Profile Update Research Articles

The Danish Centre for Strategic Research in Type 2 Diabetes (DD2) Project Cohort and Biobank from 2010 Through 2023-A Cohort Profile Update.

This paper provides an overview of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort and biobank, including baseline characteristics of participants enrolled up to 2023, and post-enrollment rates of cardiovascular disease outcomes and mortality. Since 2010, the DD2 project has enrolled individuals with type 2 diabetes mellitus (T2DM) recently diagnosed by general practitioners and by hospital-based clinicians across Denmark. Data from questionnaires, clinical examinations, and biological samples are collected at enrollment. Additional baseline and longitudinal follow-up data are accessed via linkage to health registries. Between 2010 and 2023, the DD2 project enrolled 11,369 participants (41.3% women, median age 61.4 years). Median T2DM duration at enrollment was 1.3 years, and median BMI was 31.6 kg/m2 for women and 30.5 kg/m2 for men. 18.3% were smokers, 5.7% consumed more than 14/21 units of alcohol weekly (women/men), and 17.9% reported leisure-time physical inactivity. Original midwife records dating back >80 years revealed that 20.2% of cohort participants had birth weights <3000 g. Based on complete hospital contact history 10 years before enrollment, 20.7% of cohort participants had macrovascular complications, 17.0% had microvascular complications, and 21.7% had kidney disease based on eGFR or urine albumin-creatinine measurements. At enrollment, statins were used by 68.2%, antihypertensive drugs by 69.9%, and glucose-lowering drugs by 86.5% of individuals. Median HbA1c was 48 mmol/mol and median LDL cholesterol 2.2 mmol/L. Genome-wide genotyping and biomarker data have been analyzed for over 9000 individuals. During the current follow-up time from the enrollment date (median 7.9 years), incident cardiovascular disease rate has been 13.8 per 1000 person-years and the mortality rate has been 17.6 per 1000 person-years. The DD2 cohort, with its detailed information and long-term follow up, can improve our understanding of the progression and prevention of complications among individuals with newly diagnosed T2DM.

Ospemifene and vulvovaginal atrophy: an update of the clinical profile for post-menopausal women.

The demand for effective and safe treatments of genitourinary syndrome (GSM) in post-menopausal women (PMW) is growing. Published data on the efficacy and safety of ospemifene (OSP) prompt an updated literature review to enlighten possible improvements in the GSM treatment. We searched articles published in English from 2010 to 2023 through Medline (PubMed) and Embase databases with Boolean terms: OSP, PMW, GSM, endometrium, breast cancer, cardiometabolic syndrome, bone metabolism, adherence to treatment, and patient satisfaction. We selected randomized controlled trials (RCTs) and observational and cross-sectional studies and completed the search manually. Of the 157 retrieved records, 25 primary studies met the inclusion criteria (15 regarding efficacy and safety, two for additional effects, and four for adherence and satisfaction with the OSP treatment). Seven RCTs involved nearly 5,000 patients, 10 out of 18 prospective observational studies 563, and six retrospective analyses 356,439. Evidence of OSP treatment in PMW with GSM relies on RCTs and remarkable real-world data. The 25 primary studies showcased the high clinical response to symptoms, the favorable safety profile of OSP with very few adverse events, a neutral impact on the endometrium, breast, bone, and thrombosis, and the possible improvement of cardiovascular risk factors.

Profile update: the effects of identity disclosure on network connections and language

Our social identities determine how we interact and engage with the world surrounding us. In online settings, individuals can make these identities explicit by including them in their public biography, possibly signaling a change in what is important to them and how they should be viewed. While there is evidence suggesting the impact of intentional identity disclosure in online social platforms, its actual effect on engagement activities at the user level has yet to be explored. Here, we perform the first large-scale study on Twitter that examines behavioral changes following identity disclosure on Twitter profiles. Combining social networks with methods from natural language processing and quasi-experimental analyses, we discover that after disclosing an identity on their profiles, users (1) tweet and retweet more in a way that aligns with their respective identities, and (2) connect more with users that disclose similar identities. We also examine whether disclosing the identity increases the chance of being targeted for offensive comments and find that in fact (3) the combined effect of disclosing identity via both tweets and profiles is associated with a reduced number of offensive replies from others. Our findings highlight that the decision to disclose one’s identity in online spaces can lead to substantial changes in how they express themselves or forge connections, with a lesser degree of negative consequences than anticipated.

Cohort Profile Update: Magu Health and Demographic Surveillance System, Tanzania.

Cohort Profile Update: Magu Health and Demographic Surveillance System, Tanzania.

Cohort Profile Update: 2015 Pelotas (Brazil) Birth Cohort Study－follow-ups from 2 to 6-7 years, with COVID-19 impact assessment.

Cohort Profile Update: 2015 Pelotas (Brazil) Birth Cohort Study－follow-ups from 2 to 6-7 years, with COVID-19 impact assessment.

Cohort Profile Update: The New South Wales Child Development Study (NSW-CDS) - Wave 3 (child age ∼18 years).

Cohort Profile Update: The New South Wales Child Development Study (NSW-CDS) - Wave 3 (child age ∼18 years).

Multiple Leap Maneuver Trajectory Design and Tracking Method Based on Prescribed Performance Control during the Gliding Phase of Vehicles

A novel standard trajectory design and tracking guidance used in the multiple active leap maneuver mode for hypersonic glide vehicles (HGVs) is proposed in this paper. First, the dynamic equation and multiconstraint model are first established in the flight path coordinate system. Second, the reference drag acceleration-normalized energy (D-e) profile of the multiple active leap maneuver mode is quickly determined by the Newton iterative algorithm with a single design parameter. The range to go error is corrected by the drag acceleration profile update algorithm, and the drag acceleration error of the gliding terminal is corrected by the aerodynamic parameter estimation algorithm. Then, the reference drag acceleration tracking guidance law is designed based on the prescribed performance control method. Finally, the CAV-L vehicle model is used for numerical simulation. The results show that the proposed method can satisfy the design requirements of drag acceleration under multiple active leap maneuver modes, and the reference drag acceleration can be tracked precisely. The adaptability and robustness of the proposed method are verified by the Monte Carlo simulations under various combined deviation conditions.

Cohort Profile Update: The Québec Birth Cohort on Immunity and Health (CO·MMUNITY).

Cohort Profile Update: The Québec Birth Cohort on Immunity and Health (CO·MMUNITY).

Cohort Profile Update: The Young-HUNT Study, Norway.

Cohort Profile Update: The Young-HUNT Study, Norway.

Cohort Profile Update: 2004 Pelotas (Brazil) Birth Cohort Study follow-up during adolescent years.

Cohort Profile Update: 2004 Pelotas (Brazil) Birth Cohort Study follow-up during adolescent years.

Blockchain Technology in the Intrusion Detection Domain

The ability of blockchain technology to improve security and transparency across a range of industries has receivedA great deal of attention has been garnered lately in correcting the sentence.. In the domain of intrusion detection, where the identification and mitigation of cyber threats are paramount, blockchain has emerged as a promising solution. This abstract examines how blockchain is used in intrusion detection systems and emphasizes its advantages. Blockchain technology improves the security and integrity of intrusion detection systems by using a decentralized and immutable ledger. It provides an immutable audit trail, distributed consensus, and increased resilience to attacks. Moreover, blockchain fosters trust, transparency, and collaboration among stakeholders, enabling faster threat detection and response. This research can explore novel approaches to integrating blockchain into intrusion detection systems, providing stronger protection against cyber threats.Immutable Audit Trail: In the context of intrusion detection, the capacity of blockchain to produce an unalterable and transparent audit trail is of enormous value. Research in this area can focus on developing techniques to leverage the blockchain's audit trail for effective incident response, forensic investigations, and attribution of cyberattacks. We will use theweighted product model in this study, which is a research approach that gives weights to various factors and combines them to make conclusions based on their relative relevance in a weighted way. Taken as alternative is“IDS1, IDS2, IDS3, IDS4, IDS5, IDS6, IDS7, and IDS8”.Detection Quality, Performance, Stability, User Interface, Profile update, ConvenienceThe By this we can see that IDS4 has 1 RANK and IDS5 has the 8th RANK.In conclusion, blockchain technology holds great potential in the intrusion detection domain. Its decentralized and immutable nature can enhance the security and reliability of intrusion detection systems by providing transparent and tamper-proof logs of network activity. Blockchain-based solutions can improve threat detection, facilitate secure information sharing among entities, and enhance the overall resilience of intrusion detection systems. As the technology continues to evolve, further research and development in integrating blockchain with intrusion detection will unlock new possibilities for combating cyber threats.

Cohort Profile Update: Project Viva mothers.

Cohort Profile Update: Project Viva mothers.

Deep operator learning-based surrogate models with uncertainty quantification for optimizing internal cooling channel rib profiles

This paper focuses on designing surrogate models that have uncertainty quantification capabilities to effectively improve the thermal performance of rib-turbulated internal cooling channels. To construct the surrogate, we use the deep operator network (DeepONet) framework, a novel class of neural networks designed to approximate mappings between infinite-dimensional spaces using relatively small datasets. The proposed DeepONet takes an arbitrary rib geometry as input and outputs continuous detailed pressure and heat transfer distributions around the profiled ribs. The datasets needed to train and test the proposed DeepONet framework were obtained by simulating a 2D rib-roughened internal cooling channel. To accomplish this, we continuously modified the input rib geometry by adjusting the control points according to a simple random distribution with constraints, rather than following a predefined path or sampling method. The studied channel has a hydraulic diameter, Dh, of 66.7 mm, and a length-to-hydraulic diameter ratio, L/Dh, of 10. The ratio of rib center height to hydraulic diameter (e/Dh), which was not changed during the rib profile update, was maintained at a constant value of 0.048. The ribs were placed in the channel with a pitch-to-height ratio (P/e) of 10. In addition, we provide the proposed surrogates with effective uncertainty quantification capabilities. This is achieved by converting the DeepONet framework into a Bayesian DeepONet (B-DeepONet). B-DeepONet samples from the posterior distribution of DeepONet parameters using the novel framework of stochastic gradient replica-exchange MCMC. Finally, we demonstrate the performance of the proposed DeepONet-based surrogate models with uncertainty quantification by incorporating them into a constrained, gradient-free optimization problem that enhances the thermal performance of the rib-turbulated internal cooling channel.

Cohort profile update: the Norwegian STORK Groruddalen (STORK G) pregnancy and birth cohort—the role of ethnicity and causal pathways for obesity, type 2 diabetes, cardiovascular disease and other health issues

PurposeThe STORK Groruddalen cohort was set up in 2008 to explore ethnic differences in: (1) maternal health, primarily gestational diabetes (GDM) and related health issues during pregnancy and post partum,...

Cohort Profile Update: The Neuroscience in Psychiatry Network (NSPN) 2400 cohort during the COVID-19 pandemic.

Cohort Profile Update: The Neuroscience in Psychiatry Network (NSPN) 2400 cohort during the COVID-19 pandemic.

Salivary glands adenoid cystic carcinoma: a molecular profile update and potential implications.

Adenoid cystic carcinoma (ACC) is an aggressive tumor with a high propensity for distant metastasis and perineural invasion. This tumor is more commonly found in regions of the head and neck, mainly the salivary glands. In general, the primary treatment modality for ACC is surgical resection and, in some cases, postoperative radiotherapy. However, no effective systemic treatment is available for patients with advanced disease. Furthermore, this tumor type is characterized by recurrent molecular alterations, especially rearrangements involving the MYB, MYBL1, and NFIB genes. In addition, they also reported copy number alterations (CNAs) that impact genes. One of them is C-KIT, mutations that affect signaling pathways such as NOTCH, PI3KCA, and PTEN, as well as alterations in chromatin remodeling genes. The identification of new molecular targets enables the development of specific therapies. Despite ongoing investigations into immunotherapy, tyrosine kinase inhibitors, and anti-angiogenics, no systemic therapy is approved by the FDA for ACC. In this review, we report the genetic and cytogenetic findings on head and neck ACC, highlighting possible targets for therapeutic interventions.

Cohort Profile Update: The US Millennium Cohort Study-evaluating the impact of military experiences on service members and veteran health.

Cohort Profile Update: The US Millennium Cohort Study-evaluating the impact of military experiences on service members and veteran health.

Cohort Profile Update: The Bissau HIV Cohort-a Cohort of HIV-1, HIV-2 and Co-infected Patients.

The Bissau HIV cohort was initiated in 2007 and a cohort profile was published in 2014.1 The aim was to gain insights into different HIV types, human immunodeficiency virus 1 (HIV-1), human immunodeficiency virus 2 (HIV-2) and HIV 1/2-dual infections and human t-lympotropic virus 1 (HTLV-1) and tuberculosis and other co-infections. It was established at Hospital Nacional Simão Mendes (HNSM), the main hospital in Bissau, as a collaboration between researchers from the Bandim Health Project [https://www.bandim.org/], Aarhus University Hospital and local nurses and doctors from HNSM. The original cohort was singl-centred at HNSM and, by the time of the original cohort article in 2014, included 3765 patients. The cohort was continuously updated when patients arrived at the clinic for antiretroviral treatment (ART) supplies and clinical evaluations. Besides ART and clinical outcomes, the cohort has also been used to study co-infections such as HTLV,2,3 Hepatitis B and C,4 tuberculosis,5,6 cryptococcus,7 cytomegalovirus (CMV),8 pneumocystic jiroveci9 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)10 that are prevalent.

Cohort profile update: The Cork and Kerry Diabetes and Heart Disease Study.

Background: The Cork and Kerry Diabetes and Heart Disease Study was established to investigate the prevalence of diabetes and cardiovascular disease among middle-aged adults in Ireland. The Mitchelstown cohort was recruited from a single large primary care centre between 2010-2011. A rescreen of this cohort was conducted in 2015. Methods: Data were collected on cardiovascular health and associated risk factors. In addition, the rescreen incorporated new measures which included information on cognition and frailty, medication adherence, dietary factors and the collection of stool samples with RNA sequencing of the gut microbiome. Results: Of 2047 participants in the original cohort, 237 (11.6%) were deceased, too ill to participate or were lost to follow-up. Of the remaining 1810 baseline study participants, 1378 men and women aged 51-77 years agreed to take part in the rescreen (response rate of 76.1%). The prevalence of hypertension was high, ranging from 50% to 64% depending on the measurement method. An investigation of the association of gut microbiota with metabolic syndrome and obesity indicated greater microbiome diversity in metabolically healthy non-obese individuals relative to their unhealthy counterparts. Analysis of prescribing data over time demonstrated a high prevalence of potentially inappropriate prescribing among older-aged people in primary care which increased as they progressed to more advanced old age. Conclusions: The rescreen has provided new insights into cardiovascular health. In addition, this study is embedded in a single primary care centre, enabling passive follow-up of study participants through electronic health records. All data collected at baseline and rescreen are maintained and stored at the School of Public Health, University College Cork and specific proposals for future collaborations are welcome.

Blockchain Voting with Tamper Verification using Telegram Bot

Blockchain technology has the potential to revolutionize the voting process by providing a secure and transparent method for recording votes. This paper proposes a voting system that utilizes blockchain technology, along with the Django web framework and Django administration for user profile updates, login using Aadhar number. The system incorporates a unique login feature that utilizes an Aadhar number, and two-step authentication through email OTP and private key authentication. The use of Merkle trees and SHA ensures a proof of work that prevents double voting, while tamper verification is achieved through a Telegram bot. The proposed system provides a secure, transparent, and efficient method for conducting elections, which is essential for ensuring a fair and democratic society.