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Continuous cropping has resulted in the accumulation of self-toxic substances in faba beans which has restricted their global production. Intercropping is widely used to alleviate these problems. To explore the role of cinnamic acid stress in faba bean physiology and disease resistance, and the potential mitigating effects of intercropping the faba bean with wheat. Faba bean seedlings were grown with or without wheat in both field and hydroponic conditions in the presence of different cinnamic acid concentrations and (FOF), the occurrence of. -mediated wilt and oxidative stress, as well as plant growth indices and the anti-pathogen defense system were analyzed. Cinnamic acid significantly increased pathogenicity, inhibited the activity of defense enzymes and reduced the ability of plants to resist pathogens, indicating the importance of cinnamic acid in the promotion of wilt resulting in reduced seedling growth. Intercropping with wheat improved plant resistance by alleviating cinnamic acid-induced stress, which promoted crop growth and decreased the incidence and disease index of wilt. Cinnamic acid promotes wilt by stimulating pathogen enzyme production and destroying the defense capability of faba bean roots. Intercropping reduces wilt by alleviating the damage caused by cinnamic acid to the defense system of the faba bean root system.

Hepatoblastoma is the most common liver tumor of early childhood, which is usually characterized by unusual hypervascularity. Recently, long non-coding RNAs (lncRNA) have emerged as gene regulators and prognostic markers in several cancers, including hepatoblastoma. We previously reveal that lnRNA-TUG1 is upregulated in hepatoblastoma specimens by microarray analysis. In this study, we aim to elucidate the biological and clinical significance of TUG1 upregulation in hepatoblastoma. We show that TUG1 is significantly upregulated in human hepatoblastoma specimens and metastatic hepatoblastoma cell lines. TUG1 knockdown inhibits tumor growth and angiogenesis in vivo , and decreases hepatoblastoma cell viability, proliferation, migration, and invasion in vitro . TUG1, miR-34a-5p, and VEGFA constitutes to a regulatory network, and participates in regulating hepatoblastoma cell function, tumor progression, and tumor angiogenesis. Overall, our findings indicate that TUG1 upregulation contributes to unusual hypervascularity of hepatoblastoma. TUG1 is a promising therapeutic target for aggressive, recurrent, or metastatic hepatoblastoma.

The current understanding of the microstructural features and mechanical properties of micro-alloyed low carbon steels strengthened by interphase precipitation of nano-sized alloy carbides are critically reviewed in this paper. The experimental results obtained via advanced quantitative characterization have revealed that interphase precipitation is promoted at the ferrite/austenite interface with a relatively lower degree of coherency caused by the deviation from the exact Kurdjumov–Sachs orientation relationship. Its dispersion becomes refined by enlarging the driving force for its precipitation, as adjusted by changing the transformation condition and chemical composition. The occurrence of interphase precipitation can significantly increase the strength of steels due to its large precipitation strengthening, and maintain good ductility as a result of enhanced work-hardening and dynamic recovery in different stages of tensile deformation. Finally, the application of interphase precipitation to ferrite/martensite dual-phase steels, together with our outlook on the challenging points in future research, are briefly explained.

Alpine grassland and the soil on which it is growing in the Qinghai-Tibetan Plateau (QTP) of China is being degraded in an attempt to increase food and feed production for an increasing global population. Our objective was to use soil quality assessment to quantify changes in soil chemical and physical properties at three depth increments (0 to 4, 4 to 10, and 10 to 20 cm) and thus determine the linkages between soil and vegetation changes, the soil element(s) limiting grassland restoration in alpine region, and the ability to restore soil fertility by reestablishing grasslands. The soil and vegetation were sampled in the different types of degraded grasslands, that is, moderately degraded grassland (MDG), heavily degraded grassland (HDG) and severely degraded grassland (SDG) as well as in the reestablished grasslands at different ages, that is, 5-yr restored grassland (5yRG), 7-yr restored grassland (7yRG), and 9-yr restored grassland (9yRG) for comparative study. The results show: (i) decreased water holding capacity and increased soil hardness as vegetative cover declined, (ii) decreased soil organic carbon (OC) and total nitrogen (TN) and increased total soil potassium, (TK) (iii) the establishment of artificial grassland did not restore soil quality or nutrient stocks within degraded grassland soils, and (iv) yearly variations in soil properties at different depths were significant along the degree of grassland degradation. Significant variations of soil physical and chemical parameters might be attributed to loss of the top soil and changes of vegetation composition and soil and textures. Soil quality can be used to assess grassland degradation and restoration in the alpine region. In conclusion, better soil management is needed for restoring the degraded alpine grasslands on the QTP.

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal study of 216 adults with TBM; 73 (34%) were HIV-positive, a factor highly correlated with mortality. We implemented an end-to-end framework to model clinical and imaging features to predict disease progression. Our model used state-of-the-art machine learning models for automatic imaging feature encoding, and time-series models for forecasting, to predict TBM progression. The proposed approach is designed to be robust to missing data via a novel tailored model optimisation framework. Our model achieved a 60% balanced accuracy in predicting the prognosis of TBM patients over the six different classes. HIV status did not alter the performance of the models. Furthermore, our approach identified brain morphological lesions caused by TBM in both HIV and non-HIV-infected, associating lesions to the disease staging with an overall accuracy of 96%. These results suggest that the lesions caused by TBM are analogous in both populations, regardless of the severity of the disease. Lastly, our models correctly identified changes in disease symptomatology and severity in 80% of the cases. Our approach is the first attempt at predicting the prognosis of TBM by combining imaging and clinical data, via a machine learning model. The approach has the potential to accurately predict disease progression and enable timely clinical intervention.

Background Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can enhance these outcomes. Methods We conducted a study on a cohort of 3467 pregnant women during their pregnancy, with a total of 5649 clinical and biochemical records collected. We utilized this dataset as our training dataset to develop a web server called GDMPredictor. The GDMPredictor utilizes advanced machine learning techniques to predict the risk of GDM in pregnant women. We also personalize treatment recommendations based on essential biochemical indicators, such as A1MG, BMG, CysC, CO2, TBA, FPG, and CREA. Our assessment of GDMPredictor's effectiveness involved training it on the dataset of 3467 pregnant women and measuring its ability to predict GDM risk using an AUC and auPRC. Results GDMPredictor demonstrated an impressive level of precision by achieving an AUC score of 0.967. To tailor our treatment recommendations, we use the GDM risk level to identify higher risk candidates who require more intensive care. The GDMPredictor can accept biochemical indicators for predicting the risk of GDM at any period from 1 to 24 weeks, providing healthcare professionals with an intuitive interface to identify high-risk patients and give optimal treatment recommendations. Conclusions The GDMPredictor presents a valuable asset for clinical practice, with the potential to change the management of GDM in pregnant women. Its high accuracy and efficiency make it a reliable tool for doctors to improve patient outcomes. Early identification of high-risk individuals and tailored treatment can improve maternal and fetal health outcomes http://www.bioinfogenetics.info/GDM/ .

s Background This study aimed to evaluate clinical and angiographic outcomes of Y-configuration double-stent-assisted (Y-stent) coiling using two closed-cell stents for wide-necked basilar tip aneurysm (BTA). Materials A total of 25 patients underwent Y-stent coiling using two closed-cell stents as a first-time treatment in 18 (3 ruptured) BTAs, retreatment in 2 BTAs and as a third treatment in 5 wide-necked BTAs. Clinical and angiographic outcomes were evaluated retrospectively. Results Treatment-related complications were three (12.0 %) thromboembolic infarctions due to two acute in-stent thromboses and one embolism. Twenty-two (88 %) patients had favorable outcomes (modified Rankin scale score [mRS], 0–2) during the follow-up period (mean, 30 months; range, 6–54 months). Two patients died: one from initial subarachnoid hemorrhage and the other from intracerebral hemorrhage due to underlying Moyamoya disease. Post-treatment angiograms showed complete occlusion in nine aneurysms, residual neck in 11 aneurysms and residual sac in five aneurysms. Follow-up angiograms were available at least once between 5 to 34 months (mean, 16 months) in 21 patients. Nineteen patients showed improved or stable states (complete occlusion, n  = 17; residual neck, n  = 2). Major recurrences occurred in two BTAs (9.5 %). Those two major recurrent aneurysms had been large-sized aneurysms at the initial coiling procedure. Both showed not only coil compaction but also progressive growth to giant-sized aneurysms and intra-aneurysmal thrombus formation at the Y-stent coiling as a third-time treatment. Conclusions Y-stent coiling using two closed-cell stents is a safe and durable treatment option for wide-necked BTA, but may have limited efficacy for large/giant sized and thrombosed aneurysms.

The control and manipulation of quantum systems without excitation are challenging, due to the complexities in fully modeling such systems accurately and the difficulties in controlling these inherently fragile systems experimentally. For example, while protocols to decompress Bose–Einstein condensates (BECs) faster than the adiabatic timescale (without excitation or loss) have been well developed theoretically, experimental implementations of these protocols have yet to reach speeds faster than the adiabatic timescale. In this work, we experimentally demonstrate an alternative approach based on a machine-learning algorithm which makes progress toward this goal. The algorithm is given control of the coupled decompression and transport of a metastable helium condensate, with its performance determined after each experimental iteration by measuring the excitations of the resultant BEC. After each iteration the algorithm adjusts its internal model of the system to create an improved control output for the next iteration. Given sufficient control over the decompression, the algorithm converges to a solution that sets the current speed record in relation to the adiabatic timescale, beating out other experimental realizations based on theoretical approaches. This method presents a feasible approach for implementing fast-state preparations or transformations in other quantum systems, without requiring a solution to a theoretical model of the system. Implications for fundamental physics and cooling are discussed.

Mountain social‐ecological systems (MtSES) are vital to humanity, providing ecosystem services to over half the planet's human population. Despite their importance, there has been no global assessment of threats to MtSES, even as they face unprecedented challenges to their sustainability. With survey data from 57 MtSES sites worldwide, we test a conceptual model of the types and scales of stressors and ecosystem services in MtSES and explore their distinct configurations according to their primary economic orientation and land use. We find that MtSES worldwide are experiencing both gradual and abrupt climatic, economic, and governance changes, with policies made by outsiders as the most ubiquitous challenge. Mountains that support primarily subsistence‐oriented livelihoods, especially agropastoral systems, deliver abundant services but are also most at risk. Moreover, transitions from subsistence‐ to market‐oriented economies are often accompanied by increased physical connectedness, reduced diversity of cross‐scale ecosystem services, lowered importance of local knowledge, and shifting vulnerabilities to threats. Addressing the complex challenges facing MtSES and catalyzing transformations to MtSES sustainability will require cross‐scale partnerships among researchers, stakeholders, and decision makers to jointly identify desired futures and adaptation pathways, assess trade‐offs in prioritizing ecosystem services, and share best practices for sustainability. These transdisciplinary approaches will allow local stakeholders, researchers, and practitioners to jointly address MtSES knowledge gaps while simultaneously focusing on critical issues of poverty and food security. Plain Language Summary Mountain ecosystems and the human communities that inhabit them deliver critical resources—such as fresh water and timber—to over half the planet's human population. Despite their importance, there has been no global assessment of threats to mountain systems, even as they face unprecedented challenges to their sustainability. With survey data from 57 mountain sites worldwide, we test our understanding of the types of stresses that are threatening mountain systems as well as the resources and benefits that come from mountains. We find that mountain systems worldwide are experiencing both gradual and abrupt climatic, economic, and governance changes. One of the most ubiquitous challenges facing mountain systems is that policies directly affecting mountain systems are being made by those living outside of the mountains themselves. Mountains that support primarily subsistence‐oriented livelihoods in the developing world, especially mixed agriculture and animal husbandry systems, deliver abundant services but are also most at risk. Addressing the complex challenges facing mountain systems will require partnerships among researchers, stakeholders, and decision makers to jointly identify the types of futures they desire and the actions to achieve these. This approach will address knowledge gaps in mountains while simultaneously focusing on critical issues of poverty and food security. Key Points Mountain social‐ecological systems (MtSES) worldwide face climatic, economic, and governance threats; policies made by outsiders are a critical challenge Mountains that support subsistence‐oriented livelihoods deliver abundant cross‐scale ecosystems services, but these MtSES are also most threatened Addressing threats to MtSES requires the united effort of policymakers, land users, scientists, and practitioners at local to global scales

Background The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival. Methods Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs. Results K17 expression had profound effects on the exclusion of intratumoral CD8+ T cells and was also associated with decreased numbers of peritumoral CD8+ T cells, CD16+ macrophages, and CD163+ macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8+ T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations. Conclusions Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.