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.

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.

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.

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).

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.

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.

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.

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.

A Population-Based and Clinical Cohort Validation of the Novel Consensus Definition of Metabolic Hyperferritinemia.

CONTEXT: There is limited data on the clinical significance of metabolic hyperferritinemia (MHF) based on the most recent consensus. OBJECTIVE: We aimed to validate the clinical outcomes of MHF in the general population and patients with biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD). METHODS: The NHANES database and PERSONS cohort were included. MHF was defined as elevated serum ferritin with metabolic dysfunction (MD) and stratified into different grades according to ferritin (grade 1: 200 [females]/300 [males]-550 ng/mL; grade 2: 550-1000 ng/mL; grade 3: >1000 ng/mL). The clinical outcomes, including all-cause death, comorbidities, and liver histology, were compared between non-MHF and MHF in adjusted models. RESULTS: In NHANES, compared with non-MHF with MD, MHF was related to higher risks of advanced fibrosis (P = .036), elevated albumin-creatinine ratio (UACR, P = .001), and sarcopenia (P = .013). Although the association between all grades of MHF and mortality was insignificant (P = .122), grades 2/3 was associated with increased mortality (P = .029). When comparing with non-MHF without MD, the harmful effects of MHF were more significant in mortality (P < .001), elevated UACR (P < .001), cardiovascular disease (P = .028), and sarcopenia (P < .001). In the PERSONS cohort, MHF was associated with more advanced grades of steatosis (P < .001), lobular inflammation (P < .001), advanced fibrosis (P = .017), and more severe hepatocellular iron deposition (P < .001). CONCLUSION: Both in the general population and in at-risk individuals with MAFLD, MHF was related with poorer clinical outcomes.