Artemisinin-Type Drugs in Tumor Cell Death:Mechanisms, Combination Treatment with Biologics and Nanoparticle Delivery

Artemisinin, the most famous anti-malaria drug initially extracted from Artemisia annua L., also exhibits anti-tumor properties in vivo and in vitro. To improve its solubility and bioavailability, multiple derivatives have been synthesized. However, to reveal the anti-tumor mechanism and improve the efficacy of these artemisinin-type drugs, studies have been conducted in recent years. In this review, we first provide an overview of the effect of artemisinin-type drugs on the regulated cell death pathways, which may uncover novel therapeutic approaches. Then, to overcome the shortcomings of artemisinin-type drugs, we summarize the recent advances in two different therapeutic approaches, namely the combination therapy with biologics influencing regulated cell death, and the use of nanocarriers as drug delivery systems. For the former approach, we discuss the superiority of combination treatments compared to monotherapy in tumor cells based on their effects on regulated cell death. For the latter approach, we give a systematic overview of nanocarrier design principles used to deliver artemisinin-type drugs, including inorganic-based nanoparticles, liposomes, micelles, polymer-based nanoparticles, carbon-based nanoparticles, nanostructured lipid carriers and niosomes. Both approaches have yielded promising findings in vitro and in vivo, providing a strong scientific basis for further study and upcoming clinical trials

Effects of Scleral-lens Tear Clearance on Corneal Edema and Post-lens Tear Dynamics: A Pilot Study.

SignificanceThe present study with small-diameter scleral lenses (SLs) revealed that post-lens tear thickness (PoLTT) was significantly associated with post-lens tear mixing, but not with central corneal edema, after short-term SL wear.PurposeThe aim of this study was to investigate the influence of SL tear clearance (PoLTT) on central corneal thickness and post-lens tear dynamics during 5-hour lens wear.MethodsNeophytes with no active ocular disease were fitted bilaterally with SLs (hofocon A; 15.6-mm diameter; ~438-μm thickness; 97 Dk; 1.44 refractive index) with various initial PoLTT values ranging from 74 to 543 μm. Central corneal thickness and PoLTT were measured using optical coherence tomography during lens wear. Tear mixing was assessed using fluorogram and "out-in" method.ResultsThe mean central corneal edema after 5-hour lens wear was 1.51% (95% confidence interval, 1.26 to 1.76%; P < .001), reached its peak at 2-hour post-lens insertion (1.65% [95% confidence interval, 1.45 to 1.85%]), and was independent of PoLTT. The fastest fluorescence decay of the post-lens tear film was observed superiorly. The fluorescence decay rate increased from center to periphery in all quadrants except superiorly. An inverse relationship was found between PoLTT and fluorescence decay rate at both 20-minute and 5-hour wear after lens insertion (P < .05). Excluding observations with out-in time exceeding 5 minutes, we found a direct relationship between PoLTT at 20 minutes after lens insertion and out-in time (P = .047). The % change in the PoLTT after 5-hour wear was greater with a thinner initial tear clearance than those with a thicker one (P = .034).ConclusionsWithin our study parameters, a thinner PoLTT under a small-diameter SL was associated with faster PoLTT mixing. However, there was no relationship between PoLTT and central corneal thickness during 5-hour SL wear

Effects of scleral-lens oxygen transmissibility on corneal thickness: A pilot study.

PurposeTo investigate the effect of various oxygen transmissibilities (Dk/t) of scleral lenses and corneal thickness recovery time from overnight eye closure with patching on corneal edema during 5 h lens wear.MethodsScleral lenses (hofocon A, 15.6 mm diameter) were worn bilaterally with three different Dks (100, 140, and 160 Barrer). Central and peripheral corneal thickness (CCT and PCT) were measured using optical coherence tomography. Four subjects were randomly selected for one additional visit and asked to patch one eye before night sleeping. The patch was not removed until lens insertion to avoid corneal deswelling. Then CCT of both eyes was measured.ResultsTen neophytes with healthy eyes participated in the study. Mean [95% CI] Dk/t of the study lenses was 32.0 [29.2, 34.7] hBarrer/cm. Mean [95% CI] CCT immediately upon lens insertion and after 5 h of lens wear were 532.4 [520.3, 544.5] μm and 538.7 [526.5, 551.0] μm, respectively. Mean [95% CI] percentage change (%Δ) in CCT was 1.2% [0.9%, 1.5%], 1.2% [0.9%, 1.4%], and 0.8% [0.6%, 1.1%] for CCT, nasal PCT, and temporal PCT, respectively. There was an inverse relationship between temporal Dk/t and %ΔPCT (p < 0.05) while Dk/t was not found significantly associated with either CCT or nasal PCT. The patched eyes maintained a relatively stable CCT and showed progressive deswelling, starting and ending with 2.8% and 0.6%, respectively. In contrast, the unpatched eyes swelled, starting with nearly 0% and ending with 0.7% with a maximum swelling of 1.8%.ConclusionThere was limited amount of corneal edema induced by short-term scleral lens wear with lens Dk/t ranging from 21 to 47 hBarrer/cm and lenses with lower lens Dk/t did not induce significantly higher corneal swelling. Scleral lens insertion soon after overnight eye closure with patching did not introduce additional swelling for young and healthy eyes

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Artificial intelligence (AI) has been widely used in bioimage image analysis nowadays, but the efficiency of AI models, like the energy consumption and latency is not ignorable due to the growing model size and complexity, as well as the fast-growing analysis needs in modern biomedical studies. Like we can compress large images for efficient storage and sharing, we can also compress the AI models for efficient applications and deployment. In this work, we present EfficientBioAI, a plug-and-play toolbox that can compress given bioimaging AI models for them to run with significantly reduced energy cost and inference time on both CPU and GPU, without compromise on accuracy. In some cases, the prediction accuracy could even increase after compression, since the compression procedure could remove redundant information in the model representation and therefore reduce over-fitting. From four different bioimage analysis applications, we observed around 2-5 times speed-up during inference and 30-80$\%$ saving in energy. Cutting the runtime of large scale bioimage analysis from days to hours or getting a two-minutes bioimaging AI model inference done in near real-time will open new doors for method development and biomedical discoveries. We hope our toolbox will facilitate resource-constrained bioimaging AI and accelerate large-scale AI-based quantitative biological studies in an eco-friendly way, as well as stimulate further research on the efficiency of bioimaging AI.Comment: 17 pages, 6 figure

Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning

The placement of charging stations in areas with developing charging infrastructure is a critical component of the future success of electric vehicles (EVs). In Albany County in New York, the expected rise in the EV population requires additional charging stations to maintain a sufficient level of efficiency across the charging infrastructure. A novel application of Reinforcement Learning (RL) is able to find optimal locations for new charging stations given the predicted charging demand and current charging locations. The most important factors that influence charging demand prediction include the conterminous traffic density, EV registrations, and proximity to certain types of public buildings. The proposed RL framework can be refined and applied to cities across the world to optimize charging station placement.Comment: 25 pages with 12 figures. Shankar Padmanabhan and Aidan Petratos provided equal contributio

Radicalized by Thinness: Using a Model of Radicalization to Understand Pro-Anorexia Communities on Twitter

The rise in eating disorders, a condition with serious health complications, has been linked to the proliferation of idealized body images on social media platforms. However, the relationship between social media and eating disorders is more complex, with online platforms potentially enabling harmful behaviors by linking people to ``pro-ana'' communities that promote eating disorders. We conceptualize the growth of harmful pro-ana communities as a process of online radicalization. We show that a model of radicalization explains how individuals are driven to conversations about extreme behaviors, like fasting, to achieve the ``thin body'' goal, and how these conversations are validated by pro-ana communities. By facilitating social connections to like-minded others, a shared group identity and emotional support, social media platforms can trap individuals within toxic echo chambers that normalize extreme disordered eating behaviors and other forms of self-harm. Characterizing and quantifying the role of online communities in amplifying harmful conversations will support the development of strategies to mitigate their impact and promote better mental health

Thymidine Kinase 2 Deficiency-Induced mtDNA Depletion in Mouse Liver Leads to Defect beta-Oxidation

Thymidine kinase 2 (TK2) deficiency in humans causes mitochondrial DNA (mtDNA) depletion syndrome. To study the molecular mechanisms underlying the disease and search for treatment options, we previously generated and described a TK2 deficient mouse strain (TK2(-/-)) that progressively loses its mtDNA. The TK2(-/-) mouse model displays symptoms similar to humans harboring TK2 deficient infantile fatal encephalomyopathy. Here, we have studied the TK2(-/-) mouse model to clarify the pathological role of progressive mtDNA depletion in liver for the severe outcome of TK2 deficiency. We observed that a gradual depletion of mtDNA in the liver of the TK2(-/-) mice was accompanied by increasingly hypertrophic mitochondria and accumulation of fat vesicles in the liver cells. The levels of cholesterol and nonesterified fatty acids were elevated and there was accumulation of long chain acylcarnitines in plasma of the TK2(-/-) mice. In mice with hepatic mtDNA levels below 20%, the blood sugar and the ketone levels dropped. These mice also exhibited reduced mitochondrial beta-oxidation due to decreased transport of long chain acylcarnitines into the mitochondria. The gradual loss of mtDNA in the liver of the TK2(-/-) mice causes impaired mitochondrial function that leads to defect beta-oxidation and, as a result, insufficient production of ketone bodies and glucose. This study provides insight into the mechanism of encephalomyopathy caused by TK2 deficiency-induced mtDNA depletion that may be used to explore novel therapeutic strategies

Oxygen depletion recorded in upper waters of the glacial Southern Ocean

Oxygen depletion in the upper ocean is commonly associated with poor ventilation and storage of respired carbon, potentially linked to atmospheric CO2 levels. Iodine to calcium ratios (I/Ca) in recent planktonic foraminifera suggest that values less than ~2.5 μmol mol−1 indicate the presence of O2-depleted water. Here we apply this proxy to estimate past dissolved oxygen concentrations in the near surface waters of the currently well-oxygenated Southern Ocean, which played a critical role in carbon sequestration during glacial times. A down-core planktonic I/Ca record from south of the Antarctic Polar Front (APF) suggests that minimum O2 concentrations in the upper ocean fell below 70 μmol kg−1 during the last two glacial periods, indicating persistent glacial O2 depletion at the heart of the carbon engine of the Earth’s climate system. These new estimates of past ocean oxygenation variability may assist in resolving mechanisms responsible for the much-debated ice-age atmospheric CO2 decline