Alkyl effects on charge recombination in copper electrolyte-based dye-sensitized solar cells: Insights for targeted molecular design towards high performance.

Two quinoxaline dyes utilized in copper-electrolyte-based dye-sensitized solar cells (Cu-DSSCs) are theoretically investigated to analyze the impact of alkyl chains on dye performance. The investigation shows that ZS4, known for its record efficiency of up to 13.2 %, exhibits higher electron coupling and fewer binding sites for dye-[Cu(tmby)2]2+ interaction compared to ZS5. Contrary to common belief, alkyl chains are found to not only provide shielding but also hinder the interaction between dye and [Cu(tmby)2]2+ by influencing the optimal conformation of dyes, thereby impeding the charge recombination process. It is crucial to consider the influence of alkyl chains on dye conformation when discussing the relationship between dye structure and performance, rather than oversimplifying it as often done traditionally. Building on these findings, eight dyes are strategically designed by adjusting the position of the alkyl chain to further decrease charge recombination compared to ZS4. Theoretical evaluation of these dyes reveals that changing the alkyl chain on the nitrogen atom from 2-ethylhexyl (ZS4) to 1-hexylheptyl (D3-2) not only reduces the charge recombination rate but also enhances light harvesting ability. Therefore, D3-2 shows potential as a candidate for experimental synthesis of high-performance Cu-DSSCs with improved efficiency.

Using 2D U-Net convolutional neural networks for automatic acetabular and proximal femur segmentation of hip MRI images and morphological quantification: a preliminary study in DDH.

BACKGROUND: Developmental dysplasia of the hip (DDH) is a common pediatric orthopedic condition characterized by varying degrees of acetabular dysplasia and hip dislocation. Current 2D imaging methods often fail to provide sufficient anatomical detail for effective treatment planning, leading to higher rates of misdiagnosis and missed diagnoses. MRI, with its advantages of being radiation-free, multi-planar, and containing more anatomical information, can provide the crucial morphological and volumetric data needed to evaluate DDH. However, manual techniques for measuring parameters like the center-edge angle (CEA) and acetabular index (AI) are time-consuming. Automating these processes is essential for accurate clinical assessments and personalized treatment strategies. METHODS: This study employed a U-Net-based CNN model to automate the segmentation of hip MRI images in children. The segmentation process was validated using a leave-one-out method during training. Subsequently, the segmented hip joint images were utilized in clinical settings to perform automated measurements of key angles: AI, femoral neck angle (FNA), and CEA. This automated approach aimed to replace manual measurements and provide an objective reference for clinical assessments. RESULTS: The U-Net-based network demonstrates high effectiveness in hip segmentation compared to manual radiologist segmentations. In test data, it achieves average DSC values of 0.9109 (acetabulum) and 0.9244 (proximal femur), with a 91.76% segmentation success rate. The average ASD values are 0.3160 mm (acetabulum) and 0.6395 mm (proximal femur) in test data, with Ground Truth (GT) edge points and predicted segmentation maps having a mean distance of less than 1 mm. Using automated segmentation models for clinical hip angle measurements (CEA, AI, FNA) shows no statistical difference compared to manual measurements (p > 0.05). CONCLUSION: Utilizing U-Net-based image segmentation and automated measurement of morphological parameters significantly enhances the accuracy and efficiency of DDH assessment. These methods improve precision in automatic measurements and provide an objective basis for clinical diagnosis and treatment of DDH.

The Functional and Prognostic Impact of TIGIT Expression on Bone Marrow NK Cells in Core Binding Factor-Acute Myeloid Leukemia Patients at Diagnosis.

Background: The effect of the expression of the newly identified immune checkpoint, T cell immunoglobulin and immunoreceptor tyrosine-based inhibition motif domain (TIGIT) on NK cells in core binding factor-acute myeloid leukemia (CBF-AML) remains to be investigated. Methods: Fresh bone marrow samples from a total of 39 newly diagnosed CBF-AML patients and 25 healthy donors (HDs) were collected for testing the phenotype and function state of total NK, CD56bright, and CD56dim NK cell subsets after in vitro stimulation. Results: The frequencies of TIGIT+ cells in total NK, CD56bright, and CD56dim NK cell subsets had no significant difference between patients and HDs. TNF-α and INF-γ levels were uniformly lower in TIGIT+ cells than the corresponding TIGIT- cells in all HDs, whereas those for TIGIT+ to TIGIT- cells in patients were highly heterogenous; TIGIT expression was not related to PFP and GZMB expression in HDs, whereas it was related to higher intracellular PFP and GZMB levels in patients. Patients' TIGIT+ NK cells displayed lower K562 cell-killing activity than their TIGIT- NK cells. In addition, high frequencies of TIGIT+ cells in total NK and CD56dim NK cells were associated with poor RFS. Conclusions: TIGIT expression affected the diagnostic bone marrow-sited NK cell function and had prognostic significance in CBF-AML patients.

The role of iron transporters and regulators in Alzheimer's disease and Parkinson's disease: Pathophysiological insights and therapeutic prospects.

Brain iron homeostasis plays a vital role in maintaining brain development and controlling neuronal function under physiological conditions. Many studies have shown that the imbalance of brain iron homeostasis is closely related to the pathogenesis of neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD). Recent advances have revealed the importance of iron transporters and regulatory molecules in the pathogenesis and treatment of NDs. This review summarizes the research progress on brain iron overload and the aberrant expression of several key iron transporters and regulators in AD and PD, emphasizes the pathological roles of these molecules in the pathogenesis of AD and PD, and highlights the therapeutic prospects of targeting these iron transporters and regulators to restore brain iron homeostasis in the treatment of AD and PD. A comprehensive understanding of the pathophysiological roles of iron, iron transporters and regulators, and their regulations in NDs may provide new therapeutic avenues for more targeted neurotherapeutic strategies for treating these diseases.

Single-Cell Transcriptomics Reveals Early Effects of Ionizing Radiation on Bone Marrow Mononuclear Cells in Mice.

Ionizing radiation exposure can cause damage to diverse tissues and organs, with the hematopoietic system being the most sensitive. However, limited information is available regarding the radiosensitivity of various hematopoietic cell populations in the bone marrow due to the high heterogeneity of the hematopoietic system. In this study, we observed that granulocyte-macrophage progenitors, hematopoietic stem/progenitor cells, and B cells within the bone marrow showed the highest sensitivity, exhibiting a rapid decrease in cell numbers following irradiation. Nonetheless, neutrophils, natural killer (NK) cells, T cells, and dendritic cells demonstrated a certain degree of radioresistance, with neutrophils exhibiting the most pronounced resistance. By employing single-cell transcriptome sequencing, we investigated the early responsive genes in various cell types following irradiation, revealing that distinct gene expression profiles emerged between radiosensitive and radioresistant cells. In B cells, radiation exposure led to a specific upregulation of genes associated with mitochondrial respiratory chain complexes, suggesting a connection between these complexes and cell radiosensitivity. In neutrophils, radiation exposure resulted in fewer gene alterations, indicating their potential for distinct mechanisms in radiation resistance. Collectively, this study provides insights into the molecular mechanism for the heterogeneity of radiosensitivity among the various bone marrow hematopoietic cell populations.

Distinguishing Quantum Phases through Cusps in Full Counting Statistics.

Measuring physical observables requires averaging experimental outcomes over numerous identical measurements. The complete distribution function of possible outcomes or its Fourier transform, known as the full counting statistics, provides a more detailed description. This method captures the fundamental quantum fluctuations in many-body systems and has gained significant attention in quantum transport research. In this Letter, we propose that cusp singularities in the full counting statistics are a novel tool for distinguishing between ordered and disordered phases. As a specific example, we focus on the superfluid-to-Mott transition in the Bose-Hubbard model. Through both analytical analysis and numerical simulations, we demonstrate that the full counting statistics exhibit a cusp singularity as a function of the phase angle in the superfluid phase when the subsystem size is sufficiently large, while it remains smooth in the Mott phase. This discontinuity can be interpreted as a first-order transition between different semiclassical configurations of vortices. We anticipate that our discoveries can be readily tested using state-of-the-art ultracold atom and superconducting qubit platforms.

Deciphering the Language of Protein-DNA Interactions: A Deep Learning Approach Combining Contextual Embeddings and Multi-Scale Sequence Modeling.

Deciphering the mechanisms governing protein-DNA interactions is crucial for understanding key cellular processes and disease pathways. In this work, we present a powerful deep learning approach that significantly advances the computational prediction of DNA-interacting residues from protein sequences. Our method leverages the rich contextual representations learned by pre-trained protein language models, such as ProtTrans, to capture intrinsic biochemical properties and sequence motifs indicative of DNA binding sites. We then integrate these contextual embeddings with a multi-window convolutional neural network architecture, which scans across the sequence at varying window sizes to effectively identify both local and global binding patterns. Comprehensive evaluation on curated benchmark datasets demonstrates the remarkable performance of our approach, achieving an area under the ROC curve (AUC) of 0.89 - a substantial improvement over previous state-of-the-art sequence-based predictors. This showcases the immense potential of pairing advanced representation learning and deep neural network designs for uncovering the complex syntax governing protein-DNA interactions directly from primary sequences. Our work not only provides a robust computational tool for characterizing DNA-binding mechanisms, but also highlights the transformative opportunities at the intersection of language modeling, deep learning, and protein sequence analysis. The publicly available code and data further facilitate broader adoption and continued development of these techniques for accelerating mechanistic insights into vital biological processes and disease pathways. In addition, the code and data for this work are available at https://github.com/B1607/DIRP.

Brain-wide mapping of c-Fos expression in nitroglycerin-induced models of migraine.

BACKGROUND: Migraine is a neurological disorder characterized by complex, widespread, and sudden attacks with an unclear pathogenesis, particularly in chronic migraine (CM). Specific brain regions, including the insula, amygdala, thalamus, and cingulate, medial prefrontal, and anterior cingulate cortex, are commonly activated by pain stimuli in patients with CM and animal models. This study employs fluorescence microscopy optical sectioning tomography (fMOST) technology and AAV-PHP.eB whole-brain expression to map activation patterns of brain regions in CM mice, thus enhancing the understanding of CM pathogenesis and suggesting potential treatment targets. METHODS: By repeatedly administering nitroglycerin (NTG) to induce migraine-like pain in mice, a chronic migraine model (CMM) was established. Olcegepant (OLC) was then used as treatment and its effects on mechanical pain hypersensitivity and brain region activation were observed. All mice underwent mechanical withdrawal threshold, light-aversive, and elevated plus maze tests. Viral injections were administered to the mice one month prior to modelling, and brain samples were collected 2 h after the final NTG/vehicle control injection for whole-brain imaging using fMOST. RESULTS: In the NTG-induced CMM, mechanical pain threshold decreased, photophobia, and anxiety-like behavior were observed, and OLC was found to improve these manifestations. fMOST whole-brain imaging results suggest that the isocortex-cerebral cortex plate region, including somatomotor areas (MO), somatosensory areas (SS), and main olfactory bulb (MOB), appears to be the most sensitive area of activation in CM (P < 0.05). Other brain regions such as the inferior colliculus (IC) and intermediate reticular nucleus (IRN) were also exhibited significant activation (P < 0.05). The improvement in migraine-like symptoms observed with OLC treatment may be related to its effects on these brain regions, particularly SS, MO, ansiform lobule (AN), IC, spinal nucleus of the trigeminal, caudal part (Sp5c), IRN, and parvicellular reticular nucleus (PARN) (P < 0.05). CONCLUSIONS: fMOST whole-brain imaging reveals c-Fos + cells in numerous brain regions. OLC improves migraine-like symptoms by modulating brain activity in some brain regions. This study demonstrates the activation of the specific brain areas in NTG-induced CMM and suggests some regions as a potential treatment mechanism according to OLC.

Heterometallic Eu/Zn-MOF-based ratiometric sensing platform: Highly sensitive fluorescence / second-order scattering identification of tetracycline analogs and its molecular informatization applications.

The traditional preparation method of ratiometric probes faces challenges such as cumbersome preparation and low sensitivity. Thus, there is an urgent need to provide a simple method of preparing a highly sensitive ratiometric probe. Here, Eu3+-doped zinc-based organic framework (Eu/Zn-MOF) was prepared through hydrothermal method for the detection of tetracycline analogs (TCs). Under the same excitation conditions, the probe can simultaneously display valuable fluorescence and second-order scattering signals. The developed probe enabled specific identification and fast detection (1 min) of TCs, including tetracycline, oxytetracycline, doxycycline, and chlortetracycline. The linear detection ranges of tetracycline, oxytetracycline, doxycycline and chlortetracycline were respectively 100 nM - 200 µM, 100 nM - 200 µM, 98 nM - 195 µM, and 97 nM - 291 µM, and the corresponding detection limits were respectively 15.79 nM, 20.83 nM, 15.31 nM, and 28.30 nM. The developed sensor was successfully applied to detect TCs in real samples, and the recovery rate was from 92.54 % to 109.69 % and the relative standard deviation was from 0.04 % to 2.97 %. Moreover, the heterometallic Eu/Zn-MOF was designed as a ratiometric neuron for Boolean logic computing and information encryption based on the specific identification of TCs. As a proof of concept, molecular steganography was successfully employed to encode, store, and conceal information by transforming the specific identification patterns of Eu/Zn-MOF into binary strings. This study is anticipated to advance the application of metal-organic frameworks in logic detection and information security, and bridging the gap between molecular sensors and the realm of information.

Advances in the study of ferroptosis and its relationship to autoimmune diseases.

Ferroptosis represents a novel mode of programmed cell death characterized by the intracellular accumulation of iron and lipid peroxidation, culminating in oxidative stress and subsequent cell demise. Mounting evidence demonstrates that ferroptosis contributes significantly to the onset and progression of diverse pathological conditions and diseases, including infections, neurodegenerative disorders, tissue ischemia-reperfusion injury, and immune dysregulation. Recent investigations have underscored the pivotal role of ferroptosis in the pathogenesis of rheumatoid arthritis, ulcerative colitis, systemic lupus erythematosus, and asthma. This review provides a comprehensive overview of the current understanding of the regulatory mechanisms governing ferroptosis, particularly its interplay with iron, lipid, and amino acid metabolism. Furthermore, we explore the implications of ferroptosis in autoimmune diseases and deliberate on its potential as a promising therapeutic target for diverse autoimmune disorders.

The role of halophyte-induced saline fertile islands in soil microbial biogeochemical cycling across arid ecosystems.

Halophyte shrubs, prevalent in arid regions globally, create saline fertile islands under their canopy. This study investigates the soil microbial communities and their energy utilization strategies associated with tamarisk shrubs in arid ecosystems. Shotgun sequencing revealed that high salinity in tamarisk islands reduces functional gene alpha-diversity and relative abundance compared to bare soils. However, organic matter accumulation within islands fosters key halophilic archaea taxa such as Halalkalicoccus, Halogeometricum, and Natronorubrum, linked to processes like organic carbon oxidation, nitrous oxide reduction, and sulfur oxidation, potentially strengthening the coupling of nutrient cycles. In contrast, bare soils harbor salt-tolerant microbes with genes for autotrophic energy acquisition, including carbon fixation, H2 or CH4 consumption, and anammox. Additionally, isotope analysis shows higher microbial carbon use efficiency, N mineralization, and denitrification activity in tamarisk islands. Our findings demonstrate that halophyte shrubs serve as hotspots for halophilic microbes, enhancing microbial nutrient transformation in saline soils.

Carbon-metal versus metal-metal synergistic mechanism of ethylene electro-oxidation via electrolysis of water on TM2N6 sites in graphene.

Acetaldehyde (AA) and ethylene oxide (EO) are important fine chemicals, and are also substrates with wide applications for high-value chemical products. Direct electrocatalytic oxidation of ethylene to AA and EO can avoid the untoward effects from harmful byproducts and high energy emissions. The most central intermediate state is the co-adsorption and coupling of ethylene and active oxygen intermediates (*O) at the active site(s), which is restricted by two factors: the stability of the *O intermediate generated during the electrolysis of water on the active site at a certain applied potential and pH range; and the lower kinetic energy barriers of the oxidation process based on the thermo-migration barrier from the *O intermediate to produce AA/EO. The benefit of two adjacent active atoms is more promising, since diverse adsorption and flexible catalytic sites may be provided for elementary reaction steps. Motivated by this strategy, we explored the feasibility of various homonuclear TM2N6@graphenes with dual-atomic-site catalysts (DASCs) for ethylene electro-oxidation through first-principles calculations via thermodynamic evaluation, analysis of the surface Pourbaix diagram, and kinetic evaluation. Two reaction mechanisms through C-TM versus TM-TM synergism were determined. Between them, a TM-TM mechanism on 4 TM2N6@graphenes and a C-TM mechanism on 5 TM2N6@graphenes are built. All 5 TM2N6@graphenes through the C-TM mechanism exhibit lower kinetic energy barriers for AA and EO generation than the 4 TM2N6@graphenes through the TM-TM mechanism. In particular, Pd2N6@graphene exhibits the most excellent catalytic activity, with energy barriers for generating AA and EO of only 0.02 and 0.65 eV at an applied potential of 1.77 V vs. RHE for the generation of an active oxygen intermediate. Electronic structure analysis indicates that the intrinsic C-TM mechanism is more advantageous than the TM-TM mechanism for ethylene electro-oxidation, and this study also provides valuable clues for further experimental exploration.

Women's views and experiences of breastfeeding during the coronavirus disease 2019 pandemic: A systematic review of qualitative evidence.

The coronavirus disease 2019 pandemic affected breastfeeding women in various ways. Understanding their experiences during the pandemic is crucial for informing actionable recommendations, evidence-based strategies and future policies to support breastfeeding during global pandemics. This review aimed to synthesise qualitative evidence on women's breastfeeding perceptions, experiences and support needs during the pandemic. The Joanna Briggs Institute's (JBI) guidelines on systematic reviews of qualitative evidence were followed. MEDLINE, Embase, CINAHL and Web of Science Core Collection databases were searched. Methodological quality of included papers was assessed using JBI's checklist for qualitative research. The synthesised findings were generated using JBI's meta-aggregation approach. The JBI ConQual process was used to rank each synthesised finding. Fifty-two papers were included. The synthesised findings included: (1) women's awareness and commitment to breastfeeding during the pandemic, (2) the multifaceted breastfeeding experiences of women during the pandemic, (3) breastfeeding practices and challenges for working women, (4) professional support during the pandemic: navigating breastfeeding in an evolving health care context and (5) family and peer support groups during the challenging times of the pandemic. Breastfeeding women require clear information, accessible in-person lactation support, family emotional support, food security and protection of psychological well-being. The review reported diverse breastfeeding experiences, from social support challenges to positive aspects like remote work. Breastfeeding support and lactation consultants should be considered as essential services in future pandemics. Food security is crucial for breastfeeding households. Lactation services could prioritise face-to-face consultations for physical challenges and providing online informational support. Future research could explore innovative breastfeeding education strategies.

MCNN_MC: Computational Prediction of Mitochondrial Carriers and Investigation of Bongkrekic Acid Toxicity Using Protein Language Models and Convolutional Neural Networks.

Mitochondrial carriers (MCs) are essential proteins that transport metabolites across mitochondrial membranes and play a critical role in cellular metabolism. ADP/ATP (adenosine diphosphate/adenosine triphosphate) is one of the most important carriers as it contributes to cellular energy production and is susceptible to the powerful toxin bongkrekic acid. This toxin has claimed several lives; for example, a recent foodborne outbreak in Taipei, Taiwan, has caused four deaths and sickened 30 people. The issue of bongkrekic acid poisoning has been a long-standing problem in Indonesia, with reports as early as 1895 detailing numerous deaths from contaminated coconut fermented cakes. In bioinformatics, significant advances have been made in understanding biological processes through computational methods; however, no established computational method has been developed for identifying mitochondrial carriers. We propose a computational bioinformatics approach for predicting MCs from a broader class of secondary active transporters with a focus on the ADP/ATP carrier and its interaction with bongkrekic acid. The proposed model combines protein language models (PLMs) with multiwindow scanning convolutional neural networks (mCNNs). While PLM embeddings capture contextual information within proteins, mCNN scans multiple windows to identify potential binding sites and extract local features. Our results show 96.66% sensitivity, 95.76% specificity, 96.12% accuracy, 91.83% Matthews correlation coefficient (MCC), 94.63% F1-Score, and 98.55% area under the curve (AUC). The results demonstrate the effectiveness of the proposed approach in predicting MCs and elucidating their functions, particularly in the context of bongkrekic acid toxicity. This study presents a valuable approach for identifying novel mitochondrial complexes, characterizing their functional roles, and understanding mitochondrial toxicology mechanisms. Our findings, that utilize computational methods to improve our understanding of cellular processes and drug-target interactions, contribute to the development of therapeutic strategies for mitochondrial disorders, reducing the devastating effects of bongkrekic acid poisoning.

[Dobutamine Enhances the Targeted Inhibitory Effect of Quizartinib on FLT3-ITD Mutant Acute Myeloid Leukemia].

OBJECTIVE: To observe the inhibitory effect of dobutamine on proliferation of FLT3-ITD mutated acute myeloid leukemia (AML) cells and explore the feasibility of dobutamine as a monotherapy or in combination with quizartinib for the treatment of this type of AML. METHODS: FLT3-ITD mutant cell lines MOLM13 and MV4-11 were cultured in vitro and divided into control group, dobutamine treatment group, quizartinib treatment group, and dobutamine combined with quizartinib treatment group. Cell viability, ROS levels, and apoptosis rate were detected by CCK-8, Flow cytometry, respectively, as well as the expression of YAP1 protein by Western blot. RESULTS: Both dobutamine and quizartinib inhibited the proliferation of FLT3-ITD mutant AML cell lines. Compared with the control group, the dobutamine group exhibited a significant increase in ROS levels (P < 0.01), an increase in apoptosis rates (P < 0.05), and a decrease in YAP1 protein expression (P < 0.01), and decreased YAP1 expression (P < 0.05). CONCLUSION: Dobutamine as a monotherapy can inhibit theproliferation of FLT3-ITD mutated AML cells, inducing apoptosis. Additionally, the combination of quizartinib enhances the targeted inhibitory effect on FLT3-ITD mutated AML. The mechanism may involve the inhibition of YAP1 protein expression in AML cells of this type, leading to an increase in ROS levels and exerting its anti-tumor effects.

LASSO-derived nomogram for early identification of pediatric monogenic lupus.

BACKGROUND: Monogenic lupus is defined as systemic lupus erythematosus (SLE)/SLE-like patients with either dominantly or recessively inherited pathogenic variants in a single gene with high penetrance. However, because the clinical phenotype of monogenic SLE is extensive and overlaps with that of classical SLE, it causes a delay in diagnosis and treatment. Currently, there is a lack of early identification models for clinical practitioners to provide early clues for recognition. Our goal was to create a clinical model for the early identification of pediatric monogenic lupus, thereby facilitating early and precise diagnosis and treatment for patients. METHODS: This retrospective cohort study consisted of 41 cases of monogenic lupus treated at the Department of Pediatrics at Peking Union Medical College Hospital from June 2012 to December 2022. The control group consisted of classical SLE patients recruited at a 1:2 ratio. Patients were randomly divided into a training group and a validation group at a 7:3 ratio. A logistic regression model was established based on the least absolute shrinkage and selection operator to generate the coefficient plot. The predictive ability of the model was evaluated using receiver operator characteristic curves and the area under the curve (AUC) index. RESULTS: A total of 41 cases of monogenic lupus patients and 82 cases of classical SLE patients were included. Among the monogenic lupus cases (with a male-to-female ratio of 1:1.05 and ages of onset ranging from birth to 15 years), a total of 18 gene mutations were identified. The variables included in the coefficient plot were age of onset, recurrent infections, intracranial calcifications, growth and developmental delay, abnormal muscle tone, lymphadenopathy/hepatosplenomegaly, and chilblain-like skin rash. Our model demonstrated satisfactory diagnostic performance through internal validation, with an AUC value of 0.97 (95% confidence interval = 0.92-0.97). CONCLUSIONS: We summarized and analyzed the clinical characteristics of pediatric monogenic lupus and developed a predictive model for early identification by clinicians. Clinicians should exercise high vigilance for monogenic lupus when the score exceeds - 9.032299.

Measurement of Intracellular Ca2+ for Studying GPCR-Mediated Lipid Signaling.

Intracellular Ca2+ can be conveniently monitored by sensitive Ca2+ fluorescent dyes in live cells. The Gαq involved lipid signaling pathways and, thus, can be studied by intracellular Ca2+ imaging. Here we describe the protocols to measure intracellular Ca2+ for studying PEG2-EP1 activity in esophageal smooth muscle cells. The ratiometric Fura-2 imaging provides quantitative data, and the Fluo-4 confocal microscopic imaging has high-spatial resolution.

The role of exosomal lncRNAs in acetaminophen-induced induced liver injury in SD rats.

Background: Drug-induced liver injury (DILI) is a leading cause of drug development failures during clinical trials and post-market introduction. Current biomarkers, such as ALT and AST, lack the necessary specificity and sensitivity needed for accurate detection. Exosomes, which protect LncRNAs from RNase degradation, could provide reliable and easily accessible options for biomarkers. Materials and methods: RNA-sequencing was used to identify differentially expressed LncRNAs (DE-LncRNAs), followed by isolation of LncRNAs from plasma exosomes in this study. Exosome characterization was conducted by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blot (WB). Bioinformatics analysis included functional enrichment and co-expression network analysis. Five rat models were established, and quantitative real-time PCR was used to verify the specificity and sensitivity of two candidate exosomal LncRNAs. Results: The APAP-induced hepatocellular injury model was successfully established for RNA-sequencing, leading to the identification of several differentially expressed exosomal LncRNAs. Eight upregulated exosomal DE-LncRNAs were selected for validation. Among them, NONRATT018001.2 (p < 0.05) and MSTRG.73954.4 (p < 0.05) exhibited a more than 2-fold increase in expression levels. In hepatocellular injury and intrahepatic cholestasis models, both NONRATT018001.2 and MSTRG.73954.4 showed earlier increases compared to serum biomarkers ALT and AST. However, no histological changes were observed until the final time point. In the fatty liver model, NONRATT018001.2 and MSTRG.73954.4 increased earlier than ALT and AST at 21 days. By the 7th day, minor steatosis was evident in liver tissue, while the expression levels of the two candidate exosomal LncRNAs exceeded 2 and 4 times, respectively. In the hepatic fibrosis model, NONRATT018001.2 and MSTRG.73954.4 showed increases at every time point. By the 49th day, hepatocellular necrosis and fibrosis were observed in the liver tissue, with NONRATT018001.2 showing an increase of more than 8 times. The specificity of the identified exosomal DE-LncRNAs was verified using a myocardial injury model and they showed no significant differences between the case and control groups. Conclusion: NONRATT018001.2 and MSTRG.73954.4 hold potential as biomarkers for distinguishing different types of organ injury induced by drugs, particularly enabling early prediction of liver injury. Further experiments, such as siRNA interference or gene knockout, are warranted to explore the underlying mechanisms of these LncRNAs.

A novel bioaccessibility-based probabilistic risks assessment of potentially toxic elements (PTEs) in earthworm.

Introduction: Early risk assessment studies usually based on total heavy metal (loid) contents, inevitably leading to an overestimation of the health risks. In addition, inputs are represented as single-point estimates in deterministic models, leading to underestimation or overestimation of the health risks. Methods: To overcome these barriers, a novel probabilistic risk assessment strategy based on the combinational use of bioaccessibility and Monte Carlo simulation was developed to assess heavy metal (loid) associated health risks of earthworms in this study. To obtain a realistic and robust probabilistic risk assessment, heavy metal (loid) exposure duration and frequency were determined using our questionnaire data. Results: As a result, the mean gastrointestinal bioaccessibility was in the order: Cd > As > Cu > Hg. The mean hazard index (HI) values for investigated metal (loid)s were 0.65 and 0.59 for male and female, respectively, demonstrating an acceptable health risk in an average community. However, the 90th percentile of HI values was 1.87 and 1.65 for male and female, respectively. And the total non-cancer risks of heavy metal (loid) exposure exceeded the acceptable threshold for 19.9% and 17.8% of male and female, respectively. In addition, the total cancer risk (TCR) value through co-exposure to As and Cd suggested that the carcinogenic risks may be of concern for average exposure population. Sensitivity analyses revealed that the exposure frequency and bioaccessible As concentration were the dominant contributors to the total risk variance, which provided meaningful implications for environmental management. Conclusion: Altogether, the refined strategy based on bioaccessibility and Monte Carlo simulation is the first of its kind, such effort attempts to scientifically guide the rational clinic use of TCM and the improvement of population-health.