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Background: Multi-gene panel testing and advancements in molecular targeted therapy have improved the overall survival of patients with driver mutation-positive non-small cell lung cancer (NSCLC). Mesenchymal-epithelial transition factor (MET) exon 14 skipping mutation-positive NSCLC, which remains untreated with MET inhibitors, shows a poorer prognosis than do cases of NSCLC without MET mutations. However, serious treatment-related adverse events (TRAEs) act as substantial treatment barriers. Case Description: Herein, we report a case of advanced NSCLC in a male in his 40s with MET exon 14 skipping mutation. A MET-inhibitory investigational drug was administered as first-line treatment; the development of grade 3 maculopapular rash necessitated dose reduction, which resulted in disease progression. Tepotinib was then administered with dexamethasone as a third-line treatment but was discontinued owing to the re-development of the grade 3 maculopapular rash. Finally, capmatinib administration as the fifth-line treatment appeared partially effective, with no serious adverse events. The patient could successfully resume work. Conclusions: This is the first report of MET exon 14 skipping mutation-positive NSCLC wherein partial response was achieved without severe TRAEs by alternating between two MET inhibitors. If no alternative treatments are available, cautious repeated re-administration of MET inhibitors after resolving serious rashes can be considered a potential approach.

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Introduction: The hair coat status of cattle serves as an easily observed indicator of economic value in livestock production; however, the underlying mechanism remains largely unknown. Therefore, the objective of the current study was to determine differences in the intestinal microbiota and metabolome of cattle based on a division of with either slick and shining (SHC) or rough and dull (MHC) hair coat in Simmental cows. Methods: Eight SHC and eight MHC late-pregnancy Simmental cows (with similar parities, body weights, and body conditions) were selected based on their hair coat status, and blood samples (plasma) from coccygeal venipuncture and fecal samples from the rectum were collected. The intestinal microbiota (in the fecal samples) was characterized by employing 16S rRNA gene sequencing targeting the V3-V4 hypervariable region on the Illumina MiSeq PE300 platform, and plasma samples were subjected to LC-MS/MS-based metabolomics with Progenesis QI 2.3. Plasma macromolecular metabolites were examined for differences in the metabolism of lipids, proteins, mineral elements, and hormones. Results: Notable differences between the SHC and MHC groups related to host hair coat status were observed in the host metabolome and intestinal microbiota (P < 0.05). The host metabolome was enriched in histidine metabolism, cysteine and methionine metabolism, and purine metabolism in the SHC group, and the intestinal microbiota were also enriched in histidine metabolism (P < 0.05). In the MHC group, the symbiotic relationship transitioned from cooperation to competition in the MHC group, and an uncoupling effect was present in the microbe-metabolite association of intestine microbiota-host interactions. The hubs mediating the relationships between intestinal microbiota and plasma metabolites were the intestinal bacterial genus g__norank_f__Eubacterium_coprostanoligenes_group, plasma inosine, triiodothyronine, and phosphorus, which could be used to differentiate cows' hair coat status (P < 0.05). Conclusion: Overall, the present study identified the relationships between the features of the intestinal microbiota and host hair coat status, thereby providing evidence and a new direction (intestine microbiota-host interplay) for future studies aimed at understanding the hair coat status of cattle.

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The incidence of metabolic diseases has progressively increased, which has a negative impact on human health and life safety globally. Due to the good efficacy and limited side effects, there is growing interest in developing effective drugs to treat metabolic diseases from natural compounds. Kaempferol (KMP), an important flavonoid, exists in many vegetables, fruits, and traditional medicinal plants. Recently, KMP has received widespread attention worldwide due to its good potential in the treatment of metabolic diseases. To promote the basic research and clinical application of KMP, this review provides a timely and comprehensive summary of the pharmacological advances of KMP in the treatment of four metabolic diseases and its potential molecular mechanisms of action, including diabetes mellitus, obesity, non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH), and atherosclerosis. According to the research, KMP shows remarkable therapeutic effects on metabolic diseases by regulating multiple signaling transduction pathways such as NF-κB, Nrf2, AMPK, PI3K/AKT, TLR4, and ER stress. In addition, the most recent literature on KMP's natural source, pharmacokinetics studies, as well as toxicity and safety are also discussed in this review, thus providing a foundation and evidence for further studies to develop novel and effective drugs from natural compounds. Collectively, our manuscript strongly suggested that KMP could be a promising candidate for the treatment of metabolic diseases.

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Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

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Neoplasias Pulmonares, Metabolômica, Medicina de Precisão, Humanos, Neoplasias Pulmonares/sangue, Neoplasias Pulmonares/metabolismo, Metabolômica/métodos, Medicina de Precisão/métodos, Biomarcadores Tumorais/sangue, Masculino, Pessoa de Meia-Idade, Feminino, Lipidômica/métodos, Fenótipo, Metaboloma, Idoso, Lipídeos/sangue

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Ischemia‒reperfusion (I/R) injury is a frequently observed complication after flap surgery, and it affects skin flap survival and patient prognosis. Currently, there are no proven safe and effective treatment options to treat skin flap I/R injury. Herein, the potential efficacies of the bioactive peptide from maggots (BPM), as well as its underlying mechanisms, were explored in a rat model of skin flap I/R injury and LPS- or H2O2-elicited RAW 264.7 cells. We demonstrated that BPM significantly ameliorated the area of flap survival, and histological changes in skin tissue in vivo. Furthermore, BPM could markedly restore or enhance Nrf2 and HO-1 levels, and suppress the expression of pro-inflammatory cytokines, including TLR4, p-IκB, NFκB p65, p-p65, IL-6, and TNF-α in I/R-injured skin flaps. In addition, BPM treatment exhibited excellent biocompatibility with an adequate safety profile, while it exhibited superior ROS-scavenging ability and the upregulation of antioxidant enzymes in vitro. Mechanistically, the above benefits related to BPM involved the activation of Nrf2/HO-1 and suppression of TLR4/NF-κB pathway. Taken together, this study may provide a scientific basis for the potential therapeutic effect of BPM in the prevention of skin flap I/R injury and other related diseases.

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Tensor networks developed in the context of condensed matter physics try to approximate order-N tensors with a reduced number of degrees of freedom that is only polynomial in N and arranged as a network of partially contracted smaller tensors. As we have recently demonstrated in the context of quantum many-body physics, computation costs can be further substantially reduced by imposing constraints on the canonical polyadic (CP) rank of the tensors in such networks. Here, we demonstrate how tree tensor networks (TTN) with CP rank constraints and tensor dropout can be used in machine learning. The approach is found to outperform other tensor-network-based methods in Fashion-MNIST image classification. A low-rank TTN classifier with branching ratio b = 4 reaches a test set accuracy of 90.3% with low computation costs. Consisting of mostly linear elements, tensor network classifiers avoid the vanishing gradient problem of deep neural networks. The CP rank constraints have additional advantages: The number of parameters can be decreased and tuned more freely to control overfitting, improve generalization properties, and reduce computation costs. They allow us to employ trees with large branching ratios, substantially improving the representation power.

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Background & Aims: Inflammatory bowel disease (IBD) is commonly associated with extraintestinal complications, including autoimmune liver disease. The co-occurrence of IBD and primary biliary cholangitis (PBC) has been increasingly observed, but the underlying relationship between these conditions remains unclear. Methods: Using summary statistics from genome-wide association studies (GWAS), we investigated the causal effects between PBC and IBD, including Crohn's disease (CD) and ulcerative colitis (UC). We also analyzed the shared genetic architecture between IBD and PBC using data from GWAS, bulk-tissue RNA sequencing, and single cell RNA sequencing, and explored potential functional genes. Result: There was a strong positive genetic correlation between PBC and IBD (linkage disequilibrium score regression: rg = 0.2249, p = 3.38 × 10-5). Cross-trait analysis yielded 10 shared-risk single nucleotide polymorphisms (SNPs), as well as nine novel SNPs, which were associated with both traits. Using Mendelian randomization, a stable causal effect was established of PBC on IBD. Genetically predicted PBC was found to have a risk effect on IBD (1.105; 95% CI: 1.058-1.15; p = 1.16 × 10-10), but not vice versa. Shared tissue-specific heritability enrichment was identified for PBC and IBD (including CD and UC) in lung, spleen, and whole-blood samples. Furthermore, shared enrichment was observed of specific cell types (T cells, B cells, and natural killer cells) and their subtypes. Nine functional genes were identified based on summary statistics-based Mendelian randomization. Conclusions: This study detected shared genetic architecture between IBD and PBC and demonstrated a stable causal relationship of genetically predicted PBC on the risk of IBD. These findings shed light on the biological basis of comorbidity between IBD and PBC, and have important implications for intervention and treatment targets of these two diseases simultaneously. Impact and Implications: The discovery of novel shared single nucleotide polymorphisms (SNPs) and functional genes provides insights into the common targets between inflammatory bowel disease (IBD) and primary biliary cholangitis (PBC), serving as a basis for new drug development and contributing to the study of disease pathogenesis. Additionally, the established significant causality and genetic correlation underscore the importance of clinical intervention in preventing the comorbidity of IBD and PBC. The enrichment of SNP heritability in specific tissues and cell types reveals the role of immune factors in the potential disease mechanisms shared between IBD and PBC. This stimulates further research on potential interventions and could lead to the development of new targets for immune-based therapies.

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AIM: To identify the differential methylation sites (DMS) and their according genes associated with diabetic retinopathy (DR) development in type 1 diabetes (T1DM) children. METHODS: This study consists of two surveys. A total of 40 T1DM children was included in the first survey. Because no participant has DR, retina thinning was used as a surrogate indicator for DR. The lowest 25% participants with the thinnest macular retinal thickness were included into the case group, and the others were controls. The DNA methylation status was assessed by the Illumina methylation 850K array BeadChip assay, and compared between the case and control groups. Four DMS with a potential role in diabetes were identified. The second survey included 27 T1DM children, among which four had DR. The methylation patterns of the four DMS identified by 850K were compared between participants with and without DR by pyrosequencing. RESULTS: In the first survey, the 850K array revealed 751 sites significantly and differentially methylated in the case group comparing with the controls (|Δß|>0.1 and Adj.P<0.05), and 328 of these were identified with a significance of Adj.P<0.01. Among these, 319 CpG sites were hypermethylated and 432 were hypomethylated in the case group relative to the controls. Pyrosequencing revealed that the transcription elongation regulator 1 like (TCERG1L, cg07684215) gene was hypermethylated in the four T1DM children with DR (P=0.018), which was consistent with the result from the first survey. The methylation status of the other three DMS (cg26389052, cg25192647, and cg05413694) showed no difference (all P>0.05) between participants with and without DR. CONCLUSION: The hypermethylation of the TCERG1L gene is a risk factor for DR development in Chinese children with T1DM.

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Radiation therapy treatment planning requires balancing the delivery of the target dose while sparing normal tissues, making it a complex process. To streamline the planning process and enhance its quality, there is a growing demand for knowledge-based planning (KBP). Ensemble learning has shown impressive power in various deep learning tasks, and it has great potential to improve the performance of KBP. However, the effectiveness of ensemble learning heavily depends on the diversity and individual accuracy of the base learners. Moreover, the complexity of model ensembles is a major concern, as it requires maintaining multiple models during inference, leading to increased computational cost and storage overhead. In this study, we propose a novel learning-based ensemble approach named LENAS, which integrates neural architecture search with knowledge distillation for 3-D radiotherapy dose prediction. Our approach starts by exhaustively searching each block from an enormous architecture space to identify multiple architectures that exhibit promising performance and significant diversity. To mitigate the complexity introduced by the model ensemble, we adopt the teacher-student paradigm, leveraging the diverse outputs from multiple learned networks as supervisory signals to guide the training of the student network. Furthermore, to preserve high-level semantic information, we design a hybrid loss to optimize the student network, enabling it to recover the knowledge embedded within the teacher networks. The proposed method has been evaluated on two public datasets: 1) OpenKBP and 2) AIMIS. Extensive experimental results demonstrate the effectiveness of our method and its superior performance to the state-of-the-art methods. Code: github.com/hust-linyi/LENAS.

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Objective: Recombinase-aided polymerase chain reaction (RAP) is a sensitive, single-tube, two-stage nucleic acid amplification method. This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus (SA), Pseudomonas aeruginosa (PA), and Acinetobacter baumannii (AB) in the bloodstream based on recombinant human mannan-binding lectin protein (M1 protein)-conjugated magnetic bead (M1 bead) enrichment of pathogens combined with RAP. Methods: Recombinant plasmids were used to evaluate the assay sensitivity. Common blood influenza bacteria were used for the specific detection. Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR (M-RAP) and quantitative PCR (qPCR) assays. Kappa analysis was used to evaluate the consistency between the two assays. Results: The M-RAP method had sensitivity rates of 1, 10, and 1 copies/µL for the detection of SA, PA, and AB plasmids, respectively, without cross-reaction to other bacterial species. The M-RAP assay obtained results for < 10 CFU/mL pathogens in the blood within 4 h, with higher sensitivity than qPCR. M-RAP and qPCR for SA, PA, and AB yielded Kappa values of 0.839, 0.815, and 0.856, respectively ( P < 0.05). Conclusion: An M-RAP assay for SA, PA, and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

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Bacteriemia, Lectina de Ligação a Manose, Humanos, Lectina de Ligação a Manose/sangue, Bacteriemia/diagnóstico, Bacteriemia/microbiologia, Bacteriemia/sangue, Recombinases/metabolismo, Acinetobacter baumannii/genética, Acinetobacter baumannii/isolamento & purificação, Staphylococcus aureus/isolamento & purificação, Staphylococcus aureus/genética, Pseudomonas aeruginosa/isolamento & purificação, Pseudomonas aeruginosa/genética, Reação em Cadeia da Polimerase/métodos, Sensibilidade e Especificidade, Bactérias/genética, Bactérias/isolamento & purificação

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PURPOSE: Spectacle lenses with peripheral lenslets have shown promise for myopia control by providing peripheral myopic defocus signals. Here, we aimed to investigate the impact of prolonged exposure (>6 months) to peripheral myopic defocus on visual information processing in myopic children. METHODS: The study included 30 myopic children who habitually wore spectacle lenses with highly aspherical lenslets (HAL group) and 34 children who habitually wore single-vision (SV group) spectacles. The quick contrast sensitivity function (qCSF) was used to measure contrast sensitivity (CS) under conditions of no or high noise. Both groups were tested with HAL and SV lenses. The perceptual template model was utilised to fit the contrast sensitivity function (CSF) and determine differences in information processing efficiency through internal additive noise ( N add $$ {N}_{\mathrm{add}} $$ ) and perceptual template gain (ß). RESULTS: The areas under the log CSF in the SV group were significantly higher than for the HAL group in both zero-noise conditions with the SV test lens (p = 0.03) and high-noise conditions with the HAL test lens (p = 0.02). For 2 cycle per degree (cpd) stimuli, ß was significantly higher in the SV group with the HAL test lens than in the HAL group (p = 0.02), while there was a trend towards a significant difference in ß for 6 cpd stimuli (p = 0.07). However, there were no significant differences in N add $$ {N}_{\mathrm{add}} $$ between the two groups, with or without noise interference. CONCLUSION: The reduced CS observed in myopic children wearing HAL lenses for 6 months or more may be due to decreased ß. This suggests that prolonged use of spectacle lenses with peripheral myopic defocus signals may compromise the central visual system's ability to process additional external noise, resulting in decreased efficiency in visual information processing.

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In the context of using aircraft as a pivotal tool for detecting radioactive hotspots, the acquisition of radioactivity data was conducted through a CeBr3 scintillation crystal detector mounted on a helicopter. However, challenges arose, including managing extensive data volumes, computationally demanding tasks, and susceptibility to local optima issues. To address these challenges and leverage the benefits of the Sparrow Search Algorithm (SSA) in global optimization and convergence speed, an improved SSA was devised. This improved version integrated SSA principles with the intricacies of searching for radioactive hotspots. The algorithm employed a matrix segmentation method to process data matrices derived from measured data, aiming to enhance efficiency and accuracy. An empirical analysis was conducted, performing 100 iterations on an experimental matrix to scrutinize the impact of matrix segmentation. Computation times and results were compared across different segmentation levels, confirming the favorable algorithmic outcomes of the method. The practical viability and convergence stability of the algorithm were further assessed using genuine measured data, with segmented matrices generated for evaluation. Remarkably, a comparison between computational outcomes and manually identified data reaffirmed the algorithm's reliability in effectively detecting radioactive hotspots.

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The gut commensal bacteria Christensenellaceae species are negatively associated with many metabolic diseases, and have been seen as promising next-generation probiotics. However, the cultured Christensenellaceae strain resources were limited, and their beneficial mechanisms for improving metabolic diseases have yet to be explored. In this study, we developed a method that enabled the enrichment and cultivation of Christensenellaceae strains from fecal samples. Using this method, a collection of Christensenellaceae Gut Microbial Biobank (ChrisGMB) was established, composed of 87 strains and genomes that represent 14 species of 8 genera. Seven species were first described and the cultured Christensenellaceae resources have been significantly expanded at species and strain levels. Christensenella strains exerted different abilities in utilization of various complex polysaccharides and other carbon sources, exhibited host-adaptation capabilities such as acid tolerance and bile tolerance, produced a wide range of volatile probiotic metabolites and secondary bile acids. Cohort analyses demonstrated that Christensenellaceae and Christensenella were prevalent in various cohorts and the abundances were significantly reduced in T2D and OB cohorts. At species level, Christensenellaceae showed different changes among healthy and disease cohorts. C. faecalis, F. tenuis, L. tenuis, and Guo. tenuis significantly reduced in all the metabolic disease cohorts. The relative abundances of C. minuta, C. hongkongensis and C. massiliensis showed no significant change in NAFLD and ACVD. and C. tenuis and C. acetigenes showed no significant change in ACVD, and Q. tenuis and Geh. tenuis showed no significant change in NAFLD, when compared with the HC cohort. So far as we know, this is the largest collection of cultured resource and first exploration of Christensenellaceae prevalences and abundances at species level.

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Fezes, Microbioma Gastrointestinal, Humanos, Fezes/microbiologia, Clostridiales/genética, Clostridiales/metabolismo, Clostridiales/isolamento & purificação, Clostridiales/classificação, Probióticos/metabolismo, Metabolômica, Genômica, Masculino, Filogenia, Feminino, Genoma Bacteriano

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BACKGROUND: Citrus canker is a significant bacterial disease caused by Xanthomonas citri subsp. citri (Xcc) that severely impedes the healthy development of the citrus industry. Especially when citrus fruit is infected by Xcc, it will reduce or even lost its commercial value. However, due to the prolonged fruiting cycle and intricate structure, much less research progress had been made in canker disease on fruit than on leaf. In fact, limited understanding has been achieved on canker development and the response to Xcc infection in fruit. RESULTS: Herein, the progression of canker disease on sweet orange fruit was tracked in the field. Results indicated that typical lesions initially appear on the sepal, style residue, nectary disk, epicarp, and peduncle of young fruits after petal fall. The susceptibility of fruits to Xcc infection diminished as the fruit developed, with no new lesions forming at the ripening stage. The establishment of an efficient method for inoculating Xcc on fruit as well as the artificial inoculation throughout the fruit's developmental cycle clarified this infection pattern. Additionally, microscopic observations during the infection process revealed that Xcc invasion caused structural changes on the surface and cross-section of the fruit. CONCLUSIONS: An efficient system for inoculation on citrus fruit with Xcc was established, by which it can serve for the evaluation of citrus germplasm for canker disease resistance and systematic research on the interactions between Xcc and citrus fruits.

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OBJECTIVE: The study investigated the effects of loving-kindness meditation (LKM) on doctors' communication anxiety, trust, calling, and defensive medicine practice. METHODS: This study recruited 94 doctors from a hospital in China, randomized them to an LKM group (n = 47), and waited for the control group (n = 47). The experimental group accepted an 8-week LKM interference while the waiting for the control group underwent no interference. Researchers measured four major variable factors (communication anxiety, trust, calling, and defensive medicine practice) before and after the LKM intervention. RESULTS: In the experimental group, trust, and calling were significantly higher, and communication anxiety, and defensive medicine practice were significantly lower than in the control group. In the control group, there were no noticeable differences in any of the four variables between the pre-test and post-test. CONCLUSIONS: The results of this study demonstrate that LKM may help to improve trust, and calling, and reduce communication anxiety and defensive medicine practice. The finding of LKM's effect extends the understanding of the integrative effects of positive psychology on the decrease of defensive medicine practice. TRIAL REGISTRATION: ChiCTR2300074568. Registered in Chinese Clinical Trial Registry (ChiCTR), 9 August, 2023.

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The Shack-Hartmann wavefront sensor (SHWFS) is widely utilized for ocular aberration measurement. However, large ocular aberrations caused by individual differences can easily make the spot move out of the range of the corresponding sub-aperture in SHWFS, rendering the traditional centroiding method ineffective. This study applied a novel convolutional neural network (CNN) model to wavefront sensing for large dynamic ocular aberration measurement. The simulation results demonstrate that, compared to the modal method, the dynamic range of our method for main low-order aberrations in ocular system is increased by 1.86 to 43.88 times in variety. Meanwhile, the proposed method also has the best measurement accuracy, and the statistical root mean square (RMS) of the residual wavefronts is 0.0082 ± 0.0185 λ (mean ± standard deviation). The proposed method generally has a higher accuracy while having a similar or even better dynamic range as compared to traditional large-dynamic schemes. On the other hand, compared with recently developed deep learning methods, the proposed method has a much larger dynamic range and better measurement accuracy.

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Full waveform inversion (FWI) is recognized as a leading data-fitting methodology, leveraging the detailed information contained in physical waveform data to construct accurate, high-resolution velocity models essential for crosshole surveys. Despite its effectiveness, FWI is often challenged by its sensitivity to data quality and inherent nonlinearity, which can lead to instability and the inadvertent incorporation of noise and extraneous data into inversion models. To address these challenges, we introduce the scale-aware edge-preserving FWI (SAEP-FWI) technique, which integrates a cutting-edge nonlinear anisotropic hybrid diffusion (NAHD) filter within the gradient computation process. This innovative filter effectively reduces noise while simultaneously enhancing critical small-scale structures and edges, significantly improving the fidelity and convergence of the FWI inversion results. The application of SAEP-FWI across a variety of experimental and authentic crosshole datasets clearly demonstrates its effectiveness in suppressing noise and preserving key scale-aware and edge-delineating features, ultimately leading to clear inversion outcomes. Comparative analyses with other FWI methods highlight the performance of our technique, showcasing its ability to produce images of notably higher quality. This improvement offers a robust solution that enhances the accuracy of subsurface imaging.

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Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(ß-GlcNAc)TGNL-OH and NYSVPSS(ß-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

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Bio-ingestion of microplastics poses a global threat to ecosystems, yet studies within nature reserves, crucial habitats for birds, remain scarce despite the well-documented ingestion of microplastics by avian species. Located in Jiangsu Province, China, the Yancheng Wetland Rare Birds Nature Reserve is home to diverse bird species, including many rare ones. This study aimed to assess the abundance and characteristics of microplastics in common bird species within the reserve, investigate microplastic enrichment across different species, and establish links between birds' habitat types and microplastic ingestion. Microplastics were extracted from the feces of 110 birds, with 84 particles identified from 37.27% of samples. Among 8 species studied, the average microplastic abundance ranged from 0.97 ± 0.47 to 43.43 ± 61.98 items per gram of feces, or 1.5 ± 0.87 to 3.4 ± 1.50 items per individual. The Swan goose (Anser cygnoides) exhibited the highest microplastic abundance per gram of feces, while the black-billed gull (Larus saundersi) had the highest abundance per individual. The predominant form of ingested microplastics among birds in the reserve was fibers, with polyethylene being the most common polymer type. Significant variations in plastic exposure were observed among species and between aquatic and terrestrial birds. This study represents the first quantitative assessment of microplastic concentrations in birds within the reserve, filling a crucial gap in research and providing insights for assessing microplastic pollution and guiding bird conservation efforts in aquatic and terrestrial environments.