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Abstract Pancreatic cancer, predominantly pancreatic ductal adenocarcinoma (PDAC), remains a highly lethal malignancy with limited therapeutic options and a dismal prognosis. By targeting the underlying molecular abnormalities responsible for PDAC development and progression, gene therapy offers a promising strategy to overcome the challenges posed by conventional radiotherapy and chemotherapy. This study sought to explore the therapeutic potential of small activating RNAs (saRNAs) specifically targeting the CCAAT/enhancer-binding protein alpha (CEBPA) gene in PDAC. To overcome the challenges associated with saRNA delivery, tetrahedral framework nucleic acids (tFNAs) were rationally engineered as nanocarriers. These tFNAs were further functionalized with a truncated transferrin receptor aptamer (tTR14) to enhance targeting specificity for PDAC cells. The constructed tFNA-based saRNA formulation demonstrated exceptional stability, efficient saRNA release ability, substantial cellular uptake, biocompatibility, and nontoxicity. In vitro experiments revealed successful intracellular delivery of CEBPA-saRNA utilizing tTR14-decorated tFNA nanocarriers, resulting in significant activation of tumor suppressor genes, namely, CEBPA and its downstream effector P21, leading to notable inhibition of PDAC cell proliferation. Moreover, in a mouse model of PDAC, the tTR14-decorated tFNA-mediated delivery of CEBPA-saRNA effectively upregulated the expression of the CEBPA and P21 genes, consequently suppressing tumor growth. These compelling findings highlight the potential utility of saRNA delivered via a designed tFNA nanocarrier to induce the activation of tumor suppressor genes as an innovative therapeutic approach for PDAC.

The pre-analytical steps in blood-based liquid biopsy, involving sample collection techniques and storage conditions, play a critical role in ensuring the integrity and reliability of collected samples. These steps have a directly impact on the accuracy and reliability of test results and are therefore of utmost importance. Mass spectrometry (MS)-based proteomics is an exceptionally powerful tool in the field of liquid biopsy. It enables the comprehensive analysis of the protein content within biological specimens, providing valuable insights into the underlying mechanisms and pathogenesis of diseases. In this study, we aim to explore the variations in the protein landscape between serum and plasma specimens and evaluate the impact of delayed centrifugation on LC/MS-analyzed protein profiles. We seek to provide recommendations on optimal pre-analytical protocols for MS-based proteomics studies. This will enhance the accuracy and reliability of liquid biopsy for precision medicine, ultimately leading to improved patient outcomes.

It is crucial to provide adequate iodine nutrition to infants and toddlers for proper thyroid function and subsequent brain development. Infants are particularly vulnerable to iodine deficiency during the transition from a milk-based diet (breast milk and/or infant formula) to solid food. This study examines the current iodine levels of children during their first two years of life and investigates the association between these levels and feeding behaviors and the iodine status of their mothers in Shanghai, a city located in eastern China. A hospital-based cohort study was conducted to enroll mother–child pairs, where the child is aged 6–23 months, who visited community health service centers in the 16 districts of Shanghai, China. Data on socio-demographic factors and feeding behavior data were collected from the participants. The urinary iodine concentration (UIC) in both the young children and their mothers were analyzed. A total of 2282 mother–child pairs were included in this analysis. The median (p25–p75) UIC for lactating women, weaning women, and children were 121.3 μg/L (68.1–206.4 μg/L), 123.4 μg/L (58.4–227.2 μg/L), and 152.1 μg/L (75.8–268.3 μg/L), respectively. The UIC in children was found to be higher than that in their mothers (p < 0.001). Children who consumed less than 500 mL per day of formula milk in the last week had lower UICs compared with those who consumed 500 mL per day or more (p = 0.026). Furthermore, the children’s UIC was positively correlated with the maternal UIC (rs = 0.285, p < 0.001). Multiple quantile regression analysis revealed a statistically significant positive association between maternal UIC and children’s UIC between the 0.1 and 0.9 quantiles (all p < 0.001). We found that the iodine status of infants and toddlers, as well as of mothers, was sufficient. However, a large minority of children and mothers may be at risk of iodine deficiency. Furthermore, no associations between children’s UIC and feeding behaviors were observed. Moreover, there was a positive correlation between the UIC of young children and their mothers.

In situ capping and biochemical oxidation are two of the most commonly used methods for internal phosphorus (P) control, but there are few studies on the combined use of these two methods. In this study, two lanthanum (La)-based materials, La-modified bentonite (LMB) and the La-modified attapulgite and chitosan composite (LMA&C), were combined with calcium nitrate (CN) to investigate the effect on sediment P control. Results showed that SRP removal rates by LMB+CN and LMA&C+CN were much higher than that by LMB, LMA&C and CN alone. LMB+CN and LMA&C+CN decreased DGT-labile P flux both in overlying water and surface 65 mm sediment, while LMB and LMA&C had an effect only on overlying water and surface 10~40 mm sediment, and CN was effective only on sediments. LMB and LMA&C transformed NH4Cl-P, BD-P, NaOH-SRP and NaOH-NRP in surface 20 mm sediment to HCl-P and Residual-P on day 60. CN transformed NaOH-SRP and NaOH-NRP to BD-P, resulting in the increase in NH4Cl-P. LMB+CN and LMA&C+CN sequestered P in the surface 20 mm mainly as HCl-P and Residual-P, and mainly as BD-P in −20~−60 mm. Results indicate that the combination of capping by La-based material and oxidation by CN is a promising method for sediment P control.

Polynucleotide kinase (PNK) is a key enzyme that is necessary for ligation-based DNA repair. The activity assay and inhibitor screening for PNK may contribute to the prediction and improvement of tumor treatment sensitivity, respectively. Herein, we developed a simple, low-background, and label-free method for both T4 PNK activity detection and inhibitor screening by combining a designed ligation-triggered T7 transcriptional amplification system and a crafty light-up malachite green aptamer. Moreover, this method successfully detected PNK activity in the complex biological matrix with satisfactory outcomes, indicating its great potential in clinical practice.

Calprotectin (CP) is an established biomarker that allows the noninvasive evaluation of inflammation levels in the gastrointestinal tract of patients with inflammatory bowel disease and is helpful for the diagnosis and management of the disease. Herein, we demonstrate that CP can effectively suppress the activity of 17E DNAzyme (17E) by chelating Zn(Ⅱ), which is the cofactor of 17E. As the inhibition efficiency of CP on the DNAzyme is proportional to the concentration of CP, the detection of CP can be readily achieved by assessing the activity of 17E.

With the development of artificial intelligence and Internet of Things (IoT), the era of industry 4.0 has come. According to the prediction of IBM, with the continuous popularization of 5G technology, the IoT technology will be more widely used in factories. In recent years, federated learning has become a hot topic for Industrial Internet of Things (IIoT) researchers. However, many devices in the IIoT currently have a problem of low computing power, so these devices cannot perform well facing the tasks of training and updating models in federated learning. In order to solve the above problems, we introduce edge computing into the IIot, so that the device can complete the federated learning operation. In order to ensure the security of data transmission, blockchain is introduced as the main algorithm of equipment authentication in the system. What’s more, in order to increase the efficiency and versatility of training model in IIoT, we introduce transfer learning to improve the system performance. The experimental results show that our algorithm can achieve high security and high training accuracy.