GDF11 improves hippocampal neurogenesis and cognitive abilities in diabetic mice by reducing neural inflammation.

BACKGROUND: The cognitive decline associated with type 2 diabetes (T2D) is often attributed to compromised hippocampal neurogenesis and exacerbated neural inflammation. This study investigates the therapeutic potential of growth differentiation factor 11 (GDF11) in reversing these neurodegenerative processes in diabetic mice. RESULT: We utilized a murine model of T2D and examined the effects of GDF11 on learning, memory, neurogenesis, and neuroinflammatory markers. Our results indicate that diabetic mice exhibit significant deficits in cognitive function, mirrored by reduced hippocampal neurogenesis and increased neuroinflammation. Chronic administration of GDF11 was observed to significantly enhance cognitive abilities, as evidenced by improved performance in learning and memory tasks. Concurrently, GDF11 treatment restored neural activity and promoted the regeneration of new neurons within the hippocampus. Inflammatory profiling revealed a reduction in neuroinflammatory markers, which was further supported by reduced microglia numbers. To delineate the role of neuroinflammation, we pharmacologically depleted microglia, leading to a restoration of neurogenesis and cognitive functions in diabetic mice. CONCLUSION: These findings endorse the hypothesis that GDF11 exerts its beneficial effects by modulating neuroinflammatory pathways. Consequently, GDF11 represents a promising intervention to ameliorate diabetes-induced cognitive impairments and neural degeneration through its anti-inflammatory properties.

Impacts of climate change on winter wheat net primary production: the regulatory role of crop management.

BACKGROUND: The Huang-Huai-Hai Plain (3HP) is the main agricultural area in China. Although climate change (CC) and crop management (CM) are considered factors affecting the winter wheat net primary production (NPP) in this region, their effects remain unclear. In the present study, we evaluated the relative contributions of CC and CM to winter wheat aboveground NPP (ANPP) in the 3HP and the relationships between climatic factors and ANPP using the first-order difference method from 2000 to 2020. RESULTS: CM had a greater influence on the ANPP of winter wheat than did CC. However, the relative contribution of CM to ANPP gradually decreased in humid and dry sub-humid regions with the development of winter wheat. Furthermore, in areas characterized by low temperatures and limited precipitation, CC became the dominant factor contributing to ANPP, indicating that varieties resilient to drought and cold should be selected in these regions. Minimum and average temperatures were the dominant factors driving spatiotemporal variations in ANPP during the early stage of winter wheat growth, whereas maximum temperature constrained growth throughout the winter wheat growth cycle. When winter wheat entered the vigorous growth stage, precipitation and solar radiation replaced temperature as the driving factors influencing winter wheat growth. CONCLUSION: The results of the present study provide guidance for optimizing winter wheat crop management in the 3HP. © 2023 Society of Chemical Industry.

Effects of climate change and deep fertilization on the growth and yield of winter wheat in the Loess Plateau of China.

BACKGROUND: Global temperature is projected to rise continuously under climate change, negatively impacting the growth and yield of winter wheat. Optimizing traditional agricultural measures is necessary to mitigate potential winter wheat yield losses caused by future climate change. This study aims to explore the variations in winter wheat growth and yield on the Loess Plateau of China under future climate change, identify the key meteorological factors affecting winter wheat growth and yield, and analyze the differences in winter wheat yield and root characteristics under different fertilization depths. RESULTS: Meteorological data from 20 General Circulation Models were applied to drive the Decision Support System for Agrotechnology Transfer model, simulating the future growth characteristics of winter wheat under various fertilization depths. The Random Forest model was used to determine the relative importance of meteorological factors influencing winter wheat yield, root length density and leaf area index. The results showed that temperature and high emission concentration were primary factors influencing crop yield under future climate change. The temperature increase projected from 2021 to 2100 would be anticipated to shorten the phenology period of winter wheat by 2-16 days and reduce grain yield by 2.9-12.7% compared to the period from 1981 to 2020. Conversely, the root length density and root weight of winter wheat would increase by 1.2-10.9% and 0.2-24.1%, respectively, in the future, and excessive allocation of root system resources was identified as a key factor contributing to the reduction in winter wheat yield. Compared with the shallow fertilization treatment (N5), the deep fertilization treatments (N15 and N25) increased the proportion of roots in the deep soil layer (30-60 cm) by 2.7-10.2%. Because of the improvement in root structure, the decline in winter wheat yield under deep fertilization treatments in the future is expected to be reduced by 1.2% to 6.5%, whereas water use efficiency increases by 1.1% to 2.4% compared to the shallow fertilization treatment. CONCLUSION: The deep fertilization treatment can enhance the root structure of winter wheat and increase the proportion of roots in the deep soil layer, thereby effectively mitigating the decline in winter wheat yield under future climate change. Overall, optimizing fertilization depth effectively addresses the reduced winter wheat yield risks and agricultural production challenges under future climate change. © 2024 Society of Chemical Industry.

Interactions between Helicobacter pylori infection and host metabolic homeostasis: A comprehensive review.

The microbiota actively and extensively participates in the regulation of human metabolism, playing a crucial role in the development of metabolic diseases. Helicobacter pylori (H. pylori), when colonizing gastric epithelial cells, not only induces local tissue inflammation or malignant transformation but also leads to systemic and partial changes in host metabolism. These shifts can be mediated through direct contact, toxic components, or indirect immune responses. Consequently, they influence various molecular metabolic events that impact nutritional status and iron absorption in the host. Unraveling the intricate and diverse molecular interaction links between H. pylori and human metabolism modulation is essential for understanding pathogenesis mechanisms and developing targeted treatments for related diseases. However, significant challenges persist in comprehensively understanding the complex association networks among H. pylori itself, the infected host's status, the host microbiome, and the immune response. Previous metabolomics research has indicated that H. pylori infection and eradication may selectively shape the metabolite and microbial profiles of gastric lesions. Yet, it remains largely unknown how these diverse metabolic pathways, including isovaleric acid, cholesterol, fatty acids, and phospholipids, specifically modulate gastric carcinogenesis or affect the host's serum metabolism, consequently leading to the development of metabolic-associated diseases. The direct contribution of H. pylori to metabolisms still lacks conclusive evidence. In this review, we summarize recent advances in clinical evidence highlighting associations between chronic H. pylori infection and metabolic diseases, as well as its potential molecular regulatory patterns.

Optimization of sowing date for spring maize in China's loess plateau based on presowing temperature and soil water content.

BACKGROUND: The sowing date of spring maize in China's Loess Plateau is often restricted by the presowing temperature and soil water content (SWC). The effective measurement of the effects of presowing temperature and SWC on the sowing date is a major concern for agricultural production in this region. In this paper, we considered the average daily air temperature of ˃10 °C in the 7 days before sowing. The Decision Support System for Agrotechnology Transfer (DSSAT) model was used to simulate a spring maize yield under distinct combinations of SWC and sowing date for 51 years (1970-2020). Subsequently, through the cumulative probability distribution function, the contribution of presowing SWC to the spring maize yield was quantified, and the optimal sowing date of spring maize in each production location was determined. RESULTS: The results revealed that the daily average temperature of ˃10 °C for 7 days consecutively can be used effectively as the basis for the simulation of spring maize sowing date. The presowing SWC affected the spring maize yield but did not change the optimal sowing date. When the SWC of each study site is about 70% of the field capacity, Wenshui and Yuanping can properly delay sowing, and Lin county can sow early to obtain a higher yield. CONCLUSION: This study provides an effective approach for optimizing presowing soil moisture management and the sowing date of spring maize in the semiarid regions of the Loess Plateau. © 2023 Society of Chemical Industry.

DNA-MnO2 Nanoconjugates Investigation and Application for Electrochemical Polymerase Chain Reaction.

Manganese dioxide (MnO2) nanosheets are emerging for biomedical applications with excellent physical and chemical properties. Adsorption of DNA on MnO2 is important for biosensing, bioimaging, and therapy. Nevertheless, current fundamental understanding about the interaction is preliminary. Herein, UV-vis absorption spectra are applied to systematically explore the biointerfacial interaction between DNA and MnO2 with the factors of salt concentration, pH value, temperature, DNA concentration, and length. The results offer important fundamental insights into the investigation of DNA-MnO2 nanocomposites. Meanwhile, the optimal parameters are applied to construct a screen-printed electrode (SPE) modified with polymerase chain reaction (PCR) primer-decorated MnO2 nanosheets. An electrochemical PCR system is then developed for ultrasensitive detection of circulating tumor DNA (ctDNA). The limit of detection is determined to be 0.1 fM, and high selectivity is demonstrated. Combining the merits of SPE, DNA-MnO2 nanosheets, and an amplified reaction, this developed strategy shows great promise in bioanalysis, clinical disease diagnosis, and biomedicine applications.

Acidic and hypoxic tumor microenvironment regulation by CaO2-loaded polydopamine nanoparticles.

Hypoxia and high accumulation of lactic acid in the tumor microenvironment provide fertile soil for tumor development, maintenance and metastasis. Herein, we developed a calcium peroxide (CaO2)-loaded nanostructure that can play a role of "one stone kill two birds", i.e., acidic and hypoxic tumor microenvironment can be simultaneously regulated by CaO2 loaded nanostructure. Specifically, CaO2-loaded mesoporous polydopamine nanoparticles modified with sodium hyaluronate (denoted as CaO2@mPDA-SH) can gradually accumulate in a tumor site. CaO2 exposed in acidic microenvironment can succeed in consuming the lactic acid with oxygen generation simultaneously, which could remodel the acid and hypoxia tumor microenvironment. More importantly, the relief of hypoxia could further reduce lactate production from the source by down-regulating the hypoxia inducible factor-1α (HIF-1α), which further down-regulated the glycolysis associated enzymes including glycolysis-related glucose transporter 1 (GLUT1) and lactate dehydrogenase A (LDHA). As a result, CaO2@mPDA-SH alone without the employment of other therapeutics can dually regulate the tumor hypoxia and lactic acid metabolism, which efficiently represses tumor progression in promoting immune activation, antitumor metastasis, and anti-angiogenesis.

Evaluating the accuracy of ARMA and multi-index methods for predicting winter wheat maturity date.

BACKGROUND: Accurate and timely prediction of regional winter wheat maturity date can provide essential information to improve the management of agriculture and avoid declines in the yield and quality of crops. In this paper, we propose the use of an autoregressive moving-average model to predict vegetation indices on 1, 9, and 17 May each year, and applied them to the methods of evaluating crop maturity based on vegetation indices. Growing degree days and a widely applied local empirical method were selected to explore and compare the feasibility of several methods. We analyzed winter wheat harvested from the Guanzhong Plain during 2003-2013 and used leave-one-out cross-validation to compare and verify the performance of the maturity prediction methods. RESULTS: The results demonstrated that (i) the vegetation index methods and growing degree days methods predicted maturity with higher accuracy than did the widely applied local empirical method, and (ii) the two-step filtering method based on future meteorological data from The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble exhibited the highest prediction accuracy on 1 May and had the lowest error fluctuation range on 17 May. CONCLUSION: These results provide new insights for predicting regional crop maturity, deploying agricultural harvesting equipment in various regions, and avoiding decreases in crop yields caused by adverse weather. © 2021 Society of Chemical Industry.

Metformin restores hippocampal neurogenesis and learning and memory via regulating gut microbiota in the obese mouse model.

Numerous studies have shown that over-nutritional obesity may lead to pre-diabetes, type 2 diabetes and cognitive decline. As the degree of metabolic disorders increases, the cognitive decline is getting worse. However, the cellular events that cause this cognitive dysfunction is yet to be clarified. We used a high-fat diet (HFD) consumption-induced obesity mouse model to test the effects of metformin on the hippocampal neurogenesis and learning and memory abilities of obese mice. 5-Bromo-2'-deoxyuridine (BrdU) labelling and retrovirus labeling were applied to detect hippocampal newborn neurons. Behavioral experiments were used to detect learning and memory abilities of mice. 16S rRNA gene sequencing was performed to detect the composition of gut microbiota. The positron emission tomography (PET) was conducted to detect the energy metabolism activity of different mouse brain regions. Our results reveal that metformin restores the impairment of neurogenesis in the dentate gyrus and finally prevents the cognitive decline of the obese mice. Moreover, the therapeutic effects of metformin are achieved by regulating the composition of gut microbiota of mice, which may inhibit microglia activation and neuroinflammation in the brain of obese mice. This study suggests that metformin may be taken as a promising candidate for the intervention of cognitive decline related to imbalance of gut microbiota caused by obesity.

Ratiometric fluorescence method for ctDNA analysis based on the construction of a DNA four-way junction.

We present a novel ratiometric fluorescent biosensor for ctDNA analysis based on the construction of a DNA four-way junction (FWJ). Three fuel strands for the FWJ are firstly designed and prepared. Another essential strand for the formation of the structure is the DNA product generated from target ctDNA initiated strand displacement amplification. With the transformation of the DNA structure, the FRET states of two fluorophores change and the ratiometric fluorescence response can be recorded to indicate the level of the initial ctDNA. The proposed method also has excellent capability to discriminate mismatches and shows potential practical utility for clinical samples.

Recognition of Helicobacter pylori by protein-targeting aptamers.

BACKGROUND: Helicobacter pylori (H pylori) is a disease-causing pathogen capable of surviving under acidic conditions of the human stomach. Almost half of the world's population is infected with H pylori, with gastric cancer being the most unsatisfactory prognosis. Although H pylori has been discovered 30 years ago, the effective treatment and elimination of H pylori continue to be problematic. MATERIALS AND METHODS: In our study, we screened nucleic acid aptamers using H pylori surface recombinant antigens as targets. Trypsin was used for separating aptamers that were bound to proteins. Following nine rounds of screening, we performed sequence similarity analyses to assess whether the aptamers can recognize the target protein. Two sequences with desirable recognition ability were selected for affinity detection. Aptamer Hp4 with the strongest binding ability to the H pylori surface recombinant antigen was chosen. After optimization of the binding conditions, we conducted specificity tests for Hp4 using Escherichia coli, Staphylococcus aureus, Vibrioanguillarum, and H pylori. RESULTS: The data indicated that the aptamer Hp4 had an equilibrium dissociation constant (Kd ) of 26.48 ± 5.72 nmol/L to the target protein. This aptamer was capable of exclusively detecting H pylori cells, without displaying any specificity for other bacteria. CONCLUSIONS: We obtained a high-affinity aptamer for H pylori, which is expected to serve as a new molecular probe for detection of H pylori.

Electrochemical Determination of Ca2+ Based On Recycling Formation of Highly Selective DNAzyme and Gold Nanoparticle-Mediated Amplification.

Calcium ion (Ca2+) plays a critical and indispensable role in many physiological and biochemical processes in the human body. In this report, we demonstrate a novel electrochemical method for the determination of the Ca2+ level aided by three functional DNA probes and gold nanoparticles (AuNPs). It affords high selectivity in sensing Ca2+ over other metal cations, which is due to the adoption of the DNAzyme at the electrode interface with exceptionally high binding ability. This method also integrates recycling formation of DNAzyme and AuNPs-mediated amplification; thus, high sensitivity is promised. Therefore, this work provides a favorable way to probe Ca2+ for biomedical applications.

Colorimetric theophylline aggregation assay using an RNA aptamer and non-crosslinking gold nanoparticles.

The authors are presenting a rapid method for the determination of theophylline using unique non-crosslinking gold nanoparticle (AuNP) aggregation. An RNA aptamer against theophylline is firstly split into two RNA fragments which then interact with bare AuNPs. The two RNA probes cause an enhancement of the salt tolerance of AuNPs. However, in the presence of theophylline, the RNA probes form a complex with theophylline so that less RNA probes are available to protect the AuNPs from salt-induced aggregation. Theophylline induced aggregation of AuNPs is accompanied by a color change from red to blue. The color change can be detected visually and via UV-vis absorptiometry by ratioing the absorbances at 650 and 520 nm. The ratio increases linearly in the 0.1 to 20 µM theophylline concentration range, with a 67 nM limit of detection. The method is highly sensitive and selective. Graphical abstract Single-stranded split RNA aptamers (R1 and R2) protect gold nanoparticles (AuNPs) from salt-induced non-crosslinking aggregation. After recognition of theophylline by the RNA probe, the unprotected AuNPs aggregate and undergo a color change from red to blue, and this is used to quantify the theophylline concentration.

Assessment of herbicide transport and distribution in subsurface environments of an orange field.

The demand for assessing both the variability of risk areas and the intensity of pollutant load rates on pesticide transferring to waters in China has been increasingly vigorous in recent decades. Therefore, to explore the transport of linuron with rainfall and irrigation in canopy-soil systems, an integrated pesticide transport modeling system has been selected and verified for simulating the three-phase linuron environmental fate in an orange field of the Three Gorges Reservoir (TGR) area. Results demonstrate that spatio-temporal distributions of linuron in surface soil primarily depend on its properties, rainfall, irrigation, and its applications; the peak levels of linuron in subsurface and deep soil are closely related to the cumulative and delayed effects. The findings may be used for policy supporting of soil-water-crop-pesticide management in an agricultural field of the TGR area.

Long-term outcomes of IVUS-guided and angiography-guided drug-eluting stent implantation for left main coronary artery disease: a retrospective consort study.

BACKGROUND: In patients with unprotected left main coronary artery disease (ULMCAD), this study compared the long-term prognosis of drug-eluting stent insertion guided by intravascular ultrasonography (IVUS) vs. angiography. PATIENTS AND METHODS: This retrospective consort investigation was performed in December 2021. This analysis included 199 patients who underwent IVUS-guided (IVUS group, n = 81) or angiography-guided (angiography group, n = 118) drug-eluting stent implantation at the Affiliated Hospital of Inner Mongolia Medical University between September 2013 and September 2018. Major adverse cardiac events (MACE) were defined as cardiovascular death, sudden cardiac death, myocardial infarction. RESULTS: The IVUS group had considerably lower proportions of MACE within 1 year postoperatively (P = 0.002) and cardiac mortality within 3 years postoperatively (P = 0.018) compared to the angiography group. However, after adjusting for confounding variables, the hazard ratio for 3-year cardiac mortality was similar between the two groups (P = 0.28). In the IVUS group, there was considerably greater minimum lumen diameter (MLD) (P = 0.046), and reduced frequencies of target vessel restenosis (P < 0.050) and myocardial infarction (MI) (P = 0.024) compared to the angiography group. Cox regression analysis for 3-year cardiac mortality found that MSD was independently associated with low cardiac mortality (HR = 0.1, 95% CI: 0.01-14.92, P = 0.030). CONCLUSION: IVUS-guided drug-eluting stent implantation may lead to better long-term prognosis in patients with ULMCAD, and MSD may be a predictor for lower cardiac mortality.

Development and advancements in rodent MRI-based brain atlases.

Rodents, particularly mice and rats, are extensively utilized in fundamental neuroscience research. Brain atlases have played a pivotal role in this field, evolving from traditional printed histology atlases to digital atlases incorporating diverse imaging datasets. Magnetic resonance imaging (MRI)-based brain atlases, also known as brain maps, have been employed in specific studies. However, the existence of numerous versions of MRI-based brain atlases has impeded their standardized application and widespread use, despite the consensus within the academic community regarding their significance in mice and rats. Furthermore, there is a dearth of comprehensive and systematic reviews on MRI-based brain atlases for rodents. This review aims to bridge this gap by providing a comprehensive overview of the advancements in MRI-based brain atlases for rodents, with a specific focus on mice and rats. It seeks to explore the advantages and disadvantages of histologically printed brain atlases in comparison to MRI brain atlases, delineate the standardized methods for creating MRI brain atlases, and summarize their primary applications in neuroscience research. Additionally, this review aims to assist researchers in selecting appropriate versions of MRI brain atlases for their studies or refining existing MRI brain atlas resources, thereby facilitating the development and widespread adoption of standardized MRI-based brain atlases in rodents.

Factor analysis of hydrologic services in water-controlled grassland ecosystems by InVEST model and geodetector.

Water conservation is highly important for a successful desert grassland ecosystem, but there was no comprehensive view on how to assess influencing factors in managing and addressing water yield and water conservation in desert steppe. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which is specifically used for the assessment of ecosystem services, was combined with geographic detectors to identify the priority areas for water conservation function and analyze the driving factors of water conservation in the Tabu River Basin, Inner Mongolia Autonomous Region, China, using different meteorological data sources. (i) The InVEST model has the advantage of modeling water yield and water conservation at spatial scales by fusion downscaling data. High water yield mainly occurs in the southern hilly mountainous areas, low water yield in the northern desert and grassland areas, and between the two in the central agro-pastoral areas; the multi-year average water conservation and water yield based on the InVEST model are 3.3 and 16 mm, respectively. (ii) Water yield and water conservation roughly show a transitional phenomenon of "high in the south and low in the north." The water yield and water conservation per unit area of the Tabu River Basin are relatively large for construction land, unused land, and cropland, relatively small for grassland and forestland, and basically zero for water bodies. Forest land has the strongest water conservation capacity, followed by grassland and farmland, while the order of water yield capacity is the opposite. (iii) Precipitation shows the strongest explanatory power for water yield (q = 0.427), followed by land use types (q = 0.411). The precipitation ∩ actual evapotranspiration has the strongest explanatory power for water yield (q = 0.87). The explanatory power of water yield on water conservation is the strongest (q = 0.752), followed by precipitation (q = 0.4), and the water yield ∩ soil has the greatest explanatory power on water conservation (q = 0.91). These findings are crucial for promoting regional hydrologic services and can provide a water resources management strategy for decision-makers.

Study on the relationship between regional soil desertification and salinization and groundwater based on remote sensing inversion: A case study of the windy beach area in Northern Shaanxi.

Soil desertification and salinization are important environmental concerns in arid regions, and their relationship with groundwater change must be further clarified. However, the relationships among soil desertification, salinization, and groundwater are difficult to investigate on a large spatiotemporal scale using traditional ground surveys. In the windy beach area in Northern Shaanxi (WBANS), desertification and salinization problems coexist; therefore, this area was selected as the study area. The feasibility of implementing large-scale remote sensing inversions to identify the degree of desertification and salinization was verified based on measured data, and the degree of influence of groundwater burial depth (GBD) on desertification and salinization was quantified using the geodetector and residual trend analysis methods. The results showed that the GBD in the WBANS presented an increasing trend and the degree of salinization showed a decreasing trend. Moreover, the joint influence of the unique natural environment and anthropogenic activities has led to increases in fractional vegetation cover and considerable improvements in the ecological environment. The intensity of desertification explained by GBD in the WBANS increased significantly (p < 0.01) at a rate of change of 0.0190/year, with high q-values above 0.66 for both Yuyang and Shenmu. The contribution rate of potential evapotranspiration and precipitation to salinization in Yuyang and Shenmu was >97 %, and the contribution rate of GBD to salinization in Dingbian, Jingbian, and Hengshan was 34.78 %, 31.15 %, and 29.41 %, respectively. Overall, the suitable GBD in the WBANS is 2-4 m. The study results provide a reference for research on the inversion, monitoring, and prevention of desertification and salinization dynamics on a large spatiotemporal scale and offer a scientific basis for rationally determining GBD.

Higher dietary live microbe intake is associated with a lower risk of sarcopenia.

OBJECTIVE: This study aimed to investigate the potential association between dietary live microbe intake and sarcopenia. METHODS: Data from 5368 participants were gathered from the National Health and Nutrition Examination Survey (NHANES). Dietary information was assessed using a self-report questionnaire. The participants were categorized into low, medium, and high dietary live microbe groups. Sarcopenia was defined according to the National Institutes of Health (NIH) definition (appendicular skeletal muscle mass/body mass index <0.789 for men and <0.512 for women). Multivariate regression analysis and stratified analyses were performed. RESULTS: After adjusting for potential confounding factors, individuals in the high dietary live microbe group exhibited a lower prevalence of sarcopenia compared to those in the low dietary live microbe group. The adjusted odds ratio (with 95% confidence intervals) was 0.63 (0.44-0.89) (p for trend <0.05). Subgroup analyses indicated a potential difference in the impact of dietary live microbe intake on sarcopenia between individuals with and without diabetes (p for interaction = 0.094). CONCLUSION: Higher dietary live microbe intake was associated with a lower risk of sarcopenia.