Networked Federated Learning

We develop the theory and algorithmic toolbox for networked federated learning in decentralized collections of local datasets with an intrinsic network structure. This network structure arises from domain-specific notions of similarity between local datasets. Different notions of similarity are induced by spatio-temporal proximity, statistical dependencies or functional relations. Our main conceptual contribution is to formulate networked federated learning using a generalized total variation minimization. This formulation unifies and considerably extends existing federated multi-task learning methods. It is highly flexible and can be combined with a broad range of parametric models including Lasso or deep neural networks. Our main algorithmic contribution is a novel networked federated learning algorithm which is well suited for distributed computing environments such as edge computing over wireless networks. This algorithm is robust against inexact computations arising from limited computational resources including processing time or bandwidth. For local models resulting in convex problems, we derive precise conditions on the local models and their network structure such that our algorithm learns nearly optimal local models. Our analysis reveals an interesting interplay between the convex geometry of local models and the (cluster-) geometry of their network structure

The Saudi National Mental Health Survey: Sample design and weight development

ObjectivesTo describe the sample design and weighting procedures used in the Saudi National Mental Health Survey (SNMHS).MethodsA multistage clustered area probability design was used to select the SNMHS sample with one male and one female KSA citizen ages 15- 65 surveyed in each sample household.ResultsA design representative of the household population was developed and modified iteratively to adjust for unanticipated field complications. These modifications, along with variation in within- household probabilities of selection and geographic- demographic variation in response rates were accounted for through survey weights. Design- based estimation methods were used to adjust for the effects of these weights and of geographic clustering. Design effects were estimated and simulations were carried out on bias- variancetrade- offs in weight trimming to evaluate the implication of design features for precision of estimates.ConclusionsThe multiple purposes of the survey will require the use of different weights for different types of analyses, including household and person weights as well as weights for proxy reports about household members whose disabilities prevented them from participating in the survey. It will be important to use these different weights appropriately in the diverse analyses that will be undertaken with the SNMHS data.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162744/2/mpr1829.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162744/1/mpr1829_am.pd

Implementing the TRAPD model for the Saudi adaptation of the World Mental Health Composite International Diagnostic Interview 3.0

Abstract Background The World Mental Health-Composite International Diagnostic Interview (CIDI) 3.0, originally in English, is a fully-structured interview designed for the assessment of mental disorders. Although Arabic translations of CIDI from countries like Lebanon and Iraq exist, a Modern Standard Arabic translation was developed to suit the Saudi population. While the translation model used in the present paper has been used to translate instruments in Asian and European languages, there is no study to the best of our knowledge which has used this specific model to translate a validated instrument from English to Arabic. Case presentation This paper describes the Saudi adaptation of CIDI 3.0. The TRAPD team translation model—comprising of translation, review, adjudication, pretesting and documentation—was implemented to carry out the Saudi adaptation of CIDI 3.0. Pretests involving cognitive interviewing and pilot study led to translation revisions which consequently confirmed that Saudi respondents had a good understanding of various items of the instrument. The adaptation procedures for the Saudi CIDI 3.0 were well documented and the instrument was linguistically validated with the Saudi population. Conclusion The TRAPD model was successfully implemented to adapt the CIDI 3.0 to be used as the main survey instrument for the Saudi National Mental Health Survey, findings of which will provide health policy makers mental health indicators for health decision making and planning.https://deepblue.lib.umich.edu/bitstream/2027.42/148144/1/13033_2019_Article_267.pd

Targeting autophagy by small molecule inhibitors of vacuolar protein sorting 34 (Vps34) improves the sensitivity of breast cancer cells to Sunitinib

Resistance to chemotherapy is a challenging problem for treatment of cancer patients and autophagy has been shown to mediate development of resistance. In this study we systematically screened a library of 306 known anti-cancer drugs for their ability to induce autophagy using a cell-based assay. 114 of the drugs were classified as autophagy inducers; for 16 drugs, the cytotoxicity was potentiated by siRNA-mediated knock-down of Atg7 and Vps34. These drugs were further evaluated in breast cancer cell lines for autophagy induction, and two tyrosine kinase inhibitors, Sunitinib and Erlotinib, were selected for further studies. For the pharmacological inhibition of autophagy, we have characterized here a novel highly potent selective inhibitor of Vps34, SB02024. SB02024 blocked autophagy in vitro and reduced xenograft growth of two breast cancer cell lines, MDA-MB-231 and MCF-7, in vivo. Vps34 inhibitor significantly potentiated cytotoxicity of Sunitinib and Erlotinib in MCF-7 and MDA-MB-231 in vitro in monolayer cultures and when grown as multicellular spheroids. Our data suggests that inhibition of autophagy significantly improves sensitivity to Sunitinib and Erlotinib and that Vps34 is a promising therapeutic target for combination strategies in breast cancer.Peer reviewe

Patient-level performance evaluation of a smartphone-based malaria diagnostic application

Background Microscopic examination is commonly used for malaria diagnosis in the field. However, the lack of well-trained microscopists in malaria-endemic areas impacted the most by the disease is a severe problem. Besides, the examination process is time-consuming and prone to human error. Automated diagnostic systems based on machine learning offer great potential to overcome these problems. This study aims to evaluate Malaria Screener, a smartphone-based application for malaria diagnosis. Methods A total of 190 patients were recruited at two sites in rural areas near Khartoum, Sudan. The Malaria Screener mobile application was deployed to screen Giemsa-stained blood smears. Both expert microscopy and nested PCR were performed to use as reference standards. First, Malaria Screener was evaluated using the two reference standards. Then, during post-study experiments, the evaluation was repeated for a newly developed algorithm, PlasmodiumVF-Net. Results Malaria Screener reached 74.1% (95% CI 63.5–83.0) accuracy in detecting Plasmodium falciparum malaria using expert microscopy as the reference after a threshold calibration. It reached 71.8% (95% CI 61.0–81.0) accuracy when compared with PCR. The achieved accuracies meet the WHO Level 3 requirement for parasite detection. The processing time for each smear varies from 5 to 15 min, depending on the concentration of white blood cells (WBCs). In the post-study experiment, Malaria Screener reached 91.8% (95% CI 83.8–96.6) accuracy when patient-level results were calculated with a different method. This accuracy meets the WHO Level 1 requirement for parasite detection. In addition, PlasmodiumVF-Net, a newly developed algorithm, reached 83.1% (95% CI 77.0–88.1) accuracy when compared with expert microscopy and 81.0% (95% CI 74.6–86.3) accuracy when compared with PCR, reaching the WHO Level 2 requirement for detecting both Plasmodium falciparum and Plasmodium vivax malaria, without using the testing sites data for training or calibration. Results reported for both Malaria Screener and PlasmodiumVF-Net used thick smears for diagnosis. In this paper, both systems were not assessed in species identification and parasite counting, which are still under development. Conclusion Malaria Screener showed the potential to be deployed in resource-limited areas to facilitate routine malaria screening. It is the first smartphone-based system for malaria diagnosis evaluated on the patient-level in a natural field environment. Thus, the results in the field reported here can serve as a reference for future studies

Gut Microbiota and Blood Metabolites Related to Fiber intake and Type 2 Diabetes

BACKGROUND: Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D). METHODS: This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years. RESULTS: We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, CONCLUSIONS: Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D

Stabilization of the RAS:PDE6D complex is a novel strategy to inhibit RAS signaling

This work was supported by Cancer Research UK core funding number A17196.RAS is a major anticancer drug target which requires membrane localization to activate downstream signal transduction. The direct inhibition of RAS has proven to be challenging. Here, we present a novel strategy for targeting RAS by stabilizing its interaction with the prenyl-binding protein PDE6D and disrupting its localization. Using rationally designed RAS point mutations, we were able to stabilize the RAS:PDE6D complex by increasing the affinity of RAS for PDE6D, which resulted in the redirection of RAS to the cytoplasm and the primary cilium and inhibition of oncogenic RAS/ERK signaling. We developed an SPR fragment screening and identified fragments that bind at the KRAS:PDE6D interface, as shown through cocrystal structures. Finally, we show that the stoichiometric ratios of KRAS:PDE6D vary in different cell lines, suggesting that the impact of this strategy might be cell-type-dependent. This study forms the foundation from which a potential anticancer small-molecule RAS:PDE6D complex stabilizer could be developed.Publisher PDFPeer reviewe

Simulation of frequency selection for invasive approach of electrical capacitance tomography for conducting pipe application using oil-gas regimes

Electrical capacitance tomography (ECT) is a common imaging technique in process tomography that has been used in various applications especially in pipe applications. It works by measuring the dielectric permittivity distribution in the interior of pipe using capacitive sensors. Based on the principle of ECT, signals are generated from transmitter and delivered to the right receiver using certain frequency. Assuming random selection of frequency could affect the wanted signal at the receivers, this paper will analyse the frequency selection ranged from 100 to 500 kHz with increment of 50 kHz thoroughly. The objective of this paper is to select the right frequency for the invasive approach of ECT for the conducting pipe applications using common parameter in ECT and oil-gas regimes as a medium. The frequency selection is observed using the voltage reading at each of the receivers and simulated using COMSOL Multiphysics software. Based on the results, the optimal frequency selection is 400 kHz where the best coverage area of sensor is 90%. This selection has the highest value of electrical voltage among other range proposed while the least electrical voltage produce is at frequency 300 kHz and coverage area of 50%

Peroxynitrate formed during a transient episode of brain ischemia increases endothelium-derived hyperpolarization-type dilations in thromboxane/prostaglandin receptor stimulated rat cerebral arteries

Aim Increased thromboxane A2 and peroxynitrite are hallmarks of cerebral ischemia/reperfusion (I/R). Stimulation of thromboxane/prostaglandin receptors (TP) attenuates endothelium-derived hyperpolarization (EDH). We investigated whether EDH-type middle cerebral artery (MCA) relaxations following TP stimulation are altered after I/R and the influence of peroxynitrite. Methods Vascular function was determined by wire myography after TP stimulation with the thromboxane A2 mimetic 9,11-Dideoxy-9α,11α-methano-epoxy prostaglandin F2α (U46619) in MCA of Sprague-Dawley rats subjected to MCA occlusion (90 min)/reperfusion (24 h) or sham operation, and in non-operated (control) rats. Some rats were treated with saline or the peroxynitrite decomposition catalyst 5,10,15,20-tetrakis(4-sulfonatophenyl)prophyrinato iron (III) (20 mg kg-1). Protein expression was evaluated in MCA and in human microvascular endothelial cells submitted to hypoxia (overnight)/reoxygenation (24 h) (H/R) using immunofluorescence and immunoblotting. Results In U46619-preconstricted MCA, EDH-type relaxation by the proteinase-activated receptor 2 agonist serine–leucine–isoleucine–glycine–arginine–leucine–NH2 (SLIGRL) was greater in I/R than sham rats due to an increased contribution of small-conductance calcium-activated potassium channels (SKCa), which was confirmed by the enlarged relaxation to the SKCa activator N-cyclohexyl-N-2-(3,5-dimethyl-pyrazol-1-yl)-6-methyl-4-pyrimidinamine. I/R and H/R induced endothelial protein tyrosine nitration and filamentous-actin disruption. In control MCA, either cytochalasin D or peroxynitrite disrupted endothelial filamentous-actin and augmented EDH-type relaxation. Furthermore, peroxynitrite decomposition during I/R prevented the increase in EDH-type responses. Conclusion Following TP stimulation in MCA, EDH-type relaxation to SLIGRL is greater after I/R due to endothelial filamentous-actin disruption by peroxynitrite, which prevents TP-induced block of SKCa input to EDH. These results reveal a novel mechanism whereby peroxynitrite could promote postischemic brain injury

The effects of material formulation and manufacturing process on mechanical and thermal properties of epoxy/clay nanocomposites

A holistic study was conducted to investigate the combined effect of three different pre-mixing processes, namely mechanical mixing, ultrasonication and centrifugation, on mechanical and thermal properties of epoxy/clay nanocomposites reinforced with different platelet-like montmorillonite (MMT) clays (Cloisite Na+, Cloisite 10A, Cloisite 15 or Cloisite 93A) at clay contents of 3–10 wt%. Furthermore, the effect of combined pre-mixing processes and material formulation on clay dispersion and corresponding material properties of resulting composites was investigated using X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), flexural and Charpy impact tests, Rockwell hardness tests and differential scanning calorimetry (DSC). A high level of clay agglomeration and partially intercalated/exfoliated clay structures were observed regardless of clay type and content. Epoxy/clay nanocomposites demonstrate an overall noticeable improvement of up to 10 % in the glass transition temperature (Tg) compared to that of neat epoxy, which is interpreted by the inclusion of MMT clays acting as rigid fillers to restrict the chain mobility of epoxy matrices. The impact strength of epoxy/clay nanocomposites was also found to increase by up to 24 % with the addition of 3 wt% Cloisite Na+ clays. However, their flexural strength and hardness diminished when compared to those of neat epoxy, arising from several effects including clay agglomeration, widely distributed microvoids and microcracks as well as weak interfacial bonding between clay particles and epoxy matrices, as confirmed from TEM and SEM results. Overall, it is suggested that an improved technique should be used for the combination of pre-mixing processes in order to achieve the optimal manufacturing condition of uniform clay dispersion and minimal void contents