Explore the vast range of titles available.

Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

Microglia activation is recognized as the hallmark of neuroinflammation. However, the activation profile and phenotype changes of microglia during the process of retinal degeneration are poorly understood. This study aimed to elucidate the time-spatial pattern of microglia distribution and characterize the polarized phenotype of activated microglia during retinal neuroinflammation and degeneration in rd1 ( ) mice, the classic model of inherited retinal degeneration. Retinae of rd1 mice at different postnatal days (P7, P14, P21, P28, P56, and P180) were prepared for further analysis. We found most CD11b or IBA1 microglia expressed Ki-67 and CD68 in rd1 mice and these cells migrated toward the layer of degenerative photoreceptors at the rapid rods degeneration phase from P14 to P28. These microglia exhibited typical ameboid activated shape with round bodies and scarce dendrites, while at late phase at P180, they displayed resting ramified morphology with elongated dendrites. Flow cytometry revealed that the percentage of CD86 CD206 M1 microglia increased markedly in rd1 retinae, however, no significant change was observed in CD206 CD86 M2 microglia. Interestingly, CD86 CD206 microglia, an intermediate state between the two extremes of M1 and M2, increased markedly at the rapid rods degeneration phase. The immunofluorescence images revealed that microglia in rd1 mice highly expressed M1 markers including CD16/32, CD86, and CD40. In addition, increased expression of pro-inflammatory cytokines (TNF-α, IL-6, and CCL2) was observed in rd1 mice. Our findings unfolded a panorama for the first time that microglia conducted distinctive behaviors with the progression of retinal degeneration in rd1 mice. Microglia is activated and particularly polarized to a pro-inflammatory M1 phenotype at the rapid rods degenerative phase, suggesting that the involvement of M1 microglia in the retinal neuroinflammation and degeneration. Most microglia adopted an intermediate polarization \"M1½\" state in rd1, revealing that microglia orchestrated a complicated continuous spectrum in degenerative retina.

Background Atherogenic index of plasma (AIP) has been reported to be associated with cardiovascular diseases. However no study has yet systematically evaluated the association between AIP and obesity and its advantage in obesity prediction compared with conventional lipid components. Methods A total of 6465 participants aged over 30 years were included in this study. Blood lipid components including triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured, and AIP was calculated as log 10 (TG/HDL-C). Pearson correlation analyses, multivariable logistic analyses and predictive analyses were used to evaluate the association and discrimination ability between AIP, four conventional lipid profiles and obesity. Results Subjects in the higher quartiles of AIP all had a significantly increased risk of obesity compared with those in the lowest quartile ( P for trend< 0.01). AIP showed a stronger association with obesity than the conventional lipid components as the pearson coefficient reached up to 0.372 and the adjusted odds ratio was 5.55. Using AIP rather than HDL-C and TG significantly improved risk prediction for obesity (AUC improvement = 0.011, P  = 0.011; Continuous net reclassification index = 29.55%, P  < 0.01; Category net reclassification index = 6.06%; Integrated discrimination improvement = 0.68%, P  < 0.01). Conclusions Higher AIP level was positively and strongly associated with obesity. AIP is a novel and better biomarker associated with obesity. Controlling the AIP level would be more helpful for the prevention of obesity.

Cystic echinococcosis (CE), caused by Echinococcus granulosus sensu lato (E. granulosus s.l.), remains a significant zoonotic parasitic disease affecting both livestock and humans. It arises from the ingestion of food and water contaminated with canine feces containing E. granulosus eggs. The detection of these eggs in canine feces is essential for guiding effective preventative measures against the disease. Therefore, the development of a novel accurate, rapid, and visually interpretable point-of-care test is crucial for controlling CE. We combined recombinase polymerase amplification (RPA) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) with a CRISPR-associated protein 12a (Cas12a) system, forming the RPA-CRISPR/Cas12a assay. This assay targeted the E. granulosus mitochondrial nad2 gene and utilized a lateral flow strip for visual readout. To improve field applicability, we integrated a simple and cost-effective NaOH-Based DNA extraction method. Clinical validation included testing DNA extracted from eighteen canine fecal samples, followed by comparison with quantitative PCR (qPCR) and two commercial enzyme-linked immunosorbent assay (ELISA) kits. The RPA-CRISPR/Cas12a assay showed a detection limit of 1 fg/μL DNA, without any cross-reactivity with related tapeworms such as Echinococcus multilocularis, Dipylidium caninum, Taenia hydatigera, Taenia multiceps, and Taenia pisiformis. When applied to 62 clinical fecal samples from dogs, the RPA-CRISPR/Cas12a assay demonstrated 68% sensitivity, while the developed RPA-CRISPR/Cas12a-NaOH assay exhibited 45% sensitivity. In the field performance comparison of the RPA-CRISPR/Cas12a and the RPA-CRISPR/Cas12a-NaOH assay with qPCR and two ELISA kits, the sensitivity, consistency rate, and Youden's index suggested good or fair agreement with the currently employed detection methods. This study describes the development and validation of the RPA-CRISPR/Cas12a and RPA-CRISPR/Cas12a-NaOH assays for detecting E. granulosus in canine feces. The developed assays surpassed previous detection methods in providing enhanced diagnostic sensitivity and enabling point-of-care testing. Moreover, these assays hold potential for surveilling E. granulosus in low-income countries.

The data are sent by the nodes taking part in frequency hopping communications (FHC) utilising carrier frequencies and time slots that are pseudo-randomly assigned. Because of this, a high degree of protection against eavesdropping and anti-interference capabilities is provided. When using FHC in an environment, sharing time and frequency resources, avoiding collisions, and differentiating services are all made more complex as a result of this. A protocol for FHC that is based on dispersed wireless networks is presented by the authors of this research. It is a mechanism for multiple access control, which is prioritised and distributed. The ratio of empty channels metric can be found in the previous sentence. It is possible to provide priority in channel access by assigning different preset ratios of empty channel thresholds to the various traffic classes. Frames from frequency spread segments that have a partial collision are included as well. An analytical model is simulated for the analysis in terms of collision probability, transmission probability, and frame service time in order to carry out a theoretical examination of the performance of FHC. The objective of this inquiry is to determine how well FHC works. The analytical model has been proven correct by the exhaustive simulations as well as the theoretical findings. Cloud platforms are often used in the instruction of the most cutting-edge machine learning techniques of today, such as deep neural networks. This is done in order to take advantage of the cloud's capacity to scale elastically. In order to satisfy the criteria of these sorts of applications, federated learning, has been proposed as a distributed machine learning solution. This is done in order to fulfil the requirements of these kinds of applications. In federated learning (FL), even though everyone who uses the system works together to train a model, nobody ever shares their data with anybody else. Each user trains a local model with their own data, and then communicates the updated models with a FL server so that the data can be aggregated and a global model can be constructed. This process ensures that each user's model is unique. This process is repeated until a global model has been developed. This kind of training not only reduces the amount of network overhead that is necessary to transfer data to a centralised server, but it also safeguards the personal information of the users. Within the framework of this work, we looked at the feasibility of using the FL technique of learning on the many devices that are part of the dispersed network. On a centralised server, we conduct an analysis of the performance of the FL model by comparing its accuracy and the amount of time it takes to train using a range of various parameter value combinations. Additionally, the accuracy of these federated models may be made to reach a level that is comparable to that of the accuracy of central models.

Active mobile elements in the human genome can create novel mobile element insertions (MEIs) in somatic tissues. Detection of somatic MEIs, particularly those with low mosaicism, remains a significant challenge due to sequencing artifacts and alignment errors. Existing methods lack sensitivity or require biased manual inspection. Here we present RetroNet, a deep learning algorithm that encodes sequencing reads into images to identify somatic MEIs with as few as two reads. Trained on diverse datasets, RetroNet outperforms previous methods and eliminates the need for manual examinations. RetroNet achieves high precision (0.885) and recall (0.579) on a cancer cell line, detecting insertions in just 1.79% of cells. RetroNet is also effective for degraded DNA, like circulating tumor DNA. This tool is applicable to the rapidly generated short-read sequencing data and has the potential to provide further insights into the functional and pathological implications of somatic retrotranspositions. Detection of somatic mobile element insertions (MEIs), particularly those with low mosaicism, remains a significant challenge. This study presents RetroNet, a deep learning method that transforms sequencing reads into images to detect somatic MEIs, enabling accurate discovery of rare insertions with very low read support.

The irrational use of nitrogen (N) fertilizer has become a major threat to soil quality and food security, resulting in serious ecological and environmental problems. Holistic approaches to N fertilizer application are required to maintain a high N utilization efficiency (NUE) and sustainable agriculture development. Biochar is an efficient carbon-rich material for amending soil quality and promoting crop N uptake, but knowledge pertaining to the promoting effects of biochar application on N fertilizers is still limited. In this study, a field plot experiment was designed to detect the combined effects of biochar (0, 15 and 30 t ha−1) and N fertilizer (204, 240 and 276 kg N ha−1) on the soil nutrient levels, NUE, plant growth performance and crop production of maize. The results demonstrated that the combined application of N fertilizer and biochar can significantly decrease the soil pH and increase the contents of soil organic carbon, mineral N, available phosphorus and potassium. The crop N uptake and N content were largely promoted by the addition of N fertilizer and biochar, resulting in higher leaf photosynthetic efficiency, dry matter accumulation and grain yields. The highest yields (14,928 kg ha−1) were achieved using 276 kg N ha−1 N fertilizer in combination with 15 t ha−1 biochar, and the highest NUE value (46.3%) was reached with 204 kg N ha−1 N of fertilizer blended with 30 t ha−1 of biochar. According to structural equation modeling, the beneficial effects of N fertilizer and biochar on the plant biomass of maize were attributed to the direct effects related to soil chemical properties and plant growth parameters. In conclusion, N fertilizer combined with biochar application is an effective strategy to enhance the utilization of N fertilizer and crop production for maize by increasing soil fertility, improving plant crop uptake and promoting plant growth.

Synthetic micro/nanomotors have been extensively exploited over the past decade to achieve active transportation. This interest is a result of their broad range of potential applications, from environmental remediation to nanomedicine. Nevertheless, it still remains a challenge to build a fast-moving biodegradable polymeric nanomotor. Here we present a light-propelled nanomotor by introducing gold nanoparticles (Au NP) onto biodegradable bowl-shaped polymersomes (stomatocytes) via electrostatic and hydrogen bond interactions. These biodegradable nanomotors show controllable motion and remarkable velocities of up to 125 μm s −1 . This unique behavior is explained via a thorough three-dimensional characterization of the nanomotor, particularly the size and the spatial distribution of Au NP, with cryogenic transmission electron microscopy (cryo-TEM) and cryo-electron tomography (cryo-ET). Our in-depth quantitative 3D analysis reveals that the motile features of these nanomotors are caused by the nonuniform distribution of Au NPs on the outer surface of the stomatocyte along the z-axial direction. Their excellent motile features are exploited for active cargo delivery into living cells. This study provides a new approach to develop robust, biodegradable soft nanomotors with application potential in biomedicine. The development of methodologies to construct fast-moving, biodegradable polymeric nanomotors remains a challenge. Here, the authors present a light-propelled nanomotor by adorning the surface of bowl-shaped stomatocytes with gold nanoparticles achieving particle translocation in mammalian cells through the temporary disruption of the cell membrane.

Cystic echinococcosis (CE) is caused by the infection of Echinococcus granulosus sensu lato (E. granulosus s.l.), one of the most harmful zoonotic helminths worldwide. Infected dogs are the major source of CE transmission. While praziquantel-based deworming is a main measure employed to control dog infections, its efficacy is at times compromised by the persistent high rate of dog re-infection and the copious discharge of E. granulosus eggs into the environment. Therefore, the dog vaccine is a welcome development, as it offers a substantial reduction in the biomass of E. granulosus. This study aimed to use previous insights into E. granulosus functional genes to further assess the protective efficacy of six recombinant proteins in dogs using a two-time injection vaccination strategy. We expressed and combined recombinant E. granulosus triosephosphate isomerase (rEgTIM) with annexin B3 (rEgANXB3), adenylate kinase 1 (rEgADK1) with Echinococcus protoscolex calcium binding protein 1 (rEgEPC1), and fatty acid-binding protein (rEgFABP) with paramyosin (rEgA31). Beagle dogs received two subcutaneous vaccinations mixed with Quil-A adjuvant, and subsequently orally challenged with protoscoleces two weeks after booster vaccination. All dogs were sacrificed for counting and measuring E. granulosus tapeworms at 28 days post-infection, and the level of serum IgG was detected by ELISA. Dogs vaccinated with rEgTIM&rEgANXB3, rEgADK1&rEgEPC1, and rEgFABP-EgA31 protein groups exhibited significant protectiveness, with a worm reduction rate of 71%, 57%, and 67%, respectively, compared to the control group (P < 0.05). Additionally, the vaccinated groups exhibited an inhibition of worm growth, as evidenced by a reduction in body length and width (P < 0.05). Furthermore, the level of IgG in the vaccinated dogs was significantly higher than that of the control dogs (P < 0.05). These verified candidates may be promising vaccines for the prevention of E. granulosus infection in dogs following two injections. The rEgTIM&rEgANXB3 co-administrated vaccine underscored the potential for the highest protective efficacy and superior protection stability for controlling E. granulosus infections in dogs.