Stepwise analysis of thyroid diagnostic modalities with genomic imprinting detection.

BACKGROUND: The current preoperative malignancy risk evaluation for thyroid nodules involves stepwise diagnostic modalities including ultrasonography, thyroid function serology and fine-needle aspiration (FNA) cytopathology, respectively. We aimed to substantiate the stepwise contributions of each diagnostic step and additionally investigate the diagnostic significance of quantitative chromogenic imprinted gene in-situ hybridization (QCIGISH)-an adjunctive molecular test based on epigenetic imprinting alterations. METHODS: A total of 114 cytopathologically-diagnosed and histopathologically-confirmed thyroid nodules with complete ultrasonographic and serological examination records were evaluated using QCIGISH in the study. Logistic regression models for thyroid malignancy prediction were developed with the stepwise addition of each diagnostic modality and the contribution of each step evaluated in terms of discrimination performance and goodness-of-fit. RESULTS: From the baseline model using ultrasonography [area under the receiver operating characteristics curve (AUROC): 0.79; 95% confidence interval (CI): 0.71-0.86], significant improvements in thyroid malignancy discrimination were observed with the stepwise addition of thyroid function serology (AUROC: 0.82; 95% CI: 0.74-0.90; P=0.23) and FNA cytopathology (AUROC: 0.88; 95% CI: 0.81-0.94; P=0.02), respectively. The inclusion of QCIGISH as an adjunctive molecular test further advanced the preceding model's diagnostic performance (AUROC: 0.95; 95% CI: 0.91-1.00, P=0.007). CONCLUSIONS: Our study demonstrated the significant stepwise diagnostic contributions of standard clinical assessments in the malignancy risk stratification of thyroid nodules. However, the addition of molecular imprinting detection further enabled a more accurate and definitive preoperative evaluation especially for morphologically indeterminate thyroid nodules and cases with potentially discordant results among standard modalities.

Cuticle properties, wax composition, and crystal morphology of Hami melon cultivars (Cucumis melo L.) with differential resistance to fruit softening.

Cuticle wax chemicals are cultivar-dependent and contribute to storage quality. Few research reported on wax analysis between melting flesh-type (MF; 'Jinhuami 25') and nonmelting flesh-type (NMF; 'Xizhoumi 17' and 'Chougua') Hami melons. Chemicals and crystal structures of Hami melon cuticular wax, cell wall metabolism related to fruit melting, and fruit physiology were analyzed to observe wax functions. Results showed that Hami melon cuticle wax predominantly consists of esters, alkanes, alcohols, aldehydes, and terpenoids. MF-type has a lower alkane/terpenoid ratio, concomitant to its higher weight loss and cuticle permeability. Micromorphology of wax crystals appears as numerous platelets with irregular crystals, and the transformation of wax structure in NMF Hami melon is delayed. Waxy components affect cell wall metabolism and physiological quality, which results in the pulp texture difference between MF-type and NMF-type during storage. Results provide a reference for the regulation of wax synthesis in both types of melons.

Association Between Quality of Life Defined by EuroQol Group 5 Dimension and Composite Inferior Outcome Among Inpatients with Cirrhosis.

Purpose: The utility of the EuroQol Group 5 Dimension (EQ-5D) measuring health-related quality of life (HRQoL) has been verified; however, knowledge gaps remain concerning predictive performance in cirrhosis. We aimed to identify the optimal threshold for risk stratification and the pronounced domain in the EQ-5D linked to inferior outcomes. Patients and Methods: The X-tile project was used to obtain a threshold, considering the composite outcome of 1-year all-cause mortality or readmission. A restricted cubic spline (RCS) was performed to test the non-linear relationship between the EQ-5D utility value and the primary outcome. Six multivariate Cox regression models incorporating EQ-5D utility value and each of the five domains were constructed. Setting/Participants: Totally, 420 patients with cirrhosis were recruited. Results: The median utility value of the study population was 0.77 and 59.8% reported impairment in minimal one EQ-5D domain. RCS indicated a linear relationship between the utility value and composite inferior outcome. X-tile pinpointed a utility value of 0.59 stratifying populations into high- and low-risk groups based on the outcome. Inpatients with cirrhosis and deteriorated HRQoL (utility value ≤0.59) were at higher risk of death or readmission (adjusted HR: 2.18, P < 0.001). Furthermore, mobility and usual activities were the most pronounced domains associated with composite inferior outcome. Conclusion: A utility value ≤0.59 can identify cirrhotic inpatients exhibiting compromised HRQoL and mortality/readmission risk. It is tempting to reverse the decreased HRQoL by applying longitudinal measurements and keeping surveillance on utility value, while interventions appear to mainly focus on improving mobility and usual activities.

COVID-19 Infection Percentage Estimation from Computed Tomography Scans: Results and Insights from the International Per-COVID-19 Challenge.

COVID-19 analysis from medical imaging is an important task that has been intensively studied in the last years due to the spread of the COVID-19 pandemic. In fact, medical imaging has often been used as a complementary or main tool to recognize the infected persons. On the other hand, medical imaging has the ability to provide more details about COVID-19 infection, including its severity and spread, which makes it possible to evaluate the infection and follow-up the patient's state. CT scans are the most informative tool for COVID-19 infection, where the evaluation of COVID-19 infection is usually performed through infection segmentation. However, segmentation is a tedious task that requires much effort and time from expert radiologists. To deal with this limitation, an efficient framework for estimating COVID-19 infection as a regression task is proposed. The goal of the Per-COVID-19 challenge is to test the efficiency of modern deep learning methods on COVID-19 infection percentage estimation (CIPE) from CT scans. Participants had to develop an efficient deep learning approach that can learn from noisy data. In addition, participants had to cope with many challenges, including those related to COVID-19 infection complexity and crossdataset scenarios. This paper provides an overview of the COVID-19 infection percentage estimation challenge (Per-COVID-19) held at MIA-COVID-2022. Details of the competition data, challenges, and evaluation metrics are presented. The best performing approaches and their results are described and discussed.

Health-related quality of life and frailty in liver cirrhosis.

BACKGROUND AND OBJECTIVES: There is limited evidence concerning the predictive value of health-related quality of life (HRQoL) on the presence of frailty in the context of cirrhosis. We aimed to elucidate the relationship between HRQoL and multidimensional frailty and to determine which HRQoL dimension independently impacted frail phenotype in our established cohort. METHODS: This was a prospective observational study by consecutively enrolling 355 patients with cirrhotic with decompensated signs in China. The HRQoL and frail phenotype were evaluated by the EuroQol-5D (EQ-5D) Questionnaire and Frailty Index, respectively. The relationship between EQ-5D utility index, as well as respective EQ-5D dimension, and Frailty Index was analysed according to the multiple linear regression analyses. RESULTS: More than half of the patients (56.3%) reported problems in any dimension of the EQ-5D, suggestive of impaired HRQoL. Moreover, the proportion of patients experiencing some/extreme problems significantly increased across all five dimensions (all p<0.001) in correspondence to transition from the robust to frail phenotype. Multiple linear regression analyses demonstrated that age, ascites and hepatic encephalopathy were positively associated with Frailty Index, while EQ-5D utility index (standardised ß coefficient= -0.442, p<0.001) negatively associated with Frailty Index. Notably, usual activities, self-care and mobility were the most influencing predictors associated with frailty. CONCLUSIONS: Our results support a rapid HRQoL assessment via EQ-5D may assist in predicting multidimensional frailty, and usual activities, self-care and mobility tend to be remediable targets while taking their effect on frail phenotype into consideration among patients with cirrhosis.

Integrating image and gene-data with a semi-supervised attention model for prediction of KRAS gene mutation status in non-small cell lung cancer.

KRAS is a pathogenic gene frequently implicated in non-small cell lung cancer (NSCLC). However, biopsy as a diagnostic method has practical limitations. Therefore, it is important to accurately determine the mutation status of the KRAS gene non-invasively by combining NSCLC CT images and genetic data for early diagnosis and subsequent targeted therapy of patients. This paper proposes a Semi-supervised Multimodal Multiscale Attention Model (S2MMAM). S2MMAM comprises a Supervised Multilevel Fusion Segmentation Network (SMF-SN) and a Semi-supervised Multimodal Fusion Classification Network (S2MF-CN). S2MMAM facilitates the execution of the classification task by transferring the useful information captured in SMF-SN to the S2MF-CN to improve the model prediction accuracy. In SMF-SN, we propose a Triple Attention-guided Feature Aggregation module for obtaining segmentation features that incorporate high-level semantic abstract features and low-level semantic detail features. Segmentation features provide pre-guidance and key information expansion for S2MF-CN. S2MF-CN shares the encoder and decoder parameters of SMF-SN, which enables S2MF-CN to obtain rich classification features. S2MF-CN uses the proposed Intra and Inter Mutual Guidance Attention Fusion (I2MGAF) module to first guide segmentation and classification feature fusion to extract hidden multi-scale contextual information. I2MGAF then guides the multidimensional fusion of genetic data and CT image data to compensate for the lack of information in single modality data. S2MMAM achieved 83.27% AUC and 81.67% accuracy in predicting KRAS gene mutation status in NSCLC. This method uses medical image CT and genetic data to effectively improve the accuracy of predicting KRAS gene mutation status in NSCLC.

A narrative review of deep learning in thyroid imaging: current progress and future prospects.

Background and Objective: Deep learning (DL) has contributed substantially to the evolution of image analysis by unlocking increased data and computational power. These DL algorithms have further facilitated the growing trend of implementing precision medicine, particularly in areas of diagnosis and therapy. Thyroid imaging, as a routine means to screening for thyroid diseases on large-scale populations, is a massive data source for the development of DL models. Thyroid disease is a global health problem and involves structural and functional changes. The objective of this study was to evaluate the general rules and future directions of DL networks in thyroid medical image analysis through a review of original articles published between 2018 and 2023. Methods: We searched for English-language articles published between April 2018 and September 2023 in the databases of PubMed, Web of Science, and Google Scholar. The keywords used in the search included artificial intelligence or DL, thyroid diseases, and thyroid nodule or thyroid carcinoma. Key Content and Findings: The computer vision tasks of DL in thyroid imaging included classification, segmentation, and detection. The current applications of DL in clinical workflow were found to mainly include management of thyroid nodules/carcinoma, risk evaluation of thyroid cancer metastasis, and discrimination of functional thyroid diseases. Conclusions: DL is expected to enhance the quality of thyroid images and provide greater precision in the assessment of thyroid images. Specifically, DL can increase the diagnostic accuracy of thyroid diseases and better inform clinical decision-making.

A comparative analysis of core needle biopsy and repeat fine needle aspiration in patients with inconclusive initial cytology of thyroid nodules.

Purpose: To assess and compare the effectiveness of ultrasound-guided core needle biopsy (CNB) in comparison to repeat fine-needle aspiration(rFNA) for thyroid nodules that yield inconclusive results following the initial fine-needle aspiration (FNA). Methods: A cohort of 471 patients who received an inconclusive cytological diagnosis following the initial FNA were included in this study. These patients subsequently underwent either CNB (n=242) or rFNA (n=229). The inconclusive FNA results encompassed categories I, III, and IV of The Bethesda System for Reporting Thyroid Cytopathology(TBSRTC), as well as the ultrasound images indicating malignancy despite FNA results falling under TBSRTC category II. This study assessed the sampling satisfaction rate, diagnostic efficacy, and complications associated with CNB compared to rFNA. Additionally, the impact of repeat puncture time and nodule size on diagnostic efficacy was analyzed. Results: Following repeat punctures, the satisfaction rate of the CNB sampling was found to be significantly higher than that of rFNA (83.9% vs 66.8%). The diagnostic rate in the CNB group was significantly greater compared to that of the rFNA group (70.7% vs 35.8%). In patients with nodule maximum diameters ranging from 5 mm to 20 mm, the diagnostic accuracy was significantly higher in the CNB group compared to that in the rFNA group. In patients with intervals less than 90 days, between 90 days and one year, the diagnostic rate in the CNB group was found to be higher compared to that in the rFNA group. In CNB, not immediately adjacent to the capsule was a risk factor for nodular puncture bleeding (37.0% vs 22.7%.). Conclusion: CNB demonstrated higher rates of satisfaction and diagnosis compared to the rFNA. The diagnostic effectiveness of CNB was not influenced by the time interval or the size of the thyroid nodule. Therefore, in cases where the initial FNA diagnosis of thyroid nodules is inconclusive, CNB should be considered as a viable option for re-puncture.

Clinical value of contrast-enhanced ultrasound quantitative analysis for differentiating thyroid lesions in Hashimoto's thyroiditis patients.

Background: The role of quantitative contrast-enhanced ultrasound (CEUS) in the evaluation of thyroid nodules with Hashimoto's thyroiditis (HT) has received little attention. Methods: This was a retrospective cohort study. We consecutively enrolled 242 patients (49 males, 193 females, average age 52 years) with a combined total of 248 thyroid nodules coexisting with HT who underwent biopsy/resection-proven pathology from December 2016 to June 2021. All patients underwent preoperative ultrasound (US) and CEUS examinations performed by 2 radiologists independently. Quantitative analysis of CEUS using time-intensity curves (TIC) was measured by an expert radiologist from the thyroid intra-nodule and the surrounding parenchyma and their ratios. Receiver operating characteristic (ROC) analysis was performed to evaluate their diagnostic performance. Results: The patients were divided into the nodular HT (NHT) group (n=42), the papillary thyroid carcinoma (PTC) group (n=154), and the primary thyroid lymphoma (PTL) group (n=52) according to their pathological results. TIC parameters revealed that PTC and PTL showed faster time to peak (TTP) (P=0.044, P=0.049), lower peak intensity (PI) (both P<0.001), and smaller areas under the curve (both P<0.001) than those of NHT. The intra nodule of PTL showed an obviously slower perfusion (ratio =0.90, P<0.001) and lower PI (ratio =0.84, P<0.001) compared with the thyroid parenchyma. TIC improved performance in distinguishing PTL from NHT [area under the curve (AUC): 0.947, 95% confidence interval (CI): 0.903-0.991], but inferior performance in differentiating PTC and NHT (AUC: 0.838, 95% CI: 0.759-0.917). Conclusions: CEUS quantitative analysis could be valuable in differentiating thyroid malignancies in patients with HT.

PEGylated-liposomal astaxanthin ameliorates Aß neurotoxicity and Alzheimer-related phenotypes by scavenging formaldehyde.

Alzheimer's disease (AD), which is a prevailing type of dementia, presents a significant global health concern. The current therapies do not meet clinical expectations. Amyloid-beta (Aß) has been found to induce endogenous formaldehyde (FA) accumulation by inactivating FA dehydrogenase (FDH); in turn, excessive FA triggers Aß aggregation that eventually leads to AD onset. Hence, scavenging FA by astaxanthin (ATX, a strong exogenous antioxidant) may be pursued as a promising disease-modifying approach. Here, we report that liposomal nanoparticles coupled with PEG (PEG-ATX@NPs) could enhance water-solubility of ATX and alleviate cognitive impairments by scavenging FA and reducing Aß deposition. To enable drug delivery to the brain, liposomes were used to encapsulate ATX and then coupled with PEG, which produced liposomal nanoparticles (PEGATX@NPs) with a diameter of <100 nm. The PEG-ATX@NPs reduced Aß neurotoxicity by both degrading FA and reducing FA-induced Aß assembly in vitro. Intraperitoneal administration of PEG-ATX@NPs in APPswe/PS1dE9 mice (APP/PS1, a familial model of AD), not only decreased the levels of brain FA and malondialdehyde (MDA, a typical product of oxidative stress), but also attenuated both intracellular Aß oligomerization and extracellular Aß-related senile plaque (SP) formation. These pathological changes were accompanied by rescued ability of spatial learning and memory. Collectively, PEG-ATX@NPs improved the water-solubility, bioavailability, and effectiveness of ATX. Thus, it has the potential to be developed as a safe and effective strategy for treating AD.

The network dynamics of self-compassion components and psychological symptoms during an intervention.

The change process of psychological interventions is complex and should be understood with a systems perspective. This study sought to examine the network dynamics of self-compassion components and psychological symptoms during an intervention. A total of 139 participants completed daily assessments during a 28-day intervention. Utilizing multilevel vector autoregressive (VAR) model, temporal and contemporaneous networks were generated and group differences in network dynamics were evaluated through descriptive assessment and permutation tests. The intervention group displayed a significant increase in self-compassion and decrease in psychological symptoms, with self-compassion mediating the intervention effects on symptoms. Network analysis revealed some network dynamics that might be relevant to desirable therapeutic changes in the intervention group. The intervention group demonstrated a significantly less connected contemporaneous depression network, indicating a decreased vulnerability to symptom activation. Additionally, the intervention group showed significantly more temporal connections from self-compassion to anxiety, indicating an increased influence of self-compassion on anxiety. These findings suggest that the intervention may have reshaped the interconnection pattern of symptoms and that between self-compassion components and symptoms.

Transcriptional regulation of FACT involves Coordination of chromatin accessibility and CTCF binding.

Histone chaperone FACT (facilitates chromatin transcription) is well known to promote chromatin recovery during transcription. However, the mechanism how FACT regulates genome-wide chromatin accessibility and transcription factor binding has not been fully elucidated. Through loss-of-function studies, we show here that FACT component Ssrp1 is required for DNA replication and DNA damage repair and is also essential for progression of cell phase transition and cell proliferation in mouse embryonic fibroblast cells. On the molecular level, absence of the Ssrp1 leads to increased chromatin accessibility, enhanced CTCF binding, and a remarkable change in dynamic range of gene expression. Our study thus unequivocally uncovers a unique mechanism by which FACT complex regulates transcription by coordinating genome-wide chromatin accessibility and CTCF binding.

HBcrAg-based risk score performs better than the HBV DNA-based scores for HCC prediction in grey zone patients who are HBeAg-negative.

Background & Aims: Risk scores have been designed to predict the development of hepatocellular carcinoma (HCC) in treatment-naive patients with chronic hepatitis B (CHB). However, little is known about their predictive accuracy in HBeAg-negative patients in the grey zone (GZ). We aimed to develop a HBcrAg-based HCC risk score and explore whether it outperforms other risk scores in GZ patients. Methods: Two retrospective cohorts of HBeAg-negative patients with American Association for the Study of Liver Diseases-defined GZ were established for derivation and validation (Taiwanese, N = 911; Japanese, N = 806). All of them were non-cirrhotic at baseline and remained treatment-naive during the follow-up. The primary endpoint was HCC development. Results: In a median follow-up period of 15.5 years, 85 patients developed HCC in the derivation cohort. We found that age, sex, alanine aminotransferase, platelet count, and HBcrAg, but not HBV DNA levels, were independent predictors and a 20-point GZ-HCC score was developed accordingly. The 10-year and 15-year area under the ROC curve (AUROC) ranged from 0.83 to 0.86, which outperformed the HBV DNA-based HCC risk scores, including REACH-B and GAG-HCC scores (AUROC ranging from 0.66 to 0.74). The better performance was also validated in EASL- and Asian Pacific Association for the Study of the Liver-defined GZ patients. These findings remained consistent in the validation cohort. Finally, the low-risk and high-risk GZ patients (stratified by a score of 8) had an HCC risk close to inactive CHB and immune-active CHB patients, respectively, in both cohorts. Conclusions: The HBcrAg-based GZ-HCC score predicts HCC better than other HBV DNA-based risk scores in GZ patients who are HBeAg-negative patients, which may help optimise their clinical management. Impact and implications: We have developed a risk score based on HBcrAg, which has shown better predictive ability for HCC compared with other risk scores based on HBV DNA. Using a score of 8, GZ patients can be classified into low- and high-risk groups, which can guide follow up and early treatment, respectively. This validated risk score is a valuable tool for optimising the management of GZ patients who are HBeAg-negative.

Study on atomization mechanisms and spray fragmentation characteristics of water and emulsion butachlor.

Agricultural chemicals are commonly used to control pests and weeds, but cause pesticide waste problems. Oil-based emulsions are often used as pesticide formulations to improve pesticide utilization. In this study, the spray visualization experiment of the water and oil-based emulsion butachlor is carried out using an ST flat fan nozzle at 0.1-0.5 MPa pressure. The dimensionless method is used to analyze the difference in liquid sheet fragmentation morphology and disintegration process and the influence of different fragmentation methods on droplet size. It is found that the hydrophobic components in pesticide have a significant effect on the morphology and process of atomization fragmentation. When spray liquid is water, the liquid sheet breaks up into liquid ligaments due to the Rayleigh instability, then the ligaments break up into droplets. The side view of a liquid sheet is a large-amplitude wave disturbance. When the spray liquid is the emulsion butachlor, holes are generated on the liquid sheet, then the holes break up into droplets. The fragmentation method of emulsion spray is the perforation mechanism. Compared with water spray, the presence of the pesticide butachlor increases the droplet size and spray angle and improves the uniformity of droplet size distribution but reduces the breakup length. The spray angle shows a power law dependence of the Weber number with a power of 0.17 for all conditions tested here. At 0.3 MPa, DV50 increases 25%, and span decreases from 1.187 to 1.172. This study could provide reference for the addition of agricultural additives, the improvement of spray operation efficiency, and the establishment of spray fragmentation mechanism.

The influence path of community green exposure index on activity behavior under multi-dimensional spatial perception.

The purpose of this research is to reveal the internal relationship among community green space, space perception, and activity behavior response to supplement the lack of research results on the binary relationship between green space and behavior. Nine residential community green spaces and 398 residents were selected as the research objects. Thematic clustering and factor identification were used to determine the spatial dimensions of community green space that residents were concerned about. The analysis of the green exposure index, spatial perception evaluation, and activity behavior survey were combined to determine the influence of the green exposure index on spatial perception and activity behavior and its internal correlation path. According to research data, the community green view index (GVI) and normalized difference vegetation index (NDVI) negatively affected the perception factor, while the perception factor positively affected the activity frequency. The SEM model shows that the green exposure index stimulated activity behavior through the intermediate effect of the internal perception path of perceived landscape quality, perceived workability, and perceived accessibility. Spatial perception as the basis of the instantaneous emotional reaction process may affect people's choices for activities but be unable to extend the duration of the activities. The internal association among community green space, spatial perception, and physical activity behavior develops on the basis of spatial patterns at certain scales. This study provides a theoretical basis for understanding the spatial experience and residents' behavioral needs, evaluating the quality of urban green space scientifically, and promoting the optimization of community green space structure.

Reduced muscle strength is closely linked to computed tomography-defined myosteatosis among inpatients with cirrhosis.

BACKGROUND: Myosteatosis indicates pathological fat infiltration in muscles and is regarded as a distinct disease from sarcopenia. This muscular condition exhibits a link to muscle fiber disarrangement coinciding with disrupted muscle contractility and weakened mechanical action, mirrored as decreased muscle quality. However, the relationship between handgrip strength (HGS) and computed tomography-defined myosteatosis among cirrhosis is unclear. We aimed to investigate the association between HGS and myosteatosis and determine gender-specific cutoffs regarding HGS to identify myosteatotic subjects. METHODS: We prospectively recruited 221 cirrhotic patients. The presence of myosteatosis was determined according to intramuscular adipose tissue content. The relationship between HGS and myosteatosis was evaluated according to Spearman correlation coefficient, area under the ROC curve, and multivariate logistic regression analysis. Moreover, a model based on the classification and regression tree method was generated. RESULTS: Our results showed that HGS exhibits modestly negative correlation with intramuscular adipose tissue content in the entire cohort (rs = -0.269, P < .001) and across diverse subgroups precluding extremely deteriorating conditions. After controlling for multiple clinical features and biochemical parameters, HGS (odds ratio = 0.921, P = .010) was independently associated with myosteatosis in addition to age and body mass index. On applying the Japan Society of Hepatology-recommended cutoffs, an area under the ROC curve of HGS was 0.627 with a sensitivity of 77.4% and a specificity of 47.9%. The decision tree including body mass index and low HGS correctly classified ~85% of the cases in development and validation sets. CONCLUSIONS: HGS was in close relation to myosteatosis among inpatients with cirrhosis.

Coexistent GLIM-Defined Malnutrition and Sarcopenia Increase the Long-Term Mortality Risk in Hospitalized Patients with Decompensated Cirrhosis.

INTRODUCTION: The synergistic impact of coexistent malnutrition and sarcopenia on morality in hospitalized patients with decompensated cirrhosis remains elusive. This prospective cohort study aimed to delineate the prevalence concerning coexistence of malnutrition and sarcopenia and the prognosticating role on long-term mortality among cirrhosis. METHODS: Adult cirrhotic patients with decompensated episodes between 2019 and 2021 were consecutively enrolled. Malnutrition and sarcopenia were diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria and the European Working Group on Sarcopenia in Older People (EWGSOP2) algorithm, respectively. The entire cohort was divided into three groups: non-malnutrition and non-sarcopenia (NN), malnutrition or sarcopenia, and coexistent malnutrition and sarcopenia (MS). Log-rank test and multivariate Cox regression model were utilized to evaluate survival status and independent risk factors for mortality, respectively. RESULTS: Our findings indicated that malnutrition manifested in 44.6% of inpatients with decompensated cirrhosis, while sarcopenia presented in 16.4% of the entire cohort, indicative of a prevalence of 14.7% regarding coexistent malnutrition and sarcopenia. The Kaplan-Meier graphic demonstrated a significant difference regarding survival curves among the three groups, referring to the MS group presented with the lowest survival rate (log-rank test: p < 0.001). Moreover, coexistent malnutrition and sarcopenia were associated with nearly 4 times higher mortality risk (model 1: hazard ratio [HR] = 3.31, 95% confidence interval [CI]: 1.20-9.13, p = 0.020; model 2: HR = 4.34, 95% CI: 1.52-12.4, p = 0.006) in comparison with patients without any condition (NN group). CONCLUSIONS: Malnutrition and sarcopenia had superimposed negative impacts on inpatients with decompensated cirrhosis. It is imperative to identify this vulnerable subset to provide prompt therapeutic intervention for better prognosis.

Association between serum trace elements and sleep disturbance in patients with decompensated cirrhosis.

Background: Sleep disturbance and trace elements imbalance are common features in patients with decompensated cirrhosis, partially sharing similar mechanistic contributors and linking to adverse outcomes. However, there is a paucity of data concerning their relationship. Objectives: To investigate the association between serum trace elements levels and sleep quality in the context of cirrhosis. Design: Cross-sectional study. Methods: We consecutively enrolled 160 patients with decompensated cirrhosis. The sleep disturbance was determined by the Pittsburgh Sleep Quality Index (PSQI > 5). Serum trace elements [magnesium, calcium, iron, copper (Cu), zinc (Zn), lead, and manganese] was measured by inductively coupled plasma mass spectrometry. Association of examined trace elements levels and sleep disturbance was analyzed by multiple linear (global PSQI scores) and multivariate logistic (dichotomized PSQI categories) regression models, respectively. Results: In total, 91 patients (56.88%) represented PSQI-defined sleep disturbance, characterized by female preponderance, lower body mass index levels, and higher serum Cu levels (all p < 0.05). Looking into its clinical relevance with debilitating conditions, we showed that Cu/Zn ratio (CZr) is significantly higher in cirrhosis with poor sleep quality (1.77 versus 1.48, p = 0.003). Diagnostic performance analysis indicated CZr > 1.62 to exhibit better discrimination relative to respective Cu. Both multiple linear (ß = 0.355, p < 0.001) and multivariate logistic regression (odds ratio = 2.364, p = 0.019) identified higher CZr as an independent risk factor associated with sleep disturbance. Conclusion: Our findings implied an association between higher CZr and the presence of sleep disturbance in patients with decompensated cirrhosis.

PMSG-Net: A priori-guided multilevel graph transformer fusion network for immunotherapy efficacy prediction.

In the case of specific immunotherapy regimens and access to pre-treatment CT scans, developing reliable, interpretable intelligent image biomarkers to predict efficacy is essential for physician decision-making and patient treatment selection. However, varying levels of prognosis show a similar appearance on CT scans. It becomes challenging to stratify patients by a single pre-treatment CT scan when presenting subtle differences in images for experienced experts and existing prognostic classification methods. In addition, the pattern of peri-tumoural radiological structures also determines the patient's response to ICIs. Therefore, it is essential to develop a method that focuses on the clinical priori features of the tumour edges but also makes full use of the rich information within the 3D tumour. This paper proposes a priori-guided multilevel graph transformer fusion network (PMSG-Net). Specifically, a graph convolutional network is first used to obtain a feature representation of the tumour edge, and complementary information from that detailed representation is used to enhance the global representation. In the tumour global representation branch (MSGNet), we designed the cascaded scale-enhanced swin transformer to obtain attributes of graph nodes, and efficiently learn and model spatial dependencies and semantic connections at different scales through multi-hop context-aware attention (MCA), yielding a richer global semantic representation. To our knowledge, this is the first attempt to use graph neural networks to predict the efficacy of immunotherapy, and the experimental results show that this method outperforms the current mainstream methods.

Dissecting the potential role of ferroptosis in liver diseases: an updated review.

Ferroptosis is a novel form of cell death, manifested by iron-dependent, non-apoptotic manner resulting from the intracellular accumulation of large clusters of reactive oxygen species (ROS) and lipid peroxides due to abnormal iron metabolism. Since the liver is the main organ of human body for storing iron, it is essential to perform in-depth investigation on the role and mechanistic basis of ferroptosis in the context of divergent liver diseases. We previously summarized the emerging role of ferroptosis among various liver diseases, however, the past few years have been a surge in research establishing ferroptosis as the molecular basis or treatment option. This review article concentrated on the accumulating research progress of ferroptosis in a range of liver diseases such as acute liver injury/failure (ALI/ALF), immune-mediated hepatitis, alcoholic liver disease (ALD), nonalcoholic fatty liver disease and liver fibrosis. Ferroptosis may be a promising target for the prevention and treatment of various liver diseases, providing a strategy for exploring new therapeutic avenues for these entities.