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The amino acid antiporter system Xc − is important for the synthesis of glutathione (GSH) that functions to prevent lipid peroxidation and protect cells from nonapoptotic, iron-dependent death (i.e., ferroptosis). While the activity of system Xc − often positively correlates with the expression level of its light chain encoded by SLC7A11 , inhibition of system Xc − activity by small molecules (e.g., erastin) causes a decrease in the intracellular GSH level, leading to ferroptotic cell death. How system Xc − is regulated during ferroptosis remains largely unknown. Here we report that activating transcription factor 3 (ATF3), a common stress sensor, can promote ferroptosis induced by erastin. ATF3 suppressed system Xc − , depleted intracellular GSH, and thereby promoted lipid peroxidation induced by erastin. ATF3 achieved this activity through binding to the SLC7A11 promoter and repressing SLC7A11 expression in a p53-independent manner. These findings thus add ATF3 to a short list of proteins that can regulate system Xc − and promote ferroptosis repressed by this antiporter.

Background The ataxia telangiectasia and Rad3-related (ATR) checkpoint kinase 1 (CHK1) pathway plays an essential role in suppressing replication stress from DNA damage and oncogene activation. Main body Preclinical studies have shown that cancer cells with defective DNA repair mechanisms or cell cycle checkpoints may be particularly sensitive to ATR inhibitors. Preclinical and clinical data from early-phase trials on three ATR inhibitors (M6620, AZD6738, and BAY1895344), either as monotherapy or in combination, were reviewed. Conclusion Data from ATR inhibitor-based combinational trials might lead to future expansion of this therapy to homologous recombination repair pathway-proficient cancers and potentially serve as a rescue therapy for patients who have progressed through poly ADP-ribose polymerase inhibitors.

Background Recently, deep learning technologies have rapidly expanded into medical image analysis, including both disease detection and classification. As far as we know, migraine is a disabling and common neurological disorder, typically characterized by unilateral, throbbing and pulsating headaches. Unfortunately, a large number of migraineurs do not receive the accurate diagnosis when using traditional diagnostic criteria based on the guidelines of the International Headache Society. As such, there is substantial interest in developing automated methods to assist in the diagnosis of migraine. Methods To the best of our knowledge, no studies have evaluated the potential of deep learning technologies in assisting with the classification of migraine patients. Here, we used deep learning methods in combination with three functional measures (the amplitude of low-frequency fluctuations, regional homogeneity and regional functional correlation strength) based on rs-fMRI data to distinguish not only between migraineurs and healthy controls, but also between the two subtypes of migraine. We employed 21 migraine patients without aura, 15 migraineurs with aura, and 28 healthy controls. Results Compared with the traditional support vector machine classifier, which has an accuracy of 83.67%, our Inception module-based convolutional neural network approach showed a significant improvement in classification output (over 86.18%). Our data also indicate that the Inception module-based CNN performs better than the AlexNet-based CNN (Inception module-based CNN reached an accuracy of 99.25%). Finally, we also found that regional functional correlation strength (RFCS) could be regarded as the optimum input out of the three indices (ALFF, ReHo, RFCS). Conclusions Overall, our study shows that combining the three functional measures of rs-fMRI with deep learning classification is a powerful method to distinguish between migraineurs and healthy individuals. Our data also highlight that deep learning-based frameworks could be used to develop more complicated models or systems to aid in clinical decision making in the future.

Conventional liquid-phase methods lack precise control in synthesizing and processing materials with macroscopic sizes and atomic thicknesses. Water interfaces are ubiquitous and unique in catalyzing many chemical reactions. However, investigations on two-dimensional (2D) materials related to water interfaces remain limited. Here we report the growth of millimeter-sized 2D PbI 2 single crystals at the water-air interface. The growth mechanism is based on an inherent ion-specific preference, i.e. iodine and lead ions tend to remain at the water-air interface and in bulk water, respectively. The spontaneous accumulation and in-plane arrangement within the 2D crystal of iodide ions at the water-air interface leads to the unique crystallization of PbI 2 as well as other metal iodides. In particular, PbI 2 crystals can be customized to specific thicknesses and further transformed into millimeter-sized mono- to few-layer perovskites. Additionally, we have developed water-based techniques, including water-soaking, spin-coating, water-etching, and water-flow-assisted transfer to recycle, thin, pattern, and position PbI 2 , and subsequently, perovskites. Our water-interface mediated synthesis and processing methods represents a significant advancement in achieving simple, cost-effective, and energy-efficient production of functional materials and their integrated devices. Here, the authors report the growth of millimetre-scale 2D PbI 2 single crystals via the spontaneous accumulation and in-plane arrangement of iodide ions at the water-air interface. The metal iodide crystals could be thinned down to a single monolayer via water etching, and subsequently converted into perovskite optoelectronic devices.

In sustaining arch locked-segment-type slopes, natural soil arches play a key anti-sliding role in the slope's evolution. In this study, a self-developed model test device was used to simulate the whole process of deformation evolution of sustaining arch locked-segment-type slopes, and the formation of natural sustaining arch and its locking control effect on slope stability were studied. The test results show that the continuous formation and progressive destruction of the sustaining arch were observed. The sustaining arch formed in the second time has the best locking effect, and the anti-sliding force reaches its stress peak point. However, the slope is not in a critically unstable state, instead, the stress is continuously adjusted to form a larger range of soil arch to resist the slope thrust. Consequently, the slope destabilizes until the ultimate shear strength of arch foots is exceeded, at which point the critical arch height of the arch is reached. The critical arch height mechanical model for slope stability analysis was developed based on the soil arching effect and limit equilibrium theory. The applicability of the model was demonstrated by the physical test and Xintan slope data, which can provide some guidance for early warning of landslides.

The knee osteoarthritis (KOA) pain is the most common form of arthritis pain affecting millions of people worldwide. Long-term KOA pain causes motor impairment and affects affective and cognitive functions. However, little is known about the structural and functional abnormalities induced by long-term KOA pain. In this work, high-resolution structural magnetic resonance imaging (sMRI) and resting-state functional MRI (rs-fMRI) data were acquired in patients with KOA and age-, sex-matched healthy controls (HC). Gray matter volume (GMV) and fractional amplitude of low-frequency fluctuation (fALFF) were used to study the structural and functional abnormalities in patients with KOA. Compared with HC, patients with KOA showed reduced GMV in bilateral insula and bilateral hippocampus, and reduced fALFF in left cerebellum, precentral gyrus, and the right superior occipital gyrus. Patients with KOA also showed increased fALFF in left insula and bilateral hippocampus. In addition, the abnormal GMV in left insula and fALFF in left fusiform were closely correlated with the pain severity or disease duration. These results indicated that long KOA pain leads to brain structural and functional impairments in motor, visual, cognitive, and affective functions that related to brain areas. Our findings may facilitate to understand the neural basis of KOA pain and the future therapy to relieve disease symptoms.

Crystallization-induced photoluminescence weakening was recently revealed in ultrasmall metal nanoparticles. However, the fundamentals of the phenomenon are not understood yet. By obtaining conformational isomer crystals of gold nanoclusters, we investigate crystallization-induced photoluminescence weakening and reveal that the shortening of interparticle distance decreases photoluminescence, which is further supported by high-pressure photoluminescence experiments. To interpret this, we propose a distance-dependent non-radiative transfer model of excitation electrons and support it with additional theoretical and experimental results. This model can also explain both aggregation-induced quenching and aggregation-induced emission phenomena. This work improves our understanding of aggregated-state photoluminescence, contributes to the concept of conformational isomerism in nanoclusters, and demonstrates the utility of high pressure studies in nanochemistry. Crystallization-induced photoluminescence weakening in ultrasmall metal nanoparticles is not well understood. Here, the authors study conformational isomers of gold nanoclusters to examine the effect of interparticle distance on this phenomenon, and propose a model of distance-dependent non-radiative excitation electron transfer.

Checkpoint kinase 1 (CHK1) is critical for cell survival under replication stress (RS). CHK1 inhibitors (CHK1i’s) in combination with chemotherapy have shown promising results in preclinical studies but have displayed minimal efficacy with substantial toxicity in clinical trials. To explore combinatorial strategies that can overcome these limitations, we perform an unbiased high-throughput screen in a non-small cell lung cancer (NSCLC) cell line and identify thioredoxin1 (Trx1), a major component of the mammalian antioxidant-system, as a determinant of CHK1i sensitivity. We establish a role for redox recycling of RRM1, the larger subunit of ribonucleotide reductase (RNR), and a depletion of the deoxynucleotide pool in this Trx1-mediated CHK1i sensitivity. Further, the TrxR inhibitor auranofin, an approved anti-rheumatoid arthritis drug, shows a synergistic interaction with CHK1i via interruption of the deoxynucleotide pool. Together, we show a pharmacological combination to treat NSCLC that relies on a redox regulatory link between the Trx system and mammalian RNR activity. The clinical application of inhibitors targeting checkpoint kinase 1 (CHK1) is challenged by limited efficacy. Here, the authors identify that thioredoxin (Trx) system inhibition mediates sensitivity to CHK1 inhibitor via regulating the activity of ribonucleotide reductase, demonstrating the synergistic effect of CHK1 inhibitor and inhibitors targeting Trx system in lung cancer models.

The well-known ion migration in mixed halide perovskites has been intensely investigated within the area under uniform light illumination. Here, the authors demonstrate that the anion segregation in these materials is a nonlocal effect of which the ion redistribution may occur at a macroscopic or mesoscopic scale beyond.Ions in mixed halide perovskite migrate to the non-illuminated region to form a macroscopic ring structure under laser irradiation, which is reversible after removing the light.

Many functional neuroimaging studies have reported differential patterns of spontaneous brain activity in posttraumatic stress disorder (PTSD), but the findings are inconsistent and have not so far been quantitatively reviewed. The present study set out to determine consistent, specific regional brain activity alterations in PTSD, using the Effect Size Signed Differential Mapping technique to conduct a quantitative meta-analysis of resting-state functional neuroimaging studies of PTSD that used either a non-trauma (NTC) or a trauma-exposed (TEC) comparison control group. Fifteen functional neuroimaging studies were included, comparing 286 PTSDs, 203 TECs and 155 NTCs. Compared with NTC, PTSD patients showed hyperactivity in the right anterior insula and bilateral cerebellum, and hypoactivity in the dorsal medial prefrontal cortex (mPFC); compared with TEC, PTSD showed hyperactivity in the ventral mPFC. The pooled meta-analysis showed hypoactivity in the posterior insula, superior temporal, and Heschl’s gyrus in PTSD. Additionally, subgroup meta-analysis (non-medicated subjects vs. NTC) identified abnormal activation in the prefrontal-limbic system. In meta-regression analyses, mean illness duration was positively associated with activity in the right cerebellum (PTSD vs. NTC), and illness severity was negatively associated with activity in the right lingual gyrus (PTSD vs. TEC).