DPP: deep phase prior for parallel imaging with wave encoding.

OBJECTIVE: In MR parallel imaging with virtual channel-expanded Wave encoding, limitations are imposed on the ability to comprehensively and accurately characterize the background phase. These limitations are primarily attributed to the calibration process relying solely on center low-frequency ACS data for calibration. Approach: To tackle the challenge of accurately estimating the background phase in wave encoding, a novel deep neural network model guided by deep phase priors (DPP) is proposed with integrated virtual conjugate coil (VCC) extension. Concretely, within the proposed framework, the background phase is implicitly characterized by employing a carefully designed decoder convolutional neural network, leveraging the inherent characteristics of phase smoothness and compact support in the transformed domain. Furthermore, the proposed model with wave encoding benefits from additional priors, which incorporate transmission sparsity of the latent image and coil sensitivity smoothness. Main results: Ablation experiments were conducted to ascertain the proposed method's capability to implicitly represent CSM and the background phase. Subsequently, the superiority of the proposed method is demonstrated through confidence comparisons with competing methods, employing 4-fold and 5-fold acceleration experiments. In achieving 4-fold and 5-fold acceleration, the optimal quantitative metrics (PSNR/SSIM/NMSE) are 44.1359 dB/0.9863/0.0008 (4-fold) and 41.2074/0.9846/0.0017 (5-fold), respectively. Furthermore, the generalizability of the proposed method is further validated by conducting acceleration experiments with T1, T2, T2*, and various undersampling patterns. In addition, the DPP delivered much better performance than the conventional methods by exploring accelerated phase-sensitive SWI imaging. In SWI accelerated imaging, it also surpasses the optimal competing method in terms of (PSNR/SSIM/NMSE) with 0.096%/0.009%/0.0017%. Significance: The proposed method enables precise characterization of the background phase in the integrated VCC and wave encoding framework, supported via theoretical analysis and empirical findings. Our code is available at: https://github.com/sober235/DPP.

Biochar and Manure Co-Application Increases Rice Yield in Low Productive Acid Soil by Increasing Soil pH, Organic Carbon, and Nutrient Retention and Availability.

In recent years, overuse of chemical fertilization has led to soil acidification and decreased rice yield productivity in southern China. Biochar and manure co-application remediation may have positive effects on rice yield and improve acid paddy soil fertility. This study was conducted to understand the effects of co-application of wood biochar and pig manure on rice yield and acid paddy soil quality (0-40 cm soil layers) in a 5-year field experiment. The experiment consisted of six treatments: no biochar and no fertilizer (CK); biochar only (BC); mineral fertilizer (N); mineral fertilizer combined with biochar (N + BC); manure (25% manure N replacing fertilizer N) combined with mineral fertilizer (MN); and manure combined with mineral fertilizer and biochar (MN + BC). Total nitrogen application for each treatment was the same at 270 kg nitrogen ha-1y-1, and 30 t ha-1 biochar was added to the soil only in the first year. After five years, compared with N treatments, N + BC, MN, and MN + BC treatments increased the rice yield rate to 2.8%, 4.3%, and 6.3%, respectively, by improving soil organic matter, total nitrogen, and available phosphate under a 0-40 cm soil layer. MN + BC had the strongest resistance to soil acidification among all the treatments. The interaction between fertilizers and biochar application was significant (p < 0.05) in rice yield, soil electrical conductivity (10-20 cm), and soil available phosphate (20-40 cm). Principal component analysis indicated that the effect of manure on soil property was stronger than that of biochar in the 0-40 cm soil layer. The overall rice yield and soil fertility decreased in the order of biochar + mineral fertilizer + manure > mineral fertilizer + manure > biochar + mineral fertilizer > mineral fertilizer > biochar > control. These results suggest that biochar and manure co-application is a long-term viable strategy for improving acid soil productivity due to its improvements in soil pH, organic carbon, nutrient retention, and availability.

Progressive thalamic nuclear atrophy in blepharospasm and blepharospasm-oromandibular dystonia.

The thalamus is considered a key region in the neuromechanisms of blepharospasm. However, previous studies considered it as a single, homogeneous structure, disregarding potentially useful information about distinct thalamic nuclei. Herein, we aimed to examine (i) whether grey matter volume differs across thalamic subregions/nuclei in patients with blepharospasm and blepharospasm-oromandibular dystonia; (ii) causal relationships among abnormal thalamic nuclei; and (iii) whether these abnormal features can be used as neuroimaging biomarkers to distinguish patients with blepharospasm from blepharospasm-oromandibular dystonia and those with dystonia from healthy controls. Structural MRI data were collected from 56 patients with blepharospasm, 20 with blepharospasm-oromandibular dystonia and 58 healthy controls. Differences in thalamic nuclei volumes between groups and their relationships to clinical information were analysed in patients with dystonia. Granger causality analysis was employed to explore the causal effects among abnormal thalamic nuclei. Support vector machines were used to test whether these abnormal features could distinguish patients with different forms of dystonia and those with dystonia from healthy controls. Compared with healthy controls, patients with blepharospasm exhibited reduced grey matter volume in the lateral geniculate and pulvinar inferior nuclei, whereas those with blepharospasm-oromandibular dystonia showed decreased grey matter volume in the ventral anterior and ventral lateral anterior nuclei. Atrophy in the pulvinar inferior nucleus in blepharospasm patients and in the ventral lateral anterior nucleus in blepharospasm-oromandibular dystonia patients was negatively correlated with clinical severity and disease duration, respectively. The proposed machine learning scheme yielded a high accuracy in distinguishing blepharospasm patients from healthy controls (accuracy: 0.89), blepharospasm-oromandibular dystonia patients from healthy controls (accuracy: 0.82) and blepharospasm from blepharospasm-oromandibular dystonia patients (accuracy: 0.94). Most importantly, Granger causality analysis revealed that a progressive driving pathway from pulvinar inferior nuclear atrophy extends to lateral geniculate nuclear atrophy and then to ventral lateral anterior nuclear atrophy with increasing clinical severity in patients with blepharospasm. These findings suggest that the pulvinar inferior nucleus in the thalamus is the focal origin of blepharospasm, extending to pulvinar inferior nuclear atrophy and subsequently extending to the ventral lateral anterior nucleus causing involuntary lower facial and masticatory movements known as blepharospasm-oromandibular dystonia. Moreover, our results also provide potential targets for neuromodulation especially deep brain stimulation in patients with blepharospasm and blepharospasm-oromandibular dystonia.

Multi-omics and chemical profiling approaches to understand the material foundation and pharmacological mechanism of Sophorae Tonkinensis Radix et Rhizome-induced liver injury in mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Sophorae tonkinensis Radix et Rhizoma (STR) is an extensively applied traditional Chinese medicine (TCM) in southwest China. However, its clinical application is relatively limited due to its hepatotoxicity effects. AIM OF THE STUDY: To understand the material foundation and liver injury mechanism of STR. MATERIALS AND METHODS: Chemical compositions in STR and its prototypes in mice were profiled by ultra-performance liquid chromatography coupled quadrupole-time of flight mass spectrometry (UPLC-Q/TOF MS). STR-induced liver injury (SILI) was comprehensively evaluated by STR-treated mice mode. The histopathologic and biochemical analyses were performed to evaluate liver injury levels. Subsequently, network pharmacology and multi-omics were used to analyze the potential mechanism of SILI in vivo. And the target genes were further verified by western blot. RESULTS: A total of 152 compounds were identified or tentatively characterized in STR, including 29 alkaloids, 21 organic acids, 75 flavonoids, 1 quinone, and 26 other types. Among them, 19 components were presented in STR-medicated serum. The histopathologic and biochemical analysis revealed that hepatic injury occurred after 4 weeks of intragastric administration of STR. Network pharmacology analysis revealed that IL6, TNF, STAT3, etc. were the main core targets, and the bile secretion might play a key role in SILI. The metabolic pathways such as taurine and hypotaurine metabolism, purine metabolism, and vitamin B6 metabolism were identified in the STR exposed groups. Among them, taurine, hypotaurine, hypoxanthine, pyridoxal, and 4-pyridoxate were selected based on their high impact value and potential biological function in the process of liver injury post STR treatment. CONCLUSIONS: The mechanism and material foundation of SILI were revealed and profiled by a multi-omics strategy combined with network pharmacology and chemical profiling. Meanwhile, new insights were taken into understand the pathological mechanism of SILI.

Computational and Experimental Approaches Exploring the Role of Hesperetin in Improving Autophagy in Rat Diabetic Retinopathy.

Diabetic retinopathy (DR) is a debilitating diabetic disorder of the retinal microvasculature and the main cause of avoidable blindness in old people. Hesperetin is a plant flavanone largely abundant in citrus species with neuroprotective properties in animal models. This study aimed to explore the neuroprotective and autophagy-enhancing effect of hesperetin in rats with DR. Twenty-four male rats were utilized and allocated to groups: (i) the vehicle group, (ii) DR group and (iii-iv) the DR + hesperetin (50 and 100 mg/kg) groups. Treatment with hesperetin continued for 6 weeks. After the rats were euthanized, their eyes were dissected to detect the biochemical and histological changes in the retinas. Quantification of autophagy markers, beclin 1/LC3/p62, and inflammation markers was performed. Histopathologic changes were investigated after staining with hematoxylin and eosin and periodic acid-Schiff (PAS). Results demonstrated that hesperetin decreased the PAS staining in diabetic rats and attenuated histopathological changes and restored retinal organization and thickness of layers in hematoxylin and eosin staining. Moreover, hesperetin reduced the level of mRNA expression for TNF-α (4.9-fold), IL-1ß (4.15-fold), IL-6 (4.6-fold) and NFκB (5.2-fold), as well as the protein level. This was accompanied by induction of autophagy proteins, beclin 1 and LC3-II. Our results afford evidence that hesperetin is effective in alleviating the pathology of DR via suppressing the inflammatory burden and induction of autophagy. After extensive clinical examinations, hesperetin may prove to be a useful option for treatment of DR.

Population Structure and Selection Signal Analysis of Nanyang Cattle Based on Whole-Genome Sequencing Data.

With a rich breeding history, Nanyang cattle (NY cattle) have undergone extensive natural and artificial selection, resulting in distinctive traits such as high fertility, excellent meat quality, and disease resistance. This makes them an ideal model for studying the mechanisms of environmental adaptability. To assess the population structure and genetic diversity of NY cattle, we performed whole-genome resequencing on 30 individuals. These data were then compared with published whole-genome resequencing data from 432 cattle globally. The results indicate that the genetic structure of NY cattle is significantly different from European commercial breeds and is more similar to North-Central Chinese breeds. Furthermore, among all breeds, NY cattle exhibit the highest genetic diversity and the lowest population inbreeding levels. A genome-wide selection signal analysis of NY cattle and European commercial breeds using Fst, θπ-ratio, and θπ methods revealed significant selection signals in genes associated with reproductive performance and immunity. Our functional annotation analysis suggests that these genes may be responsible for reproduction (MAP2K2, PGR, and GSE1), immune response (NCOA2, HSF1, and PAX5), and olfaction (TAS1R3). We provide a comprehensive overview of sequence variations in the NY cattle genome, revealing insights into the population structure and genetic diversity of NY cattle. Additionally, we identify candidate genes associated with important economic traits, offering valuable references for future conservation and breeding efforts of NY cattle.

Triterpenoids and triterpenoid saponins from Vitex negundo and their anti-inflammatory activities.

Seven undescribed polyoxygenated ursane-type triterpenoids (vitnegundins A-G), three undescribed triterpenoid saponins (vitnegundins H-J), and 17 known ones were isolated from an EtOH extract of the aerial parts of Vitex negundo L. The structures of the undescribed compounds were established by extensive spectroscopic analysis. The absolute configurations of vitnegundins A, B, and E were determined by single-crystal X-ray diffraction data. Vitnegundins B-D are pentacyclic triterpenoids possessing rare cis-fused C/D rings and vitnegundins C-H represent undescribed ursane-type triterpenoids with 12,19-epoxy moiety. In the biological activity assay, vitnegundin A, vitnegundin E, and swinhoeic acid displayed inhibitory effects against LPS-induced NO release in BV-2 microglial cells, with IC50 values of 11.8, 44.2, and 19.6 µM, respectively.

High-performance multi-junction cascade 1.3†µm quantum dot vertical cavity surface-emitting laser.

A high-performance 5-junction cascade quantum dot (QD) vertical cavity surface-emitting laser (VCSEL) with 1.3 µm wavelength was designed. The characteristics of the QD as active regions and tunnel junctions are combined to effectively increase output power. The photoelectric characteristics of single-junction, 3-junction cascade, and 5-junction cascade QD VCSELs are compared at continuous-wave conditions. Results indicate that the threshold current gradually decreases, and the output power and slope efficiency exponential increase with the increase of the number of active regions. The peak power conversion efficiency of 58.4% is achieved for the 5-junction cascade individual QD VCSEL emitter with 10 µm oxide aperture. The maximum slope efficiency of the device is 6.27 W/A, which is approximately six times than that of the single-junction QD VCSEL. The output power of the 5-junction cascade QD VCSEL reaches 188.13 mW at injection current 30 mA. High-performance multi-junction cascade 1.3-µm QD VCSEL provides data and theoretical support for the preparation of epitaxial materials.

Effects of Potassium-Containing Fertilizers on Sugar and Organic Acid Metabolism in Grape Fruits.

To identify suitable potassium fertilizers for grape (Vitis vinifera L.) production and study their mechanism of action, the effects of four potassium-containing fertilizers (complex fertilizer, potassium nitrate, potassium sulfate, and potassium dihydrogen phosphate) on sugar and organic acid metabolism in grape fruits were investigated. Potassium-containing fertilizers increased the activity of sugar and organic acid metabolism-related enzymes at all stages of grape fruit development. During the later stages of fruit development, potassium-containing fertilizers increased the total soluble solid content and the sugar content of the different sugar fractions and decreased the titratable acid content and organic acid content of the different organic acid fractions. At the ripening stage of grape fruit, compared with the control, complex fertilizer, potassium nitrate, potassium sulfate, and potassium dihydrogen phosphate increased the total soluble solid content by 1.5, 1.2, 3.5, and 3.4 percentage points, decreased the titratable acid content by 0.09, 0.06, 0.18, and 0.17 percentage points, respectively, and also increased the total potassium content in grape fruits to a certain degree. Transcriptome analysis of the differentially expressed genes (DEGs) in the berries showed that applying potassium-containing fertilizers enriched the genes in pathways involved in fruit quality, namely, carbon metabolism, carbon fixation in photosynthetic organisms, glycolysis and gluconeogenesis, and fructose and mannose metabolism. Potassium-containing fertilizers affected the expression levels of genes regulating sugar metabolism and potassium ion uptake and transport. Overall, potassium-containing fertilizers can promote sugar accumulation and reduce acid accumulation in grape fruits, and potassium sulfate and potassium dihydrogen phosphate had the best effects among the fertilizers tested.

Integrating data distribution prior via Langevin dynamics for end-to-end MR reconstruction.

PURPOSE: To develop a novel deep learning-based method inheriting the advantages of data distribution prior and end-to-end training for accelerating MRI. METHODS: Langevin dynamics is used to formulate image reconstruction with data distribution before facilitate image reconstruction. The data distribution prior is learned implicitly through the end-to-end adversarial training to mitigate the hyper-parameter selection and shorten the testing time compared to traditional probabilistic reconstruction. By seamlessly integrating the deep equilibrium model, the iteration of Langevin dynamics culminates in convergence to a fix-point, ensuring the stability of the learned distribution. RESULTS: The feasibility of the proposed method is evaluated on the brain and knee datasets. Retrospective results with uniform and random masks show that the proposed method demonstrates superior performance both quantitatively and qualitatively than the state-of-the-art. CONCLUSION: The proposed method incorporating Langevin dynamics with end-to-end adversarial training facilitates efficient and robust reconstruction for MRI. Empirical evaluations conducted on brain and knee datasets compellingly demonstrate the superior performance of the proposed method in terms of artifact removing and detail preserving.

Amendment of straw with decomposing inoculants benefits the ecosystem carbon budget and carbon footprint in a subtropical wheat cropping field.

The incorporation of straw with decomposing inoculants into soils has been widely recommended to sustain agricultural productivity. However, comprehensive analyses assessing the effects of straw combined with decomposing inoculants on greenhouse gas (GHG) emissions, net primary production (NPP), the net ecosystem carbon budget (NECB), and the carbon footprint (CF) in farmland ecosystems are scant. Here, we carried out a 2-year field study in a wheat cropping system with six treatments: rice straw (S), a straw-decomposing Bacillus subtilis inoculant (K), a straw-decomposing Aspergillus oryzae inoculant (Q), a combination of straw and Bacillus subtilis inoculant (SK), a combination of straw and Aspergillus oryzae inoculant (SQ), and a control with no rice straw or decomposing inoculant (Control). We found that all the treatments resulted in a positive NECB ranging between 838 and 5065 kg C ha-1. Relative to the Control, the S treatment increased CO2 emissions by 16%, while considerably enhancing the NECB by 349%. This difference might be attributed to the straw C input and an increase in plant productivity (NPP, 30%). More importantly, in comparison to that in S, the NECB in SK and SQ significantly increased by 27-35% due to the positive response of NPP to the decomposing inoculants. Although the combination of straw and decomposing inoculants yielded a 3% increase in indirect GHG emissions, it also exhibited the lowest CF (0.18 kg CO2-eq kg-1 of grain). This result was attributed to the synergistic effects of straw and decomposing inoculants, which reduced direct N2O emissions and increased wheat productivity. Overall, the findings of the present study suggested that the combined amendment of straw and decomposing inoculants is an environmentally sustainable management practice in wheat cropping systems that can generate win-win scenarios through improvements in soil C stock, crop productivity, and GHG mitigation.

Emergence, Pattern, and Frequency of Spontaneous Waves in Spreading Epithelial Monolayers.

A striking phenomenon of collective cell motion is that they can exhibit a spontaneously emerging wave during epithelia expansions. However, the fundamental mechanism, governing the emergence and its crucial characteristics (e.g., the eigenfrequency and the pattern), remains an enigma. By introducing a mechanochemical feedback loop, we develop a highly efficient discrete vertex model to investigate the spatiotemporal evolution of spreading epithelia. We find both numerically and analytically that expanding cell monolayers display a power-law dependence of wave frequency on the local heterogeneities (i.e., cell density) with a scaling exponent of -1/2. Moreover, our study demonstrates the quantitative capability of the proposed model in capturing distinct X-, W-, and V-mode wave patterns. We unveil that the phase transition between these modes is governed by the distribution of active self-propulsion forces. Our work provides an avenue for rigorous quantitative investigations into the collective motion and pattern formation of cell groups.

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection.

Accurate detection and segmentation of brain tumors is critical for medical diagnosis. However, current supervised learning methods require extensively annotated images and the state-of-the-art generative models used in unsupervised methods often have limitations in covering the whole data distribution. In this paper, we propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor detection and segmentation. The CycleGAN is trained on unpaired data to generate abnormal images from healthy images as data prior. Then VE-JP is implemented to reconstruct healthy images using synthetic paired abnormal images as a guide, which alters only pathological regions but not regions of healthy. Notably, our method directly learned the joint probability distribution for conditional generation. The residual between input and reconstructed images suggests the abnormalities and a thresholding method is subsequently applied to obtain segmentation results. Furthermore, the multimodal results are weighted with different weights to improve the segmentation accuracy further. We validated our method on three datasets, and compared with other unsupervised methods for anomaly detection and segmentation. The DSC score of 0.8590 in BraTs2020 dataset, 0.6226 in ITCS dataset and 0.7403 in In-house dataset show that our method achieves better segmentation performance and has better generalization.

The dyadic effects of family resilience and social support on quality of life among older adults with chronic illness and their primary caregivers in multigenerational families in China: A cross-sectional study.

Older adults with chronic illness, as well as their primary caregivers in multigenerational families, may experience a complex interplay of factors that affect their quality of life (QOL). However, this interplay is not yet well-characterized for Chinese multigenerational families in particular. In this study, we analyzed how family resilience and social support affect the QOL of both older adults and caregivers in multigenerational Chinese families specifically. We enrolled 258 pairs of older adults with chronic illness and their primary caregivers in a multicenter cross-sectional study conducted in southern China in December 2021. Using the Actor-Partner Interdependence Model (APIM), we then examined the correlation between family resilience, social support, and QOL in dyadic analysis and found that QOL, family resilience, and social support for primary caregivers were better than those of older adults with chronic illness (t = 3.66-16.3, p＜0.01). These factors were found to be positively correlated (r = 0.22-0.60, p＜0.05), except for the family resilience of primary caregivers and the QOL of older adults with chronic illness (r = -0.14, p = 0.04). Additionally, actor effect results showed that when a dyadic member has high family resilience and objective social support, they tend to have a better QOL (ß = 0.5-1.48, P < 0.01). However, partner effect results showed that when the primary caregiver has high family resilience, this is associated with a worse QOL for the older adult (ß = -1.06, P < 0.01). Furthermore, we found that objective social support of dyads does not significantly influence their partner's QOL (ß = 0.88/0.31, P＞0.05) for any pair. This suggests that medical staff should pay attention to the impact of family resilience on the QOL of older adult and caregiver dyads and explore health management plans that focus on binary coping in multigenerational families.

N-Cinnamoylpyrrole-derived alkaloids from the genus Piper as promising agents for ischemic stroke by targeting eEF1A1.

BACKGROUND: Ischemic stroke (IS) is a serious cerebrovascular disease characterized by significantly elevated mortality and disability rates, and the treatments available for this disease are limited. Neuroinflammation and oxidative stress are deemed the major causes of cerebral ischemic injury. N-Cinnamoylpyrrole alkaloids form a small group of natural products from the genus Piper and have not been extensively analyzed pharmacologically. Thus, identifying the effect and mechanism of N-cinnamoylpyrrole-derived alkaloids on IS is worthwhile. PURPOSE: The present research aimed to explore the antineuroinflammatory and antioxidative stress effects of N-cinnamoylpyrrole-derived alkaloids isolated from the genus Piper and to explain the effects and mechanism on IS. METHODS: N-cinnamoylpyrrole-derived alkaloids were isolated from Piper boehmeriaefolium var. tonkinense and Piper sarmentosum and identified by various chromatographic methods. Lipopolysaccharide (LPS)-induced BV-2 microglia and a mouse model intracerebroventricularly injected with LPS were used to evaluate the antineuroinflammatory and antioxidative stress effects. Oxygen‒glucose deprivation/reperfusion (OGD/R) and transient middle cerebral artery occlusion (tMCAO) models were used to evaluate the effect of PB-1 on IS. To elucidate the fundamental mechanism, the functional target of PB-1 was identified by affinity-based protein profiling (ABPP) strategy and verified by cellular thermal shift assay (CETSA), drug affinity responsive target stability (DARTS), and circular dichroism (CD) analyses. The effect of PB-1 on the NF-κB and NRF2 signaling pathways was subsequently evaluated via western blotting and immunofluorescence staining. RESULTS: The results showed that N-cinnamoylpyrrole-derived alkaloids significantly affected neuroinflammation and oxidative stress. The representative compound, PB-1 not only inhibited neuroinflammation and oxidative stress induced by LPS or OGD/R insult, but also alleviated cerebral ischemic injury induced by tMCAO. Further molecular mechanism research found that PB-1 promoted antineuroinflammatory and antioxidative stress activities via the NF-κB and NRF2 signaling pathways by targeting eEF1A1. CONCLUSION: Our research initially unveiled that the therapeutic impact of PB-1 on cerebral ischemic injury might rely on its ability to target eEF1A1, leading to antineuroinflammatory and antioxidative stress effects. The novel discovery highlights eEF1A1 as a potential target for IS treatment and shows that PB-1, as a lead compound that targets eEF1A1, may be a promising therapeutic agent for IS.

Antireflective vertical-cavity surface-emitting laser for LiDAR.

Multijunction vertical-cavity surface-emitting lasers (VCSELs) have gained popularity in automotive LiDARs, yet achieving a divergence of less than 16° (D86) is difficult for conventional extended cavity designs due to multiple-longitudinal-mode lasing. Our innovation, the antireflective vertical-cavity surface-emitting laser (AR-VCSEL), addresses this challenge by introducing an antireflective light reservoir, where the electric field intensity is substantially higher than the gain region. This reduces the required cavity length for minimal divergence, preserving the single-longitudinal-mode lasing. A 6-junction AR-VCSEL array showcases a halved divergence and tripled brightness compared to its conventional counterpart. Various multijunction AR-VCSEL array designs achieve a divergence range of 8° to 16° (D86). Notably, a 7 µm AR-VCSEL emitter achieves 28.4 mW in single transverse mode lasing. AR-VCSEL stands out among semiconductor lasers, offering a well-balanced power density and brightness, making it a cost-effective solution for long-distance LiDARs. The antireflective cavity concept may inspire diverse applications in photonic devices beyond LiDARs.

TiO2-modified two-dimensional composite of nitrogen-doped molybdenum trioxide nanosheets as a high-performance anode for lithium-ion batteries.

Nitrogen-doped molybdenum trioxide (MoO3/NC) has drawbacks such as volume expansion during long-term charging and discharging cycles, which severely limit its further application. This work proposes the addition of titanium dioxide nanoparticles (TiO2 NPs) for performance improvement of MoO3/NC. TiO2 NPs embedded on the surface of a MoO3/NC nanosheet can alleviate its volume expansion and the accumulation of lithiated products and improve the conductivity of the electrode material. The results show that the MoO3/NC nanosheet decorated with TiO2 NPs (TiO2@MoO3/NC), when used as an electrode material, exhibited a discharge specific capacity of 419 mA h g-1 at a current density of 0.05 A g-1 and retained a discharge specific capacity of 517 mA h g-1 after 600 cycles at a current density of 1 A g-1.

Multiple-cycle photochemical cascade reactions.

Cascade reactions represent an efficient and economical synthetic approach, enabling the rapid synthesis of a wide array of structurally complex organic compounds. These compounds, previously inaccessible, can now be synthesized in a remarkably limited number of steps. Concurrently, the photochemical reactions of organic molecules have gained prominence as a potent strategy for accessing a diverse range of radical species and intermediates. This is achieved in a controlled manner under mild conditions. Owing to the relentless endeavors of chemists, significant strides have been made in the realm of photochemical cascade reactions. These advancements have facilitated the synthesis of novel molecular structures with high complexity, structures that are typically challenging to generate under thermal conditions. In this review, we comprehensively summarize and underscore the recent pivotal advancements in visible-light-induced cascade reactions. Our focus is on the elucidation of multiple photochemical catalytic cycles, emphasizing the catalytic activation modes and the types of reactions involved.

Dynamic X-ray imaging with screen-printed perovskite CMOS array.

High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-lifetime product is 5.2 × 10-4 cm2 V-1 and X-ray sensitivity is 1.6 × 104 µC Gyair-1 cm-2. Samples larger than 5 cm[Formula: see text]10 cm can be rapidly imaged by scanning this detector at a speed of 300 frames per second along the vertical and horizontal directions. In comparison to traditional indirect-conversion CMOS X-ray detector, this perovskite CMOS detector offers high spatial resolution (5.0 lp mm-1) X-ray radiographic imaging capability at low radiation dose (260 nGy). Moreover, 3D tomographic images of a biological specimen are also successfully reconstructed. These results highlight the perovskite CMOS detector's potential in high-resolution, large-area, low-dose dynamic biomedical X-ray and CT imaging, as well as in non-destructive X-ray testing and security scanning.