A novel treatment strategy for lapatinib resistance in a subset of HER2-amplified gastric cancer

Background Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide. Human epidermal growth factor receptor 2 (HER2) amplification occurs in approximately 13–23% of all GC cases and patients with HER2 overexpression exhibit a poor prognosis. Lapatinib, a dual EGFR/HER2 tyrosine kinase inhibitor, is an effective agent to treat HER2-amplified breast cancer but it failed in gastric cancer (GC) clinical trials. However, the molecular mechanism of lapatinib resistance in HER2-amplified GC is not well studied. Methods We employed an unbiased, genome-scale screening with pooled CRISPR library on HER2-amplified GC cell lines to identify genes that are associated with resistance to lapatinib. To validate the candidate genes, we applied in vitro and in vivo pharmacological tests to confirm the function of the target genes. Results We found that loss of function of CSK or PTEN conferred lapatinib resistance in HER2-amplified GC cell lines NCI-N87 and OE19, respectively. Moreover, PI3K and MAPK signaling was significantly increased in CSK or PTEN null cells. Furthermore, in vitro and in vivo pharmacological study has shown that lapatinib resistance by the loss of function of CSK or PTEN, could be overcome by lapatinib combined with the PI3K inhibitor copanlisib and MEK inhibitor trametinib. Conclusions Our study suggests that loss-of-function mutations of CSK and PTEN cause lapatinib resistance by re-activating MAPK and PI3K pathways, and further proved these two pathways are druggable targets. Inhibiting the two pathways synergistically are effective to overcome lapatinib resistance in HER2-amplified GC. This study provides insights for understanding the resistant mechanism of HER2 targeted therapy and novel strategies that may ultimately overcome resistance or limited efficacy of lapatinib treatment for subset of HER2 amplified GC.This study is supported in part by the operational funds from The First Affiliated Hospital of Xian Jiaotong University. C. Lee was a distinguished Ewha Womans University Professor supported in part by the Ewha Womans University Research grant of 2017–2019

Tailored growth of single-crystalline InP tetrapods

Despite the technological importance of colloidal covalent III-V nanocrystals with unique optoelectronic properties, their synthetic process still has challenges originating from the complex energy landscape of the reaction. Here, we present InP tetrapod nanocrystals as a crystalline late intermediate in the synthetic pathway that warrants controlled growth. We isolate tetrapod intermediate species with well-defined surfaces of (110) and ((1) over bar(1) over bar(1) over bar) via the suppression of further growth. An additional precursor supply at low temperature induces [(1) over bar(1) over bar(1) over bar]-specific growth, whereas the [110]-directional growth occurs over the activation barrier of 65.7 kJ/mol at a higher temperature, thus finalizes into the (111)-faceted tetrahedron nanocrystals. We address the use of late intermediates with well-defined facets at the sub-10 nm scale for the tailored growth of covalent III-V nanocrystals and highlight the potential for the directed approach of nanocrystal synthesis

Planning for Sustainability in Small Municipalities: The Influence of Interest Groups, Growth Patterns, and Institutional Characteristics

How and why small municipalities promote sustainability through planning efforts is poorly understood. We analyzed ordinances in 451 Maine municipalities and tested theories of policy adoption using regression analysis.We found that smaller communities do adopt programs that contribute to sustainability relevant to their scale and context. In line with the political market theory, we found that municipalities with strong environmental interests, higher growth, and more formal governments were more likely to adopt these policies. Consideration of context and capacity in planning for sustainability will help planners better identify and benefit from collaboration, training, and outreach opportunities

Alcohol-Induced Blackout

For a long time, alcohol was thought to exert a general depressant effect on the central nervous system (CNS). However, currently the consensus is that specific regions of the brain are selectively vulnerable to the acute effects of alcohol. An alcohol-induced blackout is the classic example; the subject is temporarily unable to form new long-term memories while relatively maintaining other skills such as talking or even driving. A recent study showed that alcohol can cause retrograde memory impairment, that is, blackouts due to retrieval impairments as well as those due to deficits in encoding. Alcoholic blackouts may be complete (en bloc) or partial (fragmentary) depending on severity of memory impairment. In fragmentary blackouts, cueing often aids recall. Memory impairment during acute intoxication involves dysfunction of episodic memory, a type of memory encoded with spatial and social context. Recent studies have shown that there are multiple memory systems supported by discrete brain regions, and the acute effects of alcohol on learning and memory may result from alteration of the hippocampus and related structures on a cellular level. A rapid increase in blood alcohol concentration (BAC) is most consistently associated with the likelihood of a blackout. However, not all subjects experience blackouts, implying that genetic factors play a role in determining CNS vulnerability to the effects of alcohol. This factor may predispose an individual to alcoholism, as altered memory function during intoxication may affect an individual’s alcohol expectancy; one may perceive positive aspects of intoxication while unintentionally ignoring the negative aspects. Extensive research on memory and learning as well as findings related to the acute effects of alcohol on the brain may elucidate the mechanisms and impact associated with the alcohol-induced blackout

Alcohol-Induced Blackout

For a long time, alcohol was thought to exert a general depressant effect on the central nervous system (CNS). However, currently the consensus is that specific regions of the brain are selectively vulnerable to the acute effects of alcohol. An alcohol-induced blackout is the classic example; the subject is temporarily unable to form new long-term memories while relatively maintaining other skills such as talking or even driving. A recent study showed that alcohol can cause retrograde memory impairment, that is, blackouts due to retrieval impairments as well as those due to deficits in encoding. Alcoholic blackouts may be complete (en bloc) or partial (fragmentary) depending on severity of memory impairment. In fragmentary blackouts, cueing often aids recall. Memory impairment during acute intoxication involves dysfunction of episodic memory, a type of memory encoded with spatial and social context. Recent studies have shown that there are multiple memory systems supported by discrete brain regions, and the acute effects of alcohol on learning and memory may result from alteration of the hippocampus and related structures on a cellular level. A rapid increase in blood alcohol concentration (BAC) is most consistently associated with the likelihood of a blackout. However, not all subjects experience blackouts, implying that genetic factors play a role in determining CNS vulnerability to the effects of alcohol. This factor may predispose an individual to alcoholism, as altered memory function during intoxication may affect an individual‟s alcohol expectancy; one may perceive positive aspects of intoxication while unintentionally ignoring the negative aspects. Extensive research on memory and learning as well as findings related to the acute effects of alcohol on the brain may elucidate the mechanisms and impact associated with the alcohol- induced blackout

Weight Minimization of Type 2 Composite Pressure Vessel for Fuel Cell Electric Vehicles Considering Mechanical Safety with Kriging Metamodel

In recent years, increased sales of fuel cell electric vehicles (FCEVs) have required composite overwrapped pressure vessel (COPV) designs to be lightweight and allow safe high-pressure hydrogen storage. In this study, we propose the weight minimization of Type 2 COPVs for FCEVs considering mechanical safety. Steel liner thickness, ply thickness, ply orientation, and the number of plies were set as design variables, and weight minimization was performed. For the constraints of optimization, the Tsai–Wu failure index of the composite layer and von Mises stress of the steel liner are considered. The design of experiments (DoE) was conducted to generate kriging model and perform sensitivity analysis. The optimized design of Type 2 COPVs was determined by satisfying all constraints, with significant weight reduction and preserved mechanical safety of the structure

Synaptic Transistors Based on PVA: Chitosan Biopolymer Blended Electric-Double-Layer with High Ionic Conductivity

This study proposed a biocompatible polymeric organic material-based synaptic transistor gated with a biopolymer electrolyte. A polyvinyl alcohol (PVA):chitosan (CS) biopolymer blended electrolyte with high ionic conductivity was used as an electrical double layer (EDL). It served as a gate insulator with a key function as an artificial synaptic transistor. The frequency-dependent capacitance characteristics of PVA:CS-based biopolymer EDL were evaluated using an EDL capacitor (Al/PVA: CS blended electrolyte-based EDL/Pt configuration). Consequently, the PVA:CS blended electrolyte behaved as an EDL owing to high capacitance (1.53 µF/cm2) at 100 Hz and internal mobile protonic ions. Electronic synaptic transistors fabricated using the PVA:CS blended electrolyte-based EDL membrane demonstrated basic artificial synaptic behaviors such as excitatory post-synaptic current modulation, paired-pulse facilitation, and dynamic signal-filtering functions by pre-synaptic spikes. In addition, the spike-timing-dependent plasticity was evaluated using synaptic spikes. The synaptic weight modulation was stable during repetitive spike cycles for potentiation and depression. Pattern recognition was conducted through a learning simulation for artificial neural networks (ANNs) using Modified National Institute of Standards and Technology datasheets to examine the neuromorphic computing system capability (high recognition rate of 92%). Therefore, the proposed synaptic transistor is suitable for ANNs and shows potential for biological and eco-friendly neuromorphic systems