Evaluation of modified clear Twin Block aligner in treating adolescents with skeletal class II malocclusion: A two-centre cephalometric study.

INTRODUCTION: The purpose of this study was to evaluate the therapeutic effect of modified clear Twin Block (CTB) aligner and traditional twin block (TB) appliance from skeletal, dentoalveolar and soft tissue changes in adolescents with skeletal class II malocclusion. METHODS: A total of 80 adolescents, included in this study from two medical centres, were distributed into CTB group, TB group and control group based on the treatment they received. Lateral cephalograms at pre-treatment (T1) and post-treatment (T2) were measured by modified Pancherz's cephalometric analysis, and dentoskeletal and soft tissue changes were analysed by independent-sample t-test, paired-sample t-test, ANOVA test and Scheffe's Post Hoc test. RESULTS: Seventy-five adolescents completed the study, including 32 in the CTB group, 32 in the TB group and 11 in the control group. Both CTB and TB treatment showed significant differences in most dentoskeletal and soft tissue measurements. Compared with the control group, improvements were observed in class II molar relationship through significant different in S Vert/Ms-S Vert/Mi in the CTB group (P < .01) and the TB group (P < .001), as well as deep overjet through significant different in S Vert/Is-S Vert/Ii in the CTB group (P < .001) and the TB group (P < .001). Besides, the CTB group also showed less protrusion of lower incisors and resulted in a more significant improvement in profile with fewer adverse effects on speaking, eating and social activities. CONCLUSIONS: For adolescents with skeletal class II malocclusion, CTB appliance was as effective as TB on improving dentoskeletal and soft tissue measurements, featuring more reliable teeth control and patient acceptance.

Identification of lymph node adulteration in minced pork by comprehensive metabolomics and lipidomics approach based on UPLC/LTQ-Orbitrap MS.

The deliberate pork adulteration with lymph nodes is a common adulteration phenomenon, and it poses a serious threat to public health and food safety. An untargeted metabolomics and lipidomics approach based on ultrahigh performance liquid chromatography coupled with linear ion trap quadrupole-Orbitrap high resolution mass spectrometry (MS) was used to distinguish lymph nodes from minced pork. The principal component analysis and orthogonal projection to latent structures discriminant analysis models were established with the good of fitness and predictivity. The results showed that there were significant differences in metabolites and lipids between lymph nodes and pork. A total of 16 significantly differentiated metabolites were identified, of which 1-palmitoylglycerophosphocholine, 12,13-dihydroxy-9-octadecenoic acid, and prostaglandin E2 (PGE2) were positively correlated with lymph node content and were identified as potential markers of lymph nodes. These three markers were combined to create a binary logistic regression model, and a combined-factor exceeding 0.75 was ultimately identified as a marker for pork adulteration with lymph nodes. The desorption electrospray ionization-MS images showed that PGE2 had a higher relative abundance in the lymph node region than in adjacent non-lymph node regions, indicating that PGE2 was a marker that contributed significantly for identifying lymph nodes adulteration into pork. Our results provide a theoretical basis for identifying lymph node adulteration, which will contribute to combating fraud in the meat industry.

Anti-DNA antibody-targeted D-peptide nanoparticles ameliorate lupus nephritis in MRL/lpr mice.

Peptide ALW (ALWPPNLHAWVP) targeting anti-dsDNA antibodies has shown promising therapeutic effects in alleviating lupus nephritis, but is potentially limited by poor stability and non-kidney targeting. We recently developed a D-form modified ALW, called D-ALW, which has the capacity to widely inhibit pathogenic polyclonal anti-dsDNA antibody reactions. Further modification of D-ALW using PEG-PLGA nanoparticles to enhance good kidney-targeting ability and extend half-life. Here, we demonstrate that the D-form modified ALW maintains higher binding and inhibition efficiencies and achieves higher stability. Most importantly, D-ALW nanoparticles exhibit excellent kidney-targeting ability and prolong the half-life of the peptides in BALB/c mice. Additionally, compared to D-ALW, D-ALW nanoparticles significantly reduce the glomerular deposition of IgG and C3, improve renal histopathologies, such as glomerular proliferation and inflammatory cells infiltration, and markedly prolong lifespan in MRL/lpr lupus-prone mice. Overall, these results establish that the D-ALW nanoparticles offer synergistic benefits in both safety and efficacy, providing long-term renal preservation and treatment advantages in lupus nephritis.

An Evaluation of Paddy Rice as an Alternative Energy Source in Protein-Restricted Diets for Growing, Early-Finishing, and Late-Finishing Pigs.

Three experiments were conducted to evaluate paddy rice as an alternative energy feedstuff in low-protein diets for pigs. In Experiment 1, a total of 400 growing pigs (20.68 ± 0.29 kg initial bodyweight), were randomly allocated four dietary treatments with 0, 10, 15, and 20% paddy rice for 30 days. Feeding 10% or 15% paddy rice had no adverse impacts on average daily gain (ADG) and feed to gain ratio (F:G), while the inclusion of 20% rice in diets significantly influenced the growth performance of pigs. In Experiment 2, 364 early-finishing pigs (42.25 ± 0.47 kg) were divided into four treatments with 0, 15, 20, and 25% paddy rice for 35 days. Feeding 15% or 20% paddy rice had no negative consequences on growth performance, while pigs fed with 25% rice had the lowest ADG and the greatest F:G. In Experiment 3, 364 late-finishing pigs (79.52 ± 1.28 kg) were divided into four treatments with 0, 20, 25, and 30% paddy rice for 60 days. Paddy rice can be included at up to 30% in diets without compromising growth performance, while feeding with 25% rice significantly improved the performance for pigs compared with the corn-fed control.

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). METHODS: In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. RESULTS: Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. CONCLUSION: DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. CLINICAL RELEVANCE STATEMENT: Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. KEY POINTS: • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.

OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs). METHODS: A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared. RESULTS: DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups. CONCLUSION: For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both. CLINICAL RELEVANCE STATEMENT: The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs. KEY POINTS: • DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. • DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. • On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.

Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.

OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: • The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. • Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. • The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.

Neuronal aerobic glycolysis exacerbates synapse loss in aging mice.

Brain consumes nearly 20% supply of energy from glucose metabolism by oxidative phosphorylation and aerobic glycolysis. Less active state of glycolytic enzymes results in a limited capacity of glycolysis in the neurons of adult brain. Here we identified that Warburg effect is enhanced in hippocampal neurons during aging. As hippocampal neurons age, lactate levels progressively increase. Notably, we observed upregulated protein levels of PFKFB3 in the hippocampus of 20-month-old mice compared to young mice, and this higher PFKFB3 expression correlated with declining memory performance in aging mice. Remarkably, in aging mice, knocking down Pfkfb3 in hippocampal neurons rescued cognitive decline and synapse loss. Conversely, Pfkfb3 overexpression in hippocampal neurons led to cognitive impairment and synapse elimination, associated with heightened glycolysis. In vitro experiments with cultured primary neurons confirmed that Pfkfb3 overexpression increased glycolysis and that glycolytic inhibition could prevent apoptotic competency in neurons. These findings underscore that glycolysis in hippocampal neurons could potentially be targeted as a therapeutic avenue to mitigate cognitive decline and preserve synaptic integrity during aging.

LncRNA MALAT1 knockdown inhibits the development of choroidal neovascularization.

In the pathogenesis of age-related macular degeneration, long non-coding RNAs have become important regulators. This study aimed to investigate the role of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in the progression of choroidal neovascularization (CNV) and the underlying mechanisms. The in vivo and in vitro model of CNV was established using laser-induced mouse CNV model and human choroidal vascular endothelial cells (HCVECs) exposed to hypoxia respectively. We explore the role of MALAT1 in the pathogenesis of CNV by using the small interference RNA both in vivo and in vitro. MALAT1 expression was found to be upregulated in the retinal pigment epithelial-choroidal complexes. MALAT1 knockdown inhibited CNV development and leakage in vivo and decreased HCVECs proliferation, migration, and tube formation in vitro. MALAT1 performed the task as a miR-17-5p sponge to regulate the expression of vascular endothelial growth factor A (VEGFA) and E26 transformation specific-1 (ETS1). This study provides a new perspective on the pathogenesis of CNV and suggests that the axis MALAT/miR-17-5p/VEGFA or ETS1 may be an effective therapeutic target for CNV.

An online preparative high-performance liquid chromatography system with enrichment and purification modes for the efficient and systematic separation of Panax notoginseng saponins.

In this study, an online preparative high-performance liquid chromatography (prep-HPLC) system based on the combination of the enrichment and purification modes for the efficient and systematic separation of Panax notoginseng saponins (PNS) was achieved. Five separation columns were used for the first and second separation of target components, eighteen trap columns were used to capture the effluents from the first separation or loading the trapped sample effluents, and a two-position eight-port valve was used to switch between the first and second separations. The conditions for the first and second separation of PNS were simulated and optimized with the online prep-HPLC system. Then, the PNS were separated using optimized chromatographic conditions. Notably, 14 monomer compounds with >90% purity (11 compounds with purity >97%) were simultaneously isolated from PNS using the above self-developed device, and their chemical structures were identified. Moreover, the separation time was less than 33.0 h. After 6 repeated enrichment and purification, the weight of each compound obtained was more than 5.0 mg, with compound 2 weighing over 900 mg. In brief, the self-developed prep-HPLC system, which integrated enrichment and purification, is suitable for the efficient and systematic separation of PNS and has broad application prospects, especially for the separation of complex chemical components in natural products.

LncRNA CCAT1 facilitates the progression of gastric cancer via PTBP1-mediated glycolysis enhancement.

BACKGROUND: Gastric cancer (GC) is one of the most prevalent malignant tumors of the digestive system. As a hallmark of cancer, energy-related metabolic reprogramming is manipulated by multiple factors, including long non-coding RNAs (lncRNAs). Notably, lncRNA CCAT1 has been identified as a crucial regulator in tumor progression. Nevertheless, the precise molecular mechanisms underlying the involvement of CCAT1 in metabolic reprogramming of GC remain unclear. METHODS: Gain- and loss-of-function experiments were performed to evaluate the roles of CCAT1 in tumorigenesis and glycolysis of GC. Bioinformatics analyses and mechanistic experiments, such as mass spectrometry (MS), RNA-pulldown, and RNA immunoprecipitation (RIP), were employed to reveal the potential interacting protein of CCAT1 and elucidate the regulatory mechanism of CCAT1 in GC glycolysis. Moreover, the nude mice xenograft assay was used to evaluate the effect of CCAT1 on GC cells in vivo. RESULTS: In this study, we identified that CCAT1 expression was significantly elevated in the tissues and plasma exosomes of GC patients, as well as GC cell lines. Functional experiments showed that the knockdown of CCAT1 resulted in a substantial decrease in the proliferation, migration and invasion of GC cells both in vitro and in vivo through decreasing the expression of glycolytic enzymes and glycolytic rate. Conversely, overexpression of CCAT1 exhibited contrasting effects. Mechanistically, CCAT1 interacted with PTBP1 and effectively maintained its stability by inhibiting the ubiquitin-mediated degradation process. As a critical splicing factor, PTBP1 facilitated the transition from PKM1 to PKM2, thereby augmenting the glycolytic activity of GC cells and ultimately fostering the progression of GC. CONCLUSIONS: Our findings demonstrate that CCAT1 plays a significant role in promoting the proliferation, migration, and invasion of GC cells through the PTBP1/PKM2/glycolysis pathway, thus suggesting CCAT1's potential as a biomarker and therapeutic target for GC.

Unraveling the aging dynamics in the simultaneous immobilization of soil metal(loid)s using oxides.

Immobilization represents the most extensively utilized technique for the remediation of soils contaminated by heavy metals and metalloids. However, it is crucial to acknowledge that contaminants are not removed during this process, thereby leaving room for potential mobilization over time. Currently, our comprehension of the temporal variations in immobilization efficacy, specifically in relation to amendments suitable for industrial sites, remains very limited. To address this knowledge gap, our research delved into the aging characteristics of diverse oxides, hydroxides, and hydroxy-oxides (collectively referred to as oxides) for the simultaneous immobilization of arsenic (As), cadmium (Cd), and antimony (Sb) in soils procured from 16 contaminated industrial sites. Our findings unveiled that Ca-oxides initially showed excellent immobilization performance for As and Sb within 7 days but experienced substantial mobilization by up to 71 and 13 times within 1 year, respectively. In contrast, the efficacy of Cd immobilization by Ca-oxides was enhanced with the passage of time. Fe- and Mg-oxides, which primarily operate through encapsulation or surface complexation, exhibited steady immobilization performances over time. This reliable and commendable immobilization effect was observed across distinct soils characterized by varying physicochemical properties, including pH, texture, CEC, TOC, and EC, underscoring the suitability of such amendments for immobilizing metal(loid)s in diverse soil types. MgO, in particular, displayed even superior immobilization performance over time, owing primarily to gradual hydration and physical entrapment effects. Remarkably, Mg-Al LDHs emerged as the most effective candidate for the simultaneous immobilization of As, Cd, and Sb. The results obtained from this study furnish valuable data for future investigations on the immobilization of metals and metalloids in industrial soils. They enable the projection of immobilization performance and offer practical guidance in selecting suitable amendments for the immobilization of metal(loid)s.

Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging.

Purpose: This study aimed to investigate the value of quantified extracellular volume fraction (fECV) derived from dual-energy CT (DECT) for predicting the survival outcomes of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE). Materials and methods: A total of 63 patients with HCC who underwent DECT before treatment were retrospectively included. Virtual monochromatic images (VMI) (70 keV) and iodine density images (IDI) during the equilibrium phase (EP) were generated. The tumor VMI-fECV and IDI-fECV were measured and calculated on the whole tumor (Whole) and maximum enhancement of the tumor (Maximum), respectively. Univariate and multivariate Cox models were used to evaluate the effects of clinical and imaging predictors on overall survival (OS) and progression-free survival (PFS). Results: The correlation between tumor VMI-fECV and IDI-fECV was strong (both p< 0.001). The Bland-Altman plot between VMI-fECV and IDI-fECV showed a bias of 5.16% for the Whole and 6.89% for the Maximum modalities, respectively. Increasing tumor VMI-fECV and IDI-fECV were positively related to the effects on OS and PFS (both p< 0.05). The tumor IDI-fECV-Maximum was the only congruent independent predictor in patients with HCC after TACE in the multivariate analysis on OS (p = 0.000) and PFS (p = 0.028). Patients with higher IDI-fECV-Maximum values had better survival rates above the optimal cutoff values, which were 35.42% for OS and 29.37% for PFS. Conclusion: The quantified fECV determined by the equilibrium-phase contrast-enhanced DECT can potentially predict the survival outcomes of patients with HCC following TACE treatment.

Selective polypeptide ligand binding to the extracellular surface of the transmembrane domains of the class B GPCRs GLP-1R and GCGR.

Crystal and cryo-EM structures of the glucagon-like peptide-1 receptor (GLP-1R) and glucagon receptor (GCGR) bound with their peptide ligands have been obtained with full-length constructs, indicating that the extracellular domain (ECD) is indispensable for specific ligand binding. This article complements these data with studies of ligand recognition of the two receptors in solution. Paramagnetic NMR relaxation enhancement measurements using dual labeling with fluorine-19 probes on the receptor and nitroxide spin labels on the peptide ligands provided new insights. The glucagon-like peptide-1 (GLP-1) was found to interact with GLP-1R by selective binding to the extracellular surface. The ligand selectivity toward the extracellular surface of the receptor was preserved in the transmembrane domain (TMD) devoid of the ECD. The dual labeling approach further provided evidence of cross-reactivity of GLP-1R and GCGR with glucagon and GLP-1, respectively, which is of interest in the context of medical treatments using combinations of the two polypeptides.

The NR_109/FUBP1/c-Myc axis regulates TAM polarization and remodels the tumor microenvironment to promote cancer development.

BACKGROUND: Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and exert an important role in tumor progression. Due to the heterogeneity and plasticity of TAMs, modulating the polarization states of TAMs is considered as a potential therapeutic strategy for tumors. Long noncoding RNAs (lncRNAs) have been implicated in various physiological and pathological processes, yet the underlying mechanism on how lncRNAs manipulate the polarization states of TAMs is still unclear and remains to be further investigated. METHODS: Microarray analyses were employed to characterize the lncRNA profile involved in THP-1-induced M0, M1 and M2-like macrophage. Among those differentially expressed lncRNAs, NR_109 was further studied, for its function in M2-like macrophage polarization and the effects of the condition medium or macrophages mediated by NR_109 on tumor proliferation, metastasis and TME remodeling both in vitro and in vivo. Moreover, we revealed how NR_109 interacted with far upstream element-binding protein 1 (FUBP1) to regulate the protein stability through hindering ubiquitination modification by competitively binding with JVT-1. Finally, we examined sections of tumor patients to probe the correlation among the expression of NR_109 and related proteins, showing the clinical significance of NR_109. RESULTS: We found that lncRNA NR_109 was highly expressed in M2-like macrophages. Knockdown NR_109 impeded IL-4 induced M2-like macrophage polarization and significantly reduced the activity of M2-like macrophages to support the proliferation and metastasis of tumor cells in vitro and in vivo. Mechanistically, NR_109 competed with JVT-1 to bind FUBP1 at its C-terminus domain, impeded the ubiquitin-mediated degradation of FUBP1, activated c-Myc transcription and thus promoted M2-like macrophages polarization. Meanwhile, as a transcription factor, c-Myc could bind to the promoter of NR_109 and enhance the transcription of NR_109. Clinically, high NR_109 expression was found in CD163+ TAMs from tumor tissues and was positively correlated with poor clinical stages of patients with gastric cancer and breast cancer. CONCLUSIONS: Our work revealed for the first time that NR_109 exerted a crucial role in regulating the phenotype-remodeling and function of M2-like macrophages via a NR_109/FUBP1/c-Myc positive feedback loop. Thus, NR_109 has great translational potentials in the diagnosis, prognosis and immunotherapy of cancer.

Radiotherapy for primary thyroid adenoid cystic carcinoma.

Primary thyroid adenoid cystic carcinoma (PTACC) is an extremely rare type of mucin-secreting adenocarcinoma. Currently, it is difficult to diagnose, and it lacks standard treatment protocols. We report the case of a 53-year-old female patient with PTACC who underwent additional intensity-modulated radiotherapy 1 month after surgical treatment with an uneventful course. No invasion or distant metastasis was detected at the 7-month follow-up after radiotherapy, and the prognosis was favorable. In this case, herein, we have summarized the diagnostic features of the disease and proposed that postoperative adjuvant radiotherapy can significantly improve the patient's prognosis. Finally, we further confirmed the important role of radiotherapy in PTACC by reviewing relevant literature, which may provide clinicians with valuable treatment experience.

Latent group detection in functional partially linear regression models.

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. We develop an algorithm in the spirit of the K-means clustering to identify latent groups of the subjects under study. We establish the consistency of the proposed estimator, derive the convergence rate and the asymptotic distribution, and develop inference procedures. We show by simulation studies that the proposed method has higher accuracy for recovering latent groups and for estimating the functional coefficients than existing methods. The analysis of the barley data shows that the proposed method can help identify groups of barley families with different salinity tolerant abilities.

Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR). METHODS: A contrast-detail phantom consisting of low-contrast objects was scanned at five CT dose index levels (10, 6, 3, 2, and 1 mGy). A total of 154 participants with 305 hepatic lesions who underwent abdominal CT were enrolled in a prospective non-inferiority trial with a three-arm design based on phantom results. Data sets with full dosage (13.6 mGy) and low dosages (9.5, 6.8, or 4.1 mGy) were acquired from two consecutive portal venous acquisitions, respectively. All images were reconstructed with FBP (reference), IR (control), and DLIR (test). Eleven readers evaluated phantom data sets for object detectability using a two-alternative forced-choice approach. Non-inferiority analyses were performed to interpret the differences in image quality and metastasis detection of low-dose DLIR relative to full-dose FBP/IR. RESULTS: The phantom experiment showed the dose reduction potential from DLIR was up to 57% based on the reference FBP dose index. Radiation decreases of 30% and 50% resulted in non-inferior image quality and hepatic metastasis detection with DLIR compared to full-dose FBP/IR. Radiation reduction of 70% by DLIR performed inferiorly in detecting small metastases (< 1 cm) compared to full-dose FBP (difference: -0.112; 95% confidence interval [CI]: -0.178 to 0.047) and full-dose IR (difference: -0.123; 95% CI: -0.182 to 0.053) (p < 0.001). CONCLUSION: DLIR enables a 50% dose reduction for detecting low-contrast hepatic metastases while maintaining comparable image quality to full-dose FBP and IR. KEY POINTS: • Non-inferiority study showed that deep learning image reconstruction (DLIR) can reduce the dose to oncological patients with low-contrast lesions without compromising the diagnostic information. • Radiation dose levels for DLIR can be reduced to 50% of full-dose FBP and IR for detecting low-contrast hepatic metastases, while maintaining comparable image quality. • The reduction of radiation by 70% by DLIR is clinically acceptable but insufficient for detecting small low-contrast hepatic metastases (< 1 cm).

Stimulated leaching of metalloids along 3D-printed fractured rock vadose zone.

Fractured rock aquifers are susceptible to contamination, with metal(loid)s rapidly migrating from poorly developed overburden to the fractured rock vadose zone and thus into groundwater. Compared to typical porous aquifers, retention effects within the rock matrix are small, and rapid advection along fractures leads to a higher risk of groundwater contamination. However, the highly complex anisotropic pathways of natural fractures hinder research in this field. To construct reproducible fractures, this study used 3D printing following Computed X-ray Microtomography (µCT) scans of a fractured rock collected in a natural limestone aquifer. Stimulated metalloid release was observed in the fractured rock during column leaching, and the leachate concentrations of arsenic (As) and antimony (Sb) increased by up to 17.5 and 36.4 times, respectively, compared with the porous vadose zone. Fluctuations in fracture metalloid release patterns in dissolved and adsorbed phases were attributed to retention and filtration effects induced by soil particles within fractures. Geophysical properties of the porous overburden, especially the aggregation characteristics, greatly affected the non-equilibrium leaching behavior of As, but had a limited effect on the near-equilibrium leaching of Sb, which was explored by modifying the surficial soil layer with either montmorillonite clay or charcoal. The results of this study provide a novel method and useful information for modeling and risk assessment of fractured rock aquifers.