High-Efficiency Microwave Wireless Power Transmission via Reflective Phase Gradient Metasurfaces and Surface Wave Aggregation.

Microwave Wireless Power Transfer (MWPT) technology is crucial for emergency power supply during natural disasters and powering off-grid equipment. Traditional antenna arrays, however, suffer from low energy capture efficiency, difficult impedance matching, complex synthetic networks, and intricate manufacturing processes. This paper introduces a microwave energy receiver design utilizing Reflective Phase Gradient Metasurfaces (R-PGMs) and surface wave energy convergence technology. The design leverages the effective plane wave-to-surface wave conversion capability of R-PGMs to transform incident microwave energy into a surface wave mode, which is then efficiently harvested using a circular energy convergence array before being output to a coupling port. By optimizing R-PGM parameters, an ideal 60° phase gradient distribution is achieved, facilitating the focus of surface wave energy via dispersion characteristics. These components are integrated into a hybrid antenna array, complemented by a matched energy output port structure. Numerical simulations show that this array can efficiently convert microwave energy from plane waves to surface waves, achieving a conversion efficiency of 85.32% and a collection efficiency of 68.26%. Experimental results corroborate these findings, with peak energy collection efficiency reaching 64.68% at 5.8 GHz and an RF-DC conversion efficiency of 42%, confirming the design's efficacy. Compared to conventional methods, this design simplifies the system by avoiding complex combining networks and significantly enhances the efficiency of microwave MWPT.

Diagnostic accuracy of exhaled nitric oxide for the non-invasive identification of patients with fibrotic metabolic dysfunction-associated steatohepatitis.

BACKGROUND: Fibrotic metabolic dysfunction-associated steatohepatitis (MASH) is a condition at risk of progressing to advanced liver disease. We examined whether an innovative exhaled nitric oxide (eNO) breath test (BT) can accurately diagnose fibrotic MASH without requiring blood tests. METHODS: One hundred and forty-seven patients with MASH were recruited, and all tests were undertaken within 1 week of recruitment. With fibrotic MASH (NAS ≥ 4 and fibrosis stage ≥ 2) as the main outcome indicator, the diagnostic efficacy of eNO in identifying fibrotic MASH was compared to other validated models for advanced fibrosis requiring venesection, namely FAST, Agile 3+, and FIB-4 scores. RESULTS: The mean age was 40.36 ± 12.28 years, 73.5% were men. Mean body mass index was 28.83 ± 4.31 kg/m2. The proportion of fibrotic MASH was 29.25%. The area under the receiver operating curve for eNO in diagnosing fibrotic MASH was 0.737 [95% CI 0.650-0.823], which was comparable to FAST (0.751 [0.656-0.846]), Agile 3+ (0.764 [0.670-0.858]), and FIB-4 (0.721 [0.620-0.821]) (all DeLong test p > 0.05). A cut-off of eNO <8.5 ppb gave a sensitivity of 86.0% and a negative predictive value of 88.5% for ruling-out fibrotic MASH. A cut-off of eNO >13.5 ppb provided a specificity of 91.3% and a positive predictive value of 65.4% for ruling-in fibrotic MASH. Sensitivity analyses demonstrated that the diagnostic efficacy of eNO was similar across characteristics such as age. Moreover, adding vibration-controlled transient elastography-LSM (liver stiffness measurement) reduced the uncertainty interval from 46.9% to 39.5%. CONCLUSIONS: The eNO-BT is a promising simple test for non-invasively identifying fibrotic MASH, and its performance is further improved by adding LSM measurement.

Efficacy of neuroendoscopy-assisted surgery in the treatment of chronic subdural hematoma: a meta-analysis.

BACKGROUND: Chronic subdural hematoma (CSDH) is one of the most common diseases in neurosurgery. It is the result of chronic intracranial hemorrhage that converges between the dura mater and arachnoid three weeks after externally injuring the head. Chronic subdural hematomas are a common complication in neurosurgery. With the gradual increase in the amount of hematoma, the surrounding brain tissue is pushed and compressed, resulting in corresponding clinical symptoms and signs. It is reported that the overall incidence rate of CSDH is 1.72 to 20.6 per 100,000 people every year, and the incidence rate of the elderly is particularly high. METHODS: The computer retrieves eight databases to obtain controlled trials at home and abroad on the effects of neuroendoscopy-assisted surgery in patients with chronic subdural hematoma. After a rigorous literature quality evaluation, data analysis was performed using RevMan 5.3 software. RESULTS: Twenty studies were ultimately included in this meta-analysis. Seventeen studies reported the Recurrence rate of the test group and the control group, which was significantly lower (OR 0.27; 95% Cl 0.18, 0.38; P < 0.01) than the control group, Recovery rate (OR 1.18; 95% Cl 1.01, 1.38; P = 0.03), Total effective rate (OR 1.11; 95% Cl 1.04, 1.17; P < 0.01), Operative time (SMD 15.78; 95% Cl 9.69, 21.86; P < 0.01), Hospital stay (SMD - 1.66; 95% Cl - 2.17, - 1.14; P < 0.01) and Complications (OR 0.48; 95% Cl 0.30, 0.78; P < 0.01). CONCLUSION: The results of this study suggest that neuroendoscopy-assisted surgery may be effective in patients with chronic subdural hematoma, as evidenced by recurrence rate, recovery rate, total effective rate, operative time, hospital stay, complications, and the above conclusions need to be verified by more high-quality studies.

Uninvolved liver dose prediction in stereotactic body radiation therapy for liver cancer based on the neural network method.

BACKGROUND: The quality of a radiotherapy plan often depends on the knowledge and expertise of the plan designers. AIM: To predict the uninvolved liver dose in stereotactic body radiotherapy (SBRT) for liver cancer using a neural network-based method. METHODS: A total of 114 SBRT plans for liver cancer were used to test the neural network method. Sub-organs of the uninvolved liver were automatically generated. Correlations between the volume of each sub-organ, uninvolved liver dose, and neural network prediction model were established using MATLAB. Of the cases, 70% were selected as the training set, 15% as the validation set, and 15% as the test set. The regression R-value and mean square error (MSE) were used to evaluate the model. RESULTS: The volume of the uninvolved liver was related to the volume of the corresponding sub-organs. For all sets of R-values of the prediction model, except for Dn0 which was 0.7513, all R-values of Dn10-Dn100 and Dnmean were > 0.8. The MSE of the prediction model was also low. CONCLUSION: We developed a neural network-based method to predict the uninvolved liver dose in SBRT for liver cancer. It is simple and easy to use and warrants further promotion and application.

Development and validation of prognostic models based on 18F-FDG PET radiomics, metabolic parameters, and clinical factors for elderly DLBCL patients.

This study aimed to assess the predictive value of baseline 18F-FDG PET radiomics features, metabolic parameters, and clinical factors for PFS and OS in elderly DLBCL patients. Using LASSO COX regression, we derived Radscore from PET radiomics features. We constructed and externally validated prognostic models, evaluating their performance through various metrics. From 341 training set patients and 83 external validation set patients revealed significant correlations between PET radiomics features and survival outcomes. Multivariate COX analysis identified associations of radiomics features (Radscore), metabolic parameters (TMTV, Dmax), and clinical factors (ECOG PS, hemoglobin level) with PFS and OS. In external validation, the combined model incorporating radiomic features, metabolic parameters, and clinical factors showed superior predictive performance for PFS and OS compared to other models. The combined model had higher C-index values for both PFS and OS, and its td-ROC curves exhibited significantly higher AUCs. Calibration curves demonstrated good consistency, and DCA revealed a higher net benefit for the combined model. In conclusion, the combined model that incorporated 18F-FDG PET radiomics features, metabolic parameters, and clinical factors demonstrated superior prognostic predictive ability, providing a useful tool for personalized treatment decisions in elderly DLBCL patients.

Artificial intelligence for geoscience: Progress, challenges, and perspectives.

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

[Hydrochemical Characteristics and Variation in Karst Groundwater in the Baiquan Spring Area of Xingtai Over the Last 30 Years].

To elucidate the variation patterns in the hydrochemical characteristics of karst groundwater in the Baiquan Spring area of Xingtai over the past 30 years, an integrated approach utilizing mathematical statistics, Piper trilinear diagrams, Gibbs diagrams, and ion ratio analyses was employed. Comparative analysis was conducted on 62 sets of karst water samples collected during the dry seasons of 1991 and 2020. The findings indicated that the groundwater in the spring area was generally weakly alkaline with a low salinization degree, predominantly characterized by Ca2+ and HCO3- as the dominant ions. Compared to that in 1991, the alkalinity of groundwater in 2020 had intensified, with a general increase in the concentration of various indicators. The hydrochemical types had shifted from the relatively concentrated HCO3-Ca and HCO3-Ca·Mg types to a broader spectrum of types, gradually exhibiting a salinization trend. The distribution characteristics of exceeding components such as TDS, Na++K+, SO42-, and F- showed significant spatial differences. Rock weathering played a pivotal role in the changes observed in the hydrochemical components of groundwater, with enhanced cation exchange and evaporation processes further influencing the hydrochemical characteristics and their spatial distribution.

Why is vestibular migraine associated with many comorbidities?

Vestibular migraine (VM) is a usual trigger of episodic vertigo. Patients with VM often experience spinning, shaking, or unsteady sensations, which are usually also accompanied by photophobia, phonophobia, motor intolerance, and more. VM is often associated with a number of comorbidities. Recurrent episodes of VM can affect the patient's emotions, sleep, and cognitive functioning to varying degrees. Patients with VM may be accompanied by adverse moods such as anxiety, fear, and depression, which can gradually develop into anxiety disorders or depressive disorders. Sleep disorders are also a common concomitant symptom of VM, which significantly lower patients' quality of life. The influence of anxiety disorders and sleep disorders may reduce cognitive functions of VM, such as visuospatial ability, attention, and memory decline. Clinically, it is also common to see VM comorbid with other vestibular disorders, making the diagnosis more difficult. VM episodes are relieved but lingering, in which case VM may coexist with persistent postural-perceptual dizziness (PPPD). Anxiety may be an important bridge between recurrent VM and PPPD. The clinical manifestations of VM and Meniere's disease (MD) overlap considerably, and those who meet the diagnostic criteria for both can be said to have VM/MD comorbidity. VM can also present with positional vertigo, and some patients with VM present with typical benign paroxysmal positional vertigo (BPPV) nystagmus on positional testing. In this paper, we synthesize and analyze the pathomechanisms of VM comorbidity by reviewing the literature. The results show that it may be related to the extensive connectivity of the vestibular system with different brain regions and the close connection of the trigeminovascular system with the periphery of the vestibule. Therefore, it is necessary to pay attention to the diagnosis of comorbidities in VM, synthesize its pathogenesis, and give comprehensive treatment to patients.

Integrative clinical and preclinical studies identify FerroTerminator1 as a potent therapeutic drug for MASH.

The complex etiological factors associated with metabolic dysfunction-associated fatty liver disease (MAFLD), including perturbed iron homeostasis, and the unclear nature by which they contribute to disease progression have resulted in a limited number of effective therapeutic interventions. Here, we report that patients with metabolic dysfunction-associated steatohepatitis (MASH), a pathological subtype of MAFLD, exhibit excess hepatic iron and that it has a strong positive correlation with disease progression. FerroTerminator1 (FOT1) effectively reverses liver injury across multiple MASH models without notable toxic side effects compared with clinically approved iron chelators. Mechanistically, our multi-omics analyses reveal that FOT1 concurrently inhibits hepatic iron accumulation and c-Myc-Acsl4-triggered ferroptosis in various MASH models. Furthermore, MAFLD cohort studies suggest that serum ferritin levels might serve as a predictive biomarker for FOT1-based therapy in MASH. These findings provide compelling evidence to support FOT1 as a promising novel therapeutic option for all stages of MAFLD and for future clinical trials.

Global burden of metabolic diseases, 1990-2021.

BACKGROUND: Common metabolic diseases, such as type 2 diabetes mellitus (T2DM), hypertension, obesity, hypercholesterolemia, and metabolic dysfunction-associated steatotic liver disease (MASLD), have become a global health burden in the last three decades. The Global Burden of Disease, Injuries, and Risk Factors Study (GBD) data enables the first insights into the trends and burdens of these metabolic diseases from 1990 to 2021, highlighting regional, temporal and differences by sex. METHODS: Global estimates of disability-adjusted life years (DALYs) and deaths from GBD 2021 were analyzed for common metabolic diseases (T2DM, hypertension, obesity, hypercholesterolemia, and MASLD). Age-standardized DALYs (mortality) per 100,000 population and annual percentage change (APC) between 1990 and 2021 were estimated for trend analyses. Estimates are reported with uncertainty intervals (UI). RESULTS: In 2021, among five common metabolic diseases, hypertension had the greatest burden (226 million [95 % UI: 190-259] DALYs), whilst T2DM (75 million [95 % UI: 63-90] DALYs) conferred much greater disability than MASLD (3.67 million [95 % UI: 2.90-4.61]). The highest absolute burden continues to be found in the most populous countries of the world, particularly India, China, and the United States, whilst the highest relative burden was mostly concentrated in Oceania Island states. The burden of these metabolic diseases has continued to increase over the past three decades but has varied in the rate of increase (1.6-fold to 3-fold increase). The burden of T2DM (0.42 % [95 % UI: 0.34-0.51]) and obesity (0.26 % [95 % UI: 0.17-0.34]) has increased at an accelerated rate, while the rate of increase for the burden of hypertension (-0.30 % [95 % UI: -0.34 to -0.25]) and hypercholesterolemia (-0.33 % [95 % UI: -0.37 to -0.30]) is slowing. There is no significant change in MASLD over time (0.05 % [95 % UI: -0.06 to 0.17]). CONCLUSION: In the 21st century, common metabolic diseases are presenting a significant global health challenge. There is a concerning surge in DALYs and mortality associated with these conditions, underscoring the necessity for a coordinated global health initiative to stem the tide of these debilitating diseases and improve population health outcomes worldwide.

The Protective Effect of Quercetin against the Cytotoxicity Induced by Fumonisin B1 in Sertoli Cells.

Fumonisin B1 (FB1), a mycotoxin produced by Fusarium species, is prevalent in crops and animal feed, posing significant health risks to livestock and humans. FB1 induces oxidative stress in Sertoli cells, destroys testicular structure, and affects spermatogenesis. However, methods to mitigate the reproductive toxicity of FB1 in testes remain unknown. Quercetin, a natural flavonoid antioxidant, may offer protective benefits. This study investigated the protective effects and mechanisms of quercetin against FB1-induced reproductive toxicity in TM4 cells (a Sertoli cell line). The results indicated that 40 µM quercetin improved cell viability, reduced apoptosis, and preserved cell functions. Quercetin also decreased reactive oxygen species (ROS) levels in TM4 cells exposed to FB1, enhanced the expression of antioxidant genes, and improved mitochondrial membrane potential. Compared with FB1 alone, the combination of quercetin and FB1 increased ATP levels, as well as pyruvate and lactic acid, the key glycolysis products. Furthermore, this combination elevated the mRNA and protein expression of glycolysis-related genes, including glucose-6-phosphate isomerase 1 (Gpi1), hexokinase 2 (Hk2), aldolase (Aldoa), pyruvate kinase, muscle (Pkm), lactate dehydrogenase A (Ldha) and phosphofructokinase, liver, B-type (Pfkl). Quercetin also boosted the activity of PKM and LDHA, two crucial glycolytic enzymes. In summary, quercetin mitigates FB1-induced toxicity in TM4 cells by reducing ROS levels and enhancing glycolysis. This study offers new insights into preventing and treating FB1-induced toxic damage to the male reproductive system and highlights the potential application of quercetin.

Umpolung Strategy for the One-Pot Synthesis of Highly Steric Bispirooxindoles via the l-Amino Acid Ester-Promoted In Situ Reduction/Nucleophilic Addition/Cyclization Cascade Reaction.

On the basis of a novel umpolung strategy, an efficient l-amino acid ester-mediated in situ reduction of 2-(2-oxoindolin-3-ylidene)malononitrile and sequential nucleophilic addition/cyclization cascade reaction is reported. Various densely substituted cyclopentene bispirooxindoles and dihydrofuran bispirooxindoles with two quaternary spirocenters were constructed in high yields (≤93%) with excellent diastereoselectivities (>20:1 dr). The method has advantages of readily available starting materials, mild reaction conditions, a one-pot process, a metal-free biomimetic reducing agent, a wide substrate scope, and operational simplicity (single filtration without column chromatography).

Bibliometric Analysis of Forensic Human Remains Identification Literature from 1991 to 2022.

OBJECTIVES: To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification research. METHODS: The data retrieved and extracted from the Web of Science Core Collection (WoSCC), the core database of the Web of Science information service platform (hereinafter referred to as "WoS"), was used to analyze the trends and topic changes in research on forensic identification of human remains from 1991 to 2022. Network visualisation of publication trends, countries (regions), institutions, authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10. RESULTS: A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained. The journal with the largest number of publications was Forensic Science International (164 articles). The country (region) with the largest number of published papers was China (90 articles). Katholieke Univ Leuven (Netherlands, 21 articles) was the institution with the largest number of publications. Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation, and the most commonly studied remains were teeth. CONCLUSIONS: The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing. However, the scope of both international and domestic collaborations remains limited. Traditionally, human remains identification has primarily relied on key areas such as the pelvis, skull, and teeth. Looking ahead, future research will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.

Pepper SBP-box transcription factor, CaSBP13, plays a negatively role in drought response.

The SBP-box gene significantly influences plant growth, development, and stress responses, yet its function in pepper plants during drought stress remains unexplored. Using virus-induced gene silencing and overexpression strategies, we examined the role of CaSBP13 during drought stress in plants. The results revealed that the expression of CaSBP13 can be induced by drought stress. Silencing of CaSBP13 in pepper notably boosted drought resistance, as evident by decreased active oxygen levels. Furthermore, the water loss rate, relative electrical conductivity, malondialdehyde content, and stomatal density were reduced in CaSBP13-silenced plants compared to controls. In contrast, CaSBP13 overexpression in Nicotiana benthamiana decreased drought tolerance with elevated reactive oxygen levels and stomatal density. Additionally, ABA signaling pathway genes (CaPP2C, CaAREB) exhibited reduced expression levels in CaSBP13-silenced plants post drought stress, as compared to control plants. On the contrary, CaPYL9 and CaSNRK2.4 showed heightened expression in CaSBP13-sienced plants under the same conditions. However, a converse trend for NbAREB, NbSNRK2.4, and NbPYL9 was observed post-four day drought in CaSBP13-overexpression plants. These findings suggest that CaSBP13 negatively regulates drought tolerance in pepper, potentially via ROS and ABA signaling pathways.

Adults Ischium Age Estimation Based on Deep Learning and 3D CT Reconstruction.

OBJECTIVES: To develop a deep learning model for automated age estimation based on 3D CT reconstructed images of Han population in western China, and evaluate its feasibility and reliability. METHODS: The retrospective pelvic CT imaging data of 1 200 samples (600 males and 600 females) aged 20.0 to 80.0 years in western China were collected and reconstructed into 3D virtual bone models. The images of the ischial tuberosity feature region were extracted to create sex-specific and left/right site-specific sample libraries. Using the ResNet34 model, 500 samples of different sexes were randomly selected as training and verification set, the remaining samples were used as testing set. Initialization and transfer learning were used to train images that distinguish sex and left/right site. Mean absolute error (MAE) and root mean square error (RMSE) were used as primary indicators to evaluate the model. RESULTS: Prediction results varied between sexes, with bilateral models outperformed left/right unilateral ones, and transfer learning models showed superior performance over initial models. In the prediction results of bilateral transfer learning models, the male MAE was 7.74 years and RMSE was 9.73 years, the female MAE was 6.27 years and RMSE was 7.82 years, and the mixed sexes MAE was 6.64 years and RMSE was 8.43 years. CONCLUSIONS: The skeletal age estimation model, utilizing ischial tuberosity images of Han population in western China and employing the ResNet34 combined with transfer learning, can effectively estimate adult ischium age.

A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.

BACKGROUND: With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11. METHODS: Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members. RESULTS: A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p = 0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%). CONCLUSIONS: This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.

Simultaneous integrated boost intensity-modulated radiotherapy post breast-conserving surgery: clinical efficacy, adverse effects, and cosmetic outcomes in breast cancer patients.

BACKGROUND: Simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) is an innovative technique delivering a higher dose to the tumor bed while irradiating the entire breast. This study aims to assess the clinical outcomes, adverse effects, and cosmetic results of SIB-IMRT following breast-conserving surgery in breast cancer patients. METHODS: We conducted a retrospective analysis of 308 patients with stage 0-III breast cancer who underwent breast-conserving surgery and SIB-IMRT from January 2016 to December 2020. The prescribed doses included 1.85 Gy/27 fractions to the whole breast and 2.22 Gy/27 fractions or 2.20 Gy/27 fractions to the tumor bed. Primary endpoints included overall survival (OS), local-regional control (LRC), distant metastasis-free survival (DMFS), acute and late toxicities, and cosmetic outcomes. RESULTS: The median follow-up time was 36 months. The 3-year OS, LRC, and DMFS rates were 100%, 99.6%, and 99.2%, respectively. Five patients (1.8%) experienced local recurrence or distant metastasis, and one patient succumbed to distant metastasis. The most common acute toxicity was grade 1-2 skin reactions (91.6%). The most common late toxicity was grade 0-1 skin and subcutaneous tissue reactions (96.7%). Five patients (1.8%) developed grade 1-2 upper limb lymphedema, and three patients (1.1%) had grade 1 radiation pneumonitis. Among the 262 patients evaluated for cosmetic outcomes at least 2 years post-radiotherapy, 96.9% achieved excellent or good results, while 3.1% had fair or poor outcomes. CONCLUSIONS: SIB-IMRT after breast-conserving surgery in breast cancer patients demonstrated excellent clinical efficacy, mild acute and late toxicities, and satisfactory cosmetic outcomes in our study. SIB-IMRT appears to be a feasible and effective option for breast cancer patients suitable for breast-conserving surgery.

Application and characterization of digital Sallen-Key filter in nuclear spectrum smoothing.

In the nuclear spectrum analysis processing, spectrum smoothing can remove the statistical fluctuation in the spectrum, which is beneficial for peak detection and peak area calculation. In this work, a spectrum smoothing algorithm is proposed based on digital Sallen-Key filter, which contains four parameters (m, n, k, D). The amplitude-frequency response curve of Sallen-Key filter is deduced and the filtering performance is analyzed. Meanwhile, the effects of the four parameters on the shape of the smoothed spectrum are explored: D affects the counts and peak areas of the spectrum, and the peak area can be corrected by the peak area correction function S'. The parameters of m, n and k affect the peak position after smoothing, making the peak position shift to the right, and the peak position correction function P' can be used to correct the peak position, when n¿2, the spectrum data appear negative after smoothing, when k¿2, the smoothed spectrum broadening degree is greater than 20%. Smoothness (R), noise smoothing factor (NSF), spectrum count ratio before and after smoothing (PER), and comprehensive evaluation factor (Q) are used to evaluate the smoothing effect of the algorithm. The parameters of the algorithm are optimally selected: about the gamma spectrum of 137Cs and 60Co, the optimal parameters are m=1.5 n=2 k=2 D=1, about the characteristic X-ray spectrum of Fe and quasi-geological sample (TiMnFeNiCuZn), the optimal parameters are m=1.1 n=1.1 k=1.3 D=1. Based on Sallen-Key smoothing method, Fourier transform method, Gaussian function method, wavelet transformation method, center of gravity method and least squares method, the gamma spectrum of 137Cs is smoothed and denoised in this paper. The results show that the Sallen-Key method has better spectrum denoising effect (R=0.6056) and comprehensive performance indicators (Q=0.6104), which can be further applied for the smoothing of nuclear spectrum data.

Room-temperature sub-100 nm Néel-type skyrmions in non-stoichiometric van der Waals ferromagnet Fe3-xGaTe2 with ultrafast laser writability.

Realizing room-temperature magnetic skyrmions in two-dimensional van der Waals ferromagnets offers unparalleled prospects for future spintronic applications. However, due to the intrinsic spin fluctuations that suppress atomic long-range magnetic order and the inherent inversion crystal symmetry that excludes the presence of the Dzyaloshinskii-Moriya interaction, achieving room-temperature skyrmions in 2D magnets remains a formidable challenge. In this study, we target room-temperature 2D magnet Fe3GaTe2 and unveil that the introduction of iron-deficient into this compound enables spatial inversion symmetry breaking, thus inducing a significant Dzyaloshinskii-Moriya interaction that brings about room-temperature Néel-type skyrmions with unprecedentedly small size. To further enhance the practical applications of this finding, we employ a homemade in-situ optical Lorentz transmission electron microscopy to demonstrate ultrafast writing of skyrmions in Fe3-xGaTe2 using a single femtosecond laser pulse. Our results manifest the Fe3-xGaTe2 as a promising building block for realizing skyrmion-based magneto-optical functionalities.

CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma.

BACKGROUND & AIMS: The present study utilized extracted computed tomography radiomics features to classify the gross tumor volume and normal liver tissue in hepatocellular carcinoma by mainstream machine learning methods, aiming to establish an automatic classification model. METHODS: We recruited 104 pathologically confirmed hepatocellular carcinoma patients for this study. GTV and normal liver tissue samples were manually segmented into regions of interest and randomly divided into five-fold cross-validation groups. Dimensionality reduction using LASSO regression. Radiomics models were constructed via logistic regression, support vector machine (SVM), random forest, Xgboost, and Adaboost algorithms. The diagnostic efficacy, discrimination, and calibration of algorithms were verified using area under the receiver operating characteristic curve (AUC) analyses and calibration plot comparison. RESULTS: Seven screened radiomics features excelled at distinguishing the gross tumor area. The Xgboost machine learning algorithm had the best discrimination and comprehensive diagnostic performance with an AUC of 0.9975 [95% confidence interval (CI): 0.9973-0.9978] and mean MCC of 0.9369. SVM had the second best discrimination and diagnostic performance with an AUC of 0.9846 (95% CI: 0.9835- 0.9857), mean Matthews correlation coefficient (MCC)of 0.9105, and a better calibration. All other algorithms showed an excellent ability to distinguish between gross tumor area and normal liver tissue (mean AUC 0.9825, 0.9861,0.9727,0.9644 for Adaboost, random forest, logistic regression, naivem Bayes algorithm respectively). CONCLUSION: CT radiomics based on machine learning algorithms can accurately classify GTV and normal liver tissue, while the Xgboost and SVM algorithms served as the best complementary algorithms.