Probing the Internalization and Efficacy of Antibody-Drug Conjugate via Site-Specific Fc-Glycan Labelling of a Homogeneous Antibody Targeting SSEA-4 Bearing Tumors.

Antibody drug conjugates (ADC) are an emerging class of pharmaceuticals consisting of cytotoxic agents covalently attached to an antibody designed to target a specific cancer cell surface molecule followed by internalization and intracellular release of payload to exhibit its anticancer activity. Targeted delivery of cytotoxic payload to a variety of specific cells has been demonstrated to have significant enhancement in clinical efficacy and dramatic reduction in off-target toxicity. Site-specific conjugation of payload to the antibody is highly desirable for development of ADC with well-defined antibody-to-drug ratio, enhanced internalization, reduced toxicity, improved stability, desired pharmacological profile and optimal therapeutic index. Here, we reported a site-specific conjugation strategy for evaluation of antibody internalization and efficacy of ADC designed to target SSEA4 on solid tumors. This strategy stems from the azido-fucose tag of a homogeneous antibody Fc-glycan generated via in vitro glycoengineering approach for site-specific conjugation and optimization of antibody-drug ratio to exhibit optimal efficacy. The ADC consisting of a chimeric anti-SSEA4 antibody chMC813-70, conjugated to the antineo-plastic agent monomethyl auristatin E via both cleavable and non-cleavable linkers showed excellent cytotoxicity profile towards SSEA4-bearing cancer cells. A clear distinction in cytotoxicity was observed among cancer cells with different SSEA4 expression levels.

Bayesian analysis for partly linear Cox model with measurement error and time-varying covariate effect.

The Cox proportional hazards model is commonly used to estimate the association between time-to-event and covariates. Under the proportional hazards assumption, covariate effects are assumed to be constant in the follow-up period of study. When measurement error presents, common estimation methods that adjust for an error-contaminated covariate in the Cox proportional hazards model assume that the true function on the covariate is parametric and specified. We consider a semiparametric partly linear Cox model that allows the hazard to depend on an unspecified function of an error-contaminated covariate and an error-free covariate with time-varying effect, which simultaneously relaxes the assumption on the functional form of the error-contaminated covariate and allows for nonconstant effect of the error-free covariate. We take a Bayesian approach and approximate the unspecified function by a B-spline. Simulation studies are conducted to assess the finite sample performance of the proposed approach. The results demonstrate that our proposed method has favorable statistical performance. The proposed method is also illustrated by an application to data from the AIDS Clinical Trials Group Protocol 175.

Signaling pathway of globo-series glycosphingolipids and ß1,3-galactosyltransferase V (ß3GalT5) in breast cancer.

The globo-series glycosphingolipids (GSLs) SSEA3, SSEA4, and Globo-H specifically expressed on cancer cells are found to correlate with tumor progression and metastasis, but the functional roles of these GSLs and the key enzyme ß1,3-galactosyltransferase V (ß3GalT5) that converts Gb4 to SSEA3 remain largely unclear. Here we show that the expression of ß3GalT5 significantly correlates with tumor progression and poor survival in patients, and the globo-series GSLs in breast cancer cells form a complex in membrane lipid raft with caveolin-1 (CAV1) and focal adhesion kinase (FAK) which then interact with AKT and receptor-interacting protein kinase (RIP), respectively. Knockdown of ß3GalT5 disrupts the complex and induces apoptosis through dissociation of RIP from the complex to interact with the Fas death domain (FADD) and trigger the Fas-dependent pathway. This finding provides a link between SSEA3/SSEA4/Globo-H and the FAK/CAV1/AKT/RIP complex in tumor progression and apoptosis and suggests a direction for the treatment of breast cancer, as demonstrated by the combined use of antibodies against Globo-H and SSEA4.

[Paeonol inhibits macrophage M1 polarization by down-regulating miR-155/JAK1-STAT1 pathway].

The aim of this paper was to investigate the effect and mechanism of paeonol on peritoneal macrophage M1 polarization in mice, explore whether the intervention action is related to the down-regulation of miR-155 and the inhibition of downstream JAK1-STAT1 pathway, and provide a new idea for the molecular mechanism of paeonol against atherosclerosis(AS). Lipopolysaccharide(LPS) and interferon-γ(IFN-γ) were used to stimulate macrophages for 24 hours to establish the M1 polarization model, and paeonol was given 24 hours before co-stimulation to provide a pre-protective effect on cells. CCK-8 assay was used to detect the cells damage induced by LPS and IFN-γ co-stimulation; flow cytometry was used to detect the expression of M1 surface markers F4/80 and CD86. ELISA was used to detect the secretion of interleukin 6(IL-6) and tumor necrosis factor-α(TNF-α) in supernatant. RT-qPCR was used to detect the expression of miR-155, and Western blot was used to detect the protein expression at JAK1-STAT1-SOCS1 pathway. The results showed that LPS and IFN-γ had no obvious damage to the cells at the optimal concentration, but they induced macrophages polarized to M1, resulted in high expression of M1 type marker factors F4/80 and CD86 on the cell surface, and increased secretion of IL-6 and TNF-α on the cell surface(P<0.05 or P<0.01). Paeonol significantly reduced the LPS and IFN-γ-induced high expression of F4/80 and CD86, the secretion of inflammatory factors IL-6 and TNF-α(P<0.05 or P<0.01), decreased the expression level of miR-155, significantly down-regulated the protein phosphorylation level of JAK1-STAT1 and up-regulated the protein expression of SOCS1(P<0.01) in RAW264.7 cells. The results showed that paeonol could inhibit M1 polarization of macrophages by down-regulating cell surface marker factors and inflammatory factors secreted by cells, which may be related to the down-regulation of miR-155 expression and the inhibition JAK1-STAT1 pathway activation.

Stage-specific embryonic antigen-3 (SSEA-3) and ß3GalT5 are cancer specific and significant markers for breast cancer stem cells.

The discovery of cancer stem cells (CSCs), which are responsible for self-renewal and tumor growth in heterogeneous cancer tissues, has stimulated interests in developing new cancer therapies and early diagnosis. However, the markers currently used for isolation of CSCs are often not selective enough to enrich CSCs for the study of this special cell population. Here we show that the breast CSCs isolated with CD44(+)CD24(-/lo)SSEA-3(+) or ESA(hi)PROCR(hi)SSEA-3(+) markers had higher tumorigenicity than those with conventional markers in vitro and in vivo. As few as 10 cells with CD44(+)CD24(-/lo)SSEA-3(+) formed tumor in mice, compared with more than 100 cells with CD44(+)CD24(-/lo). Suppression of SSEA-3 expression by knockdown of the gene encoding ß-1,3-galactosyltransferase 5 (ß3GalT5) in the globo-series pathway, led to apoptosis in cancer cells specifically but had no effect on normal cells. This finding is further supported by the analysis of SSEA-3 and the two related globo-series epitopes SSEA4 and globo-H in stem cells (embryonic stem cells and induced pluripotent stem cells) and various normal and cancer cells, and by the antibody approach to target the globo-series glycans and the late-stage clinical trials of a breast cancer vaccine.

Variable selection for partially linear proportional hazards model with covariate measurement error.

In survival analysis, we may encounter the following three problems: nonlinear covariate effect, variable selection and measurement error. Existing studies only address one or two of these problems. The goal of this study is to fill the knowledge gap and develop a novel approach to simultaneously address all three problems. Specifically, a partially time-varying coefficient proportional hazards model is proposed to more flexibly describe covariate effects. Corrected score and conditional score approaches are employed to accommodate potential measurement error. For the selection of relevant variables and regularized estimation, a penalization approach is adopted. It is shown that the proposed approach has satisfactory asymptotic properties. It can be effectively realized using an iterative algorithm. The performance of the proposed approach is assessed via simulation studies, and further illustrated by application to data from an AIDS clinical trial.

Controlling the false discoveries in LASSO.

The LASSO method estimates coefficients by minimizing the residual sum of squares plus a penalty term. The regularization parameter λ in LASSO controls the trade-off between data fitting and sparsity. We derive relationship between λ and the false discovery proportion (FDP) of LASSO estimator and show how to select λ so as to achieve a desired FDP. Our estimation is based on the asymptotic distribution of LASSO estimator in the limit of both sample size and dimension going to infinity with fixed ratio. We use a factor analysis model to describe the dependence structure of the design matrix. An efficient majorization-minimization based algorithm is developed to estimate the FDP at fixed value of λ. The analytic results are compared with those of numerical simulations on finite-size systems and are confirmed to be correct. An application to the high-throughput genomic riboavin data set also demonstrates the usefulness of our method.

The association between Dietary Inflammatory Index scores and the prevalence of colorectal adenoma.

OBJECTIVE: The Dietary Inflammatory Index (DII)TM, which was developed to characterize the inflammatory potential of a person's diet, has been shown to be associated with inflammatory conditions such as cancer. The present study aimed to investigate the association between DII scores and colorectal adenoma (CRA), a pre-cancerous condition. DESIGN: Responses to baseline dietary questionnaires were used calculate DII scores. In a cross-sectional study design, the association between DII scores and CRA prevalence was determined in men and women separately using logistic regression models. SETTING: Ten cancer screening centres across the USA. SUBJECTS: Participants were those included in the screening arm of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. RESULTS: Among the 44 278 individuals included in these analyses, men with diets in the most inflammatory quartile of DII scores had higher odds of all types of CRA (advanced, non-advanced and multiple (>1)) compared with those with diets in the least inflammatory quartile of DII scores. In fully adjusted models, compared with those with DII scores in quartile 1 (least inflammatory), males with DII scores in quartile 3 (adjusted odds ratio (aOR)=1·28; 95 % CI 1·12, 1·47) and quartile 4 (aOR=1·41; 95 % CI 1·23, 1·62) were more likely to have prevalent distal CRA. Higher DII scores, representing a more inflammatory diet, also were weakly associated with a higher prevalence of CRA in women. CONCLUSIONS: Implementing an anti-inflammatory diet may be an effective means of primary prevention of CRA, especially in men.

Comparison of multiple hazard rate functions.

Many robust tests have been proposed in the literature to compare two hazard rate functions, however, very few of them can be used in cases when there are multiple hazard rate functions to be compared. In this article, we propose an approach for detecting the difference among multiple hazard rate functions. Through a simulation study and a real-data application, we show that the new method is robust and powerful in many situations, compared with some commonly used tests.

B-cell maturation antigen is modified by a single N-glycan chain that modulates ligand binding and surface retention.

Glycosylation, an important posttranslational modification process, can modulate the structure and function of proteins, but its effect on the properties of plasma cells is largely unknown. In this study, we identified a panel of glycoproteins by click reaction with alkynyl sugar analogs in plasma cells coupled with mass spectrometry analysis. The B-cell maturation antigen (BCMA), an essential membrane protein for maintaining the survival of plasma cells, was identified as a glycoprotein exhibiting complex-type N-glycans at a single N-glycosylation site, asparagine 42. We then investigated the effect of N-glycosylation on the function of BCMA and found that the dexamethasone-induced apoptosis in malignant plasma cells can be rescued by treatment with BCMA ligands, such as a proliferation-inducing ligand (APRIL) and B-cell-activating factor (BAFF), whereas removal of terminal sialic acid on plasma cells further potentiated the ligand-mediated protection. This effect is associated with the increased surface retention of BCMA, leading to its elevated level on cell surface. In addition, the α1-3,-4 fucosylation, but not the terminal sialylation, assists the binding of BCMA with ligands in an in vitro binding assay. Together, our results highlight the importance of N-glycosylation on BCMA in the regulation of ligand binding and functions of plasma cells.

Detecting differentially methylated loci for multiple treatments based on high-throughput methylation data.

BACKGROUND: Because of its important effects, as an epigenetic factor, on gene expression and disease development, DNA methylation has drawn much attention from researchers. Detecting differentially methylated loci is an important but challenging step in studying the regulatory roles of DNA methylation in a broad range of biological processes and diseases. Several statistical approaches have been proposed to detect significant methylated loci; however, most of them were designed specifically for case-control studies. RESULTS: Noticing that the age is associated with methylation level and the methylation data are not normally distributed, in this paper, we propose a nonparametric method to detect differentially methylated loci under multiple conditions with trend for Illumina Array Methylation data. The nonparametric method, Cuzick test is used to detect the differences among treatment groups with trend for each age group; then an overall p-value is calculated based on the method of combining those independent p-values each from one age group. CONCLUSIONS: We compare the new approach with other methods using simulated and real data. Our study shows that the proposed method outperforms other methods considered in this paper in term of power: it detected more biological meaningful differentially methylated loci than others.

Phase transition and higher order analysis of Lq regularization under dependence.

We study the problem of estimating a [Formula: see text]-sparse signal [Formula: see text] from a set of noisy observations [Formula: see text] under the model [Formula: see text], where [Formula: see text] is the measurement matrix the row of which is drawn from distribution [Formula: see text]. We consider the class of [Formula: see text]-regularized least squares (LQLS) given by the formulation [Formula: see text], where [Formula: see text]  [Formula: see text] denotes the [Formula: see text]-norm. In the setting [Formula: see text] with fixed [Formula: see text] and [Formula: see text], we derive the asymptotic risk of [Formula: see text] for arbitrary covariance matrix [Formula: see text] that generalizes the existing results for standard Gaussian design, i.e. [Formula: see text]. The results were derived from the non-rigorous replica method. We perform a higher-order analysis for LQLS in the small-error regime in which the first dominant term can be used to determine the phase transition behavior of LQLS. Our results show that the first dominant term does not depend on the covariance structure of [Formula: see text] in the cases [Formula: see text] and [Formula: see text] which indicates that the correlations among predictors only affect the phase transition curve in the case [Formula: see text] a.k.a. LASSO. To study the influence of the covariance structure of [Formula: see text] on the performance of LQLS in the cases [Formula: see text] and [Formula: see text], we derive the explicit formulas for the second dominant term in the expansion of the asymptotic risk in terms of small error. Extensive computational experiments confirm that our analytical predictions are consistent with numerical results.

Urine sodium concentration and 28-day weight velocity in preterm infants: A retrospective cohort study.

BACKGROUND: Urine sodium concentration has been suggested as a marker to guide enteral sodium supplementation in preterm infants; however, no previous data have demonstrated relationships between urine sodium concentration and postnatal growth. METHODS: We performed a single-center retrospective cohort study on 224 preterm infants admitted to the neonatal intensive care unit at the Children's Hospital of Georgia between January 2010 and July 2022. Spot urine sodium was measured in preterm infants (<34 weeks postmenstrual age [PMA]) between days of life (DOLs) 7 and 28. Our exposure of interest was spot urine sodium concentration (milliequivalents per liter) obtained between postnatal days 7 and 28, and our primary outcome was weight velocity (grams per kilograms per day) determined at DOL 28. Statistical relationships were assessed by multivariate analysis with subgroup comparisons by Student t test and analysis of variance. RESULTS: In 224 preterm infants (199 ± 17 days, 56% male, 71% Black), urine sodium concentration did not associate with weight velocity at DOL 28 and 36 weeks PMA. Urine sodium concentration was weakly associated with gestational age at birth, and Black preterm infants had higher urine sodium values when compared with "other," but not White preterm infants. CONCLUSION: Spot urine sodium during the first month of life does not associate with weight velocity at DOL 28 or 36 weeks PMA.

Single Site N-Glycosylation of B Cell Maturation Antigen (BCMA) Inhibits γ-Secretase-Mediated Shedding and Improves Surface Retention and Cell Survival.

B cell maturation antigen (BCMA), a member of the tumor necrosis factor receptor (TNFR) family, on the cell surface plays a key role in maintaining the survival of plasma cells and malignant as well as inflammatory accessory cells. Therefore, targeting BCMA or disrupting its interaction with ligands has been a potential approach to cancer therapy. BCMA contains a single N-glycosylation site, but the function of N-glycan on BCMA is not understood. Here, we found that the N-glycosylation of BCMA promoted its cell-surface retention while removing the N-glycan increased BCMA secretion through γ-secretase-mediated shedding. Addition of γ-secretase inhibitor prevented nonglycosylated BCMA from shedding and protected cells from dexamethasone and TRAIL-induced apoptosis.

Knockdown of thioredoxin interacting protein in Müller cells attenuates photoreceptor apoptosis in streptozotocin-induced diabetic mouse model.

We explored the effect of inhibition of thioredoxin interacting protein (Txnip) on neuroprotection in Müller cells under high glucose. Wild-type (WT) and Txnip knockout (Txnip-/-) mice were used to establish a streptozotocin (STZ)-induced diabetes model and a Müller cells high glucose model. We detected BDNF expression and PI3K/AKT/CREB pathway activation levels in the retina and Müller cells of each group in vivo and in vitro experiments. The Txnip-/- STZ group showed higher expression of BDNF and phosphorylation of PI3K/AKT/CREB in retina, and less retinal photoreceptor apoptosis was observed in Txnip-/- diabetic group than in WT. After using an inhibitor of PI3K signaling pathway, BDNF expression was reduced; In vitro co-cultured with Müller cells in different groups, 661 W cells showed different situations, Txnip-/- Müller cells maximum downregulated Cleaved-caspase 3 expression in 661 W, accompanied by an increase in Bcl-2/Bax ratio. These findings indicate that inhibiting endogenous Txnip in mouse Müller cells can promote their expression and secretion of BDNF, thereby reducing HG induced photoreceptor apoptosis and having important neuroprotective effects on DR. The regulation of BDNF expression by Txnip may be achieved by activating the PI3K/AKT/CREB pathway. This study suggests that regulating Txnip may be a potential target for DR treatment.

Firefly-inspired bipolar information indication system actuated by white light.

The indication of information in materials is widely used in our daily life, and optical encoding materials are ideal for information loading due to their easily readable nature and adjustable optical properties. However, most of them could only indicate one type of information, either changing or unchanging due to the mutual interference. Inspired by firefly, we present a non-interfering bipolar information indication system capable of indicating both changing and unchanging information. A photochemical afterglow material is incorporated into the photonic crystal matrix through a high-throughput technique called shear-induced ordering technique, which can efficiently produce large-area photonic crystal films. The indication of changing and unchanging information is enabled by two different utilizations of white light by the afterglow material and photonic crystals, respectively, which overcome the limitations of mutual interference. As a proof of concept, this system is used to indicate the changing photodegradation level of mecobalamin (a photosensitive medicine) and unchanging intrinsic drug information with anti-counterfeiting functionality, which is a promising alternative to instantly ascertain the efficacy of medicine at home where conventional assays are impractical.

N-Halaminated spermidine-containing polymeric coating enables titanium to achieve dual functions of antibacterial and osseointegration.

Titanium (Ti) and its alloys have been widely employed in the treatment of orthopedics and other hard tissue diseases. However, Ti-based implants are bioinert and suffer from bacterial infections and poor osseointegration in clinical applications. Herein, we successfully modified Ti with a porous N-halaminated spermidine-containing polymeric coating (Ti-SPD-Cl) through alkali-heat treatment, surface grafting and chlorination, and it has both excellent antibacterial and osteogenic abilities to significantly enhance osseointegration. The as-obtained Ti-SPD-Cl contains abundant N-Cl groups and demonstrates effective antibacterial ability against S. aureus and E. coli. Meanwhile, due to the presence of the spermidine component and construction of a porous hydrophilic surface, Ti-SPD-Cl is also beneficial for maintaining cell membrane homeostasis and promoting cell adhesion, exhibiting good biocompatibility and osteogenic ability. The rat osteomyelitis model demonstrates that Ti-SPD-Cl can effectively suppress bacterial infection and enhance bone-implant integration. Thus, Ti-SPD-Cl shows promising clinical applicability in the prevention of orthopedic implant infections and poor osseointegration.

Recovery of ammonia nitrogen from simulated reject water by bipolar membrane electrodialysis.

Ammonia monohydrate (NH3·H2O) is an important chemical widely used in industrial, agricultural, and pharmaceutical fields. Reject water is used as the raw material in self-built bipolar membrane electrodialysis (BMED) to produce NH3·H2O. The effects of electrode materials, membrane stack structure, and operating conditions (current density, initial concentrations of the reject water, and initial volume ratio) on the BMED process were investigated, and the economic costs were analyzed. The results showed that compared with graphite electrodes, ruthenium-iridium-titanium electrodes as electrode plates for BMED could increase current efficiency (25%) and reduce energy consumption (26%). Compared with two-compartment BMED, three-compartment BMED had a higher ammonia nitrogen conversion rate (86.6%) and lower energy consumption (3.5 kW· h/kg). Higher current density (15 mA/cm2) could achieve better current efficiency (79%). The BMED performances were improved when the initial NH4+ concentrations of the reject water increased from 500 mg NH4+/L to 1000 mg NH4+/L, but the performance decreased as the concentration increased from 1000 mg NH4+/L to 1500 mg NH4+/L. High initial volume ratio of the salt compartment and product compartment was beneficial for reducing energy consumption. Under the optimal operating conditions, only 0.13 $/kg reject water was needed to eliminate the environmental impact of reject water accumulation. This work indicates that BMED can not only achieve desalination of reject water, but also generate products that alleviate the operational pressure of factories.

Age-adjusted nonparametric detection of differential DNA methylation with case-control designs.

BACKGROUND: DNA methylation profiles differ among disease types and, therefore, can be used in disease diagnosis. In addition, large-scale whole genome DNA methylation data offer tremendous potential in understanding the role of DNA methylation in normal development and function. However, due to the unique feature of the methylation data, powerful and robust statistical methods are very limited in this area. RESULTS: In this paper, we proposed and examined a new statistical method to detect differentially methylated loci for case control designs that is fully nonparametric and does not depend on any assumption for the underlying distribution of the data. Moreover, the proposed method adjusts for the age effect that has been shown to be highly correlated with DNA methylation profiles. Using simulation studies and a real data application, we have demonstrated the advantages of our method over existing commonly used methods. CONCLUSIONS: Compared to existing methods, our method improved the detection power for differentially methylated loci for case control designs and controlled the type I error well. Its applications are not limited to methylation data; it can be extended to many other case-control studies.

R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment.

UNLABELLED: R/DWD is an extensible package for classification. It is built based on a recently developed powerful classification method called distance weighted discrimination (DWD). DWD is related to, and has been shown to be superior to, the support vector machine in situations that are fundamental to bioinformatics, such as very high dimensional data. DWD has proven to be very useful for several fundamental bioinformatics tasks, including classification, data visualization and removal of biases, such as batch effects. Earlier DWD implementations, however, relied on Matlab, which is not free and requires a license. The major contribution of the R/DWD package is an implementation that is completely in R and thus can be used without any requirements for licensing or software purchase. In addition, R/DWD also provides efficient solvers for second-order-cone-programming and quadratic programming. AVAILABILITY AND IMPLEMENTATION: The package is freely available from cran.r-project.org.