In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers. Conclusion This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.To circumvent the huge cost, long R&D time and the difficulty to identify the targets of new drugs, repurposing the ones that have been clinically approved has been considered as a viable strategy to treat different diseases. In the current study, we outlined the rationale for repurposing disulfiram (DSF, an old alcohol-aversion drug) to treat primary breast cancer and its metastases. Methods To overcome a few shortcomings of the individual administration of DSF, such as the dependence on copper ions (Cu2+) and limited capability in selective targeting, we here artificially synthesized the active form of DSF, diethyldithiocarbamate (DTC)-Cu complex (CuET) for cancer therapeutics. To achieve a greater efficacy in vivo, smart nanomedicines were devised through a one-step self-assembly of three functional components including a chemically stable and biocompatible phase-change material (PCM), the robust anticancer drug (CuET) and a near-infrared (NIR) dye (DIR), namely CuET/DIR NPs. A number of in vitro assays we the nanomedicines and reach a high local concentration towards the nucleus, where the pro-apoptotic effects were conducted. Importantly, our CuET/DIR nanomedicines revealed a pronounced capability to leash breast cancer metastases through inhibition on EMT. Additionally, these nanomedicines showed great biocompatibility in animals. Conclusion These combined data unearthed a remarkably enhanced tumor-killing efficacy of our CuET nanomedicines through nuclear targeting. This work may open a new research area of repurposing DSF as innovative therapeutic agents to treat breast cancer and its metastases.Background The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.The clinical translation of new nanoparticle-based therapies for high-grade glioma (HGG) remains extremely poor. This has partly been due to the lack of suitable preclinical mouse models capable of replicating the complex characteristics of recurrent HGG (rHGG), namely the heterogeneous structural and functional characteristics of the blood-brain barrier (BBB). The goal of this study is to compare the characteristics of the tumor BBB of rHGG with two different mouse models of HGG, the ubiquitously used U87 cell line xenograft model and a patient-derived cell line WK1 xenograft model, in order to assess their suitability for nanomedicine research. Method Structural MRI was used to assess the extent of BBB opening in mouse models with a fully developed tumor, and dynamic contrast enhanced MRI was used to obtain values of BBB permeability in contrast enhancing tumor. H&E and immunofluorescence staining were used to validate results obtained from the in vivo imaging studies. Results The extent of BBB disruption and permeability in the contrast enhancing tumor was significantly higher in the U87 model than in rHGG. These values in the WK1 model are similar to those of rHGG. The U87 model is not infiltrative, has an entirely abnormal and leaky vasculature and it is not of glial origin.  https://www.selleckchem.com/products/otx015.html  The WK1 model infiltrates into the non-neoplastic brain parenchyma, it has both regions with intact BBB and regions with leaky BBB and remains of glial origin. Conclusion The WK1 mouse model more accurately reproduces the extent of BBB disruption, the level of BBB permeability and the histopathological characteristics found in rHGG patients than the U87 mouse model, and is therefore a more clinically relevant model for preclinical evaluations of emerging nanoparticle-based therapies for HGG.Rationale Monoacylglycerol lipase (Mgll), a hydrolase that breaks down the endocannabinoid 2-arachidonoyl glycerol (2-AG) to produce arachidonic acid (ARA), is a potential target for neurodegenerative diseases, such as Alzheimer's disease (AD). Increasing evidence shows that impairment of adult neurogenesis by perturbed lipid metabolism predisposes patients to AD. However, it remains unknown what causes aberrant expression of Mgll in AD and how Mgll-regulated lipid metabolism impacts adult neurogenesis, thus predisposing to AD during aging. Here, we identify Mgll as an aging-induced factor that impairs adult neurogenesis and spatial memory in AD, and show that metformin, an FDA-approved anti-diabetic drug, can reduce the expression of Mgll to reverse impaired adult neurogenesis, prevent spatial memory decline and reduce β-amyloid accumulation. Methods Mgll expression was assessed in both human AD patient post-mortem hippocampal tissues and 3xTg-AD mouse model. In addition, we used both the 3xTg-AD animal model and the CbpS436A genetic knock-in mouse model to identify that elevated Mgll expression is caused by the attenuation of the aPKC-CBP pathway, involving atypical protein kinase C (aPKC)-stimulated Ser436 phosphorylation of histone acetyltransferase CBP through biochemical methods.