Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

Tumor neoantigens: Novel strategies for application of cancer immunotherapy

Neoantigen-targeted immunotherapy is a rapidly advancing field that holds great promise for treating cancer.The recognition of antigens by immune cells is a crucial step in tumor-specific killing,and neoantigens generated by mutations in cancer cells possess high immunogenicity and are selectively expressed in tumor cells,making them an attractive therapeutic target.Currently,neoantigens find utility in various domains,primarily in the realm of neoantigen vaccines such as DC vaccines,nucleic acid vaccines,and synthetic long peptide vaccines.Additionally,they hold promise in adoptive cell therapy,encompassing tumor-infiltrating cells,T cell receptors,and chimeric antigen receptors which are expressed by genetically modified T cells.In this review,we summarized recent progress in the clinical use of tumor vaccines and adoptive cell therapy targeting neoantigens,discussed the potential of neoantigen burden as an immune checkpoint in clinical settings.With the aid of state-of-the-art sequencing and bioinformatics technologies,together with significant advancements in artificial intelligence,we anticipated that neoantigens will be fully exploited for personalized tumor immunotherapy,from screening to clinical application.

Machine Learning-Based Temperature and Wind Forecasts in the Zhangjiakou Competition Zone during the Beijing 2022 Winter Olympic Games

Weather forecasting for the Zhangjiakou competition zone of the Beijing 2022 Winter Olympic Games is a challenging task due to its complex terrain.Numerical weather prediction models generally perform poorly for cold air pools and winds over complex terrains,due to their low spatiotemporal resolution and limitations in the description of dynamics,thermodynamics,and microphysics in mountainous areas.This study proposes an ensemble-learning model,named ENSL,for surface temperature and wind forecasts at the venues of the Zhangjiakou competition zone,by integrating five individual models—linear regression,random forest,gradient boosting decision tree,support vector machine,and artificial neural network(ANN),with a ridge regression as meta model.The ENSL employs predictors from the high-resolution ECMWF model forecast(ECMWF-HRES) data and topography data,and targets from automatic weather station observations.Four categories of predictors(synoptic-pattern related fields,surface element fields,terrain,and temporal features) are fed into ENSL.The results demonstrate that ENSL achieves better performance and generalization than individual models.The root-mean-square error(RMSE) for the temperature and wind speed predictions is reduced by 48.2% and 28.5%,respectively,relative to ECMWF-HRES.For the gust speed,the performance of ENSL is consistent with ANN(best individual model) in the whole dataset,whereas ENSL outperforms on extreme gust samples(42.7% compared with 38.7% obtained by ECMWF-HRES in terms of RMSE reduction).Sensitivity analysis of predictors in the four categories shows that ENSL fits their feature importance rankings and physical explanations effectively.

Degradation potential and diversity of oil-degrading bacteria isolated from the sediments of the Jiaozhou Bay, China

A great deal of oil contaminated the shoreline by the Qingdao oil pipeline explosion in 2013. The four oildegrading consortia were enriched from sediment samples with crude oil as sole carbon and energy sources. The biodiversity and community analysis showed that the Luteibacter, Parvibaculum and a genus belonging to Alcanivoracaceae were found predominant bacteria in the four consortia, which belonged to Proteobacteria. Nine strains exhibiting distinct 16S rRNA gene sequences were isolated from the consortia. These strains were identified to eight genera based on 16S rRNA gene sequences. Five of the nine strains degraded more than 30% of the crude oil in two weeks by gravimetric method. From the analysis of GC-MS, most of the isolated strains tended to degrade n-alkanes rather than PAHs. Five strains showed high degrading ability of the total n-alkanes. Only Strain D2 showed great PAHs degrading ability and the degrading rates ranged from 34.9% to 77.5%. The sequencing analysis of the oil-degrading consortia confirmed that the genus of Alcanivorax was one of the dominant bacteria in Consortia A and E and Strain E4 might be one of the dominant bacteria. The strains obtained in this study demonstrated the potential for oil bioremediation in oil-contaminated beach ecosystems.

Post hoc power analysis:is it an informative and meaningful analysis?

Power analysis is a key component for planning prospective studies such as clinical trials. However, some journals in biomedical and psychosocial sciences ask for power analysis for data already collected and analysed before accepting manuscripts for publication. In this report, post hoc power analysis for retrospective studies is examined and the informativeness of understanding the power for detecting significant effects of the results analysed, using the same data on which the power analysis is based, is scrutinised. Monte Carlo simulation is used to investigate the performance of posthoc power analysis.

3D spiral channels combined with flexible micro-sieve for high-throughput rare tumor cell enrichment and assay from clinical pleural effusion samples

The sieving and enrichment of rare tumor cells from large-volume pleural effusion(PE)samples is a promising technique for cell-based lung tumor diagnosis and drug tests,which features high throughput and recovery,purification,as well as viability rates of rare target cells as the prerequisites for high sensitivity,specificity,and accuracy of tumor cell analysis.In this paper,we propose a three-dimensional(3 D)sieving method for rare tumor cell enrichment,which effectively eliminates the"dead zones"in traditional two-dimensional(2 D)cell filters with a dimension-raising strategy to satisfy the requirements mentioned above.The prototype device was combined with a funnel-shaped holder,a flexible micropore membrane in the middle,and a3 D spiral fluid channel covered on the membrane as a three-layer ice-creaming cone composite structure.Driven by gravity alone,the device performed as follows:(1)20-fold throughput compared with the 2 D commercial planee hich was up to 20 mL/min for a threefold dilution of whole blood sample;(2)high recovery rates of 84.5%±21%,86%±25%,83%±14%for 100,1000,and 10000 cells/mL,respectively,in 30 mL phosphate buffer saline(PBS)sample,and a 100%positive detection rate in the case of≤5 A549 cells in 1 mL PBS;(3)a typical purification rate of 85.5%±9.1%;and(4)a viability rate of>93%.In the demonstration application,this device effectively enriched rare target cells from large volumes(>25 mL)of clinical pleural effusions.The following results indicated that tumor cells were easy-to-discover in the enriched PE samples,and the proliferation capability of purified cells was(>4.6 times)significantly stronger than that of unprocessed cells in the subsequent 6-day culture.The above evaluation indicates that the proposed easily reproducible method for the effective execution of rare cell enrichments and assays is expected to become a practical technique for clinical cell-based tumor diagnosis.

Regional climate response to global warming in the source region of the Yellow River and its impact on runoff

The source region of the Yellow River has experienced obvious climate and discharge changes in recent decades due to global warming, which largely affects the water resources and ecological and environmental security in the Yellow River basin. This study analyzed the changes in runoff and several climate factors in the source region of the Yellow River based on the observed discharges at the Tangnag hydrological station, routine meteorological data from China Meteorological Administration(CMA) stations within and near this source region, and several evaporation datasets. The results indicate that the runoff in the source region was relatively abundant from 1960 to 1989 and then declined sharply afterward. It recovered slightly after 2005 but was still below normal—10% less than that during 1960–1989. Similarly, the precipitation amounts in the source region were relatively low in the 1990s, but they increased significantly after 2003, with an average increase of 31.4 mm or 6% more when compared to that in 1960–1989. In addition, the temperatures in the source region continued to rise from 1960 to 2017, and the evaporation levels also showed an upward trend after 1990. The influences of the spatial and temporal variations in climatic factors on runoff in the source region were then further analyzed. The results indicate that the decreases in precipitation and the number of days of heavy rainfall in the source region from 1990 to 2002 were important reasons for the lower runoff during this period. After 2003, the precipitation in the southeastern part of the source region, which is a key area for runoff generation,increased only to a limited extent, but the evaporation in the entire source region generally increased with increasing temperature,which might have led to the low capacity for actual runoff production in each subbasin and persistent low runoff in the source region. Therefore, such a climate response to global warming in the source region might be unfavorable for increased runoff in the future. The above analysis provides a valuable reference for the future planning and management of water resources in the source region of the Yellow River and the entire Yellow River Basin in the context of warming.

Traumatic brain injury stimulates sympathetic tone-mediated bone marrow myelopoiesis to favor fracture healing

Traumatic brain injury(TBI)accelerates fracture healing,but the underlying mechanism remains largely unknown.Accumulating evidence indicates that the central nervous system(CNS)plays a pivotal role in regulating immune system and skeletal homeostasis.However,the impact of CNS injury on hematopoiesis commitment was overlooked.Here,we found that the dramatically elevated sympathetic tone accompanied with TBI-accelerated fracture healing;chemical sympathectomy blocks TBIinduced fracture healing.TBI-induced hypersensitivity of adrenergic signaling promotes the proliferation of bone marrow hematopoietic stem cells(HSCs)and swiftly skews HSCs toward anti-inflammation myeloid cells within 14 days,which favor fracture healing.Knockout ofβ3-orβ2-adrenergic receptor(AR)eliminate TBI-mediated anti-inflammation macrophage expansion and TBIaccelerated fracture healing.RNA sequencing of bone marrow cells revealed that Adrb2 and Adrb3 maintain proliferation and commitment of immune cells.Importantly,flow cytometry confirmed that deletion ofβ2-AR inhibits M2 polarization of macrophages at 7th day and 14th day;and TBI-induced HSCs proliferation was impaired inβ3-AR knockout mice.Moreover,β3-andβ2-AR agonists synergistically promote infiltration of M2 macrophages in callus and accelerate bone healing process.Thus,we conclude that TBI accelerates bone formation during early stage of fracture healing process by shaping the anti-inflammation environment in the bone marrow.These results implicate that the adrenergic signals could serve as potential targets for fracture management.

Mineralized manganese dioxide channel as the stent coating for in situ precise tumor navigation

Drug-eluting stent(DES)is a promising strategy for esophageal cancer.However,full-covered drug-loaded stents cause damage to non-tumor tissue in the esophagus,and the development controlled-release system to prevent non-tumor tissue injure is currently a major challenge.Here,in situ mineralized manganese dioxide coating on Ce6 embedded electrospun fibers covered stent was developed for effective tumor therapy via intraluminal photodynamic therapy(PDT),which could reduce phototoxicity to normal esophageal tissue.Oxidation of manganese ions,which was previously swelled between fibers,was used to accomplish mineralization.After implantation,the manganese dioxide coating in situ reacts with tumor endogenous H^(+) and H_(2)O_(2),which,on the one hand,could effectively alleviate the hypoxic microenvironment which leads to resistance to PDT,and on the other hand,could expose the Ce6-fibers below the coating for intraluminal PDT.In addition,due to the slow degradation of the coating,this stent could own sustained photodynamic performance for up to one month.Notably,the PDT efficiency of the stent was investigated on orthotopic rabbit esophageal cancer models.Overall,this work suggests that in situ mineralized manganese dioxide coated electrospun fibers covered stent may provide a new strategy for advanced esophageal cancer patients as a functional drug delivery platform.

Conflict resolution for connected automated vehicles at unsignalized roundabouts considering personalized driving behaviours

To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.