DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction.

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes. However, different calculation methods result in distinct similarity matrices, and message passing in graph neural networks (GNNs) induces phenomena of over-smoothing and over-squashing, thereby impacting the performance of the model. To address these issues, we proposed a novel graph representation learning model, dual-modal graph learning for microbe-drug association prediction (DMGL-MDA). It comprises a dual-modal embedding module, a bipartite graph network embedding module, and a predictor module. To assess the performance of DMGL-MDA, we compared it against state-of-the-art methods using two benchmark datasets. Through cross-validation, we illustrated the superiority of DMGL-MDA. Furthermore, we conducted ablation experiments and case studies to validate the effective performance of the model.

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning.

MOTIVATION: Metabolic stability plays a crucial role in the early stages of drug discovery and development. Accurately modeling and predicting molecular metabolic stability has great potential for the efficient screening of drug candidates as well as the optimization of lead compounds. Considering wet-lab experiment is time-consuming, laborious, and expensive, in silico prediction of metabolic stability is an alternative choice. However, few computational methods have been developed to address this task. In addition, it remains a significant challenge to explain key functional groups determining metabolic stability. RESULTS: To address these issues, we develop a novel cross-modality graph contrastive learning model named CMMS-GCL for predicting the metabolic stability of drug candidates. In our framework, we design deep learning methods to extract features for molecules from two modality data, i.e. SMILES sequence and molecule graph. In particular, for the sequence data, we design a multihead attention BiGRU-based encoder to preserve the context of symbols to learn sequence representations of molecules. For the graph data, we propose a graph contrastive learning-based encoder to learn structure representations by effectively capturing the consistencies between local and global structures. We further exploit fully connected neural networks to combine the sequence and structure representations for model training. Extensive experimental results on two datasets demonstrate that our CMMS-GCL consistently outperforms seven state-of-the-art methods. Furthermore, a collection of case studies on sequence data and statistical analyses of the graph structure module strengthens the validation of the interpretability of crucial functional groups recognized by CMMS-GCL. Overall, CMMS-GCL can serve as an effective and interpretable tool for predicting metabolic stability, identifying critical functional groups, and thus facilitating the drug discovery process and lead compound optimization. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/CMMS-GCL.

Associations of Diet and Lifestyle with Mortality and Stroke: The China Cardiometabolic Disease and Cancer Cohort (4C) Study.

OBJECTIVE: This study aimed to examine the individual and combined associations between dietary habits and lifestyle factors concerning all-cause mortality and stroke in Chinese adults. METHOD: We conducted a nationwide, multicenter, prospective cohort study involving 10,008 participants, gathering baseline data on lifestyle, metabolic status, dietary habits, and living behaviors. Subsequently, a 10-year follow-up was performed, resulting in the inclusion of 7,612 participants in this study. We employed Spearman correlation analysis, restricted cubic spline regression, and Cox regression analysis to evaluate the connections between outcome events, dietary habits, and lifestyle. RESULT: For each additional serving of pulses consumed per week, there was a slight decrease in the risk of all-cause mortality (HR: 0.91, 95% CI: 0.83-0.99). The hazard ratios for stroke were 2.24 (1.48, 3.37) for current smokers, in comparison to individuals who had never smoked. Appropriate intake of specific dietary factors and certain lifestyle habits were associated with reduced stroke: fruit drinks at 0.51 (0.34, 0.87), and animal viscera at 0.58 (0.32, 1.04). Weekly consumption of at least 21 servings of vegetables (0.72, 0.53-0.98), 0-1 serving of fried food (0.58, 0.38-0.90), and at least 1 serving of carbonated beverages (0.51, 0.28-0.92) was associated with a reduced risk of stroke. CONCLUSION: Smoking was found to be linked to an increased risk of stroke. A higher intake of fruit drinks and animal viscera was associated with a reduced risk of stroke. In contrast, a higher intake of beans was associated with a decreased risk of overall mortality. Consuming an appropriate amount of vegetables, fried foods, and carbonated drinks was found to potentially lower the risk of stroke. Collectively, these findings underscore the importance of developing tailored dietary interventions conducive to the Chinese populace's health.

The causal relationship between plasma protein-to-protein ratios and type 2 diabetes and its complications: Proteomics mendelian randomization study.

AIM: In recent years, proteomics research has surged, with numerous observational studies identifying associations between plasma proteins and type 2 diabetes. However, research specifically focusing on the ratios of plasma proteins in type 2 diabetes remains relatively scarce. METHODS: This study primarily employed a two-sample, two-step Mendelian randomization (MR) approach, leveraging genetic data from several large, publicly accessible genome-wide association studies, wherein single nucleotide polymorphisms served as proxies for exposures and diseases. Within this framework, we applied two-sample MR to assess the associations between the 2821 plasma protein-to-protein ratios and type 2 diabetes along with its complications and utilized reverse MR to confirm the unidirectionality of these causal relationships. In addition, we employed two-step MR to investigate the potential mediating role of body mass index in these associations. To augment the robustness of our findings, we systematically implemented a series of sensitivity analyses. RESULTS: The results gleaned from the inverse-variance weighted method elucidated that a cumulative sum of 23 protein-to-protein ratios bore a causal nexus with type 2 diabetes across both sample cohorts. With each incremental elevation of 1 standard deviation in the genetically anticipated protein-to-protein ratio, the susceptibility to type 2 diabetes oscillated from 0.93 (95% confidence interval: 0.87, 1.00) for the CNTN3/NCSS1 protein level ratio to 1.13 (1.06, 1.22) for the DBNL/NCK2 protein level ratio. Moreover, a tally of eight protein-to-protein ratios correlated with a minimum of one complication linked to type 2 diabetes. Diverse sensitivity analyses corroborated the robustness of these observations. CONCLUSIONS: The outcomes of our investigation unveiled correlations between 23 plasma protein-to-protein ratios and type 2 diabetes, with eight of these ratios entwined with complications of type 2 diabetes. These discoveries offer novel perspectives on the diagnosis and management of type 2 diabetes and its associated complications.

MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction.

MOTIVATION: During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways for drug-like compounds. However, they neglect the knowledge that metabolic pathways are dependent on each other. Moreover, they are inadequate to elucidate why compounds participate in specific pathways. RESULTS: To address these issues, we propose a novel Multi-Label Graph Learning framework of Metabolic Pathway prediction boosted by pathway interdependence, called MLGL-MP, which contains a compound encoder, a pathway encoder and a multi-label predictor. The compound encoder learns compound embedding representations by graph neural networks. After constructing a pathway dependence graph by re-trained word embeddings and pathway co-occurrences, the pathway encoder learns pathway embeddings by graph convolutional networks. Moreover, after adapting the compound embedding space into the pathway embedding space, the multi-label predictor measures the proximity of two spaces to discriminate which pathways a compound participates in. The comparison with state-of-the-art methods on KEGG pathways demonstrates the superiority of our MLGL-MP. Also, the ablation studies reveal how its three components contribute to the model, including the pathway dependence, the adapter between compound embeddings and pathway embeddings, as well as the pre-training strategy. Furthermore, a case study illustrates the interpretability of MLGL-MP by indicating crucial substructures in a compound, which are significantly associated with the attending metabolic pathways. It is anticipated that this work can boost metabolic pathway predictions in drug discovery. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/MLGL-MP.

The value of a dual-energy CT Iodine map radiomics model for the prediction of collagen fiber content in the ccRCC tumor microenvironment.

BACKGROUND AND PURPOSE: Renal cell carcinoma (RCC) is a heterogeneous group of cancers. The collagen fiber content in the tumor microenvironment of renal cancer has an important role in tumor progression and prognosis. A radiomics model was developed from dual-energy CT iodine maps to assess collagen fiber content in the tumor microenvironment of ccRCC. METHODS: A total of 87 patients with ccRCC admitted to our hospital were included in this retrospective study. Among them, 59 cases contained large amounts of collagen fibers and 28 cases contained a small amount of collagen fibers. We established a radiomics model using preoperative dual-energy CT scan Iodine map (IV) imaging to distinguish patients with multiple collagen fibers from those with few collagen fibers in the tumor microenvironment of ccRCC. We extracted features from dual-energy CT Iodine map images to evaluate the effects of six classifiers, namely k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), logistic regression (LR), and decision tree (DT). The effects of the models built based on the dynamic and venous phases are also compared. Model performance was evaluated using quintuple cross-validation and area under the receiver operating characteristic curve (AUC). In addition, a clinical model was developed to assess the clinical factors affecting collagen fiber content. RESULTS: Compared to KNN, SVM, and LR classifiers, RF, DT, and XGBoost classifiers trained with higher AUC values, with training sets of 0.997, 1.0, and 1.0, respectively. In the validation set, the highest AUC was found in the SVM classifier with a size of 0.722. In the comparative test of the active and intravenous phase models, the SVM classifier had the best effect with its validation set AUC of 0.698 and 0.741. In addition, there was a statistically significant effect of patient age and maximum tumor diameter on the collagen fiber content in the tumor microenvironment of kidney cancer. CONCLUSION: Radionics features based on preoperative dual-energy CT IV can be used to predict the amount of collagen fibers in the tumor microenvironment of renal cancer. This study better informs clinical prognosis and patient management. Iodograms may add additional value to dual-energy CTs.

Association between Peripartum Mean Arterial Pressure and Postpartum Readmission for Preeclampsia with Severe Features.

OBJECTIVE: This study aimed to evaluate the relationship between peripartum mean arterial pressure (MAP) and postpartum readmission for preeclampsia with severe features. STUDY DESIGN: This is a retrospective case-control study comparing adult parturients readmitted for preeclampsia with severe features to matched nonreadmitted controls. Our primary objective was to evaluate the association between MAP at three time points during the index hospitalization (admission, 24-hour postpartum, and discharge) and readmission risk. We also evaluated readmission risk by age, race, body mass index, and comorbidities. Our secondary aim was to establish MAP thresholds to identify the population at highest risk of readmission. Multivariate logistic regression and chi-squared tests were used to determine the adjusted odds of readmission based on MAP. Receiver operating characteristic analyses were performed to evaluate risk of readmission relative to MAP; optimal MAP thresholds were established to identify those at highest risk of readmission. Pairwise comparisons were made between subgroups after stratifying for history of hypertension, with a focus on readmitted patients with new-onset postpartum preeclampsia. RESULTS: A total of 348 subjects met inclusion criteria, including 174 controls and 174 cases. We found that elevated MAP at both admission (adjusted odds ratio [OR]: 1.37 per 10 mm Hg, p < 0.0001) and 24-hour postpartum (adjusted OR: 1.61 per 10 mm Hg, p = 0.0018) were associated with increased risk of readmission. African American race and hypertensive disorder of pregnancy were independently associated with increased risk of readmission. Subjects with MAP > 99.5 mm Hg at admission or >91.5 mm Hg at 24-hour postpartum had a risk of at least 46% of requiring postpartum readmission for preeclampsia with severe features. CONCLUSION: Admission and 24-hour postpartum MAP correlate with risk of postpartum readmission for preeclampsia with severe features. Evaluating MAP at these time points may be useful for identifying women at higher risk for postpartum readmission. These women may otherwise be missed based on standard clinical approaches and may benefit from heightened surveillance. KEY POINTS: · Existing literature focuses on management of antenatal hypertensive disorders of pregnancy.. · Elevated peripartum MAP is associated with increased odds of readmission for preeclampsia.. · Peripartum MAP may predict readmission risk for de novo postpartum preeclampsia..

Whole genome sequencing and comparative genomic analysis of oleaginous red yeast Sporobolomyces pararoseus NGR identifies candidate genes for biotechnological potential and ballistospores-shooting.

BACKGROUND: Sporobolomyces pararoseus is regarded as an oleaginous red yeast, which synthesizes numerous valuable compounds with wide industrial usages. This species hold biotechnological interests in biodiesel, food and cosmetics industries. Moreover, the ballistospores-shooting promotes the colonizing of S. pararoseus in most terrestrial and marine ecosystems. However, very little is known about the basic genomic features of S. pararoseus. To assess the biotechnological potential and ballistospores-shooting mechanism of S. pararoseus on genome-scale, the whole genome sequencing was performed by next-generation sequencing technology. RESULTS: Here, we used Illumina Hiseq platform to firstly assemble S. pararoseus genome into 20.9 Mb containing 54 scaffolds and 5963 predicted genes with a N50 length of 2,038,020 bp and GC content of 47.59%. Genome completeness (BUSCO alignment: 95.4%) and RNA-seq analysis (expressed genes: 98.68%) indicated the high-quality features of the current genome. Through the annotation information of the genome, we screened many key genes involved in carotenoids, lipids, carbohydrate metabolism and signal transduction pathways. A phylogenetic assessment suggested that the evolutionary trajectory of the order Sporidiobolales species was evolved from genus Sporobolomyces to Rhodotorula through the mediator Rhodosporidiobolus. Compared to the lacking ballistospores Rhodotorula toruloides and Saccharomyces cerevisiae, we found genes enriched for spore germination and sugar metabolism. These genes might be responsible for the ballistospores-shooting in S. pararoseus NGR. CONCLUSION: These results greatly advance our understanding of S. pararoseus NGR in biotechnological potential and ballistospores-shooting, which help further research of genetic manipulation, metabolic engineering as well as its evolutionary direction.

Copper-catalyzed boroacylation of allenes to access tetrasubstituted vinylboronates.

A distinct copper-catalyzed boroacylation of allenes with acyl chlorides and bis(pinacolato)diboron is developed. For aromatic acyl chlorides, 1,2-boroacylation of allenes readily takes place, leading to the formation of tetrasubstituted vinylboronates with exclusive (E)-stereoselectivity. In comparison, the employment of alkyl acyl chlorides as electrophiles alters the selectivity to 2,3-boroacylated products. Additionally, the product can easily undergo Suzuki-Miyaura cross-coupling to afford tetrasubstituted alkene with complete retention of the configuration.

The benefits of expressive writing among newly diagnosed mainland Chinese breast cancer patients.

The study aimed to evaluate the effects of an expressive writing intervention on quality of life (QoL) among mainland Chinese breast cancer patients. A total of 118 Chinese breast cancer patients were randomly assigned to one of four groups: a cancer-facts writing condition (CTL group), an emotional disclosure writing condition (EMO group), a self-regulation writing condition (SR group), or a neutral control condition with no writing tasks (CON group). QoL was assessed by FACT-B at baseline, 3-, and 6-month follow-ups. A repeated measure analysis of variance revealed significant effects of time (F = 13.9, P < 0.001, η2 = 0.20) and the time × group interaction (F = 3.5, P < 0.01, η2 = 0.08) on QoL. Residualized change models showed that the CTL, EMO and SR groups reported higher levels of QoL than the CON group at the 6-month follow-up. The EMO group had a higher level of QoL than the SR group. The CTL group had higher level of physical well-being compared to the SR group. Mainland Chinese breast cancer patients shortly after diagnosis benefit from expressive writing. They benefited more from cancer-facts and emotional disclosure compared to self-regulation. The study indicated that the impact of expressive writing may differ due to stage of cancer survivorship, social, and cultural context.

Plasminogen activator, tissue type regulates germinal vesicle breakdown and cumulus expansion of bovine cumulus-oocyte complex in vitro†.

Plasminogen activator, tissue type (PLAT) and its inhibitor serpin family E member 1 (SERPINE1) cooperatively regulate PLAT activity in various reproductive processes. However, it is unknown whether this includes bovine oocyte maturation. We addressed this question in the present study by evaluating PLAT and SERPINE1 protein localization in immature cumulus-oocyte complexes (COCs), as well as PLAT mRNA and protein expression in cultured COCs after 0, 8, 16, and 24 h of in vitro maturation (IVM). We also examined the effects of PLAT and SERPINE1 on germinal vesicle breakdown (GVBD) and oocyte cyclic 3' 5' adenosine monophosphate (cAMP) levels, cumulus expansion index, and expansion-related gene expression in oocytes derived from bovine COCs cultured for 4, 8, and 12 h and in COCs cultured for 16 h. Both PLAT and SERPINE1 localized in cumulus cells but only the latter was detected in oocytes. PLAT and SERPINE1 transcript levels increased during IVM; however, from 8 to 16 h, the levels of PLAT remained stable whereas those of SERPINE1 increased, resulting in a decline in PLAT concentration. Additionally, PLAT delayed GVBD, increased oocyte cAMP levels, and blocked cumulus expansion and associated gene expression, which was reversed by SERPINE1 supplemented. Thus, PLAT delays bovine oocyte GVBD by enhancing oocyte cAMP levels during the first 8 h of IVM; suppression of PLAT activity via accumulation of SERPINE1 in COCs results in cumulus expansion from 8 to 16 h of IVM. These findings provide novel insights into the molecular mechanisms underlying in vitro bovine oocyte maturation.

Elevated GlycA in severe obesity is normalized by bariatric surgery.

Chronic inflammation drives many obesity-associated conditions including atherosclerosis. GlycA, a marker of systemic inflammation with lower intra-individual variability than high sensitivity C-reactive protein, is independently associated with incident cardiovascular events and mortality. Although GlycA is elevated in obesity, correlations with anthropometric measures are modest and the effect of body weight loss on GlycA is untested. Obese (body mass index [BMI] 44.6 ± 6.6 kg/m2 ), non-diabetic women (33.7 ± 8.2 years) undergoing Roux-en-Y gastric bypass (n = 23) or sleeve gastrectomy (n = 31) were prospectively studied at baseline, 6 and 12 months postprocedure. Women with normal BMI (n = 14) served as controls. Bariatric surgery significantly reduced GlycA by 6 months (451 ± 47 µmol/L vs. 383 ± 50 µmol/L; P < 0.001) with further reduction at 12 months (348 ± 41 µmol/L; P < 0.001) and no difference between procedures. At 12 months, despite 41% of surgical subjects maintaining BMI >30 kg/m2 , GlycA levels did not differ between surgical and control subjects (P = 0.13). Increased high density lipoprotein particle size was strongly associated with reduced GlycA (r = -0.49; P < 0.001) and was found to mediate up to 43% of its body weight-loss-associated fall. This is the first study to demonstrate that surgical body weight loss markedly reduces levels of GlycA.

Changes in High-Density Lipoprotein Cholesterol Efflux Capacity After Bariatric Surgery Are Procedure Dependent.

OBJECTIVE: High-density lipoprotein cholesterol efflux capacity (CEC) is inversely associated with incident cardiovascular events, independent of high-density lipoprotein cholesterol. Obesity is often characterized by impaired high-density lipoprotein function. However, the effects of different bariatric surgical techniques on CEC have not been compared. This study sought to determine the effects of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) on CEC. APPROACH AND RESULTS: We prospectively studied severely obese, nondiabetic, premenopausal Hispanic women not using lipid medications undergoing RYGB (n=31) or SG (n=36). Subjects were examined before and at 6 and 12 months after surgery. There were no differences in baseline characteristics between surgical groups. Preoperative CEC correlated most strongly with Apo A1 (apolipoprotein A1) concentration but did not correlate with body mass index, waist:hip, high-sensitivity C-reactive protein, or measures of insulin resistance. After 6 months, SG produced superior response in high-density lipoprotein cholesterol and Apo A1 quantity, as well as global and non-ABCA1 (ATP-binding cassette transporter A1)-mediated CEC (P=0.048, P=0.018, respectively) versus RYGB. In multivariable regression models, only procedure type was predictive of changes in CEC (P=0.05). At 12 months after SG, CEC was equivalent to that of normal body mass index control subjects, whereas it remained impaired after RYGB. CONCLUSIONS: SG and RYGB produce similar weight loss, but contrasting effects on CEC. These findings may be relevant in discussions about the type of procedure that is most appropriate for a particular obese patient. Further study of the mechanisms underlying these changes may lead to improved understanding of the factors governing CEC and potential therapeutic interventions to maximally reduce cardiovascular disease risk in both obese and nonobese patients.

CT-guided minimally-invasive penile fracture repair.

We present the case of a 28 year old patient with an incomplete tear of the tunica albuginea occurred after having sexual intercourse in the female superior position. The diagnostic assessment was performed first clinically, then with CT, owing to its high resolution, allowed to exactly detect the tear location leading to precise preoperative planning. After adequate diagnosis through imaging and proper planning, the patient was performed a selective minimally invasive surgical approach to repair the lesion. The patient had good erection with no angular deformity or plaque formation after a 3-month follow-up.

[Association between copy number variations and risk of overweight/obesity among Han, Uyghur, and Kazak children].

OBJECTIVE: To study the association between the prevalence of overweight/obesity and copy number variations (CNVs) among Han, Uyghur, and Kazak children in Xinjiang, China. METHODS: The kindergartens in Ili, Altay, and Karamay in Xinjiang were selected as research sites, and stratified cluster sampling was used to select the children aged 3-7 years. Body height and body weight were measured, and exfoliated buccal mucosa cells were collected. CNVplex® was used to measure the CNVs of FTO_1, IRX3_1, IRX3_2, MC4R_1, and MC4R_2. RESULTS: A total of 603 children were surveyed (307 boys and 296 girls). There were 261 Han children, 194 Uyghur children, and 148 Kazak children. The overweight/obesity rates in Han, Uyghur, and Kazak children were 28.3%, 10.3%, and 31.1%, respectively (P<0.001). In Kazak children, the CNVs of IRX3_1 and MC4R_2 were associated with overweight/obesity (P<0.05). The multivariate logistic regression analysis showed that the risk of overweight/obesity in Han and Kazak children was 3.443 times (95%CI: 2.016-5.880) and 3.924 times (95%CI: 2.199-7.001), respectively, that in Uyghur children. The CNV of IRX3_1 was a risk factor for overweight/obesity (P=0.028, OR=2.251, 95%CI: 1.418-5.651). CONCLUSIONS: The CNV of IRX3_1 is associated with overweight/obesity in Han, Uyghur, and Kazak children, and the association between the CNV of IRX3_1 and overweight/obesity in Kazak children should be taken seriously.

[Comparison of national standard GB/T 31774 and international standard ISO 18668 for Chinese medicines coding system].

Coding rules for Chinese medicines and their codes (GB/T 31774-2015) was issued by General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China (AQSIQ) and Standardization Administration of the People's Republic of China (SAC) in 2015. Coding system for Chinese medicines (ISO 18668-1, 2, 3 and 4) series were issued one after another by International Organization for Standardization in 2016 and 2017. In this paper, the comparative study on the GB/T 31774 and ISO 18668-1, 2, 3 to 4 would be conducted to expound the similarities and differences among them. This essay aims at promoting the application of national and international standards of coding system in production and operation enterprises and the medical institutions of traditional Chinese medicine (TCM), reducing their repetitive investment to meet the Chinese medicine import and export trade requirement in future. Moreover, it provides the cornerstone and support for TCM standardization, and makes Chinese medicines standard gain dominance in field of international TCM standards, occupying the high ground of international market in the traditional medicine field of the world. It may promote the "Internet + TCM service" in our country, and let the Chinese medicine industry go out of the country and into the world to contribute to human health.

Nemo-like kinase (NLK) negatively regulates NF-kappa B activity through disrupting the interaction of TAK1 with IKKß.

Stringent negative regulation of the transcription factor NF-κB is essential for maintaining cellular stress responses and homeostasis. However, the tight regulation mechanisms of IKKß are still not clear. Here, we reported that nemo-like kinase (NLK) is a suppressor of tumor necrosis factor (TNFα)-induced NF-κB signaling by inhibiting the phosphorylation of IKKß. Overexpression of NLK largely blocked TNFα-induced NF-κB activation, p65 nuclear localization and IκBα degradation; whereas genetic inactivation of NLK showed opposing results. Mechanistically, we identified that NLK interacted with IκB kinase (IKK)-associated complex, which in turn inhibited the assembly of the TAK1/IKKß and thereby, diminished the IκB kinase phosphorylation. Our results indicate that NLK functions as a pivotal negative regulator in TNFα-induced activation of NF-κB via disrupting the interaction of TAK1 with IKKß.

Identification and in vitro pharmacological characterization of a novel and selective α7 nicotinic acetylcholine receptor agonist, Br-IQ17B.

AIM: Alpha7-nicotinic acetylcholine receptor (α7 nAChR) is a ligand-gated Ca(2+)-permeable ion channel implicated in cognition and neuropsychiatric disorders. Activation of α7 nAChR improves learning, memory, and sensory gating in animal models. To identify novel α7 nAChR agonists, we synthesized a series of small molecules and characterized a representative compound, Br-IQ17B, N-[(3R)-1-azabicyclo[2,2,2]oct-3-yl]-5-bromoindolizine-2-carboxamide, which specifically activates α7 nAChR. METHODS: Two-electrode voltage clamp (TEVC) recordings were primarily used for screening in Xenopus oocytes expressing human α7 nAChR. Assays, including radioisotope ligand binding, Western blots, whole-cell recordings of hippocampal culture neurons, and spontaneous IPSC recordings of brain slices, were also utilized to evaluate and confirm the specific activation of α7 nAChR by Br-IQ17B. RESULTS: Br-IQ17B potently activates α7 nAChR with an EC50 of 1.8±0.2 µmol/L. Br-IQ17B is selective over other subtypes such as α4ß2 and α3ß4, but it blocks 5-HT3A receptors. Br-IQ17B displaced binding of the α7 blocker [(3)H]-MLA to hippocampal crude membranes with a Ki of 14.9±3.2 nmol/L. In hippocampal neurons, Br-IQ17B evoked α7-like currents that were inhibited by MLA and enhanced in the presence of the α7 PAM PNU-120596. In brain slice recordings, Br-IQ17B enhanced GABAergic synaptic transmission in CA1 neurons. Mechanistically, Br-IQ17B increased ERK1/2 phosphorylation that was MLA-sensitive. CONCLUSION: We identified the novel, potent, and selective α7 agonist Br-IQ17B, which enhances synaptic transmission. Br-IQ17B may be a helpful tool to understand new aspects of α7 nAChR function, and it also has potential for being developed as therapy for schizophrenia and cognitive deficits.

Successful resection of a primary cardiac fibroma in a neonate: report of a case.

During the fetal-neonatal period, a primary cardiac tumor may be completely asymptomatic and such tumors may be incidentally discovered by echocardiography. A four-hour-old male was diagnosed to have a cardiac tumor by post-natal echocardiography and was observed closely. Surgery was indicated immediately at the 3 week follow-up examination when the tumor was found to have obstructed the right ventricle outflow. The tumor was resected successfully and its histopathology indicated that it was a fibroma. Follow-up echocardiograms and magnetic resonance imaging 5 months postoperatively demonstrated no evidence of any remaining tumor and his RV function was good.

Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC. OBJECTIVE: The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models. METHODS: 200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test. RESULTS: For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC. CONCLUSIONS: DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.