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JMIR Bioinformatics and Biotechnology May 2024Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on... (Review)
Review
BACKGROUND
Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation.
OBJECTIVE
This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets.
METHODS
We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success.
RESULTS
From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants.
CONCLUSIONS
On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.
PubMed: 38935957
DOI: 10.2196/54332 -
Journal of Personalized Medicine Jun 2024The early reliable detection and quantification of autoantibodies play an important role in autoimmune disease diagnosis and in disease-course monitoring. New...
BACKGROUND
The early reliable detection and quantification of autoantibodies play an important role in autoimmune disease diagnosis and in disease-course monitoring. New technologies, such as the multiplexed determination of autoantibodies, have recently been introduced and are being adopted more frequently. The aim of this study was to evaluate the ability of a new microdot array-based multiparametric assay (ZENIT AMiDot CTD panel, A. Menarini Diagnostics, Firenze, Italy) to correctly classify patients with autoimmune rheumatic diseases (ARDs) and compare it to a fluorescence enzyme immunoassay (FEIA) for the detection of anti-ENAs.
METHODS
The study included 69 consecutive samples from patients with ARDs that were analyzed using two different methods (FEIA and AMiDot) to detect anti-CENP B and six anti-ENA antibodies: anti-Scl-70, anti-SSB/La, anti-Jo-1, anti-U1-RNP, anti-Ro52, and anti-Ro60. The control group sera came from sixty-eight blood donors. Tests were run on the automated slide processor ZENIT FLOW, and then the slides were imaged and analyzed using ZENIT fast.
RESULTS
Since the samples were selected for at least one antibody positivity with an ARD diagnosis, we did not calculate clinical sensitivity but only specificity, which was 98.53%, ranging from 90% for anti-SSB/La antibodies to 100% for anti-CENP B ones. Mean agreement among the methods assessed by Cohen's kappa was 0.816 ± 0.240.
CONCLUSIONS
The assay demonstrated good clinical performance and may be considered a valuable aid in detecting ARD patients, offering an alternative to methods such as FEIA which are largely in use today.
PubMed: 38929828
DOI: 10.3390/jpm14060607 -
Scientific Reports Jun 2024In traditional von Neumann computing architecture, the efficiency of the system is often hindered by the data transmission bottleneck between the processor and memory. A...
In traditional von Neumann computing architecture, the efficiency of the system is often hindered by the data transmission bottleneck between the processor and memory. A prevalent approach to mitigate this limitation is the use of non-volatile memory for in-memory computing, with spin-orbit torque (SOT) magnetic random-access memory (MRAM) being a leading area of research. In this study, we numerically demonstrate that a precise combination of damping-like and field-like spin-orbit torques can facilitate precessional magnetization switching. This mechanism enables the binary memristivity of magnetic tunnel junctions (MTJs) through the modulation of the amplitude and width of input current pulses. Building on this foundation, we have developed a scheme for a reconfigurable spintronic logic gate capable of directly implementing Boolean functions such as AND, OR, and XOR. This work is anticipated to leverage the sub-nanosecond dynamics of SOT-MRAM cells, potentially catalyzing further experimental developments in spintronic devices for in-memory computing.
PubMed: 38926523
DOI: 10.1038/s41598-024-65634-9 -
ACS Engineering Au Jun 2024We propose a numerical strategy based on dynamic load balancing (DLB) aimed at enhancing the computational efficiency of multiscale CFD simulation of reactive flows at...
We propose a numerical strategy based on dynamic load balancing (DLB) aimed at enhancing the computational efficiency of multiscale CFD simulation of reactive flows at catalyst surfaces. Our approach employs DLB combined with a hybrid parallelization technique, integrating both MPI and OpenMP protocols. This results in an optimized distribution of the computational load associated with the chemistry solution across processors, thereby minimizing computational overheads. Through assessments conducted on fixed and fluidized bed reactor simulations, we demonstrated a remarkable improvement of the parallel efficiency from 19 to 87% and from 19 to 91% for the fixed and fluidized bed, respectively. Owing to this improved parallel efficiency, we observe a significant computational speed-up of 1.9 and 2.1 in the fixed and fluidized bed reactor simulations, respectively, compared to simulations without DLB. All in all, the proposed approach is able to improve the computational efficiency of multiscale CFD simulations paving the way for a more efficient exploitation of high-performance computing resources and expanding the current boundaries of feasible simulations.
PubMed: 38911942
DOI: 10.1021/acsengineeringau.3c00066 -
NeuroImage Jun 2024How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure...
How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. However, the brain is obviously a single-trial processor. Thus, we here demonstrate that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial basis. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both extra-cellular neural recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.
PubMed: 38909761
DOI: 10.1016/j.neuroimage.2024.120696 -
Poultry Science Jun 2024A significant quantity of bone-rich poultry by-products must be disposed of by poultry processors. These products still contain a significant amount of nutritionally...
A significant quantity of bone-rich poultry by-products must be disposed of by poultry processors. These products still contain a significant amount of nutritionally valuable animal proteins. In the present work, a hydrolysis protocol was optimized to recover the protein fraction of bone-rich poultry by-products while simultaneously minimizing the amount of water required for hydrolysis (thus reducing drying costs) and recycling the hydrolytic broth up to 3 times, to reduce the cost of the proteolytic enzyme. The final hydrolysis conditions involved the use of (protease from B. licheniformis, ≥2.4 U/g; 0.5 V/w of raw material) and a hydrolysis time of 2 h at 65°C. The protein hydrolysate obtained has a high protein content (79-86%), a good amino acid profile (chemical amino acid score equal to 0.7-0.8) and good gastric digestibility (about 30% of peptide bonds are already hydrolyzed before digestion). This supports its use as an ingredient in food, pet food or animal feed formulations.
PubMed: 38908125
DOI: 10.1016/j.psj.2024.103924 -
Journal of Clinical Medicine Jun 2024: The growing adoption of cochlear implants (CIs) necessitates understanding the factors influencing long-term performance and improved outcomes. This work investigated...
: The growing adoption of cochlear implants (CIs) necessitates understanding the factors influencing long-term performance and improved outcomes. This work investigated the long-term effect of early activation of CIs on electrode impedance in a large sample of CI users at different time points. : A retrospective study on 915 ears from CI patients who were implanted between 2015 and 2020. According to their CI audio processor activation time, the patients were categorized into early activation (activated 1 day after surgery, n = 481) and classical activation (activated 4 weeks after surgery, n = 434) groups. Then, the impact of the activation times on the electrode impedance values, along the electrode array contacts, at different time points up to two years was studied and analyzed. : The early activation group demonstrated lower impedance values across all the electrode array sections compared to the classical activation at 1 month, 1 year, and 2 years post-implantation. At 1 month, early activation was associated with a reduction of 0.34 kΩ, 0.46 kΩ, and 0.37 kΩ in the apical, middle, and basal sections, respectively. These differences persisted at subsequent intervals. : Early activation leads to sustained reductions in the electrode impedance compared to classical activation (CA), suggesting that earlier activation might positively affect long-term CI outcomes.
PubMed: 38893010
DOI: 10.3390/jcm13113299 -
Foods (Basel, Switzerland) May 2024Milk has become a staple food product globally. Traditionally, milk quality assessment has been primarily focused on hygiene and composition to ensure its safety for... (Review)
Review
Milk has become a staple food product globally. Traditionally, milk quality assessment has been primarily focused on hygiene and composition to ensure its safety for consumption and processing. However, in recent years, the concept of milk quality has expanded to encompass a broader range of factors. Consumers now also consider animal welfare, environmental impact, and the presence of additional beneficial components in milk when assessing its quality. This shifting consumer demand has led to increased attention on the overall production and sourcing practices of milk. Reflecting on this trend, this review critically explores such novel quality parameters, offering insights into how such practices meet the modern consumer's holistic expectations. The multifaceted aspects of milk quality are examined, revealing the intertwined relationship between milk safety, compositional integrity, and the additional health benefits provided by milk's bioactive properties. By embracing sustainable farming practices, dairy farmers and processors are encouraged not only to fulfill but to anticipate consumer standards for premium milk quality. This comprehensive approach to milk quality underscores the necessity of adapting dairy production to address the evolving nutritional landscape and consumption patterns.
PubMed: 38890886
DOI: 10.3390/foods13111650 -
BMC Medical Informatics and Decision... Jun 2024Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient...
BACKGROUND
Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access.
RESULTS
We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.
CONCLUSIONS
The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.
Topics: Humans; Computer Security; Confidentiality; Artificial Intelligence; Hospitals
PubMed: 38886772
DOI: 10.1186/s12911-024-02549-5 -
The Plant Genome Jun 2024The starchy storage roots of cassava are commonly processed into a variety of products, including cassava granulated processed products (gari). The commercial value of...
The starchy storage roots of cassava are commonly processed into a variety of products, including cassava granulated processed products (gari). The commercial value of cassava roots depends on the yield and quality of processed products, directly influencing the acceptance of new varieties by farmers, processors, and consumers. This study aims to estimate genetic advance through phenotypic selection and identify genomic regions associated and candidate genes linked with gari yield and quality. Higher single nucleotide polymorphism (SNP)-based heritability estimates compared to broad-sense heritability estimates were observed for most traits highlighting the influence of genetic factors on observed variation. Using genome-wide association analysis of 188 clones, genotyped using 53,150 genome-wide SNPs, nine SNPs located on seven chromosomes were significantly associated with peel loss, gari yield, color parameters for gari and eba, bulk density, swelling index, and textural properties of eba. Future research will focus on validating and understanding the functions of identified genes and their influence on gari yield and quality traits.
PubMed: 38880944
DOI: 10.1002/tpg2.20469