Biosynthetic pathway analysis combined with feature-based molecular networking to comprehensively characterize the chemical constituents in seeds of Sterculia lychnophora.

INTRODUCTION: The seeds of Sterculia lychnophora Hance, commonly known as Pangdahai (PDH) in Chinese, have found extensive use in both culinary and traditional medicinal practices. However, a comprehensive understanding of the chemical composition of PDH has been lacking. OBJECTIVES: This study proposes a strategy that integrates biosynthetic pathway analysis with feature-based molecular networking (FBMN), aiming for a thorough and global characterization of the chemical compositions of PDH. METHODOLOGY: The FBMN map reveals potential compounds with structural similarity, and the MS/MS fragments could be annotated based on library matches, which could predict the plausible biosynthetic pathways in PDH, accomplishing the annotation of compounds clustered in FBMN by integrating biosynthetic pathways. RESULTS: Consequently, 126 compounds were plausibly or unambiguously identified, including 37 phenolic acids and glycosides, 20 flavonoids and glycosides, 12 procyanidins, 21 alkaloids, 22 lipids, and 14 others. Leveraging the information, 40 compounds, including 1 unique isoquinoline alkaloid and 2 rare linear furocoumarins, were isolated and confirmed. CONCLUSIONS: This study not only demonstrates a highly effective approach for identifying compounds within complex herbal mixtures but also establishes a robust foundation for the further development of PDH.

Customizable Click Biochemistry Strategy for the Design and Preparation of Glucagon-like Peptide-1 Conjugates and Coagonists.

The development of oligomeric glucagon-like peptide-1 (GLP-1) and GLP-1-containing coagonists holds promise for enhancing the therapeutic potential of the GLP-1-based drugs for treating type 2 diabetes mellitus (T2DM). Here, we report a facile, efficient, and customizable strategy based on genetically encoded SpyCatcher-SpyTag chemistry and an inducible, cleavable self-aggregating tag (icSAT) scheme. icSAT-tagged SpyTag-fused GLP-1 and the dimeric or trimeric SpyCatcher scaffold were designed for dimeric or trimeric GLP-1, while icSAT-tagged SpyCatcher-fused GLP-1 and the icSAT-tagged SpyTag-fused GIP were designed for dual GLP-1/GIP (glucose-dependent insulinotropic polypeptide) receptor agonist. These SpyCatcher- and SpyTag-fused protein pairs were spontaneously ligated directly from the cell lysates. The subsequent icSAT scheme, coupled with a two-step standard column purification, resulted in target proteins with authentic N-termini, with yields ranging from 35 to 65 mg/L and purities exceeding 99%. In vitro assays revealed 3.0- to 4.1-fold increased activities for dimeric and trimeric GLP-1 compared to mono-GLP-1. The dual GLP-1/GIP receptor agonist exhibited balanced activity toward the GLP-1 receptor or the GIP receptor. All the proteins exhibited 1.8- to 3.0-fold prolonged half-lives in human serum compared to mono-GLP-1 or GIP. This study provides a generally applicable click biochemistry strategy for developing oligomeric or dual peptide/protein-based drug candidates.

Experimental Generation of Spin-Photon Entanglement in Silicon Carbide.

A solid-state approach for quantum networks is advantageous, as it allows the integration of nanophotonics to enhance the photon emission and the utilization of weakly coupled nuclear spins for long-lived storage. Silicon carbide, specifically point defects within it, shows great promise in this regard due to the easy of availability and well-established nanofabrication techniques. Despite of remarkable progresses made, achieving spin-photon entanglement remains a crucial aspect to be realized. In this Letter, we experimentally generate entanglement between a silicon vacancy defect in silicon carbide and a scattered single photon in the zero-phonon line. The spin state is measured by detecting photons scattered in the phonon sideband. The photonic qubit is encoded in the time-bin degree of freedom and measured using an unbalanced Mach-Zehnder interferometer. Photonic correlations not only reveal the quality of the entanglement but also verify the deterministic nature of the entanglement creation process. By harnessing two pairs of such spin-photon entanglement, it becomes straightforward to entangle remote quantum nodes at long distance.

Catastrophic cascade of failures in interdependent hypergraphs.

The failures of individual agents can significantly impact the functionality of associated groups in interconnected systems. To reveal these impacts, we develop a threshold model to investigate cascading failures in double-layer hypergraphs with interlayer interdependence. We hypothesize that a hyperedge disintegrates when the proportion of failed nodes within it exceeds a threshold. Due to the interdependence between a node and its replica in the other layer, the disintegrations of these hyperedges could trigger a cascade of events, leading to an iterative collapse across these two layers. We find that double-layer hypergraphs undergo abrupt, discontinuous first-order phase transitions during systemic collapse regardless of the specific threshold value. Additionally, the connectivity measured by average cardinality and hyperdegree plays a crucial role in shaping system robustness. A higher average hyperdegree always strengthens system robustness. However, the relationship between system robustness and average cardinality exhibits non-monotonic behaviors. Specifically, both excessively small and large average cardinalities undermine system robustness. Furthermore, a higher threshold value can boost the system's robustness. In summary, our study provides valuable insights into cascading failure dynamics in double-layer hypergraphs and has practical implications for enhancing the robustness of complex interdependent systems across domains.

Fucoidan Improves Early Stage Diabetic Nephropathy via the Gut Microbiota-Mitochondria Axis in High-Fat Diet-Induced Diabetic Mice.

Diabetic nephropathy (DN) is a common microvascular complication of diabetes. Fucoidan, a polysaccharide containing fucose and sulfate group, ameliorates DN. However, the underlying mechanism has not been fully understood. This study aimed to explore the effects and mechanism of fucoidan on DN in high-fat diet-induced diabetic mice. A total of 90 C57BL/6J mice were randomly assigned to six groups (n = 15) as follows: normal control (NC), diabetes mellitus (DM), metformin (MTF), low-dose fucoidan (LFC), medium-dose fucoidan (MFC), and high-dose fucoidan (HFC). A technique based on fluorescein isothiocyanate (FITC-sinistin) elimination kinetics measured percutaneously was applied to determine the glomerular filtration rate (GFR). After 24 weeks, the mice were sacrificed and an early stage DN model was confirmed by GFR hyperfiltration, elevated urinary creatinine, normal urinary albumin, tubulointerstitial fibrosis, and glomerular hypertrophy. Fucoidan significantly improved the GFR hyperfiltration and renal fibrosis. An enriched SCFAs-producing bacteria and increased acetic concentration in cecum contents were found in fucoidan groups, as well as increased renal ATP levels and improved mitochondrial dysfunction. The renal inflammation and fibrosis were ameliorated through inhibiting the MAPKs pathway. In conclusion, fucoidan improved early stage DN targeting the microbiota-mitochondria axis by ameliorating mitochondrial oxidative stress and inhibiting the MAPKs pathway.

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pathological staging of colorectal cancer. The goal is to enable AI-assisted accurate pathological staging, supporting healthcare professionals in making efficient and precise staging assessments. METHODS: This study included a total of 267 colorectal cancer patients (training cohort: n = 213; testing cohort: n = 54). Logistic regression algorithms were used to construct the models. The HE image features were used to build the HE model, the Ki67 image features were used for the Ki67 model, and the combined model included features from both the HE and Ki67 images, as well as tumor markers (CEA, CA724, CA125, and CA242). The predictive results of the HE model, Ki67 model, and tumor markers were visualized through a nomogram. The models were evaluated using ROC curve analysis, and their clinical value was estimated using decision curve analysis (DCA). RESULTS: A total of 260 deep learning features were extracted from HE or Ki67 images. The AUC for the HE model and Ki67 model in the training cohort was 0.885 and 0.890, and in the testing cohort, it was 0.703 and 0.767, respectively. The combined model and nomogram in the training cohort had AUC values of 0.907 and 0.926, and in the testing cohort, they had AUC values of 0.814 and 0.817. In clinical DCA, the net benefit of the Ki67 model was superior to the HE model. The combined model and nomogram showed significantly higher net benefits compared to the individual HE model or Ki67 model. CONCLUSION: The combined model and nomogram, which integrate pathomics multi-modal data and clinical-pathological variables, demonstrated superior performance in distinguishing between Stage I-II and Stage III colorectal cancer. This provides valuable support for clinical decision-making and may improve treatment strategies and patient prognosis. Furthermore, the use of immunohistochemistry (Ki67) slides for pathomics modeling outperformed HE slide, offering new insights for future pathomics research.

The scale of zebrafish pectoral fin buds is determined by intercellular K+ levels and consequent Ca2+-mediated signaling via retinoic acid regulation of Rcan2 and Kcnk5b.

K+ channels regulate morphogens to scale adult fins, but little is known about what regulates the channels and how they control morphogen expression. Using the zebrafish pectoral fin bud as a model for early vertebrate fin/limb development, we found that K+ channels also scale this anatomical structure, and we determined how one K+-leak channel, Kcnk5b, integrates into its developmental program. From FLIM measurements of a Förster Resonance Energy Transfer (FRET)-based K+ sensor, we observed coordinated decreases in intracellular K+ levels during bud growth, and overexpression of K+-leak channels in vivo coordinately increased bud proportions. Retinoic acid, which can enhance fin/limb bud growth, decreased K+ in bud tissues and up-regulated regulator of calcineurin (rcan2). rcan2 overexpression increased bud growth and decreased K+, while CRISPR-Cas9 targeting of rcan2 decreased growth and increased K+. We observed similar results in the adult caudal fins. Moreover, CRISPR targeting of Kcnk5b revealed that Rcan2-mediated growth was dependent on the Kcnk5b. We also found that Kcnk5b enhanced depolarization in fin bud cells via Na+ channels and that this enhanced depolarization was required for Kcnk5b-enhanced growth. Lastly, Kcnk5b-induced shha transcription and bud growth required IP3R-mediated Ca2+ release and CaMKK activity. Thus, we provide a mechanism for how retinoic acid via rcan2 can regulate K+-channel activity to scale a vertebrate appendage via intercellular Ca2+ signaling.

[Effects of mixed broadleaved tree species with pure Pinus massoniana plantation on soil microbial necromass carbon and organic carbon fractions]. / é©¬å°¾æ¾çº¯æž—æ··äº¤æ”¹é€ å¯¹åœŸå£¤å¾®ç”Ÿç‰©æ®‹ä½“ç¢³å’Œæœ‰æœºç¢³ç»„åˆ†çš„å½±å“.

Mixing native broadleaved tree species is a widely used method for renovating Pinus massoniana plantations. Soil microbial necromass carbon and organic carbon fractions are important parameters for evaluating the impacts of tree species mixing and soil organic carbon (SOC) stability. However, their responses to the mixing and renovation of P. massoniana plantation has not been understood yet. Here, we selected a pure P. massoniana plantation (PP) and a mixed P. massoniana and Castanopsis hystrix plantation, with ages of 16 (MP16) and 38 years (MP38), respectively, as the research objects. We quantified soil physical and chemical properties, microbial necromass carbon content, and organic carbon components at different soil layers to reveal whether and how the introduction of C. hystrix into P. massoniana plantation affected soil microbial necromass carbon and organic carbon components. The results showed that the mixed P. massoniana and C. hystrix plantation significantly reduced fungal necromass carbon content and the ratio of fungal/bacterial necromass carbon in the 0-20 cm and 20-40 cm soil layers. There were no significant differences in microbial necromass carbon contents, bacterial necromass carbon contents, and their contributions to SOC among the different plantations. The contribution of fungal necromass carbon to SOC was higher than that of bacterial necromass carbon in all plantation types. The contribution of soil mineral-associated organic carbon (MAOC) to SOC was higher than that of occluded particulate organic carbon (oPOC) and light-free particulate organic carbon (fPOC) for all plantation types. Mixing the precious broadleaved tree species (i.e., C. hystrix) with coniferous species (P. massoniana) significantly increased MAOC content and the contribution of MAOC, oPOC, and fPOC to SOC in the 0-20 cm and 20-40 cm soil layers. The MAOC of MP38 was significantly higher than that of PP in all soil layers and the MAOC of MP38 stands were significantly higher than MP16 stands in the 20-40 cm, 40-60 cm, and 60-100 cm soil layers, indicating that hybridization enhanced SOC stability and that the SOC of MP38 stands were more stable than MP16 stands. SOC and total nitrogen contents were the main environmental factors driving the changes in soil microbial necromass carbon, while soil total nitrogen and organically complexed Fe-Al oxides were the primary factors affecting organic carbon fraction. Therefore, SOC stability can be enhanced by introducing native broadleaved species, such as C. hystrix, during the management of the P. massoniana plantation.

Targeting ATP-binding site of WRN Helicase: Identification of novel inhibitors through pocket analysis and Molecular Dynamics-Enhanced virtual screening.

WRN helicase is a critical protein involved in maintaining genomic stability, utilizing ATP hydrolysis to dissolve DNA secondary structures. It has been identified as a promising synthetic lethal target for microsatellite instable (MSI) cancers. However, few WRN helicase inhibitors have been discovered, and their potential binding sites remain unexplored. In this study, we analyzed potential binding sites for WRN inhibitors and focused on the ATP-binding site for screening new inhibitors. Through molecular dynamics-enhanced virtual screening, we identified two compounds, h6 and h15, which effectively inhibited WRN's helicase and ATPase activity in vitro. Importantly, these compounds selectively targeted WRN's ATPase activity, setting them apart from other non-homologous proteins with ATPase activity. In comparison to the homologous protein BLM, h6 exhibits some degree of selectivity towards WRN. We also investigated the binding mode of these compounds to WRN's ATP-binding sites. These findings offer a promising strategy for discovering new WRN inhibitors and present two novel scaffolds, which might be potential for the development of MSI cancer treatment.

Construction of S100 family members prognosis prediction model and analysis of immune microenvironment landscape at single-cell level in pancreatic adenocarcinoma: a tumor marker prognostic study.

Pancreatic adenocarcinoma characterized by a mere 10% five-year survival rate, poses a formidable challenge due to its specific anatomical location, making tumor tissue acquisition difficult. This limitation underscores the critical need for novel biomarkers to stratify this patient population. Accordingly, this study aimed to construct a prognosis prediction model centered on S100 family members. Leveraging six S100 genes and their corresponding coefficients, an S100 score was calculated to predict survival outcomes. The present study provided comprehensive internal and external validation along with power evaluation results, substantiating the efficacy of the proposed model. Additionally, the study explored the S100-driven potential mechanisms underlying malignant progression. By comparing immune cell infiltration proportions in distinct patient groups with varying prognoses, the research identified differences driven by S100 expression. Furthermore, the analysis explored significant ligand-receptor pairs between malignant cells and immune cells influenced by S100 genes, uncovering crucial insights. Notably, the study identified a novel biomarker capable of predicting the sensitivity of neoadjuvant chemotherapy, offering promising avenues for further research and clinical application.

[Research on the Evaluation Method and Application of Provincial Differentiated Carbon Peaking in China].

Promoting regions with favorable conditions to take the lead in reaching a carbon peak is an inevitable step towards achieving the dual carbon goals under the "nationwide coordinated action" plan. Considering the differences among Chinese provinces, this study measured the peaking pressure of each province based on the spatial distribution of carbon emissions. We then constructed a provincial peaking capacity evaluation system based on five dimensions, namely, peaking pressure, emission reduction status, economic development, policy support, and resource endowment, to comprehensively evaluate the carbon peaking capacity of 30 provincial administrative regions in China, excluding Hong Kong, Macau, Taiwan, and Tibet, using the entropy value method to determine the index weights. The 30 provinces were divided into five peaking tiers according to the evaluation results. The results showed that:① 18 regions, such as Hainan and Beijing, displayed a surplus in carbon emission space; eight regions, including Hebei and Shandong, showed a deficit in carbon emission space; and the carbon emission spaces allocated to Zhejiang, Anhui, Henan, and Hubei were comparable to their respective actual emissions. ② Developed regions generally had a higher carbon peaking capacity than that of less developed regions, with Beijing and Shanghai showing outstanding carbon peaking capacity, whereas Jiangxi and Guizhou had more room to improve their capacity. Finally, differentiated peaking targets and priority actions were proposed according to the provinces' different peaking tiers and local conditions.

Experimental Quantum Non-Gaussian Coincidences of Entangled Photons.

Quantum non-Gaussianity, a more potent and highly useful form of nonclassicality, excludes all convex mixtures of Gaussian states and Gaussian parametric processes generating them. Here, for the first time, we conclusively test quantum non-Gaussian coincidences of entangled photon pairs with the Clauser-Horne-Shimony-Holt-Bell factor S=2.328±0.004 from a single quantum dot with a depth up to 0.94±0.02 dB. Such deterministically generated photon pairs fundamentally overcome parametric processes by reducing crucial multiphoton errors. For the quantum non-Gaussian depth of the unheralded (heralded) single-photon state, we achieve the value of 8.08±0.05 dB (19.06±0.29 dB). Our Letter experimentally certifies the exclusive quantum non-Gaussianity properties highly relevant for optical sensing, communication, and computation.

Effect of waiting time for radiotherapy after last induction chemotherapy on prognosis of locally advanced nasopharyngeal carcinoma.

BACKGROUND: The effect of radiotherapy waiting time after last induction chemotherapy (IC-RT) on prognosis of patients with locally advanced nasopharyngeal carcinoma (LANPC) needs further discussion. METHODS: Three hundred and six patients with LANPC diagnosed pathologically by induction chemotherapy (IC) and radiotherapy (RT) from 2013 to 2018 were selected for this study. RESULTS: The IC-RT was a risk factor for the post-treatment progression of LANPC (OR = 1.017 95%CI: 1.003-1.031), For patients with LANPC, the IC-RT > 40 days significantly reduced 5-year PFS (70% vs. 55%; p = 0.0012), 5-year OS (84% vs. 73%; p = 0.028), 5-year DMFS (80% vs. 66%; p = 0.003), 5-year LRFS (77% vs. 67%; p = 0.012). Indicating that patients with stage IVa who IC-RT > 40 days were found to be a significant predictor of aggravated PFS (HR = 2.69; 95%CI: 1.57-4.6), OS (HR = 2.55; 95%CI: 1.29-5.03), DMFS (HR = 3.07; 95%CI: 1.64-5.76) and LRFS (HR = 2.26; 95%CI: 1.21-4.21). CONCLUSION: The prognosis of patients will be adversely affected if the IC-RT exceeds 40 days, especially for stage IVa patients.

Mussel oil is superior to fish oil in preventing atherosclerosis of ApoE-/- mice.

Objectives: The present study aimed to explore the preventive effect of mussel oil (MO) on atherosclerosis and the potential mechanism in apolipoprotein E-null (ApoE-/-) mice. Methods: ApoE-/- mice were fed with a high-fat and high-cholesterol chow and given corn oil (CO), fish oil (FO), MO, or aspirin (ASP, dissolved in CO) by gavage for 12 weeks. The total n-3 polyunsaturated fatty acids (PUFAs) in MO (51.01%) and FO (46.82%) were comparable (mainly C22:6n-3 and C20:5n-3). Wild-type mice were fed with a normal chow and given equivalent CO as health control (CON). Results: Compared with the CON group, obvious atherosclerotic plaque appeared at aorta and aortic sinus in the CO group. Compared with the CO group, MO but not FO had a significantly smaller atherosclerotic plaque area in the aorta. The aortic atherosclerotic plaque area was comparable in the MO, CON, and ASP groups. The MO group had a significantly smaller atherosclerotic plaque area, lower lipid deposition, lower contents of smooth muscle cell (SMC), and slightly lower contents of macrophage at the aortic sinus than the FO group. Serum concentrations of IL-1ß, NF-κB, and VCAM-1 were comparable in the MO and FO groups and were significantly lower than the CO group. Compared with the CO group, the MO group but not FO group had significantly lower aortic protein levels of p65NF-κB, p38MAPK, and VCAM-1. The aortic protein levels of p-p65NF-κB and p-p38MAPK were significantly lower in the MO group than the FO group. Conclusion: In conclusion, MO is more potent than FO in preventing atherosclerosis, and the possible mechanism may be by downregulating p38MAPK/NF-κB signaling pathway, decreasing VCAM-1 and macrophage, and inhibiting proliferation and migration of SMC.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study.

BACKGROUND AND AIMS: Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown. METHODS: This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset. RESULTS: Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx. CONCLUSIONS: In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Programming Polarity Heterogeneity of Energy Storage Dielectrics by Bidirectional Intelligent Design.

Dielectric capacitors, characterized by ultra-high power densities, are considered as fundamental energy storage components in electronic and electrical systems. However, synergistically improving energy densities and efficiencies remains a daunting challenge. Understanding the role of polarity heterogeneity at the nanoscale in determining polarization response is crucial to the domain engineering of high-performance dielectrics. Here, a bidirectional design with phase-field simulation and machine learning is performed to forward reveal the structure-property relationship and reversely optimize polarity heterogeneity to improve energy storage performance. Taking BiFeO3-based dielectrics as typical systems, this work establishes the mapping diagrams of energy density and efficiency dependence on the volume fraction, size and configuration of polar regions. Assisted by CatBoost and Wolf Pack algorithms, this work analyzes the contributions of geometric factors and intrinsic features and find that nanopillar-like polar regions show great potential in achieving both high polarization intensity and fast dipole switching. Finally, a maximal energy density of 188 J cm-3 with efficiency above 95% at 8 MV cm-1 is obtained in BiFeO3-Al2O3 systems. This work provides a general method to study the influence of local polar heterogeneity on polarization behaviors and proposes effective strategies to enhance energy storage performance by tuning polarity heterogeneity.

The dual function of cGAS-STING signaling axis in liver diseases.

Numerous liver diseases, such as nonalcoholic fatty liver disease, hepatitis, hepatocellular carcinoma, and hepatic ischemia-reperfusion injury, have been increasingly prevalent, posing significant threats to global health. In recent decades, there has been increasing evidence linking the dysregulation of cyclic-GMP-AMP synthase (cGAS)-stimulator of interferon gene (STING)-related immune signaling to liver disorders. Both hyperactivation and deletion of STING can disrupt the immune microenvironment dysfunction, exacerbating liver disorders. Consequently, there has been a surge in research investigating medical agents or mediators targeting cGAS-STING signaling. Interestingly, therapeutic manipulation of the cGAS-STING pathway has yielded inconsistent and even contradictory effects on different liver diseases due to the distinct physiological characteristics of intrahepatic cells that express and respond to STING. In this review, we comprehensively summarize recent advancements in understanding the dual roles of the STING pathway, highlighting that the benefits of targeting STING signaling depend on the specific types of target cells and stages of liver injury. Additionally, we offer a novel perspective on the suitability of STING agonists and antagonists for clinical assessment. In conclusion, STING signaling remains a highly promising therapeutic target, and the development of STING pathway modulators holds great potential for the treatment of liver diseases.

[Prediction of Autumn Ozone Concentration in the Pearl River Delta Based on Machine Learning].

Based on the observation data of the daily maximum 8-hour ozone (O3) average concentration[MDA8-O3, ρ(O3-8h)] and meteorological reanalysis data in the Pearl River Delta Region from 2015 to 2022, four machine learning methods, i.e., support vector machine regression (SVR), random forest (RF), multi-layer perceptron (MLP), and lightweight gradient boosting machine (LG) were used to establish MDA8-O3 prediction models. The results showed that the SVR model had the best prediction performance on MDA8-O3 during the whole year, the coefficient of determination (R2) reached 0.86, and the root mean square error (RMSE) and mean absolute error (MAE) were 16.3 µg·m-3 and 12.3 µg·m-3, respectively. The prediction performance of the SVR model in autumn was still slightly better than that of LG and MLP, with R2,RMSE,and MAE values of 0.88, 19.8 µg·m-3,and 16.1 µg·m-3, respectively. The RF model performed the worst in the autumn prediction. In addition, the models trained by data from the whole year had better prediction ability on autumn MDA8-O3 than that of those only trained by autumn data, and the R2 differed 0.08-0.14.

Discovery of novel selective phosphodiesterase­1 inhibitors for the treatment of acute myelogenous leukemia.

Acute myelogenous leukemia (AML) is the most common form of acute leukemia in adults. PDE1 (Phosphodiesterase 1) is a subfamily of the PDE super-enzyme families that can hydrolyze the second messengers cAMP and cGMP simultaneously. Previous research has shown that suppressing the gene expression of PDE1 can trigger apoptosis of human leukemia cells. However, no selective PDE1 inhibitors have been used to explore whether PDE1 is a potential target for treating AML. Based on our previously reported PDE9/PDE1 dual inhibitor 11a, a series of novel pyrazolopyrimidinone derivatives were designed in this study. The lead compound 6c showed an IC50 of 7.5 nM against PDE1, excellent selectivity over other PDEs and good metabolic stability. In AML cells, compound 6c significantly inhibited the proliferation and induced apoptosis. Further experiments indicated that the apoptosis induced by 6c was through a mitochondria-dependent pathway by decreasing the ratio of Bcl-2/Bax and increasing the cleavage of caspase-3, 7, 9, and PARP. All these results suggested that PDE1 might be a novel target for AML.

Thinned young apple powder prevents obesity-induced neuronal apoptosis via improving mitochondrial function of cerebral cortex in mice.

Mitochondrial dysfunction is one of the triggers for obesity-induced neuron apoptosis. Thinned young apple is getting more attention on account of the extensive biological activities because of rich polyphenols and polysaccharides. However, the neuroprotective effect of thinned young apple powder (YAP) is still unclear. The aim of the present study was to investigate the preventive effect of YAP on obesity-induced neuronal apoptosis. C57BL/6J male mice were divided into 5 groups, control (CON), high fat diet (HFD), HFD + orlistat (ORL), HFD + low-dose young apple powder (LYAP) and HFD + high-dose young apple powder (HYAP) groups and intervened for 12 weeks. It was found that the YAP effectively reduced body weight gain. Importantly, the levels of pro-apoptosis protein were lower in LYAP and HYAP groups than the HFD group, such as Bak/Bcl2 and cleaved caspase3/caspase3. Pathway analysis based on untargeted metabolomics suggested that YAP alleviated obesity-induced neuronal apoptosis by three main metabolic pathway including arginine metabolism, citrate cycle (TCA cycle) and glutathione metabolism. Meanwhile, YAP improved the protein expression of mitochondrial respiratory chain complex, maintained the homeostasis of TCA cycle intermediates, protected the balance of mitochondrial dynamics and alleviated lipid accumulation. In addition, the levels of several antioxidants in cerebral cortex were higher in HYAP group than the HFD group like superoxide dismutase (SOD) and catalase (CAT). In summary, YAP supplementation suppressed neuronal apoptosis in the cerebral cortex of HFD-induced obesity mice by improving mitochondrial function and inhibiting oxidative stress.