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"Fang, Ke"
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Linking high-energy cosmic particles by black-hole jets embedded in large-scale structures
The origin of ultrahigh-energy cosmic rays (UHECRs) is a half-century-old enigma1. The mystery has been deepened by an intriguing coincidence: over ten orders of magnitude in energy, the energy generation rates of UHECRs, PeV neutrinos and isotropic sub-TeV γ-rays are comparable, which hints at a grand unified picture2. Here we report that powerful black hole jets in aggregates of galaxies can supply the common origin for all of these phenomena. Once accelerated by a jet, low-energy cosmic rays confined in the radio lobe are adiabatically cooled; higher-energy cosmic rays leaving the source interact with the magnetized cluster environment and produce neutrinos and γ-rays; the highest-energy particles escape from the host cluster and contribute to the observed cosmic rays above 100 PeV. The model is consistent with the spectrum, composition and isotropy of the observed UHECRs, and also explains the IceCube neutrinos and the non-blazar component of the Fermi γ-ray background, assuming a reasonable energy output from black hole jets in clusters.
Journal Article
Stereospecific Si-C coupling and remote control of axial chirality by enantioselective palladium-catalyzed hydrosilylation of maleimides
Hydrosilylation of unsaturated carbon-carbon bonds with hydrosilanes is a very important process to access organosilicon compounds and ranks as one of the most fundamental reactions in organic chemistry. However, catalytic asymmetric hydrosilylation of activated alkenes and internal alkenes has proven elusive, due to competing reduction of carbon-carbon double bond or isomerization processes. Herein, we report a highly enantioselective Si-C coupling by hydrosilylation of carbonyl-activated alkenes using a palladium catalyst with a chiral TADDOL-derived phosphoramidite ligand, which inhibits O-hydrosilylation/olefin reduction. The stereospecific Si-C coupling/hydrosilylation of maleimides affords a series of silyl succinimides with up to 99% yield, >99:1 diastereoselectivity and >99:1 enantioselectivity. The high degree of stereoselectivity exerts remote control of axial chirality, leading to functionalized, axially chiral succinimides which are versatile building blocks. The product utility is highlighted by the enantioselective construction of N-heterocycles bearing up to three stereocenters.
Catalytic asymmetric hydrosilylation of internal alkenes has proven elusive due to more favourable double bond reduction or isomerization. Here, the authors show an enantioselective Si-C coupling by hydrosilylation of activated alkenes using a palladium/phosphoramidite catalyst affording axially chiral succinimides.
Journal Article
An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
Attitude errors, accelerometer bias, the gravity disturbance vector, and their coupling are the primary factors obstructing strapdown airborne vector gravimetry. This paper takes the geocentric inertial frame as a reference and solves the kinematic equations of its motion and its errors of the body frame and local geographic frame in the Lie group, respectively; the attitude accuracy is improved through a high-precision navigation algorithm. The constant accelerometer bias is estimated through Kalman filtering and is deducted from the accelerometer output to eliminate its influence. Based on the EGM2008 model, the low-frequency components of the gravity disturbance vector are corrected. The gravity disturbance vectors after model data fusion were low-pass filtered to obtain the ultimate results. This method was applied to flight experimental data in the South China Sea, and a gravity anomaly accuracy of better than 0.5 mGal, a northward gravity disturbance accuracy of 0.85 mGal, and an eastward gravity disturbance accuracy of 4.0 mGal were obtained, with a spatial resolution of approximately 4.8 km.
Journal Article
Quercetin Alleviates LPS-Induced Depression-Like Behavior in Rats via Regulating BDNF-Related Imbalance of Copine 6 and TREM1/2 in the Hippocampus and PFC
Quercetin is a polyphenol with multiple biological activities, and results of our preliminary study showed that it could shorten the immobility time of mice in the forced swimming test and tail suspending test. The aim of this study was to investigate its effects on the behavioral performance of lipopolysaccharide (LPS)-challenged rats and explore the potential mechanism. The results showed that intragastrical administration of quercetin (40 mg/kg) could improve the bodyweight gain of LPS-challenged rats, increase the saccharin preference index in the saccharin preference test and the novel arm preference index in the Y-maze, and decrease the immobility time in the FST. However, it showed no significant effect on the performance of LPS-challenged rats in the Morris water maze and the plasma concentrations of nesfatin-1, C-reactive protein (CRP), and IL-6. Results of western blot showed that the expression levels of BDNF, Copine 6, p-TrkB, and the triggering receptors expressed on myeloid cells (TREM) 1 were decreased in both the hippocampus and the prefrontal cortex (PFC) of LPS-challenged rats, while the expression of TREM2 was increased. The protein expression of synapsin-1 was decreased in the hippocampus without significant changes in the PFC. These imbalance protein expressions could be balanced by treatment with quercetin. The results suggested that quercetin could alleviate LPS-induced depression-like behaviors and impairment of learning and memory in rats, the mechanism of which might be involved with regulating the BDNF-related imbalance expression of Copine 6 and TREM1/2 in the hippocampus and the PFC.
Journal Article
A Novel Integrated Strategy for Discovering Absorbable Anticoagulant Bioactive Peptides: A Case Study on Leech Protein Hydrolysates
Medicinal plants and animal-derived proteins represent valuable natural sources of bioactive components with pharmaceutical potential. Whilst some medicinal plants and animal-derived proteins also offer rich sources of anticoagulant bioactive peptides, their development faces multiple challenges: anticoagulant evaluation relies on single-parameter assays with limited reliability, native proteins demonstrate suboptimal activity without enzymatic treatment, and few researchers investigate bioavailable peptides. Our study establishes an innovative framework using the leech as a case study to overcome these barriers. A novel anticoagulant evaluation model was first established with the Critic-G1 weighting method. And we optimized the enzymatically hydrolyzed extracts with high activity using Box–Behnken response surface methodology. Subsequently, the everted gut sac model was implemented to simulate intestinal absorption and screen for absorbable peptide fractions. Furthermore, peptidomics was employed to identify the bioactive peptides. Lastly, we identified the bioactivity using anticoagulation assays. Results indicated that the optimal hydrolysis conditions were achieved with trypsin at 50.48 °C, an enzyme-to-substrate ratio of 6.78%, 7.51 h, and pH of 8.06. The peptide DLRWM was identified through integrated peptidomics and molecular docking approaches, with subsequent activity validation demonstrating its potent anticoagulant effects. This study has successfully identified a novel anticoagulant peptide (DLRWM) with confirmed intestinal absorption properties and provides a template for unlocking the pharmaceutical potential of medicinal animal proteins.
Journal Article
Evaluating simulated teaching audio for teacher trainees using RAG and local LLMs
In the training of teacher students, simulated teaching is a key method for enhancing teaching skills. However, traditional evaluations of simulated teaching typically rely on direct teacher involvement and guidance, increasing teachers’ workload and limiting the opportunities for teacher students to practice independently. This paper introduces a Retrieval-Augmented Generation (RAG) framework constructed using various open-source tools (such as FastChat for model inference and Whisper for speech-to-text) combined with a local large language model (LLM) for audio analysis of simulated teaching. We then selected three leading 7B-parameter open-source Chinese LLMs from the ModelScope community to analyze their generalizability and adaptability in simulated teaching voice evaluation tasks. The results show that the internlm2 model more effectively analyzes teacher students’ teaching audio, providing key educational feedback. Finally, we conducted a system analysis of the simulated teaching of 10 participants in a teaching ability competition and invited three experts to score manually, verifying the system’s application potential. This research demonstrates a potential approach to improving educational evaluation methods using advanced language technology.
Journal Article
Integrative nomogram of intratumoral, peritumoral, and lymph node radiomic features for prediction of lymph node metastasis in cT1N0M0 lung adenocarcinomas
Radiomics studies to predict lymph node (LN) metastasis has only focused on either primary tumor or LN alone. However, combining radiomics features from multiple sources may reflect multiple characteristic of the lesion thereby increasing the discriminative performance of the radiomic model. Therefore, the present study intends to evaluate the efficiency of integrative nomogram, created by combining clinical parameters and radiomics features extracted from gross tumor volume (GTV), peritumoral volume (PTV) and LN, for the preoperative prediction of LN metastasis in clinical cT1N0M0 adenocarcinoma. A primary cohort of 163 patients (training cohort, 113; and internal validation cohort, 50) and an external validation cohort of 53 patients with clinical stage cT1N0M0 were retrospectively included. Features were extracted from three regions of interests (ROIs): GTV; PTV (5.0 mm around the tumor) and LN on pre-operative contrast enhanced computed tomography (CT). LASSO logistic regression method was used to build radiomic signatures. Multivariable regression analysis was used to build a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The discriminative performance of nomogram was validated both internally and externally. The radiomic signatures using the features of GTV, PTV and LN showed a good ability in predicting LN metastasis with an area under the curve (AUC) of 0.74 (95% CI 0.60–0.88), 0.72 (95% CI 0.57–0.87) and 0.64 (95% CI 0.48–0.80) respectively in external validation cohort. The integration of different signature together further increases the discriminatory ability: GTV + PTV (GPTV): AUC 0.75 (95% CI 0.61–0.89) and GPTV + LN: AUC 0.76 (95% CI 0.61–0.91) in external validation cohort. An integrative nomogram of clinical parameters and radiomic features demonstrated further increase in discriminatory ability with AUC of 0.79 (95% CI 0.66–0.93) in external validation cohort. The nomogram showed good calibration. Decision curve analysis demonstrated that the radiomic nomogram was clinically useful. The integration of information from clinical parameters along with CT radiomics information from GTV, PTV and LN was feasible and increases the predictive performance of the nomogram in predicting LN status in cT1N0M0 adenocarcinoma patients suggesting merit of information integration from multiple sources in building prediction model.
Journal Article
Gravity-Matching Algorithm Based on K-Nearest Neighbor
The gravity-aided inertial navigation system is a technique using geophysical information, which has broad application prospects, and the gravity-map-matching algorithm is one of its key technologies. A novel gravity-matching algorithm based on the K-Nearest neighbor is proposed in this paper to enhance the anti-noise capability of the gravity-matching algorithm, improve the accuracy of gravity-aided navigation, and reduce the application threshold of the matching algorithm. This algorithm selects K sample labels by the Euclidean distance between sample datum and measurement, and then creatively determines the weight of each label from its spatial position using the weighted average of labels and the constraint conditions of sailing speed to obtain the continuous navigation results by gravity matching. The simulation experiments of post processing are designed to demonstrate the efficiency. The experimental results show that the algorithm reduces the INS positioning error effectively, and the position error in both longitude and latitude directions is less than 800 m. The computing time can meet the requirements of real-time navigation, and the average running time of the KNN algorithm at each matching point is 5.87s. This algorithm shows better stability and anti-noise capability in the continuously matching process.
Journal Article
Global burden of respiratory system cancers in 2022 and 2050: incidence and mortality estimates from GLOBOCAN
Background
Respiratory system cancers, primarily encompassing lung cancer, tracheal cancer, bronchial cancer, and laryngeal cancer, severely jeopardize patients’ lives. Therefore, this study aimed to investigate the global burden of respiratory system cancers in 2022 using the GLOBOCAN 2022 database, to inform global prevention strategies.
Methods
This study extracted data of respiratory system cancers from GLOBOCAN 2022, stratified into two subsets: laryngeal cancer (C32) and tracheal, bronchial, and lung cancers (C33, C34). It analyzed the incidence, mortality, and age-standardized rates (ASR) of both subsets across world regions, HDI levels, genders, and age groups, and projected their disease burden from 2022 to 2050.
Results
For tracheal, bronchial, and lung cancers (C33, C34), Hungary had the highest age-standardized incidence rates (ASIR) and age-standardized mortality rates (ASMR). For laryngeal cancer alone (C32), India had the highest global ASIR and ASMR. Very high HDI regions had the highest ASR for the combined cancers. Males had higher incidence and mortality than females across regions and HDI strata for both subsets. Incidence and mortality rose markedly after age 40, with faster growth in males. Projection results indicated that by 2050, the male incidence and mortality rates of tracheal, bronchial, and lung cancers would increase by 87.97% and 94.75%, respectively. For laryngeal cancer, the number of male incident cases and male deaths was expected to grow by 72.53% and 81.33%, respectively.
Conclusion
This study, grounded in the GLOBOCAN 2022 database, elucidated the respiratory system cancers (lung cancer, tracheal cancer, bronchial cancer, and laryngeal cancer) global burden. It thereby furnished theoretical references for subsequent preventive measures.
Journal Article