Regression-based heterogeneity analysis to identify overlapping subgroup structure in high-dimensional data

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the underlying subgroup structure and estimates the subgroup-specific regression coefficients. However, most of the existing regression-based heterogeneity analyses can only address disjoint subgroups; that is, each sample is assigned to only one subgroup. In reality, some samples have multiple labels, for example, many genes have several biological functions, and some cells of pure cell types transition into other types over time, which suggest that their outcome-feature relationships (regression coefficients) can be a mixture of relationships in more than one subgroups, and as a result, the disjoint subgrouping results can be unsatisfactory. To this end, we develop a novel approach to regression-based heterogeneity analysis, which takes into account possible overlaps between subgroups and high data dimensions. A subgroup membership vector is introduced for each sample, which is combined with a loss function. Considering the lack of information arising from small sample sizes, an $l_2$ norm penalty is developed for each membership vector to encourage similarity in its elements. A sparse penalization is also applied for regularized estimation and feature selection. Extensive simulations demonstrate its superiority over direct competitors. The analysis of Cancer Cell Line Encyclopedia data and lung cancer data from The Cancer Genome Atlas shows that the proposed approach can identify an overlapping subgroup structure with favorable performance in prediction and stability.Comment: 33 pages, 16 figure

Determination of heavy metals in soil by inductively coupled plasma mass spectrometry (ICP-MS) with internal standard method

Soil ,the carrier of agricultural production and important part of the ecological environment, is heavily contaminated with hazards heavy metals. Therefore, it is oblige to research analytical techniques that could efficiently determine the total content of heavy metals in soil. The determination of heavy metals in soil was disturbed by matrix elements or spectral interferences . In this study , this problem was solved by internal standard method . GBW07402、GBW07448、GBW07423、GBW07428、GBW074079 soil sample were chosen to be the Certified Reference Materials, soils was prepared by microwave digestion with mixed acid following analyzed for determination the content（Cr,Cu, Pb,Ba,Ni,Mn ） by Inductively coupled plasma mass spectrometric in 50ug/L internal standard concentration, the method was validated by compared with certified values 、method contrast(standard addition method versus internal standard method scan the same prepared solution ) and recovery check. The results of internal standard method are in excellent agreement with the indicative values and the date obtained from standard addition method, respectively. Recoveries were adequate being in the acceptable range of 90-99% and RSD of <6.7 % for all the elements at three level of 5,20 and 50mg/kg with quantified by standard addition method and internal standard method .Finally, The graphy of quality control(n=100)were obtained to guide internal quality control in laborator

Exploring the active mechanism of berberine against HCC by systematic pharmacology and experimental validation

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Berberine (BBR) is the main component of Coptidis rhizoma, the dried rhizome of Coptis chinensis and is a potential plant alkaloid used for the treatment of cancer due to its high antitumor activity. The present study examined the therapeutic potential and molecular mechanism of action of BBR against HCC, using systematic pharmacology combined with a molecular docking approach and experimental validation in vitro. Through systematic pharmacological analysis, it was found that BBR serves a significant role in inhibiting HCC by affecting multiple pathways, especially the PI3K/AKT signaling pathway. Furthermore, the docking approach indicated that the binding of BBR to AKT could lead to the suppression of AKT activity. The present study examined the inhibitory effect of BBR on the PI3K/AKT pathway in HCC and identified that BBR downregulated the expressions of phosphorylated AKT and PI3K in MHCC97‑H and HepG2 cells, inhibiting their growth, cell migration and invasion in a dose‑dependent manner. In addition, inhibition of the AKT pathway by BBR also contributed to cell apoptosis in MHCC97‑H and HepG2 cells. Taken together, the results of the present study suggested that BBR may be a promising antitumor drug for HCC that acts by inhibiting the PI3K/AKT pathway

Explainable Artificial Intelligence and Domain Adaptation for Predicting HIV Infection With Graph Neural Networks

OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets. METHODS: Network data from two cohorts of younger sexual minority men (SMM) from two U.S. cities (Chicago, IL, and Houston, TX) were collected between 2014 and 2016. Feature importance from graph attention network (GAT) models were determined using GNNExplainer. Domain adaptation was performed to examine model transferability from one city dataset to the other dataset, training with 100% of the source dataset with 30% of the target dataset and prediction on the remaining 70% from the target dataset. RESULTS: Domain adaptation showed the ability of GAT to improve prediction over training with single city datasets. Feature importance analysis with GAT models in single city training indicated similar features across different cities, reinforcing potential application of GAT models in predicting HIV infections through domain adaptation. CONCLUSION: GAT models can be used to address the data sparsity issue in HIV study populations. They are powerful tools for predicting individual risk of HIV that can be further explored for better understanding of HIV transmission

Generating Lifetime-Enhanced Microbubbles by Decorating Shells with Silicon Quantum Nano-Dots Using a 3-Series T-Junction Microfluidic Device

Long-term stability of microbubbles is crucial to their effectiveness. Using a new microfluidic device connecting three T-junction channels of 100 μm in series, stable monodisperse SiQD-loaded bovine serum albumin (BSA) protein microbubbles down to 22.8 ± 1.4 μm in diameter were generated. Fluorescence microscopy confirmed the integration of SiQD on the microbubble surface, which retained the same morphology as those without SiQD. The microbubble diameter and stability in air were manipulated through appropriate selection of T-junction numbers, capillary diameter, liquid flow rate, and BSA and SiQD concentrations. A predictive computational model was developed from the experimental data, and the number of T-junctions was incorporated into this model as one of the variables. It was illustrated that the diameter of the monodisperse microbubbles generated can be tailored by combining up to three T-junctions in series, while the operating parameters were kept constant. Computational modeling of microbubble diameter and stability agreed with experimental data. The lifetime of microbubbles increased with increasing T-junction number and higher concentrations of BSA and SiQD. The present research sheds light on a potential new route employing SiQD and triple T-junctions to form stable, monodisperse, multi-layered, and well-characterized protein and quantum dot-loaded protein microbubbles with enhanced stability for the first time

Nocaviogua A and B: two lipolanthines from root-nodule-associated Nocardia sp.

Nocaviogua A (1) and B (2), two lipolanthines featuring a non-canonical avionin (Avi)-containing macrocycle and a long acyl chain, were identified from the mutualistic actinomycete Nocardia sp. XZ19_369, which was isolated from the nodules of sea buckthorn collected in Tibet. Their planar structures were elucidated via extensive analyses of 1D and 2D NMR, as well as HRMS data. The absolute configurations were fully elucidated by advanced Marfey’s analysis and GIAO NMR calculations, representing the first time that the configurations of this family of lipolanthines have been determined. Nocaviogua A (1) exhibited weak cytotoxicity against human chronic uveal melanoma cells (UM92-1), non-small cell lung cancer (NCI-H2170), and breast cancer (MDA-MB-231). Our work provides valuable information on this burgeoning class of lipolanthines for further investigations

Global study of anti-NMDA encephalitis: a bibliometric analysis from 2005 to 2023

BackgroundAutoimmune diseases have always been one of the difficult diseases of clinical concern. Because of the diversity and complexity of its causative factors, unclear occurrence and development process and difficult treatment, it has become a key disease for researchers to study. And the disease explored in this paper, anti-NMDA encephalitis, belongs to a common type of autoimmune encephalitis. However, the quality of articles and research hotspots in this field are not yet known. Therefore, in this field, we completed a bibliometric and visualization analysis from 2005 to 2023 in order to understand the research hotspots and directions of development in this field.Materials and methodsWe searched the SCI-expanded databases using Web of Science’s core databases on January 22, 2024 and used tools such as VOS viewer, Cite Space, and R software to visualize and analyze the authors, countries, journals, institutions, and keywords of the articles.ResultsA total of 1,161 literatures were retrieved and analyzed in this study. China was the country with the most total publications, and USA and Spain were the most influential countries in the field of anti-NMDA encephalitis. University of Pennsylvania from USA was the institution with the highest number of publications. While Dalmau Josep is the most prolific, influential and contributing author who published one of the most cited articles in Lancet Neurology, which laid the foundation for anti-NMDA encephalitis research, the top three appearances of keyword analysis were: “antibodies”, “diagnosis”, and “autoimmune encephalitis.”ConclusionBibliometric analysis shows that the number of studies on anti-NMDA encephalitis is generally increasing year by year, and it is a hot disease pursued by researchers. USA and Spain are leading in the field of anti-NMDA encephalitis, while China should continue to improve the quality of its own research. The suspected causes of anti-NMDA encephalitis other than ovarian teratoma and herpes simplex, the specific clinical manifestations that are not masked by psychiatric symptoms, the diagnostic modalities that are faster and more accurate than antibody tests, and the improvement of treatment modalities by evaluating prognosis of various types of patients are the hotspots for future research

Improved performance and stability of perovskite solar modules by interface modulating with graphene oxide crosslinked CsPbBr3quantum dots

Perovskite solar cells (PSCs) are one of the most prominent photovoltaic technologies. However, PSCs still encounter great challenges of scaling up from laboratorial cells to industrial modules without serious performance loss while maintaining excellent long-term stability, owing to the resistive losses and extra instability factors that scale quadratically with the device area. Here, we manifest a concept of multifunctional interface modulation for highly efficient and stable perovskite solar modules (PSMs). The advisably designed multifunctional interface modulator GO/QD crosslinks the CsPbBr3 perovskite quantum dots (QDs) on the conductive graphene oxide (GO) surfaces, which significantly improve charge transport and energy band alignment at the perovskite/hole transporting layer interface to reduce the charge transport resistance while passivating the surface defects of the perovskite to inhibit carrier recombination resistive losses. Moreover, the GO/QD interlayer acts as a robust permeation barrier that modulates the undesirable interfacial ion and moisture diffusion. Consequently, we adopt a scalable vacuum flash-assisted solution processing (VASP) method to achieve a certified stabilized power output efficiency of 17.85% (lab-measured champion efficiency of 18.55%) for the mini-modules. The encapsulated PSMs achieve over 90% of their initial efficiency after continuous operation under 1 sun illumination and the damp heat test at 85 °C, respectively. This journal isThe authors acknowledge financial from the National Natural Science Foundation of China (21875081, 91733301, and 51972251), the Chinese National 1000-Talent-Plan program, the Foundation of State Key Laboratory of Coal Conversion (Grant No. J18-19-913), and the Frontier Project of the Application Foundation of Wuhan Science and Technology Plan Project (2020010601012202)