Systematic dissection of sequence features affecting binding specificity of a pioneer factor reveals binding synergy between FOXA1 and AP-1.

Despite the unique ability of pioneer factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called chromatin immunoprecipitation with integrated synthetic oligonucleotides (ChIP-ISO) to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1, in human A549 cells. Combining ChIP-ISO with in vitro and neural network analyses, we find that (1) FOXA1 binding is strongly affected by co-binding transcription factors (TFs) AP-1 and CEBPB; (2) FOXA1 and AP-1 show binding cooperativity in vitro; (3) FOXA1's binding is determined more by local sequences than chromatin context, including eu-/heterochromatin; and (4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

Pioneer factors: nature or nurture?

Chromatin is densely packed with nucleosomes, which limits the accessibility of many chromatin-associated proteins. Pioneer factors (PFs) are usually viewed as a special group of sequence-specific transcription factors (TFs) that can recognize nucleosome-embedded motifs, invade compact chromatin, and generate open chromatin regions. Through this process, PFs initiate a cascade of events that play key roles in gene regulation and cell differentiation. A current debate in the field is if PFs belong to a unique subset of TFs with intrinsic "pioneering activity", or if all TFs have the potential to function as PFs within certain cellular contexts. There are also different views regarding the key feature(s) that define pioneering activity. In this review, we present evidence from the literature related to these alternative views and discuss how to potentially reconcile them. It is possible that both intrinsic properties, like tight nucleosome binding and structural compatibility, and cellular conditions, like concentration and co-factor availability, are important for PF function.

5-Methylcytosine transferase NSUN2 drives NRF2-mediated ferroptosis resistance in non-small cell lung cancer.

RNA 5-methylcytosine (m5C) is an abundant chemical modification in mammalian RNAs and plays crucial roles in regulating vital physiological and pathological processes, especially in cancer. However, the dysregulation of m5C and its underlying mechanisms in non-small cell lung cancer (NSCLC) remain unclear. Here we identified that NSUN2, a key RNA m5C methyltransferase, is highly expressed in NSCLC tumor tissue. We found elevated NSUN2 expression levels strongly correlate with tumor grade and size, predicting poor outcomes for NSCLC patients. Furthermore, RNA-seq and subsequent confirmation studies revealed the antioxidant-promoting transcription factor NRF2 is a target of NSUN2, and depleting NSUN2 decreases the expression of NRF2 and increases the sensitivity of NSCLC cells to ferroptosis activators both in vitro and in vivo. Intriguingly, the methylated-RIP-qPCR assay results indicated that NRF2 mRNA has a higher m5C level when NSUN2 is overexpressed in NSCLC cells but shows no significant changes in the NSUN2 methyltransferase-deficient group. Mechanistically, we confirmed that NSUN2 upregulates the expression of NRF2 by enhancing the stability of NRF2 mRNA through the m5C modification within its 5'UTR region recognized by the specific m5C reader protein YBX1, rather than influencing its translation. In subsequent rescue experiments, we show knocking down NRF2 diminished the proliferation, migration, and ferroptosis tolerance mediated by NSUN2 overexpression. In conclusion, our study unveils a novel regulatory mechanism in which NSUN2 sustains NRF2 expression through an m5C-YBX1-axis, suggesting that targeting NSUN2 and its regulated ferroptosis pathway might offer promising therapeutic strategies for NSCLC patients.

Overexpression of OsNAR2.1 by OsNAR2.1 promoter increases drought resistance by increasing the expression of OsPLDα1 in rice.

BACKGROUND: pOsNAR2.1:OsNAR2.1 expression could significantly increase nitrogen uptake efficiency and grain yield of rice. RESULT: This study reported the effects of overexpression of OsNAR2.1 by OsNAR2.1 promoter on physiological and agronomic traits associated with drought tolerance. In comparison to the wild-type (WT), the pOsNAR2.1:OsNAR2.1 transgenic lines exhibited a significant improvement in survival rate when subjected to drought stress and then irrigation. Under limited water supply conditions, compared with WT, the photosynthesis and water use efficiency (WUE) of transgenic lines were increased by 39.2% and 28.8%, respectively. Finally, the transgenic lines had 25.5% and 66.4% higher grain yield than the WT under full watering and limited water supply conditions, respectively. Compared with the WT, the agronomic nitrogen use efficiency (NUE) of transgenic lines increased by 25.5% and 66.4% under full watering and limited water supply conditions, and the N recovery efficiency of transgenic lines increased by 29.3% and 50.2%, respectively. The interaction between OsNAR2.1 protein and OsPLDα1 protein was verified by yeast hybrids. After drought treatment, PLDα activity on the plasma membrane of the transgenic line increased 85.0% compared with WT. CONCLUSION: These results indicated that pOsNAR2.1:OsNAR2.1 expression could improve the drought resistance of rice by increasing nitrogen uptake and regulating the expression of OsPLDα1.

Peroxidase gene TaPrx109-B1 enhances wheat tolerance to water deficit via modulating stomatal density.

Increasing the tolerance of crops to water deficit is crucial for the improvement of crop production in water-restricted regions. Here, a wheat peroxidase gene (TaPrx109-B1) belonging to the class III peroxidase gene family was identified and its function in water deficit tolerance was revealed. We demonstrated that overexpression of TaPrx109-B1 reduced leaf H2O2 level and stomatal density, increased leaf relative water content, water use efficiency, and tolerance to water deficit. The expression of TaEPF1 and TaEPF2, two key negative regulators of stomatal development, were significantly upregulated in TaPrx109-B1 overexpression lines. Furthermore, exogenous H2O2 downregulated the expression of TaEPF1 and TaEPF2 and increased stomatal density, while exogenous application of diphenyleneiodonium chloride, a potent NADPH oxidase inhibitor that repressed the synthesis of H2O2, upregulated the expression of TaEPF1 and TaEPF2, decreased stomatal density, and enhanced wheat tolerance to water deficit. These findings suggest that TaPrx109-B1 influences leaf stomatal density by modulation of H2O2 level and the expression of TaEPF1 and TaEPF2. The results of the field trial showed that overexpressing TaPrx109-B1 increased grain number per spike, which reduced the yield loss caused by water deficiency. Therefore, TaPrx109-B1 has great potential in breeding wheat varieties with improved water deficit tolerance.

Homoharringtonine enhances cytarabine-induced apoptosis in acute myeloid leukaemia by regulating the p38 MAPK/H2AX/Mcl-1 axis.

Acute myeloid leukaemia (AML) is a fatal haematopoietic malignancy and is treated with the conventional combination of cytarabine (Ara-C) and daunorubicin (Dau). The survival rate of AML patients is lower due to the cardiotoxicity of daunorubicin. Clinically, homoharringtonine (HHT) plus Ara-C has been reported to be equally effective as Dau plus Ara-C in some types of AML patients with less toxic effects. We utilized the clinical use of homoharringtonine in combination with Ara-C to test its combination mechanism. We found that the insensitivity of AML cells to cytarabine-induced apoptosis is associated with increased Mcl-1 stability and p38 inactivation. HHT downregulates Mcl-1, phosphorylates H2AX and induces apoptosis by activating p38 MAPK. Inactivation of p38 through inhibitors and siRNA blocks apoptosis, H2AX phosphorylation and Mcl-1 reduction. HHT enhances Ara-C activation of the p38 MAPK signalling pathway, overcoming Ara-C tolerance to cell apoptosis by regulating the p38/H2AX/Mcl-1 axis. The optimal ratio of HHT to Ara-C for synergistic lethality in AML cells is 1:4 (M/M). HHT synergistically induces apoptosis in combination with Ara-C in vitro and prolongs the survival of xenografts. We provide a new mechanism for AML treatment by regulating the p38 MAPK/H2AX/Mcl-1 axis to improve cytarabine therapy.

Synthesis and Evaluation of [18F]AlF-NOTA-c-DVAP: A Novel PET Probe for Imaging GRP78 in Cancer.

GRP78, a member of the HSP70 superfamily, is an endoplasmic reticulum chaperone protein overexpressed in various cancers, making it a promising target for cancer imaging and therapy. Positron emission tomography (PET) imaging offers unique advantages in real time, noninvasive tumor imaging, rendering it a suitable tool for targeting GRP78 in tumor imaging to guide targeted therapy. Several studies have reported successful tumor imaging using PET probes targeting GRP78. However, existing PET probes face challenges such as low tumor uptake, inadequate in vivo distribution, and high abdominal background signal. Therefore, this study introduces a novel peptide PET probe, [18F]AlF-NOTA-c-DVAP, for targeted tumor imaging of GRP78. [18F]AlF-NOTA-c-DVAP was radiolabeled with fluoride-18 using the aluminum-[18F]fluoride ([18F]AlF) method. The study assessed the partition coefficients, stability in vitro, and metabolic stability of [18F]AlF-NOTA-c-DVAP. Micro-PET imaging, pharmacokinetic analysis, and biodistribution studies were carried out in tumor-bearing mice to evaluate the probe's performance. Docking studies and pharmacokinetic analyses of [18F]AlF-NOTA-c-DVAP were also performed. Immunohistochemical and immunofluorescence analyses were conducted to confirm GRP78 expression in tumor tissues. The probe's binding affinity to GRP78 was analyzed by molecular docking simulation. [18F]AlF-NOTA-c-DVAP was radiolabeled in just 25 min with a high yield of 51 ± 16%, a radiochemical purity of 99%, and molar activity within the range of 20-50 GBq/µmol. [18F]AlF-NOTA-c-DVAP demonstrated high stability in vitro and in vivo, with a logD value of -3.41 ± 0.03. Dynamic PET imaging of [18F]AlF-NOTA-c-DVAP in tumors showed rapid uptake and sustained retention, with minimal background uptake. Biodistribution studies revealed rapid blood clearance and excretion through the kidneys following a single-compartment reversible metabolic model. In PET imaging, the T/M ratios for A549 tumors (high GRP78 expression), MDA-MB-231 tumors (medium expression), and HepG2 tumors (low expression) at 60 min postintravenous injection were 10.48 ± 1.39, 6.25 ± 0.47, and 3.15 ± 1.15% ID/g, respectively, indicating a positive correlation with GRP78 expression. This study demonstrates the feasibility of using [18F]AlF-NOTA-c-DVAP as a PET tracer for imaging GRP78 in tumors. The probe shows promising results in terms of stability, specificity, and tumor targeting. Further research may explore the clinical utility and potential therapeutic applications of this PET tracer for cancer diagnosis.

Aerococcus kribbianus sp. nov., a facultatively anaerobic bacterium isolated from pig faeces.

Two cocci-shaped, facultatively anaerobic, Gram-positive bacteria isolated from the faeces of a pig were designated as strains YH-aer221T and YH-aer222. Analysis of the 16S rRNA gene sequences revealed that the isolates were most closely related to Aerococcus suis JCM 18035T with 96.6 % similarity. The multi-locus sequence tree revealed that the isolates formed a sub-cluster adjacent to A. suis JCM 18035T. The average nucleotide identity values for the isolates and their most closely related strains were 71.8 and 71.7 %, respectively; and the digital DNA-DNA hybridization values for the isolates and their most closely related strains were 25.6 and 25.5 %, respectively. The main fatty acids were C18 : 1ω9c, C16 : 0 and C18 : 0. The cell wall contained the meso-diaminopimelic acid-based peptidoglycan. The two isolates shared the same metabolic pathways. Isolates YH-aer221T and YH-aer222 harboured the same CRISPR array with 33 and 46 spacers, respectively. Single-genome vs. metagenome analysis showed that the genomes of the isolates were not found in the available metagenome database. Given their chemotaxonomic, phenotypic and phylogenetic properties, YH-aer221T (= KCTC 25571T=JCM 35699T) and YH-aer222 (=KCTC 25573=JCM 35700) represent a novel taxon. The name Aerococcus kribbianus sp. nov. is proposed.

Description of an anaerobic actinobacterium, Kribbibacterium absianum gen. nov., sp. nov., a new member of the novel family Kribbibacteriaceae fam. nov., and reclassification of the genera Granulimonas and Leptogranulimonas.

Two rod-shaped, obligate anaerobic, Gram-stain-positive bacteria isolated from the pig faeces were designated YH-ols2216 and YH-ols2217T. Analysis of 16S rRNA gene sequences revealed that these isolates were most related to the members of the family Atopobiaceae, within the order Coriobacteriales, and Granulimonas faecalis KCTC 25474T with 92.0 and 92.5% similarities, respectively. The 16S rRNA gene sequence similarity within isolates was 99.9 %; and those between isolates YH-ols2216 and YH-ols2217T, and Atopobium minutum DSM 20586T, the type species of the type genus Atopobium within the family Atopobiaceae, were 88.5 and 88.7 %, respectively. Those between isolates and Coriobacterium glomerans PW2T, the type species of the type genus Coriobacterium within the family Coriobacteriaceae, were 88.7 and 89.1 %, respectively. The multi-locus sequence tree revealed that the isolates, alongside the genera Granulimonas and Leptogranulimonas, formed a distinct cluster between the families Atopobiaceae and Coriobacteriaceae. The average nucleotide identities and digital DNA-DNA hybridization values for the isolates and their most closely related strains ranged from 67.7 to 76.2 % and from 18.4 to 23.3 %, respectively. The main cellular fatty acids of the isolates were C18 : 0 DMA, C18 : 1 ω9c, C18 : 0 12OH, C18 : 0, and C16 : 0. The cell wall contained the peptidoglycan meso-diaminopimelic acid. Lactate was the main end-product of the isolates. The major polar lipids of isolate YH-ols2217T were aminophospholipid, aminolipids, and lipids. Menaquinones were not identified in the cells of the isolates. The DNA G+C contents of isolates YH-ols2216 and YH-ols2217T were 67.5 and 67.6 mol%, respectively. Considering these chemotaxonomic, phenotypic, and phylogenetic properties, Kribbibacteriaceae fam. nov. is proposed within the order Coriobacteriales. YH-ols2216 (=KCTC 25708=NBRC 116429) and YH-ols2217T (=KCTC 25709T=NBRC 116430T) represent a novel taxon within this new family and the name Kribbibacterium absianum gen. nov., sp. nov. is proposed. In addition, the genera Granulimonas and Leptogranulimonas are transferred to the family Kribbibacteriaceae fam. nov.

An effective urobilin clearance strategy based on paramagnetic beads facilitates microscale proteomic analysis of urine.

Urine provides an ideal source for disease biomarker discovery. High-adhesion contaminants such as urobilin, which are difficult to remove from urine, can severely interfere with urinary proteomic analysis. Here, we aimed to establish a strategy based on single-pot, solid-phase-enhanced sample preparation (SP3) technology to prepare samples for urinary proteomics analysis that almost completely eliminates the impact of urobilin. A systematic evaluation of the effects of two urinary protein precipitation methods, two types of protein lysis buffers, and different ratios of magnetic digestion beads on the identification and quantification of the microscale urinary proteome was conducted. Our results indicate that methanol-chloroform precipitation, coupled with efficient lysis facilitated by urea, and subsequent enzymatic digestion using a mix of hydrophilic and hydrophobic magnetic beads offers the best performance. Further applying this strategy to the urine of patients with benign prostatic hyperplasia, prostate cancer and healthy individuals, combined with a narrow window of data-independent acquisition, FGFR4, MYLK, ORM2, GOLM1, SPP1, CD55, CSF1, DLD and TIMP3 were identified as potential biomarkers to discriminate benign prostatic hyperplasia and prostate cancer patients.

A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data.

BACKGROUND: Survival prediction using high-dimensional molecular data is a hot topic in the field of genomics and precision medicine, especially for cancer studies. Considering that carcinogenesis has a pathway-based pathogenesis, developing models using such group structures is a closer mimic of disease progression and prognosis. Many approaches can be used to integrate group information; however, most of them are single-model methods, which may account for unstable prediction. METHODS: We introduced a novel survival stacking method that modeled using group structure information to improve the robustness of cancer survival prediction in the context of high-dimensional omics data. With a super learner, survival stacking combines the prediction from multiple sub-models that are independently trained using the features in pre-grouped biological pathways. In addition to a non-negative linear combination of sub-models, we extended the super learner to non-negative Bayesian hierarchical generalized linear model and artificial neural network. We compared the proposed modeling strategy with the widely used survival penalized method Lasso Cox and several group penalized methods, e.g., group Lasso Cox, via simulation study and real-world data application. RESULTS: The proposed survival stacking method showed superior and robust performance in terms of discrimination compared with single-model methods in case of high-noise simulated data and real-world data. The non-negative Bayesian stacking method can identify important biological signal pathways and genes that are associated with the prognosis of cancer. CONCLUSIONS: This study proposed a novel survival stacking strategy incorporating biological group information into the cancer prognosis models. Additionally, this study extended the super learner to non-negative Bayesian model and ANN, enriching the combination of sub-models. The proposed Bayesian stacking strategy exhibited favorable properties in the prediction and interpretation of complex survival data, which may aid in discovering cancer targets.

Synthesis and preclinical evaluation of a novel molecular probe [18F]AlF-NOTA-PEG2-Asp2-PDL1P for PET imaging of PD-L1 positive tumor.

Immunotherapy has brought great benefits to cancer patients, but only some patients benefit from it. Noninvasive, real-time and dynamic monitoring of the effectiveness of immunotherapy through PET imaging may provide assistance for the treatment plan of immunotherapy. In this study, we designed and synthesized a new targeted PD-L1 peptide NOTA-PEG2-Asp2-PDL1P, which was labeled with nuclide 18F to obtain a new imaging agent [18F]AlF-NOTA-PEG2-Asp2-PDL1P. The total radiochemical yield of [18F]AlF-NOTA-PEG2-Asp2-PDL1P was 13.7 % (Uncorrected radiochemical yield, n > 5). [18F]AlF-NOTA-PEG2-Asp2-PDL1P achieved high radiochemical purity (>95 %) with a molar activity more than 51.2 GBq/µmol. [18F]AlF-NOTA-PEG2-Asp2-PDL1P exhibited good hydrophilicity and had good stability both in vivo and in vitro, it can specifically targets B16F10 tumor with PD-L1 expression, and had a relatively high retention in tumor, a relatively fast clearance in vivo and a higher tumor-to-non-target ratio, all of which could make [18F]AlF-NOTA-PEG2-Asp2-PDL1P a potential tracer for PD-L1 prediction before clinical immunotherapy.

Comparative study of [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p as novel PD-L1 targeting PET probes for tumor imaging.

PD-L1 is expressed in many tumors but rarely in normal tissues, therefore, it can be a target of PET imaging. In this work, we developed new peptide-based PET probes [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p with yields of 20-25 % and 40-55 %, respectively. [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p were synthesized within 30 min with high molar activities. [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p showed good stability in vivo and in vitro. In vitro cell studies showed [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p target PD-L1 specifically, with high uptake of 61.52 ± 4.39 and 19.29 ± 2.17 %ID/1 million cells in B16F10 cells at 60 min, respectively. Biodistribution results showed that both [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1p had lower liver accumulation. In vivo PET imaging results showed that [18F]AlF-PAI-PDL1p had a high tumor uptake of 4.23 ± 0.81 %ID/g at 2 h and increased uptake of 6.60 ± 1.01 %ID/g at 12 h. [68Ga]Ga-PAI-PDL1p also showed high tumor uptake of 2.30 ± 0.20 %ID/g at 2 h and slightly increased uptake of 3.80 ± 0.26 %ID/g at 6 h. In conclusion, [18F]AlF-PAI-PDL1p and [68Ga]Ga-PAI-PDL1 seemed to be potential tracers for PET imaging of PD-L1 expression.

Unexplained recurrent high fever observed in a depressed adolescent.

BACKGROUND: Depressive episodes in adolescents are often accompanied by various physical symptoms, but few studies have explored the association between depression and fever, This case study is the first to report the relationship between unexplained recurrent high fever and depression. CASE PRESENTATION: H is a 15 year old adolescent female currently in junior year. 2 + months ago, H gradually felt depressed after a class change. Around the time, the patient suddenly developed chills with no obvious trigger and fever. H was treated with anti-infective and anti-viral treatments all of which did not show significant improvement. No significant abnormality was seen in any of the related examinations. Considering that the patient's anxiety, depression and somatic symptoms were obvious during the course of the disease, she was given venlafaxine hydrochloride extended-release capsule 75 mg/d; tandospirone citrate capsule 10 mg Bid; alprazolam tablets 0.4 mg qn to improve mood and sleep; supplemented with transcranial repetitive magnetic stimulation therapy 2 times/d; visible light therapy 1 time/d and psychological counseling once. Over the 6 days of treatment, the patient's body temperature gradually returned to the normal range and her mood improved significantly. CONCLUSION: Depression should be considered a potential cause of unexplained recurrent fevers in adolescents, even when the temperature is significantly outside the normal range.

Rapid analysis of the chemical constituents in Qiangli Dingxuan tablets using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry.

Qiangli Dingxuan (QLDX) tablet is a widely recognized traditional Chinese medicine formula that has been extensively used in China for decades to treat vertigo, tinnitus, and dizziness owing to its outstanding therapeutic outcomes. However, the complexity of the chemical components in this tablet makes it challenging to separate and identify these components. This study presented an effective and sensitive strategy for the rapid separation and simultaneous structural identification of QLDX tablet components using ultra-performance liquid chromatography with quadrupole time-of-flight tandem mass spectrometry and the UNIFI platform. Based on retention times, accurate masses, fragment ions, related literature, and authentic standards, 119 compounds were identified or tentatively characterized; these included 9 iridoids, 12 lignans, 21 phenylpropanoids, 27 flavonoids, 7 phthalides, and 43 others. Among them, 36 were confirmed using reference standards. The representative compounds with various chemical structures were studied by analyzing their fragmentation patterns and characteristic ions. In conclusion, this study established a rapid approach for characterizing the chemical constituents in QLDX tablet. The proposed approach provides a basis for qualitative analysis and quality control in the manufacturing process and is beneficial for advancing investigations into the efficacy and mechanism of action of this tablet.

Association between body mass index and tic disorders in school-age children.

OBJECTIVE: To explore the relationship between body mass index (BMI ) and the severity of tic disorders (TDs) in children 6-14 years old. METHODS: A total of 86 children diagnosed with TDs in a hospital between Jan. 2023 and Sept. 2023 were collected by convenient sampling method, and the general data and TD-specific data were collected and analyzed. RESULTS: Univariate analysis showed that patients with different Yale Global Tic Severity Scale (YGTSS) grades had statistically significant differences in age, BMI, residence, snacking pattern, weekly physical exercise frequency, weekly physical exercise time, and proportion of cesarean birth. Multiple linear regression analysis showed that the YGTSS score grades were related to BMI, snacking pattern, and cesarean birth of the patients. Correlation analysis revealed a positive correlation between BMI grades and the YGTSS score grades, with a higher BMI indicating more severe TDs. Predictive value evaluation showed that BMI, snacking pattern, and cesarean birth had predictive values for TD severity, and the highest value was found in the combined prediction. CONCLUSION: BMI, snacking pattern, and cesarean birth are of predictive values for the severity of TDs. In addition, BMI is positively correlated with the severity of TDs, and a higher BMI suggests more severe TDs.

Chemical characterization, multivariate analysis and comparison of biological activities of different parts of Fraxinus mandshurica.

Fraxinus mandshurica (Oleaceae) is used as a traditional medicinal plant for the treatment of red eyes, menstrual disorders, excessive leucorrhea, chronic bronchitis and psoriasis. To perform chemical characterization of the secondary metabolites of F. mandshurica roots, bark, stems and leaves, 32 samples were collected from eight provinces in this study. A total of 64 chemical components were detected from four different parts of F. mandshurica by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Meanwhile, a total of nine secoiridoids were obtained by natural product chemical extraction, isolation and identification methods. Quantitative analysis by high-performance liquid chromatography-diode array detection-mass spectrometry showed the highest total content of secoiridoids in the bark, which is also consistent with the traditional medicinal parts. The results of methodological validation showed that the correlation coefficient (R2) values were all >0.9993, indicating a good linear range of the standard curve, while the relative standard deviations of precision, reproducibility and stability were <3%, and the spiked recoveries ranged from 98.22 to 102.27%, indicating that the experimental method was reliable and stable. In addition, fingerprinting and a heatmap were established to demonstrate the content trends of F. mandshurica more visually from different origins. Multivariate analysis, including principal component analysis and partial least squares discriminant analysis, was performed to determine the chemical characteristics of different parts of F. mandshurica, and six characteristic secoiridoids that could be used to distinguish different origins were screened. Finally, the inhibition of tyrosinase, α-glucosidase, acetylcholinesterase and pancreatic lipase activities by the nine characteristic compounds and extracts from different parts were investigated, and the results showed that they all exhibited different degrees of enzyme activity inhibition and thus have potential applications in whitening and blemish removal, hypoglycemia, anti-Alzheimer's disease and anti-obesity as a new source of natural enzyme activity inhibitors. This study establishes an identification and evaluation method applicable to phytochemistry of different origins, which is a guideline for quality control, origin evaluation and clinical application of traditional medicinal plants. This is also an unprecedented study on the identification of the chemical composition of different parts of F. mandshurica, characteristic compounds and the inhibition of enzyme activity of extracts from different parts.

A Deep Learning Based Platform for Remote Sensing Images Change Detection Integrating Crowdsourcing and Active Learning.

Remote sensing images change detection technology has become a popular tool for monitoring the change type, area, and distribution of land cover, including cultivated land, forest land, photovoltaic, roads, and buildings. However, traditional methods which rely on pre-annotation and on-site verification are time-consuming and challenging to meet timeliness requirements. With the emergence of artificial intelligence, this paper proposes an automatic change detection model and a crowdsourcing collaborative framework. The framework uses human-in-the-loop technology and an active learning approach to transform the manual interpretation method into a human-machine collaborative intelligent interpretation method. This low-cost and high-efficiency framework aims to solve the problem of weak model generalization caused by the lack of annotated data in change detection. The proposed framework can effectively incorporate expert domain knowledge and reduce the cost of data annotation while improving model performance. To ensure data quality, a crowdsourcing quality control model is constructed to evaluate the annotation qualification of the annotators and check their annotation results. Furthermore, a prototype of automatic detection and crowdsourcing collaborative annotation management platform is developed, which integrates annotation, crowdsourcing quality control, and change detection applications. The proposed framework and platform can help natural resource departments monitor land cover changes efficiently and effectively.

Phase Noise Compensation Algorithm for Space-Borne Azimuth Multi-Channel SAR.

Azimuth multi-channel synthetic aperture radar (SAR) has always been an important technical means to achieve high-resolution wide-swath (HRWS) SAR imaging. However, in the space-borne azimuth multi-channel SAR system, random phase noise will be produced during the operation of each channel receiver. The phase noise of each channel is superimposed on the SAR echo signal of the corresponding channel, which will cause the phase imbalance between the channels and lead to the generation of false targets. In view of the above problems, this paper proposes a random phase noise compensation method for space-borne azimuth multi-channel SAR. This method performs feature decomposition by calculating the covariance matrix of the echo signal and converts the random phase noise estimation into the optimal solution of the cost function. Considering that the phase noise in the receiver has frequency-dependent and time-varying characteristics, this method calculates the phase noise estimation value corresponding to each range-frequency point in the range direction and obtains the phase noise estimation value by expectation in the azimuth direction. The proposed random phase noise compensation method can suppress false targets well and make the radar present a well-focused SAR image. Finally, the usefulness of the suggested method is verified by simulation experiments.

BRDF modeling and optimization of a target surface based on the gradient descent algorithm.

Addressing the current challenges in modeling and optimizing the bidirectional reflectance distribution function (BRDF) for the target surface, an improved six-parameter semi-empirical model is proposed based on an existing five-parameter semi-empirical model. In comparison with the original five-parameter model, the new, to the best of our knowledge, model considers reciprocity, and the results demonstrate that as the incident angle increases, the fitting accuracy of the six parameters gradually surpasses that of the five parameters. Additionally, this paper employs a machine learning optimization algorithm, namely, the gradient descent method, for optimizing the BRDF. The algorithm was comprehensively compared with other optimization methods, revealing that for the same dataset, the gradient descent method exhibited the smallest fitting errors. Subsequently, utilizing this algorithm for fitting experimental data resulted in errors consistently within 3%, confirming the reliability and accuracy of this optimization algorithm.