A YBCO RF-squid variable temperature susceptometer and its applications

The Superconducting QUantum Interference Device (SQUID) susceptibility using a high-temperature radio-frequency (rf) SQUID and a normal metal pick-up coil is employed in testing weak magnetization of the sample. The magnetic moment resolution of the device is 1 x 10(exp -6) emu, and that of the susceptibility is 5 x 10(exp -6) emu/cu cm

Stratosphere-troposphere coupling during stratospheric extremes in the 2022/23 winter

Using the ERA5 reanalysis, sea surface temperature, sea ice observations, and the real-time multivariate Madden-Julian Oscillation (MJO) index, the evolution of the stratospheric extreme circulation in the winter of 2022/2023 is explored. The stratospheric polar vortex was disturbed three times in the 2022/23 winter, contrasted with only one disturbance during the other three recent winters with an SSW. Possible favorable conditions for the strong stratospheric disturbances and their effects on stratospheric ozone, water vapor distribution, and near-surface temperature were examined. Around 7 December 2022 when a short but strong pulse of planetary wavenumber 2 appeared from the troposphere to stratosphere, a weakened and elongated stratospheric polar vortex formed at 10 hPa. This pulse is related to the intensifying Ural ridge and the deepening East Asian trough. After the first stratospheric disturbance, a large fraction of cold anomalies occurred in the Eurasian continent. A lagged impact after these stratospheric disturbances was observed as strong cold anomalies formed in North America from 13 to 23 December. On 28 January 2023, a minor SSW event occurred due to a displacement of the stratospheric polar vortex. A strong pulse of eddy heat flux contributed alternately by planetary wavenumber 1 and 2 showed a large accumulative effect on the stratospheric disturbance. However, the downward impact of this second disturbance was weak, and cold surges were not noticeable after this minor SSW. The third stratospheric disturbance this winter is a major displace-type SSW that occurred on 16 February 2023, and the total eddy heat flux primarily contributed by planetary wavenumber 1 increased rapidly. Following the major SSW, the North American continent was covered by large patches of strong cold anomalies until the end of March. During the three disturbances, the residual circulation correspondingly strengthened. The water vapor and ozone in the middle and lower layers of the polar stratosphere showed positive anomaly disturbances, especially after the major SSW onset. The unprecedented frequent stratospheric disturbances in winter 2022/23 were accompanied by severe loss of Barents-Laptev Sea ice and anomalously cold tropical Pacific sea surface temperatures (La Niña), which have been reported to be conducive to the enhancement of planetary waves 1 and 2 respectively. Further, two weeks before the major SSW, existing MJO developed into phases 4–6, also contributing to the occurrence of major SSW

Hierarchical Co2P microspheres assembled from nanorods grown on reduced graphene oxide as anode material for Lithium-ion batteries

Transition metal phosphides (TMPs) have been studied as promising electrodes for energy storage and conversion due to their large theoretical capacities and high activities. Herein, a hierarchically structured Co2P coupling with the reduced graphene oxide (RGO) composite (Co2P/RGO) was synthesized by a simple solid state method for Li storage. The Co2P/RGO hybrid composite exhibits a high reversible capacity of 61 mAh g−1 at 60 mA g−1, good rate capability of 327 mAh g−1 at 3000 mA g−1 and long cycle life (397 mAh g−1 at 500 mA g−1 for after 1000 cycles). The excellent electrochemical performance can be attributed to the synergistic effect of Co2P micro/nano architecture and graphene modulation, which provide more activity sites for Li+-ions and maintain the structural integrity of active material. This work may provide a new path for preparation of other metal phosphides as potential electrode materials for application in energy storage fields

Reviewing the thermo-chemical recycling of waste polyurethane foam

The worldwide production of polymeric foam materials is growing due to their advantageous properties of light weight, high thermal insulation, good strength, resistance and rigidity. Society creates ever increasing amounts of poly-urethane (PU) waste. A major part of this waste can be recycled or recovered in order to be put into further use. The PU industry is committed to assist and play its part in the process. The recycling and recovery of PU foam cover a range of mechanical, physical, chemical and thermo-chemical processes. In addition to the well- documented mechanical and chemical processing options, thermo-chemical treatments are important either as ultimate disposal (incineration) or towards feedstock recovery, leading to different products according to the thermal conditions of the treatment. The review focuses on these thermo-chemical and thermal processes. As far as pyrolysis is concerned, TDI and mostly polyol can be recovered. The highest recovery yields of TDI and polyols occur at low temperatures (150–200 ◦C). It is however clear from literature that pure feedstock will not be produced, and that a further upgrading of the condensate will be needed, together with a thermal or alternative treatment of the non-condensables. Gasification towards syngas has been studied on a larger and industrial scale. Its application would need the location of the PU treatment plant close to a chemical plant, if the syngas is to be valorized or considered in conjunction with a gas-fired CHP plant. Incineration has been studied mostly in a co- firing scheme. Potentially toxic emissions from PU combustion can be catered for by the common flue gas cleaning behind the incineration itself, making this solution less evident as a stand-alone option: the combination with other wastes (such as municipal solid waste) in MSWI′s seems the indicated route to go

The role of IGF-1 in exercise to improve obesity-related cognitive dysfunction

Obesity is an important factor that threatens human health. The occurrence of many chronic diseases is related to obesity, and cognitive function decline often occurs with the onset of obesity. With the further prevalence of obesity, it is bound to lead to a wider range of cognitive dysfunction (ORCD). Therefore, it is crucial to suppress ORCD through intervention. In this regard, exercise has been shown to be effective in preventing obesity and improving cognitive function as a non-drug treatment. There is sufficient evidence that exercise has a regulatory effect on a growth factor closely related to cognitive function—insulin-like growth factor 1 (IGF-1). IGF-1 may be an important mediator in improving ORCD through exercise. This article reviews the effects of obesity and IGF-1 on cognitive function and the regulation of exercise on IGF-1. It analyzes the mechanism by which exercise can improve ORCD by regulating IGF-1. Overall, this review provides evidence from relevant animal studies and human studies, showing that exercise plays a role in improving ORCD. It emphasizes the importance of IGF-1, which helps to understand the health effects of exercise and promotes research on the treatment of ORCD

Development and verification of a combined immune- and cancer-associated fibroblast related prognostic signature for colon adenocarcinoma

IntroductionTo better understand the role of immune escape and cancer-associated fibroblasts (CAFs) in colon adenocarcinoma (COAD), an integrative analysis of the tumor microenvironment was performed using a set of 12 immune- and CAF-related genes (ICRGs).MethodsUnivariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to establish a prognostic signature based on the expression of these 12 genes (S1PR5, AEN, IL20RB, FGF9, OSBPL1A, HSF4, PCAT6, FABP4, KIF15, ZNF792, CD1B and GLP2R). This signature was validated in both internal and external cohorts and was found to have a higher C-index than previous COAD signatures, confirming its robustness and reliability. To make use of this signature in clinical settings, a nomogram incorporating ICRG signatures and key clinical parameters, such as age and T stage, was developed. Finally, the role of S1PR5 in the immune response of COAD was validated through in vitro cytotoxicity experiments.ResultsThe developed nomogram exhibited slightly improved predictive accuracy compared to the ICRG signature alone, as indicated by the areas under the receiver operating characteristic curves (AUC, nomogram:0.838; ICRGs:0.807). The study also evaluated the relationships between risk scores (RS) based on the expression of the ICRGs and other key immunotherapy variables, including immune checkpoint expression, immunophenoscore (IPS), and microsatellite instability (MSI). Integration of these variables led to more precise prediction of treatment efficacy, enabling personalized immunotherapy for COAD patients. Knocking down S1PR5 can enhance the efficacy of PD-1 monoclonal antibody, promoting the cytotoxicity of T cells against HCT116 cells ((p<0.05).DiscussionThese findings indicate that the ICRG signature may be a valuable tool for predicting prognostic risk, evaluating the efficacy of immunotherapy, and tailoring personalized treatment options for patients with COAD

Risk of venous thromboembolism with janus kinase inhibitors in inflammatory immune diseases: a systematic review and meta-analysis

Objectives: This study aimed to evaluate the risk of venous thrombosis (VTE) associated with Janus kinase (JAK) inhibitors in patients diagnosed with immune-mediated inflammatory diseases.Methods: We conducted a comprehensive search of PUBMED, Cochrane, and Embase databases for randomized controlled trials evaluating venous thromboembolic incidence after administering JAK inhibitors in patients with immune-mediated inflammatory diseases. The studies were screened according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and a meta-analysis was performed.Results: A total of 16 studies, enrolling 17,242 participants, were included in this review. Four approved doses of JAK inhibitors were administered in the included studies. The meta-analysis revealed no significant difference in the incidence of VTE between patients receiving JAK inhibitors, a placebo, or tumor necrosis factor (TNF) inhibitors (RR 0.72, 95% CI (0.33-1.55); RR 0.94, 95%CI (0.33-2.69)). Subgroup analysis showed a lower risk of VTE with lower doses of JAK inhibitors [RR 0.56, 95%CI (0.36-0.88)]. Compared with the higher dose of tofacitinib, the lower dose was associated with a lower risk of pulmonary embolism [RR 0.37, 95%CI (0.18-0.78)].Conclusion: Our meta-analysis of randomized controlled trials observed a potential increase in the risk of VTE in patients with immune-mediated inflammatory diseases treated with JAK inhibitors compared to placebo or tumor necrosis factor inhibitors, though statistical significance was not attained. Notably, a higher risk of pulmonary embolism was observed with high doses of tofacitinib. Our findings provide valuable insights for physicians when evaluating the use of JAK inhibitors for patients with immune-mediated inflammatory diseases.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023382544, identifier CRD4202338254

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis