Miracle-dz/UniFAR-FTUs huggingface dataset:
Diabetes in a Large Dementia Cohort: Clinical Characteristics and Treatment From the Swedish Dementia Registry

OBJECTIVE We aimed to investigate the differences in clinical characteristics and pharmacological treatment associated with the presence of diabetes in a large cohort of patients with dementia. RESEARCH DESIGN AND METHODS A cross-sectional registry-based study was conducted using data from the Swedish Dementia Registry (SveDem). Data on dementia diagnosis, dementia type, and demographic determinants were extracted from SveDem. Data from the Swedish Patient Register and Prescribed Drug Register were combined for the diagnosis of diabetes. Data on antidiabetic, dementia, cardiovascular, and psychotropic medications were extracted from the Swedish Prescribed Drug Register. Logistic regression was used to determine whether the variables were associated with diabetes after adjustment for confounders. In total, 29,630 patients were included in the study, and 4,881 (16.5%) of them received a diagnosis of diabetes. RESULTS In the fully adjusted model, diabetes was associated with lower age at dementia diagnosis (odds ratio [OR] 0.97 [99% CI 0.97–0.98]), male sex (1.41 [1.27–1.55]), vascular dementia (1.17 [1.01–1.36]), and mixed dementia (1.21 [1.06–1.39]). Dementia with Lewy bodies (0.64 [0.44–0.94]), Parkinson disease dementia (0.46 [0.28–0.75]), and treatment with antidepressants (0.85 [0.77–0.95]) were less common among patients with diabetes. Patients with diabetes who had Alzheimer disease obtained significantly less treatment with cholinesterase inhibitors (0.78 [0.63–0.95]) and memantine (0.68 [0.54–0.85]). CONCLUSIONS Patients with diabetes were younger at dementia diagnosis and obtained less dementia medication for Alzheimer disease, suggesting less optimal dementia treatment. Future research should evaluate survival and differences in metabolic profile in patients with diabetes and different dementia disorders.
Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases

Beta-lactamases represent the main bacterial mechanism of resistance to beta-lactam antibiotics and are a significant challenge to modern medicine. We have developed an automated classification and analysis protocol that exploits structure- and sequence-based approaches and which allows us to propose a grouping of serine beta-lactamases that more consistently captures and rationalizes the existing three classification schemes: Classes, (A, C and D, which vary in their implementation of the mechanism of action); Types (that largely reflect evolutionary distance measured by sequence similarity); and Variant groups (which largely correspond with the Bush-Jacoby clinical groups). Our analysis platform exploits a suite of in-house and public tools to identify Functional Determinants (FDs), i.e. residue sites, responsible for conferring different phenotypes between different classes, different types and different variants. We focused on Class A beta-lactamases, the most highly populated and clinically relevant class, to identify FDs implicated in the distinct phenotypes associated with different Class A Types and Variants. We show that our FunFHMMer method can separate the known beta-lactamase classes and identify those positions likely to be responsible for the different implementations of the mechanism of action in these enzymes. Two novel algorithms, ASSP and SSPA, allow detection of FD sites likely to contribute to the broadening of the substrate profiles. Using our approaches, we recognise 151 Class A types in UniProt. Finally, we used our beta-lactamase FunFams and ASSP profiles to detect 4 novel Class A types in microbiome samples. Our platforms have been validated by literature studies, in silico analysis and some targeted experimental verification. Although developed for the serine beta-lactamases they could be used to classify and analyse any diverse protein superfamily where sub-families have diverged over both long and short evolutionary timescales.
Towards the use of breath for detecting mycobacterial infection: a case study in a murine model

In the present research, the potential of breath analysis by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) was investigated for the discrimination between healthy and infected mice. A pilot study employing a total of 16 animals was used to develop a method for breath analysis in a murine model for studying Mycobacterium tuberculosis complex (MTBC) using the M. bovis bacillus Calmette-Guérin. Breath was collected in Tedlar bags and concentrated onto thermal desorption tubes for subsequent analysis by GC×GC-MS. Immunological test and bacterial cell count in bronchoalveolar lavage fluid and mice lung homogenate confirmed the presence of bacteria in the infected group. From the GC×GC-MS analysis, 23 molecules were found to mainly drive the separation between control and infected mice and their tentative identification is provided.This study shows that the overall used methodology is able to differentiate breath between healthy and infected animals, and the information herein can be used to further develop the mouse breath model to study MTBC pathogenesis, evaluate pre-clinical drug regimen efficacy, and to further develop the concept of breath-based diagnostics.
Patiromer Lowers Serum Potassium When Taken without Food: Comparison to Dosing with Food from an Open-Label, Randomized, Parallel Group Hyperkalemia Study

Background: Patiromer is a sodium-free, nonabsorbed, potassium binder approved for treatment of hyperkalemia. This open-label study compares the efficacy and safety of patiromer administered without food versus with food. Methods: Adults with hyperkalemia (potassium ≥5.0 mEq/L) were randomized (1:1) to receive patiromer once daily without food or with food for 4 weeks. The dosage was adjusted (maximum: 25.2 g/day) using a prespecified titration schedule to achieve and maintain potassium within a target range (3.8-5.0 mEq/L). The primary efficacy endpoint was the proportion of patients with serum potassium in the target range at either week 3 or week 4. Safety was assessed by adverse events (AEs) and laboratory testing. Results: Efficacy was evaluated in 112 patients; 65.2% were ≥65 years of age, 75.9% had chronic kidney disease, and 82.1% had diabetes. Baseline mean serum potassium was similar in the without-food (5.44 mEq/L) and with-food (5.34 mEq/L) groups. The primary endpoint was achieved by 87.3% (95% CI 75.5-94.7) and 82.5% (95% CI 70.1-91.3) of patients in the with-food and without-food groups, respectively; least squares mean changes in serum potassium from baseline to week 4 were -0.65 and -0.62 mEq/L, respectively (p < 0.0001). The most common AEs were diarrhea and constipation. Serum K+ remained ≥3.5 mEq/L in all patients; 5 patients developed serum magnesium <1.4 mg/dL, including 4 whose baseline magnesium was below the lower limit of normal. Conclusion: Patiromer is equally effective and well tolerated when taken without food or with food, thereby offering the potential for dosing flexibility.
Plan Explanations as Model Reconciliation

Recent work in explanation generation for decision making agents has looked at how unexplained behavior of autonomous systems can be understood in terms of differences in the model of the system and the human's understanding of the same, and how the explanation process as a result of this mismatch can be then seen as a process of reconciliation of these models. Existing algorithms in such settings, while having been built on contrastive, selective and social properties of explanations as studied extensively in the psychology literature, have not, to the best of our knowledge, been evaluated in settings with actual humans in the loop. As such, the applicability of such explanations to human-AI and human-robot interactions remains suspect. In this paper, we set out to evaluate these explanation generation algorithms in a series of studies in a mock search and rescue scenario with an internal semi-autonomous robot and an external human commander. During that process, we hope to demonstrate to what extent the properties of these algorithms hold as they are evaluated by humans.
Recent advances in epoxy resin, natural fiber-reinforced epoxy composites and their applications

The versatile characteristic of epoxy and its diversity made it suitable for different industrial applications such as laminated circuit board, electronic component encapsulations, surface coatings, potting, fiber reinforcement, and adhesives. However, the pervasive applications in many high-performance field limited the epoxy use because of their delamination, low impact resistance, inherent brittleness, and fracture toughness behavior. The limitations of epoxy can be overcome by incorporation and modification before their industrial applications. Currently, modified epoxy resins are extensively used in fabrication of natural fiber-reinforced composites and in making its different industrial products because of their superior mechanical, thermal, and electrical properties. Present review article designed to be a comprehensive source of recent literature on epoxy structure, synthesis, modified epoxy, bio-epoxy resin, and its applications. This review article also aims to cover the recent advances in natural fiber-based epoxy composites and nanocomposites research study, including manufacturing techniques and their different industrial applications.
Experimental evaluation of the feedback loop effects in digital predistortion of a radio-over-fiber system

In this paper, we propose the linearization of a Radio-over-Fiber (RoF) system in a real scenario, where the output signals are sent back from the Remote Radio Head (RRH) to the Baseband Unit (BBU) through a feedback loop. Firstly, the feedback chain is considered ideal, so the output signals are captured in the RRH side. Then, with the feedback loop in the setup, both the input and output signals are captured in the BBU side. Experiments are carried out in an intensity modulation/direct detection (IM/DD) RoF system with a 10 km-long fiber within the LTE standard. Experimental results show that with a proper signal power attenuation in the feedback loop it is possible to minimize its distortions, obtaining similar performance regarding to the ideal case in terms of adjacent channel power ratio (ACPR), output signal power and error vector magnitude (EVM).
Doxycycline Attenuates Lipopolysaccharide-Induced Microvascular Endothelial Cell Derangements

Introduction: Lipopolysaccharide (LPS) is known to induce vascular derangements. The pathophysiology involved therein is unknown, but matrix metalloproteinases (MMPs) may be an important mediator. We hypothesized that in vitro LPS provokes vascular permeability, damages endothelial structural proteins, and increases MMP activity; that in vivo LPS increases permeability and fluid requirements; and that the MMP inhibitor doxycycline mitigates such changes. Methods: Rat lung microvascular endothelial cells were divided into four groups: control, LPS, LPS plus doxycycline, and doxycycline. Permeability, structural proteins &bgr;-catenin and Filamentous-actin, and MMP-9 activity were examined. Sprauge Dawley rats were divided into sham, IV LPS, and IV LPS plus IV doxycycline groups. Mesenteric postcapillary venules were observed. Blood pressure was measured as animals were resuscitated and fluid requirements were compared. Statistical analysis was conducted using Student's t-test and ANOVA. Results: In vitro LPS increased permeability, damaged adherens junctions, induced actin stress fiber formation, and increased MMP-9 enzyme activity. In vivo, IV LPS administration induced vascular permeability. During resuscitation, significantly more fluid was necessary to maintain normotension in the IV LPS group. Doxycycline mitigated all derangements observed. Conclusions: We conclude that LPS increases permeability, damages structural proteins, and increases MMP-9 activity in endothelial cells. Additionally, endotoxemia induces hyperpermeability and increases the amount of IV fluid required to maintain normotension in vivo. Doxycycline mitigates such changes both in vitro and in vivo. Our findings illuminate the possible role of matrix metalloproteinases in the pathophysiology of lipopolysaccharide-induced microvascular hyperpermeability and pave the way for better understanding and treatment of this process.
vSQL: Verifying Arbitrary SQL Queries over Dynamic Outsourced Databases

Cloud database systems such as Amazon RDS or Google Cloud SQLenable the outsourcing of a large database to a server who then responds to SQL queries. A natural problem here is to efficiently verify the correctness of responses returned by the (untrusted) server. In this paper we present vSQL, a novel cryptographic protocol for publicly verifiable SQL queries on dynamic databases. At a high level, our construction relies on two extensions of the CMT interactive-proof protocol [Cormode et al., 2012]: (i) supporting outsourced input via the use of a polynomial-delegation protocol with succinct proofs, and (ii) supporting auxiliary input (i.e., non-deterministic computation) efficiently. Compared to previous verifiable-computation systems based on interactive proofs, our construction has verification cost polylogarithmic in the auxiliary input (which for SQL queries can be as large as the database) rather than linear. In order to evaluate the performance and expressiveness of our scheme, we tested it on SQL queries based on the TPC-H benchmark on a database with 6 million rows and 13 columns. The server overhead in our scheme (which is typically the main bottleneck) is up to 120 times lower than previousapproaches based on succinct arguments of knowledge (SNARKs), and moreover we avoid the need for query-dependent pre-processing which is required by optimized SNARK-based schemes. In our construction, the server/client time and the communication cost are comparable to, and sometimessmaller than, those of existing customized solutions which only support specific queries.
Genetic Association and Risk Scores in a Chronic Obstructive Pulmonary Disease Meta‐analysis of 16,707 Subjects

&NA; The heritability of chronic obstructive pulmonary disease (COPD) cannot be fully explained by recognized genetic risk factors identified as achieving genome‐wide significance. In addition, the combined contribution of genetic variation to COPD risk has not been fully explored. We sought to determine: (1) whether studies of variants from previous studies of COPD or lung function in a larger sample could identify additional associated variants, particularly for severe COPD; and (2) the impact of genetic risk scores on COPD. We genotyped 3,346 single‐nucleotide polymorphisms (SNPs) in 2,588 cases (1,803 severe COPD) and 1,782 control subjects from four cohorts, and performed association testing with COPD, combining these results with existing genotyping data from 6,633 cases (3,497 severe COPD) and 5,704 control subjects. In addition, we developed genetic risk scores from SNPs associated with lung function and COPD and tested their discriminatory power for COPD‐related measures. We identified significant associations between SNPs near PPIC (P = 1.28 × 10−8) and PPP4R4/SERPINA1 (P = 1.01 × 10−8) and severe COPD; the latter association may be driven by recognized variants in SERPINA1. Genetic risk scores based on SNPs previously associated with COPD and lung function had a modest ability to discriminate COPD (area under the curve, ˜0.6), and accounted for a mean 0.9‐1.9% lower forced expiratory volume in 1 second percent predicted for each additional risk allele. In a large genetic association analysis, we identified associations with severe COPD near PPIC and SERPINA1. A risk score based on combining genetic variants had modest, but significant, effects on risk of COPD and lung function.
Intracavity Frequency Doubling and Difference Frequency Mixing for Pulsed ns Ti:Sapphire Laser Systems at On-Line Radioactive Ion Beam Facilities

Intra-cavity second harmonic generation of a Titanium:sapphire (Ti:sa) laser system has been used to improve the conversion efficiency to the second harmonic. Over the course of several experiments performance data spanning the whole wavelength range of a Ti:sa has been collected, which may be used as a guideline for future experiments. An average output power of up to 3.7 W was achieved, resulting in a conversion efficiency of >75 % to the second harmonic. A wavelength coverage from 340-525 nm has been demonstrated. To extend the wavelength range of the solid state laser system, difference frequency mixing has been applied to the intra-cavity doubled light and the fundamental output of a second Ti:sa laser. Up to 30 mW of yellow light at the sodium D2 line at 589 nm was generated. Based on numerical calculations this output power could still be improved by a factor of ten with simple changes in the experimental setup. Laser spectroscopy and measurement of the saturation behaviour has been carried out on an atomic beam of stable sodium.
Initial analytic quality assessment and method comparison of an immunoassay for adrenocorticotropic hormone measurement in equine samples.

BACKGROUND Equine pituitary pars intermedia dysfunction (PPID) may be diagnosed by measuring baseline plasma adrenocorticotrophic hormone (ACTH). The Immulite 1000 analyzer uses an automated chemiluminescence enzyme assay, previously validated for measuring equine ACTH. Recently, an automated bench-top immunoassay analyzer (AIA-360), designed for analytes in people, became available for veterinary use. OBJECTIVES Objectives were to evaluate analytic performance of the AIA immunoassay for measuring equine ACTH, and compare the results with those obtained by the Immulite. METHODS Adrenocorticotrophic hormone was measured in plasma samples from 52 clinical cases. For the AIA, within- and between-run coefficients of variation (CV) were assessed, linearity and recovery studies performed, and observed total error (TEobs ) calculated. Correlation and agreement between the 2 analyzers were also evaluated. RESULTS Within-run and between-run CV of the AIA ranged from 2.3% to 4% and 3.5% to 8%, respectively. ACTH recoveries ranged from 89.5% to 115.9%. TEobs at 26.5 pg/mL ACTH was 4.1 pg/mL. The ACTH results (median: 25.9 pg/mL; range: 4.3-276.7 pg/mL) with AIA were significantly lower (P < .0001) than with the Immulite (median: 29.9 pg/mL; range: 10.3-639.0 pg/mL). Correlation between the 2 analyzers was r = 0.882 (P < .0001), with a significant bias for the AIA of -16 pg/mL. The 2 methods were not identical within inherent imprecision. CONCLUSION The AIA is precise for measuring ACTH in horses. Although correlation between the instruments is good, the values obtained by the immunoassays cannot be used interchangeably and should be interpreted using reference intervals established for each analyzer to avoid false negatives. Diagnostic sensitivity and specificity of the AIA-360 should be evaluated before clinical use.
Outbreak-Related Disease Burden Associated with Consumption of Unpasteurized Cow’s Milk and Cheese, United States, 2009–2014

The growing popularity of unpasteurized milk in the United States raises public health concerns. We estimated outbreak-related illnesses and hospitalizations caused by the consumption of cow’s milk and cheese contaminated with Shiga toxin–producing Escherichia coli, Salmonella spp. , Listeria monocytogenes, and Campylobacter spp. using a model relying on publicly available outbreak data. In the United States, outbreaks associated with dairy consumption cause, on average, 760 illnesses/year and 22 hospitalizations/year, mostly from Salmonella spp. and Campylobacter spp. Unpasteurized milk, consumed by only 3.2% of the population, and cheese, consumed by only 1.6% of the population, caused 96% of illnesses caused by contaminated dairy products. Unpasteurized dairy products thus cause 840 (95% CrI 611–1,158) times more illnesses and 45 (95% CrI 34–59) times more hospitalizations than pasteurized products. As consumption of unpasteurized dairy products grows, illnesses will increase steadily; a doubling in the consumption of unpasteurized milk or cheese could increase outbreak-related illnesses by 96%.
An anticancer drug suppresses the primary nucleation reaction that initiates the production of the toxic Aβ42 aggregates linked with Alzheimer’s disease

An approved anticancer drug selectively targets the first step in the molecular cascade resulting in Alzheimer’s disease. The conversion of the β-amyloid (Aβ) peptide into pathogenic aggregates is linked to the onset and progression of Alzheimer’s disease. Although this observation has prompted an extensive search for therapeutic agents to modulate the concentration of Aβ or inhibit its aggregation, all clinical trials with these objectives have so far failed, at least in part because of a lack of understanding of the molecular mechanisms underlying the process of aggregation and its inhibition. To address this problem, we describe a chemical kinetics approach for rational drug discovery, in which the effects of small molecules on the rates of specific microscopic steps in the self-assembly of Aβ42, the most aggregation-prone variant of Aβ, are analyzed quantitatively. By applying this approach, we report that bexarotene, an anticancer drug approved by the U.S. Food and Drug Administration, selectively targets the primary nucleation step in Aβ42 aggregation, delays the formation of toxic species in neuroblastoma cells, and completely suppresses Aβ42 deposition and its consequences in a Caenorhabditis elegans model of Aβ42-mediated toxicity. These results suggest that the prevention of the primary nucleation of Aβ42 by compounds such as bexarotene could potentially reduce the risk of onset of Alzheimer’s disease and, more generally, that our strategy provides a general framework for the rational identification of a range of candidate drugs directed against neurodegenerative disorders.
KLF16 suppresses human glioma cell proliferation and tumourigenicity by targeting TFAM

Abstract Background This study aims to via unveiling the novel mechanisms of KLF16 in regulating expression of genes involved in glioma. Methods KLF16 or KLF16-siRNA was transfected to U87MG cells by lentivirus. Colony formation assay was applied for detecting cell proliferation. MTT assay was adopted to assess cell viability. TUNEL assay was selected to evaluate cell apoptosis. Flow cytometry was used to determine cell cycle. Real-time PCR was performed to test mRNA expression. Western blot was used to detect protein level. Luciferase assay was applied to confirm the regulatory relationship between KLF16 and Mitochondrial transcription factor A (TFAM). Chromatin immunoprecipitation was adopted to test the protein binding site. The nude mouse transplantation tumour experiment was selected to test cancer cell proliferation in vivo. Results KLF16 was decreased in glioma cells and tissues. KLF16 obviously restrained U87MG cell proliferation both in vivo and in vitro. KLF16 transfection reduced mRNA and protein levels related to cell proliferation. KLF16 targeted a putative binding site near the transcription start sites (TSSs) of TFAM gene, thus suppressing glioma cell proliferation. KLF16-siRNA exhibited the opposite impact. KLF16 presented significant negative correlation with TFAM level in glioma patients. Conclusions KLF16 is a key regulator of glioma cell proliferation by directly targeting TFAM.