A Light-Responsive Neural Circuit Suppresses Feeding.

Light plays an essential role in a variety of physiological processes, including vision, mood, and glucose homeostasis. However, the intricate relationship between light and an animal's feeding behavior has remained elusive. Here, we found that light exposure suppresses food intake, whereas darkness amplifies it in male mice. Interestingly, this phenomenon extends its reach to diurnal male Nile grass rats and healthy humans. We further show that lateral habenula (LHb) neurons in mice respond to light exposure, which in turn activates 5-HT neurons in the dorsal Raphe nucleus (DRN). Activation of the LHb→5-HTDRN circuit in mice blunts darkness-induced hyperphagia, while inhibition of the circuit prevents light-induced anorexia. Together, we discovered a light-responsive neural circuit that relays the environmental light signals to regulate feeding behavior in mice.

HDAC3 promotes Sertoli cell maturation and maintains the blood-testis barrier dynamics.

Germ cell development depends on the capacity of somatic Sertoli cells to undergo differentiation into a mature state and establish a germ cell-specific blood-testis barrier (BTB). The BTB structure confers an immunological barrier for meiotic and postmeiotic germ cells, and its dynamic permeability facilitates a transient movement of preleptotene spermatocytes through BTB to enter meiosis. However, the regulatory factors involved in Sertoli cell maturation and how BTB dynamics coordinate germ cell development remain unclear. Here, we found a histone deacetylase HDAC3 abundantly expresses in Sertoli cells and localizes in both cytoplasm and nucleus. Sertoli cell-specific Hdac3 knockout in mice causes infertility with compromised integrity of blood-testis barrier, leading to germ cells unable to traverse through BTB and an accumulation of preleptotene spermatocytes in juvenile testis. Mechanistically, nuclear HDAC3 regulates the expression program of Sertoli cell maturation genes, and cytoplasmic HDAC3 forms a complex with the gap junction protein Connexin 43 to modulate the BTB integrity and dynamics through regulating the distribution of tight junction proteins. Our findings identify HDAC3 as a critical regulator in promoting Sertoli cell maturation and maintaining the homeostasis of the blood-testis barrier.

Strong Local Polarization Fluctuations Enabled High Electrostatic Energy Storage in Pb-Free Relaxors.

Electrostatic energy-storage ceramic capacitors are essential components of modern electrified power systems. However, improving their energy-storage density while maintaining high efficiency to facilitate cutting-edge miniaturized and integrated applications remains an ongoing challenge. Herein, we report a record-high energy-storage density of 20.3 J cm-3 together with a high efficiency of 89.3% achieved by constructing a relaxor ferroelectric state with strongly enhanced local polarization fluctuations. This is realized by incorporating highly polarizable, heterovalent, and large-sized Zn and Nb ions into a Bi0.5Na0.5TiO3-BaTiO3 ferroelectric matrix with very strong tetragonal distortion. Element-specific local structure analysis revealed that the foreign ions strengthen the magnitude of the unit-cell polarization vectors while simultaneously reducing their orientation anisotropy and forming strong fluctuations in both magnitude and orientation within 1-3 nm polar clusters. This leads to a particularly high polarization variation (ΔP) of 72 µC cm-2, low hysteresis, and a high effective polarization coefficient at a high breakdown strength of 80 kV mm-1. This work has surpassed the current energy density limit of 20 J cm-3 in bulk Pb-free ceramics and has demonstrated that controlling the local structure via the chemical composition design can open up new possibilities for exploring relaxors with high energy-storage performance.

Chemical Framework to Design Linear-like Relaxors toward Capacitive Energy Storage.

ABO3-type perovskite relaxor ferroelectrics (RFEs) have emerged as the preferred option for dielectric capacitive energy storage. However, the compositional design of RFEs with high energy density and efficiency poses significant challenges owing to the vast compositional space and the absence of general rules. Here, we present an atomic-level chemical framework that captures inherent characteristics in terms of radius and ferroelectric activity of ions. By categorizing A/B-site ions as host framework, rattling, ferroelectrically active, and blocking ions and assembling these four types of ions with specific criteria, linear-like relaxors with weak locally correlated and highly extendable unit-cell polarization vectors can be constructed. As example, we demonstrate two new compositions of Bi0.5K0.5TiO3-based and BaTiO3-based relaxors, showing extremely high recoverable energy densities of 17.3 and 12.1 J cm-3, respectively, both with a high efficiency of about 90%. Further, the role of different types of ions in forming heterogeneous polar structures is identified through element-specific local structure analysis using neutron total scattering combined with reverse Monte Carlo modeling. Our work not only opens up new avenues toward rational compositional design of high energy storage performance lead-free RFEs but also sheds light on atomic-level manipulation of functional properties in compositionally complex ferroelectrics.

Outstanding Energy-Storage Density Together with Efficiency of above 90% via Local Structure Design.

Dielectric ceramic capacitors with high recoverable energy density (Wrec) and efficiency (η) are of great significance in advanced electronic devices. However, it remains a challenge to achieve high Wrec and η parameters simultaneously. Herein, based on density functional theory calculations and local structure analysis, the feasibility of developing the aforementioned capacitors is demonstrated by considering Bi0.25Na0.25Ba0.5TiO3 (BNT-50BT) as a matrix material with large local polarization and structural distortion. Remarkable Wrec and η of 16.21 J/cm3 and 90.5% have been achieved in Bi0.25Na0.25Ba0.5Ti0.92Hf0.08O3 via simple chemical modification, which is the highest Wrec value among reported bulk ceramics with η greater than 90%. The examination results of local structures at lattice and atomic scales indicate that the disorderly polarization distribution and small nanoregion (∼3 nm) lead to low hysteresis and high efficiency. In turn, the drastic increase in local polarization activated via the ultrahigh electric field (80 kV/mm) leads to large polarization and superior energy storage density. Therefore, this study emphasizes that chemical design should be established on a clear understanding of the performance-related local structure to enable a targeted regulation of high-performance systems.

Melatonin in cancer biology: pathways, derivatives, and the promise of targeted delivery.

Melatonin, historically recognized for its primary role in regulating circadian rhythms, has expanded its influence particularly due to its wide range of biological activities. It has firmly established itself in cancer research. To highlight its versatility, we delved into how melatonin interacts with key signaling pathways, such as the Wnt/ß-Catenin, PI3K, and NF-κB pathways, which play foundational roles in tumor development and progression. Notably, melatonin can intricately modulate these pathways, potentially affecting various cellular functions such as apoptosis, metastasis, and immunity. Additionally, a comprehensive review of current clinical studies provides a dual perspective. These studies confirm melatonin's potential in cancer management but also underscore its inherent limitations, particularly its limited bioavailability, which often relegates it to a supplementary role in treatments. Despite this limitation, there is an ongoing quest for innovative solutions and current advancements include the development of melatonin derivatives and cutting-edge delivery systems. By synthesizing the past, present, and future, this review provides a detailed overview of melatonin's evolving role in oncology, positioning it as a potential cornerstone in future cancer therapeutics.

Knowledge-Augmented Deep Learning for Segmenting and Detecting Cerebral Aneurysms With CT Angiography: A Multicenter Study.

Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneurysm segmentation and detection on CT angiography (CTA) images and to compare its performance with radiology reports. Materials and Methods Consecutive head or head and neck CTA images of suspected unruptured cerebral aneurysms were gathered retrospectively from eight hospitals between February 2018 and October 2021 for model development. An external test set with reference standard digital subtraction angiography (DSA) scans was obtained retrospectively from one of the eight hospitals between February 2022 and February 2023. Radiologists (reference standard) assessed aneurysm segmentation, while model performance was evaluated using the Dice similarity coefficient (DSC). The model's aneurysm detection performance was assessed by sensitivity and comparing areas under the receiver operating characteristic curves (AUCs) between the model and radiology reports in the DSA data set with use of the DeLong test. Results Images from 6060 patients (mean age, 56 years ± 12 [SD]; 3375 [55.7%] female) were included for model development (training: 4342; validation: 1086; and internal test set: 632). Another 118 patients (mean age, 59 years ± 14; 79 [66.9%] female) were included in an external test set to evaluate performance based on DSA. The model achieved a DSC of 0.87 for aneurysm segmentation performance in the internal test set. Using DSA, the model achieved 85.7% (108 of 126 aneurysms [95% CI: 78.1, 90.1]) sensitivity in detecting aneurysms on per-vessel analysis, with no evidence of a difference versus radiology reports (AUC, 0.93 [95% CI: 0.90, 0.95] vs 0.91 [95% CI: 0.87, 0.94]; P = .67). Model processing time from reconstruction to detection was 1.76 minutes ± 0.32 per scan. Conclusion The proposed DL model could accurately segment and detect cerebral aneurysms at CTA with no evidence of a significant difference in diagnostic performance compared with radiology reports. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Payabvash in this issue.

DNA methylation remodeled amino acids biosynthesis regulates flower senescence in carnation (Dianthus caryophyllus).

Dynamic DNA methylation regulatory networks are involved in many biological processes. However, how DNA methylation patterns change during flower senescence and their relevance with gene expression and related molecular mechanism remain largely unknown. Here, we used whole genome bisulfite sequencing to reveal a significant increase of DNA methylation in the promoter region of genes during natural and ethylene-induced flower senescence in carnation (Dianthus caryophyllus L.), which was correlated with decreased expression of DNA demethylase gene DcROS1. Silencing of DcROS1 accelerated while overexpression of DcROS1 delayed carnation flower senescence. Moreover, among the hypermethylated differentially expressed genes during flower senescence, we identified two amino acid biosynthesis genes, DcCARA and DcDHAD, with increased DNA methylation and reduced expression in DcROS1 silenced petals, and decreased DNA methylation and increased expression in DcROS1 overexpression petals, accompanied by decreased or increased amino acids content. Silencing of DcCARA and DcDHAD accelerates carnation flower senescence. We further showed that adding corresponding amino acids could largely rescue the senescence phenotype of DcROS1, DcCARA and DcDHAD silenced plants. Our study not only demonstrates an essential role of DcROS1-mediated remodeling of DNA methylation in flower senescence but also unravels a novel epigenetic regulatory mechanism underlying DNA methylation and amino acid biosynthesis during flower senescence.

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary between readers. This study aimed to develop a clinically applicable automatic ASPECTS system employing deep learning (DL). METHODS: This study enrolled 1987 NCCT scans that were retrospectively collected from four centers between January 2017 and October 2021. A DL-based system for automated ASPECTS assessment was trained on a development cohort (N = 1767) and validated on an independent test cohort (N = 220). The consensus of experienced physicians was regarded as a reference standard. The validity and reliability of the proposed system were assessed against physicians' readings. A real-world prospective application study with 13,399 patients was used for system validation in clinical contexts. RESULTS: The DL-based system achieved an area under the receiver operating characteristic curve (AUC) of 84.97% and an intraclass correlation coefficient (ICC) of 0.84 for overall-level analysis on the test cohort. The system's diagnostic sensitivity was 94.61% for patients with dichotomized ASPECTS at a threshold of ≥ 6, with substantial agreement (ICC = 0.65) with expert ratings. Combining the system with physicians improved AUC from 67.43 to 89.76%, reducing diagnosis time from 130.6 ± 66.3 s to 33.3 ± 8.3 s (p < 0.001). During the application in clinical contexts, 94.0% (12,591) of scans successfully processed by the system were utilized by clinicians, and 96% of physicians acknowledged significant improvement in work efficiency. CONCLUSION: The proposed DL-based system could accurately and rapidly determine ASPECTS, which might facilitate clinical workflow for early intervention. CLINICAL RELEVANCE STATEMENT: The deep learning-based automated ASPECTS evaluation system can accurately and rapidly determine ASPECTS for early intervention in clinical workflows, reducing processing time for physicians by 74.8%, but still requires validation by physicians when in clinical applications. KEY POINTS: The deep learning-based system for ASPECTS quantification has been shown to be non-inferior to expert-rated ASPECTS. This system improved the consistency of ASPECTS evaluation and reduced processing time to 33.3 seconds per scan. 94.0% of scans successfully processed by the system were utilized by clinicians during the prospective clinical application.

Single-Electron Reduction of "Push-Pull" C-C Single Bond and Decyanation Using Tertiary Amines as the Organic Electron Donor.

Using commercially available tertiary amines as an organic electron donor (OED), the reduction of "push-pull" C-C single bond and reductive decyanation of tetrahydroisoquinolines were realized. These reactions exhibited higher reaction efficiency and better functional group tolerance compared with those of metallic reductants, and the mechanistic study indicated that a radical intermediate was involved in the reduction of the C-C single bond, which provides a new way to the OED-enabled mild reduction.

Impact of Climate on Soil Organic Matter Composition in Soils of Tropical Volcanic Regions Revealed by EGA-MS and Py-GC/MS.

Soil organic matter (SOM) crucially influences the global carbon cycle, yet its molecular composition and determinants are understudied, especially for tropical volcanic regions. We investigated how SOM compounds change in response to climate, vegetation, soil horizon, and soil properties and the relationship between SOM composition and microbial decomposability in Tanzanian and Indonesian volcanic regions. We collected topsoil (0-15 cm) and subsoil (20-40 cm) horizons (n = 22; pH: 4.6-7.6; SOC: 10-152 g kg-1) with undisturbed vegetation and wide mean annual temperature and moisture ranges (14-26 °C; 800-3300 mm) across four elevational transects (340-2210 m asl.). Evolved gas analysis-mass spectrometry (EGA-MS) documented a simultaneous release of SOM compounds and clay mineral dehydroxylation. Subsequently applying double-shot pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) at 200 and 550 °C, we detailed the molecular composition of topsoil and subsoil SOM. A minor portion (2.7 ± 1.9%) of compounds desorbed at 200 °C, limiting its efficacy for investigating overall SOM characteristics. Pyrolyzed SOM closely aligns with the intermediate decomposable SOM pool, with most pyrolysates (550 °C) originating from this pool. Pyrolysates composition suggests tropical SOM is mainly microbial-derived and subsoil contains more degraded compounds. Higher litter inputs and attenuated SOM decomposition due to cooler temperatures and lower soil pH (<5.5) produce less-degraded SOM at higher elevations. Redundancy analyses revealed the crucial role of active Al/Fe (oxalate-extractable Al/Fe), abundant in low-temperature/high-moisture conditions, in stabilizing these less-degraded components. Our findings provide new insights into SOM molecular composition and its determinants, critical for understanding the carbon cycle in tropical ecosystems.

Theoretical investigation of 2D/2D van der Waals SbPO4/BiOClxBr1-x heterojunctions for photocatalytic water splitting.

Bismuth halogenoxide (BiOX)-based heterojunctions have garnered considerable attention recently due to their potential to enhance photocatalytic performance. However, the predominant focus on II-type heterojunctions has posed challenges in achieving the requisite band edge positions for efficient water splitting. In this investigation, stable van der Waals SbPO4/BiOClxBr1-x heterojunctions were constructed theoretically by using density-functional theory (DFT). Our findings demonstrate that SbPO4 can modulate the formation of Z-scheme heterojunctions with BiOClxBr1-x. The structural properties of BiOX were preserved, while reaching excellent photocatalytic capabilities with high redox capacities. Further investigation unveiled that the band edge positions of the heterojunctions fully satisfy the oxidation-reduction potential of water. Moreover, these heterojunctions exhibit notable absorption efficiency in the visible range, with absorption increasing as x decreases. Our research provides valuable theoretical insights for the experimental synthesis of high-performance BiOX-based photocatalysts for water splitting, leveraging the unique properties of SbPO4. These insights contribute to the advancement of clean energy technology.

[Risk factors for pancreatitis after endoscopic retrograde cholangiopancreatography in children]. / å„¿ç«¥ç»å† é•œé€†è¡Œèƒ°èƒ†ç®¡é€ å½±æœ¯åŽèƒ°è ºç‚Žå‘ç”Ÿçš„å±é™©å› ç´ åˆ†æž.

OBJECTIVES: To investigate the application of endoscopic retrograde cholangiopancreatography (ERCP) in children and the risk factors for post-ERCP pancreatitis (PEP). METHODS: A retrospective analysis was conducted on the clinical data of 66 children, aged ≤16 years, who underwent ERCP for pancreaticobiliary diseases at the Gastrointestinal Endoscopy Center of the Second Affiliated Hospital of Kunming Medical University from September 2013 to September 2023. The incidence rate of PEP and the risk factors for the development of PEP were analyzed. RESULTS: A total of 78 ERCP procedures were performed on 66 children, with 5 diagnostic ERCPs, 69 therapeutic ERCPs, and 4 failed procedures. The success rate of ERCP operations was 95% (74/78). There were 17 cases of PEP in total, with an incidence rate of 22%. In the PEP group, the proportion of children with normal preoperative bilirubin and the proportion of guidewire insertion into the pancreatic duct during surgery were higher than in the non-PEP group (P<0.05). The multivariate logistic regression analysis showed that guidewire insertion into the pancreatic duct was an independent risk factor for PEP (P<0.05). CONCLUSIONS: With the increasing application of ERCP in children with pancreaticobiliary diseases, it is important to select an appropriate intubation technique during surgery to avoid blindly entering the guidewire into the pancreatic duct and reduce the occurrence of PEP.

[Circadian rhythm and health: dialogue between traditional Chinese medicine and modern medicine].

Circadian rhythm refers to the daily rhythmic variations in an organism. The irregular lifestyles of modern humans have led to a high incidence of chronic diseases, highlighting an inseparable relationship between disrupted circadian rhythm and disease development. TCM has long discussed rhythmic variations, with records dating back to the Yellow Emperor's Inner Canon(Huang Di Nei Jing), which laid a rich theoretical foundation for the research on circadian rhythm. Modern medical research has provided a more comprehensive explanation of its molecular mechanisms. This article integrated the current understanding of circadian rhythm in both Chinese and western medicine, emphasizing the crucial relationship between rhythm regulation and disease treatment. By highlighting the interdisciplinary nature of the two fields, it offers new directions for exploring the field of chronomedicine.

Targeting histone deacetylase in cardiac diseases.

Histone deacetylases (HDAC) catalyze the removal of acetylation modifications on histones and non-histone proteins, which regulates gene expression and other cellular processes. HDAC inhibitors (HDACi), approved anti-cancer agents, emerge as a potential new therapy for heart diseases. Cardioprotective effects of HDACi are observed in many preclinical animal models of heart diseases. Genetic mouse models have been developed to understand the role of each HDAC in cardiac functions. Some of the findings are controversial. Here, we provide an overview of how HDACi and HDAC impact cardiac functions under physiological or pathological conditions. We focus on in vivo studies of zinc-dependent classical HDACs, emphasizing disease conditions involving cardiac hypertrophy, myocardial infarction (MI), ischemic reperfusion (I/R) injury, and heart failure. In particular, we review how non-biased omics studies can help our understanding of the mechanisms underlying the cardiac effects of HDACi and HDAC.

Transient Pressure Behavior of CBM Wells during the Injection Fall-Off Test Considering the Quadratic Pressure Gradient.

Conventional coalbed methane (CBM) reservoir models for injection fall-off testing often disregard the quadratic pressure gradient's impact. This omission leads to discrepancies in simulating the transient behavior of formation fluids and extracting critical reservoir properties. Accurate determination of permeability, storability, and other properties is crucial for effective reservoir characterization and production forecasting. Inaccurate estimations can lead to suboptimal well placement, ineffective production strategies, and ultimately, missed economic opportunities. To address this shortcoming, we present a novel analytical model that explicitly incorporates the complexities of the quadratic pressure gradient and dual-permeability flow mechanisms, prevalent in many CBM formations where nanopores are rich, presenting a kind of natural nanomaterial. This model offers significant advantages over traditional approaches. By leveraging variable substitution, it facilitates the derivation of analytical solutions in the Laplace domain, subsequently converted to real-space solutions for practical application. These solutions empower reservoir engineers to generate novel type curves, a valuable tool for analyzing wellbore pressure responses during injection fall-off tests. By identifying distinct flow regimes within the reservoir based on these type curves, engineers gain valuable insights into the dynamic behavior of formation fluids. This model goes beyond traditional approaches by investigating the influence of the quadratic pressure gradient coefficient, inter-porosity flow coefficient, and storability ratio on the pressure response. A quantitative comparison with traditional models further elucidates the key discrepancies caused by neglecting the quadratic pressure gradient. The results demonstrate the proposed model's ability to accurately depict the non-linear flow behavior observed in CBM wells. This translates to more reliable pressure and pressure derivative curves that account for the impact of the quadratic pressure gradient.

CO2 Storage Monitoring via Time-Lapse Full Waveform Inversion with Automatic Differentiation.

In the field of CO2 capture utilization and storage (CCUS), recent advancements in active-source monitoring have significantly enhanced the capabilities of time-lapse acoustical imaging, facilitating continuous capture of detailed physical parameter images from acoustic signals. Central to these advancements is time-lapse full waveform inversion (TLFWI), which is increasingly recognized for its ability to extract high-resolution images from active-source datasets. However, conventional TLFWI methodologies, which are reliant on gradient optimization, face a significant challenge due to the need for complex, explicit formulation of the physical model gradient relative to the misfit function between observed and predicted data over time. Addressing this limitation, our study introduces automatic differentiation (AD) into the TLFWI process, utilizing deep learning frameworks such as PyTorch to automate gradient calculation using the chain rule. This novel approach, AD-TLFWI, not only streamlines the inversion of time-lapse images for CO2 monitoring but also tackles the issue of local minima commonly encountered in deep learning optimizers. The effectiveness of AD-TLFWI was validated using a realistic model from the Frio-II CO2 injection site, where it successfully produced high-resolution images that demonstrate significant changes in velocity due to CO2 injection. This advancement in TLFWI methodology, underpinned by the integration of AD, represents a pivotal development in active-source monitoring systems, enhancing information extraction capabilities and providing potential solutions to complex multiphysics monitoring challenges.

A High-Performance Strain Sensor for the Detection of Human Motion and Subtle Strain Based on Liquid Metal Microwire.

Flexible strain sensors have a wide range of applications, such as human motion monitoring, wearable electronic devices, and human-computer interactions, due to their good conformability and sensitive deformation detection. To overcome the internal stress problem of solid sensing materials during deformation and prepare small-sized flexible strain sensors, it is necessary to choose a more suitable sensing material and preparation technology. We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on a polyimide substrate. The LMNPs were assembled using the femtosecond laser direct writing technology to form liquid metal microwires. A wearable strain sensor from the liquid metal microwire was fabricated with an excellent gauge factor of up to 76.18, a good linearity in a wide sensing range, and a fast response/recovery time of 159 ms/120 ms. Due to these extraordinary strain sensing performances, the strain sensor can monitor facial expressions in real time and detect vocal cord vibrations for speech recognition.

The Effect of Nutrient Deficiencies on the Annual Yield and Root Growth of Summer Corn in a Double-Cropping System.

The North China Plain has a typical winter wheat-summer corn double-cropping pattern. The effects of nutrient deficiency conditions on the root characteristics and yield of summer corn in the double-cropping system were studied for four years. Long-term monotonous fertilization patterns undermine crop rotation systems and are detrimental to the sustainability of agricultural production. To complement the development of rational fertilization strategies by exploring the response of crop rotation systems to nutrient deficiencies, an experiment was conducted in a randomized complete block design consisting of five treatments with three replicates for each treatment: (1) an adequate supply of nitrogen and phosphate fertilizers and potash-deficient treatment (T1); (2) an adequate supply of nitrogen and potash fertilizers and phosphorus-deficient treatment (T2); (3) an adequate supply of phosphorus and potash fertilizers and nitrogen-deficient treatment (T3); (4) nutrient-sufficient treatment for crop growth (T4); and (5) no-fertilizer treatment (CK). The results showed that different nutrient treatments had significant effects on the root length density (RLD), root surface area density (RSAD), and root dry weight density (RDWD) in summer corn. At the physiological maturity stage (R6), the root indexes of RLD, RSAD, and RDWD were significantly higher in the 0-20 cm soil layer in T4 compared to CK, with an increase of 86.2%, 131.4%, and 100.0%, respectively. Similarly, in the 20-40 cm soil layer, the root indexes of T4 were 85.7%, 61.3%, and 50.0% higher than CK, with varied differences observed in the other nutrient-deficient treatments. However, there was no significant difference among the treatments in the 40-60 cm layer except for T4, whose root index showed a difference. The root fresh weight and root dry matter in T4, T3, T2, and T1 were increased to different degrees compared with CK. In addition, these differences in root indexes affected the annual yield of crops, which increased by 20.96%, 21.95%, and 8.14% in T4, T2, and T1, respectively, compared to CK. The spike number and the number of grains per spike of T4 were 10.8% and 8.3% higher than those of CK, which led to the differences in summer corn yields. The 1000-kernel weight of T4, T2, and T1 were 9.5%, 8.8%, and 7.4% higher than that of CK, whereas the determining nutrient was nitrogen fertilizer, and phosphorus fertilizer had a higher effect on yield than potassium fertilizer. This provides a theoretical basis for the effect of nutrient deficiency conditions on yield stability in a double-cropping system.

Structural changes in spinal cord following optic neuritis: Insights from quantitative spinal MRI.

OBJECTIVES: Previous studies have demonstrated that optic neuritis (ON) affects brain plasticity. However, whether ON affects the spinal cord remains unclear. We aimed to investigate the spinal cord changes in ON and their associations with disability. METHODS: A total of 101 ON patients, and 41 healthy controls (HC) were retrospectively recruited. High-resolution imaging was conducted using a Magnetization Prepared Rapid Acquisition Gradient-Echo (MP-RAGE) sequence for T1-weighted images and an echo planar imaging (EPI) sequence for Diffusion Tensor Imaging (DTI) data collection. Additionally, patients' disability and cognitive impairment were evaluated using the Expanded Disability Status Scale (EDSS) and the Paced Auditory Serial Addition Test (PASAT), respectively. The quantitative spinal MRI was employed to examine the cross-sectional area (CSA) and diffusion indicators, with a specific focus on calculating the average values across the C2-C7 cervical spinal cord segments. CSA, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared between groups. Correlation analyses were performed between CSA, diffusion indicators, and clinical variables. RESULTS: No significant differences were found in CSA between ON patients and HCs. MD (p = 0.007) and RD (p = 0.018) were increased in ON patients compared with HCs, and AD was decreased in ON (p = 0.013). The AD values of the ON patients were significantly positively correlated with PASAT scores (r = 0.37, p < 0.001). CONCLUSIONS: This study provided imaging evidence for DTI abnormalities in patients with ON. Spinal cord DTI can improve our knowledge of the path physiology of ON, and clinical progression.