Mitochondria-Targetable Near-Infrared Fluorescent Probe for Visualization of Hydrogen Peroxide in Lung Injury, Liver Injury, and Tumor Models.

Hydrogen peroxide (H2O2) overexpressed in mitochondria has been regarded as a key biomarker in the pathological processes of various diseases. However, there is currently a lack of suitable mitochondria-targetable near-infrared (NIR) probes for the visualization of H2O2 in multiple diseases, such as PM2.5 exposure-induced lung injury, hepatic ischemia-reperfusion injury (HIRI), nonalcoholic fatty liver (NAFL), hepatic fibrosis (HF), and malignant tumor tissues containing clinical cancer patient samples. Herein, we conceived a novel NIR fluorescent probe (HCy-H2O2) by introducing pentafluorobenzenesulfonyl as a H2O2 sensing unit into the NIR hemicyanine platform. HCy-H2O2 exhibits good sensitivity and selectivity toward H2O2, accompanied by a remarkable "turn-on" fluorescence signal at 720 nm. Meanwhile, HCy-H2O2 has stable mitochondria-targetable ability and permits monitoring of the up-generated H2O2 level during mitophagy. Furthermore, using HCy-H2O2, we have successfully observed an overproduced mitochondrial H2O2 in ambient PM2.5 exposure-induced lung injury, HIRI, NAFL, and HF models through NIR fluorescence imaging. Significantly, the visualization of H2O2 has been achieved in both tumor-bear mice as well as surgical specimens of cancer patients, making HCy-H2O2 a promising tool for cancer diagnosis and imaging-guided surgery.

Additive-free Absorbable Keratin Sponge With Procoagulant Activity for Noncompressible Hemostasis.

The development of a natural, additive-free, absorbable sponge with procoagulant activity for noncompressible hemostasis remains a challenging task. In this study, we extracted high molecular weight keratin (HK) from human hair and transformed it into a hemostatic sponge with a well-interconnected pore structure using a foaming technique, freeze-drying, and oxidation cross-linking. By controlling the cross-linking degree, the resulting sponge demonstrated excellent liquid absorption ability, shape recovery characteristics, and robust mechanical properties. The HK10 sponge exhibited rapid liquid absorption, expanding up to 600% within 5 s. Moreover, the HK sponge showed superior platelet activation and blood cell adhesion capabilities. In SD rat liver defect models, the sponges demonstrated excellent hemostatic performance by sealing the wound and expediting coagulation, reducing the hemostatic time from 825 to 297 s. Furthermore, HK sponges have excellent biosafety, positioning them as a promising absorbable sponge with the potential for the treatment of noncompressible hemostasis.

NIR-II nanoprobes for investigating the glymphatic system function under anesthesia and stroke injury.

The glymphatic system plays an important role in the transportation of cerebrospinal fluid (CSF) and the clearance of metabolite waste in brain. However, current imaging modalities for studying the glymphatic system are limited. Herein, we apply NIR-II nanoprobes with non-invasive and high-contrast advantages to comprehensively explore the function of glymphatic system in mice under anesthesia and cerebral ischemia-reperfusion injury conditions. Our results show that the supplement drug dexmedetomidine (Dex) enhances CSF influx in the brain, decreases its outflow to mandibular lymph nodes, and leads to significant differences in CSF accumulation pattern in the spine compared to isoflurane (ISO) alone, while both ISO and Dex do not affect the clearance of tracer-filled CSF into blood circulation. Notably, we confirm the compromised glymphatic function after cerebral ischemia-reperfusion injury, leading to impaired glymphatic influx and reduced glymphatic efflux. This technique has great potential to elucidate the underlying mechanisms between the glymphatic system and central nervous system diseases.

Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting.

One of the important non-engineering measures for flood forecasting and disaster reduction in watersheds is the application of machine learning flood prediction models, with Long Short-Term Memory (LSTM) being one of the most representative time series prediction models. However, the LSTM model has issues of underestimating peak flows and poor robustness in flood forecasting applications. Therefore, based on a thorough analysis of complex underlying surface attributes, this study proposes a framework for distinguishing runoff models and integrates a Grid-based Runoff Generation Model (GRGM). Simultaneously considering the time series characteristics of runoff processes, including rising, peak, and recession, a runoff process vectorization (RPV) method is proposed. In this study, a hybrid deep learning flood forecasting framework, GRGM-RPV-LSTM, is constructed by coupling the GRGM, RPV, and LSTM neural network models. Taking the Jialu River in the Zhongmu station control basin as an example, the model is validated using 18 instances of measured floods and compared with the LSTM and GRGM-LSTM models. The study shows that the GRGM model has a relative error and average coefficient of determination for simulating runoff of 8.41% and 0.976, respectively, indicating that considering the spatial distribution of runoff patterns leads to more accurate runoff calculations. Under the same lead time conditions, the GRGM-RPV-LSTM hybrid forecasting model has a Nash efficiency coefficient greater than 0.9, demonstrating better simulation performance compared to the GRGM-LSTM and LSTM models. As the lead time increases, the GRGM-RPV-LSTM model provides more accurate peak flow predictions and exhibits better robustness. The research findings can provide scientific basis for coordinated management of flood control and disaster reduction in watersheds.

Research on runoff process vectorization and integration of deep learning algorithms for flood forecasting.

Accurate multi-step ahead flood forecasting is crucial for flood prevention and mitigation efforts as well as optimizing water resource management. In this study, we propose a Runoff Process Vectorization (RPV) method and integrate it with three Deep Learning (DL) models, namely Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), and Transformer, to develop a series of RPV-DL flood forecasting models, namely RPV-LSTM, RPV-TCN, and RPV-Transformer models. The models are evaluated using observed flood runoff data from nine typical basins in the middle Yellow River region. The key findings are as follows: Under the same lead time conditions, the RPV-DL models outperform the DL models in terms of Nash-Sutcliffe efficiency coefficient, root mean square error, and relative error for peak flows in the nine typical basins of the middle Yellow River region. Based on the comprehensive evaluation results of the train and test periods, the RPV-DL model outperforms the DL model by an average of 2.82%-22.21% in terms of NSE across nine basins, with RMSE and RE reductions of 10.86-28.81% and 36.14%-51.35%, respectively. The vectorization method significantly improves the accuracy of DL flood forecasting, and the RPV-DL models exhibit better predictive performance, particularly when the lead time is 4h-6h. When the lead time is 4-6h, the percentage improvement in NSE is 9.77%, 15.07%, and 17.94%. The RPV-TCN model shows superior performance in overcoming forecast errors among the nine basins. The research findings provide scientific evidence for flood prevention and mitigation efforts in river basins.

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning.

Baseflow is a crucial water source in the inland river basins of high-cold mountainous region, playing a significant role in maintaining runoff stability. It is challenging to select the most suitable baseflow separation method in data-scarce high-cold mountainous region and to evaluate effects of climate factors and underlying surface changes on baseflow variability and seasonal distribution characteristics. Here we attempt to address how meteorological factors and underlying surface changes affect baseflow using the Grey Wolf Optimizer Digital Filter Method (GWO-DFM) for rapid baseflow separation and the Long Short-Term Memory (LSTM) neural network model for baseflow prediction, clarifying interpretability of the LSTM model in baseflow forecasting. The proposed method was successfully implemented using a 63-year time series (1958-2020) of flow data from the Tai Lan River (TLR) basin in the high-cold mountainous region, along with 21 years of ERA5-land meteorological data and MODIS data (2000-2020). The results indicate that: (1) GWO-DFM can rapidly identify the optimal filtering parameters. It employs the arithmetic average of three methods, namely Chapman, Chapman-Maxwell and Eckhardt filter, as the best baseflow separation approach for the TLR basin. Additionally, the baseflow significantly increases after the second mutation of the baseflow rate. (2) Baseflow sources are mainly influenced by precipitation infiltration, glacier frozen soil layers, and seasonal ponding. (3) Solar radiation, temperature, precipitation, and NDVI are the primary factors influencing baseflow changes, with Nash-Sutcliffe efficiency coefficients exceeding 0.78 in both the LSTM model training and prediction periods. (4) Changes in baseflow are most influenced by solar radiation, temperature, and NDVI. This study systematically analyzes the changes in baseflow and response mechanisms in high-cold mountainous region, contributing to the management of water resources in mountainous basins under changing environmental conditions.

Lymphomatoid granulomatosis with the central nervous system involvement as the main manifestation: a case report.

BACKGROUND: Lymphomatoid granulomatosis (LyG) is a rare extralymphatic lymphoproliferative disease characterized by lymphocytic invasion into vascular walls and damage to blood vessels. The lungs are affected in 90% of LyG cases, followed by the skin, central nervous system (CNS), kidneys and liver. CASE PRESENTATION: Here we report a case of a young woman with LyG, with CNS involvement as the initial clinical manifestation. Computer tomography (CT) scans showed multiple nodular, patchy and flocculent high-density shadows in both lungs without mediastinal lymph node enlargement. Magnetic resonance imaging (MRI) scans showed multiple abnormal signal intensities in the right cerebellar hemisphere, frontal, parietal and temporal lobes, and dorsal brainstem, which became patchy and annular after enhancement. The post-operative pathological analysis of lesion samples confirmed the diagnosis of grade II LyG. CONCLUSIONS: LyG should be concerned in young adults showing multiple radiological brain and lung lesions. Resection and postoperative medication of steroid hormones and IFN-α may be effective in the treatment of LyG.

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional region.

In recent years, urban flood disasters caused by sudden heavy rains have become increasingly severe, posing a serious threat to urban public infrastructure and the life and property safety of residents. Rapid simulation and prediction of urban rain-flood events can provide timely decision-making reference for urban flood control and disaster reduction. The complex and arduous calibration process of urban rain-flood models has been identified as a major obstacle affecting the efficiency and accuracy of simulation and prediction. This study proposes a multi-scale urban rain-flood model rapid construction method framework, BK-SWMM, focusing on urban rain-flood model parameters and based on the basic architecture of Storm Water Management Model (SWMM). The framework comprises two main components: 1) constructing a SWMM uncertainty parameter sample crowdsourcing dataset and coupling Bayesian Information Criterion (BIC) and K-means clustering machine learning algorithm to discover clustering patterns of SWMM model uncertainty parameters in urban functional areas; 2) coupling BIC and K-means with SWMM model to form BK-SWMM flood simulation framework. The applicability of the proposed framework is validated by modeling three different spatial scales in the study regions based on observed rainfall-runoff data. The research findings indicate that the distribution pattern of uncertainty parameters, such as depression storage, surface Manning coefficient, infiltration rate, and attenuation coefficient. The distribution patterns of these seven parameters in urban functional zones indicate that the values are highest in the Industrial and Commercial Areas (ICA), followed by Residential Areas (RA), and lowest in Public Areas (PA). All three spatial scales' REQ, NSEQ, and RD2 indices were superior to the SWMM and less than 10%, greater than 0.80, and greater than 0.85, respectively. However, when the study area's geographical scale expands, the simulation's accuracy will decline. Further research is required on the scale dependency of urban storm flood models.

A novel adoptive synthetic TCR and antigen receptor (STAR) T-Cell therapy for B-Cell acute lymphoblastic leukemia.

We developed a T-cell-receptor (TCR) complex-based chimeric antigen receptor (CAR) named Synthetic TCR and Antigen Receptor (STAR). Here, we report pre-clinical and phase I clinical trial data (NCT03953599) of this T-cell therapy for refractory and relapsed (R/R) B-cell acute lymphoblastic leukemia (B-ALL) patients. STAR consists of two protein modules each containing an antibody light or heavy chain variable region and TCR α or ß chain constant region fused to the co-stimulatory domain of OX40. T-cells were transduced with a STAR-OX40 lentiviral vector. A leukemia xenograft mouse model was used to assess the STAR/STAR-OX40 T cell antitumor activity. Eighteen patients with R/R B-ALL were enrolled into the clinical trial. In a xenograft mouse model, STAR-T-cells exhibited superior tumor-specific cytotoxicity compared with conventional CAR-T cells. Incorporating OX40 into STAR further improved the proliferation and persistence of tumor-targeting T-cells. In our clinical trial, 100% of patients achieved complete remission 4 weeks post-STAR-OX40 T-cell infusion and 16/18 (88.9%) patients pursued consolidative allogeneic hematopoietic stem cell transplantation (allo-HSCT). Twelve of 16 patients (75%) remained leukemia-free after a median follow-up of 545 (433-665) days. The two patients without consolidative allo-HSCT relapsed on Day 58 and Day 186. Mild cytokine release syndrome occurred in 10/18 (55.6%) patients, and 2 patients experienced grade III neurotoxicity. Our preclinical studies demonstrate super anti-tumor potency of STAR-OX40 T-cells compared with conventional CAR-T cells. The first-in-human clinical trial shows that STAR-OX40 T-cells are tolerable and an effective therapeutic platform for treating R/R B-ALL.

Different Lewis Acid Promotor-Steered Highly Regioselective Phosphorylation of Tertiary Enamides.

Different Lewis acid promotor-steered highly regioselective phosphorylation of tertiary enamides with diverse H-phosphonates or H-phosphine oxides was developed. Under the catalysis of iron salt, the phosphonyl group was introduced into the α-position of tertiary enamides, affording various α-phosphorylated amides in high efficiency. On the other hand, the ß-phosphorylated tertiary enamides were efficiently obtained as the products in the presence of manganese(III) acetylacetonate.

Synthesis of Diverse Pentasubstituted Pyrroles by a Gold(I)-Catalyzed Cascade Rearrangement-Cyclization of Tertiary Enamide.

An efficient Au(I)-catalyzed intramolecular cascade reaction of tertiary enamides tethered an alkynyl group has been developed. The process is composed of a propargyl-claisen rearrangement and 5-exo-dig cyclization. This protocol provided a powerful method for the preparation of a variety of pentasubstituted pyrroles derivatives with excellent functional group tolerance in excellent yields. Scale-up experiment and chemical transformations of products exhibited the versatility of tertiary enamides in organic synthesis again.

Manganese(III)-promoted highly stereoselective phosphorylation of acyclic tertiary enamides to synthesize E-selective ß-phosphoryl enamides.

A concise manganese(III)-promoted stereoselective ß-phosphorylation of acyclic tertiary enamides and diverse H-phosphine oxides was achieved. This reaction proceeds with absolute E-selectivity in contrast to Z-selectivity obtained in other previous works and affords various E-selective ß-phosphorylated tertiary enamides in high efficiency. To the best of our knowledge, this is the first case of E-selective ß-phosphorylation of tertiary enamides through C-H functionalization. In addition, the method features broad substrate scope, good functional group compatibility and efficient scale-up.

Diverse privileged N-polycyclic skeletons accessed from a metal-free cascade cyclization reaction.

An exquisite metal-free cascade cyclization reaction of 2-acylbenzoic acids with amines was developed, which provided a powerful method for the one-pot synthesis of diverse isoindoloisoquinoline and benzoindolizinoindole derivatives. This protocol avoided the use of metal catalysts, proceeded with high efficiency and had broad substrate scope. These resulting products could be transformed into tertiary amines under the reduction of LiAlH4/AlCl3, followed by the Hofmann elimination offering lots of nitrogen-containing nine-membered ring compounds in excellent yields. All synthesized products containing fused N-polycyclic skeletons were difficult to be constructed using traditional methods and they have a wide range of applications in the pharmaceutical area.

Therapeutic potential of menstrual blood-derived endometrial stem cells in cardiac diseases.

Despite significant developments in medical and surgical strategies, cardiac diseases remain the leading causes of morbidity and mortality worldwide. Numerous studies involving preclinical and clinical trials have confirmed that stem cell transplantation can help improve cardiac function and regenerate damaged cardiac tissue, and stem cells isolated from bone marrow, heart tissue, adipose tissue and umbilical cord are the primary candidates for transplantation. During the past decade, menstrual blood-derived endometrial stem cells (MenSCs) have gradually become a promising alternative for stem cell-based therapy due to their comprehensive advantages, which include their ability to be periodically and non-invasively collected, their abundant source material, their ability to be regularly donated, their superior proliferative capacity and their ability to be used for autologous transplantation. MenSCs have shown positive therapeutic potential for the treatment of various diseases. Therefore, aside from a brief introduction of the biological characteristics of MenSCs, this review focuses on the progress being made in evaluating the functional improvement of damaged cardiac tissue after MenSC transplantation through preclinical and clinical studies. Based on published reports, we conclude that the paracrine effect, transdifferentiation and immunomodulation by MenSC promote both regeneration of damaged myocardium and improvement of cardiac function.

Efficient Interference Estimation with Accuracy Control for Data-Driven Resource Allocation in Cloud-RAN.

The emerging edge computing paradigm has given rise to a new promising mobile network architecture, which can address a number of challenges that the operators are facing while trying to support growing end user's needs by shifting the computation from the base station to the edge cloud computing facilities. With such powerfully computational power, traditional unpractical resource allocation algorithms could be feasible. However, even with near optimal algorithms, the allocation result could still be far from optimal due to the inaccurate modeling of interference among sensor nodes. Such a dilemma calls for a measurement data-driven resource allocation to improve the total capacity. Meanwhile, the measurement process of inter-nodes' interference could be tedious, time-consuming and have low accuracy, which further compromise the benefits brought by the edge computing paradigm. To this end, we propose a measurement-based estimation solution to obtain the interference efficiently and intelligently by dynamically controlling the measurement and estimation through an accuracy-driven model. Basically, the measurement cost is reduced through the link similarity model and the channel derivation model. Compared to the exhausting measurement method, it can significantly reduce the time cost to the linear order of the network size with guaranteed accuracy through measurement scheduling and the accuracy control process, which could also balance the tradeoff between accuracy and measurement overhead. Extensive experiments based on real data traces are conducted to show the efficiency of the proposed solutions.

[Effects of Early Enteral Immunonutrition on Postoperative Immune Function and Rehabilitation of Patients with Gastric Cancer and Nutritional Risk].

OBJECTIVES: To investigate the effects of early enteral immunonutrition on postoperative immune function and rehabilitation of gastric cancer patients with nutritional risk. METHODS: New hospitalized patients with gastric cancer were evaluated the nutrient status based on NRS 2002. The patients who scored between 3 to 5 points were randomized into two groups(30 cases for each group), and those in experimental group were given 7-d early postoperative enteral immune nutrition, those in control group were given normal nutrition. The immune indexes (CD3+, CD4+, CD8+ and CD4+/CD8+) and nutritional indexes(transferrin, pre-albumin, albumin) were measured before operation and at the 3rd and 7th day postoperatively. In addition, the first flatus time, gastrointestinal adverse reactions and complications, length of hospital stays were compared between the two groups. RESULTS: The level of CD4+/CD8+ and transferrin, pre-albumin, albumin in experimental group were significantly higher than those in control group at the third and seventh day postoperatively (P<0.05).Compared with the control group, the experimental group had shorter first flatus time after surgery, which were (63.5±7.3) h vs. (72.8±8.6 ) h respectively (P<0.05).There were no statistically difference on pneumonia, anastomosis leakage, severe abdominal distension, inflammatory bowel obstruction and total postoperative hospitalization time between the two groups (P>0.05). CONCLUSIONS: Early enteral immunonutrition can effectively promote the recovery of nutritional status and immune function in gastric cancer patients with nutrition risk.

Correction: Surface modification and endothelialization of biomaterials as potential scaffolds for vascular tissue engineering applications.

Correction for 'Surface modification and endothelialization of biomaterials as potential scaffolds for vascular tissue engineering applications' by Xiangkui Ren et al., Chem. Soc. Rev., 2015, DOI: .

Surface modification and endothelialization of biomaterials as potential scaffolds for vascular tissue engineering applications.

Surface modification and endothelialization of vascular biomaterials are common approaches that are used to both resist the nonspecific adhesion of proteins and improve the hemocompatibility and long-term patency of artificial vascular grafts. Surface modification of vascular grafts using hydrophilic poly(ethylene glycol), zwitterionic polymers, heparin or other bioactive molecules can efficiently enhance hemocompatibility, and consequently prevent thrombosis on artificial vascular grafts. However, these modified surfaces may be excessively hydrophilic, which limits initial vascular endothelial cell adhesion and formation of a confluent endothelial lining. Therefore, the improvement of endothelialization on these grafts by chemical modification with specific peptides and genes is now arousing more and more interest. Several active peptides, such as RGD, CAG, REDV and YIGSR, can be specifically recognized by endothelial cells. Consequently, graft surfaces that are modified by these peptides can exhibit targeting selectivity for the adhesion of endothelial cells, and genes can be delivered by targeting carriers to specific tissues to enhance the promotion and regeneration of blood vessels. These methods could effectively accelerate selective endothelial cell recruitment and functional endothelialization. In this review, recent developments in the surface modification and endothelialization of biomaterials in vascular tissue engineering are summarized. Both gene engineering and targeting ligand immobilization are promising methods to improve the clinical outcome of artificial vascular grafts.

GATA-1 directly regulates Nanog in mouse embryonic stem cells.

Nanog safeguards pluripotency in mouse embryonic stem cells (mESCs). Insight into the regulation of Nanog is important for a better understanding of the molecular mechanisms that control pluripotency of mESCs. In a silico analysis, we identify four GATA-1 putative binding sites in Nanog proximal promoter. The Nanog promoter activity can be significantly repressed by ectopic expression of GATA-1 evidenced by a promoter reporter assay. Mutation studies reveal that one of the four putative binding sites counts for GATA-1 repressing Nanog promoter activity. Direct binding of GATA-1 on Nanog proximal promoter is confirmed by electrophoretic mobility shift assay and chromatin immunoprecipitation. Our data provide new insights into the expanded regulatory circuitry that coordinates Nanog expression.

Hesx1 enhances pluripotency by working downstream of multiple pluripotency-associated signaling pathways.

Hesx1, a homeobox gene expressed in embryonic stem cells (ESCs), has been implicated in the core transcription factors governing the pluripotent state. However, data about the underlying mechanism of how Hesx1 is involved in maintaining pluripotency is still scarce. In this study, we find Hesx1 responds to multiple pluripotency-related pathway inhibitors as well as LIF stimulation. Particularly, the expression of Hesx1 can be readily induced by dual inhibition (2i) of glycogen synthase kinase 3 and mitogen-activated protein kinase. Forced expression of Hesx1 can partially compensate for the withdrawal of either LIF or each component of 2i. We also demonstrate that LIF and each inhibitor of 2i can induce Hesx1 independent of one another. We tentatively put forward that Hesx1 is a common downstream target of LIF- and 2i-mediated self-renewal signaling pathways and plays an important role in maintaining ESC identity. Our study extends the methods of identifying the missing crucial factors in establishing ESC pluripotency.