-liquid absorption, and the amino functionalization enhanced the shuttle effect of nanoparticles significantly.

MRI radiomics for brain metastasis sub-pathology classification from non-small cell lung cancer: a machine learning, multicenter study

The objective of this study is to develop a machine-learning model that can accurately distinguish between different histologic types of brain lesions in patients with non-small cell lung cancer (NSCLC) when it is not safe or feasible to perform a biopsy. To achieve this goal, the study utilized data from two patient cohorts: 116 patients from Xiangya Hospital and 35 patients from Yueyang Central Hospital. A total of eight machine learning algorithms, including Xgboost, were compared. Additionally, a 3-dimensional convolutional neural network was trained using transfer learning to further evaluate the performance of these models. The SHapley Additive exPlanations (SHAP) method was developed to determine the most important features in the best-performing model after hyperparameter optimization. The results showed that the area under the curve (AUC) for the classification of brain lesions as either lung adenocarcinoma or squamous carcinoma ranged from 0.60 to 0.87. The model based on single radiomics features extracted from contrast-enhanced T1 MRI and utilizing the Xgboost algorithm demonstrated the highest performance (AUC: 0.85) in the internal validation set and adequate performance (AUC: 0.80) in the independent external validation set. The SHAP values also revealed the impact of individual features on the classification results. In conclusion, the use of a radiomics model incorporating contrast-enhanced T1 MRI, Xgboost, and SHAP algorithms shows promise in accurately and interpretably identifying brain lesions in patients with NSCLC.

Erratum: Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV [Phys. Rev. Lett. 126, 162301 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.126.162301.

CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma

Background

To predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.

Methods

This study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.

Results

To predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.

Conclusions

This study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

Rutaecarpine induces the differentiation of triple-negative breast cancer cells through inhibiting fumarate hydratase

BACKGROUND

Triple-negative breast cancer (TNBC) is one of the most aggressive human cancers and has poor prognosis. Approximately 80% of TNBC cases belong to the molecular basal-like subtype, which can be exploited therapeutically by inducing differentiation. However, the strategies for inducing the differentiation of TNBC remain underexplored.

METHODS

A three-dimensional (3D) morphological screening model based on a natural compound library was used to identify possible candidate compounds that can induce TNBC cell differentiation. The efficacy of rutaecarpine was verified using assays: RT-qPCR, RNA-seq, flow cytometry, immunofluorescence, SCENITH and label-free LC-MS/MS. The direct targets of rutaecarpine were identified through drug affinity responsive target stability (DARTS) assay. A xenograft mice model was also constructed to confirm the effect of rutaecarpine in vivo.

RESULTS

We identified that rutaecarpine, an indolopyridoquinazolinone, induces luminal differentiation of basal TNBC cells in both 3D spheroids and in vivo mice models. Mechanistically, rutaecarpine treatment leads to global metabolic stress and elevated ROS in 3D cultured TNBC cells. Moreover, NAC, a scavenger of ROS, impedes rutaecarpine-induced differentiation of TNBC cells in 3D culture. Finally, we identified fumarate hydratase (FH) as the direct interacting target of rutaecarpine. The inhibition of FH and the knockdown of FH consistently induced the differentiation of TNBC cells in 3D culture.

CONCLUSIONS

Our results provide a platform for differentiation therapy drug discovery using 3D culture models and identify rutaecarpine as a potential compound for TNBC treatment.

Poly(ether ether ketone) Conferred Polyolefin Separators with High Dimensional Thermal Stability for Lithium-Ion Batteries

The traditional polyolefin separators used in lithium-ion batteries (LIBs) are plagued by limitations such as poor wetting of electrolytes and insufficient thermal stability, hindering the progress of LIBs. To overcome these limitations, we have developed a modified phase inversion technique to efficiently and durably coat polyolefin separators with poly(ether ether ketone) (PEEK). The resulting PEEK-coated polyolefin separators exhibit mechanical properties similar to those of unmodified polyolefin separators, with comparable tensile strength and modulus. Furthermore, the PEEK coating provides outstanding thermal stability, as the modified separators maintain their stability even at temperatures up to 200 °C, which is among the best results reported for polyolefin-based separators. In addition, the PEEK coating enhances ionic conductivity by more than 100% compared to polyolefin counterparts, leading to significant improvement in the electrochemical performance of prototype half cells. The modified phase inversion technique presented here offers a practical solution for coating polyolefin separators with functional polymers, paving the way for next-generation separator materials.

Computational modeling of hemodynamics and risk of thrombosis in the left atrial appendage using patient-specific blood viscosity and boundary conditions at the mitral valve

Hemodynamics play a vital role for the risk of thrombosis in the left atrial appendage (LAA) and left atrium (LA) for patients with atrial fibrillation. Accurate prediction of hemodynamics in the LA can provide important guidance for assessing the risk of thrombosis in the LAA. Patient specificity is a crucial factor in representing the true hemodynamic fields. In this study, we investigated the effects of blood rheology (as a function of hematocrit and shear rate), as well as patient-specific mitral valve (MV) boundary conditions (MV area and velocity profiles measured by ultrasound) on the hemodynamics and thrombosis potential of the LAA. Four scenarios were setup with different degrees of patient specificity. Though using a constant blood viscosity can classify the thrombus and non-thrombus patients for all the hemodynamic indicators, the risk of thrombosis was underestimated for all patients compared with patient-specific viscosities. The results with least patient specificities showed that patients prone to thrombosis predicted by three hemodynamic indicators were inconsistent with clinical observations. Moreover, though patients had the same MV inlet flow rate, different MV models lead to different trends in the risk of thrombosis in different patients. We also found that endothelial cell activation potential and relative residence time can effectively distinguish thrombus and non-thrombus patients for all the scenarios, relatively insensitive to patient specificities. Overall, the findings of this study provide useful insights on patients-specific hemodynamic simulations of the LA.

Evolutionarily divergent mTOR remodels translatome for tissue regeneration

An outstanding mystery in biology is why some species, such as the axolotl, can regenerate tissues whereas mammals cannot1. Here, we demonstrate that rapid activation of protein synthesis is a unique feature of the injury response critical for limb regeneration in the axolotl (Ambystoma mexicanum). By applying polysome sequencing, we identify hundreds of transcripts, including antioxidants and ribosome components that are selectively activated at the level of translation from pre-existing messenger RNAs in response to injury. By contrast, protein synthesis is not activated in response to non-regenerative digit amputation in the mouse. We identify the mTORC1 pathway as a key upstream signal that mediates tissue regeneration and translational control in the axolotl. We discover unique expansions in mTOR protein sequence among urodele amphibians. By engineering an axolotl mTOR (axmTOR) in human cells, we show that these changes create a hypersensitive kinase that allows axolotls to maintain this pathway in a highly labile state primed for rapid activation. This change renders axolotl mTOR more sensitive to nutrient sensing, and inhibition of amino acid transport is sufficient to inhibit tissue regeneration. Together, these findings highlight the unanticipated impact of the translatome on orchestrating the early steps of wound healing in a highly regenerative species and provide a missing link in our understanding of vertebrate regenerative potential.

A Comparative Study of the Effects of Whole Cereals and Refined Cereals on Intestinal Microbiota

Cereals are one of the most important foods on which human beings rely to sustain basic life activities and are closely related to human health. This study investigated the effects of different steamed buns on intestinal microbiota. Three steamed buns were prepared using refined flour (RF), 1:1 mixed flour (MF), and whole wheat flour (WF). In vitro digestion simulations were conducted using a bionic gastrointestinal reactor (BGR) to examine their influence on intestinal microbiota. The results showed that at 0.5% addition, butyric acid and short-chain fatty acids in WF were significantly different from those in RF and MF (p < 0.05). WF also promoted the proliferation of beneficial microbiota, such as Megamonas and Subdoligranulum. At 0.5%, 1.0%, and 1.5% additions of WF, acetic acid and short-chain fatty acids at 1.5% WF increased by 1167.5% and 11.4% from 0.5% WF, respectively, and by 20.2% and 7.6% from 1.0% WF, respectively. WF also promoted the proliferation of Bifidobacterium, Lactobacillus, and Bacteroides and inhibited the growth of pathogenic microbiota, such as Streptococcus, Enterococcus, and Klebsiella. These findings support the consumption of whole cereals and offer insights into the development of new functional foods derived from wheat.

Crosstalk among T cells, epithelial cells, and fibroblasts identifies a prognostic signature in oral squamous cell carcinoma

OBJECTIVES

This study aimed to analyze the crosstalk network among T cells, epithelial cells, and fibroblasts in the tumor microenvironment of oral squamous cell carcinoma (OSCC) and to determine their prognostic values.

MATERIALS AND METHODS

Single-cell subpopulation identification and communication analysis identified crosstalk markers. The least absolute shrinkage and selection operator Cox analysis identified key prognostic features by integrating the bulk transcriptome and clinical parameters. Functional analysis and immune infiltration were explored to determine possible mechanisms.

RESULTS

Interactions between epithelial cells and fibroblasts primarily involve MIF, MK, PTN, IGF, EGF, and PERIOSTIN, whereas T cells interact with epithelial cells and fibroblasts through MIF, CXCL, PAR, IFN, and EGF signals. We constructed a novel prognostic feature comprising 13 crosstalk genes: HBEGF, FGF7, GRN, ITGB5, CXCR6, ERBB2, AREG, F2RL2, NAMPT, KLK12, HMGB2, TUBA1B, and KLRD1. Patients were stratified based on the RiskScore. Functional analysis revealed that the high-risk group was enriched in immunosuppressive pathways (p < 0.001). Immune checkpoints including PD-1, PD-L1, and CTLA4 were more highly expressed in the high-risk group (p < 0.05).

CONCLUSIONS

The crosstalk network among T cells, epithelial cells, and fibroblasts is complex and may have implications for prognosis and clinical treatments of OSCC patients.

Prognosis prediction and comparison between pancreatic signet ring cell carcinoma and pancreatic duct adenocarcinoma: a retrospective observational study

Background

Pancreatic signet ring cell carcinoma (PSRCC) is a rare and aggressive cancer that has been reported primarily as case reports. Due to limited large-scale epidemiological and prognostic analyses, the outcomes of PSRCC patients varies greatly in the absence of recognized first-line treatment strategies. This study aimed to compare the clinical features, treatment, and prognosis of PSRCC and pancreatic ductal cell carcinoma (PDAC), the most common subtype of pancreatic cancer, and to establish predictive models for these subtypes.

Methods

The data on PSRCC and PDAC patients from 1998 to 2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Thereafter, the clinical, demographic, and treatment characteristics of the two groups and the differences and influencing factors of the two groups were evaluated by propensity score matching (PSM), Kaplan-Meier survival curves, Cox risk regression analyses, and least absolute shrinkage and selection operator (LASSO) analysis. Next, prognosis models were constructed and validated by KM and ROC analysis. Finally, a nomogram was constructed, based on the results of these analyses, to predict survival outcomes of PSRCC and PDAC patients.

Results

A total of 84,789 patients (432 PSRCC and 84357 PDAC patients) were included in this study. The results of the study revealed that, compared to the PDAC patients, PSRCC patients were more likely to be male, aged between 58-72 years, have larger tumor masses, and less likely to undergo chemotherapy. Before PSM, the overall survival and cancer-specific survival of the PSRCC group were significantly lower than those PDAC group, but there was no difference in the prognosis of the two groups after PSM. Additionally, lymph node ratio (LNR), log odds of positive lymph node (LODDS), tumor size, age, T-stage, marital status, and summary stage were found to be independent prognostic factors for PSRCC. Lastly, the prediction model and nomogram based on these prognostic factors could accurately predict the survival rate of the patients in SEER datasets and external validation datasets.

Conclusion

The prognosis of PSRCC and PDAC patients is similar under the same conditions; however, PSRCC patients may have more difficulty in receiving better treatment, thus resulting in their poor prognosis.

Bifunctional defect mediated direct Z-scheme g-C3N4-x/Bi2O3-y heterostructures with enhanced piezo-photocatalytic properties for efficient tooth whitening and biofilm eradication

Biofilm-associated dental diseases and tooth discoloration have recently become the major barriers to achieve healthy teeth. However, there are few effective strategies to address these issues. Herein, the piezo-photocatalytic process is first proposed to be applied for biofilm eradication and tooth whitening with well-designed direct Z scheme g-C₃N_4-x/Bi₂O_3-y heterostructures. DFT calculation and XPS results verify the formation of direct Z scheme g-C₃N₄/Bi₂O₃ heterostructures theoretically and experimentally. Using the direct Z scheme g-C₃N_4-x/Bi₂O_3-y heterostructure, excellent piezo-photocatalytic effects for tooth whitening and biofilm removal are achieved. For piezo-photocatalytic degradation of the typical food colorant of indigo carmine the degradation rate constant is about quadruple that of piezocatalytic and 2.6 times of photocatalytic treatment. Tooth whitening experiments indicate that g-C₃N_4-x/Bi₂O_3-y could whiten the stained teeth through the synergistic piezo-photocatalysis. In addition, excellent antibacterial performances can be obtained on the g-C₃N_4-x/Bi₂O_3-y heterostructure through piezo-photocatalytic treatment. Not only the planktonic S. mutans but also those bacteria embedded in biofilms can be effectively killed. The analyses of the piezo-photocatalytic mechanism indicates that the enhanced piezo-photocatalytic performance of the g-C₃N_4-x/Bi₂O_3-y heterostructure could be attributed to the much higher separation efficiency of photoexcited charge carriers, increased production amounts of ROS and superior adsorption ability for bacteria than those with bare semiconductors of g-C₃N_4-x and Bi₂O_3-y and those treated only with ultrasonic vibration or irradiation. Biosafety results show that the g-C₃N_4-x/Bi₂O_3-y heterostructure is biologically safe and piezo-photocatalytic treatment has no harm the tooth structure, demonstrating the great potential of piezo-photocatalytic effect based new tooth whitening and antibacterial technology in future dental care fields.

Rapid imaging and product screening with low-cost line-field Fourier domain optical coherence tomography

Fourier domain optical coherence tomography (FD-OCT) is a well-established imaging technique that provides high-resolution internal structure images of an object at a fast speed. Modern FD-OCT systems typically operate at speeds of 40,000-100,000 A-scans/s, but are priced at least tens of thousands of pounds. In this study, we demonstrate a line-field FD-OCT (LF-FD-OCT) system that achieves an OCT imaging speed of 100,000 A-scan/s at a hardware cost of thousands of pounds. We demonstrate the potential of LF-FD-OCT for biomedical and industrial imaging applications such as corneas, 3D printed electronics, and printed circuit boards.

Discovery of 1H-Imidazo[4,5-b]pyridine Derivatives as Potent and Selective BET Inhibitors for the Management of Neuropathic Pain

Neuropathic pain (NP) is an intolerable pain syndrome that arises from continuous inflammation and excitability after nerve injury. Only a few NP therapeutics are currently available, and all of them do not provide adequate pain relief. Herein, we report the discovery of a selective and potent inhibitor of the bromodomain and extra-terminal (BET) proteins for reducing neuroinflammation and excitability to treat NP. Starting with the screening hit 1 from an in-house compound library, iterative optimization resulted in the potent BET inhibitor DDO-8926 with a unique binding mode and a novel chemical structure. DDO-8926 exhibits excellent BET selectivity and favorable drug-like properties. In mice with spared nerve injury, DDO-8926 significantly alleviated mechanical hypersensitivity by inhibiting pro-inflammatory cytokine expression and reducing excitability. Collectively, these results implicate that DDO-8926 is a promising agent for the treatment of NP.

Rational design of a glycopeptide probe system based on a reconfigurable immune microenvironment

Glioma is a highly challenging human malignancy and conventional drugs typically exhibit low blood-brain barrier (BBB) permeability as well as poor tumor targeting. To complicate matters further, recent advances in research on oncology have highlighted the dynamic and complex cellular networks within the immunosuppressive tumor microenvironment (TME) that complicate glioma treatment. Therefore, precise and efficient targeting of tumor tissue, whilst reversing immunosuppression, may provide an ideal strategy for the treatment of gliomas. Here, by using the "one-bead-one-component" combinatorial chemistry approach, we designed and screened a peptide that can specifically target brain glioma stem cells (GSCs), which was further engineered into glycopeptide-functionalized multifunctional micelles. We demonstrated that the micelles can carry DOX and effectively penetrate the BBB to achieve targeted killing of glioma cells. Meanwhile, mannose confers a unique tumor immune microenvironment modulating function to the micelles, which can activate the anti-tumor immune response function of tumor-associated macrophages and is expected to be further applied in vivo. This study highlights that glycosylation modification of targeted peptides specific to cancer stem cells (CSCs) may serve as an effective tool to improve the therapeutic outcome of brain tumor patients.