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Background: Classic trigeminal neuralgia (CTN) seriously affects patients' quality of life. Percutaneous balloon compression (PBC) is a surgical program for treating trigeminal neuralgia. But some patients are ineffective or relapse after treatment. The aim is to use machine learning to construct clinical imaging models to predict relapse after treatment (PBC). Methods: The clinical data and intraoperative balloon imaging data of CTN from January 2017 to August 2023 were retrospectively analyzed. The relationship between least absolute shrinkage and selection operator and random forest prediction of PBC postoperative recurrence, ROC curve and decision -decision curve analysis is used to evaluate the impact of imaging histology on TN recurrence. Results: Imaging features, like original_shape_Maximum2D, DiameterRow, Original_Shape_Elongation, etc. predict the prognosis of TN on PBC. The areas under roc curve were 0.812 and 0.874, respectively. The area under the ROC curve of the final model is 0.872. DCA and calibration curves show that nomogram has a promising future in clinical application. Conclusion: The combination of machine learning and clinical imaging and clinical information has the good potential of predicting PBC in CTN treatment. The efficacy of CTN is suitable for clinical applications of CTN patients after PBC. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the risk factors for short-term residual low back pain (SRBP) following percutaneous kyphoplasty (PKP) in patients with initial thoracolumbar osteoporotic vertebral compression fractures (OVCFs). Methods: The clinical data of 389 patients with primary thoracolumbar OVCFs treated with PKP in our hospital from January 2018 to December 2022 were retrospectively analysed. A numerical rating scale (NRS) was used to evaluate whether SRBP was present 2 days after the operation. Patients with NRS scores > 4 were assigned to the SRBP group, and those with NRS scores ≤ 4 were assigned to the non-SRBP group. The general clinical data and surgical imaging-related data of the two groups were statistically analysed. Risk factors were analysed using binary logistic regression analysis. Results: Binary logistic regression analysis showed four independent predictors of SRBP after PKP, including bone mineral density (BMD) (OR = 0.087, P = 0.044), preoperative injured vertebral kyphosis (OR = 1.26, P = 0.01), preoperative thoracolumbar fascia injury (TLFI) (OR = 8.929, P < 0.001), and cement distribution type (OR = 5.921, P < 0.001) and bone cement filling ratio (OR = 0.651, P < 0.001). Conclusions: A decreased BMD, a larger preoperative kyphosis angle of the injured vertebra, preoperative TLFI, bone cement distributed in blocks and a low cement filling ratio of the injured vertebra are closely related to the occurrence of SRBP in OVCF patients after PKP. Clinicians should pay more attention to the prevention and treatment of risk indicators to further improve the therapeutic effect of PKP. Trial registration: The trial was registered in the China Trial Registry (ChiCTR 2200067164). [ABSTRACT FROM AUTHOR]

The decline in birth rates has raised concerns about the safety of infants and young children (0–18 months), particularly those who suffer suffocation or even death during sleep from their own or external causes. How to ensure that infants and young children can safely pass through this dangerous period after birth is the focus of this project. This article focuses on sleeping infants and young children as the subject of research. Blood oxygen sensors and heart rate sensors attached to socks are used to monitor changes in blood oxygen and heart rate when infants and young children experience asphyxia. The changes are then transmitted via Bluetooth to a mobile app and an alarm sound is generated to act as a good warning. At the same time, the researchers received good feedback from testing the garments on two babies and toddlers, indicating they provide an effective warning. [ABSTRACT FROM AUTHOR]

This study introduces a sophisticated methodology that integrates 3D assessment technology for the reorganization and recycling of retired lithium-ion battery packs, aiming to mitigate environmental challenges and enhance sustainability in the electric vehicle sector. By deploying a kernel extreme learning machine (KELM), variational mode decomposition (VMD), and an advanced sparrow search algorithm (SSA), the research achieves a marked increase in the precision of battery classification and performance forecasting. Implementing a three-dimensional dynamic evaluation model, the study optimizes battery pack grouping strategies, culminating in superior secondary utilization rates, extended operational lifespans, and minimized ecological footprints. The research demonstrates that balanced weight distribution strategies, which maximize energy density to 61.37571 Wh/L and cycle counts up to 947 cycles, are pivotal for the efficient reorganization of battery packs, substantiating the economic feasibility and environmental sustainability of recycling initiatives. Future endeavors will extend this research to investigate the influence of diverse battery materials and morphologies on reorganization efficacy, with the aim of broadening the application horizons to include real-world scenarios, thereby refining battery performance and lifespan predictions and propelling forward the frontiers of recycling technology and policy development. [ABSTRACT FROM AUTHOR]

Osteopetrosis is an inherited metabolic disease, characterized by increased bone density and narrow marrow cavity. Patients with severe osteopetrosis exhibit abnormal bone brittleness, anemia, and infection complications, which commonly cause death within the first decade of life. Pathologically, osteopetrosis impairs not only the skeletal system, but also the hemopoietic and immune systems during development, while the underlying osteoimmunological mechanisms remain unclear. Osteoclastic mutations are regarded as the major causes of osteopetrosis, while osteoclast non-autonomous theories have been proposed in recent years with unclear underlying mechanisms. Retinoic acid (RA), the metabolite of Vitamin A, is an essential requirement for skeletal and hematopoietic development, through the activation of retinoic acid signaling. RA can relieve osteopetrosis symptoms in some animal models, while its effect on bone health is still controversial and the underlying mechanisms remain unclear. In this study, we constructed an osteoblast-specific inhibitory retinoic acid signaling mouse model and surprisingly found it mimicked the symptoms of osteopetrosis found in clinical cases: dwarfism, increased imperfectly-formed trabecular bone deposition with a reduced marrow cavity, thin cortical bone with a brittle skeleton, and hematopoietic and immune dysfunction. Micro-CT, the three-point bending test, and histological analysis drew a landscape of poor bone quality. Single-cell RNA sequencing (scRNA-seq) of the femur and RNA-seq of osteoblasts uncovered an atlas of pathological skeletal metabolism dysfunction in the mutant mice showing that osteogenesis was impaired in a cell-autonomous manner and osteoclastogenesis was impaired via osteoblast-osteoclast crosstalk. Moreover, scRNA-seq of bone marrow and flow cytometry of peripheral blood, spleen, and bone marrow uncovered pathology in the hematopoietic and immune systems in the mutant mice, mimicking human osteopetrosis. Results showed that hematopoietic progenitors and B lymphocyte differentiation were affected and the osteoblast-dominated cell crosstalk was impaired, which may result from transcriptional impairment of the ligands Pdgfd and Sema4d. In summary, we uncovered previously unreported pathogenesis of osteopetrosis-like disorder in mice with skeletal, hematopoietic, and immune system dysfunction, which was induced by the inhibition of retinoic acid signaling in osteoblasts, and sheds new insights into a potential treatment for osteopetrosis. [ABSTRACT FROM AUTHOR]

Image super‐resolution (SR) has been widely applied in remote sensing to generate high‐resolution (HR) images without increasing hardware costs. However, SR is a severe ill‐posed problem. As deep learning advances, existing methods have solved this problem to a certain extent. However, the complex spatial distribution of remote sensing images still poses a challenge in effectively extracting abundant high‐frequency details from the images. Here, a single‐image super‐resolution (SISR) network based on the generative adversarial network (GAN) for remote sensing is presented, called JOA‐GAN. Firstly, a joint‐attention module (JOA) is proposed to focus the network on high‐frequency regions in remote sensing images to enhance the quality of image reconstruction. In the generator network, a multi‐scale densely connected feature extraction block (ERRDB) is proposed, which acquires features at different scales using MSconv blocks containing multi‐scale convolutions and automatically adjusts the features by JOA. In the discriminator network, the relative discriminator is used to compute the relative probability instead of the absolute probability, which helps the network learn clearer and more realistic texture details. JOA‐GAN is compared with other advanced methods, and the results demonstrate that JOA‐GAN has improved objective evaluation metrics and achieved superior visual effects. [ABSTRACT FROM AUTHOR]

Background: The co-occurrence of Lemierre's syndrome, primarily triggered by Fusobacterium necrophorum following oropharyngeal infection, with diabetic ketoacidosis (DKA) in diabetes mellitus (DM) patients, underscores a rare but life-threatening clinical scenario. Lemierre's syndrome induced DKA is extremely rare, with only one case report in adult and no case yet reported in elderly. Case Presentation: We reported a case of a 69-year-old female who presented with DKA triggered by deep neck space infection (DNSI), leading to rapid clinical deterioration within 6 h that necessitated high flow nasal cannula (HFNC) and antibiotic administration. Laboratory findings included leukocytosis, elevated serum C-reactive protein, hyperglycemia, ketonemia, and severe metabolic acidosis. Culture of the fluid from a neck mass puncture drainage and blood were positive for Klebsiella pneumoniae. The patient was further complicated by thrombosis of the left internal jugular vein with extension to the sigmoid and a neck abscess surrounding the carotid artery sheath, consistent with Lemierre's syndrome. This condition was managed aggressively with fluid resuscitation, insulin therapy, surgical drainage, antibiotics, and anticoagulation led to a significant improvement in her condition. Following a 13-day hospitalization, there was significant clinical improvement, culminating in the patient's discharge. Conclusions: The case highlights the need for greater awareness and understanding of the interrelated and mutually promoting conditions of DKA and Lemierre's syndrome among clinicians. Early recognition and treatment are crucial to prevent mortality in such complex cases. [ABSTRACT FROM AUTHOR]

Purpose: A major limitation of long-term peritoneal dialysis (PD) is peritoneal membrane dysfunction characterized by faster peritoneal solute-transport rate (PSTR). This study aimed to identify efficient complement factors in peritoneal effluents of continuous ambulatory peritoneal dialysis (CAPD) patients that can predict the PSTR. Methods: A multiplex suspension protein array was used to screened related complement pathways in overnight peritoneal effluents among 58 CAPD patients. Then the related complement factors in lectin and classical pathways in effluents were analyzed using ELISA kits among another cohort of 129 CAPD patients. Logistic regression modeling was fitted to predict the PSTR of PD patients. Results: The multiplex suspension protein array showed complement factors including C2, C4b, C5, C5a, Factor D, Factor I, and MBL were detected in effluents of CAPD patients, and the effluent C2 Appearance rate (Ar) and C4b Ar levels were significantly correlated with D/P Cr and D/D0 glucose. The levels of effluents MASP-1 Ar, M-Ficolin Ar, C2 Ar and C4b Ar, which belong to the lectin pathway were also positively correlated with D/P Cr according the ELISA results and these parameters were expressed higher in the high and high-average (H/HA) groups according to the PET results. Moreover, effluent Masp-1 was independently associated with increased PSTR and adverse events related peritoneal transport function failure. Conclusion: This study suggested that the lectin pathway may be involved in local complement activation and peritoneal injury of PD patients, intraperitoneal level of Masp-1 was an independent predictor of increased PSTR in PD patients. [ABSTRACT FROM AUTHOR]

Dobinin K is a novel eudesmane sesquiterpenoids compound isolated from the root of Dobinea delavayi and displays potential antiplasmodial activity in vivo. Here, we evaluate the antiplasmodial activity of dobinin K in vitro and study its acting mechanism. The antiplasmodial activity of dobinin K in vitro was evaluated by concentration-, time-dependent, and stage-specific parasite inhibition assay. The potential target of dobinin K on Plasmodium falciparum was predicted by transcriptome analysis. Apoptosis of P. falciparum was detected by Giemsa, Hoechst 33258, and TUNEL staining assay. The reactive oxygen species (ROS) level, oxygen consumption, and mitochondrial membrane potential of P. falciparum were assessed by DCFH-DA, R01, and JC-1 fluorescent dye, respectively. The effect of dobinin K on the mitochondrial electron transport chain (ETC) was investigated by enzyme activity analysis and the binding abilities of dobinin K with different enzymes were learned by molecular docking. Dobinin K inhibited the growth of P. falciparum in a concentration-, time-dependent, and stage-specific manner. The predicted mechanism of dobinin K was related to the redox system of P. falciparum. Dobinin K increased intracellular ROS levels of P. falciparum and induced their apoptosis. After dobinin K treatment, P. falciparum mitochondria lost their function, which was presented as decreased oxygen consumption and depolarization of the membrane potential. Among five dehydrogenases in P. falciparum ETC, dobinin K displayed the best inhibitory power on NDH2 activity. Our findings indicate that the antiplasmodial effect of dobinin K in vitro is mediated by the enhancement of the ROS level in P. falciparum and the disruption of its mitochondrial function. [ABSTRACT FROM AUTHOR]

With the outbreak and ongoing spread of the COVID-19 pandemic, a wave of post-COVID-19 zeitgeist has emerged worldwide. From the perspective of fashion trends, an increasing number of consumers are demanding higher standards of health, environmental friendliness, and sustainability. Over the past 10 years, the integration of technology in clothing has facilitated continuous updates in both functionality and aesthetics. This article aims to explore the relationship between clothing technology and sustainable fashion in the post-COVID-19 era, seeking to enhance the development and innovation of sustainable fashion through the empowerment of clothing technology. This study conducts extensive research on the literature and online case studies, categorizing empowered sustainable fashion technology design cases into six major categories and four directional themes. It introduces an innovative sustainable fashion design assessment model, PCBS (Product, Customer, Business, Society). Subsequently, the knowledge framework is applied in design practice alongside consumer research to validate the system's usability. Furthermore, this research synthesizes and summarizes the methods through which fashion technology can support sustainable fashion in the post-pandemic era. Designers and practitioners can reference these insights for more advanced sustainable design initiatives, thereby promoting a lower-carbon and environmentally friendly system that drives global innovation and development in a sustainable society. [ABSTRACT FROM AUTHOR]

Let be a Grothendieck category, λ an infinite regular cardinal. We investigate the λ -purity of , and the λ -pure acyclic complexes in C(). Using the λ -presentable objects, we verify that the class of λ -pure acyclic complexes is a thick subcategory of homotopy category. Then we construct λ -pure derived category naturally. Through some specific constructions, we get that bounded above λ -pure derived categories coincide with specific homotopy categories. [ABSTRACT FROM AUTHOR]

In an era of massive construction, damaged and aging infrastructure are becoming more common. Defects, such as cracking, spalling, etc., are main types of structural damage that widely occur. Hence, ensuring the safe operation of existing infrastructure through health monitoring has emerged as an important challenge facing engineers. In recent years, intelligent approaches, such as data-driven machines and deep learning crack detection have gradually dominated over traditional methods. Among them, the semantic segmentation using deep learning models is a process of the characterization of accurate locations and portraits of cracks using pixel-level classification. Most available studies rely on single-model knowledge to perform this task. However, it is well-known that the single model might suffer from low variance and low ability to generalize in case of data alteration. By leveraging the ensemble deep learning philosophy, a novel collaborative semantic segmentation of concrete cracks method called Co-CrackSegment is proposed. Firstly, five models, namely the U-net, SegNet, DeepCrack19, DeepLabV3-ResNet50, and DeepLabV3-ResNet101 are trained to serve as core models for the ensemble model Co-CrackSegment. To build the ensemble model Co-CrackSegment, a new iterative approach based on the best evaluation metrics, namely the Dice score, IoU, pixel accuracy, precision, and recall metrics is developed. Results show that the Co-CrackSegment exhibits a prominent performance compared with core models and weighted average ensemble by means of the considered best statistical metrics. [ABSTRACT FROM AUTHOR]

Titanium alloys are mostly used in high temperature and high pressure, which requires its high mechanical properties and corrosion resistance. As a good surface modification technology, arc surface cladding has been applied in various fields. In this study, the gas tungsten arc welding was used to clad titanium alloy and the nitrogen gas with different contents were added in the shielding gas. During the cladding process, the TiN strengthening phase was formed in the cladding layer. The effects of different nitrogen flow rates on the microstructure and properties of the cladding layer were studied. The scanning electron microscope (SEM) and the x-ray diffractometer (XRD) were used to observe microstructure and identify the formed phases. The mechanical properties and corrosion properties were studied by Vickers hardness and electrochemical experiments. The results show that after adding nitrogen, the grain size becomes smaller and the hardness increases from 247 to 363 HV. The formation of TiN also improves the pitting corrosion resistance of the cladding layer. The corrosion resistance of the cladding layer was the best when the nitrogen flow rate was 0.4 L/min. Therefore, adding suitable nitrogen gas in the titanium alloy arc cladding process can significantly improve the performance of the cladding layer. [ABSTRACT FROM AUTHOR]

Aim: This cross-sectional study explored the relationships among perceived stress, social support, positive coping, and mental health in frontline nurses caring for patients with COVID-19 in China. Design: A quantitative cross-sectional study. Methods: A convenience sample of 339 eligible frontline nurses was identified from a designated hospital for COVID-19 in Shanghai, China, between May 2022 and August 2022. Data from nurses were collected through an online survey that contained 4 measurement domains: perceived stress, social support, coping strategies, and mental health. Path analysis was used to analyze the data in SPSS 24.0 and AMOS 23.0. Results: The model tested in the path analysis fit the data well. The results demonstrated relationships among perceived stress, social support, positive coping, and mental health among frontline nurses caring for patients with COVID-19. Social support had a positive effect on positive coping strategies and a negative effect on perceived stress and mental health. In addition, path analysis indicated that social support moderated the relationship between perceived stress and mental health in nurses. Conclusions: Nurses experienced work-related mental stress while providing COVID-19-related care. Based on study findings, social support is expected to play a key role in stress management in nurses. Expanding opportunities for social support is an essential step for nurses to improve their mental health and quality of life. [ABSTRACT FROM AUTHOR]

The concrete panel of earth-rock dams in cold regions tends to crack due to the combination effect of non-uniform foundation settlement, ice expansion loads, and freeze-thaw damage. In this work, simulations are designed to investigate the effects of freeze-thaw damage degrees on the fracture behavior caused by the partial detachment and ice expansion loads on concrete panels. Results show that the range of detached panels and freeze-thaw damage degree are the dominant factors that affect the overall load-bearing capacity of the panel and the failure cracking modes, whereas the panel slope is a secondary factor. The failure cracking modes are found to be a combination of type II fracture modes, including compression-shear and tension-shear cracking. Besides, with the increase of detachment area and the degree of freezing-thawing damage, the concrete panels are prone to appear bending tension cracks at the bottom and a more serious smeared crack layer at the top. [ABSTRACT FROM AUTHOR]

The low carrier mobility in conventional two-dimensional materials limits their thermoelectric (TE) applications due to high "density of scatterings". Electrene, a new type of two-dimensional material has spatially interstitial electrons. These loosely bound electrons with a longer carrier–lattice distance undergo a weaker lattice perturbation, resulting in a higher mobility. Here, we systematically study the effect of loosely bound electrons, electron–phonon interaction, and spin orbital interaction on the TE properties of an electrene, HfI2, via first-principles calculations. We found that the p-type Seebeck coefficient is relatively large compared with those of other 2D materials with small effective mass. The larger hole relaxation time of HfI2 results in high p-type electrical conductivity and power factor compared with n-type ones. It is found that the spin-orbital interaction splits the spin-degenerate bands near the Fermi level inducing a decrease of the bandgap and an increase of electrical conductivity. The electron–phonon interaction also affects the phonon transport which decreases the lattice thermal conductivity by 16% under the n-type doping. Overall, our high-fidelity calculations show that the maximum ZT value of HfI2 reaches 1.12 at a temperature of 1200 K under p-type doping. Our work provides a physical picture of the effects of loosely bound electrons and their interaction with phonons and orbitals on thermoelectric properties, providing suggestions for further design of high-performance 2D thermoelectric materials. [ABSTRACT FROM AUTHOR]

The diameter of the optic nerve sheath is an important indicator for assessing the intracranial pressure in critically ill patients. The methods for measuring the optic nerve sheath diameter are generally divided into invasive and non-invasive methods. Compared to the invasive methods, the non-invasive methods are safer and have thus gained popularity. Among the non-invasive methods, using deep learning to process the ultrasound images of the eyes of critically ill patients and promptly output the diameter of the optic nerve sheath offers significant advantages. This paper proposes a CBC-YOLOv5s optic nerve sheath ultrasound image segmentation method that integrates both local and global features. First, it introduces the CBC-Backbone feature extraction network, which consists of dual-layer C3 Swin-Transformer (C3STR) and dual-layer Bottleneck Transformer (BoT3) modules. The C3STR backbone's multi-layer convolution and residual connections focus on the local features of the optic nerve sheath, while the Window Transformer Attention (WTA) mechanism in the C3STR module and the Multi-Head Self-Attention (MHSA) in the BoT3 module enhance the model's understanding of the global features of the optic nerve sheath. The extracted local and global features are fully integrated in the Spatial Pyramid Pooling Fusion (SPPF) module. Additionally, the CBC-Neck feature pyramid is proposed, which includes a single-layer C3STR module and three-layer CReToNeXt (CRTN) module. During upsampling feature fusion, the C3STR module is used to enhance the local and global awareness of the fused features. During downsampling feature fusion, the CRTN module's multi-level residual design helps the network to better capture the global features of the optic nerve sheath within the fused features. The introduction of these modules achieves the thorough integration of the local and global features, enabling the model to efficiently and accurately identify the optic nerve sheath boundaries, even when the ocular ultrasound images are blurry or the boundaries are unclear. The Z2HOSPITAL-5000 dataset collected from Zhejiang University Second Hospital was used for the experiments. Compared to the widely used YOLOv5s and U-Net algorithms, the proposed method shows improved performance on the blurry test set. Specifically, the proposed method achieves precision, recall, and Intersection over Union (IoU) values that are 4.1%, 2.1%, and 4.5% higher than those of YOLOv5s. When compared to U-Net, the precision, recall, and IoU are improved by 9.2%, 21%, and 19.7%, respectively. [ABSTRACT FROM AUTHOR]

Currently, the predominant method for indirectly obtaining cattle weight data involves establishing the correlation between cattle liveweight and measurable parameters, and subsequently calculating the liveweight of cattle using specific formulas. However, the factors considered in these methods are not comprehensive, which can easily lead to biased weight estimates. Additionally, deep learning-based cattle weight estimation methods typically rely on predicting weight from limited measurable parameters or images, limiting the potential for improved performance. In this study, we propose a novel cattle liveweight estimation algorithm based on composite image/height/length data and spatial and channel attention convolution network (SCA-ConvNet). By combining measurable parameters and images on the channel dimension, our algorithm is able to provide a more comprehensive set of learnable information. Furthermore, the incorporation of channel attention and spatial attention branches in the SCA-ConvNet enhances the network's ability to extract valuable information from the composite data. Through multi-task prediction and loss calculation, our algorithm is able to fully leverage the diverse information available in the channels during training. The experimental results demonstrate that our proposed algorithm outperforms widely used methods including multiple linear regression, Xception, and ConvNeXt in terms of mean-absolute-error, root-mean-square-error, and mean-absolute-percentage-error for cattle liveweight estimation. [ABSTRACT FROM AUTHOR]

To address the problems that a single feature in radio frequency fingerprint recognition could not fully represent the integrity of the signal and that the differences between features of different classes were small, which limited the recognition accuracy, a DA-ResNeXt50 (ResNeXt50 with dense connection and ACBlock) method for radio frequency fingerprint identification based on time-frequency and bi-spectral feature fusion was proposed. Firstly, short-time Fourier transform (STFT) and bi-spectrum transform were performed separately on the signals collected from different devices, the resulting images were bi-narized and then concatenated. By taking advantage of the advantages of both transformations in the time-frequency domain and high-order statistical characteristics respectively, the radio frequency fingerprint features of different devices can be extracted and characterized more comprehensively. Then, the DA-ResNeXt50 network model was proposed. Borrowing from the idea of dense connection, each layer of the four-layer residual unit was directly connected to all previous layers, promoting feature reuse and transmission, which enabled it to better capture subtle differences between classes. Finally, the asymmetric convolution block (ACBlock) was used to replace the 3x3 convolution in the last residual unit of the model. This effectively increased the receptive field of the network and enhanced the skeleton part of the convolutional kernel, thereby improving the performance of radio frequency fingerprint recognition. The experimental results show that compared with that of using a single feature extraction method, the proposed feature fusion approach significantly improves performance. Compared with various classical models, the improved model has higher recognition accuracy. [ABSTRACT FROM AUTHOR]

Ice compressive strength is a key property for investigating the interaction between ice and structures. In this research, a digital image correlation (DIC) technique is developed to measure the complete deformation range of ice samples in uniaxial compression tests that were conducted at different temperatures and loading rates. This method overcomes the limitations of traditional deformation measurement techniques, such as low accuracy and single-point measurements. The ice specimens are generated with initial fibrous pores instead of sphere pores for simulation. This innovative method enables the shear and splitting failure modes to be captured, which are consistent with the test results in this research. The experiments and numerical simulations reveal that the compressive strength increases when the temperature decreases and the loading rate increases. In contrast, the maximum strain decreases with lower temperatures and higher loading rates. This research introduces a novel numerical simulation procedure to study compressive ice deformation and offers experimental approaches for real-time and noncontact measurement of ice deformation at low loading rates. Practical Applications: In this research, several experiments are conducted at three different temperatures (−25°C, −30°C, and −35°C) and loading rates (1, 3, and 5 mm/min). The experimental observations reveal that varying failure modes depend on the strain rate. In addition, a correlation between the compressive strength, temperature, and strain rate is confirmed. In addition, this research investigates the application of digital image technology (DIC) for the real-time and noncontact measurement of ice deformation. The use of noncontact strain measurement technology overcomes the limitations of traditional deformation measurement methods. In addition, noncontact measurements could improve the precision and dependability of ice deformation monitoring and provide more accurate observations and a better understanding of ice behavior. In addition, it could be used in future applications in this field, which opens up new research possibilities concerning ice deformation. This new technique offers a valuable contribution to advancing ice deformation measurement research. [ABSTRACT FROM AUTHOR]

Background: An increasing number of studies have demonstrated the association of circular RNAs (circRNAs) with the pathological processes of various diseases and their involvement in the onset and progression of multiple cancers. Nevertheless, the functional roles and underlying mechanisms of circRNAs in the autophagy regulation of gastric cancer (GC) have not been fully elucidated. Methods: We used transmission electron microscopy and the mRFP-GFP-LC3 dual fluorescent autophagy indicator to investigate autophagy regulation. The cell counting kit-8 assay, colony formation assay, 5-ethynyl-2′-deoxyuridine incorporation assay, Transwell assay, and Western blot assay were conducted to confirm circPTPN22's influence on GC progression. Dual luciferase reporter assays validated the binding between circPTPN22 and miR-6788-5p, as well as miR-6788-5p and p21-activated kinase-1 (PAK1). Functional rescue experiments assessed whether circPTPN22 modulates PAK1 expression by competitively binding miR-6788-5p, affecting autophagy and other biological processes in GC cells. We investigated the impact of circPTPN22 on in vivo GC tumors using a nude mouse xenograft model. Bioinformatics tools predicted upstream regulatory transcription factors and binding proteins of circPTPN22, while chromatin immunoprecipitation and ribonucleoprotein immunoprecipitation assays confirmed the binding status. Results: Upregulation of circPTPN22 in GC has been shown to inhibit autophagy and promote cell proliferation, migration, and invasion. Mechanistically, circPTPN22 directly binds to miR-6788-5p, subsequently regulating the expression of PAK1, which activates protein kinase B (Akt) and extracellular signal-regulated kinase (Erk) phosphorylation. This modulation ultimately affects autophagy levels in GC cells. Additionally, runt-related transcription factor 1 (RUNX1) negatively regulates circPTPN22 expression, while RNA-binding proteins such as FUS (fused in sarcoma) and ELAVL1 (recombinant ELAV-like protein 1) positively regulate its expression. Inhibition of the autophagy pathway can increase FUS expression, further upregulating circPTPN22 in GC cells, thereby exacerbating the progression of GC. Conclusion: Under the regulation of the transcription factor RUNX1 and RNA-binding proteins FUS and ELAVL1, circPTPN22 activates the phosphorylation of Akt and Erk through the miR-6788-5p/PAK1 axis, thereby modulating autophagy in GC cells. Inhibition of autophagy increases FUS, which in turn upregulates circPTPN22, forming a positive feedback loop that ultimately accelerates the progression of GC. [ABSTRACT FROM AUTHOR]

Demand forecasting is essential for streamlining supply chain operations in the digital economy and exceeding customer expectations. On the other hand, traditional forecasting techniques cannot frequently present real-time data and respond to dynamic changes in the supply chain network, leading to less-than-ideal decision-making and higher costs. This research aims to create a technique for optimizing the supply chain network based on blockchain-distributed technology (SCN-BT) to overcome these drawbacks and fully utilize the potential of the digital economy. The suggested framework uses the hybridized LSTM network and Grey Wolf Optimization (GWO) algorithm to examine demand forecasting in the supply chain network for inventory planning. The SCN-BT framework develops a safe and productive, enabling precise and flexible demand by combining blockchain with optimization techniques. A thorough case study utilized information collected from an enterprise supply chain that operates in the digital economy to show the efficiency of the suggested framework. Compared to conventional approaches, the results show considerable gains in demand forecasting precision, responsiveness of the supply chain, and cost-effectiveness. In the context of the digital economy, demand sensing and prediction enable firms to react to changes swiftly, shorten turnaround times, optimize inventory levels, and improve overall supply chain performance. The results highlight how blockchain technology has the potential to enhance collaboration, trust, and transparency inside intricate supply chain networks working in the digital economy. The experimental results show the proposed to achieve prediction rate of demand prediction rate of 128.93, demand forecasting accuracy ratio of 92.18%, optimum efficiency of 94.25%, RMSE rate of 1841.25, MAE rate of 260.74, and sMAPE rate of 0.1002 compared to other methods. [ABSTRACT FROM AUTHOR]

Transient receptor potential (TRP) melastatin member 8 (TRPM8) is a non-selective cation channel that can be activated by low temperatures (8–26 °C), cooling agents (including menthol analogs such as menthol, icilin, and WS-12), voltage, and extracellular osmotic pressure changes. TRPM8 expression has been identified in the digestive system by several research teams, demonstrating its significant involvement in tissue function and pathologies of the digestive system. Specifically, studies have implicated TRPM8 in various physiological and pathological processes of the esophagus, stomach, colorectal region, liver, and pancreas. This paper aims to comprehensively outline the distinct role of TRPM8 in different organs of the digestive system, offering insights for future mechanistic investigations of TRPM8. Additionally, it presents potential therapeutic targets for treating conditions such as digestive tract inflammation, tumors, sensory and functional disorders, and other related diseases. Furthermore, this paper addresses the limitations of existing studies and highlights the research prospects associated with TRPM8. [ABSTRACT FROM AUTHOR]

Direct sequence spread spectrum (DSSS) communications are highly significant in military and civilian wireless communications because of its ability to resist narrowband interference, multipath interference and high security. However, under low signal-to-noise ratio (SNR), the detection of DSSS signals becomes very difficult under non-cooperative communication. Therefore, in order to improve the detection performance of DSSS signals in fading channels with low SNR, a DSSS signal detection method based on an eigenvalues local binary patterns residual network (EL-ResNet) is proposed with an unknown spread spectrum sequence. Firstly, according to the characteristics of DSSS signals, the eigenvalues of the sample covariance matrix of the DSSS signals are used to construct the signal eigenvalue histograms. This method uses the strong contrast of eigenvalue energy and gradient change to enlarge the discrimination of images with or without DSSS signals. Then, EL-ResNet is built to distinguish between eigenvalue histograms with or without DSSS signals. The local binary patterns (LBPs) are introduced to constrain the loss function of the network, increasing the differentiation of the two types of eigenvalue histograms, and improving the DSSS signal detection performance of the network. Finally, the experimental results show that the performance of the DSSS signal detection method based on EL-ResNet is larger than fast Fourier transform (FFT), FFT-deep neural network (FFT-DNN), covariance matrix-convolutional neural network (CM-CNN) detection methods. [ABSTRACT FROM AUTHOR]

Background: Amide proton transfer‐weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18F‐FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non‐small cell lung cancer (NSCLC) still needs to be further explored. Purpose: To determine whether pretreatment APTWI, mono‐, bi‐, and stretched‐exponential model IVIM, and 18F‐FDG PET‐derived parameters of the primary lesion may be associated with progression‐free survival (PFS) in NSCLC. Study Type: Prospective. Population: Seventy‐seven patients (mean age, 62 years, range, 20–81 years) with 37 men and 40 women were included. Field Strength/Sequence: 3.0 T 18F‐FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin‐echo sequences with magnetization transfer pulses for APTWI. Assessment: Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow‐up was 18 months, range, 4–27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand, D, D*, f, DDC, and α), and 18F‐FDG PET (SUVmax, MTV, and TLG) parameters were recorded. Statistical Tests: Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log‐rank test. A P value <0.05 was considered statistically significant. Results: Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C‐index of 0.895 (95% CI: 0.839–0.951), which was significantly superior to each of the above predictors alone (C‐index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log‐rank test results showed a significant difference in PFS between the high‐ and low‐risk groups. Data Conclusion: APTWI and multiple models IVIM based 18F‐FDG PET/MRI can be used for PFS assessment in NSCLC. Evidence Level: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Objective: To investigate the risk factors for delayed postoperative bleeding after endoscopic submucosal dissection (ESD) in patients with gastric precancerous lesions and to construct a risk prediction model. Methods: This retrospective analysis included clinical data from patients with gastric precancerous lesions who underwent ESD at Wuhan University People's Hospital between November 2016 and June 2022. An XGBoost model was built to predict delayed bleeding after ESD using risk factors identified by univariable and multivariate logistic regression analysis. The model was evaluated using receiver operating characteristic curves (ROC), and SHapely Additive exPlanations (SHAP) analysis was used to interpret the model. Results: Seven factors were statistically associated with delayed postoperative bleeding in gastric precancerous lesions after ESD: age, low-grade intraepithelial neoplasia, hypertension, lesion size ≥ 40 mm, operative time ≥ 120 min, female, and nonuse of hemoclips. A risk prediction model was established. In the training cohort, the model achieved an AUC of 0.97 (0.96–0.98), a sensitivity of 0.90, a specificity of 0.94, and an F1 score of 0.91. In the validation cohort, the AUC was 0.94(0.90–0.98), with a sensitivity of 0.85, a specificity of 0.89, and an F1 score of 0.85. In the test cohort, the AUC was 0.94 (0.89–0.99), the sensitivity was 0.80, the specificity was 0.92, and the F1 score was 0.84, indicating strong predictive capability. Conclusion: In this study, an XGBoost prediction model for assessing the risk of delayed postoperative bleeding after ESD in patients with gastric precancerous lesions was developed and validated. This model can be applied in clinical practice to effectively predict the risk of post-ESD bleeding for individual patients. [ABSTRACT FROM AUTHOR]

RNA splicing dysregulation and the involvement of specific splicing factors are emerging as common factors in both obesity and metabolic disorders. The study provides compelling evidence that the absence of the splicing factor SRSF1 in mature adipocytes results in whitening of brown adipocyte tissue (BAT) and impaired thermogenesis, along with the inhibition of white adipose tissue browning in mice. Combining single‐nucleus RNA sequencing with transmission electron microscopy, it is observed that the transformation of BAT cell types is associated with dysfunctional mitochondria, and SRSF1 deficiency leads to degenerated and fragmented mitochondria within BAT. The results demonstrate that SRSF1 effectively binds to constitutive exon 6 of Ndufs3 pre‐mRNA and promotes its inclusion. Conversely, the deficiency of SRSF1 results in impaired splicing of Ndufs3, leading to reduced levels of functional proteins that are essential for mitochondrial complex I assembly and activity. Consequently, this deficiency disrupts mitochondrial integrity, ultimately compromising the thermogenic capacity of BAT. These findings illuminate a novel role for SRSF1 in influencing mitochondrial function and BAT thermogenesis through its regulation of Ndufs3 splicing within BAT. [ABSTRACT FROM AUTHOR]

Adipose progenitor cells (APCs) are heterogeneous stromal cells and help to maintain metabolic homeostasis. However, the influence of obesity on human APC heterogeneity and the role of APC subpopulations on regulating glucose homeostasis remain unknown. Here, we find that APCs in human visceral adipose tissue contain four subsets. The composition and functionality of APCs are altered in patients with type 2 diabetes (T2D). CD9+CD55low APCs are the subset which is significantly increased in T2D patients. Transplantation of these cells from T2D patients into adipose tissue causes glycemic disturbance. Mechanistically, CD9+CD55low APCs promote T2D development through producing bioactive proteins to form a detrimental niche, leading to upregulation of adipocyte lipolysis. Depletion of pathogenic APCs by inducing intracellular diphtheria toxin A expression or using a hunter-killer peptide improves obesity-related glycemic disturbance. Collectively, our data provide deeper insights in human APC functionality and highlights APCs as a potential therapeutic target to combat T2D. All mice utilized in this study are male. Adipose tissue harbors functionally distinct progenitor cell subsets. Using scRNAseq and functional assays, we disclose a pathogenic adipose progenitor subset, which impairs glycose homeostasis through the construction of a detrimental niche. [ABSTRACT FROM AUTHOR]

Objective • To investigate the composition of immune cells in tumor microenvironment of colorectal cancer (CRC), and examine the proportion, phenotype and effector function of natural killer (NK) cells in CRC. Methods • Fresh tumor tissues, paired normal tissues adjacent to tumor, and peripheral blood samples in the same cohort were collected from CRC patients. Tissues were digested and prepared into single cell suspension. The major immune cell lineages were detected by flow cytometry. t-Distributed stochastic neighbor embedding (t-SNE) and statistical analysis were used to analyze the composition of immune cells in tumor microenvironment of CRC. To analyze the phenotype of NK cells, the expression levels of activation markers, including CD 16, CD27, CD69, human leukocyte antigen-DR (HLA-DR), and T cell immunoglobulin domain and mucin domain-3 (TIM-3), were detected by flow cytometry. NK cell subsets: CD38low NK cells and CD38high NK cells were also examined by flow cytometry. To assess the effector function of NK cells, they were stimulated with cell stimulation cocktail and the expression levels of interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and granulocyte-macrophage colony-stimulating factor (GM-CSF) were measured by flow cytometry. Results • Twenty-five pairs of fresh tumor tissues and normal tissues adjacent to tumor, and 15 peripheral blood samples in the same cohort were collected from CRC patients. The tumor microenvironment of CRC included diverse immune cell types, including T cells, B cells, NK cells and myeloid cells. The proportions of T cells (P=0.000) and myeloid cells (P=(J.026) in tumor tissues were significantly higher than those in normal tissues. By contrast, the proportion of NK cells (P=0.007) in tumor was significantly reduced. The proportion of B cells was comparable between tumor and normal tissues. Compared to normal tissues, NK cells in tumor tissues expressed significantly lower CD27 (P=0.000) and CD69 (P=0.001), while the expression levels of CD16 (P=0.008), HLA-DR (P=0.000) and TIM-3 (P=0.024) were significantly elevated. The results indicated that NK cells in CRC tumor exhibited a phenotype of late activation and exhaustion. According to the expression level of CD38, NK cells could be divided into two subsets, CD38high NK cells and CD38low NK cells. The proportion of CD38high NK cells (P=0.003) in tumor tissues was significantly lower than that in normal tissues, while the proportion of CD38low NK cells was unaffected. Compared to CD38lüwNK cells, CD38highNK cells expressed higher CD27, meanwhile significantly less CD16, NKp46, CD57, CD94, HLA-DR and CD158a (P=0,000). These results suggested that CD38high NK cells were at early differentiation state. The secretion of cytokines IFN-y (P= 0.032), TNF-α (P=0.042), and GM-CSF (P=0.019) by tumor-infiltrated NK cells was significantly decreased compared to that in normal tissues. The results showed that the function of tumor-infiltrated NK cells was impaired. Conclusion • Together, these data suggest that NK cell compartment is disrupted in tumor tissues of CRC, leading to the impaired anti-tumor immunity mediated by NK cells. [ABSTRACT FROM AUTHOR]

The study of microplastics (MPs) in soils is impeded by similarities between plastic and non-plastic particles and the misidentification of MP by current analytical methods such as visual microscopic examination. Soil MPs pose serious ecological and public health risks because of their abundance, persistence, and ubiquity. Thus, reliable identification methods are badly needed for scientific study. One possible solution is UV–Vis–NIR spectroscopy, which has the ability to rapidly identify and quantify concentrations of soil microplastics. In this study, a full-range, field portable spectrometer (350–2500 nm) with ultra-high spectral resolution (1.5 nm, 3.0 nm, and 3.8 nm) identified three types of common plastics: low-density polyethylene (LDPE), polyvinyl chloride (PVC), and polypropylene (PP). Three sets of artificially MP-treated vermiculite soil samples were prepared for model prediction testing and validation: 150 samples for model calibration and 50 samples for model validation. A partial least square regression model using the spectral signatures for quantification of soil and MP mixtures was built with all three plastic polymers. Prediction R2 values of all three polymers showed promising results: polypropylene R2 = 0.943, polyvinyl chloride R2 = 0.983, and polyethylene R2 = 0.957. Our study supports previous work showing that combining ultra-high-resolution UV–Vis–NIR spectrometry with quantitative modeling can improve the accuracy and speed of MP identification and quantification in soil. [ABSTRACT FROM AUTHOR]

Intercropping is a vital cropping system that can create a conducive growth environment for crops and enhance land productivity. Tiger nuts (Cyperus esculentus L.) have high oil content and are adaptable to various soil types, making them a promising new oil crop with significant development potential. This study evaluated the plant height, leaf area, tiller numbers, biomass, land equivalent ratio (LER), and root morphological characteristics of tiger nuts. The agronomic traits and root distribution of tiger nuts and other crops were further investigated to achieve the goal of high yield for tiger nuts. Seven intercropping systems were implemented in the experiment: maize–tiger nut intercropping (MT), soybean–tiger nut intercropping (ST), cotton–tiger nut intercropping (CT), monoculture tiger nut (T), monoculture maize (M), monoculture soybean (S), and monoculture cotton (C). The results indicated that under different planting systems, the agronomic traits of tiger nuts in MT and ST modes were superior, with plant height and tiller numbers increasing by 7.6% to 11.6%. However, the plant height and Soil Plant Analysis Development (SPAD) values in CT mode were slightly lower than in T mode. Additionally, intercropping reduced the leaf area by 6.2% to 37.9%. Root development was more pronounced in intercropping modes, with the ST mode showing the most significant improvement, increasing the 0–20 cm root length density (RLD) by 12.2% to 45.7%. Therefore, each of the three intercropping modes demonstrated distinct advantages. The LER of the intercropping systems ranged from 1.10 to 1.24, enhancing land utilization, with tiger nuts being the dominant species. Compared to monoculture, the ST mode exhibited the best overall effect. Understanding the impact of different planting systems on tiger nuts provides valuable insights for developing tiger nut cultivation in Xinjiang. [ABSTRACT FROM AUTHOR]

Low-cost, small-sized, and easy integrated high-performance photodetectors for photonics are still the bottleneck of photonic integrated circuits applications and have attracted increasing attention. The tunable narrow bandgap of two-dimensional (2D) layered molybdenum ditelluride (MoTe2) from ∼0.83 to ∼1.1 eV makes it one of the ideal candidates for near-infrared (NIR) photodetectors. Herein, we demonstrate an excellent waveguide-integrated NIR photodetector by transferring mechanically exfoliated 2D MoTe2 onto a silicon nitride (Si3N4) waveguide. The photoconductive photodetector exhibits excellent responsivity (R), detectivity (D *), and external quantum efficiency at 1550 nm and 50 mV, which are 41.9 A W−1, 16.2 × 1010 Jones, and 3360%, respectively. These optoelectronic performances are 10.2 times higher than those of the free-space device, revealing that the photoresponse of photodetectors can be enhanced due to the presence of waveguide. Moreover, the photodetector also exhibits competitive performances over a broad wavelength range from 800 to 1000 nm with a high R of 15.4 A W−1 and a large D * of 59.6 × 109 Jones. Overall, these results provide an alternative and prospective strategy for high-performance on-chip broadband NIR photodetectors. [ABSTRACT FROM AUTHOR]

Semiconductor single-crystal thin films (SCTFs) with nanoscale thickness play an important role in high-performance electronics and optoelectronic devices, owing to the excellent electrical, optical, thermal, and mechanical performance. Although enormous progress has been made in preparing two-dimensional (2D) material SCTFs, it is still challenging to grow SCTFs based on 3D materials with high efficiency. Herein, we report the efficient growth of centimeter-scale CdS SCTFs with the thickness of ∼95.41 nm on the mica substrates using a chemical vapor deposition method. The controlled experiments and the structure characterizations indicate that the SCTFs are formed by the seamless coalescence of the hexagonal CdS nanosheet domains initially grown in the same orientation on the substrate, with the epitaxial relationship of (100)CdS//(110)mica and (110)CdS//(200)mica. Importantly, the CdS SCTF-based photodetectors (PDs) demonstrate a photoswitching (Ion/Ioff) ratio up to 105 and a fast photoresponse speed (trise ≈ 0.5 ms, tdecay ≈ 1 ms). Furthermore, the PDs exhibit excellent stability to at least 2 months of storage in an ambient atmosphere and 1000-time bending. This work paves the way to synthesizing the 3D semiconductor SCTFs on a large scale and promotes their practical application in multifunctional photoelectric devices. [ABSTRACT FROM AUTHOR]

Background: Hemifacial spasm (HFS) is most effectively treated with microvascular decompression (MVD). However, there are certain challenges in performing MVD for HFS when the vertebral artery (VA) is involved in compressing the facial nerve (VA-involved). This study aimed to introduce a "bridge-layered" decompression technique for treating patients with VA-involved HFS and to evaluate its efficacy and safety to treat patients with HFS. Methods: A single-center retrospective analysis was conducted on the clinical data of 62 patients with VA-involved HFS. The tortuous trunk of VA was lifted by a multi-point "bridge" decompression technique to avoid excessive traction of the cerebellum and reduce the risk of damage to the facial-acoustic nerve complex. To fully decompress all the responsible vessels, the branch vessels of VA were then isolated using the "layered" decompression technique. Results: Among the 62 patients, 59 patients were cured immediately after the surgery, two patients were delayed cured after two months, and one had occasional facial muscle twitching after the surgery. Patients were followed up for an average of 19.5 months. The long-term follow-up results showed that all patients had no recurrence of HFS during the follow-up period, and no patients developed hearing loss, facial paralysis, or other permanent neurological damage complications. Only two patients developed tinnitus after the surgery. Conclusion: The "bridge-layered" decompression technique could effectively treat VA-involved HFS with satisfactory safety and a low risk of hearing loss. The technique could be used as a reference for decompression surgery for VA-involved HFS. [ABSTRACT FROM AUTHOR]

The impact of interfacial charge on catalytic performance of supported-metal-cluster (SMC) heterostructures remains unclear, hindering efforts to develop high-performance SMC catalysts. Herein we systematically investigated interfacial charge effects of SMCs using a model system of graphene-supported gold-nanoclusters (AuNCs/rGO) for azo hydrogenation. Three types of SMCs with different interfacial charges were synthesized by anchoring electropositive 2-aminoethanethiol (CSH), amphoteric cysteine (Cys), and electronegative 3-mercaptopropionic-acid (MPA) onto AuNCs/rGO, respectively. All three SMCs exhibited high and selective catalytic activity to azo-hydrogenation in four representative azo dyes. The catalytic activity of Cys@AuNCs/rGO was lower than that of CSH@AuNCs/rGO but higher than that of MPA@AuNCs/rGO. However, the cyclic stability of Cys@AuNCs/rGO was inferior to that of both CSH@AuNCs/rGO and MPA@AuNCs/rGO. Further mechanistic studies revealed that amino ligands modified CSH@AuNCs and Cys@AuNCs agglomerated into large-size gold nanoparticles on rGO surface during catalytic reaction under NaBH4 action, leading to reduced efficiency and cyclic stability. Conversely, non-amino ligand modified MPA@AuNCs only partially detached from rGO surface without agglomeration, resulting in better cyclic stability. Protection of amino groups in ligands such as modifying -NH3+ group in Cys into imine to form N-isobutyryl-L-cysteine (NIBC) substantially improved the cyclic stability while maintaining the high activity in the NIBC@AuNCs/rGO catalyst system. Our work provides an approach for developing a highly-active and stable SMC heterostructure catalyst via manipulating interfacial charges in SMC. [ABSTRACT FROM AUTHOR]

Reversible upconversion luminescence (RUCL) through defect engineering holds great promise for various applications, including photoswitches, information recording, and storage devices. However, the reversible photoluminescence in inorganic crystals is rarely reported. Crucially, the underlying mechanism of reversible luminescence remains unclear, which challenges the design of high‐performance reversible luminescence inorganic materials. Herein, an anomalous RUCL in a class of β‐Ba2ScAlO5:Yb3+/RE3+ (RE = Er, Ho, Tm, Tb, Sm, or Eu) phosphors is reported. By alternating annealing environments (air or hydrogen), a robust and repeatable cycle of luminescence and quenching is observed. The first‐principles calculations reveal that porous β‐Ba2ScAlO5:Yb3+/RE3+ can host oxygen interstitials (during annealing in air) with a low formation energy. The interstitial oxygen state, close to the Yb 4f state, leads to luminescence quenching. Removal of oxygen interstitials (during annealing in hydrogen) can restore the luminescence by initiating radiative energy transfer. Experimentally, the existence of interstitial oxygen is confirmed with neutron diffraction technology. It is worth noting that the strong chemical bonds in crystals make adding and removing anion vacancies challenging, unlike the more "free" interstitials. The findings offer new insights into manipulating upconversion luminescence in inorganic crystals by defect engineering and provide motivation for future research in this field. [ABSTRACT FROM AUTHOR]

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Purpose: Donor-derived infection (DDI) has become an important factor affecting the prognosis of lung transplantation patients. The risks versus benefits of using donor organs infected with multidrug-resistant organisms (MDRO), especially carbapenem-resistant organisms (CRO), are frequently debated. Traditional microbial culture and antimicrobial susceptibility testing at present fail to meet the needs of quick CRO determination for donor lungs before acquisition. In this study, we explored a novel screening method by using Xpert® Carba-R assay for CRO in donor lungs in a real-time manner to reduce CRO-associated DDI mortality. Methods: This study was registered on chictr.org.cn (ChiCTR2100053687) on November 2021. In the Xpert Carba-R screening group, donor lungs were screened for CRO infection by the Xpert Carba-R test on bronchoalveolar fluid (BALF) before acquisition. If the result was negative, donor lung acquisition and subsequent lung transplantation were performed. In the thirty-five potential donors, nine (25.71%) with positive Xpert Carba-R results in BALF were declined for lung transplantation. Twenty-six recipients and the matching CRO-negative donor lungs (74.29%) were included in the Xpert Carba-R screening group. In the control group, nineteen recipients underwent lung transplants without Xpert Carba-R screening. The incidence and mortality of CRO-associated DDI were collected and contrasted between the two groups. Results: Multivariate analysis showed that CRO-related death due to DDI within 60 days was significantly lower in the Xpert Carba-R screening group than that in the control group (OR = 0.05, 95% CI 0.003–0.74, p = 0.03). Conclusion: Real-time CRO screening of donor lungs before transplantation at the point of care by the Xpert Carba-R helps clinicians formulate lung transplantation strategies quickly and reduces the risk of subsequent CRO infection improving the prognosis of lung transplantation. [ABSTRACT FROM AUTHOR]