Data-driven rapid detection of Helicobacter pylori infection through machine learning with limited laboratory parameters in Chinese primary clinics.

Background: Helicobacter pylori (H. pylori) is a significant global health concern, posing a high risk for gastric cancer. Conventional diagnostic and screening approaches are inaccessible, invasive, inaccurate, time-consuming, and expensive in primary clinics. Objective: This study aims to apply machine learning (ML) models to detect H. pylori infection using limited laboratory parameters from routine blood tests and to investigate the association of these biomarkers with clinical outcomes in primary clinics. Methods: A retrospective analysis with three ML and five ensemble models was conducted on 1409 adults from Hubei Provincial Hospital of Traditional Chinese Medicine. evaluating twenty-three blood test parameters and using the C 14 urea breath test as the gold standard for diagnosing H. pylori infection. Results: In our comparative study employing three different feature selection strategies, Random Forest (RF) model exhibited superior performance over other ML and ensemble models. Multiple evaluation metrics underscored the optimal performance of the RF model (ROC = 0.951, sensitivity = 0.882, specificity = 0.906, F1 = 0.906, accuracy = 0.894, PPV = 0.908, NPV = 0.880) without feature selection. Key biomarkers identified through importance ranking and shapley additive Explanations (SHAP) analysis using the RF model without feature selection include White Blood Cell Count (WBC), Mean Platelet Volume (MPV), Hemoglobin (Hb), Red Blood Cell Count (RBC), Platelet Crit (PCT), and Platelet Count (PLC). These biomarkers were found to be significantly associated with the presence of H. pylori infection, reflecting the immune response and inflammation levels. Conclusion: Abnormalities in key biomarkers could prompt clinical workers to consider H. pylori infection. The RF model effectively identifies H. pylori infection using routine blood tests, offering potential for clinical application in primary clinics. This ML approach can enhance diagnosis and screening, reducing medical burdens and reliance on invasive diagnostics.

Independent and joint associations between urinary polycyclic aromatic hydrocarbon metabolites and cognitive function in older adults in the United States.

Background: Polycyclic aromatic hydrocarbons (PAHs), as organic pollutants widely present in daily environments, have been shown by existing epidemiological studies to be significantly associated with deficits in learning and memory functions in children and adults. However, the association between exposure to PAHs and cognitive function in older adults remains unclear. Additionally, existing related studies have only assessed the association between individual PAH exposures and cognitive assessments, overlooking the risks posed by mixed exposures. This study aims to use three statistical models to investigate the individual and overall effects of mixed PAH exposures on the cognition of older adults in the United States. Methods: The study cohort was obtained from the NHANES database, which included individuals aged 60 and older from 2011 to 2014. Weighted generalized linear models (GLM), weighted quantile sum (WQS) models, and Bayesian kernel machine regression (BKMR) models were utilized to evaluate the connections between urinary PAH metabolites and the standardized Z-scores of four cognitive tests: Immediate Recall Test (IRT), Delayed Recall Test (DRT), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). Results: Our analysis involved 899 individuals aged 60 and above. In the fully adjusted GLM, 2-hydroxynaphthalene (2-OHNa), 3-hydroxyfluorene (3-OHFlu), and 2-hydroxyfluorene (2-OHFlu) demonstrated negative associations with DSST Z-scores. In the WQS model, six urinary PAH metabolites were negatively linked to AFT Z-scores (ß (95% confidence intervals [CI]): -0.120 (-0.208, -0.033), p = 0.007) and DSST Z-scores (ß (95% CI): -0.182 (-0.262, -0.103), p < 0.001). In both assessments, 2-OHNa exerted the greatest influence among the urinary PAH metabolites. In the BKMR model, there was an overall negative correlation between urinary PAH metabolites and AFT and DSST Z-scores when the concentration was within the 25th to 75th percentile, where 2-OHNa dominated the main effect of the mixture. The WQS and BKMR models were adjusted for all covariates. Conclusion: Increased concentrations of urinary PAH metabolites are associated with cognitive decline in older adults, mainly on language ability, executive function, sustained attention, working memory, and information processing speed, with 2-OHNa playing a major effect.

Vanadium-Based Metal-Organic Frameworks with Peroxidase-like Activity as a Colorimetric Sensing Platform for Direct Detection of Organophosphorus Pesticides.

Colorimetry based on the bioenzyme inhibition strategy holds promising application prospects in the field of organophosphorus pesticide (OPs) detection. However, overcoming the challenges of the high cost and low stability of bioenzymes remains crucial. In this study, we successfully synthesized a peroxidase vanadium-based metal-organic framework (MOF) nanozyme named MIL-88B(V) and employed its mediated bioenzyme-free colorimetric strategy for direct OPs detection. The experimental results demonstrated that MIL-88B(V) exhibited a remarkable affinity and a remarkable catalytic rate. When the OPs target is added, it can be anchored on the MOF surface through a V-O-P bond, effectively inhibiting the MOF's activity. Subsequently, leveraging the advantages of smartphones such as convenience, speed, and sensitivity, we developed a paper sensor integrated into a smartphone for efficient OPs detection. The as-designed nanozyme-based colorimetric assay and paper sensor presented herein offer notable advantages, including affordability, speed, stability, wide adaptability, low cost, and accuracy in detecting OPs, thus providing a versatile and promising analytical approach for real sample analysis and allowing new applications of V-based MOF nanozymes.

Continual learning for seizure prediction via memory projection strategy.

Despite extensive algorithms for epilepsy prediction via machine learning, most models are tailored for offline scenarios and cannot handle actual scenarios where data changes over time. Catastrophic forgetting(CF) for learned electroencephalogram(EEG) data occurs when EEG changes dynamically in the clinical setting. This paper implements a continual learning(CL) strategy Memory Projection(MP) for epilepsy prediction, which can be combined with other algorithms to avoid CF. Such a strategy enables the model to learn EEG data from each patient in dynamic subspaces with weak correlation layer by layer to minimize interference and promote knowledge transfer. Regularization Loss Reconstruction Algorithm and Matrix Dimensionality Reduction Algorithm are introduced into the core of MP. Experimental results show that MP exhibits excellent performance and low forgetting rates in sequential learning of seizure prediction. The forgetting rate of accuracy and sensitivity under multiple experiments are below 5%. When learning from multi-center datasets, the forgetting rates for accuracy and sensitivity decrease to 0.65% and 1.86%, making it comparable to state-of-the-art CL strategies. Through ablation experiments, we have analyzed that MP can operate with minimal storage and computational cost, which demonstrates practical potential for seizure prediction in clinical scenarios.

Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits.

Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.

Enhancing the Humidity Stability of Perovskite Films through Interfacial Modification with Differentiated Hydrophilic Organics.

Preparing high-quality perovskite films is a decisive step toward realizing highly efficient and stable perovskite solar cells (Pero-SCs). Water is a key factor affecting the stability of the Pero-SCs. Here, the widely used water adsorbents chitosan, sorbitol, and sodium hyaluronate (NaHA) were used as hydrophilic layers on the upper interface of the perovskite to form a barrier against water. The water adsorbents also passivated defects on the surface of the perovskite active layer due to their -OH and -COOH functional groups. The NaHA-modified devices showed the best power conversion efficiency (PCE) (PCE = 21.74%). Although the NaHA-modified Pero-SCs showed optimal photovoltaic performance, the stability of the modified devices decreased due to the strong water adsorption ability of NaHA, while with moderate water adsorption ability sorbitol-modified devices exhibited good stability and PCE. The devices were tested in the dark and room temperature at different humidity levels for 800 h. At low humidity (25% ± 5% RH), the PCEs of the sorbitol- and NaHA-modified devices were maintained at 80% and 71% of the initial values, respectively. At high humidity (75% ± 5% RH), the PCE was maintained at 64% and 23% of the initial values, respectively. This work provides an avenue to select adsorbents with suitable water absorption ability as the interface modification layer, thus reducing the water erosion of perovskite films and obtaining highly stable inverted Pero-SCs.

An effective ultrasound fetal palate screening software based on the "sequential sector scan through the oral fissure" and three-dimensional ultrasound.

BACKGROUND: Orofacial clefts are one of the most common congenital malformations of the fetal face and ultrasound is mainly responsible for its diagnosis. It is difficult to view the fetal palate, so there is currently no unified standard for fetal palate screening, and the diagnosis of cleft palate is not included in the relevant prenatal ultrasound screening guidelines. Many prenatal diagnoses for cleft palate are missed due to the lack of effective screening methods. Therefore, it is imperative to increase the display rate of the fetal palate, which would improve the detection rate and diagnostic accuracy for cleft palate. We aim to introduce a fetal palate screening software based on the "sequential sector scan though the oral fissure", an effective method for fetal palate screening which was verified by our follow up results and three-dimensional ultrasound and to evaluate its feasibility and clinical practicability. METHODS: A software was designed and programmed based on "sequential sector scan through the oral fissure" and three-dimensional ultrasound. The three-dimensional ultrasound volume data of the fetal face were imported into the software. Then, the median sagittal plane was taken as the reference interface, the anterior upper margin of the mandibular alveolar bone was selected as the fulcrum, the interval angles, and the number of layers of the sector scan were set, after which the automatic scan was performed. Thus, the sector scan sequential planes of the mandibular alveolar bone, pharynx, soft palate, hard palate, and maxillary alveolar bone were obtained in sequence to display and evaluate the palate. In addition, the feasibility and accuracy of the software in fetal palate displaying and screening was evaluated by actual clinical cases. RESULTS: Full views of the normal fetal palates and the defective parts of the cleft palates were displayed, and relatively clear sequential tomographic images and continuous dynamic videos were formed after the three-dimensional volume data of 10 normal fetal palates and 10 cleft palates were imported into the software. CONCLUSIONS: The software can display fetal palates more directly which might allow for a new method of fetal palate screening and cleft palate diagnosis.

Intelligent medicine in focus: the 5 stages of evolution in robot-assisted surgery for prostate cancer in the past 20 years and future implications.

Robot-assisted surgery has evolved into a crucial treatment for prostate cancer (PCa). However, from its appearance to today, brain-computer interface, virtual reality, and metaverse have revolutionized the field of robot-assisted surgery for PCa, presenting both opportunities and challenges. Especially in the context of contemporary big data and precision medicine, facing the heterogeneity of PCa and the complexity of clinical problems, it still needs to be continuously upgraded and improved. Keeping this in mind, this article summarized the 5 stages of the historical development of robot-assisted surgery for PCa, encompassing the stages of emergence, promotion, development, maturity, and intelligence. Initially, safety concerns were paramount, but subsequent research and engineering advancements have focused on enhancing device efficacy, surgical technology, and achieving precise multi modal treatment. The dominance of da Vinci robot-assisted surgical system has seen this evolution intimately tied to its successive versions. In the future, robot-assisted surgery for PCa will move towards intelligence, promising improved patient outcomes and personalized therapy, alongside formidable challenges. To guide future development, we propose 10 significant prospects spanning clinical, research, engineering, materials, social, and economic domains, envisioning a future era of artificial intelligence in the surgical treatment of PCa.

A single amino acid substitution in the AAA-type ATPase LRD6-6 activates immune responses but decreases grain quality in rice.

Plant spotted leaf (spl) mutants are useful to reveal the regulatory mechanisms of immune responses. Thus, in crop plants, their agronomic traits, especially the grain quality are usually ignored. Here, we characterized a rice spl mutant named spl-A (spotted leaf mutant from A814) that shows autoimmunity, broad-spectrum disease resistance and growth deterioration including decreased rice quality. A single nucleotide mutation of C1144T, which leads to change of the 382nd proline to serine, in the gene encoding the ATPases associated with diverse cellular activities (AAA)-type ATPase LRD6-6 is responsible for the phenotype of the spl-A mutant. Mechanistically, this mutation impairs LRD6-6 ATPase activity and disrupts its interaction with endosomal sorting complex required for transport (ESCRT)-III subunits OsSNF7.1/7.2/7.3. And thus, leading to compromise of multivesicular bodies (MVBs)-mediated vesicle trafficking and accumulation of ubiquitinated proteins in both leaves and seeds of spl-A. Therefore, the immune response of spl-A is activated, and the growth and grain quality are deteriorated. Our study identifies a new amino acid residue that important for LRD6-6 and provides new insight into our understanding of how MVBs-mediated vesicle trafficking regulates plant immunity and growth, including grain quality in rice.

Loss of clear cell characteristics in aggressive clear cell odontogenic carcinoma: a case report.

BACKGROUND: Clear cell odontogenic carcinoma (CCOC) is an odontogenic carcinoma characterized by sheets and islands of vacuolated and clear cells. The diagnosis of atypical CCOC can pose a challenge when tumor cells deviate from their characteristic clear morphology, even with the aid of genetic profiling for CCOC identification. CASE PRESENTATION: In this manuscript, we detailed the inaugural instance of a recurrently recurring clear cell odontogenic carcinoma (CCOC) with pronounced squamous differentiation in a 64-year-old male. The primary tumor in this individual initially displayed a biphasic clear cell phenotype. However, subsequent to the third recurrence, the clear tumor cells were entirely supplanted by epidermoid cells characterized by eosinophilic cytoplasm, vesicular chromatin, and prominent nucleoli. Notable aggressive attributes such as necrosis, conspicuous cytological malignancy, perineural dissemination, and vascular invasion were noted. Additionally, the tumor progressed to manifest lung metastases. The tumor cells exhibited positive immunoreactivity for AE1/AE3, KRT19, Pan-CK, EMA, P40, P63, CK34ßE12, and P53, while they tested negative for CK35ßH11, KRT7, S-100, and neuroendocrine markers. The Ki-67 proliferation index was calculated at an average of 15%. Furthermore, FISH analysis unveiled the presence of the EWSR1::ATF1 gene fusion. CONCLUSIONS: This case illustrated a rare and aggressive case of CCOC characterized by significant squamous differentiation upon recurrence of the tumor.

Adding rumen microorganisms to improve fermentation quality, enzymatic efficiency, and microbial communities of hybrid Pennisetum silage.

Hybrid Pennisetum, a top biomass energy source, faces usage limitations because of its scarce lactic acid bacteria and high fiber content. This study assessed the influence of rumen fluid pretreatment on hybrid Pennisetum's silage, with focus on silage duration and rumen fluid effects on quality and fiber decomposition. Advanced third-generation sequencing was used to track microbial diversity changes and revealed that rumen fluid considerably enhanced dry matter, crude protein, and water-soluble carbohydrates, thus improving fermentation quality to satisfactory pH levels (3.40-3.67). Ideal results, including the highest fiber breakdown and enzymatic efficiency (47.23 %), were obtained with 5 % rumen fluid in 60 days. The addition of rumen fluid changed the dominant species, including Paucilactobacillus vaccinostercus (0.00 % vs. 18.21 %) and Lactiplantibacillus plantarum (21.03 % vs. 47.02 %), and no Enterobacter was detected in the high-concentration treatments. Moreover, strong correlations were found between specific lactic acid bacteria and fermentation indicators, revealing the potential of achieving efficient and economically beneficial hybrid Pennisetum production.

Simultaneous Determination of Ripretinib and Its Desmethyl Metabolite in Human Plasma Using LC-MS/MS.

BACKGROUND: Ripretinib, a recently developed tyrosine kinase inhibitor with switch-control abilities, can inhibit both primary and secondary activation of KIT(KIT proto-oncogene receptor tyrosine kinase) and platelet-derived growth factor receptor alpha (PDGFRA) mutants, which contribute to gastrointestinal stromal tumor progression. METHODS: In this study, a high-performance liquid chromatography-tandem mass spectrometry method to measure the concentrations of ripretinib and its active desmethyl metabolite DP-5439 in human plasma was developed and validated. Plasma samples were extracted and recovered by precipitation with acetonitrile containing the internal standard and diluted with acetonitrile before analysis. Ripretinib and DP-5439 were separated using chromatography on a Waters ACQUITY UPLC HSS T3 column (2.1 mm × 50 mm, 1.8 µm) with gradient elution using 0.1% formic acid and 5 mM ammonium formate in water as mobile phase A and acetonitrile as mobile phase B. The mobile phase was set to a flow rate of 0.5 mL/min. RESULTS: The calibration curves were linear across the following concentration range: 7.5 to 3000 ng/mL for ripretinib and 10 to 4000 ng/mL for DP-5439. The intraday and interday precisions were approximately 15% for all analytes in the quality control samples. The relative matrix effects in extracted plasma samples (90.3%-108.8% at different levels) were considered acceptable. CONCLUSIONS: This method will be a useful tool in oncology to facilitate the further clinical development of ripretinib.

CD74 facilitates immunotherapy response by shaping the tumor microenvironment of hepatocellular carcinoma.

BACKGROUND: CD74 is ectopically expressed in many tumors and can regulate tumor immunity. However, there are many gaps in the study of the prognostic value of CD74 expression and immune infiltration in hepatocellular carcinoma (HCC). METHODS: An online tumor database was searched to obtain data on gene/protein expression. Immune infiltration analysis was performed using the Tumor Immune Estimation Resource and Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer databases. Single-cell data were obtained from the Tissue-specific Gene Expression and Regulation, Single-cell Transcriptomes of Tumor Immune Microenvironment and Tumor Immune Single-cell Hub 2 databases. RESULTS: CD74 was highly expressed in HCC patients. HCC patients with high CD74 expression who consumed alcohol or were negative for hepatitis virus had a better prognosis than patients with low CD74 expression. CD74 was mainly enriched in immune response regulation pathways. Both copy number variations in CD74 and CD74 expression patterns affected the infiltration levels of immune cells. Interestingly, CD74 regulated the differentiation of myeloid cells. CD74 in macrophages and dendritic cells (DCs) forms complex networks with malignant cells and hepatic progenitor cell (HPC)-like cells, respectively. High CD74 expression in HPC-like cells and malignant cells significantly decreased the fraction of C-type lectin domain family 9 A (CLEC9A)-cDC1+ DCs and IL-1B+ macrophages, respectively. Their crosstalk subsequently shaped the tumor microenvironment of HCC, possibly through the CD74-MIF axis. Importantly, patients with high CD74 expression presented higher immune scores and achieved good outcomes after receiving immunotherapy. CONCLUSION: High CD74 expression is associated with the abundance of a variety of immune cell types, mediating interactions among tumor and immune cells and shaping the malignant behavior of HCC. In summary, CD74 may be a hallmark for determining the prognosis and immune cell infiltration levels of HCC patients.

Unraveling the role of NLRP3 inflammasome in allergic inflammation: implications for novel therapies.

Allergic diseases like asthma, allergic rhinitis and dermatitis pose a significant global health burden, driving the search for novel therapies. The NLRP3 inflammasome, a key component of the innate immune system, is implicated in various inflammatory diseases. Upon exposure to allergens, NLRP3 undergoes a two-step activation process (priming and assembly) to form active inflammasomes. These inflammasomes trigger caspase-1 activation, leading to the cleavage of pro-inflammatory cytokines (IL-1ß and IL-18) and GSDMD. This process induces pyroptosis and amplifies inflammation. Recent studies in humans and mice strongly suggest a link between the NLRP3 inflammasome, IL-1ß, and IL-18, and the development of allergic diseases. However, further research is needed to fully understand NLRP3's specific mechanisms in allergies. This review aims to summarize the latest advances in NLRP3 activation and regulation. We will discuss small molecule drugs and natural products targeting NLRP3 as potential therapeutic strategies for allergic diseases.

STAT3-specific nanocarrier for shRNA/drug dual delivery and tumor synergistic therapy.

Non-small cell lung cancer (NSCLC) is a major disease with high incidence, low survival rate and prone to develop drug resistance to chemotherapy. The mechanism of secondary drug resistance in NSCLC chemotherapy is very complex, and studies have shown that the abnormal activation of STAT3 (Signal Transducer and Activator of Transcription 3) plays an important role in it. In this study, the pGPU6/GFP/Neo STAT3-shRNA recombinant plasmid was constructed with STAT3 as the precise target. By modifying hydrophilic and hydrophobic blocks onto chitosan, a multifunctional vitamin E succinate-chitosan-polyethylene glycol monomethyl ether histidine (VES-CTS-mPEG-His) micelles were synthesized. The micelles could encapsulate hydrophobic drug doxorubicin through self-assembly, and load the recombinant pGPU6/GFP/Neo STAT3-shRNA (pDNA) through positive and negative charges to form dual-loaded nanoparticles DOX/VCPH/pDNA. The co-delivery and synergistic effect of DOX and pDNA could up-regulate the expression of PTEN (Phosphatase and Tensin Homolog), down-regulate the expression of CD31, and induce apoptosis of tumor cells. The results of precision targeted therapy showed that DOX/VCPH/pDNA could significantly down-regulate the expression level of STAT3 protein, further enhancing the efficacy of chemotherapy. Through this study, precision personalized treatment of NSCLC could be effectively achieved, reversing its resistance to chemotherapy drugs, and providing new strategies for the treatment of drug-resistant NSCLC.

Recent advances in near-infrared stimulated nanohybrid hydrogels for cancer photothermal therapy.

Nanomedicine has emerged as a promising avenue for advancing cancer treatment, but the challenge of mitigating its in vivo side effects necessitates the development of innovative structures and materials. Recent investigation has unveiled nanogels as particularly compelling candidates, characterized by a porous, three-dimensional network architecture that exhibits exceptional drug loading capacity. Beyond this, nanogels boast a substantial specific surface area and can be tailored with specific chemical functionalities. Consequently, nanogels are frequently engineered as a multi-modal synergistic platform for combating cancer, wherein photothermal therapy stands out due to its capacity to penetrate deep tissues and achieve localized tumor eradication through the application of elevated temperatures. In this review, we delve into the synthesis of diverse varieties of photothermal nanogels capable of controlled drug release triggered by either chemical or physical stimuli. It also summarizes their potential for synergistic integration with photothermal therapy alongside other therapeutic modalities to realize effective tumor ablation. Moreover, we analyze the primary mechanisms underlying the contribution of photothermal nanogels to cancer treatment while underscoring their adeptness in regulating therapeutic temperatures for repairing bone defects resulting from tumor-associated trauma. Envisioned as an auspicious strategy in the realm of cancer therapy, photothermal nanogels hold promise for furnishing controlled drug delivery and precise thermal ablation capabilities.

Domain-interactive Contrastive Learning and Prototype-guided Self-training for Cross-domain Polyp Segmentation.

Accurate polyp segmentation plays a critical role from colonoscopy images in the diagnosis and treatment of colorectal cancer. While deep learning-based polyp segmentation models have made significant progress, they often suffer from performance degradation when applied to unseen target domain datasets collected from different imaging devices. To address this challenge, unsupervised domain adaptation (UDA) methods have gained attention by leveraging labeled source data and unlabeled target data to reduce the domain gap. However, existing UDA methods primarily focus on capturing class-wise representations, neglecting domain-wise representations. Additionally, uncertainty in pseudo labels could hinder the segmentation performance. To tackle these issues, we propose a novel Domain-interactive Contrastive Learning and Prototype-guided Self-training (DCL-PS) framework for cross-domain polyp segmentation. Specifically, domaininteractive contrastive learning (DCL) with a domain-mixed prototype updating strategy is proposed to discriminate class-wise feature representations across domains. Then, to enhance the feature extraction ability of the encoder, we present a contrastive learning-based cross-consistency training (CL-CCT) strategy, which is imposed on both the prototypes obtained by the outputs of the main decoder and perturbed auxiliary outputs. Furthermore, we propose a prototype-guided self-training (PS) strategy, which dynamically assigns a weight for each pixel during selftraining, filtering out unreliable pixels and improving the quality of pseudo-labels. Experimental results demonstrate the superiority of DCL-PS in improving polyp segmentation performance in the target domain. The code will be released at https://github.com/taozh2017/DCLPS.

Three-dimensional visualized technology-guided surgical resection for giant hepatic hemangioma with hemorrhagic necrosis: A case report and literature review.

Background: Hepatic hemangioma is the most common type of benign mesenchymal liver tumor and often has a good prognosis. However, giant hepatic hemangioma larger than 10 cm is an unusual event, and accompanying symptoms of internal hemorrhagic necrosis are extremely rare. There are only a few cases reported. Case summary: Herein, we report the case of a 52-year-old man with hemorrhagic necrosis of a giant hepatic hemangioma. The patient presented to the Department of Hepatobiliary Surgery with a complaint of distending pain on the right abdomen. The patient underwent hepatic artery embolization for giant hepatic hemangioma 2 weeks before presentation. During hospitalization, abdominal computed tomography revealed a mass (15.8 × 14.2 × 14.7 cm) with high density below the right lobe of the liver. The patient subsequently underwent irregular right hepatectomy with the guidance of three-dimensional visualization technology. The surgical anatomy confirmed the diagnosis of internal hemorrhagic necrosis. There was no recurrence or complications in a 4-month follow-up. Previous cases were reviewed to characterize the clinical features of giant hepatic hemangioma with internal hemorrhage necrosis. Conclusion: Cases of giant hepatic hemangioma with internal hemorrhagic necrosis are rare and usually only exhibit fever or epigastric pain. All patients in reviewed cases finally underwent surgical resection. Under these circumstances, the healing effect of transhepatic arterial treatment is not very satisfactory. Patients are deemed poor laparoscopic surgical candidates due to limited abdominal cavity. In order to standardize the diagnosis of these rare cares, the aggregation of existing and future case data is certainly warranted. If diagnosed, consideration should be given to implementing surgical resection according to patients' condition by three-dimensional visualized technology.

Concomitant atypical knee gout and seronegative rheumatoid arthritis: A case report.

BACKGROUND: Gout and seronegative rheumatoid arthritis (SNRA) are two distinct inflammatory joint diseases whose co-occurrence is relatively infrequently reported. Limited information is available regarding the clinical management and prognosis of these combined diseases. CASE SUMMARY: A 57-year-old woman with a 20-year history of joint swelling, tenderness, and morning stiffness who was negative for rheumatoid factor and had a normal uric acid level was diagnosed with SNRA. The initial regimen of methotrexate, leflunomide, and celecoxib alleviated her symptoms, except for those associated with the knee. After symptom recurrence after medication cessation, her regimen was updated to include iguratimod, methotrexate, methylprednisolone, and folic acid, but her knee issues persisted. Minimally invasive needle-knife scope therapy revealed proliferating pannus and needle-shaped crystals in the knee, indicating coexistent SNRA and atypical knee gout. After postarthroscopic surgery to remove the synovium and urate crystals, and following a tailored regimen of methotrexate, leflunomide, celecoxib, benzbromarone, and allopurinol, her knee symptoms were significantly alleviated with no recurrence observed over a period of more than one year, indicating successful management of both conditions. CONCLUSION: This study reports the case of a patient concurrently afflicted with atypical gout of the knee and SNRA and underscores the significance of minimally invasive joint techniques as effective diagnostic and therapeutic tools in the field of rheumatology and immunology.