Purpose
The purpose of this paper is to empirically examine the mediating role of potential and realized absorptive capacity in intellectual capital (IC) and business performance. It also ...investigates the direct impact of the components of IC on business performance.
Design/methodology/approach
Partial least square-structural equation modeling (PLS-SEM) was used to assess the effect of IC dimensions on performance and to analyze the mediating role of absorptive capacity in this relationship. Data were collected from 192 managers using a survey questionnaire with Likert scale items.
Findings
The findings of the study show that potential absorptive capacity does not intervene in the relationship between the components of IC and those of business performance. However, realized absorptive capacity, measured as the transformation and exploitation of knowledge, played a positive mediating role in the relationship between the dimensions of IC and those of business performance. Social capital was also noted as a weak predictor of business performance, while human capital and organizational capital had a profound positive influence.
Originality/value
This study contributes to the literature on IC by examining the role of realized and potential absorptive capacity in the relationship between IC components and firm performance. This research also helps practitioners recognize the importance of transformation and the exploitation of knowledge for business performance.
While retrograde cargo selection in the Golgi is known to depend on specific signals, it is unknown whether anterograde cargo is sorted, and anterograde signals have not been identified. We suggest ...here that S-palmitoylation of anterograde cargo at the Golgi membrane interface is an anterograde signal and that it results in concentration in curved regions at the Golgi rims by simple physical chemistry. The rate of transport across the Golgi of two S-palmitoylated membrane proteins is controlled by S-palmitoylation. The bulk of S-palmitoylated proteins in the Golgi behave analogously, as revealed by click chemistry-based fluorescence and electron microscopy. These palmitoylated cargos concentrate in the most highly curved regions of the Golgi membranes, including the fenestrated perimeters of cisternae and associated vesicles. A palmitoylated transmembrane domain behaves similarly in model systems.
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•DHHC S-palmitoyltransferases are enriched in the cis-Golgi•S-palmitoylation induces concentration of membrane cargo at the cisternal rim•The rate of anterograde transport across the Golgi is controlled by S-palmitoylation
Examples exist of secretory pathway receptor-mediated protein sorting for retrograde cargo, but not for anterograde. Ernst et al. uncover an anterograde cargo sorting mechanism: S-palmitoylation at the Golgi acts as a biophysical switch that induces “self-sorting” of membrane cargo to the cisternal rim, enabling its efficient transport through the Golgi.
Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during ...antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.
PurposeThe study aims to examine the mediating role of psychological empowerment and job crafting between servant leadership and innovative work behavior.Design/methodology/approachThe data were ...collected from 689 knowledge workers employed in Pakistan's service industry. The data collection was done through survey design. The data analysis was done through structural equation modeling using PLS-Smart.FindingsServant leadership was found to be related to psychological empowerment, job crafting and innovative work behavior of the employees. Job crafting was found to be mediating between servant leadership and innovative work behavior. Additionally, psychological empowerment and job crafting were found to be sequential mediators between servant leadership and innovative work behavior.Originality/valueThe study delineated the link mechanism between servant leadership and innovative work behavior.
Membranes have been used for treating periodontal defects and play a crucial role in guided bone regeneration applications. Nano graphene oxide have been exploited in tissue engineering due to its ...biomechanical properties. Its composite formulations with hydroxyapatite and chitosan with controlled degradation could aid in becoming part of a surface layer in a functionally graded membrane. The aim of the study was to synthesize chitosan and composite formulations of nano graphene oxide, hydroxyapatite and chlorhexidine digluconate using solvent casting technique and to characterize the physiochemical, mechanical, water vapor transmission rate (barrier), degradation and antimicrobial potential of the membranes. Altogether four different membranes were prepared (CH, CCG, 3511 and 3322). Results revealed the chemical interactions of hydroxyapatite, chitosan and nanographene oxide due to inter and intra molecular hydrogen bonding. The tensile strength of 3322 (33.72 ± 6.3 MPa) and 3511 (32.06 ± 5.4 MPa) was higher than CH (27.46 ± 9.6 MPa). CCG showed the lowest water vapor transmission rate (0.23 ± 0.01 g/h.m
2
) but the highest weight loss at day 14 (76.6 %). 3511 showed a higher drug release after 72 h (55.6 %) Significant biofilm growth inhibition was observed for all membranes. 3511 showed complete inhibition against
A. actinomycetemcomitans
. Detailed characterization of the synthesized membranes revealed that 3511 composite membrane proved to be a promising candidate for use as a surface layer of membranes for guided bone regeneration of periodontal lesions.
Graphical Abstract
Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional ...screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new antibacterial molecules. Here we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE. Moreover, abaucin could control an A. baumannii infection in a mouse wound model. This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen.
Brain magnetic resonance imaging (MRI) scans are available in a wide variety of sequences, view planes, and magnet strengths. A necessary preprocessing step for any automated diagnosis is to identify ...the MRI sequence, view plane, and magnet strength of the acquired image. Automatic identification of the MRI sequence can be useful in labeling massive online datasets used by data scientists in the design and development of computer aided diagnosis (CAD) tools. This paper presents a deep learning (DL) approach for brain MRI sequence and view plane identification using scans of different data types as input. A 12-class classification system is presented for commonly used MRI scans, including T1, T2-weighted, proton density (PD), fluid attenuated inversion recovery (FLAIR) sequences in axial, coronal and sagittal view planes. Multiple online publicly available datasets have been used to train the system, with multiple infrastructures. MobileNet-v2 offers an adequate performance accuracy of 99.76% with unprocessed MRI scans and a comparable accuracy with skull-stripped scans and has been deployed in a tool for public use. The tool has been tested on unseen data from online and hospital sources with a satisfactory performance accuracy of 99.84 and 86.49%, respectively.
Major depressive disorder (MDD), a debilitating mental illness, could cause functional disabilities and could become a social problem. An accurate and early diagnosis for depression could become ...challenging. This paper proposed a machine learning framework involving EEG-derived synchronization likelihood (SL) features as input data for automatic diagnosis of MDD. It was hypothesized that EEG-based SL features could discriminate MDD patients and healthy controls with an acceptable accuracy better than measures such as interhemispheric coherence and mutual information. In this work, classification models such as support vector machine (SVM), logistic regression (LR) and Naïve Bayesian (NB) were employed to model relationship between the EEG features and the study groups (MDD patient and healthy controls) and ultimately achieved discrimination of study participants. The results indicated that the classification rates were better than chance. More specifically, the study resulted into SVM classification accuracy = 98%, sensitivity = 99.9%, specificity = 95% and
f
-measure = 0.97; LR classification accuracy = 91.7%, sensitivity = 86.66%, specificity = 96.6% and f-measure = 0.90; NB classification accuracy = 93.6%, sensitivity = 100%, specificity = 87.9% and
f
-measure = 0.95. In conclusion, SL could be a promising method for diagnosing depression. The findings could be generalized to develop a robust CAD-based tool that may help for clinical purposes.
Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Next to progressive airway disease, CF is also associated with intestinal ...inflammation and dysbiosis. Ivacaftor, a CFTR potentiator, has improved pulmonary and nutritional status but its effects on the intestinal microbiota and inflammation are unclear. Hence, we assessed the changes on the intestinal microbial communities (16S rRNA variable 3 gene region) and inflammatory markers (calprotectin and M2-pyruvate kinase M2-PK) in 16 CF individuals (8 children and 8 adults) before and after (median 6.1 months) ivacaftor. Stool calprotectin significantly decreased following ivacaftor (median IQR: 154.4 102.1-284.2 vs. 87.5 19.5-190.2 mg/kg, P = 0.03). There was a significant increase in Akkermansia with ivacaftor. Increased abundance of Akkermansia was associated with normal stool M2-PK concentrations, and decreased abundances of Enterobacteriaceae correlated with decreased stool calprotectin concentrations. In summary, changes in the gut microbiome and decrease in intestinal inflammation was associated with Ivacaftor treatment among individuals with CF carrying at least one gating CFTR mutation. Thus, CFTR-modifying therapy may adequately improve the aberrant pathophysiology and milieu of the CF gut to favor a more healthy microbiota, which in turn reduces intestinal inflammation.
Background
The aim of this systematic review and meta‐analyses was to assess the quality of evidence and efficacy of antimicrobial photodynamic therapy (aPDT) and laser irradiation (LI) as an adjunct ...to open flap debridement (OFD) in the treatment of chronic periodontitis.
Methods
Electronic searches were conducted in databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Cochrane Oral Health Group Trials Register databases) up to March 2019. Randomized clinical trials (RCTs) comparing clinical efficacy of either aPDT and/or LI, placebo, or no treatment were included. Primary outcomes included clinical attachment level (CAL), while secondary outcomes were reduction in probing depth (PD) and gingival recession (GR) depth. The weighted mean differences (WMD) of outcomes and 95% confidence intervals (CI) for each variable were calculated using random effect model.
Results
Six RCTs were included. For aPDT studies, the overall mean difference for CAL gain (WMD = −0.61, 95% CI = −1.22 to −0.016, P = .044) and PD reduction (WMD = −1.79, 95% CI = −3.44 to −0.14, P = .034) was significant between aPDT and OFD groups at follow‐up. No significant overall mean difference was observed for GR depth (WMD = 0.02, 95% CI = −0.75 to 0.79, P = .95). For LI studies, none of the clinical periodontal parameters including CAL gain (WMD = 0.23, 95% CI = −0.09 to 0.55, P = .159, Figure 3A), PD reduction (WMD = 0.31, 95% CI = −0.67 to 1.31, P = .52, Figure 3B) and GR depth (WMD = −0.34, 95% CI = −2.47 to 1.78, P = .74, Figure 3C) were found to be significant between LI and OFD groups at follow‐up.
Conclusion
With the limited data available, only aPDT as an adjunct to OFD showed superior results for clinical periodontal parameters compared to OFD alone in the treatment of chronic periodontitis. Further RCTs are warranted in order to obtain robust conclusions with regard to laser therapy.
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