A novel disulfide death-related genes prognostic signature identifies the role of IPO4 in glioma progression.

BACKGROUND: "Disulfide death," a form of cellular demise, is triggered by the abnormal accumulation of intracellular disulfides under conditions of glucose deprivation. However, its role in the prognosis of glioma remains undetermined. Therefore, the main objective of this study is to establish prognostic signature based on disulfide death-related genes (DDRGs) and to provide new solutions in choosing the effective treatment of glioma. METHODS: The RNA transcriptome, clinical information, and mutation data of glioma samples were sourced from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), while normal samples were obtained from the Genotype-Tissue Expression (GTEx). DDRGs were compiled from previous studies and selected through differential analysis and univariate Cox regression analysis. The molecular subtypes were determined through consensus clustering analysis. Further, LASSO analysis was employed to select characteristic genes, and subsequently, a risk model comprising seven DDRGs was constructed based on multivariable Cox analysis. Kaplan-Meier survival curves were employed to assess survival differences between high and low-risk groups. Additionally, functional analyses (GO, KEGG, GSEA) were conducted to explore the potential biological functions and signaling pathways of genes associated with the model. The study also explored immune checkpoint (ICP) genes, immune cell infiltration levels, and immune stromal scores. Finally, the effect of Importin-4(IPO4) on glioma has been further confirmed through RT-qPCR, Western blot, and cell functional experiments. RESULTS: 7 genes associated with disulfide death were obtained and two subgroups of patients with different prognosis and clinical characteristics were identified. Risk signature was subsequently developed and proved to serve as an prognostic predictor. Notably, the high-risk group exhibited an immunosuppressive microenvironment characterized by a high concentration of M2 macrophages and regulatory T cells (Tregs). In contrast, the low-risk group showed lower half-maximal inhibitory concentration (IC50) values. Therefore, patients in the high-risk group may benefit more from immunotherapy, while patients in the low-risk group may benefit more from chemotherapy. In addition, in vitro experiments have shown that inhibition of the expression of IPO4 leads to a significant reduction in the proliferation, migration, and invasion of glioma cells. CONCLUSION: This study identified two glioma subtypes and constructed a prognostic signature based on DDRGs. The signature has the potential to optimize the selection of patients for immune- and chemotherapy and provided a potential therapeutic target for glioma.

Differences and common ground in the frameworks of health-related quality of life in traditional Chinese medicine and modern medicine: a systematic review.

PURPOSE: This systematic review aims to explore the conceptualization of health-related quality of life (HRQoL) in China. With HRQoL influenced by both modern medicine (MM) and traditional Chinese medicine (TCM), the study seeks to identify differences and common ground between the frameworks of MM and TCM as defined in the literature. METHOD: A systematic literature search was conducted across three Chinese databases and four English databases. The data was extracted including title, author(s), publication year, region, aim, method, category, and result. When sorting data, we broke down the HRQoL frameworks into concepts, domains and facets, with a focus on overlapped facets between the frameworks of MM and TCM. RESULTS: A total of 31 studies were included. In the perspective of TCM, HRQoL is centered around three key 'concepts': (1) 'xingshentongyi' (unity of body and spirit), (2) 'tianrenheyi' (harmony between man and nature), and (3) 'qiqing' (seven emotional forms). In contrast, the MM framework comprises 'physical,' 'mental,' 'social,' and 'environment' domains. Out of the 59 unique facets identified, 28 are common to both TCM and MM, 9 specific to TCM, and 22 specific to MM. 'Appetite,' 'sleep,' and 'energy' are the most frequently mentioned facets in both frameworks. CONCLUSION: The concept of HRQoL in China encompasses frameworks rooted in both TCM and MM. While TCM and MM have distinct healthcare approaches, they share overlapping domains when measuring HRQoL through questionnaires. Furthermore, TCM and MM demonstrate considerable convergence in terms of HRQoL facets, showing the potential for utilizing HRQoL instruments across different cultural settings.

Conditional survival of patients with primary bone lymphoma of the spine: how survival changes after initial diagnosis.

Background: The current survival prediction methodologies for primary bone lymphoma (PBL) of the spine are deficient. This study represents the inaugural utilization of conditional survival (CS) to assess the outcome of this disease. Moreover, our objective was to devise a CS-based nomogram for predicting overall survival (OS) in real-time for spinal PBL. Methods: Patients with PBL of the spine diagnosed between January 2000 and December 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The OS was determined through the Kaplan-Meier method. The CS characteristic of patients with spinal PBL was delineated, with the CS being estimated utilizing the formula: CS(α|ß) = OS(α+ß)/OS(ß). CS(α|ß) denotes the probability of additional α-year survivorship, assuming the patient has already survived ß years after the time of observation. Three methods including univariate Cox regression, best subset regression (BSR) and the least absolute shrinkage and selection operator (LASSO) regression were used to identify predictors for CS-based nomogram construction. Results: Kaplan-Meier analysis was executed to determine the OS rate for these patients, revealing a survival rate of 68% and subsequently 63% at the 3-year and 5-year mark respectively. We then investigated the CS patterning exhibited by these patients and discovered the survival of PBL in the spine progressively improved with time. Meanwhile, through three different prognostic factor selection methods, we identified the best predicter subset including age, tumor histology, tumor stage, chemotherapy and marital status, for survival prediction model construction. Finally, we successfully established and validated a novel CS-based nomogram model for real-time and dynamic survival estimation. Moreover, we further designed a risk stratification system to facilitate the identification of high-risk patients. Conclusions: This is the first study to analyze the CS pattern of PBL of the spine. And we have also developed a CS-based nomogram that provide dynamic prognostic data in real-time, thereby aiding in the formulation of personalized treatment strategies in clinical practice.

Synergistic enhancement of wearable biosensor through Pt single-atom catalyst for sweat analysis.

Real-time monitoring of biological markers in sweat is a valuable tool for health assessment. In this study, we have developed an innovative wearable biosensor for precise analysis of glucose in sweat during physical activities. The sensor is based on a single-atom catalyst of platinum (Pt) uniformly dispersed on tricobalt tetroxide (Co3O4) nanorods and reduced graphene oxide (rGO), featuring a unique three-dimensional nanostructure and excellent glucose electrocatalytic performance with a wide detection range of 1-800 µM. Additionally, density functional theory calculations have revealed the synergetic role of Pt active sites in the Pt single-atom catalyst (Co3O4/rGO/Pt) in glucose adsorption and electron transfer, thereby enhancing sensor performance. To enable application in wearable devices, we designed an S-shaped microfluidic chip and a point-of-care testing (POCT) device, both of which were validated for effectiveness through actual use by volunteers. This research provides valuable insights and innovative approaches for analyzing sweat glucose using wearable devices, contributing to the advancement of personalized healthcare.

Implicit weight bias: shared neural substrates for overweight and angry facial expressions revealed by cross-adaptation.

The perception of facial expression plays a crucial role in social communication, and it is known to be influenced by various facial cues. Previous studies have reported both positive and negative biases toward overweight individuals. It is unclear whether facial cues, such as facial weight, bias facial expression perception. Combining psychophysics and event-related potential technology, the current study adopted a cross-adaptation paradigm to examine this issue. The psychophysical results of Experiments 1A and 1B revealed a bidirectional cross-adaptation effect between overweight and angry faces. Adapting to overweight faces decreased the likelihood of perceiving ambiguous emotional expressions as angry compared to adapting to normal-weight faces. Likewise, exposure to angry faces subsequently caused normal-weight faces to appear thinner. These findings were corroborated by bidirectional event-related potential results, showing that adaptation to overweight faces relative to normal-weight faces modulated the event-related potential responses of emotionally ambiguous facial expression (Experiment 2A); vice versa, adaptation to angry faces relative to neutral faces modulated the event-related potential responses of ambiguous faces in facial weight (Experiment 2B). Our study provides direct evidence associating overweight faces with facial expression, suggesting at least partly common neural substrates for the perception of overweight and angry faces.

Effect of the configuration mixing on the polarization and angular distribution of x-ray line emissions following electron-impact excitation of Ne-like ions.

We present a systematic theoretical study on the angular distribution and linear polarization of x-ray line emissions of neon-like ions following the electron-impact excitation from the ground state to the excited levels [(2p5)1/23d3/2]J=1, [(2p5)3/23d5/2]J=1, [(2p5)3/23d3/2]J=1, and [(2p5)1/23s]J=1. The cross sections are calculated by using the flexible atomic code under configuration-interaction plus many-body perturbation theory method. The angular distribution and linear polarization are obtained based on density matrix theory. Emphasis has been placed on the effect of the configuration mixing on the angular distribution and polarization. It has been proved that the strong mixing of configuration [(2p5)3/23d3/2]J=1 with configuration [(2p5)1/23s]J=1 can result in the abrupt change of Z-dependence of angular distribution and polarization. It indicates that angular distribution and polarization can be expected to serve as a tool for investigation of configuration mixing effect.

Temporal Network Embedding Enhanced With Long-Range Dynamics and Self-Supervised Learning.

Temporal network embedding (TNE) has promoted the research of knowledge discovery and reasoning on networks. It aims to embed vertices of temporal networks into a low-dimensional vector space while preserving network structures and temporal properties. However, most existing methods have limitations in capturing dynamics over long distances, which makes it difficult to explore multihop topological associations among vertices. To tackle this challenge, we propose LongTNE, which learns the long-range dynamics of vertices to endow TNE with the ability to capture high-order proximity (HP) of networks. In LongTNE, we employ graph self-supervised learning (Graph SSL) to optimize the establishment probability of deep links in each network snapshot. We also present an accumulated forward update (AFU) module to fathom global temporal evolution among multiple network snapshots. The empirical results on six temporal networks demonstrate that, in addition to achieving state-of-the-art performance on network mining tasks, LongTNE can be handily extended to existing TNE methods.

The correlation study between the length and angle of ascending aortic and the incidence risk of acute type A aortic dissection.

Objective: This study utilized computed tomography angiography (CTA) to assess the risk of acute type A aortic dissection (ATAAD) by analyzing the imaging morphology indicators of the ascending aorta, along with the relevant risk factors associated with aortic dissection. Methods: The study utilized a retrospective observational research design. The population consisted of 172 patients who received treatment in the Department of Cardiothoracic Surgery at Qilu Hospital, Shandong University, from January 2018 to December 2022. The patients were divided into two groups: the ATAAD group (n = 97) and the thoracic aortic aneurysm group (TAA, n = 75). Demographic data and ascending aorta CTA measurements were collected from all patients. Single factor and multivariate logistic regression were employed to analyze the statistical differences in clinical data and ascending aorta CTA imaging morphology indicators between the two groups. Results: The variables were included in logistic multivariate analysis for further screening, indicating that the length of the ascending aorta (LAA) before ATAAD (OR = 3.365; 95% CI :1.742-6.500, P<0.001), ascending arch angle (asc-arch angle, OR = 0.902; 95% CI: 0.816-0.996, P = 0.042) and the maximum aortic diameter (MAD) before ATAAD, (OR = 0.614; 95% CI: 0.507-0.743, P<0.001) showed statistically significant differences. Conclusions: This study suggests that increased LAA and MAD, as well as a smaller asc-arch angle may be high-risk factors for the onset of ATAAD.

Effect of fasting plasma glucose level in severe fever and thrombocytopenia syndrome patients without diabetes.

Hyperglycemia is correlated with worse in-hospital outcomes in acute infectious diseases such as coronavirus disease 2019 (COVID-19) and severe fever with thrombocytopenia syndrome (SFTS). This study assessed the relationship between fasting plasma glucose (FPG) levels and in-hospital mortality, disease type, and secondary infections among individuals with SFTS without preexisting diabetes. The clinical data and laboratory results upon admission of 560 patients with SFTS without preexisting diabetes meeting the inclusion criteria at Wuhan Union Hospital were collected. FPG levels in surviving patients with SFTS subjects were significantly lower than those in patients with SFTS who had died (P<0.0001). In multivariate Cox regression, high FPG level (≥11.1 mmol/L) was a risk factor independently associated with the in-hospital death of patients with SFTS without preexisting diabetes. Similarly, the FPG levels in general patients with SFTS were significantly lower than those in patients with severe SFTS (P<0.0001). Multivariate logistic regression identified high FPG level (7.0-11.1 mmol/L) as a risk factor independently associated with SFTS severity. While FPG levels were comparable between patients with SFTS with and without secondary infection (P = 0.5521), logistic regression analysis revealed that high FPG levels were not a risk factor for secondary infection in patients with SFTS without preexisting diabetes. High FPG level on admission was an independent predictor of in-hospital death and severe disease in individuals with SFTS without preexisting diabetes. FPG screening upon admission and glycemic control are effective methods for improving the prognosis of patients with SFTS.

A straightforward approach for the rapid detection of red Noctiluca scintillans blooms from satellite imagery.

Red Noctiluca scintillans (RNS), a prominent species of dinoflagellate known for its conspicuous size and ability to form blooms, exhibits heterotrophic behavior and functions as a microzooplankton grazer within the marine food web. In this study, a straightforward technique referred to as the blue-green index (BGI) has been introduced for the purpose of distinguishing and discerning RNS from neighboring waters, owing to its pronounced absorption in the blue-green spectral range. This method has been applied across a range of satellite imagery, encompassing both multi-spectral and hyperspectral sensors. The study delved into three instances of bloom occurrences caused by RNS: firstly, in November 2014 and April 2022 off the western coast of Guangdong, and secondly, in February 2021 within the Beibu Gulf. The notable bloom event in the Beibu Gulf during February 2021 extended across an expansive area totaling 6933.5 km2. The motion speed and direction of the RNS bloom patches were also derived from successive satellite images. The recently introduced BGI method demonstrates insensitivity to suspended sediment, though its successful application necessitates accurate atmospheric correction. Subsequent efforts will involve the quantification of RNS blooms in a more precise manner, utilizing hyperspectral satellite data grounded in optimized band configurations.

A Head-to-Head Comparison of EQ Health and Wellbeing and EQ-5D-5L in Patients, Carers, and General Public in China.

OBJECTIVES: This study aimed to understand the psychometric properties of EQ Health and Wellbeing (EQ-HWB) and to examine its relationship with EQ-5D-5L in a sample covering patients, carers, and general public. METHODS: A cross-sectional study was conducted in Guizhou Province, China. The acceptability, convergent validity (using Spearman correlation coefficients), internal structure (using exploratory factor analysis), and known-group validity of EQ-HWB, EQ-HWB-Short (EQ-HWB-S), and EQ-5D-5L were reported and compared. RESULTS: A total of 323 participants completed the survey, including 106 patients, 101 carers, and 116 individuals from the general public. Approximately 7.4% of participants had at least 1 missing response. In the EQ-HWB and EQ-5D-5L items related to activities, there were more level 1 responses. The correlations between EQ-HWB and EQ-5D-5L items ranged from low to high, confirming the convergent validity of similar aspects between the 2 instruments. Notably, EQ-HWB measures 2 additional factors compared with EQ-5D-5L or EQ-HWB-S, both of which share 3 common factors. When the patient group was included, EQ-5D-5L had the largest effect size, but it failed to differentiate between the groups of general public and carers. Both EQ-HWB and EQ-HWB-S demonstrated better known-group validity results when carers were included. CONCLUSIONS: EQ-HWB measures a broader quality of life construct that goes beyond health measured by EQ-5D-5L. By encompassing a broader scope, the impact of healthcare interventions may become diluted, given that other factors can influence wellbeing outcomes as significantly as health conditions do.

Sm and Gd Contacts in 2D Semiconductors for High-Performance Electronics and Spintronics.

Two-dimensional (2D) semiconductors have attracted great attention due to their rich electronic properties and even been considered to have the potential to extend Moore's Law. However, the Schottky barrier between the metal and 2D semiconductor is formed due to the metal-induced gap states (MIGS), which greatly hinder the development of 2D semiconductor transistors in large-scale integrated circuits. Meanwhile, most air-stable 2D semiconductors are nonmagnetic, limiting the possibility of spintronic application. Here, we report a new strategy to suppress the MIGS and reduce the Schottky barrier height on 2D semiconductors (MoS2, WS2, and WSe2) by using lanthanide metal (Sm and Gd) contacts. It was found the lanthanide contacts exhibit a good Ohmic property with a near-zero Schottky barrier. As a result, the carrier mobility of MoS2 transistors reaches 118 cm2/(V s). Furthermore, Gd-contact MoS2 transistors show the typical magnetic property where the magnetoresistance reaches 2.7% at 5 K. By studying its spin valve effect, it was demonstrated that the nonlocal magnetoresistance is 4.1% and spin polarization is 3.25%. This study provides a promising pathway for high-performance 2D electronic and spintronics, which may open a new strategy for future computing-in-memory architecture.

Electrically tunable interlayer recombination and tunneling behavior in WSe2/MoS2 heterostructure for broadband photodetector.

Electrically tunable band structure and light-matter interaction are of great importance in designing novel devices and constructing high-integrated and high-performance photodetector systems in the future. However, tunable mechanisms on the layered semiconductor, especially the heterojunction, are still unclear. Herein, the WSe2/MoS2 phototransistor with dual-gated configuration is fabricated, and its electrical and photoelectrical conversion has been studied to show large tunability. It was found that conduction and rectification characteristics can be tuned by dual gates showing four states, p-i, p-n, i-n, and n-n, as a result of the charging and depletion of WSe2 and MoS2. The rectifying ratio can be modulated across a large range from 102.5 to 10-3.2. Its photoelectronic characteristics were observed to exhibit bipolar and wavelength-dependent behaviors. The interlayer recombination of charge carriers dominates the photoresponse of the device under the illumination of visible light, while it is dominated by interlayer tunneling under the illumination of near-infrared wavelengths. This bipolar photoresponse is associated with different states of band alignment, which can be switched by dual-gating modulation. Finally, by tuning the gate voltage, responsivities reach 27 445 A W-1 and 2827 A W-1 at wavelengths of 400 and 1010 nm at room temperature, respectively, which directly extends the response region from visible light to near-infrared.

The methodological quality of systematic reviews regarding the Core Outcome Set (COS) development.

BACKGROUND: The Core Outcome Measures in Effectiveness Trials (COMET) working group proposed core outcome sets (COS) to address the heterogeneity in outcome measures in clinical studies. According to the recommendations of COMET, performing systematic reviews (SRs) usually was the first step for COS development. However, the SRs that serve as a basis for COS are not specifically appraised by organizations such as COMET regarding their quality. Here, we investigated the status of SRs related to development of COS and evaluated their methodological quality. METHODS: We conducted a search on PubMed to identify SRs related to COS development published from inception to May 2022. We qualitatively summarized the disease included in SR topics, and the studies included in the SRs. We evaluated the methodological quality of the SRs using AMSTAR 2.0 and compared the overall quality of SRs with and without protocols using the Mann-Whitney U test. RESULTS: We included 175 SRs from 23 different countries or regions, and they mainly focused on five diseases: musculoskeletal system or connective tissue disease (n = 19, 10.86%), injury, poisoning, or certain other consequences of external causes (n = 18, 10.29%), digestive system disease (n = 16, 9.14%), nervous system disease (n = 15, 8.57%), and genitourinary system disease (n = 15, 8.57%). Although 88.00% of SRs included randomized controlled trials (RCTs), only a few SRs (23.38%) employed appropriate tools to assess the risk of bias in RCTs. The assessment results on the basis of AMSTAR 2.0 indicated that most SRs (93.71%) were rated as ''critically low'' to ''low'' in terms of overall confidence. The overall confidence of SRs with protocols was significantly higher than that without protocols (P <.001). Compared to the SRs with protocols on Core Outcome Measures in Effectiveness Trials (COMET), SRs with protocols on PROSPERO were of better overall confidence (P = .017). CONCLUSION: The overall quality of published SRs regarding COS development was poor. Our findings emphasize the need for researchers to carefully select the disease topic and strictly adhere to the requirements of optimal methodology when conducting a SR for the establishment of a COS.

Predicting Protein Functions Based on Heterogeneous Graph Attention Technique.

In bioinformatics, protein function prediction stands as a fundamental area of research and plays a crucial role in addressing various biological challenges, such as the identification of potential targets for drug discovery and the elucidation of disease mechanisms. However, known functional annotation databases usually provide positive experimental annotations that proteins carry out a given function, and rarely record negative experimental annotations that proteins do not carry out a given function. Therefore, existing computational methods based on deep learning models focus on these positive annotations for prediction and ignore these scarce but informative negative annotations, leading to an underestimation of precision. To address this issue, we introduce a deep learning method that utilizes a heterogeneous graph attention technique. The method first constructs a heterogeneous graph that covers the protein-protein interaction network, ontology structure, and positive and negative annotation information. Then, it learns embedding representations of proteins and ontology terms by using the heterogeneous graph attention technique. Finally, it leverages these learned representations to reconstruct the positive protein-term associations and score unobserved functional annotations. It can enhance the predictive performance by incorporating these known limited negative annotations into the constructed heterogeneous graph. Experimental results on three species (i.e., Human, Mouse, and Arabidopsis) demonstrate that our method can achieve better performance in predicting new protein annotations than state-of-the-art methods.

Validity and responsiveness of EQ-5D-Y in children with haematological malignancies and their caregivers.

The psychometric properties of the EQ-5D-Y have not been widely tested in severely ill children. The aim of this study was to assess and compare the validity and responsiveness of the EQ-5D-Y-3L and EQ-5D-Y-5L in paediatric inpatients with haematological malignancies and caregivers. Respondents completed the interviewer-administered self-complete or proxy version of the EQ-5D-Y-3L and EQ-5D-Y-5L and an overall health assessment twice on different days. Known-groups validity was assessed by comparing patients who differed in overall health and Eastern Cooperative Oncology Group (ECOG) performance. Responsiveness to worsened health was assessed using standardised effect size (SES) for patients with worsened ECOG grade, self-reported rating, or chemotherapy initiation. Ninety-six dyads completed the baseline questionnaires. A smaller proportion of patients reported "no problems" on the EQ-5D-Y-5L compared to EQ-5D-Y-3L for most of the five dimensions. Patients in poor health reported more problems in all dimensions and had higher EQ-5D-Y-5L level sum score, lower EQ VAS and EQ-5D-Y-3L index scores (Cohen's d ES: 0.32-1.38 for patients; 0.50-2.05 for caregivers). There was a mild to good responsiveness to worsened health condition based on ECOG (SES: 0.14-0.61 for patients; 0.40-0.96 for caregivers), suggesting the proxy version was slightly responsive than the self-complete version of both instruments. The results demonstrated validity and responsiveness for both the self-complete and proxy versions of the EQ-5D-Y-3L and EQ-5D-Y-5L. The proxy and 5-level versions of the instrument were more sensitive than the self-complete and 3-level versions in this patient group.

Optimizing the Solvent Selection of the Ultrasound-Assisted Extraction of Sea Buckthorn (Hippophae rhamnoides L.) Pomace: Phenolic Profiles and Antioxidant Activity.

Sea buckthorn pomace (SBP) is a by-product of sea buckthorn processing that is rich in bioactive compounds. In this study, different active ingredients were extracted by using different solvents (water, methanol, ethanol, glycerol, ethyl acetate, and petroleum ether) combined with an ultrasonic assisted method. The correlation between the active ingredients and antioxidant properties of the extract was studied, which provided a research basis for the comprehensive utilization of SBP. This study revealed that the 75% ethanol extract had the highest total phenolic content (TPC) of 42.86 ± 0.73 mg GAE/g, while the 75% glycerol extract had the highest total flavonoid content (TFC) of 25.52 ± 1.35 mg RTE/g. The ethanol extract exhibited the strongest antioxidant activity at the same concentration compared with other solvents. The antioxidant activity of the ethanol, methanol, and glycerol extracts increased in a concentration-dependent manner. Thirteen phenolic compounds were detected in the SBP extracts using UPLC-MS/MS analysis. Notably, the 75% glycerol extract contained the highest concentration of all identified phenolic compounds, with rutin (192.21 ± 8.19 µg/g), epigallocatechin (105.49 ± 0.69 µg/g), and protocatechuic acid (27.9 ± 2.38 µg/g) being the most abundant. Flavonols were found to be the main phenolic substances in SBP. A strong correlation was observed between TPC and the antioxidant activities of SBP extracts. In conclusion, the choice of solvent significantly influences the active compounds and antioxidant activities of SBP extracts. SBP extracts are a valuable source of natural phenolics and antioxidants.

Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

OBJECTIVES: To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction-V (ASIR-V) algorithms. METHODS: An ACR464 phantom was scanned with DEsCT at four dose levels (3.5 mGy, 5 mGy, 7.5 mGy, and 10 mGy). Virtual monochromatic images were reconstructed at five energy levels (40 keV, 50 keV, 68 keV, 74 keV, and 140 keV) using FBP, 50% and 100% ASIR-V, DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) settings. The noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d') were computed and compared among reconstructions. RESULTS: NPS area and noise increased as keV decreased, with DLIR having slower increase than FBP and ASIR-V, and DLIR-H having the lowest values. DLIR had the best 40 keV/140 keV noise ratio at various energy levels, DLIR showed higher TTF (50%) than ASIR-V for all materials, especially for the soft tissue-like polystyrene insert, and DLIR-M and DLIR-H provided higher d' than DLIR-L, ASIR-V and FBP in all dose and energy levels. As keV increases, d' increased for acrylic insert, and d' of the 50 keV DLIR-M and DLIR-H images at 3.5 mGy (7.39 and 8.79, respectively) were higher than that (7.20) of the 50 keV ASIR-V50% images at 10 mGy. CONCLUSIONS: DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.

Effects of exercise on muscle fiber conversion, muscle development and meat quality of Sunit sheep.

This study aimed to investigate the effects of exercise on muscle fiber conversion, muscle development and meat quality in the biceps femoris (BF) muscle of Sunit sheep. Twelve Sunit sheep with similar body weight were divided into two groups: control group (C group) and exercise group (E group), E group lambs underwent 6 km of exercise training per day for 90 d. The findings revealed that compared with the C group, exercise training enhanced the expression of MyHC IIa mRNA, decreased the number ratio of type IIB muscle fibers and the expression of MyHC IIb mRNA (P < 0.05). Furthermore, the E group lamb displayed higher creatine kinase (CK) activity, and lactic acid levels (P < 0.05), while glycogen content and lactic dehydrogenase (LDH) activity showed opposite trends (P < 0.05). Exercise significantly up-regulated the mRNA expression of AMP-activated protein kinase α1 (AMPKα1), sirtuin1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1-α (PGC-1α), cytochrome c oxidase IV (COX IV), protein kinase B (Akt), mammalian target of rapamycin (mTOR) and p70 Ribosomal S6 Kinase 1 (p70s6k1) (P < 0.05), suggesting exercise promoted muscle fiber conversion by mediating AMPK/PGC-1α pathway, and improved skeletal muscle development via Akt/mTOR pathway. Besides, backfat thickness and pH45min value in the E group decreased significantly, while the pH24, a*, and shear force value increased significantly (P < 0.05). To conclude, this study suggested that exercise training can be used to alter muscle fiber characteristics and muscle development in lamb production.

Conditional survival analysis and dynamic survival prediction for intracranial solitary-fibrous tumor/hemangiopericytoma.

BACKGROUND: As the form of World Health Organization Central Nervous System (WHO CNS) tumor classifications is updated, there is a lack of research on outcomes for intracranial combined solitary-fibrous tumor and hemangiopericytoma (SFT/HPC). This study aimed to explore conditional survival (CS) pattern and develop a survival prediction tool for intracranial SFT/HPC patients. METHODS: Data of intracranial SFT/HPC patients was gathered from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. The patients were split into training and validation groups at a 7:3 ratio for our analysis. CS is defined as the likelihood of surviving for a specified period of time (y years), given that the patient has survived x years after initial diagnosis. Then, we used this definition of CS to analyze the intracranial SFT/HPC patients. The least absolute shrinkage and selection operator (LASSO) regression and best subset regression (BSR) were employed to identify predictive factors. The Multivariate Cox regression analysis was applied to establish a novel CS-based nomogram, and a risk stratification system was developed using this model. RESULTS: From the SEER database, 401 patients who were diagnosed with intracranial SFT/HPC between 2000 and 2019 were identified. Among them, 280 were included in the training group and 121 were included in the internal validation group for analysis. Our study revealed that in intracranial SFT/HPC, 5-year survival rates saw significant improvement ranging from 78% at initial diagnosis to rates of 83%, 87%, 90%, and 95% with each successive year after surviving for 1-4 years. The LASSO regression and BSR identified patient age, tumor behavior, surgery and radiotherapy as predictors of CS-based nomogram development. A risk stratification system was also successfully constructed to facilitate the identification of high-risk patients. CONCLUSION: The CS pattern of intracranial SFT/HPC patients was outlined, revealing a notable improvement in 5-year survival rates after an added period of survival. Our newly-established CS-based nomogram and risk stratification system can provide a real-time dynamic survival estimation and facilitate the identification of high-risk patients, allowing clinicians to better guide treatment decision for these patients.