New Insights into PI3K Inhibitor Design using X-ray Structures of PI3Kα Complexed with a Potent Lead Compound

Abstract Phosphatidylinositol 3-kinase α is an attractive target to potentially treat a range of cancers. Herein, we described the evolution of a reported PI3K inhibitor into a moderate PI3Kα inhibitor with a low molecular weight. We used X-ray crystallography to describe the accurate binding mode of the compound YXY-4F. A comparison of the p110α–YXY-4F and apo p110α complexes showed that YXY-4F induced additional space by promoting a flexible conformational change in residues Ser773 and Ser774 in the PI3Kα ATP catalytic site. Specifically, residue 773(S) in PI3Kα is quite different from that of PI3Kβ (D), γ (A), and δ (D), which might guide further optimization of substituents around the NH group and phenyl group to improve the selectivity and potency of PI3Kα

Harvesting Ambient Environmental Energy for Wireless Sensor Networks: A Survey

In recent years, wireless sensor networks (WSNs) have grown dramatically and made a great progress in many applications. But having limited life, batteries, as the power sources of wireless sensor nodes, have restricted the development and application of WSNs which often requires a very long lifespan for better performance. In order to make the WSNs prevalent in our lives, an alternative energy source is required. Environmental energy is an attractive power source, and it provides an approach to make the sensor nodes self-powered with the possibility of an almost infinite lifetime. The goal of this survey is to present a comprehensive review of the recent literature on the various possible energy harvesting technologies from ambient environment for WSNs

Distinguishing T1-2 and T3a tumors of rectal cancer with texture analysis and functional MRI parameters

PURPOSEWe aimed to investigate whether the texture analysis and functional magnetic resonance imaging (fMRI) could differentiate rectal cancer pathological stages T1-2 (pT1-2) and T3a (pT3a).METHODSEighty-two rectal adenocarcinoma patients at stage pT1-2 and pT3a received T2 and fMRI examination before surgery. The latter included apparent diffusion coefficient (ADC) sequence, dynamic contrast enhancement (DCE) MRI, and intravoxel incoherent motion (IVIM) diffusion weighted imaging. Patients were grouped into early stage (pT1-2) and advanced stage (pT3a). The MRI accuracy in diagnosing rectal cancer before surgery was calculated. The differences in clinicopathological variables, quantitative parameters including ADC values, IVIM parameters (perfusion fraction [f], true diffusion coefficient [D], and pseudo- diffusion coefficient [D*]), DCE MRI parameters (transfer constant [Ktrans], reflux constant [Kep], and extravascular extracellular fractional volume [Ve]), and texture features were compared between the groups. Receiver operating characteristic (ROC) curves of texture features and fMRI parameters were generated to distinguish pT1-2 and pT3a tumors. The multivariate analysis was used to develop a predictive model and to find independent risk factors. Hosmer–Lemeshow test was used to see the fitness of the model. DeLong test was applied to compare the ROC curves of different features. Correlation of texture features and fMRI parameters with stage were calculated using r (Spearman’s rank correlation coefficient).RESULTSThe preoperative accuracy in differentiating pT1-2 from pT3a rectal cancer using MRI was 74.39%. Kep, Ve, and ADC showed significant differences between the groups. Kep and ADC showed negative correlation with stage. Ve correlated positively with stage. Twenty-five texture features from T2 images showed significant differences between groups, and S(0,2)SumOfSqs and WavEnLH_s_2 among these showed better performance, showing negative correlation with stage. The area under the curve (AUC) values of S(0,2)SumOfSqs, WavEnLH_s_2, ADC, Kep, and Ve were 0.721, 0.699, 0.690, 0.666, and 0.653, respectively. The multivariate analysis showed that S(0,2) SumOfSqs, WavEnLH_s_2, and ADC are risk factors for advanced tumors, and the logistic model built by Kep, Ve, S(0,2)SumOfSqs, WavEnLH_s_2, and ADC has the AUC, sensitivity, and specificity of 0.833, 88.5%, and 73.3%, respectively. ROC curve of the model showed statistical significance between S(0,2)SumOfSqs, ADC, Kep, and Ve. The P value of the Hosmer–Lemeshow test was 0.65.CONCLUSIONS(0,2)SumOfSqs, WavEnLH_s_2, and ADC are risk factors for advanced rectal cancer, and the model built by Kep, Ve, S(0,2)SumOfSqs, WavEnLH_s_2, and ADC has better performance than using a single method. The application of above combinations could be beneficial to patients’ accurate and individualized treatments

Hydrolysates of whole forage-fish and Pacific krill are useful to reduce fish meal in practical diets for largemouth bass (Micropterus salmoides), and dietary fish hydrolysate suppresses expressions of intestinal oligopeptide transporter and taurine transporter genes

publishedVersio

Current understanding of CTLA-4: from mechanism to autoimmune diseases

Autoimmune diseases (ADs) are characterized by the production of autoreactive lymphocytes, immune responses to self-antigens, and inflammation in related tissues and organs. Cytotoxic T-lymphocyte antigen 4 (CTLA-4) is majorly expressed in activated T cells and works as a critical regulator in the inflammatory response. In this review, we first describe the structure, expression, and how the signaling pathways of CTLA-4 participate in reducing effector T-cell activity and enhancing the immunomodulatory ability of regulatory T (Treg) cells to reduce immune response, maintain immune homeostasis, and maintain autoimmune silence. We then focused on the correlation between CTLA-4 and different ADs and how this molecule regulates the immune activity of the diseases and inhibits the onset, progression, and pathology of various ADs. Finally, we summarized the current progress of CTLA-4 as a therapeutic target for various ADs

Co-creation using crowdsourcing to promote PrEP adherence in China: study protocol for a stepped-wedge randomized controlled trial.

BACKGROUND: Adherent pre-exposure prophylaxis (PrEP) uptake can prevent HIV infections. Despite the high HIV incidence, Chinese key populations have low PrEP uptake and adherence. New interventions are needed to increase PrEP adherence among key populations in China. Co-creation methods are helpful to solicit ideas from the community to solve public health problems. The study protocol aims to describe the design of a stepped-wedge trial and to evaluate the efficacy of co-created interventions to facilitate PrEP adherence among key populations in China. METHODS: The study will develop intervention packages to facilitate PrEP adherence among Chinese key populations using co-creation methods. The study will then evaluate the efficacy of the co-created intervention packages using a stepped-wedge randomized controlled trial. This four-phased closed cohort stepped-wedge design will have four clusters. Each cluster will start intervention at three-month intervals. Seven hundred participants who initiated PrEP will be recruited. Participants will be randomized to the clusters using block randomization. The intervention condition includes receiving co-created interventions in addition to standard of care. The control condition is the standard of care that includes routine clinical assessment every 3 months. All participants will also receive an online follow-up survey every 3 months to record medication adherence and will be encouraged to use a WeChat mini-app for sexual and mental health education throughout the study. The primary outcomes are PrEP adherence and retention in PrEP care throughout the study period. We will examine a hypothesis that a co-created intervention can facilitate PrEP adherence. Generalized linear mixed models will be used for the primary outcome analysis. DISCUSSION: Developing PrEP adherence interventions in China faces barriers including suboptimal PrEP uptake among key populations, the lack of effective PrEP service delivery models, and insufficient community engagement in PrEP initiatives. Our study design addresses these obstacles by using co-creation to generate social media-based intervention materials and embedding the study design in the local healthcare system. The study outcomes may have implications for policy and intervention practices among CBOs and the medical system to facilitate PrEP adherence among key populations. TRIAL REGISTRATION: The study is registered in Clinical Trial databases in China (ChiCTR2100048981, July 19, 2021) and the US (NCT04754139, February 11, 2021)

Intraocular complement activation is related to retinal vascular and neuronal degeneration in myopic retinopathy

PurposeTo investigate the relationship between the intraocular levels of complement proteins and myopia-related retinal neuronal and vascular degeneration.MethodsAqueous humour from 147 myopic patients, including 60 low-myopia and 87 high-myopia were collected during Implantable Collamer Lens implantation surgery. All participants received comprehensive ophthalmic examinations, including logMAR best corrected visual acuity, axial length measurement, fundus photography and ocular B-scan ultrasonography. The myopic eyes were further classified into simple myopia (SM, n = 78), myopic posterior staphyloma (PS, n = 39) and PS with myopic chorioretinal atrophy (PS + CA, n = 30). Retinal thickness and vascular density in the macula (6 mm × 6 mm) and optic nerve head (4.5 mm × 4.5 mm) were measured using Optical Coherence Tomography (OCT) and OCT angiography (OCTA). The levels of complement proteins including C1q, C3, C3b/iC3b, C4, CFB, CFH, C2, C4b, C5, C5a, CFD, MBL and CFI in the aqueous humour were measured using the Luminex Multiplexing system. The real-time RT-PCR was conducted to examine the expression of complement genes (C1q, C2, C3, C4, CFI and CFD) in the guinea pig model of long-term form deprivation-induced myopic retinal degeneration.ResultsOCTA showed that retinal neuronal thickness and vascular density in superficial and deep layers of the macular zone as well as vascular density in the optic nerve head were progressively decreased from SM to PS and PS + CA (p < 0.05). The aqueous humour levels of C1q, C3, C3b/iC3b, C4, CFB, CFH, C2, C4b, C5 and CFI were significantly higher in high-myopic eyes compared to those in low-myopic eyes. Further subgroup analysis revealed the highest levels of complement components/fragments in the PS + CA group. The intraocular levels of complement factors particularly C3b/iC3b and C4 were negatively correlated with macular zone deep layer retinal thickness and vascular density and optic nerve head vascular density. The expression of C2, C3 and C4 genes was significantly higher in guinea pig eyes with myopic retinal degeneration compared to control eyes.ConclusionsThe intraocular classical pathway and alternative pathway of the complement system are partially activated in pathological myopia. Their activation is related to the degeneration of retinal neurons and the vasculature in the macula and the vasculature in the optic nerve head

A Non-Specific Effect Associated with Conditional Transgene Expression Based on Cre-loxP Strategy in Mice

Transgenes flanked by loxP sites have been widely used to generate transgenic mice where the transgene expression can be controlled spatially and temporally by Cre recombinase. Data from this approach has led to important conclusions in cancer, neurodevelopment and neurodegeneration. Using this approach to conditionally express micro RNAs (miRNAs) in mice, we found that Cre-mediated recombination in neural progenitor cells caused microcephaly in five of our ten independent transgenic lines. This effect was not associated with the types or the quantity of miRNAs being expressed, nor was it associated with specific target knockdown. Rather, it was correlated with the presence of multiple tandem transgene copies and inverted (head-to-head or tail-to-tail) transgene repeats. The presence of these inverted repeats caused a high level of cell death in the ventricular zone of the embryonic brain, where Cre was expressed. Therefore, results from this Cre-loxP approach to generate inducible transgenic alleles must be interpreted with caution and conclusions drawn in previous reports may need reexamination

A quasi-Newton algorithm for large-scale nonlinear equations

Abstract In this paper, the algorithm for large-scale nonlinear equations is designed by the following steps: (i) a conjugate gradient (CG) algorithm is designed as a sub-algorithm to obtain the initial points of the main algorithm, where the sub-algorithm’s initial point does not have any restrictions; (ii) a quasi-Newton algorithm with the initial points given by sub-algorithm is defined as main algorithm, where a new nonmonotone line search technique is presented to get the step length α k $\alpha_{k}$ . The given nonmonotone line search technique can avoid computing the Jacobian matrix. The global convergence and the 1 + q $1+q$ -order convergent rate of the main algorithm are established under suitable conditions. Numerical results show that the proposed method is competitive with a similar method for large-scale problems

A Moving Object Detection Method Using Deep Learning-Based Wireless Sensor Networks

Aiming at the problem of real-time detection and location of moving objects, the deep learning algorithm is used to detect moving objects in complex situations. In this paper, based on the deep learning algorithm of wireless sensor networks, a novel target motion detection method is proposed. This method uses the deep learning model to extract visual potential representation features through offline similarity function ranking learning and online model incremental update and uses the hierarchical clustering algorithm to achieve target detection and positioning; the low-precision histogram and high-precision histogram cascade the method which determines the correct position of the target and achieves the purpose of detecting the moving target. In order to verify the advantages and disadvantages of the deep learning algorithm compared with traditional moving object detection methods, a large number of comparative experiments are carried out, and the experimental results were analyzed qualitatively and quantitatively from a statistical perspective. The results show that, compared with the traditional methods, the deep learning algorithm based on the wireless sensor network proposed in this paper is more efficient. The detection and positioning method do not produce the error accumulation phenomenon and has significant advantages and robustness. The moving target can be accurately detected with a small computational cost