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Obesity represents the single most important risk factor for early disability and death in developed societies, and the incidence of obesity remains at staggering levels. CNS systems that modulate energy intake and expenditure in response to changes in body energy stores serve to maintain constant body adiposity; the adipocyte-derived hormone leptin and its receptor (LEPR) represent crucial regulators of these systems. As in the case of insulin resistance, a variety of mechanisms (including feedback inhibition, inflammation, gliosis and endoplasmic reticulum stress) have been proposed to interfere with leptin action and impede the systems that control body energy homeostasis to promote or maintain obesity, although the relative importance and contribution of each of these remain unclear. However, LEPR signalling may be increased (rather than impaired) in common obesity, suggesting that any obesity-associated defects in leptin action must result from lesions somewhere other than the initial LEPR signal. It is also possible that increased LEPR signalling could mediate some of the obesity-associated changes in hypothalamic function.

In an interim analysis of this phase 3 trial, the addition of pembrolizumab to chemotherapy resulted in longer progression-free survival than chemotherapy alone among patients with advanced triple-negative breast cancer whose tumors expressed programmed death ligand 1 (PD-L1) with a combined positive score (CPS; the number of PD-L1-staining tumor cells, lymphocytes, and macrophages, divided by the total number of viable tumor cells, multiplied by 100) of 10 or more. The results of the final analysis of overall survival have not been reported. We randomly assigned patients with previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer in a 2:1 ratio to receive pembrolizumab (200 mg) every 3 weeks plus the investigator's choice of chemotherapy (nanoparticle albumin-bound paclitaxel, paclitaxel, or gemcitabine-carboplatin) or placebo plus chemotherapy. The primary end points were progression-free survival (reported previously) and overall survival among patients whose tumors expressed PD-L1 with a CPS of 10 or more (the CPS-10 subgroup), among patients whose tumors expressed PD-L1 with a CPS of 1 or more (the CPS-1 subgroup), and in the intention-to-treat population. Safety was also assessed. A total of 847 patients underwent randomization: 566 were assigned to the pembrolizumab-chemotherapy group, and 281 to the placebo-chemotherapy group. The median follow-up was 44.1 months. In the CPS-10 subgroup, the median overall survival was 23.0 months in the pembrolizumab-chemotherapy group and 16.1 months in the placebo-chemotherapy group (hazard ratio for death, 0.73; 95% confidence interval [CI], 0.55 to 0.95; two-sided P = 0.0185 [criterion for significance met]); in the CPS-1 subgroup, the median overall survival was 17.6 and 16.0 months in the two groups, respectively (hazard ratio, 0.86; 95% CI, 0.72 to 1.04; two-sided P = 0.1125 [not significant]); and in the intention-to-treat population, the median overall survival was 17.2 and 15.5 months, respectively (hazard ratio, 0.89; 95% CI, 0.76 to 1.05 [significance not tested]). Adverse events of grade 3, 4, or 5 that were related to the trial regimen occurred in 68.1% of the patients in the pembrolizumab-chemotherapy group and in 66.9% in the placebo-chemotherapy group, including death in 0.4% of the patients in the pembrolizumab-chemotherapy group and in no patients in the placebo-chemotherapy group. Among patients with advanced triple-negative breast cancer whose tumors expressed PD-L1 with a CPS of 10 or more, the addition of pembrolizumab to chemotherapy resulted in significantly longer overall survival than chemotherapy alone. (Funded by Merck Sharp and Dohme; KEYNOTE-355 ClinicalTrials.gov number, NCT02819518.).

In the last decade, biological drugs have rapidly proliferated and have now become an important therapeutic modality. This is because of their high potency, high specificity and desirable safety profile. The majority of biological drugs are peptide- and protein-based therapeutics with poor oral bioavailability. They are normally administered by parenteral injection (with a very few exceptions). Pulmonary delivery is an attractive non-invasive alternative route of administration for local and systemic delivery of biologics with immense potential to treat various diseases, including diabetes, cystic fibrosis, respiratory viral infection and asthma, etc. The massive surface area and extensive vascularisation in the lungs enable rapid absorption and fast onset of action. Despite the benefits of pulmonary delivery, development of inhalable biological drug is a challenging task. There are various anatomical, physiological and immunological barriers that affect the therapeutic efficacy of inhaled formulations. This review assesses the characteristics of biological drugs and the barriers to pulmonary drug delivery. The main challenges in the formulation and inhalation devices are discussed, together with the possible strategies that can be applied to address these challenges. Current clinical developments in inhaled biological drugs for both local and systemic applications are also discussed to provide an insight for further research.

As a type of biological macromolecule, natural polysaccharides have been widely used in wound healing due to their low toxicity, good biocompatibility, degradability and reproducibility. Electrospinning is a versatile and simple technique for producing continuous nanoscale fibers from a variety of natural and synthetic polymers. The application of electrospun nanofibers as wound dressings has made great progress and they are considered one of the most effective wound dressings. This paper reviews the preparation of polysaccharide nanofibers by electrospinning and their application prospects in the field of wound healing. A variety of polysaccharide nanofibers, including chitosan, starch, alginate, and hyaluronic acid are introduced. The preparation strategy of polysaccharide electrospun nanofibers and their functions in promoting wound healing are summarized. In addition, the future prospects and challenges for the preparation of polysaccharide nanofibers by electrospinning are also discussed.

Freshwater scarcity is a global threat to modern era of human society. Sorption-based atmospheric water harvesting (AWH) is prospective to provide fresh water for remote water-stressed areas lacking in water and electricity. Adsorbent material plays a vital role in such AWH systems. Here, we report a solid adsorbent synthesized by impregnating hygroscopic salt lithium chloride (LiCl) into solidified activated carbon fiber felt (ACFF modified by silica sol). Composite samples immersed with different mass concentrations of silica sol are prepared and characterized for dynamic water uptake, equilibrium water uptake, textural and thermal properties. AS5Li30 (ACFF + 5 wt% silica gel + 30 wt% LiCl) exhibits an efficient water uptake of 2.1 g/g at 25 °C and 70% relative humidity (RH). The material further demonstrates a heat storage capacity of 5456 kJ/kg. Its low regeneration temperature (< 80 °C) and good cycle stability make it feasible to be used in practical water production applications, driven by solar energy and other low-grade energy. Estimation results show that water harvesting unit can produce 1.41 g H2O /g AS5Li30 under 25 °C and 75% RH.

Quantum computing has emerged as a transformative paradigm, with revolutionary potential in numerous fields, including quantum image processing and compression. Applications that depend on large scale image data could benefit greatly from parallelism and quantum entanglement, which would allow images to be encoded and decoded with unprecedented efficiency and data reduction capability. This paper provides a comprehensive overview of the rapidly evolving field of quantum image compression, including its foundational principles, methods, challenges, and potential uses. The paper will also feature a thorough exploration of the fundamental concepts of quantum qubits as image pixels, quantum gates as image transformation tools, quantum image representation, as well as basic quantum compression operations. Our survey shows that work is still sparse on the practical implementation of quantum image compression algorithms on physical quantum computers. Thus, further research is needed in order to attain the full advantage and potential of quantum image compression algorithms on large-scale fault-tolerant quantum computers.

Smoothed particle hydrodynamics (SPH) is a Lagrangian method based on a meshless discretization of partial differential equations. In this review, we present SPH discretization of the Navier-Stokes and advection-diffusion-reaction equations, implementation of various boundary conditions, and time integration of the SPH equations, and we discuss applications of the SPH method for modeling pore-scale multiphase flows and reactive transport in porous and fractured media.

Acquired and inherited retinal disorders are responsible for vision loss in an increasing proportion of individuals worldwide. Photoreceptor (PR) death is central to the vision loss individuals experience in these various retinal diseases. Unfortunately, there is a lack of treatment options to prevent PR loss, so an urgent unmet need exists for therapies that improve PR survival and ultimately, vision. The retina is one of the most energy demanding tissues in the body, and this is driven in large part by the metabolic needs of PRs. Recent studies suggest that disruption of nutrient availability and regulation of cell metabolism may be a unifying mechanism in PR death. Understanding retinal cell metabolism and how it is altered in disease has been identified as a priority area of research. The focus of this review is on the recent advances in the understanding of PR metabolism and how it is critical to reduction-oxidation (redox) balance, the outer retinal metabolic ecosystem, and retinal disease. The importance of these metabolic processes is just beginning to be realized and unraveling the metabolic and redox pathways integral to PR health may identify novel targets for neuroprotective strategies that prevent blindness in the heterogenous group of retinal disorders.Photoreceptor death is central to vision loss in various retinal diseases. Disruption of nutrient availability and cell metabolism may underlie photoreceptor death. In this review, Pan et al. focus on the recent advances in the understanding of photoreceptor metabolism and suggest novel targets for neuroprotective strategies that prevent blindness.

With recent advances in the field of machine learning, the use of deep neural networks for time series forecasting has become more prevalent. The quasi-periodic nature of the solar cycle makes it a good candidate for applying time series forecasting methods. We employ a combination of WaveNet and Long Short-Term Memory neural networks to forecast the sunspot number using the years 1749 to 2019 and total sunspot area using the years 1874 to 2019 time series data for the upcoming Solar Cycle 25. Three other models involving the use of LSTMs and 1D ConvNets are also compared with our best model. Our analysis shows that the WaveNet and LSTM model is able to better capture the overall trend and learn the inherent long and short term dependencies in time series data. Using this method we forecast 11 years of monthly averaged data for Solar Cycle 25. Our forecasts show that the upcoming Solar Cycle 25 will have a maximum sunspot number around 106 ± 19.75 and maximum total sunspot area around 1771 ± 381.17. This indicates that the cycle would be slightly weaker than Solar Cycle 24.

Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model‐selection criteria available in GEE. The well‐known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is nonlikelihood based. We propose a modification to AIC, where the likelihood is replaced by the quasi‐likelihood and a proper adjustment is made for the penalty term. Its performance is investigated through simulation studies. For illustration, the method is applied to a real data set.