mRNA-CLA: An interpretable deep learning approach for predicting mRNA subcellular localization.

Messenger RNA (mRNA) is vital for post-transcriptional gene regulation, acting as the direct template for protein synthesis. However, the methods available for predicting mRNA subcellular localization need to be improved and enhanced. Notably, few existing algorithms can annotate mRNA sequences with multiple localizations. In this work, we propose the mRNA-CLA, an innovative multi-label subcellular localization prediction framework for mRNA, leveraging a deep learning approach with a multi-head self-attention mechanism. The framework employs a multi-scale convolutional layer to extract sequence features across different regions and uses a self-attention mechanism explicitly designed for each sequence. Paired with Position Weight Matrices (PWMs) derived from the convolutional neural network layers, our model offers interpretability in the analysis. In particular, we perform a base-level analysis of mRNA sequences from diverse subcellular localizations to determine the nucleotide specificity corresponding to each site. Our evaluations demonstrate that the mRNA-CLA model substantially outperforms existing methods and tools.

Targeting cathepsin S promotes activation of OLF1-BDNF/TrkB axis to enhance cognitive function.

BACKGROUND: Cathepsin S (CTSS) is a cysteine protease that played diverse roles in immunity, tumor metastasis, aging and other pathological alterations. At the cellular level, increased CTSS levels have been associated with the secretion of pro-inflammatory cytokines and disrupted the homeostasis of Ca2+ flux. Once CTSS was suppressed, elevated levels of anti-inflammatory cytokines and changes of Ca2+ influx were observed. These findings have inspired us to explore the potential role of CTSS on cognitive functions. METHODS: We conducted classic Y-maze and Barnes Maze tests to assess the spatial and working memory of Ctss-/- mice, Ctss+/+ mice and Ctss+/+ mice injected with the CTSS inhibitor (RJW-58). Ex vivo analyses including long-term potentiation (LTP), Golgi staining, immunofluorescence staining of sectioned whole brain tissues obtained from experimental animals were conducted. Furthermore, molecular studies were carried out using cultured HT-22 cell line and primary cortical neurons that treated with RJW-58 to comprehensively assess the gene and protein expressions. RESULTS: Our findings reported that targeting cathepsin S (CTSS) yields improvements in cognitive function, enhancing both working and spatial memory in behavior models. Ex vivo studies showed elevated levels of long-term potentiation levels and increased synaptic complexity. Microarray analysis demonstrated that brain-derived neurotrophic factor (BDNF) was upregulated when CTSS was knocked down by using siRNA. Moreover, the pharmacological blockade of the CTSS enzymatic activity promoted BDNF expression in a dose- and time-dependent manner. Notably, the inhibition of CTSS was associated with increased neurogenesis in the murine dentate gyrus. These results suggested a promising role of CTSS modulation in cognitive enhancement and neurogenesis. CONCLUSION: Our findings suggest a critical role of CTSS in the regulation of cognitive function by modulating the Ca2+ influx, leading to enhanced activation of the BDNF/TrkB axis. Our study may provide a novel strategy for improving cognitive function by targeting CTSS.

Clinical characteristics of pyogenic liver abscess with and without biliary surgery history: a retrospective single-center experience.

BACKGROUND & AIMS: Pyogenic liver abscess (PLA) is a common hepatobiliary infection that has been shown to have an increasing incidence, with biliary surgery being identified as a trigger. Our aim was to investigate the clinical characteristics and treatments of PLA patients with and without a history of biliary surgery (BS). METHODS: The study included a total of 353 patients with PLA who received treatment at our hospital between January 2014 and February 2023. These patients were categorized into two groups: the BS group (n = 91) and the non-BS group (n = 262). In the BS group, according to the anastomosis method, they were further divided into bilioenteric anastomoses group (BEA, n = 22) and non-bilioenteric anastomoses group (non-BEA, n = 69). Clinical characteristics were recorded and analyzed. RESULTS: The percentage of PLA patients with BS history was 25.78%. The BS group exhibited elevated levels of TBIL and activated APTT abnormalities (P = 0.009 and P = 0.041, respectively). Within the BS group, the BEA subgroup had a higher prevalence of diabetes mellitus (P < 0.001) and solitary abscesses (P = 0.008) compared to the non-BEA subgroup. Escherichia coli was more frequently detected in the BS group, as evidenced by positive pus cultures (P = 0.021). The BS group exhibited reduced treatment efficacy compared to those non-BS history (P = 0.020). Intriguingly, the BS group received a higher proportion of conservative treatment (45.05% vs. 21.76%), along with reduced utilization of surgical drainage (6.59% vs. 16.41%). CONCLUSIONS: Patients with BS history, especially those who have undergone BEA, have an increased susceptibility to PLA formation without affecting prognosis.

Synthesis of polymerizable betulin maleic diester derivative for dental restorative resins with antibacterial activity.

OBJECTIVE: Bisphenol A glycidyl methacrylate (Bis-GMA) is of great importance for dental materials as the preferred monomer. However, the presence of bisphenol-A (BPA) core in Bis-GMA structure causes potential concerns since it is associated with endocrine diseases, developmental abnormalities, and cancer lesions. Therefore, it is desirable to develop an alternative replacement for Bis-GMA and explore the intrinsic relationship between monomer structure and resin properties. METHODS: Here, the betulin maleic diester derivative (MABet) was synthesized by a facile esterification reaction using plant-derived betulin and maleic anhydride as raw materials. Its chemical structure was confirmed by 1H and 13C NMR spectra, FT-IR spectra, and HR-MS, respectively. The as-synthesized MABet was then used as polymerizable comonomer to partially or completely substitute Bis-GMA in a 50:50 Bis-GMA: TEGDMA resin (5B5T) to formulate dental restorative resins. These were then determined for the viscosity behavior, light transmittance, real-time degree of conversion, residual monomers, mechanical performance, cytotoxicity, and antibacterial activity against Streptococcus mutans (S. mutans) in detail. RESULTS: Among all experimental resins, increasing the MABet concentration to 50 wt% made the resultant 5MABet5T resin have a maximum in viscosity and appear dark yellowish after polymerization. In contrast, the 1MABet4B5T resin with 10 wt% MABet possessed comparable shear viscosity and polymerization conversion (46.6 ± 1.0% in 60 s), higher flexural and compressive strength (89.7 ± 7.8 MPa; 345.5 ± 14.4 MPa) to those of the 5B5T control (48.5 ± 0.6%; 65.7 ± 6.7 MPa; 223.8 ± 57.1 MPa). This optimal resin also had significantly lower S. mutans colony counts (0.35 ×108 CFU/mL) than 5B5T (7.6 ×108 CFU/mL) without affecting cytocompatibility. SIGNIFICANCE: Introducing plant-derived polymerizable MABet monomer into dental restorative resins is an effective strategy for producing antibacterial dental materials with superior physicochemical property.

Distribution patterns and origins of organophosphate esters in soils from different climate systems on the Tibetan Plateau.

Organophosphate esters (OPEs) are extensively applied in various materials as flame retardants and plasticizers, and have high biological toxicity. OPEs are detected worldwide, even in distant polar regions and the Tibetan Plateau (TP). However, few studies have been performed to evaluate the distribution patterns and origins of OPEs in different climate systems on the TP. This study investigated the distribution characteristics, possible sources, and ecological risks of OPEs in soils from the different climate systems on the TP and its surroundings. The total concentrations of OPEs in soil varied from 468 to 17,451 pg g-1 dry weight, with greater concentrations in southeast Tibet (monsoon zone), followed by Qinghai (transition zone) and, finally, southern Xingjiang (westerly zone). OPE composition profiles also differed among the three areas with tri-n-butyl phosphate dominant in the westerly zone and tris(2-butoxyethyl) phosphate dominant in the Indian monsoon zone. Correlations between different compounds and altitude, soil organic carbon, or longitude varied in different climate zones, indicating that OPE distribution originates from both long-range atmospheric transport and local emissions. Ecological risk assessment showed that tris(2-chloroethyl) phosphate and tri-phenyl phosphate exhibited medium risks in soil at several sites in southeast Tibet. Considering the sensitivity and vulnerability of TP ecosystems to anthropogenic pollutants, the ecological risks potentially caused by OPEs in this region should be further assessed.

Global trends and differences in the burden of alcohol use disorders attributable to childhood sexual abuse by sex, age, and socio-demographic index: Findings from the Global Burden of Disease Study 2019.

BACKGROUND: Childhood sexual abuse (CSA) is a severe global problem associated with alcohol use disorder (AUD). Previous studies have confirmed this relationship; however, there is a lack of research on the disease burden of AUD attributable to CSA. OBJECTIVE: To analyze global spatiotemporal trends and differences in the disease burden of AUD attributable to CSA and its relationship with age, sex, and the sociodemographic index (SDI). PARTICIPANTS AND SETTING: Data from the Global Burden of Disease 2019 Public Database. METHODS: Summary exposure value (SEV) was used to evaluate CSA. Disability-adjusted life year (DALY), years lived with disability (YLD), years of life lost (YLL), and their annual rates of change were used to evaluate disease burden. Cluster analysis based on Ward's method was used to examine the global burden associated with age, sex, and SDI. A 95 % uncertainty intervals (UI), excluding 0, was considered statistically significant. RESULTS: In 2019, 1.63 million (95 % UI 0.23-3.90 million) DALYs of AUD were caused by CSA and the age-standardized rates (ASRs) of DALY was 19.77 (95 % UI 2.78-47.46) globally. Annual rates of change in DALY of people over 65 years of age increased from 1990 to 2019 in all regions except the High-middle SDI regions. The ASRs of DALY of females in High SDI regions, were always at a much higher level than other SDI regions, and showed an upward trend from 1990 to 2019 (DALY 1990: 20.38 [95 % UI 2.87-47.77], 2019: 23.61 [95 % UI 3.55-54.94]). CONCLUSIONS: Substantial geographical differences were observed in the burden of AUD attributable to CSA. The level of CSA exposure was inconsistent with the related burden of AUD in different regions according to the sociodemographic index. The burden of disease increased in the elderly population and in females in high sociodemographic index regions.

Improvement of Phased Antenna Array Applied in Focused Microwave Breast Hyperthermia.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements' polarization in the vertical plane of the breast, while the second array has half of the elements' polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

Long-baseline quantum sensor network as dark matter haloscope.

Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network's multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

Melatonin alleviates endoplasmic reticulum stress and follicular granulosa cell apoptosis by regulating ATF4 to activate mTOR signaling pathway in chickens.

Follicular atresia in chickens reduces the number of follicles that can further develop, leading to decrease egg laying. Endoplasmic reticulum stress (ERS) can initiate a unique pathway inducing the apoptosis of follicular granulosa cells, thus reducing egg laying. Melatonin (MEL) is involved in the regulation of follicle development, ovulation, and oocyte maturation, and is closely related to follicle fate. Mammalian target of Rapamycin (mTOR) signaling pathway plays an important role in cell growth regulation, and that there is a possible crosstalk between melatonin and mTOR activity in granular cells maturation and ovulation. This study aimed to investigate whether MEL inhibits ERS and follicular granulosa cell apoptosis by regulating ATF4 to activate mTOR signaling pathway in chickens. Frist, we established an in vitro ERS cell model using tunicamycin (TM). The results showed that different concentrations of TM exhibited dose-dependent inhibition of cell activity and induction of granulosa cells (P<0.01). Therefore, we chose 5 µg/mL of TM and a treatment time for 6 h as the optimal concentration for the following experiments. Then we investigate whether melatonin can inhibit ERS. TM treatment decreased the cell viability and Bcl-2 expression, increasing ROS levels and the mRNA expression of Grp78, ATF4, CHOP, PERK, eIF-2α, and BAX (P<0.01), whereas TM+MEL treatment significantly inhibited these changes (P<0.01). Then we explored whether melatonin protects follicular granulosa cells from ERS-induced apoptosis through the mammalian target of rapamycin (mTOR) signaling pathway by regulating ATF4, we found that ATF4 knockdown inhibited ERS by decreasing the expression of ERS-related genes and proteins and activating mTOR signaling pathway by increasing the protein expression of p4E-BP1 and pT389-S6K (P<0.001), while these changes were promoted by TM+si-ATF4+MEL treatment (P<0.01). These results indicate that MEL could alleviate TM-induced ERS by regulating ATF4 to activate mTOR signaling pathway in follicular granulosa cells, thus providing a new perspective for prolonging the laying cycle in chickens.

Improving tumor sensitivity by the introduction of an ester chain to triaryl derivatives targeting PD-1/PD-L1.

PD-1/PD-L1 pathway blockade is a promising immunotherapy for the treatment of cancer. In this manuscript, a series of triaryl compounds containing ester chains were designed and synthesized based on the pharmacophore studies of the lead BMS-1. After several SAR iterations, 22 showed the best biochemical activity binding to hPD-L1 with an IC50 of 1.21 nM in HTRF assay, and a KD value of 5.068 nM in SPR analysis. Cell-based experiments showed that 22 effectively promoted A549 cell death by restoring T-cell immune function. 22 showed significant in vivo antitumor activity in a 4T1 mouse model without obvious toxicity, with a TGI rate of 67.8 % (20 mg/kg, ip). Immunohistochemistry data indicated that 22 activates the immune activity in tumors. These results suggest that 22 is a promising compound for further development of PD-1/PD-L1 inhibitor for cancer therapy.

Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms.

Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating photoplethysmogram (PPG) and electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls, our approach focuses on continuous, non-invasive monitoring. Key features, including the QRS interval, RR interval, augmentation index, heart rate, systolic pressure, diastolic pressure, and peak-to-peak amplitude, were carefully selected for their clinical relevance and ability to capture cardiovascular dynamics. This feature selection not only highlighted important physiological indicators but also helped reduce computational complexity and the risk of overfitting in machine learning models. The use of these features in training machine learning algorithms led to a model with impressive accuracy (98%), sensitivity (97.60%), specificity (96.90%), and precision (97.20%). Our integrated approach, combining PPG and ECG signals, demonstrates superior performance compared to single-signal strategies, emphasizing its potential in early and precise heart failure diagnosis. The study also highlights the importance of continuous monitoring with wearable technology, suggesting a significant stride forward in non-invasive cardiovascular health assessment. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions.

Optimizing transseptal puncture guided by three-dimensional mapping: the role of a unipolar electrogram in a needle tip.

AIMS: A three-dimensional electroanatomic mapping system-guided transseptal puncture (3D-TSP), without fluoroscopy or echocardiography, has been only minimally reported. Indications for 3D-TSP remain unclear. Against this background, this study aims to establish a precise technique and create a workflow for validating and selecting eligible patients for fluoroless 3D-TSP. METHODS AND RESULTS: We developed a new methodology for 3D-TSP based on a unipolar electrogram derived from a transseptal needle tip (UEGM tip) in 102 patients (the derivation cohort) with intracardiac echocardiography (ICE) from March 2018 to February 2019. The apparent current of injury (COI) was recorded at the muscular limbus of the foramen ovalis (FO) on the UEGM tip (sinus rhythm: 2.57 ± 0.95 mV, atrial fibrillation: 1.92 ± 0.77 mV), which then disappeared or significantly reduced at the central FO. Changes in the COI, serving as a major criterion to establish a 3D-TSP workflow, proved to be the most valuable indicator for identifying the FO in 99% (101/102) of patients compared with three previous techniques (three minor criteria) of reduction in atrial unipolar or bipolar potential and FO protrusion. A total of 99.9% (1042/1043) patients in the validation cohort underwent successful 3D-TSP through the workflow from March 2019 to July 2023. Intracardiac echocardiography guidance was required for 6.6% (69/1042) of patients. All four criteria were met in 740 patients, resulting in a 100% pure fluoroless 3D-TSP success rate. CONCLUSION: In most patients, fluoroless 3D-TSP was successfully achieved using changes in the COI on the UEGM tip. Patients who met all four criteria were considered suitable for 3D-TSP, while those who met none required ICE guidance.

Advancing cancer driver gene detection via Schur complement graph augmentation and independent subspace feature extraction.

Accurately identifying cancer driver genes (CDGs) is crucial for guiding cancer treatment and has recently received great attention from researchers. However, the high complexity and heterogeneity of cancer gene regulatory networks limit the precition accuracy of existing deep learning models. To address this, we introduce a model called SCIS-CDG that utilizes Schur complement graph augmentation and independent subspace feature extraction techniques to effectively predict potential CDGs. Firstly, a random Schur complement strategy is adopted to generate two augmented views of gene network within a graph contrastive learning framework. Rapid randomization of the random Schur complement strategy enhances the model's generalization and its ability to handle complex networks effectively. Upholding the Schur complement principle in expectations promotes the preservation of the original gene network's vital structure in the augmented views. Subsequently, we employ feature extraction technology using multiple independent subspaces, each trained with independent weights to reduce inter-subspace dependence and improve the model's expressiveness. Concurrently, we introduced a feature expansion component based on the structure of the gene network to address issues arising from the limited dimensionality of node features. Moreover, it can alleviate the challenges posed by the heterogeneity of cancer gene networks to some extent. Finally, we integrate a learnable attention weight mechanism into the graph neural network (GNN) encoder, utilizing feature expansion technology to optimize the significance of various feature levels in the prediction task. Following extensive experimental validation, the SCIS-CDG model has exhibited high efficiency in identifying known CDGs and uncovering potential unknown CDGs in external datasets. Particularly when compared to previous conventional GNN models, its performance has seen significant improved. The code and data are publicly available at: https://github.com/mxqmxqmxq/SCIS-CDG.

Two-dimensional binary phase gratings for zero-order and high-order diffraction suppression.

A two-dimensional binary phase grating is proposed in this paper. Unlike a conventional transmission grating, in theory, the proposed phase grating can simultaneously eliminate the zero- and high-order diffraction along certain axes on the image plane, forming a pure sinusoidal transmission modulation that leaves only the first-order diffraction. The first-ever, to the best of our knowledge, theoretical model for achieving sinusoidal transmission modulation is suggested in this paper; then the theoretical calculation and experiment results are displayed to investigate the physical mechanism of the proposed grating. Moreover, the manipulation on the arrangement of grating design can disperse or concentrate the diffraction energy at a specific axis. Finally, almost first-order-only diffraction is achieved on a single axis by introducing random changes to certain geometrical parameters of the two-dimensional binary phase grating. Our work provides potential applications in optical science and engineering fields.

Stable Q-switched and femtosecond mode-locked erbium-doped fiber laser based on a CuSe nanosheets saturable absorber.

Stable Q-switched and femtosecond mode-locked erbium-doped fiber laser (EDFL) have been achieved using CuSe nanosheets as novel saturable absorber (SA), where the CuSe nanosheets were prepared by a hydrothermal method. The nonlinear optical properties of CuSe nanosheets were measured using an Z-scan setup, revealing nonlinear absorption coefficients of -3.67 ± 0.22 cm GW-1 at 1560 nm. The prepared CuSe nanosheets were mixed with polyvinyl alcohol (PVA) to obtain a CuSe-PVA SA with a modulation depth of 3.8 ± 0.13%, and it was utilized to realize a Q-switched EDFL, obtaining the narrowest pulse duration of 1.29 µs and the maximum output power of 5.96 mW, which corresponds to a pulse energy of up to 103.7 nJ. In addition, CuSe nanosheets were deposited on a D-shaped fiber (DSF) to fabricate a CuSe-DSF SA with a modulation depth of 5.6 ± 0.17%, and it was utilized to realize a mode-locked EDFL. The mode-locked EDFL demonstrated a low threshold of only 42 mW, a pulse duration of 740 fs, and a maximum output power of 9.7 mW. Meanwhile, it exhibited a high signal-to-noise ratio of 72 dB. To the best of our knowledge, this is the first time of CuSe nanosheets as SA in EDFL. The results demonstrate that CuSe nanosheets are a highly promising nonlinear optical material with great potential for applications in ultrafast photonics.

Integrating Machine Learning in Metabolomics: A Path to Enhanced Diagnostics and Data Interpretation.

Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.

ZnO-CeO2 Hollow Nanospheres for Selective Determination of Dopamine and Uric Acid.

ZnO-CeO2 hollow nanospheres have been successfully synthesized via the hard templating method, in which CeO2 is used as the support skeleton to avoid ZnO agglomeration. The synthesized ZnO-CeO2 hollow nanospheres possess a large electrochemically active area and high electron transfer owing to the high specific surface area and synergistic effect of ZnO and CeO2. Due to the above advantages, the resulting ZnO-CeO2 hollow spheres display high sensitivities of 1122.86 µA mM-1 cm-2 and 908.53 µA mM-1 cm-2 under a neutral environment for the selective detection of dopamine and uric acid. The constructed electrochemical sensor shows excellent selectivity, stability and recovery for the selective analysis of dopamine and uric acid in actual samples. This study provides a valuable strategy for the synthesis of ZnO-CeO2 hollow nanospheres via the hard templating method as electrocatalysts for the selective detection of dopamine and uric acid.

Melatonin alleviates endoplasmic reticulum stress to improve ovarian function by regulating the mTOR pathway in aged laying hens.

Granular cell apoptosis is a key factor leading to follicular atresia and decreased laying rate in aged laying hens. Endoplasmic reticulum stress (ERS) induced cell apoptosis is a new type of apoptosis pathway. Previous studies have shown that the ERS pathway is involved in the regulation of follicular development and atresia, and can be regulated by mTOR. Melatonin (MEL) can protect the normal development of follicles, but the precise mechanism by which MEL regulates follicular development is not yet clear. So, we investigated the potential relationship between MEL and ERS and mTOR signaling pathway in vivo through intraperitoneal injection of MEL in aged laying hens. The results show that the laying rate, ovarian follicle number, plasma MEL, E2, LH, FSH concentrations, as well as the mRNA expression of mTOR signaling-associated genes TSC1, TSC2, mTOR, 4E-BP1, and S6K in old later-period chicken control (Old-CN) group was significantly decreased (P < 0.01). In contrast, the ERS-related of plasma and granular cell layer mRNA expression of Grp78, CHOP, and Caspase-3 was significantly increased (P < 0.01). While both of the effects were reversed by MEL. Then, aging granulosa cells were treated with MEL in vitro, followed by RNA seq analysis, and it was found that 259 and 322 genes were upregulated and downregulated. After performing GO enrichment analysis, it was found that DEGs significantly contribute to the biological processes including cell growth and apoptosis. Using pathway enrichment analysis, we found significant overrepresentation of cellular processes related to mTOR signaling and endoplasmic reticulum (ER) stress, involving genes such as GRB10, SGK1, PRKCA, RPS6KA2, RAF1, PIK3R3, FOXO1, DERL3, HMOX1, TLR7, VAMP7 and INSIG2. The obtained results of RT-PCR showed consistency with the RNA-Seq data. In summary, the underlined results revealed that MEL has significantly contributed to follicular development via activating the mTOR signaling pathway-related genes and alleviating ERS-related genes in laying hens. The current study provides a theoretical background for enhancing the egg-laying capability of hens and also providing a basis for elucidating the molecular mechanism of follicular selection.

A subset of megakaryocytes regulates development of hematopoietic stem cell precursors.

Understanding the regulatory mechanisms facilitating hematopoietic stem cell (HSC) specification during embryogenesis is important for the generation of HSCs in vitro. Megakaryocyte emerged from the yolk sac and produce platelets, which are involved in multiple biological processes, such as preventing hemorrhage. However, whether megakaryocytes regulate HSC development in the embryonic aorta-gonad-mesonephros (AGM) region is unclear. Here, we use platelet factor 4 (PF4)-Cre;Rosa-tdTomato+ cells to report presence of megakaryocytes in the HSC developmental niche. Further, we use the PF4-Cre;Rosa-DTA (DTA) depletion model to reveal that megakaryocytes control HSC specification in the mouse embryos. Megakaryocyte deficiency blocks the generation and maturation of pre-HSCs and alters HSC activity at the AGM. Furthermore, megakaryocytes promote endothelial-to-hematopoietic transition in a OP9-DL1 coculture system. Single-cell RNA-sequencing identifies megakaryocytes positive for the cell surface marker CD226 as the subpopulation with highest potential in promoting the hemogenic fate of endothelial cells by secreting TNFSF14. In line, TNFSF14 treatment rescues hematopoietic cell function in megakaryocyte-depleted cocultures. Taken together, megakaryocytes promote production and maturation of pre-HSCs, acting as a critical microenvironmental control factor during embryonic hematopoiesis.