Ginkgolide B effectively mitigates neuropathic pain by suppressing the activation of the NLRP3 inflammasome through the induction of mitophagy in rats.

Neuropathic pain is a pathological state induced by the aberrant generation of pain signals within the nervous system. Ginkgolide B(GB), an active component found of Ginkgo. biloba leaves, has neuroprotective properties. This study aimed to explore the effects of GB on neuropathic pain and its underlying mechanisms. In the in vivo study, we adopted the rat chronic constriction injury model, and the results showed that GB(4 mg/kg) treatment effectively reduced pain sensation in rats and decreased the expressions of Iba-1 (a microglia marker), NLRP3 inflammasome, and inflammatory factors, such as interleukin (IL)-1ß, in the spinal cord 7 days post-surgery. In the in vitro study, we induced microglial inflammation using lipopolysaccharide (500 ng/mL) / adenosine triphosphate (5 mM) and treated it with GB (10, 20, and 40 µM). GB upregulated the expression of mitophagy proteins, such as PINK1, Parkin, LC3 II/I, Tom20, and Beclin1, and decreased the cellular production of reactive oxygen species. Moreover, it lowered the expression of inflammation-related proteins, such as Caspase-1, IL-1ß, and NLRP3 in microglia. However, this effect was reversed by Parkin shRNA/siRNA or the autophagy inhibitor 3-methyladenine (5 mM). These findings reveal that GB alleviates neuropathic pain by mitigating neuroinflammation through the activation of PINK1-Parkin-mediated mitophagy.

ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding.

An Electroencephalography (EEG) dataset utilizing rich text stimuli can advance the understanding of how the brain encodes semantic information and contribute to semantic decoding in brain-computer interface (BCI). Addressing the scarcity of EEG datasets featuring Chinese linguistic stimuli, we present the ChineseEEG dataset, a high-density EEG dataset complemented by simultaneous eye-tracking recordings. This dataset was compiled while 10 participants silently read approximately 13 hours of Chinese text from two well-known novels. This dataset provides long-duration EEG recordings, along with pre-processed EEG sensor-level data and semantic embeddings of reading materials extracted by a pre-trained natural language processing (NLP) model. As a pilot EEG dataset derived from natural Chinese linguistic stimuli, ChineseEEG can significantly support research across neuroscience, NLP, and linguistics. It establishes a benchmark dataset for Chinese semantic decoding, aids in the development of BCIs, and facilitates the exploration of alignment between large language models and human cognitive processes. It can also aid research into the brain's mechanisms of language processing within the context of the Chinese natural language.

The persistence of SARS-CoV-2 in tissues and its association with long COVID symptoms: a cross-sectional cohort study in China.

BACKGROUND: Growing evidence suggests that symptoms associated with post-COVID-19 condition (also known as long COVID) can affect multiple organs and systems in the human body, but their association with viral persistence is not clear. The aim of this study was to investigate the persistence of SARS-CoV-2 in diverse tissues at three timepoints following recovery from mild COVID-19, as well as its association with long COVID symptoms. METHODS: This single-centre, cross-sectional cohort study was done at China-Japan Friendship Hospital in Beijing, China, following the omicron wave of COVID-19 in December, 2022. Individuals with mild COVID-19 confirmed by PCR or a lateral flow test scheduled to undergo gastroscopy, surgery, or chemotherapy, or scheduled for treatment in hospital for other reasons, at 1 month, 2 months, or 4 months after infection were enrolled in this study. Residual surgical samples, gastroscopy samples, and blood samples were collected approximately 1 month (18-33 days), 2 months (55-84 days), or 4 months (115-134 days) after infection. SARS-CoV-2 was detected by digital droplet PCR and further confirmed through RNA in-situ hybridisation, immunofluorescence, and immunohistochemistry. Telephone follow-up was done at 4 months post-infection to assess the association between the persistence of SARS-CoV-2 RNA and long COVID symptoms. FINDINGS: Between Jan 3 and April 28, 2023, 317 tissue samples were collected from 225 patients, including 201 residual surgical specimens, 59 gastroscopy samples, and 57 blood component samples. Viral RNA was detected in 16 (30%) of 53 solid tissue samples collected at 1 month, 38 (27%) of 141 collected at 2 months, and seven (11%) of 66 collected at 4 months. Viral RNA was distributed across ten different types of solid tissues, including liver, kidney, stomach, intestine, brain, blood vessel, lung, breast, skin, and thyroid. Additionally, subgenomic RNA was detected in 26 (43%) of 61 solid tissue samples tested for subgenomic RNA that also tested positive for viral RNA. At 2 months after infection, viral RNA was detected in the plasma of three (33%), granulocytes of one (11%), and peripheral blood mononuclear cells of two (22%) of nine patients who were immunocompromised, but in none of these blood compartments in ten patients who were immunocompetent. Among 213 patients who completed the telephone questionnaire, 72 (34%) reported at least one long COVID symptom, with fatigue (21%, 44 of 213) being the most frequent symptom. Detection of viral RNA in recovered patients was significantly associated with the development of long COVID symptoms (odds ratio 5·17, 95% CI 2·64-10·13, p<0·0001). Patients with higher virus copy numbers had a higher likelihood of developing long COVID symptoms. INTERPRETATION: Our findings suggest that residual SARS-CoV-2 can persist in patients who have recovered from mild COVID-19 and that there is a significant association between viral persistence and long COVID symptoms. Further research is needed to verify a mechanistic link and identify potential targets to improve long COVID symptoms. FUNDING: National Natural Science Foundation of China, National Key R&D Program of China, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, and New Cornerstone Science Foundation. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis.

OBJECTIVE: This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches. METHODS: Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm. RESULTS: Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen. CONCLUSIONS: The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy. SYSTEMATIC REVIEW REGISTRATION: [https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Dataset on the effects of psychological care on depression and suicide ideation in underrepresented children.

Massive increases in the risks of depressive disorders and the ensuing suicide have become the overarching menace for children/adolescents. Despite global consensus to instigate psychological healthcare policy for these children/adolescents, their effects remain largely unclear neither from a small amount of official data nor from small-scale scientific studies. More importantly, in underprivileged children/adolescents in lower-middle-economic-status countries/areas, the data collection may not be as equally accessible as in developed countries/areas, thus resulting in underrepresented observations. To address these challenges, we released a large-scale and multi-center cohort dataset (n = 249,772) showing the effects of primary psychological healthcare on decreasing depression and suicidal ideation in these children/adolescents who were underrepresented in previous studies or current healthcare systems, including unattended children/adolescents, orphans, children/adolescents in especially difficult circumstances, and "left-behind" and "single-parenting" children/adolescents. We provided all individual data recording the depressive symptoms and suicide ideation that had been collected at baseline (Oct 2022) and half-year follow-up (May 2023) from practicing this psychological healthcare system.

Replication study on the role of dopamine-dependent prefrontal reactivations in human extinction memory retrieval.

Even after successful extinction, conditioned fear can return. Strengthening the consolidation of the fear-inhibitory safety memory formed during extinction is one way to counteract return of fear. In a previous study, we found that post-extinction L-DOPA administration improved extinction memory retrieval 24 h later. Furthermore, spontaneous post-extinction reactivations of a neural activation pattern evoked in the ventromedial prefrontal cortex (vmPFC) during extinction predicted extinction memory retrieval, L-DOPA increased the number of these reactivations, and this mediated the effect of L-DOPA on extinction memory retrieval. Here, we conducted a preregistered replication study of this work in healthy male participants. We confirm that spontaneous post-extinction vmPFC reactivations predict extinction memory retrieval. This predictive effect, however, was only observed 90 min after extinction, and was not statistically significant at 45 min as in the discovery study. In contrast to our previous study, we find no evidence that L-DOPA administration significantly enhances retrieval and that this is mediated by enhancement of the number of vmPFC reactivations. However, additional non-preregistered analyses reveal a beneficial effect of L-DOPA on extinction retrieval when controlling for the trait-like stable baseline levels of salivary alpha-amylase enzymatic activity. Further, trait salivary alpha-amylase negatively predicts retrieval, and this effect is reduced by L-DOPA treatment. Importantly, the latter findings result from non-preregistered analyses and thus further investigation is needed.

Effective substances and molecular mechanisms guided by network pharmacology: An example study of Scrophulariae Radix treatment of hyperthyroidism and thyroid hormone-induced liver and kidney injuries.

ETHNOPHARMACOLOGICAL RELEVANCE: Scrophulariae Radix (Xuanshen [XS]) has been used for several years to treat hyperthyroidism. However, its effective substances and pharmacological mechanisms in the treatment of hyperthyroidism and thyroid hormone-induced liver and kidney injuries have not yet been elucidated. AIM OF THE STUDY: This study aimed to explore the pharmacological material basis and potential mechanism of XS therapy for hyperthyroidism and thyroid hormone-induced liver and kidney injuries based on network pharmacology prediction and experimental validation. MATERIALS AND METHODS: Based on 31 in vivo XS compounds identified using ultra-performance liquid chromatography tandem quadruple exactive orbitrap high-resolution accurate-mass spectrometry (UPLC-QE-HRMS), a network pharmacology approach was used for mechanism prediction. Systematic networks were constructed to identify the potential molecular targets, biological processes (BP), and signaling pathways. A component-target-pathway network was established. Mice were administered levothyroxine sodium through gavage for 30 d and then treated with different doses of XS extract with or without propylthiouracil (PTU) for 30 d. Blood, liver, and kidney samples were analyzed using an enzyme-linked immunosorbent assay (ELISA) and western blotting. RESULTS: A total of 31 prototypes, 60 Phase I metabolites, and 23 Phase II metabolites were tentatively identified in the plasma of rats following the oral administration of XS extract. Ninety-six potential common targets between the 31 in vivo compounds and the diseases were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that Bcl-2, BAD, JNK, p38, and ERK1/2 were the top targets. XS extract with or without PTU had the following effects: inhibition of T3/T4/fT3/fT4 caused by levothyroxine; increase of TSH levels in serum; restoration of thyroid structure; improvement of liver and kidney structure and function by elevating the activities of anti-oxidant enzymes catalase (CAT),superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px); activation anti-apoptotic proteins Bcl-2; inhibition the apoptotic protein p-BAD; downregulation inflammation-related proteins p-ERK1/2, p-JNK, and p-p38; and inhibition of the aggregation of pro-inflammatory cytokines TNF-α, IL-1ß, and IL-6, as well as immune cells in the liver. CONCLUSION: XS can be used to treat hyperthyroidism and liver and kidney injuries caused by thyroid hormones through its anti-oxidant, anti-inflammatory, and anti-apoptotic properties. In addition, serum pharmacochemical analysis revealed that five active compounds, namely 4-methylcatechol, sugiol, eugenol, acetovanillone, and oleic acid, have diverse metabolic pathways in vivo and exhibit potential as effective therapeutic agents.

A unified approach to demographic data collection for research with young children across diverse cultures.

Culture is a key determinant of children's development both in its own right and as a measure of generalizability of developmental phenomena. Studying the role of culture in development requires information about participants' demographic backgrounds. However, both reporting and treatment of demographic data are limited and inconsistent in child development research. A barrier to reporting demographic data in a consistent fashion is that no standardized tool currently exists to collect these data. Variation in cultural expectations, family structures, and life circumstances across communities make the creation of a unifying instrument challenging. Here, we present a framework to standardize demographic reporting for early child development (birth to 3 years of age), focusing on six core sociodemographic construct categories: biological information, gestational status, health status, community of descent, caregiving environment, and socioeconomic status. For each category, we discuss potential constructs and measurement items and provide guidance for their use and adaptation to diverse contexts. These items are stored in an open repository of context-adapted questionnaires that provide a consistent approach to obtaining and reporting demographic information so that these data can be archived and shared in a more standardized format. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effectiveness of self: A meta-analysis of using self-referential encoding techniques in education.

BACKGROUND: Self-related information is difficult to ignore and forget, which brings valuable implications for educational practice. Self-referential encoding techniques involve integrating self-referencing cues during the processing of learning material. However, the evidence base and effective implementation boundaries for these techniques in teaching and learning remain uncertain due to research variability. AIMS: The present meta-analysis aims to quantitatively synthesize the results from studies applying self-referential encoding techniques in education. METHODS: The analysis was based on data from 20 independent samples, including 1082 students from 13 primary studies identified through a systematic literature search. RESULTS: Results from random effect models show that incorporating self-referential encoding techniques improved learning (g = .40, 95% CI [.18, .62]). Subgroup analysis showed that the valence of learning material serves as a significant boundary condition for this strategy. The students' cohorts, types of learning materials, and research context did not moderate the effect sizes. CONCLUSIONS: Our results suggest that incorporating self-referential encoding techniques on negative materials shows an aversive effect. Overall, there is a universal benefit to using self-referential encoding techniques as an appropriate design guideline in educational contexts. Implications for teaching practice and future directions are discussed. Further studies are needed to investigate the effectiveness in more diverse educational and teaching situations.

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.

BACKGROUND: The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation. METHODS: Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses. RESULTS: A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (ß = - 2.75, p < .001, R2adj = 0.40; r = - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF10 > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance. CONCLUSIONS: Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.

Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.

Importance: Neuroimaging-based artificial intelligence (AI) diagnostic models have proliferated in psychiatry. However, their clinical applicability and reporting quality (ie, feasibility) for clinical practice have not been systematically evaluated. Objective: To systematically assess the risk of bias (ROB) and reporting quality of neuroimaging-based AI models for psychiatric diagnosis. Evidence Review: PubMed was searched for peer-reviewed, full-length articles published between January 1, 1990, and March 16, 2022. Studies aimed at developing or validating neuroimaging-based AI models for clinical diagnosis of psychiatric disorders were included. Reference lists were further searched for suitable original studies. Data extraction followed the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A closed-loop cross-sequential design was used for quality control. The PROBAST (Prediction Model Risk of Bias Assessment Tool) and modified CLEAR (Checklist for Evaluation of Image-Based Artificial Intelligence Reports) benchmarks were used to systematically evaluate ROB and reporting quality. Findings: A total of 517 studies presenting 555 AI models were included and evaluated. Of these models, 461 (83.1%; 95% CI, 80.0%-86.2%) were rated as having a high overall ROB based on the PROBAST. The ROB was particular high in the analysis domain, including inadequate sample size (398 of 555 models [71.7%; 95% CI, 68.0%-75.6%]), poor model performance examination (with 100% of models lacking calibration examination), and lack of handling data complexity (550 of 555 models [99.1%; 95% CI, 98.3%-99.9%]). None of the AI models was perceived to be applicable to clinical practices. Overall reporting completeness (ie, number of reported items/number of total items) for the AI models was 61.2% (95% CI, 60.6%-61.8%), and the completeness was poorest for the technical assessment domain with 39.9% (95% CI, 38.8%-41.1%). Conclusions and Relevance: This systematic review found that the clinical applicability and feasibility of neuroimaging-based AI models for psychiatric diagnosis were challenged by a high ROB and poor reporting quality. Particularly in the analysis domain, ROB in AI diagnostic models should be addressed before clinical application.

Mechanisms of Saponins in Chinese Medicinals Against Diabetic Nephropathy： A Review / 中国实验方剂学杂志

Diabetic nephropathy （DN）， the most feared microvascular complication of diabetes and one of the most common and serious complications of diabetes， is the major cause of end-stage renal disease worldwide， leading cause of morbidity and mortality in patients with diabetes， and the main non-communicable cause of death worldwide. There are many types of saponins， which are the main bioactive components of various Chinese medicinals. They have various pharmacological activities such as lowering blood glucose and blood lipids， improving insulin resistance， anti-inflammation， anti-oxidative stress， anti-tumor， and immune modulation. In recent years， it has been frequently verified that the saponins in Chinese medicinals have definite effect in regulating DN， showing multi-target， multi-pathway， multi-system， multi-effect characteristics. Thus， they have broad prospects in the prevention and treatment of this disease. There has been an explosion of research on the treatment of DN with saponins in Chinese medicinals in vivo and in vitro， but there is a lack of systematic and comprehensive summary. Therefore， this study summed up the studies of saponins in Chinese medicinals in the intervention of DN and summarized the mechanisms such as improving glucolipid metabolism， inhibiting oxidative stress， anti-inflammation， anti-apoptosis， regulating autophagy， anti-fibrosis， and protecting podocytes， with a view to providing ideas and references for the development of drugs related to DN.

Role of p38 MAPK Pathway in Diabetic Peripheral Neuropathy and Chinese Medicine Intervention： A Review / 中国实验方剂学杂志

Diabetic peripheral neuropathy （DPN） is a symptom and/or sign of peripheral nerve dysfunction that occurs in patients with diabetes mellitus when other causes are excluded. DPN， one of the most common complications of diabetes mellitus， can lead to disability， foot ulcers， and amputation at a later stage. Its pathogenesis is closely related to high glucose-induced inflammatory damage， oxidative stress， mitochondrial disorders， and apoptosis in neural tissues. The p38 mitogen-activated protein kinase （p38 MAPK） signaling pathway is a key mechanism mediating the expression of inflammatory factors， oxidative factors， and apoptotic factors of neural tissues in DPN. The inflammatory response， oxidative stress damage， and apoptosis， induced by the activation of p38 MAPK phosphorylation by factors such as high glucose， can cause cell lipid peroxidation， protein modification， and nucleic acid damage， which results in axonal degeneration and demyelination changes. The current treatment of DPN with western medicine has obvious shortcomings such as adverse effects and addictive tendencies. In recent years， the research on traditional Chinese medicine （TCM） in the prevention and treatment of DPN has gradually increased， and the exploration of Chinese medicine intervention in the p38 MAPK pathway transduction to improve DPN has advanced. The present study reviewed the relations of the p38 MAPK pathway with insulin resistance and peripheral neuropathy and summarized the molecular biological mechanisms involved in the pathological process of DPN， such as inflammation regulation， oxidative stress， polyol pathway regulation， and Schwann cell apoptosis in the past 10 years. In addition， the literature on Chinese medicine monomers， Chinese patent medicines， and Chinese medicine compounds in inhibiting inflammatory reactions， oxidative injury， and apoptosis of DPN peripheral nerves based on the p38 MAPK pathway， resisting axonal degeneration and demyelination changes， improving sensory and motor abnormalities， relieving peripheral pain sensitization， and facilitating nerve conduction mechanism to provide references for the development of new drugs for clinical prevention and treatment of DPN.

Effect of Loulianwan on Gut Microbiota in db/db Mice with Type 2 Diabetes Mellitus Based on 16S rRNA Sequencing Technology / 中国实验方剂学杂志

ObjectiveTo investigate the effect of Loulianwan on the gut microbiota of db/db mice with type 2 diabetes mellitus （T2DM）. MethodMale db/m+ mice aged 4-5 weeks were assigned to the normal group， and male db/db model mice of the same age were randomly divided into model group， metformin group （0.25 g·kg-1·d-1）， and Loulianwan group （13 g·kg-1·d-1）， with six mice in each group. Drug intervention lasted five weeks. The body weight， water intake， and fasting blood glucose （FBG） of the mice were recorded every week. After five weeks， the FBG， liver triglyceride （TG）， liver total cholesterol （TC）， glycated serum protein （GSP）， and fasting serum insulin （FINS） were detected， and the insulin resistance index （HOMA-IR） was calculated. The feces in the mouse intestines were collected， and the 16S rRNA sequencing technology was used to detect the structural changes in the fecal gut microbiota of mice in each group. ResultCompared with the normal group， the model group showed increased body weight， water intake， FBG， liver TG， liver TC， GSP， FINS， and HOMA-IR （P<0.01）. Compared with the model group， the Loulianwan group showed reduced water intake， FBG， liver TG， liver TC， GSP， FINS， and HOMA-IR （P<0.01）. The gut microbiota in the Loulian Lills group changed from phylum to genus level. The relative abundance of beneficial bacteria increased and the relative abundance of harmful bacteria decreased. Among them， the abundance of Akkermansia muciniphila， Blautia， Ruminococcus， and Parabacteroides increased （P<0.01）. ConclusionLoulianwan can significantly improve glucose and lipid metabolism in db/db mice with T2DM， and its mechanism may be related to the increase in the abundance of Akkermansia muciniphila， Blautia， Ruminococcus， and Parabacteroides in the intestine.

Hypoglycemic Effect and Mechanism of Chinese Medicine Saponins： A Review / 中国实验方剂学杂志

Type 2 diabetes mellitus （T2DM） is a chronic metabolic disease characterized by insulin resistance， hyperinsulinemia， and disturbance of glucose and lipid metabolism， with elevated blood glucose as the main clinical manifestation. Due to its complex etiology and pathogenesis， there is no effective treatment， which critically threatens human health and places a heavy burden on society and families. Saponins are a class of glycosides with complex structures that have the advantage of a wide range of sources， elevated safety， and low adverse effects. As an essential active ingredient in Chinese medicine， Chinese medicine saponins have a variety of biological activities such as hypoglycemia， hypoglycaemia， anti-inflammation， antioxidation， anti-tumor， and immune modulation. In recent years， numerous studies have shown that Chinese medicine saponins are effective in preventing and treating T2DM. Although there have been numerous studies on the hypoglycemic effects and mechanisms of Chinese medicine saponins， there has been no systematic review of the mechanisms of Chinese medicine saponins in the treatment of T2DM. Therefore， to provide a theoretical basis for an in-depth study of the hypoglycemic effects of Chinese medicine saponins and a scientific basis for the development and clinical application of drugs， this paper systematically summarized the hypoglycemic mechanisms of Chinese medicine saponins， such as improving islet β-cell function， improving insulin resistance， inhibiting glycosidase activity， reducing the inflammatory response， anti-oxidative stress， and regulating intestinal flora， and analyzed the current research problems and development trends.

Chinese Medicine Intervenes in Diabetic Kidney Disease Based on p38 MAPK Signaling Pathway：A Review / 中国实验方剂学杂志

Diabetic kidney disease （DKD）， a major microvascular complication of diabetes mellitus， serves as the most common cause of end-stage renal disease worldwide. The progression of DKD is closely related to oxidative stress， inflammatory response， apoptosis， and fibrosis in renal tissues activated by high glucose. Numerous studies have shown that the transduction of the p38 mitogen-activated protein kinase （p38 MAPK） signaling pathway is involved in the pathological process of DKD in renal tissues， activating various pathological mechanisms， such as oxidation， inflammation， apoptosis， and fibrosis. Therefore， blocking the transduction of the p38 MAPK signaling pathway is beneficial to alleviating DKD. At present， the main treatment principles of western medicine are glucose lowering， lipid lowering， and blood pressure lowering， as well as medications with new drugs renal sodium-glucose co-transporter 2 （SGLT2）， mineralocorticoid receptor， and endothelin receptor， but the progression of DKD still cannot be stopped. The treatment of DKD by traditional Chinese medicine （TCM） has the advantages of simplicity， low cost， and convenience， and the symptoms and root causes can be both treated. In recent years， the basic research on Chinese medicine intervention in DKD has greatly advanced， and p38 MAPK is the key factor of Chinese medicine intervention in DKD. The present study searched and reviewed the literature on the Chinese medicine intervention in the p38 MAPK signaling pathway in DKD treatment in the past decade. The results showed that p38 MAPK interacted with transforming growth factor-β1 （TGF-β1）， cysteinyl aspartate-specific protease-3 （Caspase-3）， nuclear factor-κB （NF-κB）， and other factors to activate fibrosis， inflammation， oxidative stress， and apoptosis. By acting on p38 MAPK and its upstream and downstream factors， Chinese medicine blocked the pathological processes of DKD and inhibited the pathological injury of DKD and the deterioration of renal function. This study is expected to provide new ideas and directions for the prevention and treatment of DKD with Chinese medicine.

Obliviate! Reviewing Neural Fundamentals of Intentional Forgetting from a Meta-Analytic Perspective.

Intentional forgetting (IF) is an important adaptive mechanism necessary for correct memory functioning, optimal psychological wellbeing, and appropriate daily performance. Due to its complexity, the neuropsychological processes that give birth to successful intentional forgetting are not yet clearly known. In this study, we used two different meta-analytic algorithms, Activation Likelihood Estimation (ALE) & Latent Dirichlet Allocation (LDA) to quantitatively assess the neural correlates of IF and to evaluate the degree of compatibility between the proposed neurobiological models and the existing brain imaging data. We found that IF involves the interaction of two networks, the main "core regions" consisting of a primarily right-lateralized frontal-parietal circuit that is activated irrespective of the paradigm used and sample characteristics and a second less constrained "supportive network" that involves frontal-hippocampal interactions when IF takes place. Additionally, our results support the validity of the inhibitory or thought suppression hypothesis. The presence of a neural signature of IF that is stable regardless of experimental paradigms is a promising finding that may open new venues for the development of effective clinical interventions.

Situational factors shape moral judgements in the trolley dilemma in Eastern, Southern and Western countries in a culturally diverse sample.

The study of moral judgements often centres on moral dilemmas in which options consistent with deontological perspectives (that is, emphasizing rules, individual rights and duties) are in conflict with options consistent with utilitarian judgements (that is, following the greater good based on consequences). Greene et al. (2009) showed that psychological and situational factors (for example, the intent of the agent or the presence of physical contact between the agent and the victim) can play an important role in moral dilemma judgements (for example, the trolley problem). Our knowledge is limited concerning both the universality of these effects outside the United States and the impact of culture on the situational and psychological factors affecting moral judgements. Thus, we empirically tested the universality of the effects of intent and personal force on moral dilemma judgements by replicating the experiments of Greene et al. in 45 countries from all inhabited continents. We found that personal force and its interaction with intention exert influence on moral judgements in the US and Western cultural clusters, replicating and expanding the original findings. Moreover, the personal force effect was present in all cultural clusters, suggesting it is culturally universal. The evidence for the cultural universality of the interaction effect was inconclusive in the Eastern and Southern cultural clusters (depending on exclusion criteria). We found no strong association between collectivism/individualism and moral dilemma judgements.