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

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

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

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

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)

Pre-pregnancy body mass index and glycated-hemoglobin with the risk of metabolic diseases in gestational diabetes: a prospective cohort study

BackgroundMetabolic diseases during pregnancy result in negative consequences for mothers. Pre-pregnancy body mass index (BMI) and late-pregnancy glycated-hemoglobin (HbA1c) are most important factors independently affecting the risk of gestational diabetes mellitus (GDM). However how both affect the combined risk of other metabolic diseases in women with GDM is unclear. The study aims to investigate the influence of pre-pregnancy BMI and pregnancy glycemic levels on other gestational metabolic diseases in women with GDM.MethodsPregnancies with GDM from January 2015 to December 2018 in the Xi’an longitudinal mother-child cohort study (XAMC) were retrospectively enrolled. Those without other metabolic diseases by the time of oral glucose tolerance test (OGTT) detection were finally recruited and divided into four groups by pre-pregnancy BMI (Underweight <18.5kg/m2; Normal weight 18.5-23.9 kg/m2; Overweight 24.0-27.9 kg/m2; Obesity ≥28.0 kg/m2, respectively) or two groups by HbA1c in late pregnancy (normal HbA1c<5.7%; high HbA1c≥5.7%). Multivariate logistic regression analysis was used to identify risk factors. Interaction between pre-pregnancy BMI (reference group 18.5-23.9 kg/m2) and HbA1c (reference group <5.7%) was determined using strata-specific analysis.ResultsA total of 8928 subjects with GDM were included, 16.2% of which had a composite of metabolic diseases. The pre-pregnancy overweight and obesity, compared with normal BMI, were linked to the elevated risk of the composite of metabolic diseases, particularly pre-eclampsia (both P <0.001) and gestational hypertension (both P <0.001). Meanwhile, patients with high HbA1c had an obvious higher risk of pre-eclampsia (P< 0.001) and gestational hypertension (P= 0.005) compared to those with normal HbA1c. In addition, there were significant interactions between pre-pregnancy BMI and HbA1c (P< 0.001). The OR of pre-pregnancy BMI≥ 28 kg/m2 and HbA1c≥ 5.7% was 4.46 (95% CI: 2.85, 6.99; P< 0.001). The risk of other metabolic diseases, except for pre-eclampsia (P= 0.003), was comparable between the two groups of patients with different HbA1c levels at normal pre-pregnancy BMI group. However, that was remarkably elevated in obese patients (P= 0.004), particularly the risk of gestational hypertension (P= 0.004).ConclusionPre-pregnancy overweight/obesity and late-pregnancy high HbA1c increased the risk of other gestational metabolic diseases of women with GDM. Monitoring and controlling late-pregnancy HbA1c was effective in reducing metabolic diseases, particularly in those who were overweight/obese before conception

Molecular epidemiology and clinical characteristics of respiratory syncytial virus in hospitalized children during winter 2021–2022 in Bengbu, China

ObjectiveThis study aimed to study the molecular epidemiology and clinical characteristics of respiratory syncytial virus (RSV) infection from hospitalized children with ARTI in Bengbu.MethodsOne hundred twenty-four nasopharyngeal swab specimens and clinical data from children with ARTI cases were collected in Bengbu, China, during winter 2021–2022. The samples were detected by qPCR of 13 respiratory viruses. Phylogenetic analysis was constructed using MEGA 7.0. All analyses were performed using SAS software, version 9.4.ResultsIn winter 2021–2022, URTI, NSCAP, SCAP, and bronchiolitis accounted for 41.03%, 27.35%, 17.09%, and 14.53% of hospitalized children in Bengbu, China. The detection rates of the top three were RSV (41.94%), ADV (5.65%), and FluB (5.65%) in hospitalized children through 13 virus detection. RSV is the main pathogen of hospitalized children under 2 years old. Forty-eight sequences of G protein of RSV were obtained through PCR amplification, including RSV-A 37 strains and RSV-B 11 strains. Phylogenetic analysis showed that all RSV-A and RSV-B were ON1 and BA9 genotypes, respectively. ON1 genotypes were further divided into two clades. The majority of ON1 strains formed a unique genetic clade with T113I, V131D, N178 G, and H258Q mutations. Furthermore, RSV infection was an independent risk factor for ventilator use (OR = 9.55, 95% CI 1.87–48.64).ConclusionThere was a high incidence of RSV among hospitalized children during winter 2021–2022 in Bengbu with ON1 and BA9 being the dominant strains. This study demonstrated the molecular epidemiological characteristics of RSV in children with respiratory infections in Bengbu, China

Respiratory Syncytial Virus Exacerbates Kidney Damages in IgA Nephropathy Mice via the C5a-C5aR1 Axis Orchestrating Th17 Cell Responses

Respiratory viral infections can directly lead to kidney damage such as IgA nephropathy (IgAN), partly due to mucosal immune system dysfunction. Although the activated C5a-C5aR1 axis results in increased Th1 and Th17 frequencies but reduced Treg frequencies in Respiratory syncytial virus (RSV) infection, how this axis affects Th cell disorders in RSV-induced IgAN exacerbation remains unknown. Here, we used a mouse model to dissect the activation of C5a-C5aR1 by RSV and the consequences on the regulation of Th1, Th17, and Treg immune responses in IgA nephropathy. RSV fusion protein was clearly deposited not only in the pulmonary interstitium but also in the glomerulus in RSV-IgAN mice, and RSV infection led to more severe pathological changes in the kidneys in IgAN mice. Blocking the C5a-C5aR1 axis resulted in a decrease in the albumin-to-creatinine ratio, and the attenuation of kidney damage in IgAN and RSV-IgAN mice might be partly attributed to the inhibition of Th cell and cytokine dysfunction. Th1, Th17 and Treg immune responses and their corelative cytokines were disrupted by RSV infection and rescued by C5aR1 inhibition. Moreover, we constructed a coculture system of human mesangial cells and CD4+ T cells and found that RSV infection might lead to CD4+ T cell production via human mesangial cells-enhanced CD4+ T cell proliferation, consequently increasing IL-17 levels. These pathological behaviors were augmented by C5a stimulation and decreased by C5aR1 inhibition. Thus, C5aR1 inhibition alters both kidney damage and Th1, Th17, and Treg cell dysfunction in RSV-induced IgAN exacerbation and locally regulates HMC antigen presentation function in the kidney. Taken together, our data offer profound evidence that blocking the C5a-C5aR1 axis might be a potential therapy for RSV-induced IgAN