Maternal Separation Alters Ethanol Drinking and Reversal Learning Processes in Adolescent Rats: The Impact of Sex and Glycine Transporter Type 1 (GlyT1) Inhibitor

Adverse early life experiences are associated with an enhanced risk for mental and physical health problems, including substance abuse. Despite clinical evidence, the mechanisms underlying these relationships are not fully understood. Maternal separation (MS) is a commonly used animal model of early neglect. The aim of the current study is to determine whether the N-methyl-D-aspartate receptor (NMDAR)/glycine sites are involved in vulnerability to alcohol consumption (two-bottle choice paradigm) and reversal learning deficits (Barnes maze task) in adolescent rats subjected to the MS procedure and whether these effects are sex dependent. By using ELISA, we evaluated MS-induced changes in the NMDAR subunits (GluN1, GluN2A, GluN2B) expression, especially in the glycine-binding subunit, GluN1, in the prefrontal cortex (PFC) and ventral striatum (vSTR) of male/female rats. Next, we investigated whether Org 24598, a glycine transporter 1 (GlyT1) inhibitor, was able to modify ethanol drinking in adolescent and adult male/female rats with prior MS experience and reversal learning in the Barnes maze task. Our findings revealed that adolescent MS female rats consumed more alcohol which may be associated with a substantial increase in GluN1 subunit of NMDAR in the PFC and vSTR. Org 24598 decreased ethanol intake in both sexes with a more pronounced decrease in ethanol consumption in adolescent female rats. Furthermore, MS showed deficits in reversal learning in both sexes. Org 24598 ameliorated reversal learning deficits, and this effect was reversed by the NMDAR/glycine site inhibitor, L-701,324. Collectively, our results suggest that NMDAR/glycine sites might be targeted in the treatment of alcohol abuse in adolescents with early MS, especially females.     

Formal verification of a modern SAT solver by shallow embedding into Isabelle/HOL

We present a formalization and a formal total correctness proof of a MiniSAT-like SAT solver within the system Isabelle/HOL. The solver is based on the DPLL procedure and employs most state-of-the-art SAT solving techniques, including the conflict-guided backjumping, clause learning, and the two-watched unit propagation scheme. A shallow embedding into Isabelle/HOL is used and the solver is expressed as a set of recursive HOL functions. Based on this specification, the Isabelle’s built-in code generator can be used to generate executable code in several supported functional languages (Haskell, SML, and OCaml). The SAT solver implemented in this way is, to our knowledge, the first fully formally and mechanically verified modern SAT solver.     

Performance Characterization of Game Recommendation Algorithms on Online Social Network Sites

Since years,online social networks have evolved from profile and communication websites to online portals where people interact with each other,share and consume multimedia-enriched data and play different types of games.Due to the immense popularity of these online games and their huge revenue potential,the number of these games increases every day,resulting in a current offering of thousands of online social games.In this paper,the applicability of neighborhood-based collaborative filtering(CF) algorithms for the recommendation of online social games is evaluated.This evaluation is based on a large dataset of an online social gaming platform containing game ratings(explicit data) and online gaming behavior(implicit data) of millions of active users.Several similarity metrics were implemented and evaluated on the explicit data,implicit data and a combination thereof.It is shown that the neighborhood-based CF algorithms greatly outperform the content-based algorithm,currently often used on online social gaming websites.The results also show that a combined approach,i.e.,taking into account both implicit and explicit data at the same time,yields overall good results on all evaluation metrics for all scenarios,while only slightly performing worse compared to the strengths of the explicit or implicit only approaches.The best performing algorithms have been implemented in a live setup of the online game platform.     

Reinforcement learning for parameter estimation in statistical spoken dialogue systems

Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estimate the parameters of a dialogue policy which selects the system's responses based on the inferred dialogue state. However, the inference of the dialogue state itself depends on a dialogue model which describes the expected behaviour of a user when interacting with the system. Ideally the parameters of this dialogue model should be also optimised to maximise the expected cumulative reward.This article presents two novel reinforcement algorithms for learning the parameters of a dialogue model. First, the Natural Belief Critic algorithm is designed to optimise the model parameters while the policy is kept fixed. This algorithm is suitable, for example, in systems using a handcrafted policy, perhaps prescribed by other design considerations. Second, the Natural Actor and Belief Critic algorithm jointly optimises both the model and the policy parameters. The algorithms are evaluated on a statistical dialogue system modelled as a Partially Observable Markov Decision Process in a tourist information domain. The evaluation is performed with a user simulator and with real users. The experiments indicate that model parameters estimated to maximise the expected reward function provide improved performance compared to the baseline handcrafted parameters.     

The Role of the Human Microbiome in the Pathogenesis of Pain

Understanding of the gut microbiome’s role in human physiology developed rapidly in recent years. Moreover, any alteration of this microenvironment could lead to a pathophysiological reaction of numerous organs. It results from the bidirectional communication of the gastrointestinal tract with the central nervous system, called the gut–brain axis. The signals in the gut–brain axis are mediated by immunological, hormonal, and neural pathways. However, it is also influenced by microorganisms in the gut. The disturbances in the gut–brain axis are associated with gastrointestinal syndromes, but recently their role in the development of different types of pain was reported. The gut microbiome could be the factor in the central sensitization of chronic pain by regulating microglia, astrocytes, and immune cells. Dysbiosis could lead to incorrect immune responses, resulting in the development of inflammatory pain such as endometriosis. Furthermore, chronic visceral pain, associated with functional gastrointestinal disorders, could result from a disruption in the gut microenvironment. Any alteration in the gut–brain axis could also trigger migraine attacks by affecting cytokine expression. Understanding the gut microbiome’s role in pain pathophysiology leads to the development of analgetic therapies targeting microorganisms. Probiotics, FODMAP diet, and fecal microbiota transplantation are reported to be beneficial in treating visceral pain.     

The Intersection of Human and Veterinary Medicine—A Possible Direction towards the Improvement of Cell Therapy Protocols in the Treatment of Perianal Fistulas

The effective treatment of perianal fistulizing Crohn’s disease is still a challenge. Local administration of mesenchymal stromal cells (MSCs) is becoming a part of accepted treatment options. However, as a fledgling technique, it still can be optimized. A new trend in translational research, which is in line with “One Health” approach, bases on exploiting parallels between naturally occurring diseases affecting humans and companion animals. Canine anal furunculosis (AF) has been indicated as condition analogous to human perianal Crohn’s disease (pCD). This narrative review provides the first comprehensive comparative analysis of these two diseases based on the published data. The paper also outlines the molecular mechanisms of action of MSCs which are likely to have a role in modulating the perianal fistula niche in humans, and refers them to the current knowledge on the immunomodulatory properties of canine MSCs. Generally, the pathogenesis of both diseases shares main determinants such as the presence of genetic predispositions, dysregulation of immune response and the relation to intestine microbiota. However, we also identified many aspects which should be further specified, such as determining the frequency of true fistulas formation in AF patients, elucidating the role of TNF and Th17 pathway in the pathogenesis of AF, or clarifying the role of epithelial-to-mesenchymal transition phenomenon in the formation of canine fistulae. Nevertheless, the available data support the hypothesis that the results from testing cell therapies in dogs with anal furunculosis have a significant translational value in optimizing MSC transplants procedures in pCD patients.     

The Role of Cluster C19MC in Pre-Eclampsia Development

Pre-eclampsia is a placenta-related complication occurring in 2–10% of all pregnancies. miRNAs are a group of non-coding RNAs regulating gene expression. There is evidence that C19MC miRNAs are involved in the development of the placenta. Deregulation of chromosome 19 microRNA cluster (C19MC) miRNAs expression leads to impaired cell differentiation, abnormal trophoblast invasion and pathological angiogenesis, which can lead to the development of pre-eclampsia. Information was obtained through a review of articles available in PubMed Medline. Articles on the role of the C19MC miRNA in the development of pre-eclampsia published in 2009–2022 were analyzed. This review article summarizes the current data on the role of the C19MC miRNA in the development of pre-eclampsia. They indicate a significant increase in the expression of most C19MC miRNAs in placental tissue and a high level of circulating fractions in serum and plasma, both in the first and/or third trimester in women with PE. Only for miR-525-5p, low levels of plasma expression were noted in the first trimester, and in the placenta in the third trimester. The search for molecular factors indicating the development of pre-eclampsia before the onset of clinical symptoms seems to be a promising diagnostic route. Identifying women at risk of developing pre-eclampsia at the pre-symptomatic stage would avoid serious complications in both mothers and fetuses. We believe that miRNAs belonging to cluster C19MC could be promising biomarkers of pre-eclampsia development.     

融合魏斯氏菌和异常威克汉姆酵母混菌发酵荞麦酸面团馒头的香气物质特征

应用分离自我国酒鬼酒曲中的融合魏斯氏菌和梅兰春酒醅中的异常威克汉姆酵母进行混菌发酵,通过测定菌株生长曲线探索两株菌的共生作用,采用固相微萃取结合气质联用(SPME-GC-MS)和气相电子鼻技术,对比混菌发酵酸面团(MBF)和单菌发酵酸面团及其荞麦馒头风味化合物的差异性。结果表明,在MBF中乳酸菌、酵母菌菌落数分别达到9.38 log CFU/g、8.51 log CFU/g,两株菌具有良好的共生关系。发酵后荞麦酸面团的主要特征风味物质为乙醇、乙酸、乙酸乙酯、乙偶姻和异戊醇。与酵母菌单菌发酵荞麦酸面团馒头相比,混菌发酵馒头中酯类物质相对含量从5.27%提高到9.53%,结合ROAV分析,混菌发酵荞麦馒头的风味强度明显高于单一乳酸发酵和单一酵母发酵,赋予馒头更浓郁的酒香和果香,感官评定证实其整体可接受度高于其他组。     

不同发酵时间甜酒酿面团的超微结构与面包香气特征研究

本研究将不同发酵时间(0、24、48、72 h)的广西农家酒曲制备的酒酿应用到面包中,采用α-氨基态氮表征蛋白酶活力,利用激光共聚焦观察面团的超微结构,通过气质联用测定面包中的挥发性风味物质,并结合感官鉴评,对面包进行品质评价。结果表明:甜酒酿面团(FRD)发酵前后α-氨基氮含量没有显著性差异(p>0.05),但添加有48 h甜酒酿面团的网络结构最稳定。与发酵0 h甜酒酿面包(FRB)相比,48 h甜酒酿面包中酯类、醇类物质明显增多,尤其是辛酸乙酯、壬酸乙酯以及异戊醇,赋予面包更浓郁的花香和果香。除72 h甜酒酿面包外,各组面包比容没有显著性差异(p>0.05),48 h甜酒酿面包在感官鉴评中获得更高的分数,面包更易被接受。     

GC-MS分析传统酸面团馒头风味及添加食用碱对其风味的影响

通过固相微萃取和GC-MS联用技术,对山东青岛SDQ、河北邢台HBX和河南驻马店HNZ三地酸面团馒头风味物质进行检测,并研究食用碱的添加对馒头风味的影响。结果显示,每个地方的酸面团馒头都有自己独特的酯、醛、烯等风味物质呈现。食用碱的引入会使风味物质种类和总量都下降,但主要呈味物质醇、醛等变化不大。其中SDQ风味物质由原来的41种下降到39种,总量下降30.33%;HBX由63种下降到60种,总量下降28.05%;HNZ由81种下降到78种,总量下降21.73%。加碱后酸类和酯类含量下降明显。