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Background: Parkinson's disease (PD), the second most common neurodegenerative disease in the world, is usually not diagnosed until the later stages of the disease, when patients might have already missed the best treatment period. Therefore, more effective prediction methods based on artificial intelligence (AI) are needed to assist physicians in timely diagnosis., New Methods: An explainable deep learning-based early Parkinson's disease diagnostic model, Parkinson's Integrative Diagnostic Gated Network (PIDGN), was designed by fusing Single Nucleotide Polymorphism (SNP) and brain sMRI data. Firstly, unimodal internal information was extracted using EmsembleTree dimensionality reduction method, Transformer encoder and 3D ResNet. Secondly, gated attention fusion technique was utilized to explore the inter-modal interactions. Finally, the classification results were output through the fully connected layer. SHapley additive interpretation (SHAP) values and Gradient-weighted Class Activation Mapping (Grad-CAM) techniques were used to help explain the importance of SNPs and brain regions for PD., Results: The results showed that the PIDGN model achieved the best results with the accuracy of 0.858 and AUROC of 0.897. Top 20 SNPs and the brain regions near the midbrain potentially related to PD were identified using two explainable techniques via SHAP values and Grad-CAM respectively., Comparison With Existing Methods and Conclusion: The PIDGN model trained by fusing genetic and imaging data outperforms 13 other commonly used unimodal or bimodal models. Explainable PIDGN model helps deepen understanding of several SNPs and sMRI key factors that may affect PD. This study provides a potentially effective solution for automated early diagnosis of PD using AI., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2025 Elsevier B.V. All rights reserved.)

Motivation: Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data., Results: We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150-350 (Illumina short reads), 850-950 (Sanger sequencing data), and 2000-5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150-350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients' unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions., Availability and Implementation: www.dllab.org/software/VirusPredictor.html., (© The Author(s) 2024. Published by Oxford University Press.)

Scandium is the best alloying element to improve the mechanical properties of industrial Al-Si-Mg casting alloys. Most literature reports devote to exploring/designing optimal Sc additions in different commercial Al-Si-Mg casting alloys with well-defined compositions. However, no attempt to optimize the contents of Si, Mg, and Sc has been made due to the great challenge of simultaneous screening in high-dimensional composition space with limited experimental data. In this paper, a novel alloy design strategy was proposed and successfully applied to accelerate the discovery of hypoeutectic Al-Si-Mg-Sc casting alloys over high-dimensional composition space. Firstly, high-throughput CALculation of PHAse Diagrams (CALPHAD) solidification simulations of ocean of hypoeutectic Al-Si-Mg-Sc casting alloys over a wide composition range were performed to establish the quantitative relation 'composition-process-microstructure'. Secondly, the relation 'microstructure-mechanical properties' of Al-Si-Mg-Sc hypoeutectic casting alloys was acquired using the active learning technique supported by key experiments designed by CALPHAD and Bayesian optimization samplings. After a benchmark in A356-xSc alloys, such a strategy was utilized to design the high-performance hypoeutectic Al-xSi-yMg alloys with optimal Sc additions that were later experimentally validated. Finally, the present strategy was successfully extended to screen the optimal contents of Si, Mg, and Sc over high-dimensional hypoeutectic Al-xSi-yMg-zSc composition space. It is anticipated that the proposed strategy integrating active learning with high-throughput CALPHAD simulations and key experiments should be generally applicable to the efficient design of high-performance multi-component materials over high-dimensional composition space., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2023 The Author(s). Published by National Institute for Materials Science in partnership with Taylor & Francis Group.)

Excessive exercise leads to body fatigue and destroys the balance of the oxidation/oxidation resistance system in the body, thus damaging the central nervous system and reducing learning and memory ability. Nrf2 is an important transcription factor that regulates the cell oxidative stress response. Therefore, the research and development of natural antioxidants with the effect of regulating Nrf2-related signalling pathways to improve central fatigue caused by body fatigue has application value. Methods and results: Cordyceps militaris polysaccharides were extracted, isolated and purified via DEAE-cellulose 52 and Sepharose CL-6B columns to obtain two saccharides, Cordyceps militaris acidic polysaccharides (CMPB) and CMPB-b. The results of behavioural tests showed that compared with the model group, the learning and memory abilities of the CMPB-H group (800 mg/kg) mice were remarkably improved in the dark avoidance and Morris water maze tasks (p < 0.01), and the levels of fatigue metabolites and oxidative stress in the body were obviously decreased (p < 0.01). The expression level of BDNF, PI3K, Nrf2 and HO-1 proteins in the hippocampus were significantly increased (p < 0.01). In vitro experiments, compared with the PC12 oxidative stress model group, CMPB-b high-dose group (100 μg/mL) had remarkably improved oxidative stress. CMPB-b also obviously promoted the phosphorylation of PI3K and AKT proteins (p < 0.01) and the nuclear translocation of Nrf2 (p < 0.01), and significantly increased the expression of HO-1 (p < 0.01). Conclusion: CMPB can alleviate the fatigue state of high-intensity swimming mice and improve the learning and memory impairment of exercise-fatigue mice by regulating the Nrf2-related signalling pathway. Its antioxidant active component CMPB-b exerts in vitro antioxidative neurological damage by the same mechanism. Our systematic studies provide strong supporting evidence for the future use of Cordyceps militaris acidic polysaccharides in health products to improve resistance to fatigue., Competing Interests: Declaration of competing interest The authors declare no conflflict of interest., (Copyright © 2022. Published by Elsevier B.V.)

Osteosarcoma (OS) is a malignant primary bone tumor with high metastatic rate. C-X-C motif chemokine ligand 6 (CXCL6) and its receptor C-X-C motif chemokine receptor 1/2 (CXCR1/2) have been found to participate in the process of carcinogenesis. In this study, we evaluated the role of CXCL6/CXCR1/2 axis in proliferation and metastasis of OS cells. According to our results, the mRNA and protein expressions of CXCL6, CXCR1, and CXCR2 in multiple OS cell lines were determined. Treatment with exogenous CXCL6 for more than 72 h significantly promoted the proliferation of OS cells. Blocking the effect of endogenous CXCL6 restrained the migration, invasion and epithelial-mesenchymal transition (EMT) as evidenced by increased E-cadherin level, decreased N-cadherin and Snail levels in OS cells. On the contrary, exogenous CXCL6 administration enhanced the migration and invasive abilities of OS cells. Moreover, silencing of CXCR1/2 suppressed migration, invasion and EMT of OS cells with or without treatment with exogenous CXCL6. In addition, exogenous CXCL6 promoted the activation of PI3K/AKT and β-catenin signaling pathways, which could be repressed by CXCR2 knockdown. Inactivation of PI3K/AKT or β-catenin pathway by specific inhibitors effectively suppressed CXCL6-induced migration, invasion and EMT of OS cells. Finally, overexpression of CXCL6 significantly contributed to tumor growth, pulmonary metastasis and activation of PI3K/AKT and β-catenin pathways in nude mice in vivo , which were repressed by treatment with CXCR2 antagonist. Our results suggest that CXCL6/CXCR1/2 axis promotes the proliferation and metastasis of OS cells.

In this paper, a selenium polysaccharide (PGP1) was isolated from the radix of Platycodon grandiflorum. We investigated the protective capacity of PGP1 against the hydrogen peroxide (H 2 O 2 )-induced oxidative damage in cultured rat pheochromocytoma (PC12) cells. Cells were pretreated with various doses of PGP1 (50, 100 and 200μg/mL) for 24h before exposure to 0.5mM H 2 O 2 for 12h. Cell viability, LDH release, apoptotic rates, malondialdehyde (MDA) content, antioxidant enzyme superoxide dismutase (SOD) activity and intracellular accumulation of reactive oxygen species (ROS) were determined. The results showed pretreatment of PC12 cells with PGP1 prior to H 2 O 2 exposure inhibited the decrease of cell viability, decreased the apoptotic rates, prevented membrane damage (LDH release) and attenuated intracellular ROS formation in PC12 cells injured by H 2 O 2 . Meanwhile, PGP1 increased SOD activity, while it decreased the level of MDA and the production of lipid peroxidation, in PC12 cells after H 2 O 2 exposure. These findings suggested that PGP1 may be considered as a potential useful antioxidant agent in reducing neuronal oxidative damage via inhibiting oxidative stress., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In the present study, we isolated and characterized one purified polysaccharide (AEP-1) from the leaves of Aralia elata, and investigated its effect on human osteosarcoma (OS) U-2 OS cell line and analyzed its mechanism. MTT assays showed that AEP-1 markedly inhibited the growth of U-2 OS cells in a dose- and time-dependent fashion, suggesting a cytotoxic effect. The AEP-1 also dose-dependently induced DNA fragmentation and caused apoptotic death in U-2 OS cells. The event of apoptosis was accompanied by increased ratio of Bax/Bcl-2, depolarization of mitochondrial membrane potential (Δym) and the release of cytochrome c from mitochondria into the cytoplasm. Moreover, AEP-1 treatment triggered the activation of caspase-9 and caspase-3, as well as the cleavage of poly (ADP-ribose) polymerase (PAPR) in U-2 OS cells. All these results suggests that the induction of apoptosis by AEP-1 in U-2 OS cells occurs through the mitochondria-dependent pathway and AEP-1 may be useful in treating OS and improving cancer chemotherapy., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In this Letter, a high-power supercontinuum (SC) laser source which spanned from 1.9 to 3.6 μm with an all-fiber configuration was reported. This SC laser was obtained by concatenating a thulium-doped fiber amplifier (TDFA) and a 12 cm long highly nonlinear germania fiber. A 1.9-2.7 μm SC laser from the TDFA was spectrally broadened continuously into the mid-infrared region (>3  μm) in the following germania fiber. When the repetition rate was 2 MHz, the obtained SC laser had a maximum output power of 6.12 W with an optical conversion efficiency of 15.3% with respect to the TDFA pump power. The SC laser had a spectral bandwidth of 1506 nm ranging from 1944 to 3450 nm at the -20  dB level. The SC power with wavelengths >3  μm was 2.9 W, corresponding to a high power ratio of 47.4% in the mid-infrared region. The achieved power ratio in the mid-infrared region, as well as the long wavelength cutoff, to the best of our knowledge, were the best results ever reported in germania fibers.

An ultra-broadband supercontinuum was generated in a short piece of step-index germania-core fiber using a fiber laser with a peak power of 4.4 kW. The pure germania core made this fiber capable of propagating light towards the desirable mid-infrared region. The spectral broadening characteristics towards the mid-infrared region under different lengths of germania-core fiber were investigated using pump pulses of 4.4 kW and 1.1 ns at 1550 nm. The large nonlinear refractive index of germania and the small core size of germania-core fiber produced a nonlinear coefficient as high as 11.8 (W km) -1 at 1550 nm, which was beneficial for supercontinuum generation. The pump wavelength was located in the anomalous dispersion regime and close to the zero dispersion wavelength of this germania-core fiber, 1.426 μm. Eventually, an ultra-broadband supercontinuum source with a spectrum spanning from 0.6 to 3.2 μm was obtained and had a total output power of 350 mW at an optimized germania-core fiber length of 0.8 m. This work is the first demonstration, to the best of our knowledge, of a germania-core fiber-based ultra-broadband supercontinuum source that spans from the visible region to the mid-infrared region.

A high-power, wavelength-tunable, all-fiber integrated thulium-doped fiber laser (TDFL) at 2 μm is presented. The TDFL has a compact configuration which only consists of a low power seed oscillator and a stage of fiber power amplifier. The seed oscillator adopts a tunable band-pass filter as the wavelength selective element, matching the gain spectrum of thulium-doped fiber. It can provide ~5 W single-mode seed laser with superb spectral characteristics, and the lasing wavelength is adjustable from 1890 to 2050 nm. The fiber power amplifier provides a total gain of ~17 dB at 2 μm which boosts the signal power to the 300 W-level. The maximum average power reaches 327.5 W at 1930 nm with the highest slope efficiency of 57.4%. This TDFL can afford >270 W lasing operation over the whole tuning range of 140 nm spanning from 1910 to 2050 nm, together with high spectral quality and power stability. This is the first demonstration, to the best of our knowledge, on an all-fiber integrated wavelength-widely-tunable TDFL at 2 μm with output power at the 300 W-level. The results are of great interest for many applications.

High-resolution fetal electrocardiogram (FECG) plays an important role in assisting physicians to detect fetal changes in the womb and to make clinical decisions. However, in real situations, clear FECG is difficult to extract because it is usually overwhelmed by the dominant maternal ECG and other contaminated noise such as baseline wander, high-frequency noise. In this paper, we proposed a novel integrated adaptive algorithm based on independent component analysis (ICA), ensemble empirical mode decomposition (EEMD), and wavelet shrinkage (WS) denoising, denoted as ICA-EEMD-WS, for FECG separation and noise reduction. First, ICA algorithm was used to separate the mixed abdominal ECG signal and to obtain the noisy FECG. Second, the noise in FECG was reduced by a three-step integrated algorithm comprised of EEMD, useful subcomponents statistical inference and WS processing, and partial reconstruction for baseline wander reduction. Finally, we evaluate the proposed algorithm using simulated data sets. The results indicated that the proposed ICA-EEMD-WS outperformed the conventional algorithms in signal denoising.

Vaccinia Tian Tan (VTT) was attenuated by deletion of the TC7L-TK2L and TA35R genes to generate MVTT3. The mutant was generated by replacing the open reading frames by a gene encoding enhanced green fluorescent protein (EGFP) flanked by loxP sites. Viruses expressing EGFP were then screened for and purified by serial plaque formation. In a second step the marker EGFP gene was removed by transfecting cells with a plasmid encoding cre recombinase and selecting for viruses that had lost the EGFP phenotype. The MVTT3 mutant was shown to be avirulent and immunogenic. These results support the conclusion that TC7L-TK2L and TA35R deletion mutants can be used as safe viral vectors or as platform for vaccines.