Over 80% of people living with HIV in low-and-middle-income countries (LMICs) take first-line TDF/XTC/DTG (TLD). Due to hard-fought activism, in >100 LMICs TLD now costs under $45pppy under Voluntary License. With final DTG patents expiring by 2029, generic TLD will soon be available globally. We identify seven critical benchmarks underpinning TLDs success which novel ART should now meet, and an eighth for which novel ART should aim. These are superior efficacy; a high genetic barrier to resistance; safety in hepatitis B coinfection; favourable drug-drug interaction profiles including with antimycobacterials; efficacy in HIV-2; safety in pregnancy, long-acting formulation availability and affordable pricing from the outset. We illustrate when generic TLD will become available worldwide and compare this with trial programmes and approval timelines for two case-study novel ART combinations: islatravir/doravirine and cabotegravir/rilpivirine. We demonstrate that currently these regimens and trial programmes will not meet key benchmarks required to compete with TLD.
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http://dx.doi.org/10.1093/cid/ciae361 | DOI Listing |
Acc Chem Res
January 2025
School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
ConspectusSymmetry is a pervasive phenomenon spanning diverse fields, from art and architecture to mathematics and science. In the scientific realms, symmetry reveals fundamental laws, while symmetry breaking─the collapse of certain symmetry─is the underlying cause of phenomena. Research on symmetry and symmetry breaking consistently provides valuable insights across disciplines, from parity violation in physics to the origin of homochirality in biology.
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MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing, China.
An important step of mainstream protein structure prediction is to model the 3D protein structure based on the predicted 2D inter-residue geometric information. This folding step has been integrated into a unified neural network to allow end-to-end training in state-of-the-art methods like AlphaFold2, but is separately implemented using the Rosetta folding environment in some traditional methods like trRosetta. Despite the inferiority in prediction accuracy, the conventional approach allows for the sampling of various protein conformations compatible with the predicted geometric constraints, partially capturing the dynamic information.
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January 2025
IDLab, Ghent University-imec, Ghent, Belgium.
Smart cities deploy various sensors such as microphones and RGB cameras to collect data to improve the safety and comfort of the citizens. As data annotation is expensive, self-supervised methods such as contrastive learning are used to learn audio-visual representations for downstream tasks. Focusing on surveillance data, we investigate two common limitations of audio-visual contrastive learning: false negatives and the minimal sufficient information bottleneck.
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January 2025
Liv Hospital, Centre for Regenerative Medicine and Stem Cell Manufacturing (LivMedCell), İstanbul, Turkey.
In vitro maturation (IVM) is a form of assisted reproductive technology (ART) applied to obtain mature oocytes in culture. Decline in IVM success rates by age has led consideration of novel approaches based on cellular dynamics. Our aim was to achieve proteostasis in old bovine oocytes from 13 to 16-year-old bovine with a lower potential for fertilization.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Industrial Engineering, Sharif University of Technology, Azadi Ave., Tehran, 1458889694, Iran.
Multiclass imbalance is a challenging problem in real-world datasets, where certain classes may have a low number of samples because they correspond to rare occurrences. To address the challenge of multiclass imbalance, this paper introduces a novel hybrid cluster-based oversampling and undersampling (HCBOU) technique. By clustering and separating classes into majority and minority categories, this algorithm retains the most information during undersampling while generating efficient data in the minority class.
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