Psilocybin for major depressive disorder: a systematic review of randomized controlled studies.

Objectives: The purpose of this systematic review of randomized controlled trials (RCTs) was to evaluate the effectiveness, safety, and tolerability of psilocybin in adult patients with major depressive disorder (MDD). Methods: A systematic search (up to September 14, 2023) was conducted for RCTs that examined the efficacy, safety, and tolerability of psilocybin in physically healthy adult patients with MDD. Three independent researchers extracted data from publications where the primary outcome was a change in depressive symptoms, and key secondary outcomes were changes in anxiety symptoms and suicidal ideation, discontinuation rates for any reason, and adverse drug reactions (ADRs). Results: Five RCTs with 472 adult patients with MDD on psilocybin (n = 274) and controls (n = 198) were included. Two of the five RCTs (40%) reported mixed results, while the other three (60%) found that psilocybin had a beneficial effect on MDD treatment. Four RCTs (80%) assessing the anxiolytic effects of psilocybin for treating MDD found that psilocybin was significantly more effective than the control group in improving anxiety symptoms. Psilocybin was more effective than the control group in improving suicidal ideation in one out of five RCTs. Discontinuation rates were similar for any reason between the psilocybin group (2-13%) and the control group (4-21%) (P > 0.05). Four RCTs (80%) reported ADRs in detail. The most common ADR in both groups was headache. Conclusion: Psilocybin was effective in improving depressive symptoms in over half of the included studies and reduced anxiety symptoms in patients with MDD. The long-term efficacy and safety of psilocybin for MDD treatment needs to be further investigated in large RCTs.

Discovery of natural product derivative triptolidiol as a direct NLRP3 inhibitor by reducing K63-specific ubiquitination.

BACKGROUND AND PURPOSE: NLRP3 is up-regulated in inflammatory and autoimmune diseases. The development of NLRP3 inhibitors is challenged by the identification of compounds with distinct mechanisms of action avoiding side effects and toxicity. Triptolide is a natural product with multiple anti-inflammatory activities, but a narrow therapeutic window. EXPERIMENTAL APPROACH: Natural product triptolide derivatives were screened for NLRP3 inhibitors in human THP-1 and mouse bone marrow-derived macrophages. The efficacy of potent NLRP3 inhibitors was evaluated in LPS-induced acute lung injury and septic shock models. KEY RESULTS: Triptolidiol was identified as a selective inhibitor of NLRP3 with high potency. Triptolidiol inactivated the NLRP3 inflammasome in human THP-1 and mouse primary macrophages primed with LPS. Triptolidiol specifically inhibited pro-caspase 1 cleavage downstream of NLRP3, but not AIM2 or NLRC4 inflammasomes. Based on the structure-activity relationship study, the C8-ß-OH group was critical for its binding to NLRP3. Triptolidiol exhibited a submicromolar KD for NLRP3, binding to residue C280. This binding prevented the interaction of NLRP3 with NEK7, the key regulator of NLRP3 inflammasome oligomerization and assembly, but not with the inflammasome adaptor protein ASC. Triptolidiol decreased the K63-specific ubiquitination of NLRP3, leading NLRP3 to a "closed" inactive conformation. Intraperitoneal administration of triptolidiol significantly attenuated LPS-induced acute lung injury and lethal septic shock. CONCLUSION AND IMPLICATIONS: Triptolidiol is a novel NLRP3 inhibitor that regulates inflammasome assembly and activation by decreasing K63-linked ubiquitination. Triptolidiol has novel structural features that make it distinct from reported NLRP3 inhibitors and represents a viable therapeutic lead for inflammatory diseases.

Spatial phytoplankton community structure revealed by photosynthetic pigments in the tropical estuarine-coastal zone (Bangladesh).

To explore the variation of phytoplankton community along the Bakkhali river estuary and its adjacent coastal water in the north of the Bay of Bengal, total Chl-a (TChl-a) concentrations and group-specific photosynthetic pigments were investigated during April 2017. Distinct spatial distribution was observed in temperature, turbidity and nutrient concentrations as well as in TChl-a concentrations, showing a seaward decreasing pattern. The different distribution of phytoplankton pigments and functional groups along the gradients was also observed. Chlorophyll-b and zeaxanthin showed their highest abundance in the turbid riverine water, while alloxanthin and prasinoxanthin dominated in the coastal water. High concentrations of fucoxanthin, peridinin and hex-fucoxanthin were associated with high-light availability and showed a seaward increasing trend. Three phytoplankton groups can be classified: the riverine group (chlorophytes and cyanobacteria), the coastal group (cryptophytes and prasinophytes) and the offshore group (diatoms, dinoflagellate and haptophytes_type 6). The predominance of cryptophytes (avg. 48%) over diatoms (avg. 28%) was basically influenced by the scarcity of nitrogen and silicate relative to phosphate. Not only availability of nutrients, the photosynthetically active radiation also plays a key role in regulating TChl-a, photosynthetic pigments and functional groups in this tropical estuarine-coastal zone.

Deep transcranial magnetic stimulation for schizophrenia: a systematic review.

Background: The efficacy and safety of deep transcranial magnetic stimulation (dTMS) as an intervention for schizophrenia remain unclear. This systematic review examined the efficacy and safety of dTMS for schizophrenia. Methods: A systematic search of Chinese (WanFang and Chinese Journal Net) and English databases (PubMed, EMBASE, PsycINFO, and Cochrane Library) were conducted. Results: Three randomized clinical trials (RCTs) comprising 80 patients were included in the analyses. Active dTMS was comparable to the sham treatment in improving total psychopathology, positive symptoms, negative symptoms, and auditory hallucinations measured by the Positive and Negative Syndrome Scale (PANSS), the Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Auditory Hallucinations Rating Scale (AHRS), respectively. Only one RCT reported the effects on neurocognitive function measured by the Cambridge Neuropsychological Test Automated Battery (CANTAB), suggesting that dTMS may only improve one Stockings of Cambridge measure (i.e., subsequent times for five move problems). All three studies reported overall discontinuation rates, which ranged from 16.7% to 44.4%. Adverse events were reported in only one RCT, the most common being tingling/twitching (30.0%, 3/10), head/facial discomfort (30.0%, 3/10), and back pain (20.0%, 2/10). Conclusion: This systematic review suggests that dTMS does not reduce psychotic symptoms in schizophrenia, but it shows potential for improving executive functions. Future RCTs with larger sample sizes focusing on the effects of dTMS on psychotic symptoms and neurocognitive function in schizophrenia are warranted to further explore these findings.

Nitrogen-fixing and non-nitrogen-fixing legume plants differ in leaf nutrient concentrations and relationships between photosynthetic and hydraulic traits.

Legumes account for a significant proportion of plants in the terrestrial ecosystems. Nitrogen (N)-fixing capability of certain legumes is a pivotal trait that contributes to their ecological dominance. Yet, the functional traits and trait relationships between N-fixer and non-N-fixer legumes are poorly understood. Here, we investigated 27 functional traits associated with morphology, nutrients, hydraulic conductance and photosynthesis in 42 woody legumes (19 N-fixers and 23 non-N-fixers) in a common garden. Our results showed that N-fixers had higher specific leaf area, photosynthetic phosphorus (P)-use efficiency, leaf N, and iron concentrations on both area and mass basis, N/P ratio, and carbon (C) to P ratio, but lower wood density, area-based maximum photosynthetic rate (Aa), photosynthetic N-use efficiency, leaf mass- and area-based P and molybdenum and area-based boron concentrations, and C/N ratio, compared with non-N-fixers. The mass-based maximum photosynthetic rate (Am), stomatal conductance (gs), intrinsic water-use efficiency (WUEi), mass- and area-based leaf potassium and mass-based boron concentrations, leaf hydraulic conductance (Kleaf), and whole-shoot hydraulic conductance (Kshoot) showed no difference between N-fixers and non-N-fixers. Significant positive associations between all hydraulic and photosynthetic trait pairs were found in N-fixers, but only one pair (Kshoot-Aa) in non-N-fixers, suggesting that hydraulic conductance plays a more important role in mediating photosynthetic capacity in N-fixers compared with non-N-fixers. Higher mass-based leaf N was linked to lower time-integrated gs and higher WUEi among non-N-fixer legumes or all legumes pooled after phylogeny was considered. Moreover, mass-based P concentration was positively related to Am and gs in N-fixers, but not in non-N-fixers, indicating that the photosynthetic capacity and stomatal conductance in N-fixers were more dependent on leaf P status than in non-N-fixers. These findings expand our understanding of the trait-based ecology within and across N-fixer and non-N-fixer legumes in tropics.

Lightweight Low-Rank Adaptation Vision Transformer Framework for Cervical Cancer Detection and Cervix Type Classification.

Cervical cancer is a major health concern worldwide, highlighting the urgent need for better early detection methods to improve outcomes for patients. In this study, we present a novel digital pathology classification approach that combines Low-Rank Adaptation (LoRA) with the Vision Transformer (ViT) model. This method is aimed at making cervix type classification more efficient through a deep learning classifier that does not require as much data. The key innovation is the use of LoRA, which allows for the effective training of the model with smaller datasets, making the most of the ability of ViT to represent visual information. This approach performs better than traditional Convolutional Neural Network (CNN) models, including Residual Networks (ResNets), especially when it comes to performance and the ability to generalize in situations where data are limited. Through thorough experiments and analysis on various dataset sizes, we found that our more streamlined classifier is highly accurate in spotting various cervical anomalies across several cases. This work advances the development of sophisticated computer-aided diagnostic systems, facilitating more rapid and accurate detection of cervical cancer, thereby significantly enhancing patient care outcomes.

A comprehensive meta-analysis on the association of SGLT2is and GLP-1RAs with vascular diseases, digestive diseases and fractures.

AIM: Sodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide 1 receptor agonists (GLP-1RAs) are two new classes of antidiabetic agents. We aimed to evaluate the association between these two drug classes and risk of various vascular diseases, digestive diseases and fractures. METHODS: Large randomized trials of SGLT2is and GLP-1RAs were included. Outcomes of interest were the various serious adverse events related to vascular diseases, digestive diseases and fractures. We performed meta-analyses using synthesize risk ratio (RR) and 95% confidence interval (CI) as effect size. RESULTS: We included 27 large trials. SGLT2is had significant association with less hypertension (RR 0.70, 95% CI 0.54-0.91), hypertensive crisis (RR 0.63, 95% CI 0.47-0.84), varicose vein (RR 0.34, 95% CI 0.13-0.92), and vomiting (RR 0.55, 95% CI 0.31-0.97); but more spinal compression fracture (RR 1.73, 95% CI 1.02-2.92) and tibia fracture. GLP-1RAs had significant association with more deep vein thrombosis (RR 1.92, 95% CI 1.23-3.00), pancreatitis (RR 1.54, 95% CI 1.07-2.22), and cholecystitis acute (RR 1.51, 95% CI 1.08-2.09); but less rib fracture (RR 0.59, 95% CI 0.35-0.97). Sensitivity analyses suggested that our findings were robust. CONCLUSIONS: SGLT2is may have protective effects against specific vascular and digestive diseases, whereas they may increase the incidence of site-specific fractures (e.g., spinal compression fracture). GLP-1RAs may have protective effects against site-specific fractures (i.e., rib fracture), whereas they may increase the incidence of specific vascular and digestive diseases. These findings may help to make a choice between SGLT2is and GLP-1RAs in clinical practice.

Deep transcranial magnetic stimulation for treatment-resistant depression: A systematic review and meta-analysis of randomized controlled studies.

The efficacy and safety of deep transcranial magnetic stimulation (dTMS) in treating treatment-resistant depression (TRD) are unknown. Up to June 21, 2023, we conducted a systematic search for RCTs, and then extracted and synthesized data using random effects models. Five RCTs involving 507 patients with TRD (243 in the active dTMS group and 264 in the control group) were included in the present study. The active dTMS group showed significantly higher study-defined response rate (45.3% versus 24.2%, n = 507, risk ratio [RR] = 1.87, 95% confidence interval [CI]: 1.21-2.91, I2 = 53%; P = 0.005) and study-defined remission rate (38.3% versus 14.4%, n = 507, RR = 2.37, 95%CI: 1.30-4.32, I2 = 58%; P = 0.005) and superiority in improving depressive symptoms (n = 507, standardized mean difference = -0.65, 95%CI: -1.11--0.18, I2 = 82%; P = 0.006) than the control group. In terms of cognitive functions, no significant differences were observed between the two groups. The two groups also showed similar rates of other adverse events and all-cause discontinuations (P > 0.05). dTMS is an effective and safe treatment strategy for the management of patients with TRD.

Applications of machine learning in phylogenetics.

Machine learning has increasingly been applied to a wide range of questions in phylogenetic inference. Supervised machine learning approaches that rely on simulated training data have been used to infer tree topologies and branch lengths, to select substitution models, and to perform downstream inferences of introgression and diversification. Here, we review how researchers have used several promising machine learning approaches to make phylogenetic inferences. Despite the promise of these methods, several barriers prevent supervised machine learning from reaching its full potential in phylogenetics. We discuss these barriers and potential paths forward. In the future, we expect that the application of careful network designs and data encodings will allow supervised machine learning to accommodate the complex processes that continue to confound traditional phylogenetic methods.

The value of ultrasound parameters in predicting the efficacy of transabdominal ultrasound-guided suction curettage alone in the treatment of cesarean scar pregnancy.

OBJECTIVE: To investigate the value of ultrasound parameters in assessing the efficacy of transabdominal ultrasound (TAUS)-guided suction curettage alone for cesarean scar pregnancy (CSP). METHODS: Secondary retrospective analysis of a prospective study consisted of 137 women diagnosed with CSP who were performed TAUS-guided suction curettage alone for the first time at Maternity and Child Health Care of Guangxi Zhuang Autonomous Region in China. Prior to surgery, an ultrasound examination was conducted. Based on the need for secondary intervention, the patients were categorized into failure group and success group, and the predictive factors for failure of TAUS-guided suction curettage alone were analyzed. RESULTS: Multivariate logistic regression showed that maximum diameter of the gestational sac>29 mm (odds ratio [OR] = 4.043, 95% CI: 1.100-14.862), residual myometrium thickness ≤1.8 mm (OR = 3.719, 95% CI: 1.148-12.048) and chorionic villi thickness at the scar >4.7 mm (OR = 15.327, 95% CI: 4.617-50.881) were independent predictors of failure in TAUS-guided suction curettage alone for CSP. Furthermore, the logistic regression model that was jointly constructed by these three predictors demonstrated an area under the curve, sensitivity, specificity, and Youden index of 0.913, 0.912, 0.864, and 0.776, respectively. CONCLUSION: The maximum diameter of the gestational sac, residual myometrium thickness, and chorionic villi thickness at the scar has certain predictive efficacy of TAUS-guided suction curettage alone for CSP. Nevertheless, it is more valuable to apply the model of this study, composed of the three ultrasound parameters, for this prediction purpose.

Safety and efficacy of sequential treatments for postmenopausal osteoporosis: a network meta-analysis of randomised controlled trials.

Background: The sequential anti-osteoporotic treatment for women with postmenopausal osteoporosis (PMO) is important, but the order in which different types of drugs are used is confusing and controversial. Therefore, we performed a network meta-analysis to compare the efficacy and safety of available sequential treatments to explore the most efficacious strategy for long-term management of osteoporosis. Methods: In this network meta-analysis, we searched the PubMed, EMBASE, Web of Science, the Cochrane Library, and ClinicalTrials.gov from inception to September 19, 2023 to identify randomised controlled trials comparing sequential treatments for women with PMO. The identified trials were screened by reading the title and abstract, and only randomised clinical trials involving sequential anti-osteoporotic treatments and reported relevant outcomes for PMO were included. The main outcomes included vertebral fracture risk, the percentage change in bone mineral density (BMD) in different body parts, and all safety indicators in the stage after switching treatment. A frequentist network meta-analysis was performed using the multivariate random effects method and evaluated using the surface under the cumulative ranking curve (SUCRA). Certainty of evidence was assessed using the Confidence in the Network Meta-Analysis (CINeMA) framework. This study is registered with PROSPERO: CRD42022360236. Findings: A total of 19 trials comprising 18,416 participants were included in the study. Five different sequential treatments were investigated as the main interventions and compared to the corresponding control groups. The intervention groups in this study comprised the following treatment switch protocols: switching from an anabolic agent (AB) to an anti-resorptive agent (AR) (ABtAR), transitioning from one AR to another AR (ARtAAR), shifting from an AR to an AB (ARtAB), switching from an AB to a combined treatment of AB and AR (ABtC), and transitioning from an AR to a combined treatment (ARtC). A significant reduction in the incidence of vertebral fractures was observed in ARtC, ABtAR and ARtAB in the second stage, and ARtC had the lowest incidence with 81.5% SUCRA. ARtAAR and ABtAR were two effective strategies for preventing fractures and improving BMD in other body parts. Especially, ARtAAR could improve total hip BMD with the highest 96.1% SUCRA, and ABtAR could decrease the risk of total fractures with the highest 94.3% SUCRA. Almost no difference was observed in safety outcomes in other comparisons. Interpretation: Our findings suggested that the ARtAAR and ABtAR strategy are the effective and safe sequential treatment for preventing fracture and improving BMD for PMO. ARtC is more effective in preventing vertebral fractures. Funding: The National Natural Science Foundation of China (82170900, 81970762), the Hunan Administration of Traditional Chinese Medicine, and the Hunan Province High-level Health Talents "225" Project.

Intraspecific plasticity and co-variation of leaf traits facilitate Ficus tinctoria to acclimate hemiepiphytic and terrestrial habitats.

Despite intensive studies on plant functional traits, the intraspecific variation and their co-variation at the multi-scale remains poorly studied, which holds the potential to unveil plant responses to changing environmental conditions. In this study, intraspecific variations of 16 leaf functional traits of a common fig species, Ficus tinctoria G. Frost., were investigated in relation to different scales: habitat types (hemiepiphytic and terrestrial), growth stages (small, medium and large) and tree crown positions (upper, middle and lower) in Xishuangbanna, Southwest China. Remarkable intraspecific variation was observed in leaf functional traits, which was mainly influenced by tree crown position, growth stage and their interaction. Stable nitrogen isotope (δ15N) and leaf area (LA) showed large variations, while stable carbon isotope (δ13C), stomata width and leaf water content showed relatively small variations, suggesting that light- and nitrogen-use strategies of F. tinctoria were plastic, while the water-use strategies have relatively low plasticity. The crown layers are formed with the growth of figs, and leaves in the lower crown increase their chlorophyll concentration and LA to improve the light energy conversion efficiency and the ability to capture weak light. Meanwhile, leaves in the upper crown increase the water-use efficiency to maintain their carbon assimilation. Moreover, hemiepiphytic medium (transitional stage) and large (free-standing stage) figs exhibited more significant trait differentiation (chlorophyll concentration, δ13C, stomata density, etc.) within the crown positions, and stronger trait co-variation compared with their terrestrial counterparts. This pattern demonstrates their acclimation to the changing microhabitats formed by their hemiepiphytic life history. Our study emphasizes the importance of multi-scaled intraspecific variation and co-variation in trait-based strategies of hemiepiphyte and terrestrial F. tinctoria, which facilitate them to cope with different environmental conditions.

LDLR is an entry receptor for Crimean-Congo hemorrhagic fever virus.

Crimean-Congo hemorrhagic fever virus (CCHFV) is the most widespread tick-born zoonotic bunyavirus that causes severe hemorrhagic fever and death in humans. CCHFV enters the cell via clathrin-mediated endocytosis which is dependent on its surface glycoproteins. However, the cellular receptors that are required for CCHFV entry are unknown. Here we show that the low density lipoprotein receptor (LDLR) is an entry receptor for CCHFV. Genetic knockout of LDLR impairs viral infection in various CCHFV-susceptible human, monkey and mouse cells, which is restored upon reconstitution with ectopically-expressed LDLR. Mutagenesis studies indicate that the ligand binding domain (LBD) of LDLR is necessary for CCHFV infection. LDLR binds directly to CCHFV glycoprotein Gc with high affinity, which supports virus attachment and internalization into host cells. Consistently, a soluble sLDLR-Fc fusion protein or anti-LDLR blocking antibodies impair CCHFV infection into various susceptible cells. Furthermore, genetic knockout of LDLR or administration of an LDLR blocking antibody significantly reduces viral loads, pathological effects and death following CCHFV infection in mice. Our findings suggest that LDLR is an entry receptor for CCHFV and pharmacological targeting of LDLR may provide a strategy to prevent and treat Crimean-Congo hemorrhagic fever.

Antiviral activity of chrysin and naringenin against porcine epidemic diarrhea virus infection.

Porcine epidemic diarrhea virus (PEDV) is one of the critical pathogens causing diarrhea in piglets and has caused huge economic losses to the swine industry in worldwide. However, there is currently no effective therapeutic medication available for the treatment of PEDV. Natural compounds are a hot topic for researching and screening antiviral lead compounds due to their abundant sources, varied activities, and low toxicity. In this study, a total of 6 compounds from different plant sources were selected for in vitro anti-PEDV screening, including chrysin, naringenin, soy isoflavone, glycyrrhetinic acid, oleanolic acid, and geniposide. Then two active compounds, chrysin and naringenin, were further evaluated on PEDV infected cells at different stage. And the anti-PEDV mechanism was analyzed by molecule docking and molecular dynamics. The results showed that both chrysin and naringenin showed the most significant anti-PEDV activity by increasing the cell viability and decreasing the virus copy number. Both natural compounds could inhibit viral titer, mRNA and protein levels in the prophylactic and post-viral entry stages of PEDV infection. Furthermore, chrysin and naringenin mainly interacted with viral replicase proteins such as 3CLpro and PLP-2 through hydrogen bonds and hydrophobic forces. The complexes formed by chrysin and naringenin with the two PEDV replication proteases had high stability. These results suggested that chrysin and naringenin may exert antiviral effects by interacting with the virus 3CLpro protein or PLP2 protein, thereby affecting their role in the formation of PEDV non-structural proteins or interfering with virus replication. This study lays the foundation for developing chrysin and naringenin as novel anti-PEDV therapeutic drugs.

XMR: an explainable multimodal neural network for drug response prediction.

Introduction: Existing large-scale preclinical cancer drug response databases provide us with a great opportunity to identify and predict potentially effective drugs to combat cancers. Deep learning models built on these databases have been developed and applied to tackle the cancer drug-response prediction task. Their prediction has been demonstrated to significantly outperform traditional machine learning methods. However, due to the "black box" characteristic, biologically faithful explanations are hardly derived from these deep learning models. Interpretable deep learning models that rely on visible neural networks (VNNs) have been proposed to provide biological justification for the predicted outcomes. However, their performance does not meet the expectation to be applied in clinical practice. Methods: In this paper, we develop an XMR model, an eXplainable Multimodal neural network for drug Response prediction. XMR is a new compact multimodal neural network consisting of two sub-networks: a visible neural network for learning genomic features and a graph neural network (GNN) for learning drugs' structural features. Both sub-networks are integrated into a multimodal fusion layer to model the drug response for the given gene mutations and the drug's molecular structures. Furthermore, a pruning approach is applied to provide better interpretations of the XMR model. We use five pathway hierarchies (cell cycle, DNA repair, diseases, signal transduction, and metabolism), which are obtained from the Reactome Pathway Database, as the architecture of VNN for our XMR model to predict drug responses of triple negative breast cancer. Results: We find that our model outperforms other state-of-the-art interpretable deep learning models in terms of predictive performance. In addition, our model can provide biological insights into explaining drug responses for triple-negative breast cancer. Discussion: Overall, combining both VNN and GNN in a multimodal fusion layer, XMR captures key genomic and molecular features and offers reasonable interpretability in biology, thereby better predicting drug responses in cancer patients. Our model would also benefit personalized cancer therapy in the future.

Tubson-2 decoction ameliorates rheumatoid arthritis complicated with osteoporosis in CIA rats involving isochlorogenic acid A regulating IL-17/MAPK pathway.

BACKGROUND: Osteoporosis (OP) is considered as one of the major comorbidities of rheumatoid arthritis (RA), and is responsible for fragility fracture. However, there is currently no effective treatment for RA complicated with OP. Tubson-2 decoction (TBD), a Mongolian medicine also known as Erwei Duzhong Decoction, has been shown to exert a preventive effect on post-menopausal osteoporosis (PMOP). The preventive effects of TBD on RA-induced OP, as well as the bioactive compound responsible and the underlying mechanisms, remain to be elucidated. OBJECTIVE: To explore the effects of TBD on RA-induced OP in vivo, and to elucidate the mechanism of isochlorogenic acid A (ICA), the effective component of TBD, in vitro. METHODS: To evaluate the anti-arthritic and anti-osteoporotic effects of TBD, we conducted H&E straining and safranine O/fast green, TEM, immunohistochemistry (IHC), bone histomorphometry, micro-CT imaging, and biomechanical testing in collagen induced arthritis (CIA) rats. The active ingredient in TBD was identified using network pharmacology and molecular docking. The identification was supported by in vivo IHC assay, and further confirmed using qRT-PCR, Western blot, and SEM analysis in TNF-α-treated MH7A cells and/or in LPS-exposed RAW264.7 cells. RESULTS: Oral administration of TBD attenuated the severity of arthritis and osteopenia as well as poor bone quality, in CIA rats. Additionally, TBD and the positive control, tripterygium glycosides (TG), exhibited similar effects in reducing inflammation in both the synovium and ankle joint. They also were both effective in improving bone loss, microarchitecture, and overall bone quality. TBD reduced the expression of MMP13, IL-17, and p-JNK protein in the synovium of CIA rats. ICA, which was screened, suppressed TNF-α or LPS-triggered inflammatory responses via down-regulating IL-17 signaling, involving in MMP13, IL-1ß, IL-23, and IL-17, and the MAPK pathway including p-ERK, p-JNK, and p-P38, both in MH7A cells and in RAW264.7 cells. Furthermore, ICA prevented osteoclasts from differentiating and bone resoprtion in a dose-dependent manner in vitro. CONCLUSION: This study provides the first evidence that TBD exerts intervening effects on RA-induced OP, possibly through the downregulation of the IL-17/MAPK signaling pathway by ICA. The findings of our study provides valuable insights for further research in this area.

Celastrol attenuates hepatitis C virus translation and inflammatory response in mice by suppressing heat shock protein 90ß.

Hepatitis C virus (HCV) infection is one of the major factors to trigger a sustained hepatic inflammatory response and hence hepatocellular carcinoma (HCC), but direct-acting-antiviral (DAAs) was not efficient to suppress HCC development. Heat shock protein 90 kDa (HSP90) is highly abundant in different types of cancers, and especially controls protein translation, endoplasmic reticulum stress, and viral replication. In this study we investigated the correlation between the expression levels of HSP90 isoforms and inflammatory response marker NLRP3 in different types of HCC patients as well as the effect of a natural product celastrol in suppression of HCV translation and associated inflammatory response in vivo. We identified that the expression level of HSP90ß isoform was correlated with that of NLRP3 in the liver tissues of HCV positive HCC patients (R2 = 0.3867, P < 0.0101), but not in hepatitis B virus-associated HCC or cirrhosis patients. We demonstrated that celastrol (3, 10, 30 µM) dose-dependently suppressed the ATPase activity of both HSP90α and HSP90ß, while its anti-HCV activity was dependent on the Ala47 residue in the ATPase pocket of HSP90ß. Celastrol (200 nM) halted HCV internal ribosomal entry site (IRES)-mediated translation at the initial step by disrupting the association between HSP90ß and 4EBP1. The inhibitory activity of celastrol on HCV RNA-dependent RNA polymerase (RdRp)-triggered inflammatory response also depended on the Ala47 residue of HSP90ß. Intravenous injection of adenovirus expressing HCV NS5B (pAde-NS5B) in mice induced severe hepatic inflammatory response characterized by significantly increased infiltration of immune cells and hepatic expression level of Nlrp3, which was dose-dependently ameliorated by pretreatment with celastrol (0.2, 0.5 mg/kg, i.p.). This study reveals a fundamental role of HSP90ß in governing HCV IRES-mediated translation as well as hepatic inflammation, and celastrol as a novel inhibitor of HCV translation and associated inflammation by specifically targeting HSP90ß, which could be developed as a lead for the treatment of HSP90ß positive HCV-associated HCC.

Updated site concordance factors minimize effects of homoplasy and taxon sampling.

MOTIVATION: Site concordance factors (sCFs) have become a widely used way to summarize discordance in phylogenomic datasets. However, the original version of sCFs was calculated by sampling a quartet of tip taxa and then applying parsimony-based criteria for discordance. This approach has the potential to be strongly affected by multiple hits at a site (homoplasy), especially when substitution rates are high or taxa are not closely related. RESULTS: Here, we introduce a new method for calculating sCFs. The updated version uses likelihood to generate probability distributions of ancestral states at internal nodes of the phylogeny. By sampling from the states at internal nodes adjacent to a given branch, this approach substantially reduces-but does not abolish-the effects of homoplasy and taxon sampling. AVAILABILITY AND IMPLEMENTATION: Updated sCFs are implemented in IQ-TREE 2.2.2. The software is freely available at https://github.com/iqtree/iqtree2/releases. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Transcranial alternating current stimulation for schizophrenia: a systematic review of randomized controlled studies.

Background: In randomized clinical trials (RCTs) investigating the application of transcranial alternating current stimulation (tACS) in schizophrenia, inconsistent results have been reported. The purpose of this exploratory systematic review of RCTs was to evaluate tACS as an adjunct treatment for patients with schizophrenia based on its therapeutic effects, tolerability, and safety. Methods: Our analysis included RCTs that evaluated adjunctive tACS' effectiveness, tolerability, and safety in schizophrenia patients. Three independent authors extracted data and synthesized it using RevMan 5.3 software. Results: Three RCTs involving 76 patients with schizophrenia were encompassed in the analysis, with 40 participants receiving active tACS and 36 receiving sham tACS. Our study revealed a significant superiority of active tACS over sham tACS in improving total psychopathology (standardized mean difference [SMD] = -0.61, 95% confidence interval [CI]: -1.12, -0.10; I2 = 16%, p = 0.02) and negative psychopathology (SMD = -0.65, 95% CI: -1.11, -0.18; I2 = 0%, p = 0.007) in schizophrenia. The two groups, however, showed no significant differences in positive psychopathology, general psychopathology, or auditory hallucinations (all p > 0.05). Two RCTs examined the neurocognitive effects of tACS, yielding varied findings. Both groups demonstrated similar rates of discontinuation due to any reason and adverse events (all p > 0.05). Conclusion: Adjunctive tACS is promising as a viable approach for mitigating total and negative psychopathology in individuals diagnosed with schizophrenia. However, to gain a more comprehensive understanding of tACS's therapeutic effects in schizophrenia, it is imperative to conduct extensive, meticulously planned, and well-documented RCTs.

[Spatial and temporal variation in normalized difference vegetation index of vegetation in Liaoning Province from the perspective of ecogeographic zoning]. / 生态地理分区视角下的辽宁省植被归一化植被指数的时空变化.

Normalized difference vegetation index (NDVI) is an important indicator reflecting vegetation cover and growth status. It is of significance for regional ecological conservation and natural resource management to investigate its spatial and temporal variation trends and response to ecological factors. We divided Liaoning Province into three ecological geographical regions, including northwest agro-pastoral zone, central agricultural zone, and eastern agroforestry zone. Based on remote sensing, vegetation, climate, topography and human activities, we used trend analysis and geographic probe model to examine the spatial and temporal trends of NDVI in Liaoning Province, and analyzed the intensity and interaction mechanism of each driver on the spatial distribution pattern of NDVI. The results showed that the annual average NDVI in Liaoning Province from 2001 to 2020 was 0-0.92, showing a distribution pattern of high in the east and low in the west, high in the inland and low in the coastal land. The overall trend of vegetation cover was increasing, and the NDVI increasing areas were mainly concentrated in the northwest agro-pastoral zone and the eastern agroforestry zone, the NDVI reduction areas were mainly concentrated at the border between the central agricultural zone and the eastern agroforestry zone, as well as in the coastal area of the eastern agroforestry zone. The annual average NDVI change varied among the three ecological-geographic zones. The NDVI of the northwest agro-pastoral zone from 2001 to 2020 were generally low, but showed a fluctuating trend of slow increase. The NDVI of the eastern agroforestry zone was high overall, and the interannual variation of NDVI was generally stable. The distribution of high and low NDVI in the central agricultural zone was staggered, and the interannual variation of NDVI showed a decreasing trend. Natural factors were the key drivers of NDVI changes in the three ecogeographic zones, with cumulative temperature and precipitation having the greatest influence. The interactions between the factors were all mutually and nonlinearly enhanced.