Striosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington's Disease Model.

Learning valence-based responses to favorable and unfavorable options requires judgments of the relative value of the options, a process necessary for species survival. We found, using engineered mice, that circuit connectivity and function of the striosome compartment of the striatum are critical for this type of learning. Calcium imaging during valence-based learning exhibited a selective correlation between learning and striosomal but not matrix signals. This striosomal activity encoded discrimination learning and was correlated with task engagement, which, in turn, could be regulated by chemogenetic excitation and inhibition. Striosomal function during discrimination learning was disturbed with aging and severely so in a mouse model of Huntington's disease. Anatomical and functional connectivity of parvalbumin-positive, putative fast-spiking interneurons (FSIs) to striatal projection neurons was enhanced in striosomes compared with matrix in mice that learned. Computational modeling of these findings suggests that FSIs can modulate the striosomal signal-to-noise ratio, crucial for discrimination and learning.

SRSF2 plays an unexpected role as reader of m5C on mRNA, linking epitranscriptomics to cancer.

A common mRNA modification is 5-methylcytosine (m5C), whose role in gene-transcript processing and cancer remains unclear. Here, we identify serine/arginine-rich splicing factor 2 (SRSF2) as a reader of m5C and impaired SRSF2 m5C binding as a potential contributor to leukemogenesis. Structurally, we identify residues involved in m5C recognition and the impact of the prevalent leukemia-associated mutation SRSF2P95H. We show that SRSF2 binding and m5C colocalize within transcripts. Furthermore, knocking down the m5C writer NSUN2 decreases mRNA m5C, reduces SRSF2 binding, and alters RNA splicing. We also show that the SRSF2P95H mutation impairs the ability of the protein to read m5C-marked mRNA, notably reducing its binding to key leukemia-related transcripts in leukemic cells. In leukemia patients, low NSUN2 expression leads to mRNA m5C hypomethylation and, combined with SRSF2P95H, predicts poor outcomes. Altogether, we highlight an unrecognized mechanistic link between epitranscriptomics and a key oncogenesis driver.

SOX2 downregulation of PML increases HCMV gene expression and growth of glioma cells.

The presence of human cytomegalovirus (HCMV) in glioblastoma (GBM) and improved outcomes of GBM patients receiving therapies targeting the virus have implicated HCMV in GBM progression. However, a unifying mechanism that accounts for the contribution of HCMV to the malignant phenotype of GBM remains incompletely defined. Here we have identified SOX2, a marker of glioma stem cells (GSCs), as a key determinant of HCMV gene expression in gliomas. Our studies demonstrated that SOX2 downregulated promyelocytic leukemia (PML) and Sp100 and consequently facilitated viral gene expression by decreasing the amount of PML nuclear bodies in HCMV-infected glioma cells. Conversely, the expression of PML antagonized the effects of SOX2 on HCMV gene expression. Furthermore, this regulation of SOX2 on HCMV infection was demonstrated in a neurosphere assay of GSCs and in a murine xenograft model utilizing xenografts from patient-derived glioma tissue. In both cases, SOX2 overexpression facilitated the growth of neurospheres and xenografts implanted in immunodeficient mice. Lastly, the expression of SOX2 and HCMV immediate early 1 (IE1) protein could be correlated in tissues from glioma patients, and interestingly, elevated levels of SOX2 and IE1 were predictive of a worse clinical outcome. These studies argue that HCMV gene expression in gliomas is regulated by SOX2 through its regulation of PML expression and that targeting molecules in this SOX2-PML pathway could identify therapies for glioma treatment.

Natural variation in yeast reveals multiple paths for acquiring higher stress resistance.

BACKGROUND: Organisms frequently experience environmental stresses that occur in predictable patterns and combinations. For wild Saccharomyces cerevisiae yeast growing in natural environments, cells may experience high osmotic stress when they first enter broken fruit, followed by high ethanol levels during fermentation, and then finally high levels of oxidative stress resulting from respiration of ethanol. Yeast have adapted to these patterns by evolving sophisticated "cross protection" mechanisms, where mild 'primary' doses of one stress can enhance tolerance to severe doses of a different 'secondary' stress. For example, in many yeast strains, mild osmotic or mild ethanol stresses cross protect against severe oxidative stress, which likely reflects an anticipatory response important for high fitness in nature. RESULTS: During the course of genetic mapping studies aimed at understanding the mechanisms underlying natural variation in ethanol-induced cross protection against H2O2, we found that a key H2O2 scavenging enzyme, cytosolic catalase T (Ctt1p), was absolutely essential for cross protection in a wild oak strain. This suggested the absence of other compensatory mechanisms for acquiring H2O2 resistance in that strain background under those conditions. In this study, we found surprising heterogeneity across diverse yeast strains in whether CTT1 function was fully necessary for acquired H2O2 resistance. Some strains exhibited partial dispensability of CTT1 when ethanol and/or salt were used as mild stressors, suggesting that compensatory peroxidases may play a role in acquired stress resistance in certain genetic backgrounds. We leveraged global transcriptional responses to ethanol and salt stresses in strains with different levels of CTT1 dispensability, allowing us to identify possible regulators of these alternative peroxidases and acquired stress resistance in general. CONCLUSIONS: Ultimately, this study highlights how superficially similar traits can have different underlying molecular foundations and provides a framework for understanding the diversity and regulation of stress defense mechanisms.

Targeting the oncogenic m6A demethylase FTO suppresses tumourigenesis and potentiates immune response in hepatocellular carcinoma.

OBJECTIVE: Fat mass and obesity-associated protein (FTO), an eraser of N 6-methyadenosine (m6A), plays oncogenic roles in various cancers. However, its role in hepatocellular carcinoma (HCC) is unclear. Furthermore, small extracellular vesicles (sEVs, or exosomes) are critical mediators of tumourigenesis and metastasis, but the relationship between FTO-mediated m6A modification and sEVs in HCC is unknown. DESIGN: The functions and mechanisms of FTO and glycoprotein non-metastatic melanoma protein B (GPNMB) in HCC progression were investigated in vitro and in vivo. Neutralising antibody of syndecan-4 (SDC4) was used to assess the significance of sEV-GPNMB. FTO inhibitor CS2 was used to examine the effects on anti-PD-1 and sorafenib treatment. RESULTS: FTO expression was upregulated in patient HCC tumours. Functionally, FTO promoted HCC cell proliferation, migration and invasion in vitro, and tumour growth and metastasis in vivo. FTO knockdown enhanced the activation and recruitment of tumour-infiltrating CD8+ T cells. Furthermore, we identified GPNMB to be a downstream target of FTO, which reduced the m6A abundance of GPNMB, hence, stabilising it from degradation by YTH N 6-methyladenosine RNA binding protein F2. Of note, GPNMB was packaged into sEVs derived from HCC cells and bound to the surface receptor SDC4 of CD8+ T cells, resulting in the inhibition of CD8+ T cell activation. A potential FTO inhibitor, CS2, suppresses the oncogenic functions of HCC cells and enhances the sensitivity of anti-PD-1 and sorafenib treatment. CONCLUSION: Targeting the FTO/m6A/GPNMB axis could significantly suppress tumour growth and metastasis, and enhance immune activation, highlighting the potential of targeting FTO signalling with effective inhibitors for HCC therapy.

Small-molecule caspase-1 inhibitor CZL80 terminates refractory status epilepticus via inhibition of glutamatergic transmission.

Status epilepticus (SE), a serious and often life-threatening medical emergency, is characterized by abnormally prolonged seizures. It is not effectively managed by present first-line anti-seizure medications and could readily develop into drug resistance without timely treatment. In this study, we highlight the therapeutic potential of CZL80, a small molecule that inhibits caspase-1, in SE termination and its related mechanisms. We found that delayed treatment of diazepam (0.5 h) easily induces resistance in kainic acid (KA)-induced SE. CZL80 dose-dependently terminated diazepam-resistant SE, extending the therapeutic time window to 3 h following SE, and also protected against neuronal damage. Interestingly, the effect of CZL80 on SE termination was model-dependent, as evidenced by ineffectiveness in the pilocarpine-induced SE. Further, we found that CZL80 did not terminate KA-induced SE in Caspase-1-/- mice but partially terminated SE in IL1R1-/- mice, suggesting the SE termination effect of CZL80 was dependent on the caspase-1, but not entirely through the downstream IL-1ß pathway. Furthermore, in vivo calcium fiber photometry revealed that CZL80 completely reversed the neuroinflammation-augmented glutamatergic transmission in SE. Together, our results demonstrate that caspase-1 inhibitor CZL80 terminates diazepam-resistant SE by blocking glutamatergic transmission. This may be of great therapeutic significance for the clinical treatment of refractory SE.

Sample size calculation for mixture model based on geometric average hazard ratio and its applications to nonproportional hazard.

With the advent of cancer immunotherapy, some special features including delayed treatment effect, cure rate, diminishing treatment effect and crossing survival are often observed in survival analysis. They violate the proportional hazard model assumption and pose a unique challenge for the conventional trial design and analysis strategies. Many methods like cure rate model have been developed based on mixture model to incorporate some of these features. In this work, we extend the mixture model to deal with multiple non-proportional patterns and develop its geometric average hazard ratio (gAHR) to quantify the treatment effect. We further derive a sample size and power formula based on the non-centrality parameter of the log-rank test and conduct a thorough analysis of the impact of each parameter on performance. Simulation studies showed a clear advantage of our new method over the proportional hazard based calculation across different non-proportional hazard scenarios. Moreover, the mixture modeling of two real trials demonstrates how to use the prior information on the survival distribution among patients with different biomarker and early efficacy results in practice. By comparison with a simulation-based design, the new method provided a more efficient way to compute the power and sample size with high accuracy of estimation. Overall, both theoretical derivation and empirical studies demonstrate the promise of the proposed method in powering future innovative trial designs.

Analyte-Triggered Excited-State Intramolecular Proton Transfer- Delayed Fluorescence: A General Approach for Time-Resolved Turn-On Fluorescence Imaging.

The research of delayed fluorescence (DF) has been a hot topic in biological imaging. However, the development of analyte-triggered small molecule DF probes remains a considerable challenge. Herein a novel excited-state intramolecular proton transfer-delayed fluorescence (ESIPT-DF) approach to construct analyte-stimulated DF probes was reported. These new classes of ESIPT-DF luminophores were strategically designed and synthesized by incorporating 2-(2'-hydroxyphenyl)benzothiazole (HBT), a known ESIPT-based fluorophore, as acceptor with a series of classic donor moieties, which formed a correspondingly twisted donor-acceptor pair within each molecule. Thereinto, HBT-PXZ and HBT-PTZ exhibited significant ESIPT and DF characters with lifetimes of 5.37 and 3.65 µs in the solid state, respectively. Furthermore, a caged probe HBT-PXZ-Ga was developed by introducing a hydrophilic d-galactose group as the recognition unit specific for ß-galactosidase (ß-gal) and ESIPT-DF blocking agent and applied to investigate the influence of metal ions on ß-gal activity on the surface of Streptococcus pneumoniae as a convenient tool. This ESIPT-DF "turn-on" approach is easily adaptable for the measurement of many different analytes using only a predictable modification on the caged group without modification of the core structure.

Chemogenetic inhibition of subicular seizure-activated neurons alleviates cognitive deficit in male mouse epilepsy model.

Cognitive deficit is a common comorbidity in temporal lobe epilepsy (TLE) and is not well controlled by current therapeutics. How epileptic seizure affects cognitive performance remains largely unclear. In this study we investigated the role of subicular seizure-activated neurons in cognitive impairment in TLE. A bipolar electrode was implanted into hippocampal CA3 in male mice for kindling stimulation and EEG recording; a special promoter with enhanced synaptic activity-responsive element (E-SARE) was used to label seizure-activated neurons in the subiculum; the activity of subicular seizure-activated neurons was manipulated using chemogenetic approach; cognitive function was assessed in object location memory (OLM) and novel object recognition (NOR) tasks. We showed that chemogenetic inhibition of subicular seizure-activated neurons (mainly CaMKIIα+ glutamatergic neurons) alleviated seizure generalization and improved cognitive performance, but inhibition of seizure-activated GABAergic interneurons had no effect on seizure and cognition. For comparison, inhibition of the whole subicular CaMKIIα+ neuron impaired cognitive function in naïve mice in basal condition. Notably, chemogenetic inhibition of subicular seizure-activated neurons enhanced the recruitment of cognition-responsive c-fos+ neurons via increasing neural excitability during cognition tasks. Our results demonstrate that subicular seizure-activated neurons contribute to cognitive impairment in TLE, suggesting seizure-activated neurons as the potential therapeutic target to alleviate cognitive impairment in TLE.

CNN neural network temporal feature storage structure fusion for the visible channel equalization algorithm.

The visible light communication channel has time-varying characteristics and is difficult to predict. This paper proposes an equalization algorithm based on the structure of a convolutional neural network (CNN), combining time series feature length and long short-term memory (LSTM), and adding a residual structure. It can be seen that the equalization coefficient vector of the optical channel is a time series, which can reflect the noise characteristics of the channel and has storage characteristics. The equalizer algorithm can accurately learn the complex channel characteristics and calculate the compensation coefficient according to the channel characteristics. It can also restore the original transmission signal. At the same time, this paper also examines the compensation method of the receiver in the mobile state. The long-term memory parameters of LSTM are used to represent the sequence causality in the memory channel, and CNN and residual structure are used to refine the results and improve the accuracy of the reconstruction. The simulation results show that the algorithm can effectively eliminate the influence of the fading characteristics of the visible optical channel, improve the bit error rate performance of system transmission, solve the overall problem of channel corruption, and precisely restore the original transmission signal with fast convergence speed. In addition, this method can achieve a better balance between performance and complexity compared to the traditional contention balancing method, which proves the potential and effectiveness of the proposed channel balancing method.

Associations of CALM1 and DRD1 polymorphisms, and their expression levels, with Taihang chicken egg-production traits.

Egg production by hens is an important reproductive performance index in the poultry industry. To investigate the effects of the CALM1 and DRD1 genes on egg production in chicken, their mRNA expression and single nucleotide polymorphisms (SNP) levels were investigated, and bioinformatics and egg-production association analyses were performed. Three SNPs (g.44069941G > A and g.44069889A > G in CALM1 and g.10742639C > T in DRD1) were detected in the exons and introns of CALM1 and DRD1 in 400 Taihang chickens. Among them, g.44069941G > A was significantly associated with Taihang chicken egg production on the 500th day (p < 0.05), whereas g.10742639C > T was significantly associated with the 300th day (p < 0.05). The expression levels of CALM1 and DRD1 in ovarian tissues of a high-yielding Taihang group were greater than in a low-yielding group (p < 0.05). The bioinformatics analysis revealed that the mutations influenced the mRNA secondary structures of CALM1 and DRD1. This study provides new insights into the potential effects of CALM1 and DRD1 polymorphisms on chicken egg production. The two SNPs g.44069941G > A and g.10742639C > T are potential molecular markers for improving the reproductive traits of Taihang chicken.

CALM1 and DRD1 were two important genes for reproduction. In this study, the entire coding regions of both genes were sequenced and mutations were detected in Taihang chickens. The results showed that two single nucleotide polymorphisms (SNPs), g.44069941G > A in the CALM1 gene and g.10742639C > T in the DRD1 gene, were associated with egg-laying traits. g.10742639C > T is a synonymous mutation predicted to affect the secondary structure of mRNA. Therefore, these two mutations might be potential molecular markers for improving reproductive traits in Taihang chickens.

Insight into Drug Resistance in Status Epilepticus: Evidence from Animal Models.

Status epilepticus (SE), a condition with abnormally prolonged seizures, is a severe type of epilepsy. At present, SE is not well controlled by clinical treatments. Antiepileptic drugs (AEDs) are the main therapeutic approaches, but they are effective for SE only with a narrow intervening window, and they easily induce resistance. Thus, in this review, we provide an updated summary for an insight into drug-resistant SE, hoping to add to the understanding of the mechanism of refractory SE and the development of active compounds. Firstly, we briefly outline the limitations of current drug treatments for SE by summarizing the extensive experimental literature and clinical data through a search of the PubMed database, and then summarize the common animal models of refractory SE with their advantages and disadvantages. Notably, we also briefly review some of the hypotheses about drug resistance in SE that are well accepted in the field, and furthermore, put forward future perspectives for follow-up research on SE.

Living Cell Nanoporation and Exosomal RNA Analysis Platform for Real-Time Assessment of Cellular Therapies.

Efficient transfection of therapeutic agents and timely potency testing are two key factors hindering the development of cellular therapy. Here we present a cellular-nanoporation and exosome assessment device, a quantitative platform for nanochannel-based cell electroporation and exosome-based in situ RNA expression analysis. In its application to transfection of anti-miRNAs and/or chemotherapeutics into cells, we have systematically described the differences in RNA expression in secreted exosomes and assessed cellular therapies in real time.

RNA-binding protein hnRNPR reduces neuronal cholesterol levels by binding to and suppressing HMGCR.

Recent studies have identified multiple RNA-binding proteins tightly associated with lipid and neuronal cholesterol metabolism and cardiovascular disorders. However, the role of heterogeneous nuclear ribonucleoprotein R (hnRNPR) in cholesterol metabolism and homeostasis, whether it has a role in regulating 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), is largely unknown. This research identifies hnRNPR as a repressor of HMGCR. Knockdown and overexpression of hnRNPR in cultured neuroblastoma cell (N2a) and MN1 cell lines enhances and inhibits HMGCR in vitro, respectively. hnRNPR may exert its repressive activity on HMGCR mRNA and protein levels by using its RNA recognition motif (RRM) in recognizing and modulating the stability of HMGCR transcript. Our RNA immunoprecipitation and luciferase reporter assays demonstrate a direct interaction between hnRNPR and HMGCR mRNA. We also demonstrated that hnRNR binds to the 3' untranslated region (3' UTR) of HMGCR and reduces its translation, while hnRNPR silencing increases HMGCR expression and cholesterol levels in MN1 and N2a cells. Overexpression of HMGCR significantly restores the decreased cholesterol levels in hnRNPR administered cells. Taken together, we identify hnRNPR as a novel post-transcriptional regulator of HMGCR expression in neuronal cholesterol homeostasis.

Coming of Age: Cryo-Electron Tomography as a Versatile Tool to Generate High-Resolution Structures at Cellular/Biological Interfaces.

Over the last few years, cryo electron microscopy has become the most important method in structural biology. While 80% of deposited maps are from single particle analysis, electron tomography has grown to become the second most important method. In particular sub-tomogram averaging has matured as a method, delivering structures between 2 and 5 Å from complexes in cells as well as in vitro complexes. While this resolution range is not standard, novel developments point toward a promising future. Here, we provide a guide for the workflow from sample to structure to gain insight into this emerging field.

A distance based multisample test for high-dimensional compositional data with applications to the human microbiome.

BACKGROUND: Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods are needed to analyze this special type of data. RESULTS: In this paper, we consider a general problem of testing for the compositional difference between K populations. Motivated by microbiome and metagenomics studies, where the data are often over-dispersed and high-dimensional, we formulate a well-posed hypothesis from a Bayesian point of view and suggest a nonparametric test based on inter-point distance to evaluate statistical significance. Unlike most existing tests for compositional data, our method does not rely on any data transformation, sparsity assumption or regularity conditions on the covariance matrix, but directly analyzes the compositions. Simulated data and two real data sets on the human microbiome are used to illustrate the promise of our method. CONCLUSIONS: Our simulation studies and real data applications demonstrate that the proposed test is more sensitive to the compositional difference than the mean-based method, especially when the data are over-dispersed or zero-inflated. The proposed test is easy to implement and computationally efficient, facilitating its application to large-scale datasets.

Determination of the levels of tryptophan and 12 metabolites in milk by liquid chromatography-tandem mass spectrometry with the QuEChERS method.

Tryptophan and metabolites have important biological functions in humans. Milk is an important source of tryptophan intake. In this study, we developed a method to detect levels of tryptophan and 12 metabolites in milk. The analytes were extracted by using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure and analyzed by liquid chromatography-tandem mass spectrometry with electrospray ionization. The proposed method resulted in suitable accuracy (standard deviation ≤10.31%) and high sensitivity (the limits of quantification were between 0.05 and 5 ng/mL). Recoveries were in the range of 44 to 126%. Finally, the developed method was successfully applied to compare the content of tryptophan and metabolites in 4 milk products produced by different processes: pasteurized milk, UHT milk, milk powder, and yogurt. The results of partial least squares-discriminant analysis (PLS-DA) showed that different types of processed milk could be distinguished clearly according to the method used here. The determined tryptophan and metabolites levels in milk can provide a new reference for evaluation of milk.

Rare combined variations of accessory left hepatic artery and accessory right hepatic artery: a case report and literature review.

Variations in the hepatic artery are commonly described in the literature, which is vital for the success procedure of all hepatobiliary surgery. Usually a variation occurs in either the accessory right hepatic artery (aRHA) or the accessory left hepatic artery (aLHA). However, we report an extremely rare case where the variation occurs in both simultaneously. We over served the aRHA arising from the gastroduodenal artery and branching into the superior pancreatic duodenum artery, while the aLHA arose from the common hepatic artery and branched into right gastric artery. This situation has never been reported in literature. We will discuss the meaning of this hepatic artery variation in a clinical setting.

An Activatable Lanthanide Luminescent Probe for Time-Gated Detection of Nitroreductase in Live Bacteria.

Herein we report the development of a turn-on lanthanide luminescent probe for time-gated detection of nitroreductases (NTRs) in live bacteria. The probe is activated through NTR-induced formation of the sensitizing carbostyril antenna and resulting energy transfer to the lanthanide center. This novel NTR-responsive trigger is virtually non-fluorescent in its inactivated form and features a large signal increase upon activation. We show that the probe is capable of selectively sensing NTR in lysates as well as in live bacteria of the ESKAPE family which are clinically highly relevant multiresistant pathogens responsible for the majority of hospital infections. The results suggest that our probe could be used to develop diagnostic tools for bacterial infections.

Analytical Platform To Characterize Dopant Solution Concentrations, Charge Carrier Densities in Films and Interfaces, and Physical Diffusion in Polymers Utilizing Remote Field-Effect Transistors.

Characterizing doping effects in a conductive polymer and physical diffusion in a passive polymer were performed using a remote-gate field-effect transistor (RG FET) detection system that was able to measure the electrical potential perturbation of a polymer film coupled to the gate of a silicon FET. Poly(3-hexylthiophene) (P3HT) film doped using various concentrations of 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) solutions imposed additional positive potentials on the P3HT RG, resulting in a lower threshold voltage ( Vth) on the n-channel silicon FET. Changes in Vth were related to the induced hole concentrations and hole mobility in P3HT films by using our Vth shifting model for the RG FET. We discovered that the electron-donating P3HT and even inorganic materials, indium tin oxide and gold, showed similar electrical potential perturbations dependent on the concentration of F4TCNQ in overlying solutions as the dopant radical anions maximally covered the surfaces. This suggests that there are limited electroactive sites for F4TCNQ binding on electron donor surfaces which results in a similar number of positive charges in film materials forming dipoles with the F4TCNQ radical counteranions. The effect of electron acceptors such as 7,7,8,8-tetracyanoquinodimethane and tetracyanoethylene was compared to that of F4TCNQ in terms of Vth shift using our analytical tool, with differences attributed to acceptor size and reduction potential. Meanwhile, this FET analysis tool offered a means of monitoring the physical diffusion of small molecules, exemplified by F4TCNQ, in the passive polymer polystyrene, driven by concentration gradients. The technique allows for nondestructive, nonspectroscopic, ambient characterization of electron donor-acceptor interactions at surfaces.