Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world’s population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with GWAS studies showing that many psoriasis risk genes lie along the IL23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. The pathogenesis of psoriasis is complex and focusing on the IL23/Th17 axis can provide insight into key cell types, cytokines and intracellular signaling pathways involved. Examination of currently available biological treatments, time to relapse post drug withdrawal and rates of drug primary/secondary drug failure show the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely reduce dis-ease burden for the longest period possible.

Dual antiplatelet therapy (DAPT), comprising aspirin and a P2Y12 receptor inhibitor, is the cornerstone of post-percutaneous coronary intervention treatment to prevent stent thrombosis and reduce the risk of adverse cardiovascular events. The selection of an optimal DAPT regimen, considering the interplay of various antiplatelet agents, patient profiles, and procedural characteristics, remains an evolving challenge. Traditionally, a standard duration of 12 months has been recommended for DAPT in most patients. While contemporary guidelines provide general frameworks, DAPT modulation with longer or shorter treatment courses followed by aspirin or P2Y12 inhibitor monotherapy are evolving towards an individualized strategy to optimize the balance between efficacy and safety. This review comprehensively examines the current landscape of DAPT strategies after coronary stenting, with a focus on emerging evidence for treatment individualization.

The real-time monitoring of food freshness in refrigerators is of significant importance in detecting potential food spoiling and preventing serious health issues. One method that is commonly reported and has received substantial attention is the discrimination of food freshness by the tracking of volatile molecules. Nevertheless, the ambient environment of low temperature (normally below 4^oC) and high humidity (90% R.H.) as well as poor selectivity in sensing gas species remain the challenge. In this research, an integrated smart gas-tracking device is designed and fabricated. By applying pump voltage on the yttria-stabilized zirconia (YSZ) membrane, the oxygen concentration in the testing chamber can be manually tailored. Due to the working principle of the sensor following the mixed potential behavior, distinct differences in sensitivity and selectivity are observed for the sensor that operated at different oxygen concentrations. Typically, the sensor gives satisfactory selectivity to H₂S, NH₃, and C₂H₅OH at the oxygen concentrations of 10%, 30%, and 40%, respectively. In addition, an acceptable response/recovery rate (within 24 s) is also confirmed. Finally, a refrigerator prototype that includes the smart gas sensor is built, and satisfactory performance in discriminating food freshness status of fresh or semi-fresh is verified for the proposed refrigerator prototype. In conclusion, these aforementioned promising results suggest that the proposed integrated smart gas sensor could be a potential candidate for alarming food spoilage.

We compared the efficacy of a tailored and a targeted intervention designed to increase clinical breast exam (CBE), mammography, and genetic services/testing among young breast cancer survivors (YBCS) (diagnosed <45 years old) and their blood relatives. A two-arm cluster randomized trial recruited a random sample of YBCS from the Michigan cancer registry and up to two of their blood relatives. Participants were stratified according to race and randomly assigned as family units to the tailored (n=637) or the targeted (n=595) intervention. Approximately 40% of participants were Black; 12% YBCS and 27% relatives were living in more than 20 different U.S. States. Higher screening rates were reported by YBCS (CBE p=0.05; mammography p=0.04) and relatives (CBE p<0.01; mammography p=0.04) in the tailored arm, and by White/Other YBCS (CBE p=0.02) and relatives (CBE p<0.01; mammography p=0.03). YBCS genetic testing rates increased from 22% to 26% (p=0.11). Black YBCS and relatives reported higher self-efficacy and intention for genetic testing, and higher satisfaction and intervention acceptance. The tailored intervention improved CBE and mammography uptake - despite having minimal contact with participants. Professional referrals will improve genetic testing uptake. Intervention materials increased self-efficacy and satisfaction for Black women but could not overcome multiple access barriers.

This research paper aims to explicate the complex issue of the Riemann's Hypothesis and ultimately presents its elementary proof. The method implements one of the binomial coefficients, to demonstrate the maximal prime gaps bound. Maximal prime gaps bound constitutes a comprehensive improvement over the Bertrand's result, and becomes one of the key elements of the theory. Subsequently, implementing the theory of the primorial function and its error bounds, an improved version of the Gauss' offset logarithmic integral is developed. This integral serves as a Supremum bound of the prime counting function Pi(n). Due to its very high precision, it permits to verify the relationship between the prime counting function Pi(n) and the offset logarithmic integral of Carl Gauss. The collective mathematical theory, via the Niels F. Helge von Koch equation, enables to prove the RIemann's Hypothesis conclusively.