Comparative prognosis and risk assessment in gallbladder neuroendocrine neoplasms versus adenocarcinomas.

Background: Gallbladder neuroendocrine neoplasms (GB-NENs) are a rare malignant disease, with most cases diagnosed at advanced stages, often resulting in poor prognosis. However, studies regarding the prognosis of this condition and its comparison with gallbladder adenocarcinomas (GB-ADCs) have yet to yield convincing conclusions. Methods: We extracted cases of GB-NENs and GB-ADCs from the Surveillance, Epidemiology, and End Results (SEER) database in the United States. Firstly, we corrected differences in clinical characteristics between the two groups using propensity score matching (PSM). Subsequently, we visualized and compared the survival outcomes of the two groups using the Kaplan-Meier method. Next, we employed the least absolute shrinkage and selection operator (LASSO) regression and Cox regression to identify prognostic factors for GB-NENs and constructed two nomograms for predicting prognosis. These nomograms were validated with an internal validation dataset from the SEER database and an external validation dataset from a hospital. Finally, we categorized patients into high-risk and low-risk groups based on their overall survival (OS) scores. Results: A total of 7,105 patients were enrolled in the study, comprising 287 GB-NENs patients and, 6,818 GB-ADCs patients. There were substantial differences in clinical characteristics between patients, and GB-NENs exhibited a significantly better prognosis. Even after balancing these differences using PSM, the superior prognosis of GB-NENs remained evident. Independent prognostic factors selected through LASSO and Cox regression were age, histology type, first primary malignancy, tumor size, and surgery. Two nomograms for prognosis were developed based on these factors, and their performance was verified from three perspectives: discrimination, calibration, and clinical applicability using training, internal validation, and external validation datasets, all of which exhibited excellent validation results. Using a cutoff value of 166.5 for the OS nomogram score, patient mortality risk can be identified effectively. Conclusion: Patients with GB-NENs have a better overall prognosis compared to those with GB-ADCs. Nomograms for GB-NENs prognosis have been effectively established and validated, making them a valuable tool for assessing the risk of mortality in clinical practice.

Multi-Functional Formaldehyde-Nitrate Batteries for Wastewater Refining, Electricity Generation, and Production of Ammonia and Formate.

As bulky pollutants in industrial and agricultural wastewater, nitrate and formaldehyde pose serious threats to the human health and ecosystem. Current purification technologies including chemical and bio-/photo-/electro-chemical methods, are generally high-cost, time-consuming, or energy-intensive. Here, we report a novel formaldehyde-nitrate battery by pairing anodic formaldehyde oxidation with cathodic nitrate reduction, which simultaneously enables wastewater purification, electricity generation, and the production of high-value-added ammonia and formate. As a result, the formaldehyde-nitrate battery remarkably exhibits an open-circuit voltage of 0.75 V, a peak power density of 3.38 mW cm-2 and the yield rates of 32.7 mg h-1 cm-2 for ammonia and 889.4 mg h-1 cm-2 for formate. In a large-scale formaldehyde-nitrate battery (25 cm2 ), 99.9 % of nitrate and 99.8 % of formaldehyde are removed from simulated industrial wastewater and the electricity of 2.03 W⋅h per day is generated. Moreover, the design of such a multi-functional battery is universally applicable to the coupling of NO3 - or NO2 - reduction with various aldehyde oxidization, paving a new avenue for wastewater purification and chemical manufacturing.

Jahn-Teller Distortions Induced by in situ Li Migration in λ-MnO2 for Boosting Electrocatalytic Nitrogen Fixation.

Lithium-mediated electrochemical nitrogen reduction reaction (Li-NRR) completely eschews the competitive hydrogen evolution reaction (HER) occurred in aqueous system, whereas the continuous deposition of lithium readily blocks the active sites and further reduces the reaction kinetics. Herein, we propose an innovative in situ Li migration strategy to realize that Li substitutes Mn sites in λ-MnO2 instead of evolving into the dead Li. Comprehensive characterizations corroborate that the intercalation of Li+ at high voltage breaks the structural integrity of MnO6 octahedron and further triggers unique Jahn-Teller distortions, which promotes the spin state regulation of Mn sites to generate the ameliorative eg orbital configuration and accelerates N≡N bond cleavage via eg -σ and eg -π* interaction. To this end, the resulted cationic disordered LiMnO4 delivers the recorded highest NH3 yield rate of 220 µg h-1 cm-2 and a Faradaic efficiency (FE) 83.80 % in organic electrolyte.

Nomogram for Estimation of Acute Liver Failure Risk in Spontaneous Ruptured Hepatocellular Carcinoma.

Purpose: Acute liver failure (ALF) is a severe complication of spontaneous ruptured hepatocellular carcinoma (SRHCC) that requires accurate prediction for effective treatment strategies. We aimed to develop a predictive nomogram to estimate the risk of ALF in patients with SRHCC undergoing treatment. Patients and Methods: We performed a retrospective analysis of historical data from 284 patients diagnosed with SRHCC at the First Hospital of Jilin University over the past decade. Variables were selected through univariate and multivariate logistic regression analyses, and a predictive nomogram was constructed. We evaluated its predictive accuracy against the Child-Pugh Score, R.MELD, and ALBI by assessing discrimination, calibration, and net clinical benefit. Results: Among the 284 patients, 65 developed ALF. The risk factors identified for model development included largest tumor size (LTS), platelet counts, prolonged prothrombin time, and elevated serum α-fetoprotein levels. The nomogram exhibited high accuracy in predicting ALF risk with a C-index of 0.91 (0.87-0.95). The Delong test showed a significant difference between the nomogram and the other three models (p<0.05). The calibration curve for the nomogram fit well, and the decision curve analysis revealed superior net benefit. The optimal cut-off point for the nomogram was determined to be 40, yielding sensitivity, specificity, positive predictive value, and negative predictive value of 83.10%, 87.20%, 65.90% and 94.60%, respectively. Conclusion: The nomogram we developed provides an optimized tool for predicting ALF in SRHCC patients. Its application can help determine individual patient's risk of ALF, enabling more rational and personalized treatment strategies.