Repression of PRMT activities sensitize homologous recombination-proficient ovarian and breast cancer cells to PARP inhibitor treatment.

An "induced PARP inhibitor (PARPi) sensitivity by epigenetic modulation" strategy is being evaluated in the clinic to sensitize homologous recombination (HR)-proficient tumors to PARPi treatments. To expand its clinical applications and identify more efficient combinations, we performed a drug screen by combining PARPi with 74 well-characterized epigenetic modulators that target five major classes of epigenetic enzymes. Both type I PRMT inhibitor and PRMT5 inhibitor exhibit high combination and clinical priority scores in our screen. PRMT inhibition significantly enhances PARPi treatment-induced DNA damage in HR-proficient ovarian and breast cancer cells. Mechanistically, PRMTs maintain the expression of genes associated with DNA damage repair and BRCAness and regulate intrinsic innate immune pathways in cancer cells. Analyzing large-scale genomic and functional profiles from TCGA and DepMap further confirms that PRMT1, PRMT4, and PRMT5 are potential therapeutic targets in oncology. Finally, PRMT1 and PRMT5 inhibition act synergistically to enhance PARPi sensitivity. Our studies provide a strong rationale for the clinical application of a combination of PRMT and PARP inhibitors in patients with HR-proficient ovarian or breast cancer.

Classification of a Massive Number of Viral Genomes and Estimation of Time of Most Recent Common Ancestor (tMRCA) of SARS-CoV-2 Using Phylodynamic Analysis.

Estimating the time of most recent common ancestor (tMRCA) is important to trace the origin of pathogenic viruses. This analysis is based on the genetic diversity accumulated in a certain time period. There have been thousands of mutant sites occurring in the genomes of SARS-CoV-2 since the COVID-19 pandemic started; six highly linked mutation sites occurred early before the start of the pandemic and can be used to classify the genomes into three main haplotypes. Tracing the origin of those three haplotypes may help to understand the origin of SARS-CoV-2. In this article, we present a complete protocol for the classification of SARS-CoV-2 genomes and calculating tMRCA using Bayesian phylodynamic method. This protocol may also be used in the analysis of other viral genomes. Key features • Filtering and alignment of a massive number of viral genomes using custom scripts and ViralMSA. • Classification of genomes based on highly linked sites using custom scripts. • Phylodynamic analysis of viral genomes using Bayesian evolutionary analysis sampling trees (BEAST). • Visualization of posterior distribution of tMRCA using Tracer.v1.7.2. • Optimized for the SARS-CoV-2.

DeepFusionCDR: Employing Multi-Omics Integration and Molecule-Specific Transformers for Enhanced Prediction of Cancer Drug Responses.

Deep learning approaches have demonstrated remarkable potential in predicting cancer drug responses (CDRs), using cell line and drug features. However, existing methods predominantly rely on single-omics data of cell lines, potentially overlooking the complex biological mechanisms governing cell line responses. This paper introduces DeepFusionCDR, a novel approach employing unsupervised contrastive learning to amalgamate multi-omics features, including mutation, transcriptome, methylome, and copy number variation data, from cell lines. Furthermore, we incorporate molecular SMILES-specific transformers to derive drug features from their chemical structures. The unified multi-omics and drug signatures are combined, and a multi-layer perceptron (MLP) is applied to predict IC50 values for cell line-drug pairs. Moreover, this MLP can discern whether a cell line is resistant or sensitive to a particular drug. We assessed DeepFusionCDR's performance on the GDSC dataset and juxtaposed it against cutting-edge methods, demonstrating its superior performance in regression and classification tasks. We also conducted ablation studies and case analyses to exhibit the effectiveness and versatility of our proposed approach. Our results underscore the potential of DeepFusionCDR to enhance CDR predictions by harnessing the power of multi-omics fusion and molecular-specific transformers. The prediction of DeepFusionCDR on TCGA patient data and case study highlight the practical application scenarios of DeepFusionCDR in real-world environments. Source code and datasets can be available on https://github.com/altriavin/DeepFusionCDR.

Proangiogenic effect and underlying mechanism of holmium oxide nanoparticles: a new biomaterial for tissue engineering.

BACKGROUND: Early angiogenesis provides nutrient supply for bone tissue repair, and insufficient angiogenesis will lead tissue engineering failure. Lanthanide metal nanoparticles (LM NPs) are the preferred materials for tissue engineering and can effectively promote angiogenesis. Holmium oxide nanoparticles (HNPs) are LM NPs with the function of bone tissue "tracking" labelling. Preliminary studies have shown that HNPs has potential of promote angiogenesis, but the specific role and mechanism remain unclear. This limits the biological application of HNPs. RESULTS: In this study, we confirmed that HNPs promoted early vessel formation, especially that of H-type vessels in vivo, thereby accelerating bone tissue repair. Moreover, HNPs promoted angiogenesis by increasing cell migration, which was mediated by filopodia extension in vitro. At the molecular level, HNPs interact with the membrane protein EphrinB2 in human umbilical vein endothelial cells (HUVECs), and phosphorylated EphrinB2 can bind and activate VAV2, which is an activator of the filopodia regulatory protein CDC42. When these three molecules were inhibited separately, angiogenesis was reduced. CONCLUSION: Overall, our study confirmed that HNPs increased cell migration to promote angiogenesis for the first time, which is beneficial for bone repair. The EphrinB2/VAV2/CDC42 signalling pathway regulates cell migration, which is an important target of angiogenesis. Thus, HNPs are a new candidate biomaterial for tissue engineering, providing new insights into their biological application.

SGCLDGA: unveiling drug-gene associations through simple graph contrastive learning.

Drug repurposing offers a viable strategy for discovering new drugs and therapeutic targets through the analysis of drug-gene interactions. However, traditional experimental methods are plagued by their costliness and inefficiency. Despite graph convolutional network (GCN)-based models' state-of-the-art performance in prediction, their reliance on supervised learning makes them vulnerable to data sparsity, a common challenge in drug discovery, further complicating model development. In this study, we propose SGCLDGA, a novel computational model leveraging graph neural networks and contrastive learning to predict unknown drug-gene associations. SGCLDGA employs GCNs to extract vector representations of drugs and genes from the original bipartite graph. Subsequently, singular value decomposition (SVD) is employed to enhance the graph and generate multiple views. The model performs contrastive learning across these views, optimizing vector representations through a contrastive loss function to better distinguish positive and negative samples. The final step involves utilizing inner product calculations to determine association scores between drugs and genes. Experimental results on the DGIdb4.0 dataset demonstrate SGCLDGA's superior performance compared with six state-of-the-art methods. Ablation studies and case analyses validate the significance of contrastive learning and SVD, highlighting SGCLDGA's potential in discovering new drug-gene associations. The code and dataset for SGCLDGA are freely available at https://github.com/one-melon/SGCLDGA.

Increased cell-free DNA is associated with oxidative damage in patients with schizophrenia.

Cell-free DNA (cfDNA) has been found to be elevated in patients with schizophrenia (SZ), potentially derived from activated apoptosis, but the underlying mechanisms remain unknown. Moreover, whether the concentrations of cfDNA are altered with disease stage has not been investigated, which limits its clinical application as an auxiliary diagnostic marker for SZ. Using an improved fluorescence correlation spectroscopy (FCS) method that does not require DNA extraction, we measured the molar concentrations of cfDNA in plasma samples of 191 patients with SZ, 78 patients with mood disorders (MD) and 65 healthy controls (HC). We also analyzed the cfDNA composition from either the nucleus or mitochondria, oxidation markers and biochemical indexes to explore the potential mechanistic associations of the increased cfDNA levels. We found that in SZ patients, the cfDNA levels were significantly increased (P = 0.003) regardless of the different disease stages or antipsychotic medication use. Furthermore, qPCR revealed that cell-free nuclear DNA (cf-nDNA) (P = 0.041) but not cell-free mitochondrial DNA (cf-mtDNA) was elevated in SZ patients. Moreover, decreased SOD activity in SZ patients (P = 0.005) was negatively correlated with cfDNA levels (P = 0.047), and fasting blood glucose was positively correlated with cfDNA levels in SZ patients (P = 0.013). Our study provides evidence to support that the elevated cfDNA may be a convenient, effective and stable trait indicator of SZ. Further analysis showed that it mainly came from nucleus, suggesting increased apoptosis, and potentially related to oxidative stress and high blood glucose levels in patients.

Systematic review of the osteogenic effect of rare earth nanomaterials and the underlying mechanisms.

Rare earth nanomaterials (RE NMs), which are based on rare earth elements, have emerged as remarkable biomaterials for use in bone regeneration. The effects of RE NMs on osteogenesis, such as promoting the osteogenic differentiation of mesenchymal stem cells, have been investigated. However, the contributions of the properties of RE NMs to bone regeneration and their interactions with various cell types during osteogenesis have not been reviewed. Here, we review the crucial roles of the physicochemical and biological properties of RE NMs and focus on their osteogenic mechanisms. RE NMs directly promote the proliferation, adhesion, migration, and osteogenic differentiation of mesenchymal stem cells. They also increase collagen secretion and mineralization to accelerate osteogenesis. Furthermore, RE NMs inhibit osteoclast formation and regulate the immune environment by modulating macrophages and promote angiogenesis by inducing hypoxia in endothelial cells. These effects create a microenvironment that is conducive to bone formation. This review will help researchers overcome current limitations to take full advantage of the osteogenic benefits of RE NMs and will suggest a potential approach for further osteogenesis research.

IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network.

Accurately delineating the connection between short nucleolar RNA (snoRNA) and disease is crucial for advancing disease detection and treatment. While traditional biological experimental methods are effective, they are labor-intensive, costly and lack scalability. With the ongoing progress in computer technology, an increasing number of deep learning techniques are being employed to predict snoRNA-disease associations. Nevertheless, the majority of these methods are black-box models, lacking interpretability and the capability to elucidate the snoRNA-disease association mechanism. In this study, we introduce IGCNSDA, an innovative and interpretable graph convolutional network (GCN) approach tailored for the efficient inference of snoRNA-disease associations. IGCNSDA leverages the GCN framework to extract node feature representations of snoRNAs and diseases from the bipartite snoRNA-disease graph. SnoRNAs with high similarity are more likely to be linked to analogous diseases, and vice versa. To facilitate this process, we introduce a subgraph generation algorithm that effectively groups similar snoRNAs and their associated diseases into cohesive subgraphs. Subsequently, we aggregate information from neighboring nodes within these subgraphs, iteratively updating the embeddings of snoRNAs and diseases. The experimental results demonstrate that IGCNSDA outperforms the most recent, highly relevant methods. Additionally, our interpretability analysis provides compelling evidence that IGCNSDA adeptly captures the underlying similarity between snoRNAs and diseases, thus affording researchers enhanced insights into the snoRNA-disease association mechanism. Furthermore, we present illustrative case studies that demonstrate the utility of IGCNSDA as a valuable tool for efficiently predicting potential snoRNA-disease associations. The dataset and source code for IGCNSDA are openly accessible at: https://github.com/altriavin/IGCNSDA.

Exploring ncRNA-Drug Sensitivity Associations Via Graph Contrastive Learning.

Increasing evidence has shown that noncoding RNAs (ncRNAs) can affect drug efficiency by modulating drug sensitivity genes. Exploring the association between ncRNAs and drug sensitivity is essential for drug discovery and disease prevention. However, traditional biological experiments for identifying ncRNA-drug sensitivity associations are time-consuming and laborious. In this study, we develop a novel graph contrastive learning approach named NDSGCL to predict ncRNA-drug sensitivity. NDSGCL uses graph convolutional networks to learn feature representations of ncRNAs and drugs in ncRNA-drug bipartite graphs. It integrates local structural neighbours and global semantic neighbours to learn a more comprehensive representation by contrastive learning. Specifically, the local structural neighbours aim to capture the higher-order relationship in the ncRNA-drug graph, while the global semantic neighbours are defined based on semantic clusters of the graph that can alleviate the impact of data sparsity. The experimental results show that NDSGCL outperforms basic graph convolutional network methods, existing contrastive learning methods, and state-of-the-art prediction methods. Visualization experiments show that the contrastive objectives of local structural neighbours and global semantic neighbours play a significant role in contrastive learning. Case studies on two drugs show that NDSGCL is an effective tool for predicting ncRNA-drug sensitivity associations. Source code and datasets can be available on https://github.com/altriavin/NDSGCL.

A dataset for fine-grained seed recognition.

The research of plant seeds has always been a focus of agricultural and forestry research, and seed identification is an indispensable part of it. With the continuous application of artificial intelligence technology in the field of agriculture, seed identification through computer vision can effectively promote the development of agricultural and forestry wisdom. Data is the foundation of computer vision, but there is a lack of suitable datasets in the agricultural field. In this paper, a seed dataset named LZUPSD is established. A device based on mobile phones and macro lenses was established to acquire images. The dataset contains 4496 images of 88 different seeds. This dataset can not only be used as data for training deep learning models in the computer field, but also provide important data support for agricultural and forestry research. As an important resource in this field, this dataset plays a positive role in modernizing agriculture and forestry.

The miR166 targets CsHDZ3 genes to negatively regulate drought tolerance in tea plant (Camellia sinensis).

Drought is the stressor with a significant adverse impact on the yield stability of tea plants. HD-ZIP III transcription factors (TFs) play important regulatory roles in plant growth, development, and stress responses. However, whether and how HD-ZIP III TFs are involved in drought response and tolerance in tea plants remains unclear. Here, we identified seven HD-ZIP III genes (CsHDZ3-1 to CsHDZ3-7) in tea plant genome. The evolutionary analysis demonstrated that CsHDZ3 members were subjected to purify selection. Subcellular localization analysis revealed that all seven CsHDZ3s located in the nucleus. Yeast self-activation and dual-luciferase reporter assays demonstrated that CsHDZ3-1 to CsHDZ3-4 have trans-activation ability whereas CsHDZ3-5 to CsHDZ3-7 served as transcriptional inhibitors. The qRT-PCR assay showed that all seven CsHDZ3 genes could respond to simulated natural drought stress and polyethylene glycol treatment. Further assays verified that all CsHDZ3 genes can be cleaved by csn-miR166. Overexpression of csn-miR166 inhibited the expression of seven CsHDZ3 genes and weakened drought tolerance of tea leaves. In contrast, suppression of csn-miR166 promoted the expression of seven CsHDZ3 genes and enhanced drought tolerance of tea leaves. These findings established the foundation for further understanding the mechanism of CsHDZ3-miR166 modules' participation in drought responses and tolerance.

The role of Neutrophil counts, infections and Smoking in mediating the Effect of Bronchiectasis on Chronic Obstructive Pulmonary Disease: a mendelian randomization study.

BACKGROUND: The causality of the relationship between bronchiectasis and chronic obstructive pulmonary disease (COPD) remains unclear. This study aims to investigate the potential causal relationship between them, with a specific focus on the role of airway inflammation, infections, smoking as the mediators in the development of COPD. METHODS: We conducted a two-sample Mendelian randomization (MR) analysis to assess: (1) the causal impact of bronchiectasis on COPD, sex, smoking status, infections, eosinophil and neutrophil counts, as well as the causal impact of COPD on bronchiectasis; (2) the causal effect of smoking status, infections and neutrophil counts on COPD; and (3) the extent to which the smoking status, infections and neutrophil counts might mediate any influence of bronchiectasis on the development of COPD. RESULTS: COPD was associated with a higher risk of bronchiectasis (OR 1.28 [95% CI 1.05, 1.56]). Bronchiectasis was associated with a higher risk of COPD (OR 1.08 [95% CI 1.04, 1.13]), higher levels of neutrophil (OR 1.01 [95% CI 1.00, 1.01]), higher risk of respiratory infections (OR 1.04 [95% CI 1.02, 1.06]) and lower risk of smoking. The causal associations of higher neutrophil cells, respiratory infections and smoking with higher COPD risk remained after performing sensitivity analyses that considered different models of horizontal pleiotropy, with OR 1.17, 1.69 and 95.13, respectively. The bronchiectasis-COPD effect was 0.99, 0.85 and 122.79 with genetic adjustment for neutrophils, respiratory infections and smoking. CONCLUSION: COPD and bronchiectasis are mutually causal. And increased neutrophil cell count and respiratory infections appears to mediate much of the effect of bronchiectasis on COPD.

A supramolecular hydrogel dressing with antibacterial, immunoregulation, and pro-regeneration ability for biofilm-associated wound healing.

Chronic wound treatment has emerged as a significant healthcare concern worldwide due to its substantial economic burden and the limited effectiveness of current treatments. Effective management of biofilm infections, regulation of excessive oxidative stress, and promotion of tissue regeneration are crucial for addressing chronic wounds. Hydrogel stands out as a promising candidate for chronic wound treatment. However, its clinical application is hindered by the difficulty in designing and fabricating easily and conveniently. To overcome these obstacles, we present a supermolecular G-quadruplex hydrogel with the desired multifunction via a dynamic covalent strategy and Hoogsteen-type hydrogen bonding. The G-quadruplex hydrogel is made from the self-assembly of guanosine, 2-formylphenyboronic acid, polyethylenimine, and potassium chloride, employing dynamic covalent strategy and Hoogsteen-type hydrogen bonding. In the acidic/oxidative microenvironment associated with bacterial infections, the hydrogel undergoes controlled degradation, releasing the polyethylenimine domain, which effectively eliminates bacteria. Furthermore, nanocomplexes comprising guanosine monophosphate and manganese sulfate are incorporated into the hydrogel skeleton, endowing it with the ability to scavenge reactive oxygen species and modulate macrophages. Additionally, the integration of basic fibroblast growth factor into the G-quadruplex skeleton through dynamic covalent bonds facilitates controlled tissue regeneration. In summary, the facile preparation process and the incorporation of multiple functionalities render the G-quadruplex hydrogel a highly promising candidate for advanced wound dressing. It holds great potential to transition from laboratory research to clinical practice, addressing the pressing needs of chronic wound management.

In vivo study on osteogenic efficiency of nHA/ gel porous scaffold with nacre water-soluble matrix.

BACKGROUND/PURPOSE: Nano-hydroxyapatite (nHA)/ gel porous scaffolds loaded with WSM carriers are promising bone replacement materials that can improve osseointegration ability. This investigation aimed to evaluate the osteoinductive activity by implanting the composition of nano-hydroxyapatite (nHA)/ Gel porous scaffolds as a carrier of WSM via an animal model. MATERIALS AND METHODS: WSM was extracted and nHA was added to the matrix to construct porous composite scaffolds. The dose-effect curve of WSM concentration and alkaline phosphatase (ALP) activity was made by culturing rat osteoblasts and examining the absorbance. Three different materials were implanted into critical size defects (CSD) in the skulls of rats, which were further divided into four groups: WSM nHA /Gel group, n-WSM nHA /Gel group, HA powder group, and control group. RESULTS: WSM (150 µg/mL-250µg/mL) effectively improved the activity of ALP in rat osteoblasts. All rats in each group had normal healing. WSM-loaded nHA /Gel group showed better performance on newly-formed bone tissue of rat skull and back at 4th week and 8th week, respectively. At the 4th week, the network of woven bone formed in the WSM-loaded nHA/Gel scaffold material. At 8th week, the reticular trabecular bone in the WSM-loaded scaffold material became dense lamellar bone, and the defect was mature lamellar bone. In the subcutaneous implantation experiment, WSM-loaded nHA/Gel scaffold material showed a better performance of heterotopic ossification than the pure nHA/Gel scaffold material. CONCLUSION: WSM promotes osteoblast differentiation and bone mineralization. The results confirm that the nHA/ Gel Porous Scaffold with Nacre Water-Soluble Matrix has a significant bone promoting effect and can be used as a choice for tissue engineering to repair bone defects.

Long-term efficacy of a recombinant hepatitis E vaccine in adults: 10-year results from a randomised, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: Hepatitis E virus (HEV) is a frequently overlooked causative agent of acute hepatitis. Evaluating the long-term durability of hepatitis E vaccine efficacy holds crucial importance. METHODS: This study was an extension to a randomised, double-blind, placebo-controlled, phase-3 clinical trial of the hepatitis E vaccine conducted in Dontai County, Jiangsu, China. Participants were recruited from 11 townships in Dongtai County. In the initial trial, a total of 112 604 healthy adults aged 16-65 years were enrolled, stratified according to age and sex, and randomly assigned in a 1:1 ratio to receive three doses of hepatitis E vaccine or placebo intramuscularly at month 0, month 1, and month 6. A sensitive hepatitis E surveillance system including 205 clinical sentinels, covering the entire study region, was established and maintained for 10 years after vaccination. The primary outcome was the per-protocol efficacy of hepatitis E virus vaccine to prevent confirmed hepatitis E occurring at least 30 days after administration of the third dose. Throughout the study, the participants, site investigators, and laboratory staff remained blinded to the treatment assignments. This study is registered with ClinicalTrials.gov (NCT01014845). FINDINGS: During the 10-year study period from Aug 22, 2007, to Oct 31, 2017, 90 people with hepatitis E were identified; 13 in the vaccine group (0·2 per 10 000 person-years) and 77 in the placebo group (1·4 per 10 000 person-years), corresponding to a vaccine efficacy of 83·1% (95% CI 69·4-91·4) in the modified intention-to-treat analysis and 86·6% (73·0 to 94·1) in the per-protocol analysis. In the subsets of participants assessed for immunogenicity persistence, of those who were seronegative at baseline and received three doses of hepatitis E vaccine, 254 (87·3%) of 291 vaccinees in Qindong at the 8·5-year mark and 1270 (73·0%) of 1740 vaccinees in Anfeng at the 7·5-year mark maintained detectable concentrations of antibodies. INTERPRETATION: Immunisation with this hepatitis E vaccine offers durable protection against hepatitis E for up to 10 years, with vaccine-induced antibodies against HEV persisting for at least 8·5 years. FUNDING: National Natural Science Foundation of China, Fujian Provincial Natural Science Foundation, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, and the Fundamental Research Funds for the Central Universities.

Re-expression of epigenetically silenced PTPRR by histone acetylation sensitizes RAS-mutant lung adenocarcinoma to SHP2 inhibition.

Silenced protein tyrosine phosphatase receptor type R (PTPRR) participates in mitogen-activated protein kinase (MAPK) signaling cascades during the genesis and development of tumors. Rat sarcoma virus (Ras) genes are frequently mutated in lung adenocarcinoma, thereby resulting in hyperactivation of downstream MAPK signaling. However, the molecular mechanism manipulating the regulation and function of PTPRR in RAS-mutant lung adenocarcinoma is not known. Patient records collected from the Cancer Genome Atlas and Gene Expression Omnibus showed that silenced PTPRR was positively correlated with the prognosis. Exogenous expression of PTPRR suppressed the proliferation and migration of lung cancer cells. PTPRR expression and Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) inhibition acted synergistically to control ERK1/2 phosphorylation in RAS-driven lung cancer cells. Chromatin immunoprecipitation assay revealed that HDAC inhibition induced enriched histone acetylation in the promoter region of PTPRR and recovered PTPRR transcription. The combination of the HDAC inhibitor SAHA and SHP2 inhibitor SHP099 suppressed the progression of lung cancer markedly in vitro and in vivo. Therefore, we revealed the epigenetic silencing mechanism of PTPRR and demonstrated that combination therapy targeting HDAC and SHP2 might represent a novel strategy to treat RAS-mutant lung cancer.

Omega-3 supplementation improves depressive symptoms, cognitive function and niacin skin flushing response in adolescent depression: A randomized controlled clinical trial.

BACKGROUND: Depressive disorder in adolescents is a major health problem with inadequate treatment. Omega-3 (ω3) polyunsaturated fatty acids are a promising adjuvant therapy in adult depression. The primary objective of this study was to investigate the efficacy of adjuvant ω3 treatment on depressive symptoms in adolescent depression. Secondarily, we explored the effects of ω3 on cognitive function and memory and niacin skin flushing response (NSFR), as their robust associations with adolescent depression. METHODS: A total of 71 adolescents with depression (aged 13-24; 59.2 % female) were randomly assigned to receive ω3 plus Paxil (n = 34) or Paxil alone (n = 37) for 12 weeks. Primary outcome was depression severity according to scores on Montgomery-Asberg Depression Rating Scale (MADRS). Secondary outcomes were cognitive function and memory, and NSFR. RESULTS: Significant improvements in depressive symptoms over time (p = 0.00027 at week 12) were observed in the ω3 + Paxil group compared with Paxil group. Additionally, in the ω3 + Paxil group, significant improvements in memory over time, and greater cognitive function and NSFR were also observed compared with the Paxil group; the NSFR was negatively correlated with MADRS scores at baseline. LIMITATIONS: The trial was open label; thus, the outcome measures should be viewed as preliminary since inherent bias in outcomes due to the potential of a placebo effect. CONCLUSIONS: Our results demonstrate that adjuvant ω3 treatment is effective for reducing depressive symptoms as well as improving cognitive function, memory and the NSFR; these results suggest ω3 is a promising adjuvant treatment for adolescent depression.

Monomeric CXCL12-Engineered Adipose-Derived Stem Cells Transplantation for the Treatment of Ischemic Stroke.

Adipose-derived stem cells (ASCs) possess therapeutic potential for ischemic brain injury, and the chemokine CXCL12 has been shown to enhance their functional properties. However, the cumulative effects of ASCs when combined with various structures of CXCL12 on ischemic stroke and its underlying molecular mechanisms remain unclear. In this study, we genetically engineered mouse adipose-derived ASCs with CXCL12 variants and transplanted them to the infarct region in a mice transient middle cerebral artery occlusion (tMCAO) model of stroke. We subsequently compared the post-ischemic stroke efficacy of ASC-mCXCL12 with ASC-dCXCL12, ASC-wtCXCL12, and unmodified ASCs. Neurobehavior recovery was assessed using modified neurological severity scores, the hanging wire test, and the elevated body swing test. Changes at the tissue level were evaluated through cresyl violet and immunofluorescent staining, while molecular level alterations were examined via Western blot and real-time PCR. The results of the modified neurological severity score and cresyl violet staining indicated that both ASC-mCXCL12 and ASC-dCXCL12 treatment enhanced neurobehavioral recovery and mitigated brain atrophy at the third and fifth weeks post-tMCAO. Additionally, we observed that ASC-mCXCL12 and ASC-dCXCL12 promoted angiogenesis and neurogenesis, accompanied by an increased expression of bFGF and VEGF in the peri-infarct area of the brain. Notably, in the third week after tMCAO, the ASC-mCXCL12 exhibited superior outcomes compared to ASC-dCXCL12. However, when treated with the CXCR4 antagonist AMD3100, the beneficial effects of ASC-mCXCL12 were reversed. The AMD3100-treated group demonstrated worsened neurological function, aggravated edema volume, and brain atrophy. This outcome is likely attributed to the interaction of monomeric CXCL12 with CXCR4, which regulates the recruitment of bFGF and VEGF. This study introduces an innovative approach to enhance the therapeutic potential of ASCs in treating ischemic stroke by genetically engineering them with the monomeric structure of CXCL12.

A long-term experiment reveals no trade-off between seed persistence and seedling emergence.

Information on seed persistence and seedling emergence from the soil seed bank is critical for understanding species coexistence and predicting community dynamics. However, quantifying seed persistence in the soil is challenging; thus, its association with other life-history traits is poorly known on a broad scale. Using germination phenology for 349 species in a 42-yr experiment, we quantified the persistence-emergence correlations and their associations with intrinsic regeneration traits using Bayesian phylogenetic multilevel models. We showed no trade-off between seed persistence and seedling emergence. Physically dormant seeds were more persistent but exhibited lower emergence than nondormant seeds. Monocarpic species had both higher persistence and emergence than polycarpic species. Seed mass posed a marginal proxy for persistence, while emergence almost doubled from the smallest to the largest seeds. This study challenges the traditional assumption and is the first demonstration of noncorrelation between persistence and emergence, probably owing to the complexity of regenerative strategies. Species with short persistence and low emergence would be the most vulnerable for in situ conservation. Our analyses of this unique, long-term dataset provide a strong incentive for further experimental studies and a rich data resource for future syntheses.

Scalable Photochromic Film for Solar Heat and Daylight Management.

The adaptive control of sunlight through photochromic smart windows could have a huge impact on the energy efficiency and daylight comfort in buildings. However, the fabrication of inorganic nanoparticle and polymer composite photochromic films with a high contrast ratio and high transparency/low haze remains a challenge. Here, a solution method is presented for the in situ growth of copper-doped tungsten trioxide nanoparticles in polymethyl methacrylate, which allows a low-cost preparation of photochromic films with a high luminous transparency (luminous transmittance Tlum = 91%) and scalability (30 × 350 cm2 ). High modulation of visible light (ΔTlum = 73%) and solar heat (modulation of solar transmittance ΔTsol = 73%, modulation of solar heat gain coefficient ΔSHGC = 0.5) of the film improves the indoor daylight comfort and energy efficiency. Simulation results show that low-e windows with the photochromic film applied can greatly enhance the energy efficiency and daylight comfort. This photochromic film presents an attractive strategy for achieving more energy-efficient buildings and carbon neutrality to combat global climate change.