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Improving energy utilization efficiency is a crucial means to achieve energy conservation, emission reduction, and green development. At present, to establish a high-quality development framework and satisfy the growing need for a better life among all its people, China must steadfastly pursue the path of green development. Although China’s substantial economic scale and achievements in ecological civilization construction provide favorable conditions for green transformation, there remains a significant gap compared to developed countries in the application of green and clean technologies. Confronted with technological bottlenecks, leveraging emerging technologies such as industrial robots from the new round of scientific and technological revolutions to improve the green total factor energy efficiency (GTFEE) is of critical importance to China’s green development. This study explores the potential impact of industrial robots on enhancing China’s GTFEE. It begins by reviewing the current research landscape in this field, highlighting its shortcomings, and theorizing potential impact pathways of industrial robots. Subsequently, the paper analyzes data from 2010 to 2019 on the usage of industrial robots and GTFEE across 276 cities at the prefectural level or above in China. Through empirical regression models that incorporate control variables and interaction terms, the study investigates the specific impacts of industrial robots on energy efficiency and their mechanisms of action. The results indicate that industrial robots significantly enhance the GTFEE of Chinese cities, especially in the Northeastern region. Industrial robots notably improve the GTFEE in resource-based cities, old industrial bases, and low-carbon pilot cities. Additionally, robots indirectly boost GTFEE by increasing labor productivity. Enhanced levels of green innovation and environmental regulations also positively moderate the effectiveness of industrial robots in improving energy efficiency. The findings of this research can assist local government agencies in coordinating and implementing policies that are conducive to green development, making better use of industrial robots to serve the people, and are of significant importance for promoting the transformation of China’s economy and society towards high-quality development.

As a crucial regulator influencing tumor progression, nicotinamide adenine dinucleotide (NAD+) is widely acknowledged. However, its role in endometrial cancer (EC) is not completely understood. In this study, we aimed to develop an NAD+metabolic-related genes (NMRGs) risk signature that could reflect the prognosis of EC patients and their responsiveness to immunotherapy and chemotherapy. Data from The Cancer Genome Atlas (TCGA) databases and the Molecular Signatures Database (MSigDB) confirmed two distinct NMRG subtypes in EC patients using consensus clustering, and a risk score was constructed utilizing an NAD+-related prognostic signature depending on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves were employed to assess the model’s precision. Additionally, we used Gene Set Enrichment Analysis (GSEA) to predict the biological signaling pathways that might be involved. We also explored the role of the risk score in immune cell infiltration, tumor mutation burden (TMB), immunotherapy, and chemotherapy. Our study established a prognostic risk signature based on six NMRGs, and we observed that the high-risk group was associated with a poorer prognosis. Furthermore, we identified a strong correlation between the high-risk group and several pathways, including DNA replication, cell cycle, and mismatch repair. Lastly, our findings highlighted the influence of NMRGs on the regulation of immune infiltration in EC. Therefore, this signature holds potential value in predicting the prognosis of EC patients and guiding their management, including decisions regarding immunotherapy and chemotherapy, ultimately improving the accuracy of EC patient care.

ObjectiveTo study the effect of type 2 diabetes mellitus(T2DM)on overall ovarian reserve and pregnancy outcomes during assisted reproductive technology (ART) among childbearing infertile women.DesignRetrospective cohort study.SettingThe Reproductive Medicine Special Hospital, The First Hospital of Lanzhou University, between January 2019 and December 2022.Patient(s)A total of 265 infertile female patients aged 20–45 years who underwent in vitro fertilization-embryo transfer (IVF-ET), intracytoplasmic sperm injection-embryo transfer (ICSI-ET), or rescue intracytoplasmic sperm injection-embryo transfer (RICSI-ET) in the first fresh cycle.Intervention(s)None.Main Outcome Measure(s)Serum Anti-Müllerian Hormone (AMH) levels, clinical pregnancy rate (CPR), live birth rate (LBR), and abortion rate (AR) in the T2DM group and non-T2DM group.Result(s)Patients with T2DM showed statistically decreased levels of AMH compared to the non-T2DM group. During ovarian stimulation, those with T2DM required significantly higher total and initial doses of gonadotropin (GN), although they had fewer retrieved oocytes and worse pregnancy outcomes than the non-T2DM group. Multivariate logistic regression analysis adjusting for confounding factors showed that T2DM alone was an independent risk factor for CPR and LBR (adjusted odds ratio [a OR], 0.458, adjusted 95% confidence interval [CI], 0.235-0.891, P = 0.022; a OR, 0.227, 95% CI, 0.101-0.513, P

The molecular mechanisms leading to the establishment of immunological memory are inadequately understood, limiting the development of effective vaccines and durable antitumor immune therapies. Here, we show that ectopic OCA-B expression is sufficient to improve antiviral memory recall responses, while having minimal effects on primary effector responses. At peak viral response, short-lived effector T cell populations are expanded but show increased Gadd45b and Socs2 expression, while memory precursor effector cells show increased expression of Bcl2, Il7r, and Tcf7 on a per-cell basis. Using an OCA-B mCherry reporter mouse line, we observe high OCA-B expression in CD4+ central memory T cells. We show that early in viral infection, endogenously elevated OCA-B expression prospectively identifies memory precursor cells with increased survival capability and memory recall potential. Cumulatively, the results demonstrate that OCA-B is both necessary and sufficient to promote CD4 T cell memory in vivo and can be used to prospectively identify memory precursor cells. [ABSTRACT FROM AUTHOR]

The mechanical environment of a cell can have many effects, but whether it impacts the DNA sequence of a cell has remained unexamined. To investigate this, we developed a live-cell method to measure changes in chromosome numbers. We edited constitutive genes withGFP or RFP tags on single alleles and discovered that cells that lose Chromosome reporters (ChReporters) become nonfluorescent. We applied our new tools to confined mitosis and to inhibition of the putative tumor suppressor myosin-II. We quantified compression of mitotic chromatin in vivo and demonstrated that similar compression in vitro resulted in cell death, but also rare and heritable ChReptorter loss. Myosin-II suppression rescued lethal multipolar divisions and maximized ChReporter loss during three-dimensional (3D) compression and two-dimensional (2D) lateral confinement, but not in standard 2D culture. ChReporter loss was associated with chromosome mis-segregation, rather than just the number of divisions, and loss in vitro and in mice was selected against in subsequent 2D cultures. Inhibition of the spindle assembly checkpoint (SAC) caused ChReporter loss in 2D culture, as expected, but not during 3D compression, suggesting a SAC perturbation. Thus, ChReporters enable diverse studies of viable genetic changes, and show that confinement and myosin-II affect DNA sequence and mechanoevolution. [ABSTRACT FROM AUTHOR]

Cell proliferation and migration play important parts in ovarian cancer progression. BMP9, as one of the members of the TGF-β superfamily and BMP family, plays a diverse and significant array of biological roles, including cell differentiation, proliferation, apoptosis, tumorigenesis, and metabolism. However, the role and mechanism of BMP9 in ovarian cancer progression remains uncertain. We found that the expression of BMP9 was increased in human ovarian cancer cell lines, which induced Notch1 intracellular domain (NICD1) accumulation. And we also found the expression abundance of BMP9 is low in ovarian cancer cells. Thus, we generated recombinant adenoviruses overexpressing BMP9 to perform the research. We found that overexpression of BMP9 promoted ovarian cancer cell proliferative viability, cell cycle progression, cell migration in vitro, and accelerated subcutaneous tumor growth in vivo, which was inhibited by dominant-negative mutant Notch1 recombinant adenoviruses. Besides, we also demonstrated that silencing of BMP9 by recombinant adenoviruses inhibited ovarian cancer cell viability and migration in vitro. Additionally, BMP9-induced ovarian cancer cell progression also involved the elevation of HES2, c-Myc, MMP9, and Cyclin D1, as well as repressed expression of p27. Together, these results revealed that BMP9 acts as a promoting factor in ovarian cancer progression, and overexpression of BMP9 promotes ovarian cancer progression and growth via Notch1 signaling. Thereby our research may provide new insight into the pathogenesis of ovarian cancer and BMP9-Notch1 signaling may serve as a novel therapeutic target axis for ovarian cancer treatment. [ABSTRACT FROM AUTHOR]

Objective: The study aimed to investigate changes in basal levels of the inhibitory γ-aminobutyric acid (GABA) neurotransmitter in the sensorimotor cortex (SMC) and cortical gyrification in patients with Parkinson’s disease (PD), which could further identify potential imaging biomarkers for PD, particularly in patients with early-onset Parkinson’s disease (EOPD). Method: Fifty patients with PD (EOPD: 10, late-onset Parkinson’s disease [LOPD]: 40) and fifty-two age- and gender-matched healthy controls (HC) underwent GABA-edited 1H MRS of the SMC and high-resolution 3D T1-weighted brain imaging. GABA levels and local gyrification index (LGI) were calculated to assess GABAergic and cortical gyrification deficits in PD. Result: The Pearson correlation coefficients revealed significant negative associations between eight indicators, including GABA/Cr level and local gyrification index (LGI) of specific cortical regions (precentral, postcentral, entorhinal, superiortemporal, posteriorcingulate, cuneus, and transversetemporal cortex), and the likelihood of Parkinson’s disease (r

Visualization techniques are effective tools in diagnosis and therapy for biomedical applications. Due to the unavoidable shortcomings of single optical or magnetic resonance imaging, the introduction of dual functional imaging system is of great significance. Herein a new Gd1-xNdx(CO3)OH@SiO2 core–shell nanostructure were developed to fulfill the corresponding demands. Uniform nanospheres were acquired with surface modification and coated with thickness tunable silica shells. The samples presented strong luminescence penetrating biological tissue, due to the wide spectral region covering NIR I & II window of Nd3+ under 808 nm laser excitation. On the other hand, distinct contrast enhancement could be viewed for in vitro and in vivo MRI trials, which generates from high paramagnetic relaxation of Gd3+ and well dispersibility caused by silica shells. Along with the non-toxicity proved by the low concentration of leaching Gd3+ and nice biocompatibility of silica coated nanospheres, it is a superior candidate for NIR and MRI dual functional imaging platform in biological applications.

BackgroundFrontal lobe epilepsy (FLE) is the second most common type of focal epilepsy, however, imaging studies of FLE have been far less than Temporal lobe epilepsy (TLE) and the structural findings were not consistent in previous literature.ObjectInvestigate the changes in cortical thickness in patients with FLE and the alteration of the structural covariance networks (SCNs) of cortical thickness with graph-theory.MethodThirty patients with FLE (18 males/12 females; 28.33 ± 11.81 years) and 27 demographically matched controls (15 males/12 females; 29.22 ± 9.73 years) were included in this study with high-resolution structural brain MRI scans. The cortical thickness was calculated, and structural covariance network (SCN) of cortical thickness were reconstructed using 68 × 68 matrix and analyzed with graph-theory approach.ResultCortical thickness was not significantly different between two groups, but path length and node betweenness were significantly increased in patients with FLE, and the regional network alterations were significantly changed in right precentral gyrus and right temporal pole (FDR corrected, p

Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumonia patients.

Although there has been a lot of research in multi-label learning task, little attention has been paid on the weak label problem, in which only a subset of labels has been assigned to each instance in the training set. The extreme form of weak label learning is to predict all the labels from just one label set in the training phase. In this paper, we focus on dealing with this kind of weak label learning task, which is commonly met in old legacy information system, and it is also called “Hercules Learning.”We propose a label-group-optimization-based Hercules learning algorithm, which divides the entire label set into multiple groups according to the classifier's capability to distinguish them, so for each group, we can train a classifier which can predict instance's label within the group with high accuracy. The experimental results show that our algorithm is obviously superior to the existing weak label learning algorithm.