QAL-BP: an augmented Lagrangian quantum approach for bin packing.

The bin packing is a well-known NP-Hard problem in the domain of artificial intelligence, posing significant challenges in finding efficient solutions. Conversely, recent advancements in quantum technologies have shown promising potential for achieving substantial computational speedup, particularly in certain problem classes, such as combinatorial optimization. In this study, we introduce QAL-BP, a novel Quadratic Unconstrained Binary Optimization (QUBO) formulation designed specifically for bin packing and suitable for quantum computation. QAL-BP utilizes the Augmented Lagrangian method to incorporate the bin packing constraints into the objective function while also facilitating an analytical estimation of heuristic, but empirically robust, penalty multipliers. This approach leads to a more versatile and generalizable model that eliminates the need for empirically calculating instance-dependent Lagrangian coefficients, a requirement commonly encountered in alternative QUBO formulations for similar problems. To assess the effectiveness of our proposed approach, we conduct experiments on a set of bin packing instances using a real Quantum Annealing device. Additionally, we compare the results with those obtained from two different classical solvers, namely simulated annealing and Gurobi. The experimental findings not only confirm the correctness of the proposed formulation, but also demonstrate the potential of quantum computation in effectively solving the bin packing problem, particularly as more reliable quantum technology becomes available.

Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.

Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three image collections wherein rodent neuronal cell nuclei and cytoplasm are stained with diverse markers to highlight their anatomical or functional characteristics. Specifically, we release 1874 high-resolution images alongside 750 corresponding ground-truth annotations for several learning tasks, including semantic segmentation, object detection and counting. The contribution is two-fold. First, thanks to the variety of annotations and their accessible formats, we anticipate our work will facilitate methodological advancements in computer vision approaches for segmentation, detection, feature extraction, unsupervised and self-supervised learning, transfer learning, and related areas. Second, by enabling extensive exploration and benchmarking, we hope Fluorescent Neuronal Cells v2 will catalyze breakthroughs in fluorescence microscopy analysis and promote cutting-edge discoveries in life sciences.

Development and Preclinical Evaluation of New Inhaled Lipoglycopeptides for the Treatment of Persistent Pulmonary Methicillin-Resistant Staphylococcus aureus Infections.

Chronic pulmonary methicillin-resistant Staphylococcus aureus (MRSA) disease in cystic fibrosis (CF) has a high probability of recurrence following treatment with standard-of-care antibiotics and represents an area of unmet need associated with reduced life expectancy. We developed a lipoglycopeptide therapy customized for pulmonary delivery that not only demonstrates potent activity against planktonic MRSA, but also against protected colonies of MRSA in biofilms and within cells, the latter of which have been linked to clinical antibiotic failure. A library of next-generation potent lipoglycopeptides was synthesized with an emphasis on attaining superior pharmacokinetics (PK) and pharmacodynamics to similar compounds of their class. Our strategy focused on hydrophobic modification of vancomycin, where ester and amide functionality were included with carbonyl configuration and alkyl length as key variables. Candidates representative of each carbonyl attachment chemistry demonstrated potent activity in vitro, with several compounds being 30 to 60 times more potent than vancomycin. Selected compounds were advanced into in vivo nose-only inhalation PK evaluations in rats, where RV94, a potent lipoglycopeptide that utilizes an inverted amide linker to attach a 10-carbon chain to vancomycin, demonstrated the most favorable lung residence time after inhalation. Further in vitro evaluation of RV94 showed superior activity to vancomycin against an expanded panel of Gram-positive organisms, cellular accumulation and efficacy against intracellular MRSA, and MRSA biofilm killing. Moreover, in vivo efficacy of inhaled nebulized RV94 in a 48 h acute model of pulmonary MRSA (USA300) infection in neutropenic rats demonstrated statistically significant antibacterial activity that was superior to inhaled vancomycin.