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Chronic pain (CP) is a leading cause of disability and a potential factor that affects biological processes, family relationships, and self-esteem of patients. However, the need for treatment of CP is presently unmet. Current methods of pain management involve the use of drugs, but there are different degrees of concerning side effects. At present, the potential mechanisms underlying CP are not completely clear. As research progresses and novel therapeutic approaches are developed, the shortcomings of current pain treatment methods may be overcome. In this review, we discuss the retinal photoreceptors and brain regions associated with photoanalgesia, as well as the targets involved in photoanalgesia, shedding light on its potential underlying mechanisms. Our aim is to provide a foundation to understand the mechanisms underlying CP and develop light as a novel analgesic treatment has its biological regulation principle for CP. This approach may provide an opportunity to drive the field towards future translational, clinical studies and support pain drug development. [ABSTRACT FROM AUTHOR]

Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential attacks. Previous research has shown classic adversarial examples have different logits distribution compared to normal speech. This paper proposes a logit-traction attack to eliminate this difference at the statistical level. Experiments on the LibriSpeech dataset show that the proposed attack reduces the accuracy of the LOGITS NOISE detection to 52.1%. To further verify the effectiveness of this approach in attacking detection based on logits, three different features quantifying the dispersion of logits are constructed in this paper. Furthermore, a richer target sentence is adopted for experiments. The results indicate that these features can detect baseline adversarial examples with an accuracy of about 90% but cannot effectively detect Logits-Traction adversarial examples, proving that Logits-Traction attack can evade the logits-based detection method. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding small, human-imperceptible perturbations to the original images, but make the model output inaccurate predictions. Before DNNs are deployed, adversarial attacks can thus be an important method to evaluate and select robust models in safety-critical applications. However, under the challenging black-box setting, the attack success rate, i.e., the transferability of adversarial examples, still needs to be improved. Based on image augmentation methods, this paper found that random transformation of image brightness can eliminate overfitting in the generation of adversarial examples and improve their transferability. In light of this phenomenon, this paper proposes an adversarial example generation method, which can be integrated with Fast Gradient Sign Method (FGSM)-related methods to build a more robust gradient-based attack and to generate adversarial examples with better transferability. Extensive experiments on the ImageNet dataset have demonstrated the effectiveness of the aforementioned method. Whether on normally or adversarially trained networks, our method has a higher success rate for black-box attacks than other attack methods based on data augmentation. It is hoped that this method can help evaluate and improve the robustness of models. [ABSTRACT FROM AUTHOR]

5G provides a unified authentication architecture and access management for IoT (Internet of Things) devices. But existing authentication services cannot cover massive IoT devices with various computing capabilities. In addition, with the development of quantum computing, authentication schemes based on traditional digital signature technology may not be as secure as we expected. This paper studies the authentication mechanism from the user equipment to the external data network in 5G and proposed an authentication protocol prototype that conforms to the Third Generation Partnership Program (3GPP) standard. This prototype can accommodate various Hash-based signature technologies, applying their advantages in resource consumption to meet the authentication requirements of multiple types of IoT devices. The operation of the proposed authentication scheme is mainly based on the Hash function, which is more efficient than the traditional authentication scheme. It provides flexible and high-quality authentication services for IoT devices cluster in the 5G environment combining the advantages of Hash-based signature technology and 5G architecture. [ABSTRACT FROM AUTHOR]

Premenstrual dysphoric disorder (PMDD) is a severe form of premenstrual syndrome (PMS), a common mental health disturbance associated with several periodic psychological symptoms in women. Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for PMS/PMDD patients; however, side effects are inevitable, especially in long-term treatment. In previous studies, the natural compound paeonol in Moutan Cortex was found to play effective roles in central nervous system disorders with its anti-inflammatory, anti-oxidant, and neuroprotective effects. Consequently, we assume that paeonol might produce positive effects in the treatment of PMS/PMDD. In this study, the open-field test (OFT) and elevated plus maze (EPM) and light dark box (LDB) tests were performed in mice to determine the optimal dose of paeonol for treating anxiety. Then, paeonol was used to treat the progesterone withdrawal (PWD) and resident intruder paradigm (RIP) rat models of PMDD. Using these two reliable models, the OFT and EPM, LDB, and composite aggressive tests were performed to evaluate the effect of the drug on behavioural symptoms of PMDD. From the dosage screening results, the optimal anti-anxiety dose of paeonol was identified as 17.5 mg/kg/d for 7 days. With regard to the effect of paeonol on PMDD rat models, a significantly improvement was found in the behavioural symptoms, but the effective dose varied in different models. For the PWD model rats, treatment with 6.05 mg/kg paeonol could significantly improve anxiety and irritability, while that with 24.23 mg/kg paeonol resulted in anxiety-like effects in behavioural tests. In RIP model rats, treatment with 12.11 mg/kg paeonol demonstrated excellent effects in improving anxiety, particularly irritable emotional behaviour. In conclusion, our study indicates that paeonol is a potential therapeutic compound for PMS/PMDD; it is a drug option that helps establish dosage guidance for treatment of this condition. [ABSTRACT FROM AUTHOR]

Curcumin is a chemical constituent extracted from Curcuma longa L . Several clinical and preclinical studies have demonstrated that it can mitigate exercise fatigue, but the exact mechanism is still unknown. Therefore, we applied a mouse model of exercise fatigue to investigate the possible molecular mechanisms of curcumin's anti-fatigue effect. Depending on body mass, Kunming mice were randomly divided into control, caffeine (positive drug), and curcumin groups, and were given 28 days intragastric administration. Both the caffeine group and curcumin group showed significant improvement in exercise fatigue compared to the control group, as evidenced by the increase in time to exhaustion, as well as the higher quadriceps coefficient, muscle glycogen (MG) content, and increase in the expression of Akt, AMPK, PI3K, and mTOR proteins. While the curcumin group also significantly improved the exercise fatigue of the mice, demonstrating a lower AMP/ATP ratio and lactic acid (LA) content, and increased glycogen synthase (GS), and myonectin content compared to the caffeine group. Therefore, in the present study, we found that curcumin can exert a similar anti-fatigue effect to caffeine and may act by regulating energy metabolism through modulating the expression of the proteins in the PI3K/Akt/AMPK/mTOR pathway.

Autism spectrum disorders (ASD) is a group of generalized neurodevelopmental disorders. Its main clinical features are social communication disorder and repetitive stereotyped behavioral interest. The abnormal structure and function of brain network is the basis of social dysfunction and stereotyped performance in patients with autism spectrum disorder. The number of patients diagnosed with ASD has increased year by year, but there is a lack of effective intervention and treatment. Oxytocin has been revealed to effectively improve social cognitive function and significantly improve the social information processing ability, empathy ability and social communication ability of ASD patients. The change of serotonin level also been reported affecting the development of brain and causes ASD-like behavioral abnormalities, such as anxiety, depression like behavior, stereotyped behavior. Present review will focus on the research progress of serotonin and oxytocin in the pathogenesis, brain circuit changes and treatment of autism. Revealing the regulatory effect and neural mechanism of serotonin and oxytocin on patients with ASD is not only conducive to a deeper comprehension of the pathogenesis of ASD, but also has vital clinical significance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao, Zhang, Wang, Cui, Xu, Chen, Hu, Li, Geng and Wei.)

Premenstrual dysphoric disorder (PMDD), a form of premenstrual syndrome (PMS), is a severe health disturbance that affects a patient's emotions; it is caused by periodic psychological symptoms, and its pathogenesis remains unclear. As depression-like symptoms are found in a majority of clinical cases, a reliable animal model of premenstrual depression is indispensable to understand the pathogenesis. Herein, we describe a novel rat model of premenstrual depression, based on the forced swimming test, with a regular estrous cycle. The results showed that in the estrous cycle, the depression-like behavior of rats occurred in the non-receptive phase and disappeared in the receptive phase. Following ovariectomy, the depression-like symptoms disappeared and returned after a hormone priming regimen. Moreover, fluoxetine, an anti-depressant, could reverse the behavioral symptoms in these model rats with normal estrous cycle. Further, the model rats showed significant changes in the serum levels of estrogen and progesterone, hippocampal levels of allopregnanolone, 5-hydroxytryptamine, norepinephrine, and γ-aminobutyric acid (GABA), and in the expression of GABA A receptor 4α subunit, all of which were reversed to physiological levels by fluoxetine. Overall, we established a reliable and standardized rat model of premenstrual depression, which may facilitate the elucidation of PMS/PMDD pathogenesis and development of related therapies.

Previous studies have reported that maternal chronic stress or depression is linked to an increased risk of affective disorders in progeny. However, the impact of maternal chronic stress before pregnancy on the progeny of animal models is unknown. We investigated the behaviors and the neurobiology of 60-day-old male offspring of female rats subjected to 21 days of resident-intruder stress before pregnancy. An anger stressed parental rat model was established using the resident-intruder paradigm and it was evaluated using behavioral tests. Anger stressed maternal rats showed a significant increase in locomotion and aggression but a reduction in sucrose preference. Offspring subjected to pre-gestational anger stress displayed enhanced aggressive behaviors, reduced anxiety, and sucrose preference. Further, offspring subjected to pre-gestational stress showed significant impairments in the recognition index (RI) on the object recognition test and the number of platform crossings in the Morris water maze test. The monoaminergic system was significantly altered in pre-gestationally stressed offspring, and the expression of phosphorylated cyclic adenosine monophosphate response element binding protein (P-CREB), brain-derived neurotrophic factor (BDNF), and serotonin transporter (SERT) levels in pre-gestational stressed offspring were altered in some brain regions. Fluoxetine was used to treat pre-gestational stressed maternal rats and it significantly reduced the changes caused by stress, as evidenced by both behaviors and neural biochemical indexes in the offspring in some but not all cases. These findings suggest that anger stress before pregnancy could induce aggressive behaviors, cognitive deficits, and neurobiological alterations in offspring., Competing Interests: CONFLICTS OF INTEREST No author has any potential conflicts of interest.