Abstract: To explore the molecular mechanism by which long non-coding RNA Surfactant Associated 1 Pseudogene(SFTA1P) promotes the proliferation and migration of clear cell renal cell carcinoma(ccRCC) cells by regulating the microRNA-182-5p(miR-182-5p)/fibronectin 1(FN1) pathway. Methods: GEPIA2 software was utilized to analyze the expression ofSFTA1Pin ccRCC tissues from the TCGA database. Quantitative real-time PCR(qPCR) was employed to detect the expression ofSFTA1Pin ccRCC tissues, normal kidney tissues and ccRCC cell lines. A subcellular localization experiment was performed to explore the localization ofSFTA1Pwithin the human renal cell adenocarcinoma cell line(ACHN) derived from ccRCC. ACHN cells were then divided into the following groups: si-Con group, si-SFTA1P #2 group, mimic NC group, miR-182-5p mimic group, anti-miR-Con group, anti-miR-182-5p group, anti-miR-182-5p+si-FN1 group, si-Con+anti-miR-Con group, si-SFTA1P #2+anti-miR-Con group, and si-SFTA1P #2+anti-miR-182-5p group. CCK-8 and Transwell chamber experiments were conducted to assess cell proliferation and migration abilities. qPCR, Western blot, and dual-luciferase reporter assays were employed to elucidate the regulatory interactions amongSFTA1P,miR-182-5p, andFN1. Results: Analysis of The Cancer Genome Atlas(TCGA) database indicated thatSFTA1Pwas overexpressed in ccRCC tissues(P<0.05). When compared to normal kidney tissues,SFTA1Pexpression was markedly elevated in ccRCC tissues(P<0.01). Furthermore, the expression levels ofSFTA1Pin ccRCC cell lines 786-O, SN12-PM6, ACHN, and A498 were significantly higher than those in human renal proximal tubule cells(HK-2)(allP<0.01). Subcellular localization experiments revealed thatSFTA1Ppredominantly localized in the cytoplasm of ACHN cells. Compared to the si-Con group, the si-SFTA1P #2 group exhibited a significant reduction in proliferation and migration abilities of ACHN cells, accompanied by a decrease inFN1mRNA and protein expression(P<0.05). Compared to the mimic NC group, the expression ofFN1mRNA and protein in ACHN cells in the miR-182-5p mimic group reduced(P<0.01). In comparison to the anti-miR-Con group, the expression levels ofFN1mRNA and protein in ACHN cells were significantly elevated in the anti-miR-182-5p group. Additionally, there was a significant enhancement in both cell proliferation and migration capabilities(P<0.05). Conversely, the proliferation and migration abilities of ACHN cells in the anti-miR-182-5p+si-FN1 group were significantly reduced compared to the anti-miR-182-5p group(P<0.05). Furthermore, relative to the si-SFTA1P #2+anti-miR-Con group, the ACHN cells in the si-SFTA1P #2+anti-miR-182-5p group demonstrated increased proliferation and migration abilities, along with elevatedFN1mRNA and protein expression levels(P<0.05). Conclusion SFTA1Pexhibits elevated expression levels in ccRCC and facilitates the proliferation and migration of ccRCC cells through the modulation of themiR-182-5p/FN1signaling pathway.

Ischemic stroke is the leading cause of disability and mortality worldwide. The blood‒brain barrier (BBB) is the first line of defense after ischemic stroke. Disruption of the BBB induced by brain microvascular endothelial cells (BMECs) dysfunction is a key event that triggers secondary damage to the central nervous system, where blood-borne fluids and immune cells penetrate the brain parenchyma, causing cerebral edema and inflammatory response and further aggravating brain damage. Here, we develop a novel artificial mesenchymal stem cell (MSC) extracellular vesicles by integrating MSC membrane proteins into liposomal bilayers, which encapsulated miR-132-3p with protective effects on BMECs. The artificial extracellular vesicles (MSCo/miR-132-3p) had low immunogenicity to reduce non-specific clearance by the mononuclear phagocytosis system (MPS) and could target ischemia-injured BMECs. After internalization into the damaged BMECs, MSCo/miR-132-3p escaped the lysosomes via the H_II phase transition of 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) and decreased cellular reactive oxygen species (ROS) and apoptosis levels by regulating the RASA1/RAS/PI3K/AKT signaling pathway. In the transient middle cerebral artery occlusion (tMCAO) models, MSCo/miR-132-3p targeted impaired brain regions (approximately 9 times the accumulation of plain liposomes at 12 h), reduced cerebral vascular disruption, protected BBB integrity, and decreased infarct volume (from 44.95% to 6.99%).

Direct electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations.
Humans ; Male ; Female ; Adult ; Visual Perception/physiology* ; Electric Stimulation ; Middle Aged ; Young Adult ; Electrocorticography ; Electroencephalography ; Brain Mapping

Sennoside A (SA), a typical prodrug, exerts its laxative effect only after its transformation into rheinanthrone catalyzed by gut microbial hydrolases and reductases. Hydrolases have been identified, but reductases remain unknown. By linking a photoreactive group to the SA scaffold, we synthesized a photoaffinity probe to covalently label SA reductases and identified SA reductases using activity-based protein profiling (ABPP). From lysates of an active strain, Bifidobacterium pseudocatenulatum (B. pseudocatenulatum), 397 proteins were enriched and subsequently identified using mass spectrometry (MS). Among these proteins, chromate reductase/nicotinamide adenine dinucleotide (NADH) phosphate (NADPH)-dependent flavin mononucleotide (FMN) reductase/oxygen-insensitive NADPH nitroreductase (nfrA) was identified as a potent SA reductase through further bioinformatic analysis and The Universal Protein Resource (UniProt) database screening. We also determined that recombinant nfrA could reduce SA. Our study contributes to further illuminating mechanisms of SA transformation to rheinanthrone and simultaneously offers an effective method to identify gut bacterial reductases.

Image 1.

Accurate prediction of drug-induced adverse drug reactions (ADRs) is crucial for drug safety evaluation, as it directly impacts public health and safety. While various models have shown promising results in predicting ADRs, their accuracy still needs improvement. Additionally, many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints, which can introduce bias. To address these challenges, we propose ToxBERT, an efficient transformer encoder model that leverages attention and masking mechanisms for simplified molecular input line entry system (SMILES) representations. Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve (AUROC) scores of 0.839, 0.759, and 0.664 for predicting drug-induced QT prolongation (DIQT), rhabdomyolysis, and liver injury, respectively, outperforming previous studies. Furthermore, ToxBERT can identify drug substructures that are closely associated with specific ADRs. These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.

Efficient drug response prediction is crucial for reducing drug development costs and time, but current computational models struggle with limited experimental data and out-of-distribution issues between in vitro and in vivo settings. To address this, we introduced drug response prediction meta-learner (metaDRP), a novel few-shot learning model designed to enhance predictive accuracy with limited sample sizes across diverse drug-tissue tasks. metaDRP achieves performance comparable to state-of-the-art models in both genomics of drug sensitivity in cancer (GDSC) drug screening and in vivo datasets, while effectively mitigating out-of-distribution problems, making it reliable for translating findings from controlled environments to clinical applications. Additionally, metaDRP's inherent interpretability offers reliable insights into drug mechanisms of action, such as elucidating the pathways and molecular targets of drugs like epothilone B and pemetrexed. This work provides a promising approach to overcoming data scarcity and out-of-distribution challenges in drug response prediction, while promoting the integration of few-shot learning in this field.

Accurate prediction of drug-induced adverse drug reactions(ADRs)is crucial for drug safety evaluation,as it directly impacts public health and safety.While various models have shown promising results in predicting ADRs,their accuracy still needs improvement.Additionally,many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints,which can introduce bias.To address these challenges,we propose ToxBERT,an efficient transformer encoder model that leverages attention and masking mechanisms for simplified molecular input line entry system(SMILES)representations.Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve(AUROC)scores of 0.839,0.759,and 0.664 for predicting drug-induced QT prolongation(DIQT),rhabdomyolysis,and liver injury,respectively,outperforming previous studies.Furthermore,ToxBERT can identify drug substructures that are closely associated with specific ADRs.These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.

Sennoside A(SA),a typical prodrug,exerts its laxative effect only after its transformation into rhei-nanthrone catalyzed by gut microbial hydrolases and reductases.Hydrolases have been identified,but reductases remain unknown.By linking a photoreactive group to the SA scaffold,we synthesized a photoaffinity probe to covalently label SA reductases and identified SA reductases using activity-based protein profiling(ABPP).From lysates of an active strain,Bifidobacterium pseudocatenulatum(B.pseu-docatenulatum),397 proteins were enriched and subsequently identified using mass spectrometry(MS).Among these proteins,chromate reductase/nicotinamide adenine dinucleotide(NADH)phosphate(NADPH)-dependent flavin mononucleotide(FMN)reductase/oxygen-insensitive NADPH nitroreductase(nfrA)was identified as a potent SA reductase through further bioinformatic analysis and The Universal Protein Resource(UniProt)database screening.We also determined that recombinant nfrA could reduce SA.Our study contributes to further illuminating mechanisms of SA transformation to rheinanthrone and simultaneously offers an effective method to identify gut bacterial reductases.