Intraductal papillary mucinous neoplasm of the bile duct with choledochoduodenal fistula: a case report and literature review.

Background: Intraductal papillary mucinous neoplasm of the bile duct (IPMN-B) is a neoplastic disease of the bile duct with papillary hyperplasia and mucus secretion, which originates from the duct epithelium and rarely complicates with fistula formation. Case Description: The patient was admitted to the hospital due to abdominal pain and yellow skin. Laboratory results showed alanine aminotransferase 299 U/L, total bilirubin 350 µmol/L, computerized tomography showed severe dilatation of common bile duct and extrahepatic bile duct. Magnetic resonance cholangiopancreatography showed the intra- and extrahepatic bile ducts were markedly dilated, and the signal of the bile ducts was uneven. Endoscope identified a large amount of mucus above the papilla that flowing out from the fistula. Further cholangiography through the fistula showed significant dilatation of the extrahepatic bile duct. SpyGlass examination showed a large amount of gelatinous mucus in the bile duct lumen and "fish-scaly or coral" changes in the mucosa of the right anterior branch bile duct, hepatic hilum as well as lower common bile duct. IPMN-B with choledochoduodenal fistula was diagnosed. The patient was then discharged with nasal biliary drainage and biliary stenting, oral antipyretic and hepatoprotective drugs. The patient's biliary obstruction and symptoms of infection improved with medical treatment but recured. Unfortunately, the patient died 10 months after his first visit. Conclusions: SpyGlass has advantages in identifying the nature and extent of lesions, providing important references for diagnosis and treatment. Endoscopic intervention relieves biliary obstruction to some extent in patients with high operative risk or reluctance to undergo surgery.

Temperature Measurement Timings and the Fever Detection Rate After Gastrointestinal Surgery: Retrospective Cross-Sectional Study.

BACKGROUND: Postoperative fever frequently indicates surgical complications and is commonly used to evaluate the efficacy of interventions against surgical stress. However, the presence of circadian rhythms in body temperature may compromise the accurate detection of fever. OBJECTIVE: This study aimed to investigate the detection rate of fever under intermittent measurement. METHODS: We retrospectively reviewed the clinical records of patients who underwent nonemergency gastrointestinal surgery between November 2020 and April 2021. Patients' temperature data were continuously collected every 4 seconds using a wireless axillary thermometer, and fever was defined as a temperature exceeding 38 °C within a day. To simulate intermittent measurement in clinical practice, the body temperature at each hour was selected from the continuously collected temperature dataset. Considering that temperatures are measured multiple times per day, all possible measurement plans using intermittent measurement were composed by combining 1-24 time points from the 24-hour daily cycle. Fever was clinically diagnosed based on the temperature readings at the selected time points per day. The fever detection rates for each plan, with varying measurement times, were listed and ranked. RESULTS: Based on the temperature data continuously collected by the thermometer, fever occurred in 60 (40.8%) of the 147 included patients within 3 days after surgery. Of the measurement plans that included 1-24 measurements daily, the fever detection rates ranged from 3.3% (2/60) to 85% (51/60). The highest detection rates and corresponding timings for measurement plans with 1, 2, 3, and 4 measurements daily were 38.3% (23/60; at 8 PM), 56.7% (34/60; at 3 AM and 7 or 8 PM), 65% (39/60; at 3 AM, 8 PM, and 10 or 11 PM), and 70% (42/60; at 12 AM, 3 AM, 8 PM, and 11 PM), respectively; and the lowest detection rates were 3.3% (2/60), 6.7% (4/60), 6.7% (4/60), and 8.3% (5/60), respectively. Although fever within 3 days after surgery was not correlated with an increased incidence of postoperative complications (5/60, 8.3% vs 6/87, 6.9%; P=.76), it was correlated with a longer hospital stay (median 7, IQR 6-9 days vs median 6, IQR 5-7 days; P<.001). CONCLUSIONS: The fever detection rate of the intermittent approach is determined by the timing and frequency of measurement. Measuring at randomly selected time points can miss many fever events after gastrointestinal surgery. However, we can improve the fever detection rate by optimizing the timing and frequency of measurement.

Antimicrobial Isochroman-Derived Atropo-diastereomeric Dimers from Penicillium steckii SCISO 41228.

A pair of unidentified atropisomeric dimers, penicisteckins G (1) and H (2), and twelve known compounds (3-16) were isolated from the marine coral-derived fungus Penicillium steckii SCISO41228. Their structures including the absolute configuration were determined by HR-ESI-MS, ECD, 1D-, and 2D-NMR spectra. Compounds 1 and 2 exhibited potent antibacterial activity against most pathogenic strains, especially for MASA and Micrococcus luteus, with MIC values of 4.0 µg·mL-1. In addition, compounds 2 and 3 exhibit potent antioxidant activity with IC50 values of 10.76 and 8.66 µg·mL-1, respectively.

Expert Consensus on Big Data Collection of Skin and Appendage Disease Phenotypes in Chinese.

The collection of big data on skin and appendage phenotypes has revolutionized the field of personalized diagnosis and treatment by enabling the evaluation of individual characteristics and early detection of abnormalities. To establish a standardized system for collecting and measuring big data on phenotypes, a systematic categorization of measurement entries has been undertaken, accompanied by recommendations on measurement entries, environmental equipment requirements, and collection processes, tailored to the needs of different usage scenarios. Specific collection sites have also been recommended based on different index characteristics. A multi-center, multi-regional collaboration has been initiated to collect big date on phenotypes of healthy and diseased skin in the Chinese population. This data will be correlated with patient disease information, exploring the factors influencing skin phenotype, analyzing the phenotypic data features that can predict prognosis, and ultimately promoting the exploration of the pathophysiology and pathogenesis of skin diseases and therapeutic approaches. Non-invasive skin measurement robots are also in development. This consensus aims to provide a reference for the study of phenomics and the standardization of phenotypic measurements of skin and appendages in China.

Efficacy of Azvudine Therapy in Patients with Severe and Non-Severe COVID-19: A Propensity Score-Matched Analysis.

Objective: Azvudine is used to treat patients with the coronavirus disease 2019 (COVID-19). This study evaluated the clinical efficacy of azvudine in hospitalized patients with different severities of COVID-19 because few studies have described this in patients with severe and non-severe COVID-19. Methods: This retrospective study included hospitalized patients with COVID-19 in Guizhou Provincial People's Hospital between December 2022 and January 2023. Azvudine-treated patients and controls were matched for sex, age, and disease severity at admission. Laboratory results and outcomes, including all-cause mortality, invasive mechanical ventilation, intensive care unit admission, and hospital stay length, were evaluated. Stratified analysis was used to explore the difference in the efficacy of azvudine in severe and non-severe COVID-19 patients. Results: No significant differences in all-cause mortality were observed between the 303 azvudine recipients and 303 matched controls. However, azvudine-treated patients had shorter hospital stays (8.34±4.79 vs 9.17±6.25 days, P=0.046) and higher lymphocyte improvement rates (21.5% vs 13.9%, P=0.019), with a more pronounced effect in patients with non-severe COVID-19 (length of hospital stay, 8.07±4.35 vs 10.00±6.29 days, P=0.001; lymphocyte improvement rate, 23.8% vs 12.8%, P=0.015). Conclusion: Azvudine treatment shortens hospital stay length and increases the rate of lymphocyte count improvement in patients with non-severe COVID-19, suggesting that azvudine may be a treatment option for these patients.

A Comparative Study of Traditional and Computer-aided Surgical Simulation Guides in Orthognathic Correction of Bimaxillary Protrusion.

OBJECTIVE: To compare the efficacy of traditional occlusal guides with computer-aided surgical simulation (CASS) guides in enhancing postoperative outcomes for patients with bimaxillary protrusion. METHODS: This retrospective study evaluated 34 patients undergoing anterior maxillary and mandibular subapical osteotomy at the Plastic Surgery Hospital of the Chinese Academy of Medical Sciences. Fourteen patients were treated using traditional occlusal guides, whereas 20 patients were treated with CASS guides (median age 28.6 years, median follow-up 259 days). Pre and postoperative cephalometric indicators were measured using cephalometric software. Data analysis was conducted using SPSS 14.0, with significant differences determined at P < 0.05. RESULTS: All 34 patients experienced primary healing without complications. Follow-up indicated significant improvements in key cephalometric measurements in the CASS group compared with the traditional group, including mandibular position (SNB angle, P < 0.001), jaw relationship (ANB angle, P < 0.001), facial angle (FH-NPo, P = 0.002), and condyle-to-sella distance (Co-S, P = 0.024). The CASS group also showed better aesthetic outcomes, with significant reductions in overjet (P = 0.012), overbite (P = 0.001), and improved alignment of upper and lower incisors (U1-L1 angle, P = 0.031). CONCLUSION: CASS-guided surgery offers a superior alternative to traditional methods for treating bimaxillary protrusion, providing more precise and aesthetically pleasing results. This study highlights the significant advantages of using advanced digital simulation and 3-dimensional printing technologies in orthognathic surgery.

RNALocate v3.0: Advancing the Repository of RNA Subcellular Localization with Dynamic Analysis and Prediction.

Subcellular localization of RNA is a crucial mechanism for regulating diverse biological processes within cells. Dynamic RNA subcellular localizations are essential for maintaining cellular homeostasis; however, their distribution and changes during development and differentiation remain largely unexplored. To elucidate the dynamic patterns of RNA distribution within cells, we have upgraded RNALocate to version 3.0, a repository for RNA-subcellular localization (http://www.rnalocate.org/ or http://www.rna-society.org/rnalocate/). RNALocate v3.0 incorporates and analyzes RNA subcellular localization sequencing data from over 850 samples, with a specific focus on the dynamic changes in subcellular localizations under various conditions. The species coverage has also been expanded to encompass mammals, non-mammals, plants and microbes. Additionally, we provide an integrated prediction algorithm for the subcellular localization of seven RNA types across eleven subcellular compartments, utilizing convolutional neural networks (CNNs) and transformer models. Overall, RNALocate v3.0 contains a total of 1 844 013 RNA-localization entries covering 26 RNA types, 242 species and 177 subcellular localizations. It serves as a comprehensive and readily accessible data resource for RNA-subcellular localization, facilitating the elucidation of cellular function and disease pathogenesis.

Dynamic Graph Regularized Broad Learning With Marginal Fisher Representation for Noisy Data Classification.

Broad learning system (BLS) is an effective neural network requiring no deep architecture, however it is somehow fragile to noisy data. The previous robust broad models directly map features from the raw data, which inevitably learn useless or even harmful features for data representation when the inputs are corrupted by noise and outliers. To address this concern, a discriminative and robust network named as dynamic graph regularized broad learning (DGBL) with marginal fisher representation is proposed for noisy data classification. Different from the previous works, DGBL eliminates the effect of noise before the random feature mapping by the proposed robust and dynamic marginal fisher analysis (RDMFA) algorithm. The RDMFA is able to extract more robust and informative representations for classification from the latent clean data space with dynamically generated graphs. Furthermore, the dynamic graphs learned from RDMFA are incorporated as regularization terms into the objective of DGBL to enhance the discrimination capacity of the proposed network. Extensive quantitative and qualitative experiments conducted on numerous benchmark datasets demonstrate the superiority of the proposed model compared to several state-of-the-art methods.

A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and its potential to assist radiologists in diagnosis. METHODS: Two medical centers retrospectively recruited 535 node-positive breast cancer patients who had undergone NAC. Center 1 included 288 patients in the training cohort and 123 patients in the internal validation cohort, while center 2 enrolled 124 patients for the external validation cohort. Five DL models (ResNet 34, ResNet 50, VGG19, GoogLeNet, and DenseNet 121) were trained on pre- and post-NAC US images, and the best model was chosen. A US-based DL nomogram was constructed using DL predictive probabilities and clinicopathological characteristics. Furthermore, the performances of radiologists were compared with and without the assistance of the nomogram. RESULT: ResNet 50 performed best among all DL models, achieving areas under the curve (AUCs) of 0.837 and 0.850 in the internal and external validation cohorts, respectively. The US-based DL nomogram demonstrated strong predictive ability for ALN status post-NAC, with AUCs of 0.890 and 0.870 in the internal and external validation cohorts, respectively, outperforming both the clinical model and the DL model (p all < 0.05, except p = 0.19 for DL model in external validation cohort). Moreover, the nomogram significantly improved radiologists' diagnostic ability. CONCLUSION: The US-based DL nomogram is promising for predicting ALN status post-NAC and could assist radiologists for better diagnostic performance.

Inhibition of Ubiquitin C-Terminal Hydrolase L1 Facilitates Cutaneous Wound Healing via Activating TGF-ß/Smad Signalling Pathway in Fibroblasts.

Ubiquitin C-terminal hydrolase L1 (UCHL1) plays vital roles in cell proliferation, angiogenesis, inflammation and oxidative stress. Nevertheless, it is unclear whether UCHL1 could regulate the biologic behaviour of cells and ultimately influences wound healing. We aim to illustrate the roles and the underlying mechanism of UCHL1 in cutaneous wound healing. Murine full-thickness excisional wound model was utilised to study the effects of UCHL1 on wound healing through topical administration of the UCHL1 inhibitor LDN57444, followed by assessment of wound areas and histological alterations. Subsequently, ethynyldeoxyuridine, scratch and transwell assays were performed to examine fibroblast migration and proliferation. The extracellular matrix (ECM)-related genes expression and transforming growth factor-ß (TGF-ß)/Smad signalling pathways activation were investigated by immuno-fluorescent staining, Western blots and quantitative reverse transcription polymerase chain reaction. We identified elevated UCHL1 expression in non-healing wound tissues. The UCHL1 expression displayed a dynamic change and reached a peak on Day-7 post-wounding during the healing process in mice. Cutaneous administration of LDN57444 promoted wound healing by facilitating collagen deposition, myofibroblast activation and angiogenesis. In vitro experiments demonstrated that UCHL1 concentration dependently inhibited migration, ECM synthesis and activation of human dermal fibroblasts, which was mechanistically related to downregulation of TGF-ß/Smad signalling. Furthermore, these effects could be reversed by TGF-ß inhibitor SB431542. Our findings reveal that UCHL1 is a negative regulator of cutaneous wound healing and considered as a novel prospective therapeutic target for effective wound healing.

Superior metabolic improvement of polycystic ovary syndrome traits after GLP1-based multi-agonist therapy.

Polycystic ovary syndrome (PCOS) is a heterogeneous condition, defined by oligo-/anovulation, hyper-androgenism and/or polycystic ovaries. Metabolic complications are common in patients suffering PCOS, including obesity, insulin resistance and type-2 diabetes, which severely compromise the clinical course of affected women. Yet, therapeutic options remain mostly symptomatic and of limited efficacy for the metabolic and reproductive alterations of PCOS. We report here the hormonal, metabolic and gonadal responses to the glucagon-like peptide-1 (GLP1)-based multi-agonists, GLP1/Estrogen (GLP1/E), GLP1/gastric inhibitory peptide (GLP1/GIP) and GLP1/GIP/Glucagon, in two mouse PCOS models, with variable penetrance of metabolic and reproductive traits, and their comparison with metformin. Our data illustrate the superior efficacy of GLP1/E vs. other multi-agonists and metformin in the management of metabolic complications of PCOS; GLP1/E ameliorates also ovarian cyclicity in an ovulatory model of PCOS, without direct estrogenic uterotrophic effects. In keeping with GLP1-mediated brain targeting, quantitative proteomics reveals changes in common and distinct hypothalamic pathways in response to GLP1/E between the two PCOS models, as basis for differential efficiency. Altogether, our data set the basis for the use of GLP1-based multi-agonists, and particularly GLP1/E, in the personalized management of PCOS.

Different FeS Concentrations for Encapsulating ZIF-67 Nanomaterials toward the Enhanced Oxidation Evolution Reaction.

Due to the slow kinetic nature of the oxygen evolution reaction (OER), the development of electrocatalysts with high efficiency, stability, and economy for oxygen production using metal-organic framework (MOF) materials is still a challenging research topic. In this work, we chose the different concentrations of FeS adsorption to encapsulate metal cobalt-based ZIF-67 MOF for preparing a series of electrocatalysts (ZIF1FeSx, x = 0.2, 0.5, 0.75, and 1), which were mainly explored for the electrocatalytic OER. Among them, ZIF1FeS0.5 has excellent electrocatalytic activity for OER, which can be driven by low overpotentials of 276 and 349 mV at 10 and 50 mA cm-2 current densities, and more than 92% of the initial overpotential can be maintained after 100 h of continuous OER at 10 mA cm-2 current density. This is mainly due to the electronic interactions between the cobalt-based MOF and the FeS, which shift the electronic state of the active metal center to a higher valence state for increasing the number of active sites and enhancing the efficiency of electron transfer to facilitate the OER course. This work may contribute to the design of effective catalysts for the OER during the electrolysis of alkaline solutions.

DMSO-Catalyzed Double P-O Bond or Double P-S Bond Formations of Phosphinic Acids.

A DMSO-catalyzed double P-O bond or double P-S bond formation of phosphinic acid with an O- or S-containing nucleophile has been developed. Under metal-free and mild conditions, this simple procedure provides a compatible and rapid access to a variety of phosphonates and dithiophosphates. The DFT calculation of stabilization energy (SE) and the mechanism studies demonstrated that the "just right" Lewis base property and the relatively "soft" interaction strength with the phosphenium-dication ensure the unique catalytic activity of DMSO in this transformation.

Gold-antibody-aptamer complexed electrochemical sensing surface for septic arthritis biomarker determination.

Septic arthritis (SA) is more severe in patients with rheumatoid arthritis, joint surgical issues, or a weakened immune system. Timely diagnosis of SA is crucial for effective treatment. Traditional diagnostic methods such as ELISA, white blood cell counting, blood culture, qPCR, and imaging techniques are often less accurate and time-consuming. Researchers are focusing on developing highly sensitive biosensors for SA using blood-based biomarkers. Procalcitonin is a protein and a well-established biomarker for SA. This research focuses on developing a procalcitonin interdigitated electrode (IDE) biosensor using a probe made of an aptamer and antibody-modified gold nanoparticle (AuNP) complex. The probe was attached to the IDE through an amine linker and then interacted with procalcitonin. AuNPs increased the attachment of the aptamer and antibody to the IDE, enabling the detection of procalcitonin at levels as low as 10 ng/mL, with a linear regression curve ranging from 10 to 100 ng/mL [y = 4.0691x - 2.1887; R2 = 0.9937]. Furthermore, procalcitonin-spiked serum elevated the current level with increasing procalcitonin concentrations, while control performances did not enhance the current, indicating the selective and specific detection of procalcitonin. This AuNP-aptamer-antibody complexed biosensor effectively identifies procalcitonin at low levels and aids in the diagnosis of SA.

Accelerated Proton-Coupled Electron Transfer via Engineering Palladium Sub-Nanoclusters for Scalable Electrosynthesis of Hydrogen Peroxide.

Electrosynthesis of H2O2 from oxygen reduction reaction via a two-electron pathway is vital as an alternative for the energy-intensive anthraquinone process. However, this process is largely hindered in neutral and alkaline conditions due to sluggish kinetics associated with the transformation of intermediate O2* into OOH* via proton-coupled electron transfer sourced from slow water dissociation. Herein, we developed Pd sub-nanoclusters on the nickel ditelluride nanosheets (Pd SNCs/NiTe2) to enhance the performance of H2O2 electrosynthesis. The newly-developed Pd SNCs/NiTe2 exhibited a H2O2 selectivity of as high as 99% and a positive shift of onset potential up to 0.81 V. Combined theoretical calculations and experimental studies (e.g., X-ray absorption and attenuated total reflectance-Fourier transform infrared spectra measurements) revealed that the Pd sub-nanoclusters supported by NiTe2 nanosheets efficiently reduced the energy barrier of water dissociation to generate more protons, facilitating the proton feeding kinetics. When used in a flow cell, Pd SNCs/NiTe2 cathode efficiently produced H2O2 with a maximum yield rate of 1.75 mmol h-1 cm-2 and current efficiency of 95% at 100 mA cm-2. Further, an accumulated H2O2 concentration of 1.43 mol L-1 was reached after 10 hours of continuous electrolysis, showing the potential for practical H2O2 electrosynthesis.

Phosphorylated vimentin-triggered fibronectin matrix disaggregation enhances the dissemination of Treponema pallidum subsp. pallidum across the microvascular endothelial barrier.

Fibronectin (FN) is an essential component of the extracellular matrix (ECM) that protects the integrity of the microvascular endothelial barrier (MEB). However, Treponema pallidum subsp. pallidum (Tp) breaches this barrier through elusive mechanisms and rapidly disseminates throughout the host. We aimed to understand the impact of Tp on the surrounding FN matrix of MEB and the underlying mechanisms of this effect. In this study, immunofluorescence assays (IF) were conducted to assess the integrity of the FN matrix surrounding human microvascular endothelial cell-1 (HMEC-1) with/without Tp co-culture, revealing that only live Tp exhibited the capability to mediate FN matrix disaggregation in HMEC-1. Western blotting and IF were employed to determine the protein levels associated with the FN matrix during Tp infection, which showed the unaltered protein levels of total FN and its receptor integrin α5ß1, along with reduced insoluble FN and increased soluble FN. Simultaneously, the integrin α5ß1-binding protein-intracellular vimentin maintained a stable total protein level while exhibiting an increase in the soluble form, specifically mediated by the phosphorylation of its 39th residue (pSer39-vimentin). Besides, this process of vimentin phosphorylation, which could be hindered by a serine-to-alanine mutation or inhibition of phosphorylated-AKT1 (pAKT1), promoted intracellular vimentin rearrangement and FN matrix disaggregation. Moreover, within the introduction of additional cellular FN rather than other Tp-adhered ECM protein, in vitro endothelial barrier traversal experiment and in vivo syphilitic infectivity test demonstrated that viable Tp was effectively prevented from penetrating the in vitro MEB or disseminating in Tp-challenged rabbits. This investigation revealed the active pAKT1/pSer39-vimentin signal triggered by live Tp to expedite the disaggregation of the FN matrix and highlighted the importance of FN matrix stability in syphilis, thereby providing a novel perspective on ECM disruption mechanisms that facilitate Tp dissemination across the MEB.

QSOX1 exerts anti-inflammatory effects in sepsis-induced acute lung injury: Regulation involving EGFR phosphorylation mediated M1 polarization of macrophages.

Sepsis is a systemic inflammatory response caused by an infection, which can easily lead to acute lung injury. Quiescin Q6 sulfhydryl oxidase 1 (QSOX1) is a sulfhydryl oxidase involved in oxidative stress and the inflammatory response. However, there are few reports on the role of QSOX1 in sepsis-induced acute lung injury (SALI). In this study, mice model of SALI was constructed by intraperitoneal injection with lipopolysaccharide (LPS). The increased inflammatory response and lactate dehydrogenase activity in bronchoalveolar lavage fluid (BALF) indicated successful modeling. Increased QSOX1 expression was both observed in lung tissues and lung macrophages of sepsis mice accompanied by increased polarization of M1-type macrophages. To explore the role of QSOX1 in the SALI, lentivirus containing QSOX1-specific overexpression or knockdown vectors were used to change QSOX1 expression in LPS-treated RAW264.7 cells. QSOX1 suppressed LPS-induced M1 polarization and further inhibited inflammatory response in RAW264.7 cells. Interestingly, the phosphorylation of epidermal growth factor receptor (EGFR), the promoter of M1 polarization in macrophages, was found to be downregulated upon QSOX1 overexpression in RAW264.7 cells. Mechanically, the binding of QSOX1 to EGFR protein promoted EGFR ubiquitination and degradation, thereby down-regulating EGFR phosphorylation. Moreover, inhibiting EGFR expression or its phosphorylation restored the impact of QSOX1 silencing on M1 polarization and inflammation in the LPS-treated RAW264.7 cells. In summary, QSOX1 may exert anti-inflammatory effects in SALI by inhibiting EGFR phosphorylation-mediated M1 macrophage polarization. This presented a potential target for the treatment and prevention of SALI.

Low-dose CT image super-resolution with noise suppression based on prior degradation estimator and self-guidance mechanism.

The anatomies in low-dose computer tomography (LDCT) are usually distorted during the zooming-in observation process due to the small amount of quantum. Super-resolution (SR) methods have been proposed to enhance qualities of LDCT images as post-processing approaches without increasing radiation damage to patients, but suffered from incorrect prediction of degradation information and incomplete leverage of internal connections within the 3D CT volume, resulting in the imbalance between noise removal and detail sharpening in the super-resolution results. In this paper, we propose a novel LDCT SR network where the degradation information self-parsed from the LDCT slice and the 3D anatomical information captured from the LDCT volume are integrated to guide the backbone network. The prior degradation estimator (PDE) is proposed following the contrastive learning strategy to estimate the degradation features in the LDCT images without paired low-normal dose CT images. The self-guidance fusion module (SGFM) is designed to capture anatomical features with internal 3D consistencies between the squashed images along the coronal, sagittal, and axial views of the CT volume. Finally, the features representing degradation and anatomical structures are integrated to recover the CT images with higher resolutions. We apply the proposed method to the 2016 NIH-AAPM Mayo Clinic LDCT Grand Challenge dataset and our collected LDCT dataset to evaluate its ability to recover LDCT images. Experimental results illustrate the superiority of our network concerning quantitative metrics and qualitative observations, demonstrating its potential in recovering detail-sharp and noise-free CT images with higher resolutions from the practical LDCT images.