Perspectives of community pharmacists on extended pharmacy services and value-added services in Malaysia: a cross-sectional survey

Objective This study aimed to investigate patterns of extended pharmacy services (EPS) provided by Malaysian community pharmacists and their willingness to provide value-added services (VAS) in addition to EPS. Additionally, this study examined the barriers to the effective implementation of these two services. Method A cross-sectional survey was conducted using a self-administered questionnaire among community pharmacists in Selangor and Kuala Lumpur. Convenience sampling was done, and descriptive statistics and correlation analysis were performed. Results Two hundred and thirty-six pharmacists participated. The most rendered EPS were nutritional supplements, hypertension management, and diabetic management, while chronic kidney disease management, smoking cessation, and mental health services were the least rendered. Pharmacists were willing to provide medication waste management and vaccination as VAS but were less inclined towards therapeutic drug monitoring and sterile compounding. Barriers included limited access to medical records of patients, lack of designated counselling areas, and concerns about remuneration. High sales pressure and busy workloads were additional barriers to providing VAS. Continuous professional development (CPD) positively influenced pharmacists’ engagement in EPS and VAS. Conclusions This study highlights service provision trends and areas for improvement. Addressing identified barriers, such as enhancing access to patient records and establishing designated counselling areas, can improve service delivery. Remuneration models and workload management strategies should be considered to alleviate barriers related to sales pressure and time constraints. Promoting CPD opportunities is crucial for enhancing pharmacist engagement and optimizing EPS and VAS

A sparse Bayesian learning method for structural equation model-based gene regulatory network inference

Gene regulatory networks (GRNs) are underlying networks identified by interactive relationships between genes. Reconstructing GRNs from massive genetic data is important for understanding gene functions and biological mechanism, and can provide effective service for medical treatment and genetic research. A series of artificial intelligence based methods have been proposed to infer GRNs from both gene expression data and genetic perturbations. The accuracy of such algorithms can be better than those models that just consider gene expression data. A structural equation model (SEM), which provides a systematic framework integrating both types of gene data conveniently, is a commonly used model for GRN inference. Considering the sparsity of GRNs, in this paper, we develop a novel sparse Bayesian inference algorithm based on Normal-Equation-Gamma (NEG) type hierarchical prior (BaNEG) to infer GRNs modeled with SEMs more accurately. First, we reparameterize an SEM as a linear type model by integrating the endogenous and exogenous variables; Then, a Bayesian adaptive lasso with a three-level NEG prior is applied to deduce the corresponding posterior mode and estimate the parameters. Simulations on synthetic data are run to compare the performance of BaNEG to some state-of-the-art algorithms, the results demonstrate that the proposed algorithm visibly outperforms the others. What’s more, BaNEG is applied to infer underlying GRNs from a real data set composed of 47 yeast genes from Saccharomyces cerevisiae to discover potential relationships between genes

The Social Relationship Based Adaptive Multi-Spray-and-Wait Routing Algorithm for Disruption Tolerant Network

The existing spray-based routing algorithms in DTN cannot dynamically adjust the number of message copies based on actual conditions, which results in a waste of resource and a reduction of the message delivery rate. Besides, the existing spray-based routing protocols may result in blind spots or dead end problems due to the limitation of various given metrics. Therefore, this paper proposes a social relationship based adaptive multiple spray-and-wait routing algorithm (called SRAMSW) which retransmits the message copies based on their residence times in the node via buffer management and selects forwarders based on the social relationship. By these means, the proposed algorithm can remove the plight of the message congestion in the buffer and improve the probability of replicas to reach their destinations. The simulation results under different scenarios show that the SRAMSW algorithm can improve the message delivery rate and reduce the messages' dwell time in the cache and further improve the buffer effectively

The human language effective connectome

To advance understanding of brain networks involved in language, the effective connectivity between 26 cortical regions implicated in language by a community analysis and 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography, all using the HCP multimodal parcellation atlas. A (semantic) network (Group 1) involving inferior cortical regions of the superior temporal sulcus cortex (STS) with the adjacent inferior temporal visual cortex TE1a and temporal pole TG, and the connected parietal PGi region, has effective connectivity with inferior temporal visual cortex (TE) regions; with parietal PFm which also has visual connectivity; with posterior cingulate cortex memory-related regions; with the frontal pole, orbitofrontal cortex, and medial prefrontal cortex; with the dorsolateral prefrontal cortex; and with 44 and 45 for output regions. It is proposed that this system can build in its temporal lobe (STS and TG) and parietal parts (PGi and PGs) semantic representations of objects incorporating especially their visual and reward properties. Another (semantic) network (Group 3) involving superior regions of the superior temporal sulcus cortex and more superior temporal lobe regions including STGa, auditory A5, TPOJ1, the STV and the Peri-Sylvian Language area (PSL) has effective connectivity with auditory areas (A1, A4, A5, Pbelt); with relatively early visual areas involved in motion, e.g., MT and MST, and faces/words (FFC); with somatosensory regions (frontal opercular FOP, insula and parietal PF); with other TPOJ regions; and with the inferior frontal gyrus regions (IFJa and IFSp). It is proposed that this system builds semantic representations specialising in auditory and related facial motion information useful in theory of mind and somatosensory / body image information, with outputs directed not only to regions 44 and 45, but also to premotor 55b and midcingulate premotor cortex. Both semantic networks (Groups 1 and 3) have access to the hippocampal episodic memory system via parahippocampal TF. A third largely frontal network (Group 2) (44, 45, 47l; 55b; the Superior Frontal Language region SFL; and including temporal pole TGv) receives effective connectivity from the two semantic systems, and is implicated in syntax and speech output

Novel peptide–dendrimer conjugates as drug carriers for targeting nonsmall cell lung cancer

Phage display technology has been demonstrated to be a powerful tool for screening useful ligands that are capable of specifically binding to biomarkers on the surface of tumor cells. The ligands found by this technique, such as peptides, have been successfully applied in the fields of early cancer diagnostics and chemotherapy. In this study, a novel nonsmall cell lung cancer-targeting peptide (LCTP, sequence RCPLSHSLICY) was screened in vivo using a Ph.D.-C7C™ phage display library. In order to develop a universal tumor-targeting drug carrier, the LCTP and fluorescence-labeled molecule (FITC) were conjugated to an acetylated polyamidoamine (PAMAM) dendrimer of generation 4 (G4) to form a PAMAM–Ac–FITC–LCTP conjugate. The performance of the conjugate was first tested in vitro. In vitro results of cell experiments analyzed by flow cytometry and inverted fluorescence microscopy indicated that PAMAM–Ac–FITC–LCTP was enriched more in NCI-H460 cells than in 293T cells, and cellular uptake was both time- and dose-dependent. The tissue distribution of the conjugate in athymic mice with lung cancer xenografts was also investigated to test the targeting efficiency of PAMAM–Ac–FITC–LCTP in vivo. The results showed that LCTP can effectively facilitate the targeting of PAMAM–Ac–FITC–LCTP to nonsmall cell lung cancer cells and tumors. These results suggest that the LCTP-conjugated PAMAM dendrimer might be a promising drug carrier for targeted cancer diagnosis and treatment

The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation

The human posterior cingulate, retrosplenial, and medial parietal cortex are involved in memory and navigation. The functional anatomy underlying these cognitive functions was investigated by measuring the effective connectivity of these Posterior Cingulate Division (PCD) regions in the Human Connectome Project-MMP1 atlas in 171 HCP participants, and complemented with functional connectivity and diffusion tractography. First, the postero-ventral parts of the PCD (31pd, 31pv, 7m, d23ab, and v23ab) have effective connectivity with the temporal pole, inferior temporal visual cortex, cortex in the superior temporal sulcus implicated in auditory and semantic processing, with the reward-related vmPFC and pregenual anterior cingulate cortex, with the inferior parietal cortex, and with the hippocampal system. This connectivity implicates it in hippocampal episodic memory, providing routes for “what,” reward and semantic schema-related information to access the hippocampus. Second, the antero-dorsal parts of the PCD (especially 31a and 23d, PCV, and also RSC) have connectivity with early visual cortical areas including those that represent spatial scenes, with the superior parietal cortex, with the pregenual anterior cingulate cortex, and with the hippocampal system. This connectivity implicates it in the “where” component for hippocampal episodic memory and for spatial navigation. The dorsal–transitional–visual (DVT) and ProStriate regions where the retrosplenial scene area is located have connectivity from early visual cortical areas to the parahippocampal scene area, providing a ventromedial route for spatial scene information to reach the hippocampus. These connectivities provide important routes for “what,” reward, and “where” scene-related information for human hippocampal episodic memory and navigation. The midcingulate cortex provides a route from the anterior dorsal parts of the PCD and the supracallosal part of the anterior cingulate cortex to premotor regions

Clinical Comparison of Outcomes of Early versus Delayed Carotid Artery Stenting for Symptomatic Cerebral Watershed Infarction due to Stenosis of the Proximal Internal Carotid Artery

The aim of this study was to compare the clinical outcomes of early versus delayed carotid artery stenting (CAS) for symptomatic cerebral watershed infarction (sCWI) patients due to stenosis of the proximal internal carotid artery. We retrospectively collected clinical data of those who underwent early or delayed CAS from March 2011 to April 2014. The time of early CAS and delayed CAS was within a week of symptom onset and after four weeks from symptom onset. Clinical data such as second stroke, the National Institutes of Health Stroke Scale (NHISS) score, and modified Rankin Scale (mRS) score and periprocedural complications were collected. The rate of second stroke in early CAS group is lower when compared to that of delayed CAS group. There was no significant difference regarding periprocedural complications in both groups. There was a significant difference regarding mean NHISS score 90 days after CAS in two groups. Early CAS group had a significant better good outcome (mRS score ≤ 2) than delayed CAS group. We suggest early CAS for sCWI due to severe proximal internal carotid artery stenosis as it provides lower rate of second stroke, comparable periprocedural complications, and better functional outcomes compared to that of delayed CAS

A powerful and efficient multivariate approach for voxel-level connectome-wide association studies

We describe an approach to multivariate analysis, termed structured kernel principal component regression (sKPCR), to identify associations in voxel-level connectomes using resting-state functional magnetic resonance imaging (rsfMRI) data. This powerful and computationally efficient multivariate method can identify voxel-phenotype associations based on the whole-brain connectivity pattern of voxels, and it can detect linear and non-linear signals in both volume-based and surface-based rsfMRI data. For each voxel, sKPCR first extracts low-dimensional signals from the spatially smoothed connectivities by structured kernel principal component analysis, and then tests the voxel-phenotype associations by an adaptive regression model. The method's power is derived from appropriately modelling the spatial structure of the data when performing dimension reduction, and then adaptively choosing an optimal dimension for association testing using the adaptive regression strategy. Simulations based on real connectome data have shown that sKPCR can accurately control the false-positive rate and that it is more powerful than many state-of-the-art approaches, such as the connectivity-wise generalized linear model (GLM) approach, multivariate distance matrix regression (MDMR), adaptive sum of powered score (aSPU) test, and least-square kernel machine (LSKM). Moreover, since sKPCR can reduce the computational cost of non-parametric permutation tests, its computation speed is much faster. To demonstrate the utility of sKPCR for real data analysis, we have also compared sKPCR with the above methods based on the identification of voxel-wise differences between schizophrenic patients and healthy controls in four independent rsfMRI datasets. The results showed that sKPCR had better between-sites reproducibility and a larger proportion of overlap with existing schizophrenia meta-analysis findings. Code for our approach can be downloaded from https://github.com/weikanggong/sKPCR. [Abstract copyright: Copyright © 2018 Elsevier Inc. All rights reserved.