Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations.

Connections between circular RNAs (circRNAs) and microRNAs (miRNAs) assume a pivotal position in the onset, evolution, diagnosis and treatment of diseases and tumors. Selecting the most potential circRNA-related miRNAs and taking advantage of them as the biological markers or drug targets could be conducive to dealing with complex human diseases through preventive strategies, diagnostic procedures and therapeutic approaches. Compared to traditional biological experiments, leveraging computational models to integrate diverse biological data in order to infer potential associations proves to be a more efficient and cost-effective approach. This paper developed a model of Convolutional Autoencoder for CircRNA-MiRNA Associations (CA-CMA) prediction. Initially, this model merged the natural language characteristics of the circRNA and miRNA sequence with the features of circRNA-miRNA interactions. Subsequently, it utilized all circRNA-miRNA pairs to construct a molecular association network, which was then fine-tuned by labeled samples to optimize the network parameters. Finally, the prediction outcome is obtained by utilizing the deep neural networks classifier. This model innovatively combines the likelihood objective that preserves the neighborhood through optimization, to learn the continuous feature representation of words and preserve the spatial information of two-dimensional signals. During the process of 5-fold cross-validation, CA-CMA exhibited exceptional performance compared to numerous prior computational approaches, as evidenced by its mean area under the receiver operating characteristic curve of 0.9138 and a minimal SD of 0.0024. Furthermore, recent literature has confirmed the accuracy of 25 out of the top 30 circRNA-miRNA pairs identified with the highest CA-CMA scores during case studies. The results of these experiments highlight the robustness and versatility of our model.

Biolinguistic graph fusion model for circRNA-miRNA association prediction.

Emerging clinical evidence suggests that sophisticated associations with circular ribonucleic acids (RNAs) (circRNAs) and microRNAs (miRNAs) are a critical regulatory factor of various pathological processes and play a critical role in most intricate human diseases. Nonetheless, the above correlations via wet experiments are error-prone and labor-intensive, and the underlying novel circRNA-miRNA association (CMA) has been validated by numerous existing computational methods that rely only on single correlation data. Considering the inadequacy of existing machine learning models, we propose a new model named BGF-CMAP, which combines the gradient boosting decision tree with natural language processing and graph embedding methods to infer associations between circRNAs and miRNAs. Specifically, BGF-CMAP extracts sequence attribute features and interaction behavior features by Word2vec and two homogeneous graph embedding algorithms, large-scale information network embedding and graph factorization, respectively. Multitudinous comprehensive experimental analysis revealed that BGF-CMAP successfully predicted the complex relationship between circRNAs and miRNAs with an accuracy of 82.90% and an area under receiver operating characteristic of 0.9075. Furthermore, 23 of the top 30 miRNA-associated circRNAs of the studies on data were confirmed in relevant experiences, showing that the BGF-CMAP model is superior to others. BGF-CMAP can serve as a helpful model to provide a scientific theoretical basis for the study of CMA prediction.

Phase-separated ParB enforces diverse DNA compaction modes and stabilizes the parS-centered partition complex.

The tripartite ParABS system mediates chromosome segregation in the majority of bacterial species. Typically, DNA-bound ParB proteins around the parS sites condense the chromosomal DNA into a higher-order multimeric nucleoprotein complex for the ParA-driven partition. Despite extensive studies, the molecular mechanism underlying the dynamic assembly of the partition complex remains unclear. Herein, we demonstrate that Bacillus subtilis ParB (Spo0J), through the multimerization of its N-terminal domain, forms phase-separated condensates along a single DNA molecule, leading to the concurrent organization of DNA into a compact structure. Specifically, in addition to the co-condensation of ParB dimers with DNA, the engagement of well-established ParB condensates with DNA allows for the compression of adjacent DNA and the looping of distant DNA. Notably, the presence of CTP promotes the formation of condensates by a low amount of ParB at parS sites, triggering two-step DNA condensation. Remarkably, parS-centered ParB-DNA co-condensate constitutes a robust nucleoprotein architecture capable of withstanding disruptive forces of tens of piconewton. Overall, our findings unveil diverse modes of DNA compaction enabled by phase-separated ParB and offer new insights into the dynamic assembly and maintenance of the bacterial partition complex.

PharmBERT: a domain-specific BERT model for drug labels.

Human prescription drug labeling contains a summary of the essential scientific information needed for the safe and effective use of the drug and includes the Prescribing Information, FDA-approved patient labeling (Medication Guides, Patient Package Inserts and/or Instructions for Use), and/or carton and container labeling. Drug labeling contains critical information about drug products, such as pharmacokinetics and adverse events. Automatic information extraction from drug labels may facilitate finding the adverse reaction of the drugs or finding the interaction of one drug with another drug. Natural language processing (NLP) techniques, especially recently developed Bidirectional Encoder Representations from Transformers (BERT), have exhibited exceptional merits in text-based information extraction. A common paradigm in training BERT is to pretrain the model on large unlabeled generic language corpora, so that the model learns the distribution of the words in the language, and then fine-tune on a downstream task. In this paper, first, we show the uniqueness of language used in drug labels, which therefore cannot be optimally handled by other BERT models. Then, we present the developed PharmBERT, which is a BERT model specifically pretrained on the drug labels (publicly available at Hugging Face). We demonstrate that our model outperforms the vanilla BERT, ClinicalBERT and BioBERT in multiple NLP tasks in the drug label domain. Moreover, how the domain-specific pretraining has contributed to the superior performance of PharmBERT is demonstrated by analyzing different layers of PharmBERT, and more insight into how it understands different linguistic aspects of the data is gained.

Phenotypic Heterogeneity Analysis of APC-Mutant Colon Cancer by Proteomics and Phosphoproteomics Identifies RAI14 as a Key Prognostic Determinant in East Asians and Westerners.

Adenomatous polyposis coli (APC) is an important tumor suppressor and is mostly linked to the regulation of the Wnt/ß-catenin signaling pathway. APC mutation has been identified as an early event in more than 80% of sporadic colorectal cancers (CRCs). Moreover, prognostic differences are observed in CRC patients with APC mutations. Although previous genomics studies have investigated the roles of concomitant gene mutations in determining the phenotypic heterogeneity of APC-mutant tumors, valuable prognostic determinants for APC-mutant CRC patients are still lacking. Based on the proteome and phosphoproteome data, we classified APC-mutant colon cancer patients and revealed genomic, proteomic, and phosphoproteomic heterogeneity in APC-mutant tumors. More importantly, we identified RAI14 as a key prognostic determinant for APC-mutant but not APC-wildtype colon cancer patients. The heterogeneity and the significance of prognostic biomarkers in APC-mutant tumors were further validated in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) colon cancer cohort. In addition, we found that colon cancer patients with high expression of RAI14 were less responsive to chemotherapy. Knockdown of RAI14 in cell lines led to reduced cell migration and changes in epithelial-mesenchymal transition (EMT)-related markers. Mechanistically, knockdown of RAI14 remodeled the phosphoproteome associated with cell adhesion, which might affect EMT marker expression and promote F-actin degradation. Collectively, this work describes the phenotypic heterogeneity of APC-mutant tumors and identifies RAI14 as an important prognostic determinant for APC-mutant colon cancer patients. The prognostic utility of RAI14 in APC-mutant colon cancer will provide early warning and increase the chance of successful treatment.

Deciphering the Clinical Significance and Kinase Functions of GSK3α in Colon Cancer by Proteomics and Phosphoproteomics.

GSK3α and GSK3ß are two GSK3 isoforms with 84% overall identity and 98% identity in their catalytic domains. GSK3ß plays important roles in the pathogenesis of cancer, while GSK3α has long been considered a functionally redundant protein of GSK3ß. Few studies have specifically investigated the functions of GSK3α. In this study, unexpectedly, we found that the expression of GSK3α, but not GSK3ß, was significantly correlated with the overall survival of colon cancer patients in 4 independent cohorts. To decipher the roles of GSK3α in colon cancer, we profiled the phosphorylation substrates of GSK3α and uncovered 156 phosphosites from 130 proteins specifically regulated by GSK3α. A number of these GSK3α-mediated phosphosites have never been reported before or have been incorrectly identified as substrates of GSK3ß. Among them, the levels of HSF1S303p, CANXS583p, MCM2S41p, POGZS425p, SRRM2T983p, and PRPF4BS431p were significantly correlated with the overall survival of colon cancer patients. Further pull-down assays identified 23 proteins, such as THRAP3, BCLAF1, and STAU1, showing strong binding affinity to GSK3α. The interaction between THRAP3 and GSK3α was verified by biochemical experiments. Notably, among the 18 phosphosites of THRAP3, phosphorylation at S248, S253, and S682 is specifically mediated by GSK3α. Mutation of S248 to D (S248D), which mimics the effect of phosphorylation, obviously increased cancer cell migration and the binding affinity to proteins related to DNA damage repair. Collectively, this work not only discloses the specific function of GSK3α as a kinase but also suggests GSK3α as a promising therapeutic target for colon cancer.

RTL1/PEG11 imprinted in human and mouse brain mediates anxiety-like and social behaviors and regulates neuronal excitability in the locus coeruleus.

RTL1/PEG11, which has been associated with anxiety disorders, is a retrotransposon-derived imprinted gene in the placenta. However, imprinting patterns and functions of RTL1 in the brain have not been well-investigated. We found Rtl1 was paternally, but not maternally, expressed in brain stem, thalamus, and hypothalamus of mice, and imprinting status of RTL1 was maintained in human brain. Paternal Rtl1 knockout (Rtl1m+/p-) mice had higher neonatal death rates due to impaired suckling, and low body weights beginning on embryonic day 16.5. High paternal expression of Rtl1 was detected in the locus coeruleus (LC) and Rtl1m+/p- mice showed an increased delay in time of onset for action potentials and inward currents with decreased neuronal excitability of LC neurons. Importantly, Rtl1m+/p- mice exhibited behaviors associated with anxiety, depression, fear-related learning and memory, social dominance, and low locomotor activity. Taken together, our findings demonstrate RTL1 is imprinted in brain, mediates emotional and social behaviors, and regulates excitability in LC neurons.

Dendritic morphology of developing hippocampal neurons in Cyp11a1 null mice.

INTRODUCTION: Neurosteroids have a variety of neurological functions, such as neurite growth, neuroprotection, myelination, and neurogenesis. P450scc, encoded by CYP11A1 gene, is the cholesterol side chain cleavage enzyme that catalyzes the first and rate limiting step in the steroidogenesis. In this study, we examine the dendritic morphology in developing hippocampal neurons of Cyp11a1 null mice at P15, a critical period for synapse formation and maturation. METHODS: Knockout mice were maintained until P15 with hormone administration. The Golgi-Cox method stained CA1 and CA3 pyramidal neurons in the hippocampus to reveal dendritic morphology. RESULTS: We demonstrated that Cyp11a1 null mice usually die within 7 days after birth and thus collected brain samples at postnatal day 5 (P5) for examination. There were significant shrinkage of dendrite size and diminishment of dendritic branching in CA1 and CA3 pyramidal neurons in the hippocampus of Cyp11a1 null mice, suggesting a developmental delay. We wonder if this delay may catch up later in life. Since the age of P15 is a critical period for synapse formation and maturation, the Cyp11a1 null mice were rescued by receiving hormone administration until P15 that the dendritic morphology in the developing hippocampal neurons could be examined. The results indicated that the total dendritic length, number of dendritic branches, as well as dendritic arborization in the CA1 and CA3 pyramidal neurons are significantly decreased in P15 knockout mice when compared to the wild type. The spine densities were also significantly decreased. In addition, the western blot analysis revealed decrease PSD-95 expression levels in the knockout mice compared to the wild type at P15. CONCLUSION: These results suggested that Cyp11a1 deficiency impairs the dendritic structures in the developing hippocampal pyramidal neurons.

PagJAZ5 regulates cambium activity through coordinately modulating cytokinin concentration and signaling in poplar.

Wood is resulted from the radial growth paced by the division and differentiation of vascular cambium cells in woody plants, and phytohormones play important roles in cambium activity. Here, we identified that PagJAZ5, a key negative regulator of jasmonate (JA) signaling, plays important roles in enhancing cambium cell division and differentiation by mediating cytokinin signaling in poplar 84K (Populus alba × Populus glandulosa). PagJAZ5 is preferentially expressed in developing phloem and cambium, weakly in developing xylem cells. Overexpression (OE) of PagJAZ5m (insensitive to JA) increased cambium activity and xylem differentiation, while jaz mutants showed opposite results. Transcriptome analyses revealed that cytokinin oxidase/dehydrogenase (CKXs) and type-A response regulators (RRs) were downregulated in PagJAZ5m OE plants. The bioactive cytokinins were significantly increased in PagJAZ5m overexpressing plants and decreased in jaz5 mutants, compared with that in 84K plants. The PagJAZ5 directly interact with PagMYC2a/b and PagWOX4b. Further, we found that the PagRR5 is regulated by PagMYC2a and PagWOX4b and involved in the regulation of xylem development. Our results showed that PagJAZ5 can increase cambium activity and promote xylem differentiation through modulating cytokinin level and type-A RR during wood formation in poplar.

Mesenchymal Stromal Cells Facilitate Tip Cell Fusion Downstream of BMP-Mediated Venous Angiogenesis-Brief Report.

BACKGROUND: The goal of this study was to identify and characterize cell-cell interactions that facilitate endothelial tip cell fusion downstream of BMP (bone morphogenic protein)-mediated venous plexus formation. METHODS: High resolution and time-lapse imaging of transgenic reporter lines and loss-of-function studies were carried out to study the involvement of mesenchymal stromal cells during venous angiogenesis. RESULTS: BMP-responsive stromal cells facilitate timely and precise fusion of venous tip cells during developmental angiogenesis. CONCLUSIONS: Stromal cells are required for anastomosis of venous tip cells in the embryonic caudal hematopoietic tissue.

Organo-photoredox catalyzed gem-difluoroallylation of ketone-derived dihydroquinazolinones via C(sp3)-C bond and C(sp3)-F bond cleavage.

An organo-photoredox catalyzed gem-difluoroallylation of both acyclic and cyclic ketone derivatives with α-trifluoromethyl alkenes has been demonstrated, thus giving access to a diverse set of gem-difluoroalkenes in moderate to high yields. Pro-aromatic dihydroquinazolinones can be either pre-formed or in situ generated for ketone activation. This reaction is characterized by readily available starting materials, mild reaction conditions, and broad substrate scope. The feasibility of this reaction has been highlighted by the late-stage modification of several natural products and drug-like molecules as well as the in vitro antifungal activity.

Bacteremia caused by Nocardia farcinica: a case report and literature review.

BACKGROUND: Nocardia farcinica is one of the most common Nocardia species causing human infections. It is an opportunistic pathogen that often infects people with compromised immune systems. It could invade human body through respiratory tract or skin wounds, cause local infection, and affect other organs via hematogenous dissemination. However, N. farcinica-caused bacteremia is uncommon. In this study, we report a case of bacteremia caused by N. farcinica in China. CASE PRESENTATION: An 80-year-old woman was admitted to Peking Union Medical College Hospital with recurrent fever, right abdominal pain for one and a half month, and right adrenal gland occupation. N. farcinica was identified as the causative pathogen using blood culture and plasma metagenomics next-generation sequencing (mNGS). The clinical considerations included bacteremia and adrenal gland abscess caused by Nocardia infection. As the patient was allergic to sulfanilamide, imipenem/cilastatin and linezolid were empirically administered. Unfortunately, the patient eventually died less than a month after the initiation of anti-infection treatment. CONCLUSION: N. farcinica bacteremia is rare and its clinical manifestations are not specific. Its diagnosis depends on etiological examination, which can be confirmed using techniques such as Sanger sequencing and mNGS. In this report, we have reviewed cases of Nocardia bloodstream infection reported in the past decade, hoping to improve clinicians' understanding of Nocardia bloodstream infection and help in its early diagnosis and timely treatment.

The smallest Schwarzite carbon with only heptagonal carbon rings.

Carbon materials with full sp2-hybridized buckling is a major challenge pervading fundamental nanoscience and nanotechnology research. Carbon atoms that are sp2 hybridized prefer to form hexagonal rings, such as in carbon nanotubes and graphene, which are low-dimensional materials. The incorporation of heptagonal, octagonal, and/or larger rings into a hexagonal sp2 carbon meshwork has been identified as a strategy for assembling three-dimensional (3D) sp2 carbon crystals, and one of the typical representatives are Schwarzite carbons, which possess a negative surface Gaussian curvature as well as unique physical properties. Herein, a 3D Schwarzite carbon consisting of only sp2-buckled heptagonal carbon rings, which is referred to as Hepta-carbon, is proposed based on first-principles calculations. Hepta-carbon is mechanically and thermodynamically stable, and energetically more favourable than experimental graphdiyne, fullerene C20 and most Schwarzite carbons under ambient conditions. Molecular dynamics simulations indicate that Hepta-carbon exhibits high-temperature thermostability up to 1500 K. Band structure and mechanical property simulations indicate that Hepta-carbon is a semi-metallic material with electron conduction and exhibits impressive mechanical properties such as high strength with quasi-isotropy, high incompressibility similar to diamonds, elastic deformation behaviour under uniaxial stress, and high ductility. Hepta-carbon presents a porous network with a low mass density of 1.84 g cm-3 and connected channels with diameters of 3.3-6.1 Å. Theoretical simulations of gas adsorption energy demonstrate that Hepta-carbon can effectively adsorb and stabilize greenhouse gases, including N2O, CO2, CH4, and SF6.

Quantifying the energy landscape in weakly and strongly disordered frictional media.

We investigate the "roughness" of the energy landscape of a system that diffuses in a heterogeneous medium with a random position-dependent friction coefficient α(x). This random friction acting on the system stems from spatial inhomogeneity in the surrounding medium and is modeled using the generalized Caldira-Leggett model. For a weakly disordered medium exhibiting a Gaussian random diffusivity D(x) = kBT/α(x) characterized by its average value ⟨D(x)⟩ and a pair-correlation function ⟨D(x1)D(x2)⟩, we find that the renormalized intrinsic diffusion coefficient is lower than the average one due to the fluctuations in diffusivity. The induced weak internal friction leads to increased roughness in the energy landscape. When applying this idea to diffusive motion in liquid water, the dissociation energy for a hydrogen bond gradually approaches experimental findings as fluctuation parameters increase. Conversely, for a strongly disordered medium (i.e., ultrafast-folding proteins), the energy landscape ranges from a few to a few kcal/mol, depending on the strength of the disorder. By fitting protein folding dynamics to the escape process from a metastable potential, the decreased escape rate conceptualizes the role of strong internal friction. Studying the energy landscape in complex systems is helpful because it has implications for the dynamics of biological, soft, and active matter systems.

In biased and soft-walled channels: Insights into transport phenomena and damped modulation.

The motion of a particle along a channel of finite width is known to be affected by either the presence of energy barriers or changes in the bias forces along the channel direction. By using the lateral equilibrium hypothesis, we have successfully derived the effective diffusion coefficient for soft-walled channels, and the diffusion is found to be influenced by the curvature profile of the potential. A typical phenomenon of diffusion enhancement is observed under the appropriate parameter conditions. We first discovered an anomalous phenomenon of quasi-periodic enhancement of oscillations, which cannot be captured by the one-dimensional effective potential, under the combination of sub-Ohmic damping with two-dimensional restricted channels. We innovatively develop the effective potential and the formation mechanism of velocity variance under super-Ohmic and ballistic damping, and meanwhile, ergodicity is of concern. The theoretical framework of a ballistic system can be reinterpreted through the folding acceleration theory. This comprehensive analysis significantly enhances our understanding of diffusion processes in constrained geometries.

pyDarwin machine learning algorithms application and comparison in nonlinear mixed-effect model selection and optimization.

Forward addition/backward elimination (FABE) has been the standard for population pharmacokinetic model selection (PPK) since NONMEM® was introduced. We investigated five machine learning (ML) algorithms (Genetic algorithm [GA], Gaussian process [GP], random forest [RF], gradient boosted random tree [GBRT], and particle swarm optimization [PSO]) as alternatives to FABE. These algorithms were applied to PPK model selection with a focus on comparing the efficiency and robustness of each of them. All machine learning algorithms included the combination of ML algorithms with a local downhill search. The local downhill search consisted of systematically changing one or two "features" at a time (a one-bit or a two-bit local search), alternating with the ML methods. An exhaustive search (all possible combinations of model features, N = 1,572,864 models) was the gold standard for robustness, and the number of models examined leading prior to identification of the final model was the metric for efficiency.All algorithms identified the optimal model when combined with the two-bit local downhill search. GA, RF, GBRT, and GP identified the optimal model with only a one-bit local search. PSO required the two-bit local downhill search. In our analysis, GP was the most efficient algorithm as measured by the number of models examined prior to finding the optimal (495 models), and PSO exhibited the least efficiency, requiring 1710 unique models before finding the best solution. Additionally, GP was also the algorithm that needed the longest elapsed time of 2975.6 min, in comparison with GA, which only required 321.8 min.

A novel fluorescent indicator-based fluorene derivative for rapid and visual trace water sensing.

Fluorene nucleus derivatives show great potential for building outstanding fluorescence probes. In this paper, a novel fluorescent probe was developed by reacting with fluorene core with azacyclobutane, which exhibits typical solvation chromogenic effect in solvent. The fluorescence of the probe quenched in highly polar solvent. Based on this phenomenon, a novel fluorescence system for trace water was constructed. The response of this probe was fast (30 s) and sensitive for the detection of trace water in organic solvents, and the detection limit of water content in DMSO reached 0.13%. In addition, the probe can also be made as a test strip combined with homemade portable device and a smartphone for rapid detection of trace water. The luminescence mechanism of the probe is theoretically calculated based on time-contained density functional theory (TDDFT). To showcase its practicality, it has been applied for the detection of trace water in honey and alcohol by dipstick. This method provides a new idea for designing efficient fluorescent probes based on dipstick and mobile phone rapid detection.

Rapid Screening of 34 Emerging Contaminants in Surface Water by UHPLC-Q-TOF-MS.

OBJECTIVES: To establish a rapid screening method for 34 emerging contaminants in surface water by ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF-MS). METHODS: The pretreatment conditions of solid phase extraction (SPE) were optimized by orthogonal experimental design and the surface water samples were concentrated and extracted by Oasis® HLB and Oasis® MCX SPE columns in series. The extracts were separated by Kinetex® EVO C18 column, with gradient elution of 0.1% formic acid aqueous solution and 0.1% formic acid methanol solution. Q-TOF-MS 'fullscan' and 'targeted MS/MS' modes were used to detect 34 emerging contaminants and to establish a database with 34 emerging contaminants precursor ion, product ion and retention times. RESULTS: The 34 emerging contaminants exhibited good linearity in the concentration range respectively and the correlation coefficients (r) were higher than 0.97. The limit of detection was 0.2-10 ng/L and the recoveries were 81.2%-119.2%. The intra-day precision was 0.78%-18.70%. The method was applied to analyze multiple surface water samples and 6 emerging contaminants were detected, with a concentration range of 1.93-157.71 ng/L. CONCLUSIONS: The method is simple and rapid for screening various emerging contaminants at the trace level in surface water.

Postmortem Diffusion of Aconitum Alkaloids and Their Metabolites in Rabbits.

OBJECTIVES: To explore the postmortem diffusion rule of Aconitum alkaloids and their metabolites in poisoned rabbits, and to provide a reference for identifying the antemortem poisoning or postmortem poisoning of Aconitum alkaloids. METHODS: Twenty-four rabbits were sacrificed by tracheal clamps. After 1 hour, the rabbits were administered with aconitine LD50 in decocting aconite root powder by intragastric administration. Then, they were placed supine and stored at 25 ℃. The biological samples from 3 randomly selected rabbits were collected including heart blood, peripheral blood, urine, heart, liver, spleen, lung and kidney tissues at 0 h, 4 h, 8 h, 12 h, 24 h, 48 h, 72 h and 96 h after intragastric administration, respectively. Aconitum alkaloids and their metabolites in the biological samples were analyzed by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). RESULTS: At 4 h after intragastric administration, Aconitum alkaloids and their metabolites could be detected in heart blood, peripheral blood and major organs, and the contents of them changed dynamically with the preservation time. The contents of Aconitum alkaloids and their metabolites were higher in the spleen, liver and lung, especially in the spleen which was closer to the stomach. The average mass fraction of benzoylmesaconine metabolized in rabbit spleen was the highest at 48 h after intragastric administration. In contrast, the contents of Aconitum alkaloids and their metabolites in kidney were all lower. Aconitum alkaloids and their metabolites were not detected in urine. CONCLUSIONS: Aconitum alkaloids and their metabolites have postmortem diffusion in poisoned rabbits, diffusing from high-content organs (stomach) to other major organs and tissues as well as the heart blood. The main mechanism is the dispersion along the concentration gradient, while urine is not affected by postmortem diffusion, which can be used as the basis for the identification of antemortem and postmortem Aconitum alkaloids poisoning.

Iron-Catalyzed Allylic C(sp3)-H Silylation: Spin-Crossover-Efficiency-Determined Chemoselectivity.

The nuanced role of spin effects remains a critical gap in designing proficient open-shell catalysts. This study elucidates an iron-catalyzed allylic C(sp3)-H silylation/alkyne hydrosilylation reaction, in which the spin state of the open-shell iron catalyst dictates the reaction kinetics and pathway. Specifically, spin crossover led to alkyne hydrosilylation, whereas spin conservation resulted in a novel allylic C(sp3)-H silylation reaction. This chemoselectivity, governed by the spin-crossover efficiency, reveals an unexpected dimension in spin effects and a first in the realm of transition-metal-catalyzed in situ silylation of allylic C(sp3)-H bonds, which had been previously inhibited by the heightened reactivity of alkenes in hydrosilylation reactions. Furthermore, this spin crossover can either accelerate or hinder the reaction at different stages within a single catalytic reaction, a phenomenon scarcely documented. Moreover, we identify a substrate-assisted C-H activation mechanism, a departure from known ligand-assisted processes, offering a fresh perspective on C-H activation strategies.