Behavioral responses to predator and heterospecific alarm calls are habitat-specific in Eurasian tree sparrows.

Acoustic communication plays a vital role in predator-prey interactions. Although habitat structure has been shown to affect anti-predator tactics, little is known about how animals vary their behaviors in response to predator calls or heterospecific alarm calls in different environments. Here we used sound playbacks to test the responses of Eurasian tree sparrows (Passer montanus) foraging in harvested/unharvested rice paddy and open residential area. In the first experiment, we tested their behavioral responses to dove calls, male common cuckoo (Cuculus canorus) calls, hawk-like calls mimicked by female common cuckoo, sparrowhawk (Accipiter nisus) calls, and human yell calls produced to scare birds (predator signal playbacks). In the second experiment, we tested their behavioral responses to the Japanese tit's (Parus minor) territorial songs and alarm calls (heterospecific alarm signal playbacks). Results showed that the tree sparrows had less fleeing in unharvested ripe rice paddy than in harvested rice paddy and open residential area. In predator signal playbacks, call type affected the escape behavior of sparrows in unharvested rice paddy and open residential area but not harvested rice paddy. In alarm signal playbacks, tit alarm calls evoked more fleeing than territorial songs in harvested rice paddy and open residential area but not unharvested rice paddy. These results suggest that anthropogenic habitat changes may influence avian anti-predator tactics.

Exploring the performance of protected areas in alleviating future human pressure.

Protected areas (PAs) are effective in mitigating human pressures, yet their future pressure alleviating effects remain unclear. In this study, we employed the ConvLSTM model to forecast the future human footprint and analyzed human pressure trends using Theil-Sen median and Mann-Kendall tests. We further evaluated the mitigating effects of PAs within their buffer zones (1-10 km) and the contributions of different IUCN categories of PAs to mitigating human pressure using linear regression models. The results indicate that by 2035, the average human pressure value is expected to increase by 11%, with trends exhibiting a polarized pattern. Furthermore, PAs also effectively mitigate human pressure within their 1 km buffer zones. Different categories of PAs vary in their effectiveness in mitigating human pressure, and stricter conservation areas are not always the most effective. This study can offer insights for evaluating the effectiveness of PAs in reducing human pressure and advocate for their targeted management in urban areas.

Genetic identification of human remains from the Korean War.

The genetic identification of skeletal remains from Chinese People's Volunteers (CPVs) of the Korean War has been challenging because of the degraded DNA samples and the lack of living close relatives. This study established a workflow for identifying CPVs by combining Y-chromosome short tandem repeats (Y-STRs), mitochondrial DNA (mtDNA) hypervariable regions I and II, autosomal STRs (aSTRs), and identity-informative SNPs (iiSNPs). A total of 20 skeletal remains of CPVs and 46 samples from their alleged relatives were collected. The success rate of DNA extraction from human remains was 100%. Based on Y-STRs, six remains shared the same male lineages with their alleged relatives. Meanwhile, mtDNA genotyping supports two remains sharing the same maternal lineages with their alleged relatives. Likelihood ratios (LRs) were further obtained from 27 aSTRs and 94 iiSNPs or 1936 iiSNPs to confirm their relationship. All joint pedigree LRs were >100. Finally, six remains were successfully identified. This pilot study for the systematic genetic identification of CPVs from the Korean War can be applied for the large-scale identification of CPVs in the future.

NEPE Propellant Mesoscopic Modeling and Damage Mechanism Study Based on Inversion Algorithm.

To accurately characterize the mesoscopic properties of NEPE (Nitrate Ester Plasticized Polyether) propellant, the mechanical contraction method was used to construct a representative volume element (RVE) model. Based on this model, the macroscopic mechanical response of NEPE propellant at a strain rate of 0.0047575 s-1 was simulated and calculated, and the parameters of the cohesive zone model (CZM) were inversely optimized using the Hooke-Jeeves algorithm by comparing the simulation results with the results of the uniaxial tensile test of NEPE propellants. Additionally, the macroscopic mechanical behavior of NEPE composite solid propellants at strain rates of 0.00023776 s-1 and 0.023776 s-1 was also predicted. The mesoscopic damage evolution process of NEPE propellants was investigated by the established model. The study results indicate that the predicted curves are relatively consistent with the basic features and change trends of the test curves. Therefore, the established model can effectively simulate the mesoscopic damage process of NEPE composite solid propellants and their macroscopic mechanical properties.

Self-Assembly of Heterogeneous Ferritin Nanocages for Tumor Uptake and Penetration.

Well-defined nanostructures are crucial for precisely understanding nano-bio interactions. However, nanoparticles (NPs) fabricated through conventional synthesis approaches often lack poor controllability and reproducibility. Herein, a synthetic biology-based strategy is introduced to fabricate uniformly reproducible protein-based NPs, achieving precise control over heterogeneous components of the NPs. Specifically, a ferritin assembly toolbox system is developed that enables intracellular assembly of ferritin subunits/variants in Escherichia coli. Using this strategy, a proof-of-concept study is provided to explore the interplay between ligand density of NPs and their tumor targets/penetration. Various ferritin hybrid nanocages (FHn) containing human ferritin heavy chains (FH) and light chains are accurately assembled, leveraging their intrinsic binding with tumor cells and prolonged circulation time in blood, respectively. Further studies reveal that tumor cell uptake is FH density-dependent through active binding with transferrin receptor 1, whereas in vivo tumor accumulation and tissue penetration are found to be correlated to heterogeneous assembly of FHn and vascular permeability of tumors. Densities of 3.7 FH/100 nm2 on the nanoparticle surface exhibit the highest degree of tumor accumulation and penetration, particularly in tumors with high permeability compared to those with low permeability. This study underscores the significance of nanoparticle heterogeneity in determining particle fate in biological systems.

Correction: Lactobacillus fermentum F40-4 ameliorates hyperuricemia by modulating the gut microbiota and alleviating inflammation in mice.

Correction for 'Lactobacillus fermentum F40-4 ameliorates hyperuricemia by modulating the gut microbiota and alleviating inflammation in mice' by Jiayuan Cao et al., Food Funct., 2023, 14, 3259-3268, https://doi.org/10.1039/D2FO03701G.

Oral Milk-Derived Extracellular Vesicles Inhibit Osteoclastogenesis and Ameliorate Bone Loss in Ovariectomized Mice by Improving Gut Microbiota.

Milk-derived extracellular vesicles can improve intestinal health and have antiosteoporosis potential. In this paper, we explored the effects of bovine raw milk-derived extracellular vesicles (mEVs) on ovariectomized (OVX) osteoporotic mice from the perspective of the gut-bone axis. mEVs could inhibit osteoclast differentiation and improve microarchitecture. The level of osteoporotic biomarkers in OVX mice was restored after the mEVs intervened. Compared with OVX mice, mEVs could enhance intestinal permeability, reduce endotoxin levels, and improve the expression of TNF-α, IL-17, and IL-10. 16S rDNA sequencing indicated that mEVs altered the composition of gut microbiota, specifically for Bacteroides associated with short-chain fatty acids (SCFAs). In-depth analysis of SCFAs demonstrated that mEVs could restore acetic acid, propionic acid, valeric acid, and isovaleric acid levels in OVX mice. Correlation analysis revealed that changed gut microbiota and SCFAs were significantly associated with gut inflammation and osteoporotic biomarkers. This study demonstrated that mEVs could inhibit osteoclast differentiation and improve osteoporosis by reshaping the gut microbiota, increasing SCFAs, and decreasing the level of pro-inflammatory cytokines and osteoclast differentiation-related factors in OVX mice. These findings provide evidence for the use of mEVs as a food supplement for osteoporosis.

A Magnetic-Optical Triple-Mode Lateral Flow Immunoassay for Sensitive and Rapid Detection of Respiratory Adenovirus.

Human respiratory adenovirus (ADV) is a highly infectious respiratory virus with potential for pandemics. There are currently no specific drugs to treat ADV worldwide, so early rapid detection of ADV infection is essential. In this study, we developed an innovative magnetic-optical triple-mode lateral flow immunoassay (LFIA) using magnetic quantum dots as immunomarkers. This novel approach addresses the need for rapid and accurate ADV detection, allowing for multimodal quantitative/semiquantitative analysis of magnetic, fluorescent, and visible signals within a mere 15 min. The lower limit of detection (LOD) for magnetic, fluorescent, and visual signals was determined to be 5.6 × 103, 1.2 × 103, and 1.95 × 104 copies/mL, respectively. The detection range for ADV using this approach was 1.2 × 103-5 × 107 copies/mL. Additionally, semiquantitative analysis, which is user-friendly and does not necessitate specialized equipment, was successfully implemented. Notably, seven respiratory viruses showed no cross-reactivity with the generated LFIA test strips. The intrabatch repeatability exhibited a coefficient of variation (CV) of less than 5%, while the interbatch repeatability had a CV of less than 15%. Furthermore, recovery values ranged from 95% to 106.8% for samples analyzed concurrently with dual signals at the same spiking concentration. The assay developed in this study boasts a wide detection range and exceptional sensitivity and specificity. This technique is exceptionally well-suited for on-site rapid detection, with the potential for personal self-testing and early ADV infection diagnosis. Its versatility extends to a broad array of application scenarios.

A nanogap-enhanced SERS nanotag-based lateral flow assay for ultrasensitive and simultaneous monitoring of SARS-CoV-2 S and NP antigens.

A lateral flow assay (LFA) strip based on dual 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB)-encoded satellite Fe3O4@Au (Mag@Au) SERS tags with nanogap is reported for  ultrasensitive and simultaneous diagnosis of two SARS-CoV-2 functional proteins. Composed of Fe3O4 core, satellite gold shell with nanogaps, and double-layer DTNB, the Mag@Au nanoparticles with an average size of 238 nm were designed as multifunctional tags to efficiently enrich the target SARS-CoV-2 protein from complex samples, significantly enhancing the SERS signal of the LFA strip and provide quantitative SERS detection of analyte on test lines. The developed dual DTNB-encoded satellite Mag@Au-based LFA allowed simultaneous quantification of spike (S) protein and nucleocapsid (NP) protein with detection limits of 23 pg mL-1 and 2 pg mL-1, respectively, lower than commercial ELISA kits and reported SERS-LFA detection system-based Au NPs and Fe3O4@3 nm Au MNPs. This magnetic SERS-LFA also showed high performance of multi-variant strain detection and further distinguished clinical samples of Omicron variant infection, demonstrating the potential of in situ detection of respiratory virus diseases.

Serum Protein Fishing for Machine Learning-Boosted Diagnostic Classification of Small Nodules of Lung.

Diagnosis of benign and malignant small nodules of the lung remains an unmet clinical problem which is leading to serious false positive diagnosis and overtreatment. Here, we developed a serum protein fishing-based spectral library (ProteoFish) for data independent acquisition analysis and a machine learning-boosted protein panel for diagnosis of early Non-Small Cell Lung Cancer (NSCLC) and classification of benign and malignant small nodules. We established an extensive NSCLC protein bank consisting of 297 clinical subjects. After testing 5 feature extraction algorithms and six machine learning models, the Lasso algorithm for a 15-key protein panel selection and Random Forest was chosen for diagnostic classification. Our random forest classifier achieved 91.38% accuracy in benign and malignant small nodule diagnosis, which is superior to the existing clinical assays. By integrating with machine learning, the 15-key protein panel may provide insights to multiplexed protein biomarker fishing from serum for facile cancer screening and tackling the current clinical challenge in prospective diagnostic classification of small nodules of the lung.

City-level building operation and end-use carbon emissions dataset from China for 2015-2020.

The building sector, which accounts for over 20% of China's total energy-related carbon emissions, has great potential to reduce emissions and is critical to achieving China's emissions peak and carbon neutrality targets. However, the lack of data on operational carbon emissions and end-use carbon emissions in the building sector at the city level has become a major barrier to the development of building energy conservation policies and carbon peaking action plans. This study uses a combination of "top-down" and "bottom-up" methods to account for the operational carbon emissions of buildings in 321 cities in China from 2015 to 2020. The energy consumption in buildings is further broken down into six end uses: central heating, distributed heating, cooking and water heating (C&W), lighting, cooling, appliances and others (A&O). The dataset can serve as a reference to support city-level policies on peak building emissions and is of great value for the improvement of the carbon emissions statistical accounting system.

Machine-Learning-Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes.

Nanozymes are nanomaterials that exhibit enzyme-like biomimicry. In combination with intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials science, chemical engineering, bioengineering, biochemistry, and disease theranostics. Recently, the heterogeneity of published results has highlighted the complexity and diversity of nanozymes in terms of consistency of catalytic capacity. Machine learning (ML) shows promising potential for discovering new materials, yet it remains challenging for the design of new nanozymes based on ML approaches. Alternatively, ML is employed to promote optimization of intelligent design and application of catalytic materials and engineered enzymes. Incorporation of the successful ML algorithms used in the intelligent design of catalytic materials and engineered enzymes can concomitantly facilitate the guided development of next-generation nanozymes with desirable properties. Here, recent progress in ML, its utilization in the design of catalytic materials and enzymes, and how emergent ML applications serve as promising strategies to circumvent challenges associated with time-expensive and laborious testing in nanozyme research and development are summarized. The potential applications of successful examples of ML-aided catalytic materials and engineered enzymes in nanozyme design are also highlighted, with special focus on the unified aims in enhancing design and recapitulation of substrate selectivity and catalytic activity.

Building a Better Silver Bullet: Current Status and Perspectives of Non-Viral Vectors for mRNA Vaccines.

In recent years, messenger RNA (mRNA) vaccines have exhibited great potential to replace conventional vaccines owing to their low risk of insertional mutagenesis, safety and efficacy, rapid and scalable production, and low-cost manufacturing. With the great achievements of chemical modification and sequence optimization methods of mRNA, the key to the success of mRNA vaccines is strictly dependent on safe and efficient gene vectors. Among various delivery platforms, non-viral mRNA vectors could represent perfect choices for future clinical translation regarding their safety, sufficient packaging capability, low immunogenicity, and versatility. In this review, the recent progress in the development of non-viral mRNA vectors is focused on. Various organic vectors including lipid nanoparticles (LNPs), polymers, peptides, and exosomes for efficient mRNA delivery are presented and summarized. Furthermore, the latest advances in clinical trials of mRNA vaccines are described. Finally, the current challenges and future possibilities for the clinical translation of these promising mRNA vectors are also discussed.

Effect of Extracelluar Vesicles Derived from Akkermansia muciniphila on Intestinal Barrier in Colitis Mice.

Inflammatory bowel disease (IBD) is a chronic and recurrent disease. It has been observed that the incidence and prevalence of IBD are increasing, which consequently raises the risk of developing colon cancer. Recently, the regulation of the intestinal barrier by probiotics has become an effective treatment for colitis. Akkermansia muciniphila-derived extracellular vesicles (Akk EVs) are nano-vesicles that contain multiple bioactive macromolecules with the potential to modulate the intestinal barrier. In this study, we used ultrafiltration in conjunction with high-speed centrifugation to extract Akk EVs. A lipopolysaccharide (LPS)-induced RAW264.7 cell model was established to assess the anti-inflammatory effects of Akk EVs. It was found that Akk EVs were able to be absorbed by RAW264.7 cells and significantly reduce the expression of nitric oxide (NO), TNF-α, and IL-1ß (p < 0.05). We explored the preventative effects on colitis and the regulating effects on the intestinal barrier using a mouse colitis model caused by dextran sulfate sodium (DSS). The findings demonstrated that Akk EVs effectively prevented colitis symptoms and reduced colonic tissue injury. Additionally, Akk EVs significantly enhanced the effectiveness of the intestinal barrier by elevating the expression of MUC2 (0.53 ± 0.07), improving mucus integrity, and reducing intestinal permeability (p < 0.05). Moreover, Akk EVs increased the proportion of the beneficial bacteria Firmicutes (33.01 ± 0.09%) and downregulated the proportion of the harmful bacteria Proteobacteria (0.32 ± 0.27%). These findings suggest that Akk EVs possess the ability to regulate immune responses, protect intestinal barriers, and modulate the gut microbiota. The research presents a potential intervention approach for Akk EVs to prevent colitis.

[Construction of a 10rolGLP-1-expressing glucose-lowing Saccharomyces cerevisiae by CRISPR/Cas9 technique].

To develop a novel glucose-lowering biomedicine with potential benefits in the treatment of type 2 diabetes, we used the 10rolGLP-1 gene previously constructed in our laboratory and the CRISPR/Cas9 genome editing technique to create an engineered Saccharomyces cerevisiae strain. The gRNA expression vector pYES2-gRNA, the donor vector pNK1-L-PGK-10rolGLP-1-R and the Cas9 expression vector pGADT7-Cas9 were constructed and co-transformed into S. cerevisiae INVSc1 strain, with the PGK-10rolGLP-1 expressing unit specifically knocked in through homologous recombination. Finally, an S. cerevisiae strain highly expressing the 10rolGLP-1 with glucose-lowering activity was obtained. SDS-PAGE and Western blotting results confirmed that two recombinant strains of S. cerevisiae stably expressed the 10rolGLP-1 and exhibited the desired glucose-lowering property when orally administered to mice. Hypoglycemic experiment results showed that the recombinant hypoglycemic S. cerevisiae strain offered a highly hypoglycemic effect on the diabetic mouse model, and the blood glucose decline was adagio, which can avoid the dangerous consequences caused by rapid decline in blood glucose. Moreover, the body weight and other symptoms such as polyuria also improved significantly, indicating that the orally hypoglycemic S. cerevisiae strain that we constructed may develop into an effective, safe, economic, practical and ideal functional food for type 2 diabetes mellitus treatment.

Microwave ablation versus laparoscopic resection for hepatocellular carcinoma in patients with clinically significant portal hypertension: a propensity score-matched study of postoperative liver decompensation.

OBJECTIVES: The study of postoperative liver decompensation after microwave ablation (MWA) for hepatocellular carcinoma (HCC) in patients with clinically significant portal hypertension (CSPH) is still lacking. The purpose of the present study was to compare the postoperative liver decompensation after MWA and laparoscopic resection (LR) for HCC in patients with CSPH. METHODS: The present retrospective study enrolled 222 HCC patients with CSPH who underwent MWA (n = 67) or LR (n = 155). Postoperative liver decompensation, complications, postoperative hospital stays, and overall survival were analyzed. Factors associated with postoperative liver decompensation were identified. RESULTS: After propensity score matching, the postoperative liver decompensation rate was significantly lower in the MWA group than that in the LR group (15.5% versus 32.8%, p = 0.030). The multivariable regression analysis identified that type of treatment (MWA vs. LR, odds ratio [OR] 0.44; 95% confidence interval [CI], 0.21-0.91; p = 0.026) and Child-Pugh B (OR, 2.86; 95% CI, 1.24-6.61; p = 0.014) were independent predictors for postoperative liver decompensation. The rate of complications for patients in the MWA group was significantly lower than that in the LR group (p < 0.001). And MWA showed shorter postoperative hospital stays than LR (3 days vs. 6 days, p < 0.001). Overall survival rate between the two groups was not significantly different (p = 0.163). CONCLUSION: Compared with laparoscopic resection, microwave ablation has a lower rate of postoperative liver decompensation and might be a better option for HCC patients with CSPH. CLINICAL RELEVANCE STATEMENT: Microwave ablation exhibited a lower incidence of postoperative liver decompensation in comparison to laparoscopic resection, thereby conferring greater advantages to hepatocellular carcinoma patients with clinically significant portal hypertension. KEY POINTS: •Postoperative liver decompensation rate after microwave ablation was lower than that of laparoscopic resection for hepatocellular carcinoma in patients with clinically significant portal hypertension. •Microwave ablation showed shorter postoperative hospital stays than laparoscopic resection. •Microwave ablation had fewer complications than laparoscopic resection.

A Social Recommendation Model Based on Basic Spatial Mapping and Bilateral Generative Adversarial Networks.

Social recommender systems are expected to improve recommendation quality by incorporating social information when there is little user-item interaction data. Therefore, how to effectively fuse interaction information and social information becomes a hot research topic in social recommendation, and how to mine and exploit the heterogeneous information in the interaction and social space becomes the key to improving recommendation performance. In this paper, we propose a social recommendation model based on basic spatial mapping and bilateral generative adversarial networks (MBSGAN). First, we propose to map the base space to the interaction and social space, respectively, in order to overcome the issue of heterogeneous information fusion in two spaces. Then, we construct bilateral generative adversarial networks in both interaction space and social space. Specifically, two generators are used to select candidate samples that are most similar to user feature vectors, and two discriminators are adopted to distinguish candidate samples from high-quality positive and negative examples obtained from popularity sampling, so as to learn complex information in the two spaces. Finally, the effectiveness of the proposed MBSGAN model is verified by comparing it with both eight social recommendation models and six models based on generative adversarial networks on four public datasets, Douban, FilmTrust, Ciao, and Epinions.

The relationship between sublingual immunotherapy for allergic rhinitis and the risk of symptoms in patients with COVID-19 infection.

To evaluated the risk ratio of Allergic rhinitis (AR) people on the symptoms after COVID-19 infection, and explored the relationship between AR and the symptoms after COVID-19 infection. An observational study was performed of people from outpatient department of the Hospital of Chengdu University of Chinese Medicine. Participants completed an electronic survey and between January 10 to January 20, 2023. We divided the participants into three groups according to the disease information of the population: non-AR people group (AR-N), AR patients with sublingual immunotherapy group (AR-S), and AR patients with conventional therapy group (AR-C). A total of 1116 participants were included in the study, with an average age of 21.76 ± 8.713, women accounted for 62.5%, men accounted for 37.5%. The final results showed that the risk of most symptoms after AR-C infection was not different from that of AR-N, except for sore throat, dry and itchy, chest distress, shortness of breath, and dyspnea. AR-S could effectively reduce the risk of post-infection symptoms including: dry and itchy (OR = 0.484, 95%CI: 0.335-0.698), pain (OR = 0.513, 95%CI:0.362-0.728), cough (OR = 0.506, 95% CI:0.341-0.749), expectoration (OR = 0.349, 95% CI:0.244-0.498), fever (OR = 0.569, 95% CI:0.379-0.853), head and body pain (OR = 0.456, 95% CI:0.323-0.644), fatigue (OR = 0.256, 95% CI:0.177-0.371), cold limbs (OR = 0.325, 95%CI:0.227-0.465), diarrhea (OR = 0.246, 95% CI:0.132-0.457), constipation (OR = 0.227, 95%CI:0.100-0.513), hyposmia (OR = 0.456, 95% CI:0.296-0.701), hypogeusia (OR = 0.397, 95% CI:0.259-0.607), chest distress (OR = 0.534, 95% CI:0.343-0.829), shortness of breath (OR = 0.622, 95% CI:0.398-0.974), palpitations (OR = 0.355, 95% CI:0.206-0.613). The risk of symptoms after COVID-19 infection in allergic rhinitis population receiving sublingual immunotherapy is lower.

Genetic Variation of Magnaporthe oryzae Population in Hunan Province.

Studies on the population structure and variation of Magnaporthe oryzae in fields are of great significance for the control of rice blast disease. In this study, a total of 462 isolates isolated from different areas of Hunan Province in 2016 and 2018 were analyzed for their population structure and variation tendency. The results showed that from 2016 to 2018, the concentration of fungal races of M. oryzae increased and the diversity decreased; furthermore, 218 isolates in 2016 belonged to ZA, ZB, ZC, ZE, ZF and ZG, with a total of 6 groups and 29 races, in which the dominant-population ZB group accounted for 66.2%; meanwhile, in 2018, 244 isolates were classified into 4 groups and 21 races, including ZA, ZB, ZC and ZG, in which the dominant-population ZB group accounted for 72.54%. In 2018, isolates of ZD, ZE and ZF populations were absent, and the number of total races and isolates of the ZA and ZC groups decreased. Fungal pathogenicity was identified, with 24 monogenic lines (MLs) carrying 24 major R genes. The resistance frequency of R genes to fungal isolates in 2018 decreased significantly, in which except Pikm was 64.5%, the other monogenic lines were less than 50%. Rep-PCR analysis for isolates of Guidong in Hunan also showed that fungal diversity decreased gradually. The influence of R genes on fungal variation was analyzed. The pathogenicity of isolates purified from Xiangwanxian 11 planted with monogenic lines was significantly more enhanced than those without monogenic lines. All the results indicated that in recent years, the fungal abundance in Hunan has decreased while fungal pathogenicity has increased significantly. This study will greatly benefit rice-resistance breeding and the control of rice blast disease in Hunan Province.