Severe Organ Impairment Was Common in Elderly Individuals with Dengue in Guangdong, China.

Guangdong, China, has experienced several dengue epidemics involving thousands of confirmed cases in recent decades, and elderly individuals suffered severe dengue (SD) most seriously. However, the clinical characteristics and risk factors for SD among elderly patients in Guangdong have not been investigated. Patients older than 65 years were recruited and divided into a dengue fever (DF) group and an SD group according to the 2009 Dengue Guidelines of the WHO. We analyzed the clinical manifestations of the elderly patients with dengue and then assessed the risk factors for SD. Of a total of 1,027 patients, 868 patients were diagnosed as having DF and 159 as having SD. Of the 159 elderly patients with SD, 129 (81%) had comorbidities, with hypertension being the most common. Severe organ impairment (SOI) (115, 54%) was the most common presentation in SD patients, followed by severe plasma leakage (52, 24.4%) and severe hemorrhage (46, 21.6%). The most common symptom of SOI was kidney injury, followed by heart injury and central nervous system injury. Furthermore, multivariate regression revealed that the presence of chronic obstructive pulmonary disease (COPD), a lower red blood cell (RBC) count (≤3.5 × 1012/L; odds ratio [OR], 0.35; 95% CI, 0.17-0.55; P <0.001), lower serum albumin (ALB) (≤35 U/L; OR, 0.18; 95% CI, 0.09-0.32; P <0.001), and hyperpyrexia (body temperature ≥39°C; OR, 1.8; 95% CI, 1.2-2.6, P <0.001) were risk factors for SD. Severe organ impairment was the predominant manifestation in elderly individuals with SD characterized by kidney injury. The potential risk factors of SD such as presence of COPD and hyperpyrexia and lower RBC and ALB levels might help clinicians identify patients with SD early.

The application of 3D printing in dentistry: A bibliometric analysis from 2012 to 2023.

STATEMENT OF PROBLEM: Three-dimensional (3D) printing has had extensive applications across dentistry, but a comprehensive bibliometric analysis relating to the application of 3D printing in dentistry is lacking. PURPOSE: The purpose of this study was to conduct a comprehensive bibliometric analysis of the scientific literature concerning the application of 3D printing in dentistry from 2012 to 2023. MATERIAL AND METHODS: The literature search was conducted in the Web of Science Core Collection Database. The retrieved literature data were downloaded as plain text file in "full record and cited references" format, with software programs (VOSviewer, CiteSpace, Biblioshiny, RStudio, Carrot2, and Microsoft Excel) used for bibliometric analysis and quantitative assessment. RESULTS: The bibliometric analysis incorporated 1911 publications. Revilla-León, Marta was the most productive author. Zurich University had the highest number of publications and citations. The United States dominated the research landscape with the highest publication volume and H-index. The Journal of Prosthetic Dentistry was the leading journal in both publication volume and citation frequency. Co-occurrence analysis of keyword and co-cited analysis of reference indicated a robust research environment, characterized by a strong focus on the pursuit of accuracy in dental restorative solutions, biocompatibility of materials, and clinical applications. CONCLUSIONS: Research on 3D printing in the field of dentistry continues to grow. Collaborations with leading organizations and countries have been established, with Revilla-León, Marta et al playing a pivotal role. Top journals represented included the Journal of Prosthetic Dentistry and Dental Materials. Main research domain resided in prosthodontics and implantology. Hot research topics included improvements in accuracy, dental materials, and clinical applications centered on implant guide design.

Prediction of personalised postprandial glycaemic response in type 1 diabetes mellitus.

Objectives: Patients with type 1 diabetes (T1D) face unique challenges in glycaemic control due to the complexity and uniqueness of the dietary structure in China, especially in terms of postprandial glycaemic response (PPGR). This study aimed to establish a personalized model for predicting PPGR in patients with T1D. Materials and methods: Data provided by the First People's Hospital of Yunnan Province, 13 patients with T1D, were recruited and provided with an intervention for at least two weeks. All patients were asked to wear a continuous glucose monitoring (CGM) device under free-living conditions during the study period. To tackle the challenge of incomplete data from wearable devices for CGM measurements, the GAIN method was used in this paper to achieve a more rational interpolation process. In this study, patients' PPGRs were calculated, and a LightGBM prediction model was constructed based on a Bayesian hyperparameter optimisation algorithm and a random search algorithm, which integrated glucose measurement, insulin dose, dietary nutrient content, blood measurement and anthropometry as inputs. Results: The experimental outcomes revealed that the PPGR prediction model presented in this paper demonstrated superior accuracy (R=0.63) compared to both the carbohydrate content only model (R=0.14) and the baseline model emulating the standard of care for insulin administration (R=0.43). In addition, the interpretation of the model using the SHAP method showed that blood glucose levels at meals and blood glucose trends 30 minutes before meals were the most important features of the model. Conclusion: The proposed model offers a heightened precision in predicting PPGR in patients with T1D, so it can better guide the diet plan and insulin intake dose of patients with T1D.

Rare presentation of maxillary osteonecrosis and tooth exfoliation induced by herpes zoster infection in a 29-year-old Chinese male: a case report and literature review.

BACKGROUND: We present a case of a 29-year-old male patient without immunodeficiency who suffered from rapid osteonecrosis and tooth exfoliation resulting from herpes zoster (HZ) infection in the left maxillary branch of the trigeminal nerve. Various complications associated with shingles infections have been reported, cases of osteonecrosis and tooth exfoliation due to HZ infection among young people without immunodeficiency are rare. In this case, we focus on the particular manifestation of HZ infection. CASE PRESENTATION: The patient presented with clusters of erythema and papules, along with non-hemorrhagic blisters on the left face and the loss of the left upper incisor. All lesions were localized to the left side of the face without exceeding the midline. After receiving antibacterial and antiviral treatment, successful control over the infection was achieved; however, he experienced the loss of all upper teeth on the left side except for the first and second upper left molars. CONCLUSION: This case highlights that rapid osteonecrosis and tooth exfoliation may occur among young individuals without immunodeficiency after HZ infection. HZ infection of the face should be taken very seriously to obtain prompt treatment to prevent the rare complications of bone necrosis and tooth loss as much as possible.

Correction: Incorporating mesopelagic fish into the evaluation of marine protected areas under climate change scenarios.

[This corrects the article DOI: 10.1007/s42995-023-00188-9.].

BCSLinker: automatic method for constructing a knowledge graph of venous thromboembolism based on joint learning.

Background: Venous thromboembolism (VTE) is characterized by high morbidity, mortality, and complex treatment. A VTE knowledge graph (VTEKG) can effectively integrate VTE-related medical knowledge and offer an intuitive description and analysis of the relations between medical entities. However, current methods for constructing knowledge graphs typically suffer from error propagation and redundant information. Methods: In this study, we propose a deep learning-based joint extraction model, Biaffine Common-Sequence Self-Attention Linker (BCSLinker), for Chinese electronic medical records to address the issues mentioned above, which often occur when constructing a VTEKG. First, the Biaffine Common-Sequence Self-Attention (BCsSa) module is employed to create global matrices and extract entities and relations simultaneously, mitigating error propagation. Second, the multi-label cross-entropy loss is utilized to diminish the impact of redundant information and enhance information extraction. Results: We used the electronic medical record data of VTE patients from a tertiary hospital, achieving an F1 score of 86.9% on BCSLinker. It outperforms the other joint entity and relation extraction models discussed in this study. In addition, we developed a question-answering system based on the VTEKG as a structured data source. Conclusion: This study has constructed a more accurate and comprehensive VTEKG that can provide reference for diagnosing, evaluating, and treating VTE as well as supporting patient self-care, which is of considerable clinical value.

Risk factors and outcomes for refeeding syndrome in acute ischaemic stroke patients.

AIM: Patients with acute ischaemic stroke are more likely to develop refeeding syndrome due to increased need for nutritional support when suffering alterations of consciousness and impairment of swallowing. This study aimed to evaluate the incidence, risk factors and outcomes of refeeding syndrome in stroke patients. METHODS: This was a retrospective observational study, using the prospective stroke database from hospital, included all consecutive acute ischaemic stroke patients who received enteral nutrition for more than 72 h from 1 January 2020 and 31 December 2022. Refeeding syndrome was defined as occurrence of new-onset hypophosphataemia within 72 h after enteral feeding. Multiple logistic regression analysis was conducted to evaluate risk factors and relationships between refeeding syndrome and stroke outcomes. RESULTS: 338 patients were included in the study. 50 patients (14.8%) developed refeeding syndrome. Higher scores on National Institutes of Health Stroke Scale and Nutritional Risk Screening 2002, albumin <30 g/L and BMI <18.5 kg/m2 were risk factors for refeeding syndrome. Moreover, refeeding syndrome was independently associated with a 3-month modified Rankin Scale score of >2 and 6-month mortality. CONCLUSIONS: Refeeding syndrome was common in stroke patients and higher baseline National Institutes of Health Stroke Scale, higher Nutritional Risk Screening 2002, albumin <30 g/L and BMI <18.5 kg/m2 were independent risk factors of refeeding syndrome. Occurrence of refeeding syndrome was significantly associated with higher 3-month modified Rankin Scale and 6-month mortality.

Fusion with ARRDC1 or CD63: A Strategy to Enhance p53 Loading into Extracellular Vesicles for Tumor Suppression.

Small extracellular vesicles (sEVs) have emerged as promising therapeutic agents and drug delivery vehicles. Targeted modification of sEVs and their contents using genetic modification strategies is one of the most popular methods. This study investigated the effects of p53 fusion with arrestin domain-containing protein 1 (ARRDC1) and CD63 on the generation of sEVs, p53 loading efficiency, and therapeutic efficacy. Overexpression of either ARRDC1-p53 (ARP) or CD63-p53 (CDP) significantly elevated p53 mRNA and protein levels. The incorporation of ARRDC1 and CD63 significantly enhanced HEK293T-sEV biogenesis, evidenced by significant increases in sEV-associated proteins TSG101 and LAMP1, resulting in a boost in sEV production. Importantly, fusion with ARRDC1 or CD63 substantially increased the efficiency of loading both p53 fusion proteins and its mRNA into sEVs. sEVs equipped with ARP or CDP significantly enhanced the enrichment of p53 fusion proteins and mRNA in p53-null H1299 cells, resulting in a marked increase in apoptosis and a reduction in cell proliferation, with ARP-sEVs demonstrating greater effectiveness than CDP-sEVs. These findings underscore the enhanced functionality of ARRDC1- and CD63-modified sEVs, emphasizing the potential of genetic modifications in sEV-based therapies for targeted cancer treatment.

Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China.

BACKGROUND: After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive. METHODS: We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited. RESULTS: 90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection. CONCLUSIONS: The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.

N-acetylcysteine Protects Against Myocardial Ischemia-Reperfusion Injury Through Anti-ferroptosis in Type 1 Diabetic Mice.

The hearts of subjects with diabetes are vulnerable to ischemia-reperfusion injury (IRI). In contrast, experimentally rodent hearts have been shown to be more resistant to IRI at the very early stages of diabetes induction than the heart of the non-diabetic control mice, and the mechanism is largely unclear. Ferroptosis has recently been shown to play an important role in myocardial IRI including that in diabetes, while the specific mechanisms are still unclear. Non-diabetic control (NC) and streptozotocin-induced diabetic (DM) mice were treated with the antioxidant N-acetylcysteine (NAC) in drinking water for 4 week starting at 1 week after diabetes induction. Mice were subjected to myocardial IRI induced by occluding the coronary artery for 30 min followed by 2 h of reperfusion, subsequently at 1, 2, and 5 week of diabetes induction. The post-ischemic myocardial infarct size in the DM mice was smaller than that in NC mice at 1 week of diabetes but greater than that in the NC mice at 2 and 5 week of diabetes, which were associated with a significant increase of ferroptosis at 2 and 5 week but a significant reduction of ferroptosis at 1 week of diabetes. NAC significantly attenuated post-ischemic ferroptosis as well as oxidative stress and reduced infarct size at 2 and 5 week of diabetes. Application of erastin, a ferroptosis inducer, reversed the cardioprotective effects of NAC. It is concluded that increased oxidative stress and ferroptosis are the major factors attributable to the increased vulnerability to myocardial IRI in diabetes and that attenuation of ferroptosis represents a major mechanism whereby NAC confers cardioprotection against myocardial IRI in diabetes.

Incorporating mesopelagic fish into the evaluation of conservation areas for marine living resources under climate change scenarios.

Mesopelagic fish (meso-fish) are central species within the Southern Ocean (SO). However, their ecosystem role and adaptive capacity to climate change are rarely integrated into protected areas assessments. This is a pity given their importance as crucial prey and predators in food webs, coupled with the impacts of climate change. Here, we estimate the habitat distribution of nine meso-fish using an ensemble model approach (MAXENT, random forest, and boosted regression tree). Four climate model simulations were used to project their distribution under two representative concentration pathways (RCP4.5 and RCP8.5) for short-term (2006-2055) and long-term (2050-2099) periods. In addition, we assess the ecological representativeness of protected areas under climate change scenarios using meso-fish as indicator species. Our models show that all species shift poleward in the future. Lanternfishes (family Myctophidae) are predicted to migrate poleward more than other families (Paralepididae, Nototheniidae, Bathylagidae, and Gonostomatidae). In comparison, lanternfishes were projected to increase habitat area in the eastern SO but lose area in the western SO; the opposite was projected for species in other families. Important areas (IAs) of meso-fish are mainly distributed near the Antarctic Peninsula and East Antarctica. Negotiated protected area cover 23% of IAs at present and 38% of IAs in the future (RCP8.5, long-term future). Many IAs of meso-fish still need to be included in protected areas, such as the Prydz Bay and the seas around the Antarctic Peninsula. Our results provide a framework for evaluating protected areas incorporating climate change adaptation strategies for protected areas management. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00188-9.

Research on Ocular Artifacts Removal from Single-Channel Electroencephalogram Signals in Obstructive Sleep Apnea Patients Based on Support Vector Machine, Improved Variational Mode Decomposition, and Second-Order Blind Identification.

The electroencephalogram (EEG) has recently emerged as a pivotal tool in brain imaging analysis, playing a crucial role in accurately interpreting brain functions and states. To address the problem that the presence of ocular artifacts in the EEG signals of patients with obstructive sleep apnea syndrome (OSAS) severely affects the accuracy of sleep staging recognition, we propose a method that integrates a support vector machine (SVM) with genetic algorithm (GA)-optimized variational mode decomposition (VMD) and second-order blind identification (SOBI) for the removal of ocular artifacts from single-channel EEG signals. The SVM is utilized to identify artifact-contaminated segments within preprocessed single-channel EEG signals. Subsequently, these signals are decomposed into variational modal components across different frequency bands using the GA-optimized VMD algorithm. These components undergo further decomposition via the SOBI algorithm, followed by the computation of their approximate entropy. An approximate entropy threshold is set to identify and remove components laden with ocular artifacts. Finally, the signal is reconstructed using the inverse SOBI and VMD algorithms. To validate the efficacy of our proposed method, we conducted experiments utilizing both simulated data and real OSAS sleep EEG data. The experimental results demonstrate that our algorithm not only effectively mitigates the presence of ocular artifacts but also minimizes EEG signal distortion, thereby enhancing the precision of sleep staging recognition based on the EEG signals of OSAS patients.

Feasibility of implant placement in healed mandibular molar sites: A retrospective cone beam computed tomography study.

STATEMENT OF PROBLEM: Implant placement in the mandibular molar sites plays a crucial role in the restoration of edentulous mandibles. However, the evaluation of bone quantity before implant surgery using cone beam computed tomography (CBCT) is lacking. PURPOSE: The purpose of this clinical study was to evaluate CBCT images of edentulous patients to analyze the feasibility of implant placement in healed mandibular molar sites. MATERIAL AND METHODS: The CBCT data of 138 patients were analyzed in the sagittal plane for measurements of mandibular bone height (MBH), superior bone height (SBH), inferior bone height (IBH), buccal bone width (BBW), lingual bone width (LBW), and alveolar bone widths (ABWs). The edentulous sites were categorized according to the bone quantity and complexity of the implant surgery. Multivariate analysis of variance (MANOVA) was used to analyze the site, sex, and age-related variations. An independent t test was used to compare the difference of bone dimension in different sites and between sexes. One-way ANOVA followed by post hoc tests were used to analyze the difference between different age groups. Categorical variables were presented as number of events and percentages. The chi-squared test was used to compare categorical variables (α=.05). RESULTS: A total of 534 sites of interest were recorded, including 274 hemimandibles. A significant difference in BBW was found between the first and second molar sites. Men had higher MBH, SBH, IBH, and BBW than women. The distribution of implant surgical complexity in the conventional group was 63.5%, while the buccolingual tilted implant group accounted for 17.0%, and the complicated group accounted for 19.5%. Of the 274 hemimandibles, an implant could be placed directly at molar sites in 88% of situations. CONCLUSIONS: The BBW at the mandibular second molar site was greater than that at the first molar site. The amount of available bone in the SBH and BBW was greater in men than in women at the healed molar sites. Age did not significantly affect the complexity of the implant surgery. Implants can be placed directly in healed mandibular molar sites in most patients who require a complete arch mandibular implant-supported restoration.

SMMF: a self-attention-based multi-parametric MRI feature fusion framework for the diagnosis of bladder cancer grading.

Background: Multi-parametric magnetic resonance imaging (MP-MRI) may provide comprehensive information for graded diagnosis of bladder cancer (BCa). Nevertheless, existing methods ignore the complex correlation between these MRI sequences, failing to provide adequate information. Therefore, the main objective of this study is to enhance feature fusion and extract comprehensive features from MP-MRI using deep learning methods to achieve an accurate diagnosis of BCa grading. Methods: In this study, a self-attention-based MP-MRI feature fusion framework (SMMF) is proposed to enhance the performance of the model by extracting and fusing features of both T2-weighted imaging (T2WI) and dynamic contrast-enhanced imaging (DCE) sequences. A new multiscale attention (MA) model is designed to embed into the neural network (CNN) end to further extract rich features from T2WI and DCE. Finally, a self-attention feature fusion strategy (SAFF) was used to effectively capture and fuse the common and complementary features of patients' MP-MRIs. Results: In a clinically collected sample of 138 BCa patients, the SMMF network demonstrated superior performance compared to the existing deep learning-based bladder cancer grading model, with accuracy, F1 value, and AUC values of 0.9488, 0.9426, and 0.9459, respectively. Conclusion: Our proposed SMMF framework combined with MP-MRI information can accurately predict the pathological grading of BCa and can better assist physicians in diagnosing BCa.

Application of LightGBM hybrid model based on TPE algorithm optimization in sleep apnea detection.

Introduction: Sleep apnoea syndrome (SAS) is a serious sleep disorder and early detection of sleep apnoea not only reduces treatment costs but also saves lives. Conventional polysomnography (PSG) is widely regarded as the gold standard diagnostic tool for sleep apnoea. However, this method is expensive, time-consuming and inherently disruptive to sleep. Recent studies have pointed out that ECG analysis is a simple and effective diagnostic method for sleep apnea, which can effectively provide physicians with an aid to diagnosis and reduce patients' suffering. Methods: To this end, in this paper proposes a LightGBM hybrid model based on ECG signals for efficient detection of sleep apnea. Firstly, the improved Isolated Forest algorithm is introduced to remove abnormal data and solve the data sample imbalance problem. Secondly, the parameters of LightGBM algorithm are optimised by the improved TPE (Tree-structured Parzen Estimator) algorithm to determine the best parameter configuration of the model. Finally, the fusion model TPE_OptGBM is used to detect sleep apnoea. In the experimental phase, we validated the model based on the sleep apnoea ECG database provided by Phillips-University of Marburg, Germany. Results: The experimental results show that the model proposed in this paper achieves an accuracy of 95.08%, a precision of 94.80%, a recall of 97.51%, and an F1 value of 96.14%. Discussion: All of these evaluation indicators are better than the current mainstream models, which is expected to assist the doctor's diagnostic process and provide a better medical experience for patients.

Resolving the In Situ Three-Dimensional Structure of Fly Mechanosensory Organelles Using Serial Section Electron Tomography.

Mechanosensory organelles (MOs) are specialized subcellular entities where force-sensitive channels and supporting structures (e.g., microtubule cytoskeleton) are organized in an orderly manner. The delicate structure of MOs needs to be resolved to understand the mechanisms by which they detect forces and how they are formed. Here, we describe a protocol that allows obtaining detailed information about the nanoscopic ultrastructure of fly MOs by using serial section electron tomography (SS-ET). To preserve fine structural details, the tissues are cryo-immobilized using a high-pressure freezer followed by freeze-substitution at low temperature and embedding in resin at room temperature. Then, sample sections are prepared and used to acquire the dual-axis tilt series images, which are further processed for tomographic reconstruction. Finally, tomograms of consecutive sections are combined into a single larger volume using microtubules as fiducial markers. Using this protocol, we managed to reconstruct the sensory organelles, which provide novel molecular insights as to how fly mechanosensory organelles work and are formed. Based on our experience, we think that, with minimal modifications, this protocol can be adapted to a wide range of applications using different cell and tissue samples. Key features • Resolving the high-resolution 3D ultrastructure of subcellular organelles using serial section electron tomography (SS-ET). • Compared with single-axis tilt series, dual-axis tilt series provides a much wider coverage of Fourier space, improving resolution and features in the reconstructed tomograms. • The use of high-pressure freezing and freeze-substitution maximally preserves the fine structural details.

Effect of brominated flame retardants exposure on liver function and the risk of non-alcoholic fatty liver disease in the US population.

BACKGROUND: The relationship between brominated flame retardants (BFRs) exposure and the human liver was still not well understood. METHODS: A total of 3108 participants (age > 12) from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2005 to 2016 were included as the study population, with nine BFRs exhibiting a detection rate of over 70% serving as the exposure factor. The singular effects and combined effects of BFRs exposure on liver injury, non-alcoholic fatty liver disease (NAFLD), and advanced hepatic fibrosis (AHF) were evaluated separately. Finally, COX regression was employed to explore the hazard ratios associated with individual BFRs. RESULTS: In our analysis of individual exposures, we found significant positive association of PBB153 with alanine aminotransferase (ALT), PBB153 with aspartate aminotransferase (AST), PBDE47, PBDE85, PBDE99, PBDE100, and PBDE154 with alkaline phosphatase (ALP), PBDE28 and PBB153 with gamma-glutamyl transaminase (GGT), PBB153 with the risk of NAFLD and AHF; and significant negative association of PBB153 with ALP, PBDE28, PBDE47, PBDE99, PBDE100, PBDE85, PBDE209, and PBDE154 with albumin (ALB), PBB153 with AST/ALT. The nonlinear analysis results from Restricted Cubic Spline (RCS) further validated these associations (all P<0.05). In the mixed analysis combining Weighted Quantile Sum (WQS) regression and Quantile G-computation (QGC) analysis, BFRs were positively associated with ALT (ß>0, P<0.001), GGT (ß>0, P<0.001), and the risk of NAFLD (OR>1, P=0.007). Conversely, BFRs exhibited significant negative correlations with ALP (ß<0, P<0.001), ALB (ß<0, P<0.001), and AST/ALT (ß<0, P<0.001). Furthermore, the COX regression analysis revealed that PBB153 had the highest hazard ratio among the BFRs. CONCLUSIONS: BFR exposure may increase the risk of liver injury and NAFLD, with no significant association with AHF risk. The impact of BFR exposure on liver health should not be overlooked, especially in individuals residing in impoverished areas.

Kinetic 18F-FDG PET/CT imaging of hepatocellular carcinoma: a dual input four-compartment model.

BACKGROUND: The endoplasmic reticulum plays an important role in glucose metabolism and has not been explored in the kinetic estimation of hepatocellular carcinoma (HCC) via 18F-fluoro-2-deoxy-D-glucose PET/CT. METHODS: A dual-input four-compartment (4C) model, regarding endoplasmic reticulum was preliminarily used for kinetic estimation to differentiate 28 tumours from background liver tissue from 24 patients with HCC. Moreover, parameter images of the 4C model were generated from one patient with negative findings on conventional metabolic PET/CT. RESULTS: Compared to the dual-input three-compartment (3C) model, the 4C model has better fitting quality, a close transport rate constant (K1) and a dephosphorylation rate constant (k6/k4), and a different removal rate constant (k2) and phosphorylation rate constant (k3) in HCC and background liver tissue. The K1, k2, k3, and hepatic arterial perfusion index (HPI) from the 4C model and k3, HPI, and volume fraction of blood (Vb) from the 3C model were significantly different between HCC and background liver tissues (all P < 0.05). Meanwhile, the 4C model yielded additional kinetic parameters for differentiating HCC. The diagnostic performance of the top ten genes from the most to least common was HPI(4C), Vb(3C), HPI(3C), SUVmax, k5(4C), k3(3C), k2(4C), v(4C), K1(4C) and Vb(4C). Moreover, a patient who showed negative findings on conventional metabolic PET/CT had positive parameter images in the 4C model. CONCLUSIONS: The 4C model with the endoplasmic reticulum performed better than the 3C model and produced additional useful parameters in kinetic estimation for differentiating HCC from background liver tissue.

Magnetic resonance-guided focused ultrasound for essential tremor: a prospective, single center, single-arm study.

JOURNAL/nrgr/04.03/01300535-202409000-00041/figure1/v/2024-01-16T170235Z/r/image-tiff The safety and effectiveness of magnetic resonance-guided focused ultrasound thalamotomy has been broadly established and validated for the treatment of essential tremor. In 2018, the first magnetic resonance-guided focused ultrasound system in Chinese mainland was installed at the First Medical Center of the PLA General Hospital. This prospective, single center, open-label, single-arm study was part of a worldwide prospective multicenter clinical trial (ClinicalTrials.gov Identifier: NCT03253991) conducted to confirm the safety and efficacy of magnetic resonance-guided focused ultrasound for treating essential tremor in the local population. From 2019 to 2020, 10 patients with medication refractory essential tremor were recruited into this open-label, single arm study. The treatment efficacy was determined using the Clinical Rating Scale for Tremor. Safety was evaluated according to the incidence and severity of adverse events. All of the subjects underwent a unilateral thalamotomy targeting the ventral intermediate nucleus. At the baseline assessment, the estimated marginal mean of the Clinical Rating Scale for Tremor total score was 58.3 ± 3.6, and this improved after treatment to 23.1 ± 6.4 at a 12-month follow-up assessment. A total of 50 adverse events were recorded, and 2 were defined as serious. The most common intraoperative adverse events were nausea and headache. The most frequent postoperative adverse events were paresthesia and equilibrium disorder. Most of the adverse events were mild and usually disappeared within a few days. Our findings suggest that magnetic resonance-guided focused ultrasound for the treatment of essential tremor is effective, with a good safety profile, for patients in Chinese mainland.

EI-MVSNet: Epipolar-Guided Multi-View Stereo Network With Interval-Aware Label.

Recent learning-based methods demonstrate their strong ability to estimate depth for multi-view stereo reconstruction. However, most of these methods directly extract features via regular or deformable convolutions, and few works consider the alignment of the receptive fields between views while constructing the cost volume. Through analyzing the constraint and inference of previous MVS networks, we find that there are still some shortcomings that hinder the performance. To deal with the above issues, we propose an Epipolar-Guided Multi-View Stereo Network with Interval-Aware Label (EI-MVSNet), which includes an epipolar-guided volume construction module and an interval-aware depth estimation module in a unified architecture for MVS. The proposed EI-MVSNet enjoys several merits. First, in the epipolar-guided volume construction module, we construct cost volume with features from aligned receptive fields between different pairs of reference and source images via epipolar-guided convolutions, which take rotation and scale changes into account. Second, in the interval-aware depth estimation module, we attempt to supervise the cost volume directly and make depth estimation independent of extraneous values by perceiving the upper and lower boundaries, which can achieve fine-grained predictions and enhance the reasoning ability of the network. Extensive experimental results on two standard benchmarks demonstrate that our EI-MVSNet performs favorably against state-of-the-art MVS methods. Specifically, our EI-MVSNet ranks 1st on both intermediate and advanced subsets of the Tanks and Temples benchmark, which verifies the high precision and strong robustness of our model.