Optimization of multiple ecological infrastructures across the land-sea interface for coordination management: A case study around Laizhou Bay in China.

Ecological infrastructure (EI), providing ecosystem services across the land-sea interface, has been proposed as a key element in sustainable terrestrial-marine ecosystem coordinated governance. Terrestrial and marine ecosystems should be regarded as an integrated unit for guaranteeing coastal ecological security. However, the existing EI construction framework focused on terrestrial ecosystems, and few studies consider the composite characteristics of the terrestrial-marine ecosystem in coastal areas. In the case study of Laizhou Bay, China, this study proposes an optimization method for multiple ecological infrastructures (MEIs) across the land-sea interface. The method is oriented towards achieving trans-regional scale cohesion, enhancing terrestrial-riverine-marine linkages, providing adequate pathways for marine ecological protection, and promoting coordinated conservation of terrestrial and marine ecosystems. The results showed that: (1) The new optimization framework synthetically considering the terrestrial multi-scale EI networks cohesion, hydrological corridors, and marine conservation network is available. (2) The preliminary ecological sources (PESs) are mainly distributed in the eastern mountainous areas, the estuary of the Yellow River, and six marine protected areas. The spatial imbalance of EI resulted in four marine protected areas in the southwest of the Bohai Sea insufficiently connected between sea-to-sea ecological sources. (3) The integrated MEIs includes four newly added ecological sources (two each for land and sea), eight trans-regional ecological corridors, 17 hydrological corridors, and 11 marine ecological corridors. Through optimization, the MEIs avoid fragmentation across multi-scale terrestrial regions, promote river-based connectivity between land and sea, and increase pathways for marine ecological protection, thereby ensuring effective circulation of regional ecological materials. (4) MEIs-conserved priority areas include 12.4 km2 ecological pinch points and 6.39 km2 marine biological protective points. Focusing on these conserved priority areas provides spatial references for the implementation planning of MEIs. Compared with traditional respective ecosystem networks, the MEIs across land-sea interface optimization approach is feasible for terrestrial-marine ecosystem coordinated management.

Multisource information fusion method for vegetable disease detection.

Automated detection and identification of vegetable diseases can enhance vegetable quality and increase profits. Images of greenhouse-grown vegetable diseases often feature complex backgrounds, a diverse array of diseases, and subtle symptomatic differences. Previous studies have grappled with accurately pinpointing lesion positions and quantifying infection degrees, resulting in overall low recognition rates. To tackle the challenges posed by insufficient validation datasets and low detection and recognition rates, this study capitalizes on the geographical advantage of Shouguang, renowned as the "Vegetable Town," to establish a self-built vegetable base for data collection and validation experiments. Concentrating on a broad spectrum of fruit and vegetable crops afflicted with various diseases, we conducted on-site collection of greenhouse disease images, compiled a large-scale dataset, and introduced the Space-Time Fusion Attention Network (STFAN). STFAN integrates multi-source information on vegetable disease occurrences, bolstering the model's resilience. Additionally, we proposed the Multilayer Encoder-Decoder Feature Fusion Network (MEDFFN) to counteract feature disappearance in deep convolutional blocks, complemented by the Boundary Structure Loss function to guide the model in acquiring more detailed and accurate boundary information. By devising a detection and recognition model that extracts high-resolution feature representations from multiple sources, precise disease detection and identification were achieved. This study offers technical backing for the holistic prevention and control of vegetable diseases, thereby advancing smart agriculture. Results indicate that, on our self-built VDGE dataset, compared to YOLOv7-tiny, YOLOv8n, and YOLOv9, the proposed model (Multisource Information Fusion Method for Vegetable Disease Detection, MIFV) has improved mAP by 3.43%, 3.02%, and 2.15%, respectively, showcasing significant performance advantages. The MIFV model parameters stand at 39.07 M, with a computational complexity of 108.92 GFLOPS, highlighting outstanding real-time performance and detection accuracy compared to mainstream algorithms. This research suggests that the proposed MIFV model can swiftly and accurately detect and identify vegetable diseases in greenhouse environments at a reduced cost.

Global prevalence of claudin 18 isoform 2 in tumors of patients with locally advanced unresectable or metastatic gastric or gastroesophageal junction adenocarcinoma.

BACKGROUND: Limited data exist for global prevalence of claudin 18 isoform 2 (CLDN18.2) positivity and association of CLDN18.2 status with clinical and tumor characteristics in patients with locally advanced (LA) unresectable or metastatic gastric or gastroesophageal junction (mG/GEJ) adenocarcinoma. We report prevalence of CLDN18.2 positivity (phase 3; SPOTLIGHT, NCT03504397; GLOW, NCT03653507) and concordance of CLDN18.2 status between a subset of pair-matched tumor samples (phase 2, ILUSTRO, NCT03505320; phase 1, NCT03528629) from clinical studies of zolbetuximab. METHODS: Tumor samples from patients with LA unresectable or mG/GEJ adenocarcinoma were tested for CLDN18.2 status by immunohistochemistry. Human epidermal growth factor receptor 2 (HER2) expression was tested per central or local assessment. RESULTS: Across SPOTLIGHT and GLOW, the prevalence of CLDN18.2 positivity (≥ 75% of tumor cells demonstrating moderate-to-strong membranous CLDN18 staining) was 38.4%. Prevalence was similar in gastric versus GEJ adenocarcinoma samples and regardless of collection method (biopsy versus resection) or collection site (primary versus metastatic). CLDN18.2 positivity was most prevalent in patients with diffuse-type tumors. In ILUSTRO and the phase 1 study, concordance of CLDN18.2 positivity was 61.1% between archival (i.e., any time before treatment) and baseline (i.e., ≤ 3 months before first treatment) samples, and concordance of any CLDN18 staining (≥ 1% of tumor cells demonstrating moderate-to-strong membranous CLDN18 staining) was 88.9%. CONCLUSIONS: CLDN18.2 was a highly prevalent biomarker in patients with HER2-negative, LA unresectable or mG/GEJ adenocarcinoma. CLDN18.2 positivity remained relatively stable over time in many patients. Biomarker testing for CLDN18.2 should be considered in standard clinical practice in these patients.

Mapping Somatosensory Afferent Circuitry to Bone Identifies Neurotrophic Signals Required for Fracture Healing.

The profound pain accompanying bone fracture is mediated by somatosensory neurons, which also appear to be required to initiate bone regeneration following fracture. Surprisingly, the precise neuroanatomical circuitry mediating skeletal nociception and regeneration remains incompletely understood. Here, we characterized somatosensory dorsal root ganglia (DRG) afferent neurons innervating murine long bones before and after experimental long bone fracture in mice. Retrograde labeling of DRG neurons by an adeno-associated virus with peripheral nerve tropism showed AAV-tdT signal. Single cell transcriptomic profiling of 6,648 DRG neurons showed highest labeling across CGRP+ neuron clusters (6.9-17.2%) belonging to unmyelinated C fibers, thinly myelinated Aδ fibers and Aß-Field LTMR (9.2%). Gene expression profiles of retrograde labeled DRG neurons over multiple timepoints following experimental stress fracture revealed dynamic changes in gene expression corresponding to the acute inflammatory ( S100a8 , S100a9 ) and mechanical force ( Piezo2 ). Reparative phase after fracture included morphogens such as Tgfb1, Fgf9 and Fgf18 . Two methods to surgically or genetically denervate fractured bones were used in combination with scRNA-seq to implicate defective mesenchymal cell proliferation and osteodifferentiation as underlying the poor bone repair capacity in the presence of attenuated innervation. Finally, multi-tissue scRNA-seq and interactome analyses implicated neuron-derived FGF9 as a potent regulator of fracture repair, a finding compatible with in vitro assessments of neuron-to-skeletal mesenchyme interactions.

Monofluorophore-based Two-Photon Ratiometric Fluorescent Probe for the Quantitative Imaging of Fatty Acid Amide Hydrolase in Live Neurons and Mouse Brain Tissues.

Fatty acid amide hydrolase (FAAH) plays a crucial role in the metabolism of the endocannabinoid system by hydrolyzing a series of bioactive amides, whose abnormal levels are associated with neuronal disorders including Alzheimer's disease (AD). However, due to the lack of suitable quantitative sensing tools, real-time and accurate monitoring of the activity of FAAH in living systems remains unresolved. Herein, a novel enzyme-activated near-infrared two-photon ratiometric fluorescent probe (CANP) based on a naphthylvinylpyridine monofluorophore is successfully developed, in which the electron-withdrawing amide moiety is prone to be hydrolyzed to an electron-donating amine group under the catalysis of FAAH, leading to the activation of the intramolecular charge transfer process and the emergence of a new 80 nm red-shifted emission, thereby achieving a ratiometric luminescence response. Benefiting from the high selectivity, high sensitivity, and ratiometric response to FAAH, the probe CANP is successfully used to quantitatively monitor and image the FAAH levels in living neurons, by which an amyloid ß (Aß)-induced upregulation of endogenous FAAH activity is observed. Similar increases in FAAH activity are found in various brain regions of AD model mice, indicating a potential fatty acid amide metabolite-involved pathway for the pathological deterioration of AD. Moreover, our quantitative FAAH inhibition experiments further demonstrate the great value of CANP as an efficient visual probe for in situ and precise assessment of FAAH inhibitors in complex living systems, assisting the discovery of FAAH-related therapeutic agents.

The interfacial synergy of hierarchical FeCoNiP@FeNi-LDH heterojunction for efficient alkaline water splitting.

In response to the growing demand for clean, green, and sustainable energy sources, the development of cost-effective and durable high-activity overall water splitting electrocatalysts is urgently needed. In this study, the heterogeneous structure formed by the combination of FeCoNiP and FeNi-LDH was homogeneously dispersed onto CuO nanowires generated by in-situ oxidation of copper foam as a substrate using an electrodeposition method. This multilevel structure exhibits excellent bifunctional properties as an electrode material in alkaline solutions, for the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER) only 206 mV and 147 mV overpotentials are needed to achieve a current density of 100 mA cm-2 respectively. Full water electrolysis is thus enabled to take place at such a low cell voltage as 1.64 V to reach the current density of 100 mA cm-2, which exhibits a long-term stability of 30 h. These improved electrocatalytic performances stem from the construction of multilevel structures. The X-ray photoelectron spectroscopy suggests that strong electron transfer occurs between heterogeneous structures, thus facilitating the OER and HER process. The dispersion of CuO nanowires not only increases the electrochemically active surface areas but also improves the overall hydrophilic and aerophobic properties. This work highlights the positive effect of multilevel structure in the design of more efficient electrocatalysts and provides a reference for the preparation of other low-cost, high-activity bifunctional electrocatalysts.

Antibody-activation of connexin hemichannels in bone osteocytes with ATP release suppresses breast cancer and osteosarcoma malignancy.

Bone tissue represents the most frequent site of cancer metastasis. We developed a hemichannel-activating antibody, Cx43-M2. Cx43-M2, directly targeting osteocytes in situ, activates osteocytic hemichannels and elevates extracellular ATP, thereby inhibiting the growth and migration of cultured breast and osteosarcoma cancer cells. Cx43-M2 significantly decreases breast cancer metastasis, osteosarcoma growth, and osteolytic activity, while improving survival rates in mice. The antibody's inhibition of breast cancer and osteosarcoma is dose dependent in both mouse and human cancer metastatic models. Furthermore, Cx43-M2 enhances anti-tumor immunity by increasing the population and activation of tumor-infiltrating immune-promoting effector T lymphocytes, while reducing immune-suppressive regulatory T cells. Our results suggest that the Cx43-M2 antibody, by activating Cx43 hemichannels and facilitating ATP release and purinergic signaling, transforms the cancer microenvironment from a supportive to a suppressive state. Collectively, our study underscores the potential of Cx43-M2 as a therapeutic for treating breast cancer bone metastasis and osteosarcoma.

Human birth tissue products as a non-opioid medicine to inhibit post-surgical pain.

Pain after surgery causes significant suffering. Opioid analgesics cause severe side effects and accidental death. Therefore, there is an urgent need to develop non-opioid therapies for managing post-surgical pain. Local application of Clarix Flo (FLO), a human amniotic membrane (AM) product, attenuated established post-surgical pain hypersensitivity without exhibiting known side effects of opioid use in mice. This effect was achieved through direct inhibition of nociceptive dorsal root ganglion (DRG) neurons via CD44-dependent pathways. We further purified the major matrix component, the heavy chain-hyaluronic acid/pentraxin 3 (HC-HA/PTX3) from human AM that has greater purity and water solubility than FLO. HC-HA/PTX3 replicated FLO-induced neuronal and pain inhibition. Mechanistically, HC-HA/PTX3 induced cytoskeleton rearrangements to inhibit sodium current and high-voltage activated calcium current on nociceptive neurons, suggesting it is a key bioactive component mediating pain relief. Collectively, our findings highlight the potential of naturally derived biologics from human birth tissues as an effective non-opioid treatment for post-surgical pain and unravel the underlying mechanisms.

CRISPR/Cas9 edited SlGT30 improved both drought resistance and fruit yield through endoreduplication.

There is often a trade-off effect between different agronomic traits due to gene pleiotropy, leading to a negative correlation between yield and resistance. Consequently, using gene-editing techniques to develop superior traits becomes challenging. Genetic resources that defy this constraint are scarce but hold great potential as targets for improvement through the utilisation of CRISPR. Transcription factors are critical in modulating numerous gene expressions across diverse biological processes. Here, we found that the trihelix transcription factor SlGT30 plays a role in drought resistance and tomato fruit development. We edited the SlGT30 gene with CRISPR/Cas9 technology and found that the knockout lines showed decreased stomata density in the leaves and large fruits. Subsequent examination revealed that cell ploidy was impacted in the leaves and fruits of SlGT30 knockout lines. SlGT30 knockout affected cell size through the endoreduplication pathway, manifested in decreased stomata density and reduced water loss. Consequently, this resulted in an enhancement of drought resistance. For the fruit, both cell size and cell number increased in the fruit pericarp of knockout lines, improving the fruit size and weight accordingly. Therefore, SlGT30 represents a promising candidate gene for gene editing in breeding practice.

An efficient deep learning model for tomato disease detection.

Tomatoes possess significant nutritional and economic value. However, frequent diseases can detrimentally impact their quality and yield. Images of tomato diseases captured amidst intricate backgrounds are susceptible to environmental disturbances, presenting challenges in achieving precise detection and identification outcomes. This study focuses on tomato disease images within intricate settings, particularly emphasizing four prevalent diseases (late blight, gray leaf spot, brown rot, and leaf mold), alongside healthy tomatoes. It addresses challenges such as excessive interference, imprecise lesion localization for small targets, and heightened false-positive and false-negative rates in real-world tomato cultivation settings. To address these challenges, we introduce a novel method for tomato disease detection named TomatoDet. Initially, we devise a feature extraction module integrating Swin-DDETR's self-attention mechanism to craft a backbone feature extraction network, enhancing the model's capacity to capture details regarding small target diseases through self-attention. Subsequently, we incorporate the dynamic activation function Meta-ACON within the backbone network to further amplify the network's ability to depict disease-related features. Finally, we propose an enhanced bidirectional weighted feature pyramid network (IBiFPN) for merging multi-scale features and feeding the feature maps extracted by the backbone network into the multi-scale feature fusion module. This enhancement elevates detection accuracy and effectively mitigates false positives and false negatives arising from overlapping and occluded disease targets within intricate backgrounds. Our approach demonstrates remarkable efficacy, achieving a mean Average Precision (mAP) of 92.3% on a curated dataset, marking an 8.7% point improvement over the baseline method. Additionally, it attains a detection speed of 46.6 frames per second (FPS), adeptly meeting the demands of agricultural scenarios.

Microbial phosphorus-cycling genes in soil under global change.

The ongoing climate change on the Tibetan Plateau, leading to warming and precipitation anomalies, modifies phosphorus (P) cycling in alpine meadow soils. However, the interactions and cascading effects of warming and precipitation changes on the key "extracellular" and "intracellular" P cycling genes (PCGs) of bacteria are largely unknown for these P-limited ecosystems. We used metagenomics to analyze the individual and combined effects of warming and altered precipitation on soil PCGs and P transformation in a manipulation experiment. Warming and increased precipitation raised Olsen-P (bioavailable P, AP) by 13% and 20%, respectively, mainly caused by augmented hydrolysis of organic P compounds (NaOH-Po). The decreased precipitation reduced soil AP by 5.3%. The richness and abundance of the PCGs' community in soils on the cold Tibetan plateau were more sensitive to warming than altered precipitation. The abundance of PCGs and P cycling processes decreased under the influence of individual climate change factors (i.e., warming and altered precipitation alone), except for the warming combined with increased precipitation. Pyruvate metabolism, phosphotransferase system, oxidative phosphorylation, and purine metabolism (all "intracellular" PCG) were closely correlated with P pools under climate change conditions. Specifically, warming recruited bacteria with the phoD and phoX genes, which encode enzymes responsible for phosphoester hydrolysis (extracellular P cycling), strongly accelerated organic P mineralization and so, directly impacted P bioavailability in alpine soil. The interactions between warming and altered precipitation profoundly influenced the PCGs' community and facilitated microbial adaptation to these environmental changes. Warming combined with increased precipitation compensated for the detrimental impacts of the individual climate change factors on PCGs. In conclusion, warming combined with rising precipitation has boosting effect on most P-related functions, leading to the acceleration of P cycling within microbial cells and extracellularly, including mineralization and more available P release for microorganisms and plants in alpine soils.

Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma.

Disulfidptosis, a newly discovered type of programmed cell death, could be a mechanism of cell death controlled by SLC7A11. This could be closely associated with tumor development and advancement. Nevertheless, the biological mechanism behind disulfidptosis-related genes (DRGs) in sarcoma (SARC) is uncertain. This study identified three valuable genes (SLC7A11, RPN1, GYS1) associated with disulfidptosis in sarcoma (SARC) and developed a prognostic model. The multiple databases and RT-qPCR data confirmed the upregulated expression of prognostic DRGs in SARC. The TCGA internal and ICGC external validation cohorts were utilized to validate the predictive model capacity. Our analysis of DRG riskscores revealed that the low-risk group exhibited a more favorable prognosis than the high-risk group. Furthermore, we observed a significant association between DRG riskscores and different clinical features, immune cell infiltration, immune therapeutic sensitivity, drug sensitivity, and RNA modification regulators. In addition, two external independent immunetherapy datasets and clinical tissue samples were collected, validating the value of the DRGs risk model in predicting immunotherapy response. Finally, the SLC7A11/hsa-miR-29c-3p/LINC00511, and RPN1/hsa-miR-143-3p/LINC00511 regulatory axes were constructed. This study provided DRG riskscore signatures to predict prognosis and response to immunotherapy in SARC, guiding personalized treatment decisions.

GnT-V-mediated aberrant N-glycosylation of TIMP-1 promotes diabetic retinopathy progression.

BACKGROUND: Vascular endothelial growth factor (VEGF) signaling pathway plays an important role in the progression of diabetic retinopathy (DR). The glycosylation modification process of many key functional proteins in DR patients is abnormal. However, the potential involvement of abnormal N-glycoproteins in DR progression remains unclear. METHODS: Glycoproteomic profiling of the vitreous humor was performed. The level of protein and N-glycoprotein was confirmed by Western blot and Lectin blot, respectively. The cell viability and migration efficiency were detected by CCK-8 and Transwell assay. Flow cytometry was conducted to analyze the level of cell apoptosis and reactive oxygen specie. Malondialdehyde, superoxide dismutase activity and VEGF content were detected by Enzyme linked immunosorbent assays. The interaction of metalloproteinase 1 (TIMP-1) with N-acetylglucosamine transferase V (GnT-V) was detected by GST pull-down. Hematoxylin and eosin staining and choroidal and retinal flat mount stained with fluorescein isothiocyanate-Dextran assay were used for functional research in vivo. RESULTS: We found that N-glycosylation was up-regulated in DR rats and high glucose (HG)-induced human retinal pigment epithelium cell line ARPE-19. HG-induced inhibited the viability of ARPE-19 cells and promoted cell apoptosis and oxidative stress (OS), but these effects were reversed with kifunensine treatment, GnT-V knockdown and TIMP-1 mutation. Additionally, GnT-V binds to TIMP-1 to promote N-glycosylation of TIMP-1. Over-expression of GnT-V inhibited the viability of ARPE-19 cells and promoted cell apoptosis, OS and VEGF release, which these effects were reversed with TIMP-1 mutation. Interestingly, over-expression of GnT-V promoted retinal microvascular endothelial cells (RMECs) angiogenesis but was revered with TIMP-1 mutation, which was terminally boosted by VEGF-A treatment. Finally, knockdown of GnT-V relieved DR progression. CONCLUSION: The findings indicate that GnT-V can promote RMECs angiogenesis and ARPE-19 cells injury through activation VEGF signaling pathway by increasing TIMP-1 N-glycosylation level, which provides a new theoretical basis for the prevention of DR.

lncRNA TMEM161B-AS1 screened the onset of oral squamous cell carcinoma in HPV-infected patients, predicted poor prognosis, and regulated cell progression via modulating the miR-651-5p/BDNF axis.

Oral squamous cell carcinoma (OSCC) has become the most common HPV-related cancer with high invasion and metastasis. Exploring biomarkers for the screening and monitoring of OSCC, especially for the HPV-OSCC, would benefit patients' diagnosis and prognosis. This study evaluated the significance and mechanism of TMEM161B-AS1 and miR-651-5p in HPV-OSCC aiming to provide novel insight into the mechanism of HPV-OSCC development. Expression of TMEM161B-AS1 and miR-561-5p was analyzed in healthy individuals, HPV-infected non-OSCC patients, and HPV-OSCC patients using PCR. Their significance in HPV-OSCC occurrence and prognosis was evaluated by logistic regression, ROC, Kaplan-Meier, and Cox regression analysis. In OSCC cells, CCK8 and Transwell assays were employed for assessing cell growth and metastasis. The luciferase reporter assay and cell transfection were performed to evaluate the regulatory association between TMEM161B-AS1, miR-561-5p, and BDNF. Significant upregulation of TMEM161B-AS1 and downregulation of miR-561-5p were observed in oral HPV-infected patients. Both TMEM161B-AS1 and miR-651-5p served as risk factors for the occurrence of OSCC in oral HPV-infected patients and could distinguish HPV-OSCC patients from HPV-infected non-OSCC patients. Increased TMEM161B-AS1 and reduced miR-561-5p indicated severe development and adverse prognosis of HPV-OSCC patients. In OSCC cells, silencing TMEM161-AS1 suppressed cell proliferation and motility via negatively modulating miR-561-5p. miR-561-5p negatively regulated BDNF, which was considered the underlying mechanism of TMEM161B-AS1. Increasing TMEM161B-AS expression and decreasing miR-561-5p showed the occurrence of OSCC in HPV-infected patients and predicted malignant development and adverse prognosis. TMEME161B-AS1 served as a tumor promoter via regulating the miR-561-5p/BDNF axis.

Vegetable disease detection using an improved YOLOv8 algorithm in the greenhouse plant environment.

This study introduces YOLOv8n-vegetable, a model designed to address challenges related to imprecise detection of vegetable diseases in greenhouse plant environment using existing network models. The model incorporates several improvements and optimizations to enhance its effectiveness. Firstly, a novel C2fGhost module replaces partial C2f. with GhostConv based on Ghost lightweight convolution, reducing the model's parameters and improving detection performance. Second, the Occlusion Perception Attention Module (OAM) is integrated into the Neck section to better preserve feature information after fusion, enhancing vegetable disease detection in greenhouse settings. To address challenges associated with detecting small-sized objects and the depletion of semantic knowledge due to varying scales, an additional layer for detecting small-sized objects is included. This layer improves the amalgamation of extensive and basic semantic knowledge, thereby enhancing overall detection accuracy. Finally, the HIoU boundary loss function is introduced, leading to improved convergence speed and regression accuracy. These improvement strategies were validated through experiments using a self-built vegetable disease detection dataset in a greenhouse environment. Multiple experimental comparisons have demonstrated the model's effectiveness, achieving the objectives of improving detection speed while maintaining accuracy and real-time detection capability. According to experimental findings, the enhanced model exhibited a 6.46% rise in mean average precision (mAP) over the original model on the self-built vegetable disease detection dataset under greenhouse conditions. Additionally, the parameter quantity and model size decreased by 0.16G and 0.21 MB, respectively. The proposed model demonstrates significant advancements over the original algorithm and exhibits strong competitiveness when compared with other advanced object detection models. The lightweight and fast detection of vegetable diseases offered by the proposed model presents promising applications in vegetable disease detection tasks.

Flexible Copper-Based Thermistors Fabricated by Laser Direct Writing for Low-Temperature Sensing.

With the flexibilization tendency of traditional electronics, developing sensing devices for the low-temperature field is demanding. Here, we fabricated a flexible copper-based thermistor by a laser direct writing process with Cu ion precursors. The copper-based thermistor performs with excellent temperature sensing ability and high stability under different environments. We discussed the effect of laser power on the temperature sensitivity of the copper-based thermistor, explained the sensing mechanism of the as-written copper-based films, and fabricated a temperature sensor array for realizing temperature management in a specific zone. All of the investigations have demonstrated that such copper-based thermistors can be used as candidate devices for low-temperature sensing fields.

A robust and precise centroid positioning method for the weak beacon spot in long-distance inter-satellite optical wireless communications.

The centroid estimation of the beacon spot is crucial to the pointing, acquisition, and tracking subsystem in inter-satellite optical wireless communication (IsOWC), especially for the received very weak beacon caused by a long link distance. In this work, we propose an accurate centroid positioning method to calculate the centroid of such a weak beacon with a low peak signal-to-noise ratio. The proposed method is based on the idea that uses the normalized amplitude of the gray gradient to enhance the weights near the center of the beacon spot. Both comparative numerical simulation and experimental verification are implemented, which demonstrate the effectiveness and feasibility of the proposed method. Compared to the gray centroid method, interpolation-based method, Hough transform method, and Gaussian fitting method, the proposed method has stronger robustness and higher accuracy, which could be helpful to applications in IsOWC as well as beacon-based pointing and tracking systems.

Sestrin2 ameliorates diabetic retinopathy by regulating autophagy and ferroptosis.

Diabetic retinopathy (DR) is a serious microvascular complication of diabetes. The aim of this study was to explore the effect of Sestrin2 on DR through the regulation of autophagy and ferroptosis levels and its mechanism. In vitro and in vivo DR models were established by high glucose (HG) and streptozotocin (STZ) induction of ARPE-19 human retinal pigment epithelial cells and C57BL/6 mice, respectively. In this study, we demonstrated that after HG treatment, the activity of ARPE-19 cells was decreased, the apoptosis rate was increased, endoplasmic reticulum (ER) stress was activated, autophagy levels were decreased, and ferroptosis levels were increased. Overexpression of Sestrin2 enhanced cell viability, reduced apoptosis and ferroptosis, and enhanced autophagy. However, the effect of overexpression of Sestrin2 was attenuated after the addition of the STAT3 phosphorylation activator Colivelin TFA (C-TFA), the mTOR pathway activator MHY1485 or the autophagy inhibitor 3-methyladenine (3-MA). In addition, the effect of Sestrin2 knockdown on cells was opposite to the effect of overexpression of Sestrin2, while the effect of Sestrin2 knockdown was attenuated after treatment with the ER stress inhibitor 4-phenylbutyric acid (4-PBA). Animal experiments also confirmed the results of cell experiments and attenuated the effects of overexpression of Sestrin2 after injection of the ferroptosis activators erastin or 3-MA. Our study revealed that Sestrin2 inhibits ferroptosis by inhibiting STAT3 phosphorylation and ER stress and promoting autophagy levels, thereby alleviating DR.