Efficiency evaluation of dual-energy CT to predict the postoperative early recurrence of pancreatic ductal adenocarcinoma.

OBJECTIVES: To evaluate the efficacy of quantitative parameters from dual-energy CT (DECT) and basic CT features in predicting the postoperative early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). METHODS: In this study, patients with PDAC who underwent radical resection and DECT from 2018 to 2022 were enrolled and categorised into ER and non-ER groups. The clinical data, basic CT features and DECT parameters of all patients were analyzed. Independent predictors of ER were identified with Logistic regression analyses. Three models (model A: basic CT features; model B: DECT parameters; model C: basic CT features + DECT parameters) were established. Receiver operating characteristic curve analysis was utilized to evaluate predictive performance. RESULTS: A total of 150 patients were enrolled (ER group: n = 63; non-ER group: n = 87). Rim enhancement (odds ratio [OR], 3.32), peripancreatic strands appearance (OR, 2.68), electron density in the pancreatic parenchymal phase (P-Rho; OR, 0.90), arterial enhancement fraction (AEF; OR, 0.05) and pancreatic parenchyma fat fraction in the delayed phase (OR, 1.25) were identified as independent predictors of ER. Model C showed the highest area under the curve of 0.898. In addition, the corresponding ER risk factors were identified separately for resectable and borderline resectable PDAC subgroups. CONCLUSIONS: DECT quantitative parameters allow for the noninvasive prediction of postoperative ER in patients with PDAC, and the combination of DECT parameters and basic CT features shows a high prediction efficiency. Our model can help to identify patients with high-risk factors to guide preoperative decision making.

Extracellular volume fraction derived from dual-energy CT: a potential predictor for acute pancreatitis after pancreatoduodenectomy.

OBJECTIVES: To investigate the value of extracellular volume (ECV) fraction and fat fraction (FF) derived from dual- energy CT (DECT) for predicting postpancreatectomy acute pancreatitis (PPAP) after pancreatoduodenectomy (PD). METHODS: This retrospective study included patients who underwent DECT and PD between April 2022 and September 2022. PPAP was determined according to the International Study Group for Pancreatic Surgery (ISGPS) definition. Iodine concentration (IC) and FF of the pancreatic parenchyma were measured on preoperative DECT. The ECV fraction was calculated from iodine map images of the equilibrium phase. The independent predictors for PPAP were assessed by univariate and multivariable logistic regression analysis and receiver operating characteristic (ROC) curve analysis. RESULTS: Sixty-nine patients were retrospectively enrolled (median age, 60 years; interquartile range, 55-70 years; 47 men). Of these, nine patients (13.0%) developed PPAP. These patients had lower portal venous phase IC, equilibrium phase IC, FF, and ECV fraction, and higher pancreatic parenchymal-to-portal venous phase IC ratio and pancreatic parenchymal-to-equilibrium phase IC ratio, compared with patients without PPAP. After multivariable analysis, ECV fraction was independently associated with PPAP (odd ratio [OR], 0.87; 95% confidence interval [CI]: 0.79, 0.96; p < 0.001), with an area under the curve (AUC) of 0.839 (sensitivity 100.0%, specificity 58.3%). CONCLUSIONS: A lower ECV fraction is independently associated with the occurrence of PPAP after PD. ECV fraction may serve as a potential predictor for PPAP after PD. CLINICAL RELEVANCE STATEMENT: DECT-derived ECV fraction of pancreatic parenchyma is a promising biomarker for surgeons to preoperatively identify patients with higher risk for postpancreatectomy acute pancreatitis after PD and offer selective perioperative management. KEY POINTS: PPAP is a complication of pancreatic surgery, early identification of higher-risk patients allows for risk mitigation. Lower DECT-derived ECV fraction was independently associated with the occurrence of PPAP after PD. DECT aids in preoperative PAPP risk stratification, allowing for appropriate treatment to minimize complications.

Multi-target free-space laser communication system based on a rotating double prism with an RF signal beacon.

Traditional free-space laser communication systems use beacon and signal lights for target detection and alignment. However, these approaches are inaccurate owing to signal dispersion errors. To overcome this difficulty, we propose a new method using transient radio frequency (RF) signals to achieve highly accurate target detection and alignment. To validate the feasibility of our proposed method, we built an experimental multi-target space-laser communication system based on a rotating double prism and applied it to achieve multi-target space-laser communication. The results demonstrate the efficiency of the proposed method to capture multi-target positions in the field of view using wireless RF signals and a rotating double prism. In addition, we show that the system is capable of rapid scanning and accurate pointing as well as establishing a one-way stable communication with multiple targets. When the target is 36 cm away, the pointing accuracy of the system motor is less than 0.8°, the pointing time is 1.2 s, and the average pointing lateral error is 0.666 mm.

Preclinical and clinical advances in dual-target chimeric antigen receptor therapy for hematological malignancies.

In recent years, the excellent curative effect of CD19-specific chimeric antigen receptor (CAR) T-cell therapy has brought hope to patients with relapsing or refractory B-cell hematological malignancies, however relapse after CAR T-cell infusion has hindered the widespread clinical application of this immunotherapy and targeted antigen-negative relapse has caused widespread concern. Consequently, strategies for increasing targeted antigens have been created. In addition to the most widely applied target, namely CD19, researchers have further explored the possibility of other targets, such as CD20, CD22, CD33, and CD123, and have tested a series of combination antigen CAR T-cell therapies. Here, we summarize the current preclinical and clinical studies of dual-target CAR T cells.

Design optimization of office building envelope by developed farmland fertility algorithm for energy saving.

This study focuses on designing sustainable buildings with a specific emphasis on reducing energy consumption and optimizing costs. To address the time-consuming nature of simulation software like TRNSYS and Energy Plus, a novel meta-heuristic optimization algorithm called the Developed Optimization Algorithm of Farmland Fertility (DFFA) is provided. The DFFA algorithm is utilized to optimize parameters related to the building envelope, encompassing walls, windows, and glass curtain walls, aiming to minimize energy demand and construction expenses. Comparative analysis with other approaches such as EPO, LOA, MVO, and FFA demonstrates significant reductions in energy consumption and building design costs achieved by employing the proposed algorithm. Furthermore, the DFFA algorithm yields the desired results within fewer iterations. By increasing the surface area of the glass curtain wall and total window space, improvements in natural ventilation and interior lighting are observed. Despite similar window opening measurements across the compared methods, the suggested algorithm surpasses others when it comes to overall cost and energy efficiency. The total cost reduction compared to the initial design amounts to 39 %. Thus, the DFFA algorithm proves to be more effective in conserving energy in buildings compared to other analyzed procedures. This research serves as a case study and presents a promising method applicable to designing various building types under different weather conditions in future projects.

Unravelling diagnostic clusters and immune landscapes of disulfidptosis patterns in gastric cancer through bioinformatic assay.

Disulfidptosis is a novel type of cell death mediated by SLC7A11-induced disulfide stress. Gastric cancer (GC) is a common malignant gastrointestinal tumor. Existing evidence shows that SLC7A11 can regulate cell death and improve the progression of GC, suggesting disulfidptosis may exist in the pathological process of GC. However, the underlying functions of disulfidptosis regulators in GC remain unknown. The dataset of GSE54129 was screened to comprehensively investigate the disulfidptosis-related diagnostic clusters and immune landscapes in GC. Totally 15 significant disulfidptosis regulators were identified via difference analysis between GC samples and controls. Then random forest model was utilized to assess their importance score (mean decrease Gini). Then a nomogram model was constructed, which could offer benefit to patients based on our subsequent decision curve analysis. All the included GC patients were divided into 2 disulfidptosis subgroups (clusterA and clusterB) according to the significant disulfidptosis regulators in virtue of consensus clustering analysis. The disulfidptosis score of each sample was calculated through PCA algorithms to quantify the disulfidptosis subtypes. Patients from clusterB exhibited lower disulfidptosis scores than those of patients in clusterA. In addition, we found that the cases in clusterB were closely associated with the immunity of activated CD4 T cell, etc., while clusterA was linked to immature dendritic cell, mast cell, natural killer T cell, natural killer cell, etc., which has a higher disulfidptosis score. Therefore, disulfidptosis regulators play an important role in the pathological process of GC, providing a promising marker and an immunotherapeutic strategy for future GC therapy.

Robustness and accuracy evaluation of moisture prediction model for black tea withering process using hyperspectral imaging.

The rapid and non-destructive detection of moisture in withering leaves is an unsolved problem because the leaves are stacked together and have random orientation. To address this issue, this study aimed to establish more robust and accurate models. The performance of front side, back side and multi-region models were compared, and the front side model showed the worst transferability. Therefore, five effective wavelength (EW) selection algorithms were combined with a successive projection algorithm (SPA) to select EWs. It was found that the shuffled frog leaping algorithm (SFLA) combined with SPA was the best method for the front side model for moisture analyses. Based on the selected EWs, the extreme learning machine (ELM) became the model with the best self-verification result. Subsequently, moisture distribution maps of withering leaves were successfully generated. Considering the processing demand of withering leaves, local region models developed based on partial least squares and the SFLA-SPA method were applied to predict the moisture of withering leaves in the local and stacked region. The results showed that the RPD, Rcv and Rp values were above 1.6, 0.870 and 0.897, respectively. These results provide a useful reference for the non-destructive detection of moisture in withering leaves.

Antibacterial PDT nanoplatform capable of releasing therapeutic gas for synergistic and enhanced treatment against deep infections.

Antibacterial photodynamic therapy (aPDT) has emerged as an attractive treatment option for efficient removal of pathogenic bacteria. However, aPDT in deep tissue will encounter difficulties such as limited light penetration depth, insufficient oxygen (O2) supply and inability to eliminate inflammation introduced by bacteria, which hinders its clinical application. Herein, the near infrared (NIR) strategy of simultaneously generating O2 and CO was developed for aPDT based antibacterial therapy and mitigation of deep infection inflammation. Methods: We prepared NIR-mediated multifunctional aPDT nanoplatform (POS-UCNPs/ICG) producing therapeutic gas of O2 and CO. The CO, O2 and ROS generation of the nanoplatform were characterized by dye probes, respectively. The antibacterial activity and anti-inflammation of POS-UCNPs/ICG were demonstrated in vitro and in vivo. In addition, the therapeutic effects in vivo were serially analyzed by immunofluorescence staining, Masson's staining, hematoxylin and eosin staining, colony formation units (CFU) and so on. Results: NIR-mediated multifunctional aPDT nanoplatform was realized by combining the up-conversion nanoparticles (UCNPs) and partially oxidized SnS2 (POS) nanosheets (NSs) as well as indocyanine green (ICG). Using a single 808 nm light, aPDT can be achieved via ICG molecules, meanwhile, O2/CO can be generated by POS NSs through upconversion light excitation. During the aPDT process, O2 can enhance aPDT, while CO can regulate inflammation through the PI3K/NF-κB pathway. Therefore, POS-UCNPs/ICG groups had a highest percentage of healing area up to 91.55±1.26% in mouse abscess model. Conclusion: Due to enhanced aPDT and anti-inflammatory collaborative therapy, the POS-UCNPs/ICG composites showed remarkably accelerated recovery in animal abscess models. Such NIR light responsive nanoplatform with optimized antibacterial capacity and immunomodulatory functions is promising for clinical therapeutics of bacteria-induced infections.

Ferritin-based targeted delivery of arsenic to diverse leukaemia types confers strong anti-leukaemia therapeutic effects.

Trivalent arsenic (AsIII) is an effective agent for treating patients with acute promyelocytic leukaemia, but its ionic nature leads to several major limitations like low effective concentrations in leukaemia cells and substantial off-target cytotoxicity, which limits its general application to other types of leukaemia. Here, building from our clinical discovery that cancerous cells from patients with different leukaemia forms featured stable and strong expression of CD71, we designed a ferritin-based As nanomedicine, As@Fn, that bound to leukaemia cells with very high affinity, and efficiently delivered cytotoxic AsIII into a large diversity of leukaemia cell lines and patient cells. Moreover, As@Fn exerted strong anti-leukaemia effects in diverse cell-line-derived xenograft models, as well as in a patient-derived xenograft model, in which it consistently outperformed the gold standard, showing its potential as a precision treatment for a variety of leukaemias.

Targeting breast cancer cells with a CuInS2/ZnS quantum dot-labeled Ki-67 bioprobe.

The aim of the present study was to develop a water-soluble biomarker for the detection of breast cancer using quantum dots (QDs) conjugated to Ki-67, a nuclear protein associated with the cell cycle. Ki-67 is also a marker of cell proliferation, with expression levels categorizing good and poor prognosis in invasive breast cancer. Ki-67 is a clinically used biomarker for breast cancer diagnosis, treatment and prognosis. Owing to the optical and chemical advantages of QDs, QD-based nanotechnology may aid the construction of a biomedical imaging platform for the study of cancer cell behavior. In the present study, a biomarker was prepared by employing the water-soluble CuInS2/ZnS QDs conjugated to an anti-Ki-67 monoclonal antibody to detect Ki-67 expression in breast cancer. The QDs, which were hydrophobic and coated with octadecylamine, were encapsulated with an amphiphilic biocompatible centipede-like polymer, and then conjugated to anti-Ki-67 monoclonal antibodies (QD-Ki-67 probes). The QD-Ki-67 probes retained the original optical properties of the unadorned QDs and did not exhibit distinct toxic side effects in in vitro cytotoxicity experiments. Therefore, this CuInS2/ZnS QD-labeled bioprobe, with a high quantum yield and low cytotoxicity, is a promising candidate for bioimaging and may be used as a cell label.

Klebsiella pneumoniae thyroid abscess complicated with esophagitis in a woman with newly diagnosed diabetes mellitus: A case report.

The thyroid is resistant to infection because of the anatomical and physiological characteristics of the gland, and even though diabetes can induce a compromised immune system, thyroid infection disease is scarcely encountered in diabetic patients. Thyroid abscess formation in an asymptomatic diabetic patient is an even rarer entity. We present a case of a previously asymptomatic diabetic patient showing clinical symptoms of painful swelling in the anterior neck followed by progressing dysphagia, who was later diagnosed with thyroid abscess as a result of Klebsiella pneumoniae, complicated with esophagitis caused by the same microorganism. To our knowledge, this is the first reported case of asymptomatic diabetes being clinically diagnosed with thyroid abscess as the first sign.