Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer.

CD8+ cytotoxic T cells (CTLs) orchestrate antitumour immunity and exhibit inherent heterogeneity1,2, with precursor exhausted T (Tpex) cells but not terminally exhausted T (Tex) cells capable of responding to existing immunotherapies3-7. The gene regulatory network that underlies CTL differentiation and whether Tex cell responses can be functionally reinvigorated are incompletely understood. Here we systematically mapped causal gene regulatory networks using single-cell CRISPR screens in vivo and discovered checkpoints for CTL differentiation. First, the exit from quiescence of Tpex cells initiated successive differentiation into intermediate Tex cells. This process is differentially regulated by IKAROS and ETS1, the deficiencies of which dampened and increased mTORC1-associated metabolic activities, respectively. IKAROS-deficient cells accumulated as a metabolically quiescent Tpex cell population with limited differentiation potential following immune checkpoint blockade (ICB). Conversely, targeting ETS1 improved antitumour immunity and ICB efficacy by boosting differentiation of Tpex to intermediate Tex cells and metabolic rewiring. Mechanistically, TCF-1 and BATF are the targets for IKAROS and ETS1, respectively. Second, the RBPJ-IRF1 axis promoted differentiation of intermediate Tex to terminal Tex cells. Accordingly, targeting RBPJ enhanced functional and epigenetic reprogramming of Tex cells towards the proliferative state and improved therapeutic effects and ICB efficacy. Collectively, our study reveals that promoting the exit from quiescence of Tpex cells and enriching the proliferative Tex cell state act as key modalities for antitumour effects and provides a systemic framework to integrate cell fate regulomes and reprogrammable functional determinants for cancer immunity.

SLC38A2 and glutamine signalling in cDC1s dictate anti-tumour immunity.

Cancer cells evade T cell-mediated killing through tumour-immune interactions whose mechanisms are not well understood1,2. Dendritic cells (DCs), especially type-1 conventional DCs (cDC1s), mediate T cell priming and therapeutic efficacy against tumours3. DC functions are orchestrated by pattern recognition receptors3-5, although other signals involved remain incompletely defined. Nutrients are emerging mediators of adaptive immunity6-8, but whether nutrients affect DC function or communication between innate and adaptive immune cells is largely unresolved. Here we establish glutamine as an intercellular metabolic checkpoint that dictates tumour-cDC1 crosstalk and licenses cDC1 function in activating cytotoxic T cells. Intratumoral glutamine supplementation inhibits tumour growth by augmenting cDC1-mediated CD8+ T cell immunity, and overcomes therapeutic resistance to checkpoint blockade and T cell-mediated immunotherapies. Mechanistically, tumour cells and cDC1s compete for glutamine uptake via the transporter SLC38A2 to tune anti-tumour immunity. Nutrient screening and integrative analyses show that glutamine is the dominant amino acid in promoting cDC1 function. Further, glutamine signalling via FLCN impinges on TFEB function. Loss of FLCN in DCs selectively impairs cDC1 function in vivo in a TFEB-dependent manner and phenocopies SLC38A2 deficiency by eliminating the anti-tumour therapeutic effect of glutamine supplementation. Our findings establish glutamine-mediated intercellular metabolic crosstalk between tumour cells and cDC1s that underpins tumour immune evasion, and reveal glutamine acquisition and signalling in cDC1s as limiting events for DC activation and putative targets for cancer treatment.

Rickettsia symbionts spread via mixed mode transmission, increasing female fecundity and sex ratio shift by host hormone modulating.

Heritable symbionts are common among animals in nature, but the molecular mechanisms underpinning symbiont invasions of host populations have been elusive. In this study, we demonstrate the spread of Rickettsia in an invasive agricultural pest, the whitefly Bemisia tabaci Mediterranean (MED), across northeastern China from 2018 to 2023. Here, we show that the beneficial symbiont Rickettsia spreads by manipulating host hormone signals. Our analyses suggest that Rickettsia have been horizontally acquired by B. tabaci MED from another invasive whitefly B. tabaci Middle East-Asia Minor 1 during periods of coexistence. Rickettsia is transmitted maternally and horizontally from female B. tabaci MED individuals. Rickettsia infection enhances fecundity and results in female bias among whiteflies. Our findings reveal that Rickettsia infection stimulates juvenile hormone (JH) synthesis, in turn enhancing fecundity, copulation events, and the female ratio of the offspring. Consequently, Rickettsia infection results in increased whitefly fecundity and female bias by modulating the JH pathway. More female progeny facilitates the transmission of Rickettsia. This study illustrates that the spread of Rickettsia among invasive whiteflies in northeastern China is propelled by host hormone regulation. Such symbiont invasions lead to rapid physiological and molecular evolution in the host, influencing the biology and ecology of an invasive species.

Histone modification-linked prognostic model for ovarian cancer reveals LBX2 as a novel growth promoter.

Ovarian cancer (OC) is a deadly disease with limited treatment options and poor overall survival rates. This study aimed to investigate the role of histone modification-related genes in predicting the prognosis of OC patients. Transcriptome data from multiple cohorts, including bulk RNA-Seq data and single-cell scRNA-Seq data, were collected. Gene set enrichment analysis was used to identify enriched gene sets in the histone modification pathway. Differentially expressed genes (DEGs) between histone modification-high and histone modification-low groups were identified using Lasso regression. A prognostic model was constructed using five selected prognostic genes from the DEGs in the TCGA-OV cohort. The study found enrichment of gene sets in the histone modification pathway and identified five prognostic genes associated with OC prognosis. The constructed risk score model based on histone modification-related genes was correlated with immune infiltration of T cells and M1 macrophages. Mutations are more prevalent in the high-risk group compared to the low-risk group. Several drugs were screened against the model genes. Through in vitro experiments, we confirmed the expression patterns of the model genes. LBX2 facilitates the proliferation of OC. Histone modification-related genes have the potential to serve as biomarkers for predicting OC prognosis. Targeting these genes may lead to the development of more effective therapies for OC. Additionally, LBX2 represents a novel cell proliferation promoter in OC carcinogenesis.

Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer.

There are hundreds of prognostic models for ovarian cancer. These genes are based on different gene classes, and there are many ways to construct the models. Therefore, this paper aims to build the most stable prognostic evaluation system known to date through 101 machine learning strategies. We combined 101 algorithm combinations with 10 machine learning algorithms to create antigen presentation-associated genetic markers (AIDPS) with outstanding precision and steady performance. The inclusive set of algorithms comprises the elastic network (Enet), Ridge, stepwise Cox, Lasso, generalized enhanced regression model (GBM), random survival forest (RSF), supervised principal component (SuperPC), Cox partial least squares regression (plsRcox), survival support vector machine (Survival-SVM). Then, in the train cohort, the prediction model was fitted using a leave-one cross-validation (LOOCV) technique, which involved 101 different possible combinations of prognostic genes. Seven validation data sets (GSE26193, GSE26712, GSE30161, GSE63885, GSE9891, GSE140082 and ICGC_OV_AU) were compared and analysed, and the C-index was calculated. Finally, we collected 32 published ovarian cancer prognostic models (including mRNA and lncRNA). All data sets and prognostic models were subjected to a univariate Cox regression analysis, and the C-index was calculated to demonstrate that the antigen presentation process should be the core criterion for evaluating ovarian cancer prognosis. In a univariate Cox regression analysis, 22 prognostic genes were identified based on the expression profiles of 283 genes involved in antigen presentation and the intersection of genes (p < 0.05). AIDPS were developed by our machine learning-based integration method, which was applied to these 22 genes. One hundred and one prediction models are fitted using the LOOCV framework, and the C-index is calculated for each model across all validation sets. Interestingly, RSF + Lasso was the best model overall since it had the greatest average C-index and the highest C-index of any combination of models tested on the validated data sets. In comparing external cohorts, we found that the C-index correlated AIDPS method using the RSF + Lasso method in 101 prediction models was in contrast to other features. Notably, AIDPS outperformed the vast majority of models across all data sets. Antigen-presenting anti-tumour immune pathways can be used as a representative gene set of ovarian cancer to track the prognosis of patients with cancer. The antigen-presenting model obtained by the RSF + Lasso method has the best C-INDEX, which plays a key role in developing antigen-presenting targeted drugs in ovarian cancer and improving the treatment outcome of patients.

Autophagy-related risk signature based on CDNK2A to facilitate survival prediction of patients with endometrial cancer.

BACKGROUND: Autophagy plays an important role in immunity and inflammation. The present study aimed to explore the prognostic significance of autophagy-related genes (ARGs) in endometrial cancer (EC) using bioinformatics. METHODS: The list of ARGs was obtained from the Human Autophagy Database. The differentially expressed ARGs (DEARGs) between the EC and normal endometrial tissue samples were screened from The Cancer Genome Atlas database. Cox regression analysis was performed on the DEARGs to screen the prognostic ARGs and construct risk signatures for overall survival (OS) and progression-free survival (PFS). The hub ARGs were identified from a protein-protein interaction network, and CDKN2A was obtained from the intersection of prognostic ARGs and hub ARGs. The association of CDKN2A expression with clinical characteristics and immune infiltration were analyzed. Finally, the role of CDKN2A in autophagy was confirmed in EC cell lines. RESULTS: CDKN2A, PTK6 and DLC1 were used to establish risk signatures for predicting the survival of EC patients. Receiver operating characteristic curve analysis indicated that the risk signatures can accurately predict both OS and PFS. CDKN2A was the only hub prognostic ARG, and showed significant association with the age, survival status, grade, histological type, body mass index and FIGO (i.e. International Federation of Gynecology and Obstetrics) stage (p < 0.05). Furthermore, CDKN2A expression was also correlated with the infiltration of immune cells, indicating that CDKN2A might play a critical role in regulating the immune microenvironment and immune responses in EC. In addition, silencing of CDKN2A gene promoted autophagy in the HEC-1A cell line and upregulated the expression levels of autophagy-related proteins. CONCLUSIONS: CDKN2A is a prognostic factor and therapeutic target in EC, and is likely associated with the tumor immune landscape and autophagy.

Ovarian carcinoma immune-related microRNA affects the heterogeneity of the endocrine microenvironment and anti-tumor immune pattern.

BACKGROUND: The eighth-leading cause of cancer-related mortality and the seventh-most prevalent malignancy in women globally is ovarian cancer (OV). However, 5-year survival expectancy after conventional treatment is not good. Therefore, there is an urgent need for novel signatures to guide the designation of therapeutic schemes for OV patients. METHODS: We used univariate Cox analysis to screen hormone secretion regulation axis-related microRNAs (miRNAs), least absolute shrinkage and selection operator analysis to select candidate miRNAs and multivariate Cox analysis to build the risk model. To evaluate possible route and functional differences, enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the differentially expressed genes (DEGs) across various risk groups. We compared Tumor Immune Dysfunction and Exclusion (TIDE) scores across risk categories by analyzing immune cell infiltration, immune checkpoint gene expression, immunological function and TIDE scores. In the end, we determined the half maximal inhibitory concentration (IC50 ) of chemotherapy and targeted medicines for individual patients. Cell assays were determined to test the migration of the miRNA-target genes and western blotting was used to test the correlation of the miRNA-target genes and the pathways. RESULTS: We finally identified hormone secretion regulation axis-related 13 microRNAs to build a risk model. The validation of observed and anticipated values revealed a fair level of agreement. To evaluate the molecular pathways between various groups in accordance with the GO and KEGG analyses, we then discovered 173 DEGs between distinct risk groups. The risk score was shown to be inversely related to the number of immune cells, including myeloid dendritic, granulocytes, M1 and M2 macrophages, B cells, t-lymphocytes, and CD4+ and CD8+ cells, suggesting that immune cells are more frequent in the low-risk group. Immune cell infiltration investigation yielded these results. Finally, we recognized 11 chemotherapeutic drugs and 30 novels targeted drugs on the basis of IC50 between the different risk groups. GJB5 was determined to be the mir-219 target gene and was identified as promoting the cell cycle process. In addition, hormone secretion regulation axis related miRNAs were reported to affects the heterogeneity of endocrine microenvironment and anti-tumor immune pattern. CONCLUSIONS: In conclusion, a 13-miRNA prognostic model was constructed to know the immune status, prognosis, immunotherapeutic response and anti-tumor drug sensitivity for OV, which provides theoretical guidance for the effective and individualized treatment of OV patients.

Interfacial Electronic Interaction in Amorphous-Crystalline CeOx -Sn Heterostructures for Optimizing CO2 to Formate Conversion.

Formate, a crucial chemical raw material, holds significant promise for industrial applications in the context of CO2 electroreduction reaction (CO2 RR). Despite its potential, challenges, such as poor selectivity and low formation rate at high current densities persist, primarily due to the competing hydrogen evolution reaction (HER) and high energy barriers associated with *OCHO intermediate generation. Herein, one-step chemical co-reduction strategy is employed to construct an amorphous-crystalline CeOx -Sn heterostructure, demonstrating remarkable catalytic performance in converting CO2 to formate. The optimized CeOx -Sn heterostructures reach a current density of 265.1 mA cm-2 and a formate Faraday efficiency of 95% at -1.07 V versus RHE. Especially, CeOx -Sn achieves a formate current density of 444.4 mA cm-2 and a formate production rate of 9211.8 µmol h-1  cm-2 at -1.67 V versus RHE, surpassing most previously reported materials. Experimental results, coupled with （density functional theory）DFT calculations confirm that robust interface interaction between CeOx and Sn active center induces electron transfer from crystalline Sn site to amorphous CeOx , some Ce4+ of CeOx get electrons and convert to unsaturated Ce3+ , optimizing the electronic structure of active Sn. This amorphous-crystalline heterostructure promotes electron transfer during CO2 RR, reducing the energy barrier formed by *OCHO intermediates, and thus achieving efficient reduction of CO2 to formate.

LncRNA MALAT1 facilitates BM-MSCs differentiation into endothelial cells and ameliorates erectile dysfunction via the miR-206/CDC42/PAK1/paxillin signalling axis.

BACKGROUND: Erectile dysfunction (ED) is a common male sexual dysfunction, with an increasing incidence, and the current treatment is often ineffective. METHODS: Vascular endothelial growth factor (VEGFA) was used to treat bone marrow-derived mesenchymal stem cells (BM-MSCs), and their cell migration rates were determined by Transwell assays. The expression of the von Willebrand Factor (vWF)VE-cadherin, and endothelial nitric oxide synthase(eNOS) endothelial markers was determined by qRT‒PCR and Western blot analyses. The MALAT1-induced differentiation of BM-MCs to ECs via the CDC42/PAK1/paxillin pathway was explored by transfecting VEGFA-induced BM-MSC with si-MALAT1 and overexpressing CDC42 and PAK1. The binding capacity between CDC42, PAK1, and paxillin in VEGFA-treated and non-VEGFA-treated BM-MSCs was examined by protein immunoprecipitation. MiR-206 was overexpressed in VEGFA-induced BM-MSC, and the binding sites of MALAT1, miR-206, and CDC42 were identified using a luciferase assay. Sixty male Sprague‒Dawley rats were divided into six groups (n = 10/group). DMED modelling was demonstrated by APO experiments and was assessed by measuring blood glucose levels. Erectile function was assessed by measuring the intracavernosa pressure (ICP) and mean arterial pressure (MAP). Penile erectile tissue was analysed by qRT‒PCR, Western blot analysis, and immunohistochemical staining. RESULTS: MALAT1 under VEGFA treatment conditions regulates the differentiation of BM-MSCs into ECs by modulating the CDC42/PAK1/paxillin axis. In vitro experiments demonstrated that interference with CDC42 and MALAT1 expression inhibited the differentiation of BM-MSCs to ECs. CDC42 binds to PAK1, and PAK1 binds to paxillin. In addition, CDC42 in the VEGFA group had a greater ability to bind to PAK1, whereas PAK1 in the VEGFA group had a greater ability to bind to paxillin. Overexpression of miR-206 in VEGFA-induced BM-MSCs demonstrated that MALAT1 competes with the CDC42 3'-UTR for binding to miR-206, which in turn is involved in the differentiation of BM-MSCs to ECs. Compared to the DMED model group, the ICP/MAP ratio was significantly greater in the three BM-MSCs treatment groups. CONCLUSIONS: MALAT1 facilitates BM-MSC differentiation into ECs by regulating the miR-206/CDC42/PAK1/paxillin axis to improve ED. The present findings revealed the vital role of MALAT1 in the repair of BM-MSCs for erectile function and provided new mechanistic insights into the BM-MSC-mediated repair of DMED.

ATP9A deficiency causes ADHD and aberrant endosomal recycling via modulating RAB5 and RAB11 activity.

ATP9A, a lipid flippase of the class II P4-ATPases, is involved in cellular vesicle trafficking. Its homozygous variants are linked to neurodevelopmental disorders in humans. However, its physiological function, the underlying mechanism as well as its pathophysiological relevance in humans and animals are still largely unknown. Here, we report two independent families in which the nonsense mutations c.433C>T/c.658C>T/c.983G>A (p. Arg145*/p. Arg220*/p. Trp328*) in ATP9A (NM_006045.3) cause autosomal recessive hypotonia, intellectual disability (ID) and attention deficit hyperactivity disorder (ADHD). Atp9a null mice show decreased muscle strength, memory deficits and hyperkinetic movement disorder, recapitulating the symptoms observed in patients. Abnormal neurite morphology and impaired synaptic transmission are found in the primary motor cortex and hippocampus of the Atp9a null mice. ATP9A is also required for maintaining neuronal neurite morphology and the viability of neural cells in vitro. It mainly localizes to endosomes and plays a pivotal role in endosomal recycling pathway by modulating small GTPase RAB5 and RAB11 activation. However, ATP9A pathogenic mutants have aberrant subcellular localization and cause abnormal endosomal recycling. These findings provide strong evidence that ATP9A deficiency leads to neurodevelopmental disorders and synaptic dysfunctions in both humans and mice, and establishes novel regulatory roles for ATP9A in RAB5 and RAB11 activity-dependent endosomal recycling pathway and neurological diseases.

High-accuracy measurement of 36SF5 + signal using an ultrahigh-resolution isotope ratio mass spectrometer.

RATIONALE: The Δ36S standard deviation measured in a conventional isotope ratio mass spectrometer such as MAT 253 is ca 0.1‰ to 0.3‰. At this precision, it is difficult to resolve the origin of non-mass-dependent sulfur isotope fractionation in tropospheric sulfate aerosol and in Martian meteorites or small deviations from the canonical mass-dependent fractionation laws. Interfering ions with m/z at 131 of 36SF5 + are suggested by the community as the cause of the poor precision, but the exact ion species has not been identified or confirmed. METHODS: Here we examined the potential interfering ions by using a Thermo Scientific ultrahigh-resolution isotope ratio mass spectrometer to measure SF6 working gas and SF6 gases converted from IAEA-S1/2/3 Ag2S reference materials. RESULTS: We found that there are two resolvable peaks to the right of the 36SF5 + peak when a new filament was installed, which are 186WF4 2+ followed by 12C3F5 +. However, only the 12C3F5 + interference peak was observed after more than three days of filament use. 12C3F5 + is generated inside the instrument during the ionization process. Avoiding the interfering signals, we were able to achieve a Δ36S standard deviation of 0.046‰ (n = 8) for SF6 zero-enrichment and 0.069‰ (n = 8) for overall measurement start from silver sulfide IAEA-S1. CONCLUSIONS: Aging the filament with SF6 gas can avoid the interference of 186WF4 2+. Minimizing the presence of carbon-bearing compounds and avoiding the interfering signals of 12C3F5 + from 36SF5 +, we can improve Δ36S measurement accuracy and precision, which helps to open new territories for research using quadruple sulfur isotope composition.

A copper-catalyzed asymmetric Friedel-Crafts hydroxyalkylation of pyrazole-4,5-diones with 5-aminoisoxazoles.

An asymmetric Friedel-Crafts hydroxyalkylation reaction of 5-aminoisoxazoles with pyrazole-4,5-diones was developed under the catalysis of 5% chiral copper complexes. This reaction exhibits functional group tolerance and excellent enantioselectivity. Moreover, the reaction can be scaled up and its mechanism was studied.

Modeled Pathways and Fluxes of PCB Dechlorination by Redox Potentials.

Dechlorination is one of the main processes for the natural degradation of polychlorinated biphenyls (PCBs) in an anaerobic environment. However, PCB dechlorination pathways and products vary with PCB congeners, types of functional dechlorinating bacteria, and environmental conditions. The present study develops a novel model for determining dechlorination pathways and fluxes by tracking redox potential variability, transforming the complex dechlorination process into a stepwise sequence. The redox potential is calculated via the Gibbs free energy of formation, PCB concentrations in reactants and products, and environmental conditions. Thus, the continuous change in the PCB congener composition can be tracked during dechlorination processes. The new model is assessed against four measurements from several published studies on PCB dechlorination. The simulation errors in all four measurements are calculated between 2.67 and 35.1% under minimum (n = 0) and maximum (n = 34) numbers of co-eluters, respectively. The dechlorination fluxes for para-dechlorination pathways dominate PCB dechlorination in all measurements. Furthermore, the model also considers multiple-step dechlorination pathways containing intermediate PCB congeners absent in both the reactants and the products. The present study indicates that redox potential might be an appropriate indicator for predicting PCB dechlorination pathways and fluxes even without prior knowledge of the functional dechlorinating bacteria.

PGAM5 exacerbates acute renal injury by initiating mitochondria-dependent apoptosis by facilitating mitochondrial cytochrome c release.

Acute kidney injury (AKI) is a worldwide public health problem characterized by the massive loss of tubular cells. However, the precise mechanism for initiating tubular cell death has not been fully elucidated. Here, we reported that phosphoglycerate mutase 5 (PGAM5) was upregulated in renal tubular epithelial cells during ischaemia/reperfusion or cisplatin-induced AKI in mice. PGAM5 knockout significantly alleviated the activation of the mitochondria-dependent apoptosis pathway and tubular apoptosis. Apoptosis inhibitors alleviated the activation of the mitochondria-dependent apoptosis pathway. Mechanistically, as a protein phosphatase, PGAM5 could dephosphorylate Bax and facilitate Bax translocation to the mitochondrial membrane. The translocation of Bax to mitochondria increased membrane permeability, decreased mitochondrial membrane potential and facilitated the release of mitochondrial cytochrome c (Cyt c) into the cytoplasm. Knockdown of Bax attenuated PGAM5 overexpression-induced Cyt c release and tubular cell apoptosis. Our results demonstrated that the increase in PGAM5-mediated Bax dephosphorylation and mitochondrial translocation was implicated in the development of AKI by initiating mitochondrial Cyt c release and activating the mitochondria-dependent apoptosis pathway. Targeting this axis might be beneficial for alleviating AKI.

Semiclassical approaches to perturbative time-convolution and time-convolutionless quantum master equations for electronic transitions in multistate systems.

Understanding the dynamics of photoinduced processes in complex systems is crucial for the development of advanced energy-conversion materials. In this study, we investigate the nonadiabatic dynamics using time-convolution (TC) and time-convolutionless (TCL) quantum master equations (QMEs) based on treating electronic couplings as perturbation within the framework of multistate harmonic (MSH) models. The MSH model Hamiltonians are mapped from all-atom simulations such that all pairwise reorganization energies are consistently incorporated, leading to a heterogeneous environment that couples to the multiple electronic states differently. Our exploration encompasses the photoinduced charge transfer dynamics in organic photovoltaic carotenoid-porphyrin-C60 triad dissolved in liquid solution and the excitation energy transfer (EET) dynamics in photosynthetic Fenna-Matthews-Olson complexes. By systematically comparing the perturbative TC and TCL QME approaches with exact quantum-mechanical and various semiclassical approximate kernels, we demonstrate their efficacy and accuracy in capturing the essential features of photoinduced dynamics. Our calculations show that TC QMEs generally yield more accurate results than TCL QMEs, especially in EET, although both methods offer versatile approaches adaptable across different systems. In addition, we investigate various semiclassical approximations featuring the Wigner-transformed and classical nuclear densities as well as the governing dynamics during the quantum coherence period, highlighting the trade-off between accuracy and computational cost. This work provides valuable insights into the applicability and performance of TC and TCL QME approaches via the MSH model, offering guidance for realistic applications to condensed-phase systems on the atomistic level.

Generalized nonequilibrium Fermi's golden rule and its semiclassical approximations for electronic transitions between multiple states.

The nonequilibrium Fermi's golden rule (NE-FGR) approach is developed to simulate the electronic transitions between multiple excited states in complex condensed-phase systems described by the recently proposed multi-state harmonic (MSH) model Hamiltonian. The MSH models were constructed to faithfully capture the photoinduced charge transfer dynamics in a prototypical organic photovoltaic carotenoid-porphyrin-C60 molecular triad dissolved in tetrahydrofuran. A general expression of the fully quantum-mechanical NE-FGR rate coefficients for transitions between all pairs of states in the MSH model is obtained. Besides, the linearized semiclassical NE-FGR formula and a series of semiclassical approximations featuring Wigner and classical nuclear sampling choices and different dynamics during the quantum coherence period for the MSH model are derived. The current approach enables all the possible population transfer pathways between the excited states of the triad, in contrast to the previous applications that only addressed the donor-to-acceptor transition. Our simulations for two triad conformations serve as a demonstration for benchmarking different NE-FGR approximations and show that the difference between all levels of approximation is small for the current system, especially at room temperature. By comparing with nonadiabatic semiclassical dynamics, we observe similar timescales for the electronic population transfer predicted by NE-FGR. It is believed that the general formulation of NE-FGR for the MSH Hamiltonian enables a variety of applications in realistic systems.

Benchmarking various nonadiabatic semiclassical mapping dynamics methods with tensor-train thermo-field dynamics.

Accurate quantum dynamics simulations of nonadiabatic processes are important for studies of electron transfer, energy transfer, and photochemical reactions in complex systems. In this comparative study, we benchmark various approximate nonadiabatic dynamics methods with mapping variables against numerically exact calculations based on the tensor-train (TT) representation of high-dimensional arrays, including TT-KSL for zero-temperature dynamics and TT-thermofield dynamics for finite-temperature dynamics. The approximate nonadiabatic dynamics methods investigated include mixed quantum-classical Ehrenfest mean-field and fewest-switches surface hopping, linearized semiclassical mapping dynamics, symmetrized quasiclassical dynamics, the spin-mapping method, and extended classical mapping models. Different model systems were evaluated, including the spin-boson model for nonadiabatic dynamics in the condensed phase, the linear vibronic coupling model for electronic transition through conical intersections, the photoisomerization model of retinal, and Tully's one-dimensional scattering models. Our calculations show that the optimal choice of approximate dynamical method is system-specific, and the accuracy is sensitively dependent on the zero-point-energy parameter and the initial sampling strategy for the mapping variables.

Systematic mining of fungal chimeric terpene synthases using an efficient precursor-providing yeast chassis.

Chimeric terpene synthases, which consist of C-terminal prenyltransferase (PT) and N-terminal class I terpene synthase (TS) domains (termed PTTSs here), is unique to fungi and produces structurally diverse di- and sesterterpenes. Prior to this study, 20 PTTSs had been functionally characterized. Our understanding of the origin and functional evolution of PTTS genes is limited. Our systematic search of sequenced fungal genomes among diverse taxa revealed that PTTS genes were restricted to Dikarya. Phylogenetic findings indicated different potential models of the origin and evolution of PTTS genes. One was that PTTS genes originated in the common Dikarya ancestor and then underwent frequent gene loss among various subsequent lineages. To understand their functional evolution, we selected 74 PTTS genes for biochemical characterization in an efficient precursor-providing yeast system employing chassis-based, robot-assisted, high-throughput automatic assembly. We found 34 PTTS genes that encoded active enzymes and collectively produced 24 di- and sesterterpenes. About half of these di- and sesterterpenes were also the products of the 20 known PTTSs, indicating functional conservation, whereas the PTTS products included the previously unknown sesterterpenes, sesterevisene (1), and sesterorbiculene (2), suggesting that a diversity of PTTS products awaits discovery. Separating functional PTTSs into two monophyletic groups implied that an early gene duplication event occurred during the evolution of the PTTS family followed by functional divergence with the characteristics of distinct cyclization mechanisms.

Hippocampal astrocytic neogenin regulating glutamate uptake, a critical pathway for preventing epileptic response.

Epilepsy, a common neurological disorder, is featured with recurrent seizures. Its underlying pathological mechanisms remain elusive. Here, we provide evidence for loss of neogenin (NEO1), a coreceptor for multiple ligands, including netrins and bone morphological proteins, in the development of epilepsy. NEO1 is reduced in hippocampi from patients with epilepsy based on transcriptome and proteomic analyses. Neo1 knocking out (KO) in mouse brains displays elevated epileptiform spikes and seizure susceptibility. These phenotypes were undetectable in mice, with selectively depleted NEO1 in excitatory (NeuroD6-Cre+) or inhibitory (parvalbumin+) neurons, but present in mice with specific hippocampal astrocytic Neo1 KO. Additionally, neurons in hippocampal dentate gyrus, a vulnerable region in epilepsy, in mice with astrocyte-specific Neo1 KO show reductions in inhibitory synaptic vesicles and the frequency of miniature inhibitory postsynaptic current(mIPSC), but increase of the duration of miniature excitatory postsynaptic current and tonic NMDA receptor currents, suggesting impairments in both GABAergic transmission and extracellular glutamate clearance. Further proteomic and cell biological analyses of cell-surface proteins identified GLAST, a glutamate-aspartate transporter that is marked reduced in Neo1 KO astrocytes and the hippocampus. NEO1 interacts with GLAST and promotes GLAST surface distribution in astrocytes. Expressing NEO1 or GLAST in Neo1 KO astrocytes in the hippocampus abolishes the epileptic phenotype. Taken together, these results uncover an unrecognized pathway of NEO1-GLAST in hippocampal GFAP+ astrocytes, which is critical for GLAST surface distribution and function, and GABAergic transmission, unveiling NEO1 as a valuable therapeutic target to protect the brain from epilepsy.

Non-intrusive reduced-order model for time-dependent stochastic partial differential equations utilizing dynamic mode decomposition and polynomial chaos expansion.

In this study, we present a novel non-intrusive reduced-order model (ROM) for solving time-dependent stochastic partial differential equations (SPDEs). Utilizing proper orthogonal decomposition (POD), we extract spatial modes from high-fidelity solutions. A dynamic mode decomposition (DMD) method is then applied to vertically stacked matrices of projection coefficients for future prediction of coefficient fields. Polynomial chaos expansion (PCE) is employed to construct a mapping from random parameter inputs to the DMD-predicted coefficient field. These lead to the POD-DMD-PCE method. The innovation lies in vertically stacking projection coefficients, ensuring time-dimensional consistency in the coefficient matrix for DMD and facilitating parameter integration for PCE analysis. This method combines the model reduction of POD with the time extrapolation strengths of DMD, effectively recovering field solutions both within and beyond the training time interval. The efficiency and time extrapolation capabilities of the proposed method are validated through various nonlinear SPDEs. These include a reaction-diffusion equation with 19 parameters, a two-dimensional heat equation with two parameters, and a one-dimensional Burgers equation with three parameters.