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Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for those not diagnosed with early screening. Therefore, early diagnosis and early treatment of pancreatic cancer are particularly critical. However, as a rare disease, the general screening cost of pancreatic cancer is high, the accuracy of existing tumor markers is not enough, and the efficacy of treatment methods is not exact. In terms of early diagnosis, artificial intelligence technology can quickly locate high-risk groups through medical images, pathological examination, biomarkers, and other aspects, then screening pancreatic cancer lesions early. At the same time, the artificial intelligence algorithm can also be used to predict the survival time, recurrence risk, metastasis, and therapy response which could affect the prognosis. In addition, artificial intelligence is widely used in pancreatic cancer health records, estimating medical imaging parameters, developing computer-aided diagnosis systems, etc. Advances in AI applications for pancreatic cancer will require a concerted effort among clinicians, basic scientists, statisticians, and engineers. Although it has some limitations, it will play an essential role in overcoming pancreatic cancer in the foreseeable future due to its mighty computing power.

Objective: The aim of the study was to evaluate the diagnostic value of contrast-enhanced ultrasound (CEUS) in distinguishing between benign and malignant cervical lymph nodes in patients with nasopharyngeal carcinoma (NPC). Material and Methods: A total of 144 NPC patients with enlarged superficial cervical lymph nodes underwent CEUS examination. The comparison of CEUS image characteristics between malignant and benign cervical lymph nodes was performed in this study as well. We analyzed parameters of the time–intensity curve (TIC), which includes time to peak (TP), area under the gamma curve (AUC), and peak intensity (PI). Furthermore, receiver operating characteristic (ROC) curve analysis was also investigated to evaluate the diagnostic value of CEUS. Result: We conducted 144 lymph node examinations in total, where 64 cases were biopsy-proven benign nodules and 80 cases were biopsy-proven metastatic nodules. The vast majority of the benign nodes displayed centrifugal perfusion (96.88%, 62/64) and homogeneous enhancement (93.75%, 60/64), while most of the malignant nodes showed centripetal perfusion (92.50%, 74/80) and inhomogeneous 80.00% (64/80). In addition, quantitative analysis showed that CEUS parameters including PI, TP, and AUC in benign lymph nodes (12.51 ± 2.15, 23.79 ± 11.80, and 1110.33 ± 286.17, respectively) were significantly higher than that in the malignant nodes (10.51 ± 2.98, 16.52 ± 6.95, and 784.09 ± 340.24, respectively). The assistance of the three aforementioned parameters and CEUS image characteristics would result in an acceptable diagnostic value. Conclusion: Our results suggest that imaging perfusion patterns as well as quantitative parameters obtained from CEUS provide valuable information for the evaluation of cervical lymph nodes in NPC patients.

There is increasing academic and pragmatic interest in leveraging patent rights to invigorate remanufacturing for waste products under governmental interventions via regulations and reward-penalty instruments. In practice, many original manufacturers that are possessed with intellectual property rights allow third-party remanufacturers to implement reproducing operations through authorization and charging licensing fees. The general purpose of this paper is to explore favorable strategies for a closed-loop supply chain (CLSC) system of waste product collection and remanufacturing, in the context of either manufacturer-remanufacturing or remanufacturer-remanufacturing. To achieve such an objective, game theory is adopted to establish models of three collection and remanufacturing modes among channel members involving a manufacturer, a seller, and a remanufacturer. In so doing, the results show that a government's allocations of elementary remanufacturing ratio and the unit amount of reward-penalty count significantly in CLSC operations, especially for the manufacturer, who acts as the leader in the system and makes mode selections.

Zinc borates have merits of low voltage polarization and suitable redox potential, but usually suffer from low rate capability and poor cycling life, as an emerging anode candidate for Na+ storage. Here, a new intercalator‐guided synthesis strategy is reported to simultaneously improve rate capability and stabilize cycling life of N, B co‐doped carbon/zinc borates (CBZG). The strategy relies on a uniform dispersion of precursors and simultaneously stimulated combustion activation and solid‐state reactions capable of scalable preparation. The Na+ storage mechanism of CBZG is studied: 1) ex situ XRD and XPS demonstrate two‐step reaction sequence of Na+ storage: Zn6O(OH)(BO3)3+Na++e−↔3ZnO+Zn3B2O6+NaBO2+0.5H2 ①, Zn3B2O6+6Na++6e−↔3Zn+3Na2O+B2O3 ②; reaction ① is irreversible in ether‐based electrolyte while reversible in ester‐based electrolyte. 2) Electrochemical kinetics reveal that ether‐based electrolyte possesses faster Na+ storage than ester‐based electrolyte. The composite demonstrates an excellent capacity of 437.4 mAh g−1 in a half‐cell, together with application potential in full cells (discharge capacity of 440.1 mAh g−1 and stable cycle performance of 2000 cycles at 5 A g−1). These studies will undoubtedly provide an avenue for developing novel synthetic methods of carbon‐based borates and give new insights into the mechanism of Na+ storage in ether‐based electrolyte for the desirable sodium storage.