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In this study, we focused on the successful construction of [(4,4'-bipy/P2Mo17Co)6] modified electrodes using the layer-by-layer assembly method for the sensitive detection of sulfathiazole (ST). The redox reaction between ST and the metal ions in the modified layer leads to the transfer of electrons, resulting in the generation of the electrical signal. The introduction of 4,4'-bipyridine (4,4'-bipy) enhanced the molecular recognition of ST by the modified electrode. Under the combined effect of P2Mo17Co and 4,4'-bipy, the sensor exhibited good performance for ST detection (LOD: 0.5616 µM, linear ST concentration range: 0-50 µM). The spiked recoveries of the two groups were 84.4%-103.2% and 90.9%-109.4% for the determination of ST residues in large yellow croaker and South American white shrimp, respectively. In addition, the electrode showed excellent performance in terms of stability, reproducibility, and anti-interference ability.

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This study aimed to assess the impact of Saccharomyces cerevisiae and different non-Saccharomyces cerevisiae (Zygosaccharomyces bailii, Hanseniaspora opuntiae and Zygosaccharomyces rouxii) on the volatile compounds and sensory properties of low-alcohol pear beverages fermented from three varieties of pear juices (Korla, Laiyang and Binzhou). Results showed that all three pear juices were favorable matrices for yeasts growth. Non-Saccharomyces cerevisiae exhibited a higher capacity for acetate ester production compared to Saccharomyces cerevisiae, resulting in a significant enhancement in sensory complexity of the beverages. PCA and sensory analysis demonstrated that pear varieties exerted a stronger influence on the crucial volatile components and aroma characteristics of the fermented beverages compared to the yeast species. CA results showed different yeast strains exhibited suitability for the fermentation of specific pear juice varieties.

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Introduction The efficacy of Telitacicept treatment in reducing proteinuria in patients with IgA nephropathy (IgAN) was indicated in a phase II clinical trial with small sample size. In this study, we conducted a large multicenter retrospective study to explore the efficacy and safety of Telitacicept in patients with IgAN. Methods This study recruited patients with IgAN from 19 sites from China who were treated with Telitacicept and had been followed up at least once or with side effect reported, since April 1, 2021 to April 1, 2023. The primary outcomes of the study were the changing in proteinuria and eGFR over time. Results A cohort of 97 patients with IgAN who were treated with Telitacicept were recruited, with a median follow-up duration of 3 months. The median baseline proteinuria was 2.3 [1.3, 3.9] g/day and eGFR was 45.0 [26.8, 73.7] ml/min/1.73m2. There was a significant reduction of proteinuria at 2,4,6 months when compared with baseline (2.3 [1.5, 4.1] vs. 1.5 [0.8, 2.3] g/day; 2.3 [1.1, 3.7] vs. 1.1 [0.6, 1.9] g/day; 2.1 [1.0, 2.7] vs. 0.9 [0.5,1.7] g/day, all P values < 0.01). The level of eGFR were comparable between at the baseline and 2, 4, 6 months of follow-up time (41.5 [29.7, 72.0] vs. 42.5 [28.8, 73.3] ml/min/1.73m2; 41.0 [26.8, 67.7] vs. 44.7 [31.0, 67.8] ml/min/1.73m2; 33.7 [24.0, 58.5] vs. 32.6 [27.8, 57.5] ml/min/1.73m2, all P values > 0.26). Telitacicept was well tolerated in the patients. Conclusions This study indicates that Telitacicept alone or on top of steroids therapy can significantly and safely reduce proteinuria in patients with IgAN. The long-term kidney protection still need to be confirmed in large Phase III trial.

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Reactive astrocytes play critical roles in the occurrence of various neurological diseases such as multiple sclerosis. Activation of astrocytes is often accompanied by a glycolysis-dominant metabolic switch. However, the role and molecular mechanism of metabolic reprogramming in activation of astrocytes have not been clarified. Here, we found that PKM2, a rate-limiting enzyme of glycolysis, displayed nuclear translocation in astrocytes of EAE (experimental autoimmune encephalomyelitis) mice, an animal model of multiple sclerosis. Prevention of PKM2 nuclear import by DASA-58 significantly reduced the activation of mice primary astrocytes, which was observed by decreased proliferation, glycolysis and secretion of inflammatory cytokines. Most importantly, we identified the ubiquitination-mediated regulation of PKM2 nuclear import by ubiquitin ligase TRIM21. TRIM21 interacted with PKM2, promoted its nuclear translocation and stimulated its nuclear activity to phosphorylate STAT3, NF-κB and interact with c-myc. Further single-cell RNA sequencing and immunofluorescence staining demonstrated that TRIM21 expression was upregulated in astrocytes of EAE. TRIM21 overexpressing in mice primary astrocytes enhanced PKM2-dependent glycolysis and proliferation, which could be reversed by DASA-58. Moreover, intracerebroventricular injection of a lentiviral vector to knockdown TRIM21 in astrocytes or intraperitoneal injection of TEPP-46, which inhibit the nuclear translocation of PKM2, effectively decreased disease severity, CNS inflammation and demyelination in EAE. Collectively, our study provides novel insights into the pathological function of nuclear glycolytic enzyme PKM2 and ubiquitination-mediated regulatory mechanism that are involved in astrocyte activation. Targeting this axis may be a potential therapeutic strategy for the treatment of astrocyte-involved neurological disease.

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Background: Severe asthma (SA) is a chronic lung disease, resistant to current treatments, symbolized by repeated symptoms of reversible airflow obstruction, airway hyper-responsiveness, and inflammation. The aim of this study was to identify genes exhibiting differential expression in individuals without asthma and SA patients. We aimed to pinpoint hub differentially expressed genes (DEGs) by utilizing a mouse model of asthma sensitized to ovalbumin (OVA). Methods: Microarray data for SA were acquired from the Gene Expression Omnibus (GEO) databases. DEGs were identified, and functional enrichment analyses were carried out. STRING and Cytoscape were utilized to design a protein-protein interaction (PPI) network and conduct module analysis. An OVA-induced asthma mice model was established. Lung tissue from the mice was collected for quantitative reverse transcription polymerase chain reaction (qRT-PCR), Western blot, and immunohistochemistry (IHC) to assess the expression of DEGs. Results: A total of 545 DEGs were identified, among which 172 genes were upregulated in SA patients compared to healthy controls. The nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3) was significantly up-regulated in SA patients [adjusted P value (Padj) =0.001]. Analysis of lung tissue using qRT-PCR, western blot, and IHC revealed higher expression of NLRP3 in OVA-induced asthma mice compared to the control group. Enrichment analysis suggests the involvement of NLRP3 in pathways related to pyroptosis, c-type lectin receptor signaling, and NOD-like receptor signaling. Conclusions: Through bioinformatics analysis, we identified a multitude of DEGs that could potentially contribute significantly to the development of SA. Notably, our findings highlight NLRP3 as a potential pivotal player in asthma pathogenesis, underscoring its prospective utility as a biomarker for SA.

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Feedstock variability represents a challenge in lignocellulosic biorefineries, as it can influence both lignocellulose deconstruction and microbial conversion processes for biofuels and biochemicals production. The impact of feedstock variability on microbial performance remains underexplored, and predictive tools for microbial behaviour are needed to mitigate risks in biorefinery scale-up. Here, twelve batches of corn stover were deconstructed via deacetylation, mechanical refining, and enzymatic hydrolysis to generate lignin-rich and sugar streams. These batches and their derived streams were characterised to identify their chemical components, and the streams were used as substrates for producing muconate and butyrate by engineered Pseudomonas putida and wildtype Clostridium tyrobutyricum, respectively. Bacterial performance (growth, product titers, yields, and productivities) differed among the batches, but no strong correlations were identified between feedstock composition and performance. To provide metabolic insights into the origin of these differences, we evaluated the effect of twenty-three isolated chemical components on these microbes, including three components in relevant bioprocess settings in bioreactors, and we found that growth-inhibitory concentrations were outside the ranges observed in the streams. Overall, this study generates a foundational dataset on P. putida and C. tyrobutyricum performance to enable future predictive models and underscores their resilience in effectively converting fluctuating lignocellulose-derived streams into bioproducts.

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Purpose: To predict the efficacy of patients treated with hepatectomy and transarterial chemoembolization (TACE) based on machine learning models using clinical and radiomics features. Patients and Methods: Patients with HCC whose first treatment was hepatectomy or TACE from June 2016 to July 2021 were collected in the retrospective cohort study. To ensure a causal effect of treatment effect and treatment modality, perfectly matched patients were obtained according to the principle of propensity score matching and used as an independent test cohort. Inverse probability of treatment weighting was used to control bias for unmatched patients, and the weighted results were used as the training cohort. Clinical characteristics were selected by univariate and multivariate analysis of cox proportional hazards regression, and radiomics features were selected using correlation analysis and random survival forest. The machine learning models (Deathhepatectomy and DeathTACE) were constructed to predict the probability of patient death after treatment (hepatectomy and TACE) by combining clinical and radiomics features, and an optimal treatment regimen was recommended. In addition, a prognostic model was constructed to predict the survival time of all patients. Results: A total of 418 patients with HCC who received either hepatectomy (n=267, mean age, 58 years ± 11 [standard deviation]; 228 men) or TACE (n=151, mean age, 59 years ± 13 [standard deviation]; 127 men) were recruited. After constructing the machine learning models Deathhepatectomy and DeathTACE, patients were divided into the hepatectomy-preferred and TACE-preferred groups. In the hepatectomy-preferred group, hepatectomy had a significantly prolonged survival time than TACE (training cohort: P < 0.001; testing cohort: P < 0.001), and vise versa for the TACE-preferred group. In addition, the prognostic model yielded high predictive capability for overall survival. Conclusion: The machine learning models could predict the outcomes difference between hepatectomy and TACE, and prognostic models could predict the overall survival for HCC patients.

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Concave nanocrystals stand out as a testament to the importance of the nanoscale morphology in dictating the functional properties of materials. In this report, we introduce a facile synthesis method for producing gold (Au) nanocrystals with a truncated octahedral morphology that features surface concavities (Au CNTOs). The incorporation of selenium (Se) doping into the truncated octahedral Au seeds was essential for their enlargement and the formation of concave structures. By simply adjusting the quantity of seeds, we could control the size of the nanocrystals while maintaining their distinctive morphology and surface concavity. The formation mechanism suggests that Se doping likely passivates the side faces, thereby slowing growth and promoting atomic deposition at the edges and corners. The resulting Se-doped Au CNTOs exhibited strong localized surface plasmon resonance (LSPR) absorptions in the visible spectrum and the SERS performance of their assemblies was demonstrated through crystal violet detection, reaching enhancement factors around 105. This study presents an innovative approach to synthesizing concave Au nanocrystals through the incorporation of selenium during a seeded growth process, offering insights into the strategic design of plasmonic nanostructures.

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To unlock the potential of indigenous non-Saccharomyces cerevisiae and develop novel starters to enhance the aromatic complexity of kiwifruit wine, Zygosaccharomyces rouxii, Pichia kudriavzevii and Meyerozyma guilliermondii were pairwise combined and then used in sequential fermentation with Saccharomyces cerevisiae. The impact of different starter cultures on the chemical composition and flavor profile of the kiwifruit wines was comprehensively analyzed, and the aroma evolution during alcoholic fermentation was investigated by examining the changes in key volatiles and their loss rates. Compared with Saccharomyces cerevisiae, mixed starter cultures not only improve antioxidant capacity but also increase esters and alcohols yields, presenting intense floral and fruity aromas with high sensory acceptability. The results indicated that sequential inoculation of non-Saccharomyces cerevisiae combination and Saccharomyces cerevisiae promoted the development of volatiles while maintaining the stability of key aroma compounds in the winemaking environment and reducing the aroma loss rates during alcoholic fermentation.

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The gut microbiome plays a key role in regulating the gut-skin axis, and host genetics partially influence this regulation. The study investigated the role of gut microbiota and host genetics in the gut-skin axis, focusing on the unusual "coffee-like" color phenotype observed in TYRP1 mutant Oujiang Color Common Carp. We employed comparative high-throughput omics data from wild-type and mutant fish to quantify the influence of both genetics and gut microbes on skin transcriptomic expression and blood metabolites. We found 525 differential metabolites (DMs) and 45 distinct gut microbial genera in TYRP1 mutant fish compared to wild type. Interaction and causal mediation analyses revealed a complex interplay. The TYRP1 mutation likely triggers an inflammatory pathway involving Acinetobacter bacteria, Leukotrience-C4 and Spermine. This inflammatory response appears to be counterbalanced by an anti-inflammatory cardiovascular genetic network. The net effect is the upregulation of COMT, PLG, C2, C3, F10, TDO2, MHC1, and SERPINF2, leading to unusual coffee-like coloration. This study highlights the intricate interplay between gut microbiota, host genetics, and metabolic pathways in shaping complex phenotypes.

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Emerging contaminants pose a potential risk to aquatic ecosystems in the Pearl River Basin, China, owing to the high population density and active industry. This study investigated samples from eight sewage treatment plants, and five surface water bodies of related watersheds. To screen the risk of emerging contaminants (ECs), and clarify their sources, this study calculated the risk quotient of detected chemical and performed source identification/apportionment using the positive matrix factorization method. In total, 149 organic pollutants were identified. Pharmaceuticals showed significant concentrations in sewage treatment plant samples (120.87 ng/L), compared with surface water samples (1.13 ng/L). The ecological risk assessment identified three chemicals with a heightened risk to aquatic organisms: fipronil sulfide, caffeine, and roxithromycin. Four principal sources of contaminants were identified: pharmaceutical wastewater, domestic sewage, medical effluent, and agricultural runoff. Pharmaceutical wastewater was the primary contributor (60.4 %), to the cumulative EC concentration and to ECs in sewage treatment plant effluent. Agricultural drainage was the main source of ECs in surface water. This study provides a strategy to obtain comprehensive information on the aquatic risks and potential sources of EC species in areas affected by artificial activities, which is of substantial importance to pollutant management and control.

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Climate change is threatening fragile alpine ecosystems and their resident ungulates, particularly the wild yak (Bos mutus) that inhabits alpine areas between the tree line and glaciers on the Tibetan Plateau. Although wild yaks tend to shift habitats in response to changes in climatic factors, the precise impacts of climate change on their habitat distribution and climate refugia remain unclear. Based on over 1000 occurrence records, the maximum entropy (MaxEnt) algorithm was applied to simulate habitat ranges in the last glacial maximum (LGM), Mid-Holocene, current stage, and three greenhouse gas emission scenarios in 2070. Three habitat patches were identified as climate refugia for wild yaks that have persisted from the LGM to the present and are projected to persist until 2070. These stable areas account for approximately 64% of the current wild yak habitat extent and are sufficiently large to support viable populations. The long-term persistence of these climate refugia areas is primarily attributed to the unique alpine environmental features of the Tibetan Plateau, where relatively stable arid or semi-arid climates are maintained, and a wide range of forage resource supplies are available. However, habitat loss by 2070 caused by insufficient protection is predicted to lead to severe fragmentation in the southeastern and northwestern Kunlun, Hengduan, central-western Qilian, and southern Tanggula-northern Himalaya Mountains. Habitat disturbance has also been caused by increasing anthropogenic effects in the southern Tanggula and northern Himalaya Mountains. We suggest that sufficient protection, transboundary cooperation, and community involvement are required to improve wild yak conservation efforts. Our combined modeling method (MaxEnt-Zonation-Linkage Mapper-FRAGSTAT) can be utilized to identify priority areas and linkages between habitat patches while assessing the conservation efficiency of protected areas and analyzing the coupled relationship between climate change and anthropogenic impacts on the habitat distribution of endangered species.

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SBS (styrene-butadiene-styrene block copolymer) is currently the most widely used asphalt modifier, and SBS modified asphalt is usually prepared by high-speed shearing. This paper combines the cavitation effect of ultrasonic to assist in the preparation of SBS modified asphalt, and conducts numerical simulation and rheological properties research on the cavitation bubbles in the molten SBS modified asphalt fluid. The cavitation bubbles in the modified asphalt fluid will expand and contract as the pressure changes inside and outside the bubbles. When the cavitation bubble is compressed to the minimum and the pressure inside the bubble reaches 1.94 × 105Pa, the direction of the velocity vector near the cavitation bubble will change with the expansion and compression of the bubble. The expansion-contraction process of a single cavitation bubble can release 6.41 × 10-7J of energy, thus breaking the long bonds in asphalt and generating a large number of free radicals react with the unsaturated C = C bonds in the SBS molecules. According to the preparation process of modified asphalt, the influence of ultrasonic wave on rheological property of modified asphalt was studied through experiments. The results show that ultrasonic treatment can enhance the elasticity of asphalt and improve the temperature sensitivity of asphalt. With the increase of ultrasonic treatment time, the anti-rutting deformation ability of SBS modified asphalt is greatly improved. At the same temperature, the recovery rate of asphalt also increases with the increase of ultrasonic treatment time, and the non-recoverable compliance (Jnr) decreases Combined with the numerical simulation of cavitation bubbles, the ultrasonic process is added to asphalt production, which is of great significance for the green production of modified asphalt and the improvement of the rheological properties of modified asphalt.

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A visible-light-induced directed decarboxylative disulfuration of α-keto acids and oxamic acids was developed. As a result, a series of versatile mono acyl disulfide derivatives was synthesized under mild and sustainable reaction conditions. This protocol has a broad substrate scope, good functional-group tolerance, and excellent synthetic applications.

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Objective: To summarize the clinical characteristics and treatment experiences of patients with plastic bronchitis (PB). Methods: All patients who were diagnosed with PB by bronchoscopic removal of tree-like casts at a single institution from January 2012 to May 2022 were retrospectively reviewed. Demographic and clinical data were retrieved from electronic patient records. Results: A total of 55 patients, with a median age of 5.3 years, were eligible for the study. Nineteen cases had underlying diseases, among which asthma was the most common. The median course of the disease before admission was 11 days. Clinical symptoms were characterized by cough and fever, while moist rales (78.2%) and dyspnea (61.8%) were the most common signs. The most common laboratory finding was elevated C-reactive protein (58.2%). Patchy opacity was the most frequent radiographic finding (81.2%), followed by consolidation (60.0%) and pleural effusion (43.6%). Respiratory pathogens were detected in 41 cases, and M. pneumoniae was the most common one (41.8%), followed by adenovirus (20.0%) and influenza B virus (10.9%). The casts were removed by alveolar lavage, combined with ambroxol immersion (63.6%) and forceps (30.9%). Patients received an average of 2.3 bronchoscopies, and the median time for the first procedure was 3 days after admission. Antibiotics were given to all patients, methylprednisolone to 33 (60.0%), and gamma globulin to 25 (45.5%). A total of 53 cases were improved with an overall mortality rate of 3.6%. Conclusions: PB in children is characterized by airway obstruction, mostly caused by respiratory infections, and timely removal of the cast by bronchoscopy is the most effective treatment.

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Urea abatement has been a prominent challenge for UPW production. This research proposed a productive strategy combining pre-chlorination and VUV/UV processes under acidic conditions to settle this problem. This study first revealed the reaction kinetics between urea and free chlorine in a large pH range from 2.5 to 9.6, where the reaction constant rate varied from 0.06 to 0.46 M-1·s-1. Substitution reaction mediated by Cl2 was the dominant process at low pH (pH<3). The differences of dominant pathways resulted in the differences in reaction products: The detected concentration of dichloramine at pH 2.5 was twice that at pH 4.5 and 6.5. Further, this study found that pre-chlorination/VUV/UV process could achieve the thorough removal of 2-mg/L urea with chlorination of less than 5 min and VUV/UV irradiation of less than 200 mJ/cm2. Chloride ions, low pH, and higher chlorine dosage were found to be the positive factors to improve urea removal efficiency in pre-chlorination/VUV/UV process. The reaction rate constants between chlorourea with·OH and·Cl were calculated to be 3.62 × 107 and 2.26 × 109 L·mol-1·s-1, respectively.·Cl,·OH and photolysis contributed 60.5 %, 22.9 % and 16.6 % in chlorourea degradation, respectively. Pre-chlorination/VUV/UV achieved a DOC removal efficiency of 78.5 %. And nitrogen in urea was converted into inorganic nitrogenous compounds. Finally, compared with direct VUV/UV/chlorine and VUV/UV/persulfate processes, this process saved more than 70 % of energy in VUV/UV unit.

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For di-nitroaromatics hydrogenation, it is a challenge to achieve the multi-step hydrogenation with high activity and selectivity due to the complexity of the process involving two nitro groups. Consequently, many precious metal catalysts suffer from low activity for this multi-step hydrogenation reaction. Herein, we employ a fully exposed Pt clusters catalyst consisting of an average of four Pt atoms on nanodiamond@graphene (Ptn/ND@G), demonstrating excellent catalytic performance for the multi-step hydrogenation of 2,4-dinitrotoluene. The TOF (40647 h-1) of Ptn/ND@G is significantly superior to that of single Pt atoms catalyst, Pt nanoparticles catalyst, and even all the known catalysts. Density functional theory calculations and absorption experiments reveal that the synergetic interaction between the multiple active sites of Ptn/ND@G facilitate the co-adsorption/activation of reactants and H2, as well as the desorption of intermediates/products, which is the key for the higher catalytic activity than single Pt atoms catalyst and Pt nanoparticles catalyst.

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Consolidated bioprocessing (CBP) of lignocellulosic biomass holds promise to realize economic production of second-generation biofuels/chemicals, and Clostridium thermocellum is a leading candidate for CBP due to it being one of the fastest degraders of crystalline cellulose and lignocellulosic biomass. However, CBP by C. thermocellum is approached with co-cultures, because C. thermocellum does not utilize hemicellulose. When compared with a single-species fermentation, the co-culture system introduces unnecessary process complexity that may compromise process robustness. In this study, we engineered C. thermocellum to co-utilize hemicellulose without the need for co-culture. By evolving our previously engineered xylose-utilizing strain in xylose, an evolved clonal isolate (KJC19-9) was obtained and showed improved specific growth rate on xylose by ∼3-fold and displayed comparable growth to a minimally engineered strain grown on the bacteria's naturally preferred substrate, cellobiose. To enable full xylan deconstruction to xylose, we recombinantly expressed three different ß-xylosidase enzymes originating from Thermoanaerobacterium saccharolyticum into KJC19-9 and demonstrated growth on xylan with one of the enzymes. This recombinant strain was capable of co-utilizing cellulose and xylan simultaneously, and we integrated the ß-xylosidase gene into the KJC19-9 genome, creating the KJCBXint strain. The strain, KJC19-9, consumed monomeric xylose but accumulated xylobiose when grown on pretreated corn stover, whereas the final KJCBXint strain showed significantly greater deconstruction of xylan and xylobiose. This is the first reported C. thermocellum strain capable of degrading and assimilating hemicellulose polysaccharide while retaining its cellulolytic capabilities, unlocking significant potential for CBP in advancing the bioeconomy.

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BACKGROUND: Current research on radiomics for diagnosing and prognosing acute pancreatitis predominantly revolves around model development and testing. However, there is a notable absence of ongoing interpretation and analysis regarding the physical significance of these models and features. Additionally, there is a lack of extensive exploration of visual information within the images. This limitation hinders the broad applicability of radiomics findings. This study aims to address this gap by specifically analyzing filtered Computed Tomography (CT) image features of acute pancreatitis to identify meaningful visual markers in the pancreas and peripancreatic area. METHODS: Numerous filtered CT images were obtained through pyradiomics. The window width and window level were fine-tuned to emphasize the pancreas and peripancreatic regions. Subsequently, the LightGBM algorithm was employed to conduct an embedded feature screening, followed by statistical analysis to identify features with statistical significance (p-value < 0.01). Within the purview of the study, for each filtering method, features of high importance to the preceding prediction model were incorporated into the analysis. The image visual markers were then systematically sought in reverse, and their medical interpretation was undertaken to a certain extent. RESULTS: In Laplacian of Gaussian filtered images within the pancreatic region, severe acute pancreatitis (SAP) exhibited fewer small areas with repetitive greyscale patterns. Conversely, in the peripancreatic region, SAP displayed greater irregularity in both area size and the distribution of greyscale levels. In logarithmic images, SAP demonstrated reduced low greyscale connectivity in the pancreatic region, while showcasing a higher average variation in greyscale between two adjacent pixels in the peripancreatic region. Moreover, in gradient images, SAP presented with decreased repetition of two adjacent pixel greyscales within the pancreatic region, juxtaposed with an increased inhomogeneity in the size of the same greyscale region within the δ range in the peripancreatic region. CONCLUSIONS: Various filtered images convey distinct physical significance and properties. The selection of the appropriate filtered image, contingent upon the characteristics of the Region of Interest (ROI), enables a more comprehensive capture of the heterogeneity of the disease.

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Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a new optimization procedure to identify the top network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

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