Predicting nickel concentration in soil using fractional-order derivative and visible-near-infrared spectroscopy indices.

Accurate monitoring and estimation of heavy metal concentrations is an important process in the prevention and treatment of soil pollution. However, the weak correlation between spectra and heavy metals in soil makes it difficult to use spectroscopy in predicting areas with a risk of heavy metal pollution. In this paper, a method for detection of Ni in soil in eastern China using the fractional-order derivative (FOD) and spectral indices was proposed. The visible-near-infrared (Vis-NIR) spectra were preprocessed using the FOD (range: 0 to 2, interval: 0.1) to solve the problems of baseline drift and overlapping peaks in the original spectra. The product index (PI), ratio index (RI), sum index (SI), difference index (DI), normalized difference index (NDI), and brightness index (BI) were applied and compared. The results showed that the spectral detail increased as the FOD increased, and the interference of the baseline drift and overlapping peaks was eliminated as the spectral reflectance decreased. Furthermore, the FOD extracted the spectral sensitivity information more effectively and improved the correlation between the Vis-NIR spectra and the Ni concentration, and the NDI had a maximum correlation coefficient (r) of 0.803 for order 1.9. The estimation model based on the NDI dataset constructed after FOD processing had the best performance, with a validation accuracy [Formula: see text] of 0.735, RMSE of 3.848, and RPD of 2.423. In addition, this method is easy to carry out and suitable for estimating other heavy metal elements in soil.

Tumor perfusion enhancement by microbubbles ultrasonic cavitation reduces tumor glycolysis metabolism and alleviate tumor acidosis.

The tumor microenvironment is increasingly acknowledged as a critical contributor to cancer progression, mediating genetic and epigenetic alterations. Beyond diverse cellular interactions from the microenvironment, physicochemical factors such as tumor acidosis also significantly affect cancer dynamics. Recent research has highlighted that tumor acidosis facilitates invasion, immune escape, metastasis, and resistance to therapies. Thus, noninvasive measurement of tumor acidity and the development of targeted interventions represent promising strategies in oncology. Techniques like contrast-enhanced ultrasound (CEUS) can effectively assess blood perfusion, while ultrasound-stimulated microbubble cavitation (USMC) has proven to enhance tumor blood perfusion. We therefore aimed to determine whether CEUS assesses tumor acidity and whether USMC treatment can modulate tumor acidity. Firstly, we tracked CEUS perfusion parameters in MCF7 tumor models and compared them with in vivo tumor pH recorded by pH microsensors. We found that the peak intensity and area under curve of tumor contrast-enhanced ultrasound correlated well with tumor pH. We further conducted USMC treatment on MCF7 tumor-bearing mice, tracked changes of tumor blood perfusion and tumor pH in different perfusion regions before and after the USMC treatment to assess its impact on tumor acidity and optimize therapeutic ultrasound pressure. We discovered that USMC with 1.0 Mpa significantly improved tumor blood perfusion and tumor pH. Furthermore, tumor vascular pathology and PGI2 assays indicated that improved tumor perfusion was mainly due to vasodilation rather than angiogenesis. More importantly, analysis of glycolysis-related metabolites and enzymes demonstrated USMC treatment can reduce tumor acidity by reducing tumor glycolysis. These findings support that CEUS may serve as a potential biomarker to assess tumor acidity and USMC is a promising therapeutic modality for reducing tumor acidosis.

A Best-Fitting B-Spline Neural Network Approach to the Prediction of Advection-Diffusion Physical Fields with Absorption and Source Terms.

This paper proposed a two-dimensional steady-state field prediction approach that combines B-spline functions and a fully connected neural network. In this approach, field data, which are determined by corresponding control vectors, are fitted by a selected B-spline function set, yielding the corresponding best-fitting weight vectors, and then a fully connected neural network is trained using those weight vectors and control vectors. The trained neural network first predicts a weight vector using a given control vector, and then the corresponding field can be restored via the selected B-spline set. This method was applied to learn and predict two-dimensional steady advection-diffusion physical fields with absorption and source terms, and its accuracy and performance were tested and verified by a series of numerical experiments with different B-spline sets, boundary conditions, field gradients, and field states. The proposed method was finally compared with a generative adversarial network (GAN) and a physics-informed neural network (PINN). The results indicated that the B-spline neural network could predict the tested physical fields well; the overall error can be reduced by expanding the selected B-spline set. Compared with GAN and PINN, the proposed method also presented the advantages of a high prediction accuracy, less demand for training data, and high training efficiency.

Modeling and self-supporting printing simulation of fuse filament fabrication.

This study presented a comprehensive computational fluid dynamics-based model for fused filament fabrication (FFF) three-dimensional (3D) printing multiphase and multiphysics coupling. A model based on the framework of computational fluid dynamics was built, utilizing the front-tracking method for high precision of multiphase material interfaces, a fully resolved simulation at the mesoscale explores the underlying physical mechanism of the self-supported horizontal printing. The study investigated the influence of printing temperature and velocity on the FFF process, exhibiting a certain self-supporting forming ability over a specific range. The results indicated that during the printing of large-span horizontal extension structures, the bridge deck material transitions from initial straight extension to sagging deformation, ultimately adopting a curved shape. The straight extension distance is inversely proportional to the depth of the sagging deformation. Additionally, the study revealed that printing temperature primarily affected the curing time of the molten material, while printing velocity fundamentally affected the relaxation time of both thermal and dynamic characteristics of the material.

Intraductal photothermal ablation: a noninvasive approach for early breast cancer treatment and prevention.

Background: Innovative treatment strategies for early-stage breast cancer (BC) are urgently needed. Tumors originating from mammary ductal cells present an opportunity for targeted intervention. Methods: We explored intraductal therapy via natural nipple openings as a promising non-invasive approach for early BC. Using functional Near-infrared II (NIR-II) nanomaterials, specifically NIR-IIb quantum dots conjugated with Epep polypeptide for ductal cell targeting, we conducted in situ imaging and photothermal ablation of mammary ducts. Intraductal administration was followed by stimulation with an 808 nm laser. Results: This method achieved precise ductal destruction and heightened immunological responses in the microenvironment. The technique was validated in mouse models of triple-negative BC and a rat model of ductal carcinoma in situ, demonstrating promising therapeutic potential for localized BC treatment and prevention. Conclusion: Our study demonstrated the effectiveness of NIR-II nanoprobes in guiding non-invasive photothermal ablation of mammary ducts, offering a compelling avenue for early-stage BC therapy.

Does androgenic alopecia aggravate the risk of prostate cancer? Evidence from Mendelian randomization.

Background: Epidemiological reports indicate a potential association between androgenic alopecia (AGA) and increased prostate cancer (PC) prevalence, but conflicting reports also exist. This study aims to elucidate the causality of AGA on PC risk using Mendelian randomization (MR) analysis. Materials and methods: Two-sample MR analyses utilized public genome-wide association studies summary data for single-nucleotide polymorphisms associated with AGA. Four statistical methods were used: inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, with IVW as the preliminary estimation method. Additionally, sensitivity analyses were conducted to address pleiotropic bias. Results: Genetically proxied AGA did not demonstrate a causal effect on PC risk (IVW P > 0.05). Consistently, complementary methods yielded results aligned with IVW. Conclusions: Our MR analysis indicates no causal relationship between genetically predicted AGA and PC risk, suggesting that observed associations in epidemiological studies may not be causal.

Risk factors related to venous thromboembolism in pregnant women: a meta-analysis.

INTRODUCTION: The aim of this paper was to make a preliminary analysis of the risk factors related to venous thromboembolism (VTE) in pregnant women by Meta-analysis. EVIDENCE ACQUISITION: Three databases including PubMed, Web of Science, and The National Library of Medicine (NLM) were systematically searched from their establishment to January 1, 2023, and the obtained data were statistically analyzed using RevMan5.3 software. EVIDENCE SYNTHESIS: A total of 10 studies were included, involving 22 risk factors, of which 16 were included for further analysis. Meta analysis showed that cesarean section (OR=2.05, 95%CI: 1.71, 2.47, P=0.007), gestational diabetes (OR=1.17, 95%CI: 1.09, 1.27, P<0.001), eclampsia or preeclampsia (OR=1.88, 95%CI: 1.42, 2.49, P< 0.001), obesity (OR=1.19, 95%CI: 1.04, 1.86, P=0.028), twin or multiple pregnancy (OR=2.34, 95%CI: 1.46, 3.76, P<0.001), chronic heart disease (OR=3.59, 95%CI: 3.28, 3.92, P<0.001), and blood transfusion history (OR=3.20, 95%CI: 2.78, 3.68, P<0.001) were risk factors for VTE in pregnant women. CONCLUSIONS: Existing evidence suggests that cesarean section, gestational diabetes, eclampsia or preeclampsia, obesity (body mass index ≥30 kg/m2), twin or multiple pregnancy, chronic heart disease, and blood transfusion history may be risk factors for VTE in pregnant women. In clinical practice, the evaluation and management of VTE should be strengthened, and a model for clinical prediction of VTE can be established to provide a reference for the prevention of VTE.

Development of a live attenuated vaccine candidate for equid alphaherpesvirus 1 control: a step towards efficient protection.

Equid alphaherpesvirus 1 (EqAHV1) is a viral pathogen known to cause respiratory disease, neurologic syndromes, and abortion storms in horses. Currently, there are no vaccines that provide complete protection against EqAHV1. Marker vaccines and the differentiation of infected and vaccinated animals (DIVA) strategy are effective for preventing and controlling outbreaks but have not been used for the prevention of EqAHV1 infection. Glycoprotein 2 (gp2), located on the envelope of viruses (EqAHV1), exhibits high antigenicity and functions as a molecular marker for DIVA. In this study, a series of EqAHV1 mutants with deletion of gp2 along with other virulence genes (TK, UL24/TK, gI/gE) were engineered. The mutant viruses were studied in vitro and then in an in vivo experiment using Golden Syrian hamsters to assess the extent of viral attenuation and the immune response elicited by the mutant viruses in comparison to the wild-type (WT) virus. Compared with the WT strain, the YM2019 Δgp2, ΔTK/gp2, and ΔUL24/TK/gp2 strains exhibited reduced growth in RK-13 cells, while the ΔgI/gE/gp2 strain exhibited significantly impaired proliferation. The YM2019 Δgp2 strain induced clinical signs and mortality in hamsters. In contrast, the YM2019 ΔTK/gp2 and ΔUL24/TK/gp2 variants displayed diminished pathogenicity, causing no observable clinical signs or fatalities. Immunization with nasal vaccines containing YM2019 ΔTK/gp2 and ΔUL24/TK/gp2 elicited a robust immune response in hamsters. In particular, compared with the vaccine containing the ΔTK/gp2 strain, the vaccine containing the ΔUL24/TK/gp2 strain demonstrated enhanced immune protection upon challenge with the WT virus. Furthermore, an ELISA for gp2 was established and refined to accurately differentiate between infected and vaccinated animals. These results confirm that the ΔUL24/TK/gp2 strain is a safe and effective live attenuated vaccine candidate for controlling EqAHV1 infection.

Research advances in serum chitinase-3-like protein 1 in liver fibrosis.

While liver fibrosis remains a serious, progressive, chronic liver disease, and factors causing damage persist, liver fibrosis may develop into cirrhosis and liver cancer. However, short-term liver fibrosis is reversible. Therefore, an early diagnosis of liver fibrosis in the reversible transition phase is important for effective treatment of liver diseases. Chitinase-3-like protein 1 (CHI3L1), an inflammatory response factor that participates in various biological processes and is abundant in liver tissue, holds promise as a potential biomarker for liver diseases. Here, we aimed to review research developments regarding serum CHI3L1 in relation to the pathophysiology and diagnosis of liver fibrosis of various etiologies, providing a reference for the diagnosis, treatment, and prognosis of liver diseases.

Optimizing Systems for Robust Heterologous Production of Biosurfactants Rhamnolipid and Lyso-Ornithine Lipid in Pseudomonas putida KT2440.

Surfactants are amphiphilic molecules that are capable of mixing water and oil. Biosurfactants are eco-friendly, low-toxicity, and stable to a variety of environmental factors. Optimizing conditions for microorganisms to produce biosurfactants can lead to improved production suitable for scaling up. In this study, we compared heterologous expression levels of the luminescence system luxCDABE operon controlled by regulatable promoters araC-PBAD and its strong version araC-PBAD-SD in Escherichia coli K12, Pseudomonas aeruginosa PAO1, and P. putida KT2440. Real-time monitoring of luminescence levels in the three strains indicated that luxCDABE controlled by araC-PBAD-SD promoter with 0.2% arabinose supplementation in P. putida produced the highest level of luminescence. By using the araC-PBAD-SD promoter-controlled rhlAB expression in P. putida, we were able to produce mono-rhamnolipid at a level of 1.5 g L-1 when 0.02% arabinose was supplemented. With the same system to express olsB, lyso-ornithine lipid was produced at a level of 10 mg L-1 when 0.2% arabinose was supplemented. To our knowledge, this is the first report about optimizing conditions for lyso-ornithine lipid production at a level up to 10 mg L-1. Taken together, our results demonstrate that regulatable araC-PBAD-SD promoter in P. putida KT2440 is a useful system for heterologous production of biosurfactants.

Asymmetric three-component Tsuji-Trost allylation reaction enabled by chiral aldehyde/palladium combined catalysis.

Despite the long-standing exploration of the catalytic asymmetric Tsuji-Trost allylation reaction since the mid-20th century, most reported instances have adhered to a two-component approach. Here, we present a remarkably efficient three-component asymmetric allylation reaction enabled by the collaborative action of chiral aldehyde and palladium. A diverse array of NH2-unprotected amino acid esters, aryl or alkenyl iodides, and allyl alcohol esters exhibit robust participation in this reaction, resulting in the synthesis of structurally diverse non-proteinogenic α-amino acid esters with favorable experimental outcomes. Mechanistic investigations reveal the dominance of the allylation/Heck coupling cascade in reactions involving electron-rich aryl iodides, while the Heck coupling/allylation cascade emerges as the dominant pathway in reactions involving electron-deficient aryl iodides. This chiral aldehyde/palladium combining catalytic system precisely governs the chemoselectivity of C-allylation and N-allylation, the regioselectivity of linear and branched allylation, and the enantioselectivity of C-allylation products.

Serotype distribution, antibiotic resistance, multilocus sequence typing, and virulence factors of invasive and non-invasive Streptococcus pneumoniae in Northeast China from 2000 to 2021.

Streptococcus pneumoniae infection is a major public health concern with high morbidity and mortality rates. This study aimed to evaluate the serotype distribution, antimicrobial resistance changes, clonal composition, and virulence factors of S. pneumoniae isolates causing pneumococcal disease in northeast China from 2000 to 2021. A total of 1,454 S. pneumoniae isolates were included, with 568 invasive strains and 886 non-invasive strains. The patients from whom the S. pneumoniae were isolated ranged in age from 26 days to 95 years, with those ≤ 5 years old comprising the largest group (67.19%). 19 F, 19 A, 23 F, 14, and 6B were the most common serotypes, of which 19 A and 19 F were the main serotypes of invasive and non-invasive S. pneumoniae, respectively. CC271 was the most common multilocus sequence type. Serotype 14 had the lowest expression of cbpA, rrgA, and psrP genes, but expression levels of 19 A and 19 F genes were similar. All isolates were sensitive to ertapenem, moxifloxacin, linezolid, and vancomycin but highly resistant to macrolides, tetracyclines, and cotrimoxazole. Simultaneous resistance to erythromycin, clindamycin, tetracyclines, and trimethoprim/sulfamethoxazole was common pattern among multidrug-resistant isolates. Non-invasive S. pneumoniae had higher resistance to ß-lactam antibiotics than invasive strains. 19 A and 19 F were the main strains of penicillin-resistant S. pneumoniae. The resistance rate of ß-lactam antibiotics decreased from 2017 to 2021 compared to previous periods. Including PCV13 in the national immunization program can reduce the morbidity and mortality rates of pneumococcal disease effectively.

Preparation, structural and morphological characterization of cartilage type II collagen peptide assemblies from sturgeon head.

BACKGROUND: Sturgeon cartilage type II collagen peptides (SHCPs) can self-assemble and be used to prepare collagen peptide assemblies. Self-assembled peptides have great potential for applications in the food industry. In the present study, self-assembled peptides were prepared from sturgeon cartilage and then characterized. RESULTS: The SHCPs self-assembled and formed collagen peptide assemblies. After response surface experiment optimization, the optimal enzyme digestion process comprised 43.1 °C, 3.37 h and 0.96% enzyme addition, and the peptide yield was 78.46%. Physicochemical analysis showed that the SHCPs were amphiphilic, with an average molecular weight of 1081 Da, and were rich in hydrophobic amino acids. Peptide sequence identification showed that the peptides of SHCPs with polar amino acids followed by hydrophobic amino acids could be self-assembled through hydrogen bonding and hydrophobic interaction. Through turbidity experiments, Fourier transform infrared spectroscopy and scanning electron microscopy, we demonstrated that SHCPs can self-assemble into reticular and tubular structures under specific conditions. Furthermore, both the SHCPs-Ca and SHCPs-Mg assemblies were stabilized within a pH range consistent with that of the human gastrointestinal tract. CONCLUSION: The present study provides a simple and safe method for preparing novel self-assembled peptide materials from sturgeon by-products, providing a scientific basis for the exploitation of sturgeon cartilage and potentially reducing resource wastage. © 2024 Society of Chemical Industry.

Uncovering novel mechanisms of chitinase-3-like protein 1 in driving inflammation-associated cancers.

Chitinase-3-like protein 1 (CHI3L1) is a secreted glycoprotein that is induced and regulated by multiple factors during inflammation in enteritis, pneumonia, asthma, arthritis, and other diseases. It is associated with the deterioration of the inflammatory environment in tissues with chronic inflammation caused by microbial infection or autoimmune diseases. The expression of CHI3L1 expression is upregulated in several malignant tumors, underscoring the crucial role of chronic inflammation in the initiation and progression of cancer. While the precise mechanism connecting inflammation and cancer is unclear, the involvement of CHI3L1 is involved in chronic inflammation, suggesting its role as a contributing factor to in the link between inflammation and cancer. CHI3L1 can aggravate DNA oxidative damage, induce the cancerous phenotype, promote the development of a tumor inflammatory environment and angiogenesis, inhibit immune cells, and promote cancer cell growth, invasion, and migration. Furthermore, it participates in the initiation of cancer progression and metastasis by binding with transmembrane receptors to mediate intracellular signal transduction. Based on the current research on CHI3L1, we explore introduce the receptors that interact with CHI3L1 along with the signaling pathways that may be triggered during chronic inflammation to enhance tumorigenesis and progression. In the last section of the article, we provide a brief overview of anti-inflammatory therapies that target CHI3L1.

Camera calibration optimization algorithm that uses a step function.

Camera calibration is very important when planning machine vision tasks. Calibration may involve 3D reconstruction, size measurement, or careful target positioning. Calibration accuracy directly affects the accuracy of machine vision. The parameters in many image distortion models are usually applied to all image pixels. However, this may be associated with rather high pixel reprojection errors at image edges, compromising camera calibration accuracy. In this paper, we present a new camera calibration optimization algorithm that features a step function that splits images into center and edge regions. First, based on the increasing pixel reprojection errors according to the pixel distance away from the image center, we gave a flexible method to divide an image into two regions, center and boundary. Then, the algorithm automatically determines the step position, and the calibration model is rebuilt. The new model can calibrate the distortions at the center and boundary regions separately. Optimized by the method, the number of distortion parameters in the old model is doubled, and different parameters represent different distortions within two regions. In this way, our method can optimize traditional calibration models, which define a global model to describe the distortion of the whole image and get a higher calibration accuracy. Experimentally, the method significantly improved pixel reprojection accuracy, particularly at image edges. Simulations revealed that our method was more flexible than traditional methods.

Effect of Perioperative Blood Transfusion on Prognosis after Radical Resection in Patients with Non-Metastatic Renal Cell Carcinoma: A Retrospective Analysis.

OBJECTIVE: Advancements in medical science have improved non-metastatic renal cell carcinoma (NM-RCC) treatment strategies, but long-term survival is influenced by various factors, including perioperative blood transfusion. This study aims to analyse prognostic factors in patients with NM-RCC after radical nephrectomy. METHODS: From January 2018 to December 2021, a total of 132 patients with NM-RCC after radical nephrectomy were studied. According to 2-year follow-up data, the patients were categorised into case (with poor outcomes, including pneumothorax, renal issues, recurrence or death) and control groups. Data on demographics, clinical characteristics and perioperative blood transfusion were collected, and key prognostic factors were identified through logistic regression. RESULTS: A total of 32 patients with poor prognosis were included in the case group, accounting for 24.24% (32/132), and 100 patients without poor prognosis were included in the control group, accounting for 75.76% (100/132). Tumour stage, tumour size and perioperative blood transfusion were all risk factors for the prognosis of patients, and odds ratio (OR) >1. The above indicators had high predictive value for the prognosis of patients after surgery. CONCLUSIONS: The prognostic factors of patients with NM-RCC after radical nephrectomy include tumour stage, tumour size and perioperative blood transfusion, and each factor had predictive value.

Regulation of IFP in solid tumours through acoustic pressure to enhance infiltration of nanoparticles of various sizes.

Numerous nanomedicines have been developed recently that can accumulate selectively in tumours due to the enhanced permeability and retention (EPR) effect. However, the high interstitial fluid pressure (IFP) in solid tumours limits the targeted delivery of nanomedicines. We were previously able to relieve intra-tumoural IFP by low-frequency non-focused ultrasound (LFNFU) through ultrasonic targeted microbubble destruction (UTMD), improving the targeted delivery of FITC-dextran. However, the accumulation of nanoparticles of different sizes and the optimal acoustic pressure were not evaluated. In this study, we synthesised Cy5.5-conjugated mesoporous silica nanoparticles (Cy5.5-MSNs) of different sizes using a one-pot method. The Cy5.5-MSNs exhibited excellent stability and biosafety regardless of size. MCF7 tumour-bearing mice were subjected to UTMD over a range of acoustic pressures (0.5, 0.8, 1.5 and 2.0 MPa), and injected intravenously with Cy5.5-MSNs. Blood perfusion, tumour IFP and intra-tumoural accumulation of Cy5.5-MSNs were analysed. Blood perfusion and IFP initially rose, and then declined, as acoustic pressure intensified. Furthermore, UTMD significantly enhanced the accumulation of differentially sized Cy5.5-MSNs in tumour tissues compared to that of the control group, and the increase was sevenfold higher at an acoustic pressure of 1.5 MPa. Taken together, UTMD enhanced the infiltration and accumulation of Cy5.5-MSNs of different sizes in solid tumours by reducing intra-tumour IFP.

Enhancement of Motor Learning and Corticospinal Excitability: The Role of Electroacupuncture and Motor Training in Healthy Volunteers.

BACKGROUND This study embarked on an innovative exploration to elucidate the effects of integrating electroacupuncture (EA) with motor training (MT) on enhancing corticospinal excitability and motor learning. Central to this investigation is the interplay between homeostatic and non-homeostatic metaplasticity processes, providing insights into how these combined interventions may influence neural plasticity and motor skill acquisition. MATERIAL AND METHODS The investigation enrolled 20 healthy volunteers, subjecting them to 4 distinct interventions to parse out the individual and combined effects of EA and MT. These interventions were EA alone, MT alone, EA-priming followed by MT, and MT-priming followed by EA. The assessment of changes in primary motor cortex (M1) excitability was conducted through motor-evoked potentials (MEPs), while the grooved pegboard test (GPT) was used to evaluate alterations in motor performance. RESULTS The findings revealed that EA and MT independently contributed to enhanced M1 excitability and motor performance. However, the additional priming with EA or MT did not yield further modulation in MEPs amplitudes. Notably, EA-priming was associated with improved GPT completion times, underscoring its potential in facilitating motor learning. CONCLUSIONS The study underscores that while EA and MT individually augment motor cortex excitability and performance, their synergistic application does not further enhance or inhibit cortical excitability. This points to the involvement of non-homeostatic metaplasticity mechanisms. Nonetheless, EA emerges as a critical tool in preventing M1 overstimulation, thereby continuously fostering motor learning. The findings call for further research into the strategic application of EA, whether in isolation or with MT, within clinical settings to optimize rehabilitation outcomes.

Active shimming for a 25 T NMR superconducting magnet by spectrum convergence method.

In the design of ultrahigh field nuclear magnetic resonance (NMR) superconducting magnets, it typically requires a high homogeneous magnetic field in the diameter of spherical volume (DSV) to obtain high spectrum resolution. However, shimming technique presents challenges due to the magnet bore space limitations, as accurate measurement of magnetic field distribution is very difficult, especially for customized micro-bore magnets. In this study, we introduced an active shimming method that utilized iterative adjustment of shim coil currents to improve the magnetic field homogeneity based on the full width at half maximum (FWHM) of the spectrum. The proposed method can determine the optimal set of currents for shim coils, effectively enhancing spatial field homogeneity by converging the FWHM. Experimental validation on a 25 T NMR superconducting magnet demonstrated the efficacy of the proposed method. Specifically, the active shimming method improved the field homogeneity of a 10 mm DSV from 7.09 ppm to 2.27 ppm with only four shim coils, providing a superior magnetic field environment for solid NMR and further magnetic resonance imaging (MRI) experiment. Furthermore, the proposed method can be promoted to more customized micro-bore magnets that require high magnetic field homogeneity.