Spatiotemporal transcriptomic changes of human ovarian aging and the regulatory role of FOXP1.

Limited understanding exists regarding how aging impacts the cellular and molecular aspects of the human ovary. This study combines single-cell RNA sequencing and spatial transcriptomics to systematically characterize human ovarian aging. Spatiotemporal molecular signatures of the eight types of ovarian cells during aging are observed. An analysis of age-associated changes in gene expression reveals that DNA damage response may be a key biological pathway in oocyte aging. Three granulosa cells subtypes and five theca and stromal cells subtypes, as well as their spatiotemporal transcriptomics changes during aging, are identified. FOXP1 emerges as a regulator of ovarian aging, declining with age and inhibiting CDKN1A transcription. Silencing FOXP1 results in premature ovarian insufficiency in mice. These findings offer a comprehensive understanding of spatiotemporal variability in human ovarian aging, aiding the prioritization of potential diagnostic biomarkers and therapeutic strategies.

Phthalate acid esters: A review of aquatic environmental occurrence and their interactions with plants.

The increasing use of phthalate acid esters (PAEs) in various applications has inevitably led to their widespread presence in the aquatic environment. This presents a considerable threat to plants. However, the interactions between PAEs and plants in the aquatic environment have not yet been comprehensively reviewed. In this review, the properties, occurrence, uptake, transformation, and toxic effects of PAEs on plants in the aquatic environment are summarized. PAEs have been prevalently detected in the aquatic environment, including surface water, groundwater, seawater, and sediment, with concentrations ranging from the ng/L or ng/kg to the mg/L or mg/kg range. PAEs in the aquatic environment can be uptake, translocated, and metabolized by plants. Exposure to PAEs induces multiple adverse effects in aquatic plants, including growth perturbation, structural damage, disruption of photosynthesis, oxidative damage, and potential genotoxicity. High-throughput omics techniques further reveal the underlying toxicity molecular mechanisms of how PAEs disrupt plants on the transcription, protein, and metabolism levels. Finally, this review proposes that future studies should evaluate the interactions between plants and PAEs with a focus on long-term exposure to environmental PAE concentrations, the effects of PAE alternatives, and human health risks via the intake of plant-based foods.

Insufficient phosphorylation of STAT5 in Tregs inhibits the expression of BLIMP-1 but not IRF4, reduction the proportion of Tregs in pediatric aplastic anemia.

Deficiency in regulatory T cells (Tregs) is an important mechanism underlying the pathogenesis of pediatric aplastic anemia, but its specific mechanism is unclear. In our study, we aimed to investigate whether IL-2/STAT5 can regulate the proliferation of Tregs in aplastic anemia (AA) by regulating their expression of B lymphocyte-induced mature protein-1 (BLIMP-1) or interferon regulatory factor 4 (IRF4). Through clinical research and animal experiments, we found that poor activation of the IL-2/STAT5 signaling pathway may leads to low expression of BLIMP-1 in Tregs of children with AA, which leads to defects in the differentiation and proliferation of Tregs in AA. In AA model mice, treatment with IL-2c reversed the decrease in Treg proportions and reduction in Blimp-1 expression in Tregs by increasing the phosphorylation of Stat5 in Tregs. In AA, deficiency of IRF4 expression in Tregs is closely related to the deficiency of Tregs, but is not regulated by the IL-2/STAT5 pathway.

Neurotoxicities induced by micro/nanoplastics: A review focusing on the risks of neurological diseases.

Pollution of micro/nano-plastics (MPs/NPs) is ubiquitously prevalent in the environment, leading to an unavoidable exposure of the human body. Despite the protection of the blood-brain barrier, MPs/NPs can be transferred and accumulated in the brain, which subsequently exert negative effects on the brain. Nevertheless, the potential neurodevelopmental and/or neurodegenerative risks of MPs/NPs remain largely unexplored. In this review, we provide a systematic overview of recent studies related to the neurotoxicity of MPs/NPs. It covers the environmental hazards and human exposure pathways, translocation and distribution into the brain, the neurotoxic effects, and the possible mechanisms of environmental MPs/NPs. MPs/NPs are widely found in different environment matrices, including air, water, soil, and human food. Ambient MPs/NPs can enter the human body by ingestion, inhalation and dermal contact, then be transferred into the brain via the blood circulation and nerve pathways. When MPs/NPs are present in the brain, they can initiate a series of molecular or cellular reactions that may harm the blood-brain barrier, cause oxidative stress, trigger inflammatory responses, affect acetylcholinesterase activity, lead to mitochondrial dysfunction, and impair autophagy. This can result in abnormal protein folding, loss of neurons, disruptions in neurotransmitters, and unusual behaviours, ultimately contributing to the initiation and progression of neurodegenerative changes and neurodevelopmental abnormalities. Key challenges and further research directions are also proposed in this review as more studies are needed to focus on the potential neurotoxicity of MPs/NPs under realistic conditions.

Highly Hydrophilic Zirconia Composite Anion Exchange Membrane for Water Electrolysis and Fuel Cells.

To prepare anion exchange membranes with high water electrolysis and single fuel cell performance, an inorganic-organic composite (IOC) strategy with click cross-linked membranes coated with different contents of hydrophilic polar nanozirconia is proposed to fabricate composite membranes (CM) PBP-SH-Zrx. The performance test results showed that the CM PBP-SH-Zr4 not only has good through-plane ionic conductivity (167.7 mS cm-1, 80 °C), but also exhibits satisfactory dimensional stability (SR 16.5%, WU 206.4%, 80 °C), especially demonstrating excellent alkaline stability with only 16% degradation (2 M NaOH for 2200 h). In water electrolysis, the "microgap" between the membrane and catalyst layer (solid-solid interface) is alleviated, and the membrane electrode assembly (MEA) interfacial compatibility (liquid-solid-solid interface) is enhanced. The CM PBP-SH-Zr4 showed the lowest charge transfer resistance (Rct, 0.037 Ω cm2) and a high current density of 2.5 A cm-2 at 2.2 V, while the voltage drop was 0.361 mV h-1 after 360 h of endurance (six start-stop cycles) at 60 °C and 500 mA cm-2, proving a good water electrolysis durability. Moreover, an acceptable peak power density of 0.464 W cm-2 at 80 °C is achieved in a H2/O2 fuel cell with a PBP-SH-Zr4-AEM. Therefore, the IOC strategy can enhance the membrane's comprehensive performance and interface compatibility of MEA and may promote the development of anion exchange membranes (AEMs) for water electrolysis and fuel cells.

Enhancement of PRMT6 binding to a novel germline GATA1 mutation associated with congenital anemia.

Mutations in the master hematopoietic transcription factor GATA1 are often associated with functional defects in erythropoiesis and megakaryopoiesis. In this study, we identified a novel GATA1 germline mutation (c.1162delGG, p.Leu387Leufs*62) in a patient with congenital anemia and occasional thrombocytopenia. The C-terminal GATA1, a rarely studied mutational region, undergoes frameshifting translation as a consequence of this double-base deletion mutation. To investigate the specific function and pathogenic mechanism of this mutant, in vitro mutant models of stable re-expression cells were generated. The mutation was subsequently validated to cause diminished transcriptional activity of GATA1 and defective differentiation of erythroid and megakaryocytes. Using proximity labeling and mass spectrometry, we identified selective alterations in the proximal protein networks of the mutant, revealing decreased binding to a set of normal GATA1-interaction proteins, including the essential co-factor FOG1. Notably, our findings further demonstrated enhanced recruitment of the protein arginine methyltransferase PRMT6, which mediates histone modification at H3R2me2a and represses transcription activity. We also found an enhanced binding of this mutant GATA1/PRMT6 complex to the transcriptional regulatory elements of GATA1's target genes. Moreover, treatment of the PRMT6 inhibitor MS023 could partially rescue the inhibited transcriptional and impaired erythroid differentiation caused by the GATA1 mutation. Taken together, our results provide molecular insights into erythropoiesis in which mutation leads to partial loss of GATA1 function and the broader role of PRMT6 and its inhibitor MS023 in congenital anemia, highlighting PRMT6 binding as a negative factor of GATA1 transcriptional activity in aberrant hematopoiesis.

Hydrodeoxygenation of furfural to 2-methylfuran over Cu-Co confined by hollow carbon cage catalyst enhanced by optimized charge transfer and alloy structure.

Hydrodeoxygenation of furfural over non-noble metal catalyst is an effective route to synthesis 2-methylfuran, but the reaction is often hampered by the low activity and selectivity of the catalyst. Herein, a bimetallic catalyst with CuCo alloy encapsulated in a hollow nitrogen-doped carbon cages (CuCo/NC) are fabricated by using ZIF-67 as a sacrificial template, which exhibited superior catalytic performance and a full conversion of furfural with a 95.7 % selectivity towards 2-methylfuran was achieved at an under relatively mild reaction conditions (150 ℃, 1.5 MPa H2 and 4.0 h). The characterizations and density functional theory calculations clearly evidenced that the introduced Cu species acts as a switch to regulate the activity and selectivity of the catalyst via two aspects. On the one hand, the Cu species perturb the Co electronic structure leading to adsorption configuration of furfural change from flat to vertical on the catalyst surface, which successfully hindered the hydrogenation of furan ring, resulting high selectivity towards 2-methylfuran. On the other hand, the formed CuCo (111) sites promotes the dissociation of hydrogen, cleavage of the CO bond and reduces the diffusion barrier of hydrogen so as to advance the formation of 2-methylfuran. This work may provide a feasible strategy for the design of nanoalloy catalyst for the hydrodeoxygenation of biomass platforms to value-added chemicals.

Twisted Poly(p-terphenyl-co-m-terphenyl)-Based Anion Exchange Membrane for Water Electrolysis.

In order to improve the mechanical and water electrolysis performance of anion exchange membranes (AEMs), we adjusted the ratio between p-terphenyl and m-terphenyl to balance the backbone conformation, which gives it a better suitability for a better combination with cations. The results showed that poly(m-terphenyl-co-p-terphenyl)-based AEMs have excellent mechanical properties. Among them, the m-p-TP-40-BOP-ASU membrane has the highest tensile strength and elongation at break (75.72 MPa and 16.07%). The ionic conductivity reaches 137.14 mS cm-1 at 80 °C owing to the fact that efficient ion-conducting channels are formed by well-balanced molecular structures. The current density of the m-p-TP-40-BOP-ASU membrane reached 1.96 A cm-2 (1 M KOH aq, 2.0 V and 60 °C). After testing for 112 h under a current density of 500 mA cm-2, the voltage increased by 102 mV compared to the initial electrolysis voltage. All results have shown that m-p-TP-x-BOP-ASU has excellent electrolysis performance and electrochemical durability and has a promising application prospect in AEM water electrolyzers.

Combining a lung microfluidic chip exposure model with transcriptomic analysis to evaluate the inflammation in BEAS-2B cells exposed to cigarette smoke.

BACKGROUND: Typically, in vitro studies on the exposure of complex gaseous substances are performed in multi-well plate experiments by trapping and redissolving them, which could introduce potential bias into the results due to the use of inadequate trapping methods. Therefore, a more effective method is to expose complex gaseous substances in gaseous form online, such as using microfluidic chips in experiments. To address these challenges, we introduce a methodology that integrates a self-designed bionic-lung chip with transcriptome analysis to assess the impact of cigarette smoke (CS) exposure on changes in BEAS-2B cells cultured on-chip. RESULTS: After the microfluidic chip underwent online gas exposure, total RNA was extracted via in situ cell lysis, and RNA-Seq transcriptome analysis was conducted. And the RNA-Seq findings revealed the significant involvement of the MAPK signaling pathway associated with the inflammatory response in the cellular effects induced by CS exposure. Moreover, the validation of inflammatory response-related biomarkers through in situ fluorescence corroborated the outcomes of the transcriptome analysis. Besides, the experiment involving the inhibition of inflammation by DEX on the microfluidic chip provided additional confirmation of the previous experimental findings. SIGNIFICANT: In this study, we present an analytical strategy that combines microfluidic-based CS in situ exposure method with RNA-Seq technology. This strategy offers an experimental scheme for in situ exposure to complex gases, transcriptome analysis, and in situ fluorescence detection. Through the integration of the comprehensiveness of transcriptome analysis with the chip's direct and intuitive in situ fluorescence detection with the stability and reliability of RT-PCR and Western blot experiments, we have successfully addressed the challenges associated with in vitro risk assessment for online exposure to complex gaseous substances.

Phlebitis in Takayasu arteritis: A case-based literature review.

Takayasu arteritis (TAK) is the main type of large vessel arteritis in young adults, which mainly affects the aorta and its main branches, leading to clinical manifestations such as syncope, intermittent limb claudication, hypertension, and abdominal pain. Among them, venous involvement is rarely reported. Here we show a case of TAK presenting as phlebitis. This was a 27-year-old woman, who initially admitted to our hospital with myalgia of the upper and lower extremities and night sweats. She was diagnosed as TAK according to the 1990 American College of Rheumatology TAK criteria. Surprisingly, vascular ultrasonography revealed wall thickening as indicated by macaroni sign of the multiple veins. TAK phlebitis appeared at the active phase, while disappearing rapidly at remission. Phlebitis might have a close relationship with disease activity. By retrospective study in our department, the estimated incidence rate of phlebitis might be 9.1% in TAK. With the literature review, it revealed that phlebitis might be an ignored manifestation in active TAK. However, due to the smaller sample size, it should be noted that a direct cause-effect relationship cannot be established.

Hydrophilic Chitosan-Doped Composite Diaphragm Reducing Gas Permeation for Alkaline Water Electrolysis Producing Hydrogen.

The present paper studied the chitosan-doped composite diaphragm by the phase exchange method with the objective of developing a composite diaphragm that complies with the alkaline water electrolysis requirements, as well as tested the electrolytic performance of the diaphragm in alkaline water electrolysis. The structure and morphology are characterized by Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The performance of chitosan-doped composite diaphragms was tested; CS3Z12 composite diaphragm with a low area resistance (0.20 Ω cm2), a high bubble point pressure (2.75 bar), and excellent electrochemical performance (current density of 650 mA cm-2 at 1.83 V) shows the best performance. Moreover, the performance of the synthesized composite diaphragm is significantly elevated compared to commercial diaphragms (Zirfon PERL), which is promising for practical application in alkaline electrolytic cells.

Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health.

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction, and medical education, and investigate whether LLMs possess the transformative power to revolutionize these tasks or whether the distinct complexities of biomedical domain presents unique challenges. Following an extensive literature survey, we find that significant advances have been made in the field of text generation tasks, surpassing the previous state-of-the-art methods. For other applications, the advances have been modest. Overall, LLMs have not yet revolutionized biomedicine, but recent rapid progress indicates that such methods hold great potential to provide valuable means for accelerating discovery and improving health. We also find that the use of LLMs, like ChatGPT, in the fields of biomedicine and health entails various risks and challenges, including fabricated information in its generated responses, as well as legal and privacy concerns associated with sensitive patient data. We believe this survey can provide a comprehensive and timely overview to biomedical researchers and healthcare practitioners on the opportunities and challenges associated with using ChatGPT and other LLMs for transforming biomedicine and health.

Associations of urinary di(2-ethylhexyl) phthalate metabolites with lipid profiles among US general adult population.

Background: Di(2-ethylhexyl) phthalate (DEHP) a parent compound that is metabolized into 4 phthalate metabolites, which correlate to adverse cardio-metabolic risk factors. This study aimed to explore the links between urinary DEHP metabolites and serum lipids in the U.S. general adult population. Methods: In this cross-sectional study, data on 11 urinary phthalate metabolites from the 2005-2018 National Health and Nutrition Examination Surveys (NHANES) were analyzed. Multivariate linear regression and restricted cubic spline (RCS) were used to examine the relationship between phthalate metabolites [specific DEHPs: mono-(2-ethyl-5-carboxy-pentyl) phthalate (MECPP), mono-(2-ethyl-5-hydroxy-hexyl) phthalate (MEHHP), mono-(2-ethylhexyl) phthalate (MEHP), mono-(2-ethyl-5-oxo-hexyl) phthalate (MEOHP)] and serum lipids (triglycerides [TG], total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]). To identify mixed exposure effects of phthalate metabolites, quantile g-computation (QG-C) and weighted quantile sum (WQS) regression were employed for the lipid profiles. Results: A total of 9141 adults were included in the analysis. MECPP, MEHHP, MEHP, and MEOHP in the highest quartile had a negative relationship with HDL-C compared to the lowest quartile (All P for trend <0.05). TG showed a significant positive relation with MECPP, MEHHP, and MEOHP (All P for trend <0.05), but there was no notable association with MEHP. RCS demonstrated a linear relationship of DEHP metabolites with HDL-C, TC, TG, and LDL-C (all P for nonlinearity >0.05). The WQS index of DEHP metabolites showed independent correlations with HDL-C [ß = -0.26, 95%CI (-0.43, -0.09), P = 0.002], TC [ß = 0.55, 95%CI (0.13, 0.98), P = 0.011], and TG [ß = 2.40, 95%CI (0.85, 3.96), P = 0.003]. Conclusion: Our study suggests that environmental DEHP exposure may affect serum HDL-C and TG levels in the general adult population. Further research is warranted to confirm these findings and illuminate the underlying mechanisms of DEHP exposure on lipids.

Regulation of epithelial cell differentiation by the Ubiquitous expressed transcript isoform 1 in ulcerative colitis.

BACKGROUND AND AIM: Mucosal healing has emerged as a desirable treatment goal for patients with ulcerative colitis (UC). Healing of mucosal wounds involves epithelial cell proliferation and differentiation, and Y-box transcription factor ZONAB has recently been identified as the key modulator of intestinal epithelial restitution. METHODS: We studied the characteristics of UXT-V1 expression in UC patients using immunohistochemistry and qPCR. The functional role of UXT-V1 in the colonic epithelium was investigated using lentivirus-mediated shRNA in vitro and ex vivo. Through endogenous Co-immunoprecipitation and LC-MS/MS, we identified ZONAB as a UXT-V1-interactive protein. RESULTS: Herein, we report that UXT-V1 promotes differentiation of intestinal epithelial cells by regulating the nuclear translocation of ZONAB. UXT-V1 was upregulated in the intestinal epithelia of UC patients compared with that of healthy controls. Knocking down UXT-V1 in NCM-460 cells led to the enrichment of pathways associated with proliferation and differentiation. Furthermore, the absence of UXT-V1 in cultured intestinal epithelial cells and colonic organoids inhibited differentiation to the goblet cell phenotype. Mechanistically, the loss of UXT-V1 in the intestinal epithelial cells allowed nuclear translocation of ZONAB, wherein it regulated the transcription of differentiation-related genes, including AML1 and KLF4. CONCLUSION: Taken together, our study reveals a potential role of UXT-V1 in regulating epithelial cell differentiation, proving a molecular basis for mucosal healing in UC.

A scoping review on multimodal deep learning in biomedical images and texts.

Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and text, has the potential to revolutionize the analysis and interpretation of biomedical data. However, it only caught researchers' attention recently. To this end, there is a critical need to conduct a systematic review on this topic, identify the limitations of current work, and explore future directions. In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research. This study reviewed the current uses of multimodal deep learning on five tasks: (1) Report generation, (2) Visual question answering, (3) Cross-modal retrieval, (4) Computer-aided diagnosis, and (5) Semantic segmentation. Our results highlight the diverse applications and potential of MDL and suggest directions for future research in the field. We hope our review will facilitate the collaboration of natural language processing (NLP) and medical imaging communities and support the next generation of decision-making and computer-assisted diagnostic system development.

A scoping review on multimodal deep learning in biomedical images and texts.

OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images and text, has the potential to revolutionize the analysis and interpretation of biomedical data. However, it only caught researchers' attention recently. To this end, there is a critical need to conduct a systematic review on this topic, identify the limitations of current work, and explore future directions. METHODS: In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research. RESULT: This study reviewed the current uses of multimodal deep learning on five tasks: (1) Report generation, (2) Visual question answering, (3) Cross-modal retrieval, (4) Computer-aided diagnosis, and (5) Semantic segmentation. CONCLUSION: Our results highlight the diverse applications and potential of MDL and suggest directions for future research in the field. We hope our review will facilitate the collaboration of natural language processing (NLP) and medical imaging communities and support the next generation of decision-making and computer-assisted diagnostic system development.

Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports.

Despite the reduction in turn-around times in radiology reporting with the use of speech recognition software, persistent communication errors can significantly impact the interpretation of radiology reports. Pre-filling a radiology report holds promise in mitigating reporting errors, and despite multiple efforts in literature to generate comprehensive medical reports, there lacks approaches that exploit the longitudinal nature of patient visit records in the MIMIC-CXR dataset. To address this gap, we propose to use longitudinal multi-modal data, i.e., previous patient visit CXR, current visit CXR, and the previous visit report, to pre-fill the "findings" section of the patient's current visit. We first gathered the longitudinal visit information for 26,625 patients from the MIMIC-CXR dataset, and created a new dataset called Longitudinal-MIMIC. With this new dataset, a transformer-based model was trained to capture the multi-modal longitudinal information from patient visit records (CXR images + reports) via a cross-attention-based multi-modal fusion module and a hierarchical memory-driven decoder. In contrast to previous works that only uses current visit data as input to train a model, our work exploits the longitudinal information available to pre-fill the "findings" section of radiology reports. Experiments show that our approach outperforms several recent approaches. Code will be published at https://github.com/CelestialShine/Longitudinal-Chest-X-Ray.

Negative association between triglyceride glucose index and BMI-adjusted skeletal muscle mass index in hypertensive adults.

BACKGROUND: The triglyceride glucose (TyG) index, an indicator of insulin resistance, is often associated with adverse outcomes in various cardiovascular diseases, while hypertension is associated with an increased risk of cardiovascular diseases. As the loss of muscle mass in people with hypertension is poorly understood, the current study aimed to explore the relationship between TyG index and muscle mass in hypertensive population. METHODS: We analyzed data from hypertensive adult participants in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. The TyG index and body mass index (BMI)-adjusted skeletal muscle mass index (SMI) were calculated and the relationship between the two was evaluated using multivariable linear regression and restricted cubic spline (RCS) regression models. RESULTS: A total of 1633 participants in the dataset were included for the final analysis. In the multivariable regression analysis, the adjusted ß of SMI with a 95% confidence interval (CI) for the highest TyG index quartile was - 5.27 (- 9.79 to - 0.75), compared with the lowest quartile. A negative linear relationship between TyG index and SMI was plotted by RCS regression (nonlinear P = 0.128). Stratified models of non-smoking women of different ages also demonstrated that SMI decreased as TyG index increased (all P for trend < 0.05). CONCLUSION: This linear and negative correlation between TyG index and SMI in hypertensive patients suggests that insulin resistance adversely affects muscle mass.