Physics-Informed DeepMRI: k-Space Interpolation Meets Heat Diffusion.

Recently, diffusion models have shown considerable promise for MRI reconstruction. However, extensive experimentation has revealed that these models are prone to generating artifacts due to the inherent randomness involved in generating images from pure noise. To achieve more controlled image reconstruction, we reexamine the concept of interpolatable physical priors in k-space data, focusing specifically on the interpolation of high-frequency (HF) k-space data from low-frequency (LF) k-space data. Broadly, this insight drives a shift in the generation paradigm from random noise to a more deterministic approach grounded in the existing LF k-space data. Building on this, we first establish a relationship between the interpolation of HF k-space data from LF k-space data and the reverse heat diffusion process, providing a fundamental framework for designing diffusion models that generate missing HF data. To further improve reconstruction accuracy, we integrate a traditional physics-informed k-space interpolation model into our diffusion framework as a data fidelity term. Experimental validation using publicly available datasets demonstrates that our approach significantly surpasses traditional k-space interpolation methods, deep learning-based k-space interpolation techniques, and conventional diffusion models, particularly in HF regions. Finally, we assess the generalization performance of our model across various out-of-distribution datasets. Our code are available at https://github.com/ZhuoxuCui/Heat-Diffusion.

Blood metabolites, neurocognition and psychiatric disorders: a Mendelian randomization analysis to investigate causal pathways.

BACKGROUND: Neurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear. METHODS: To explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder. RESULTS: MR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10-6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, -0.041 to -0.015; P = 1.31 × 10-5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings. CONCLUSION: Our results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

PM2.5 triggers tau aggregation in a mouse model of tauopathy.

The aggregation and prion-like propagation of tau are the hallmarks of Alzheimer's disease (AD) and other tauopathies. However, the molecular mechanisms underlying the assembly and spread of tau pathology remain elusive. Epidemiological data show that exposure to fine particulate matter (PM2.5) is associated with an increased risk of AD. However, the molecular mechanisms remain unknown. Here, we showed that PM2.5 triggered the aggregation of tau and promoted the formation of tau fibrils. Injection of PM2.5-induced tau preformed fibrils (PFFs) into the hippocampus of tau P301S transgenic mice promoted the aggregation of tau and induced cognitive deficits and synaptic dysfunction. Furthermore, intranasal administration of PM2.5 exacerbated tau pathology and induced cognitive impairment in tau P301S mice. In conclusion, our results indicated that PM2.5 exposure promoted tau pathology and induced cognitive impairments. These results provide mechanistic insight into how PM2.5 increases the risk of AD.

A continental-scale analysis reveals the latitudinal gradient of stomatal density across amphistomatous species: Evolutionary history vs. present-day environment.

BACKGROUND AND AIMS: Amphistomy is a potential method for increasing photosynthetic rate; however, the latitudinal gradients of stomatal density across amphistomatous species and their drivers remain unknown. METHODS: Here, the adaxial stomatal density (SDad) and abaxial stomatal density (SDab) of 486 amphistomatous species-site combinations, belonging to 32 plant families, were collected from China, and their total stomatal density (SDtotal) and stomatal ratio (SR) were calculated. KEY RESULTS: Overall, these four stomatal traits did not show significant phylogenetic signals. There were no significant differences in SDab and SDtotal between woody and herbaceous species, but SDad and SR were higher in woody species than in herbaceous species. Besides, a significantly positive relationship between SDab and SDad was observed. We also found that stomatal density (including SDab, SDad, and SDtotal) decreased with latitude while SR increased with latitude, and temperature seasonality was the most important environmental factor driving it. Besides, evolutionary history (represented by both phylogeny and species) explained about 10-22 fold more of the variation in stomatal traits than the present-day environment (65.2%-71.1% vs. 2.9%-6.8%). CONCLUSIONS: Our study extended our knowledge of trait-environment relationships and highlighted the importance of evolutionary history in driving stomatal trait variability.

The pan-tandem repeat map highlights multiallelic variants underlying gene expression and agronomic traits in rice.

Tandem repeats (TRs) are genomic regions that tandemly change in repeat number, which are often multiallelic. Their characteristics and contributions to gene expression and quantitative traits in rice are largely unknown. Here, we survey rice TR variations based on 231 genome assemblies and the rice pan-genome graph. We identify 227,391 multiallelic TR loci, including 54,416 TR variations that are absent from the Nipponbare reference genome. Only 1/3 TR variations show strong linkage with nearby bi-allelic variants (SNPs, Indels and PAVs). Using 193 panicle and 202 leaf transcriptomic data, we reveal 485 and 511 TRs act as QTLs independently of other bi-allelic variations to nearby gene expression, respectively. Using plant height and grain width as examples, we identify and validate TRs contributions to rice agronomic trait variations. These findings would enhance our understanding of the functions of multiallelic variants and facilitate rice molecular breeding.

Recent advances in nanomaterials for the treatment of femoral head necrosis.

Osteonecrosis of the femoral head (ONFH) is a condition that causes considerable pain and discomfort for patients, and its pathogenic mechanisms are not yet fully understood. While there have been many studies that suggest multiple factors may contribute to its development, current treatments involve both surgical and nonsurgical options. However, there is still much room for improvement in these treatment methods, particularly when it comes to preventing postoperative complications and optimizing surgical procedures. Nanomaterials, as a type of small molecule material, have shown great promise in treating bone tissue diseases, including ONFH. In fact, several nanocomposite materials have demonstrated specific effects in preventing ONFH, promoting bone tissue repair and growth, and optimizing surgical treatment. This article provides a comprehensive overview of current treatments for ONFH, including their advantages and limitations, and reviews the latest advances in nanomaterials for treating this condition. Additionally, this article explores the therapeutic mechanisms involved in using nanomaterials to treat ONFH and to identify new methods and ideas for improving outcomes for patients.

Single-cell RNA sequencing of peripheral blood mononuclear cells from pregnant women with Systemic lupus erythematosus.

Systemic lupus erythematosus (SLE), an autoimmune condition, presents pregnancy-related risks, impacting maternal and fetal health. The immune cell composition and gene expression profiles in pregnant SLE patients, as well as the molecular mechanisms of active SLE patients during pregnancy, remain unclear. In our study, we enrolled 12 patients: three active SLE individuals (SLE-AT group, SLEDAI > 12, non-pregnant women), three inactive SLE individuals (SLE-NP group, SLEDAI ranging 0 to 6, non-pregnant women), three pregnant women with active SLE (SLE-C group, SLEDAI > 12), and three pregnant women with inactive SLE (SLE-NC group, SLEDAI range 0 to 6 score). Transcriptome analysis of peripheral blood mononuclear cells (PBMCs) was conducted using the 10x Genomics technique. We observed upregulation of genes like CCDC15 and TRBV4-2 in T cells and CMPK2, IFIT1, and OAS2 in monocytes in the SLE-C group. Notably, gene sets related to Cell Cycle and IFN Response showed significant differences between the SLE-C and SLE-NC groups in naïve CD8 T cells. Our comparison of immune cell type ratios and transcriptional patterns between active and inactive SLE during pregnancy sheds light on the single-cell level changes in SLE status during pregnancy, offering insights for future SLE prediction and treatment strategies.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease. Furthermore, SLE women have an increased likelihood of encountering adverse pregnancy outcomes such as diabetes and hypertension. The etiology of SLE involves a multifaceted interplay of genetic, immune, endocrine, and environmental factors, which contributes to a breakdown in the immune system's tolerance to self-antigens. Recent studies have highlighted a strong correlation between the severity of renal involvement in lupus nephritis and B cell dysfunction in patients, as elucidated through single-cell transcriptomics. Additionally, comparative studies have revealed notable differences in the immune cell profile between pregnant women with lupus and healthy pregnant women. A key observation the marked reduction in the proportion of CD4+ T cells in pregnant women suffering from lupus. Despite these findings, the detailed transcriptomic alterations within high-resolution immune cell profiling during activate phase of SLE in pregnancy remain inadequately understood. In our study, we focused on comparing the transcriptomic expression patterns of peripheral blood immune cells between pregnant women with active SLE and those with stable SLE. Our data confirmed significant differences in IFN signaling and pregnancy-related factors in T cells, NK cells, B cells, and macrophages, contrasting the immune cells of pregnant women with active SLE against those with stable SLE. Additionally, the proportion of CD56+ NK cells was significantly increased in pregnant women with SLE. The correlation between the transcriptomic profiles of immune cells and the activity of SLE during pregnancy may provide potential strategies for predicting and treating SLE during pregnancy.

Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction.

Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. But PET suffers from a low signal-to-noise ratio, while MRI are time-consuming. To address time-consuming, an effective strategy involves reducing k-space data collection, albeit at the cost of lowering image quality. This study aims to leverage the inherent complementarity within PET-MRI data to enhance the image quality of PET-MRI.Approach. A novel PET-MRI joint reconstruction model, termed MC-Diffusion, is proposed in the Bayesian framework. The joint reconstruction problem is transformed into a joint regularization problem, where data fidelity terms of PET and MRI are expressed independently. The regular term, the derivative of the logarithm of the joint probability distribution of PET and MRI, employs a joint score-based diffusion model for learning. The diffusion model involves the forward diffusion process and the reverse diffusion process. The forward diffusion process adds noise to transform a complex joint data distribution into a known joint prior distribution for PET and MRI simultaneously, resembling a denoiser. The reverse diffusion process removes noise using a denoiser to revert the joint prior distribution to the original joint data distribution, effectively utilizing joint probability distribution to describe the correlations of PET and MRI for improved quality of joint reconstruction.Main results. Qualitative and quantitative improvements are observed with the MC-Diffusion model. Comparative analysis against LPLS and Joint ISAT-net on the ADNI dataset demonstrates superior performance by exploiting complementary information between PET and MRI. The MC-Diffusion model effectively enhances the quality of PET and MRI images.Significance. This study employs the MC-Diffusion model to enhance the quality of PET-MRI images by integrating the fundamental principles of PET and MRI modalities and leveraging their inherent complementarity. Furthermore, utilizing the diffusion model to learn the joint probability distribution of PET and MRI, thereby elucidating their latent correlation, facilitates a more profound comprehension of the priors obtained through deep learning, contrasting with black-box prior or artificially constructed structural similarities.

Myeloid ectopic viral integration site 2 accelerates the progression of Alzheimer's disease.

Amyloid plaques, a major pathological hallmark of Alzheimer's disease (AD), are caused by an imbalance between the amyloidogenic and non-amyloidogenic pathways of amyloid precursor protein (APP). BACE1 cleavage of APP is the rate-limiting step for amyloid-ß production and plaque formation in AD. Although the alteration of BACE1 expression in AD has been investigated, the underlying mechanisms remain unknown. In this study, we determined MEIS2 was notably elevated in AD models and AD patients. Alterations in the expression of MEIS2 can modulate the levels of BACE1. MEIS2 downregulation improved the learning and memory retention of AD mice and decreased the number of amyloid plaques. MEIS2 binds to the BACE1 promoter, positively regulates BACE1 expression, and accelerates APP amyloid degradation in vitro. Therefore, our findings suggest that MEIS2 might be a critical transcription factor in AD, since it regulates BACE1 expression and accelerates BACE1-mediated APP amyloidogenic cleavage. MEIS2 is a promising early intervention target for AD treatment.

Intermittent pulses of methylprednisolone with low-dose prednisone attenuate lupus symptoms in B6.MRL-Faslpr/J mice with fewer glucocorticoid side effects.

Glucocorticoids (GCs) are potent anti-inflammatory and immunosuppressant medications and remain the cornerstone of systemic lupus erythematosus (SLE) therapy. However, ongoing exposure to GCs has the potential to elicit multiple adverse effects. Considering the irreplaceability of GCs in SLE therapy, it is important to explore the optimal regimen of GCs. Here, we compared the long-term efficacy and safety of pulsed and oral GC therapy in a lupus-prone mouse model. Mice were grouped using a randomized block design. We monitored survival rates, proteinuria, serum autoantibodies, and complement 3 (C3) levels up to 28 weeks of age, and assessed renal damage, bone quality, lipid deposition in the liver and marrow, glucose metabolic parameters, and levels of hormones of the hypothalamic-pituitary-adrenal (HPA) axis. Finally, we explored the mechanisms underlying the superior efficacy of the pulse regimen over oral prednisone regimen. We found that both GC regimens alleviated the poor survival rate, proteinuria, and glomerulonephritis, while also reducing serum autoantibodies and increasing the level of C3. The pulsed GC regimen showed less resistance to insulin, less suppression of the HPA axis, less bone loss, and less bone marrow fat deposition than the oral GC regimen. Additionally, GC-induced leucine zipper (GILZ) was significantly overexpressed in the GC pulse group. These results suggest that the GC pulse regimen ameliorated symptoms in lupus-prone mice, with fewer side effects, which may be related to GILZ overexpression. Our findings offer a potentially promising GC treatment option for SLE.

Olanzapine suppresses mPFC activity-norepinephrine releasing to alleviate CLOCK-enhanced cancer stemness under chronic stress.

BACKGROUND: Olanzapine (OLZ) reverses chronic stress-induced anxiety. Chronic stress promotes cancer development via abnormal neuro-endocrine activation. However, how intervention of brain-body interaction reverses chronic stress-induced tumorigenesis remains elusive. METHODS: KrasLSL-G12D/WT lung cancer model and LLC1 syngeneic tumor model were used to study the effect of OLZ on cancer stemness and anxiety-like behaviors. Cancer stemness was evaluated by qPCR, western-blotting, immunohistology staining and flow-cytometry analysis of stemness markers, and cancer stem-like function was assessed by serial dilution tumorigenesis in mice and extreme limiting dilution analysis in primary tumor cells. Anxiety-like behaviors in mice were detected by elevated plus maze and open field test. Depression-like behaviors in mice were detected by tail suspension test. Anxiety and depression states in human were assessed by Hospital Anxiety and Depression Scale (HADS). Chemo-sensitivity of lung cancer was assessed by in vivo syngeneic tumor model and in vitro CCK-8 assay in lung cancer cell lines. RESULTS: In this study, we found that OLZ reversed chronic stress-enhanced lung tumorigenesis in both KrasLSL-G12D/WT lung cancer model and LLC1 syngeneic tumor model. OLZ relieved anxiety and depression-like behaviors by suppressing neuro-activity in the mPFC and reducing norepinephrine (NE) releasing under chronic stress. NE activated ADRB2-cAMP-PKA-CREB pathway to promote CLOCK transcription, leading to cancer stem-like traits. As such, CLOCK-deficiency or OLZ reverses NE/chronic stress-induced gemcitabine (GEM) resistance in lung cancer. Of note, tumoral CLOCK expression is positively associated with stress status, serum NE level and poor prognosis in lung cancer patients. CONCLUSION: We identify a new mechanism by which OLZ ameliorates chronic stress-enhanced tumorigenesis and chemoresistance. OLZ suppresses mPFC-NE-CLOCK axis to reverse chronic stress-induced anxiety-like behaviors and lung cancer stemness. Decreased NE-releasing prevents activation of ADRB2-cAMP-PKA-CREB pathway to inhibit CLOCK transcription, thus reversing lung cancer stem-like traits and chemoresistance under chronic stress.

A pan-TE map highlights transposable elements underlying domestication and agronomic traits in Asian rice.

Transposable elements (TEs) are ubiquitous genomic components and hard to study due to being highly repetitive. Here we assembled 232 chromosome-level genomes based on long-read sequencing data. Coupling the 232 genomes with 15 existing assemblies, we developed a pan-TE map comprising both cultivated and wild Asian rice. We detected 177 084 high-quality TE variations and inferred their derived state using outgroups. We found TEs were one source of phenotypic variation during rice domestication and differentiation. We identified 1246 genes whose expression variation was associated with TEs but not single-nucleotide polymorphisms (SNPs), such as OsRbohB, and validated OsRbohB's relative expression activity using a dual-Luciferase (LUC) reporter assays system. Our pan-TE map allowed us to detect multiple novel loci associated with agronomic traits. Collectively, our findings highlight the contributions of TEs to domestication, differentiation and agronomic traits in rice, and there is massive potential for gene cloning and molecular breeding by the high-quality Asian pan-TE map we generated.

Climate factors determine large-scale spatial patterns of stomatal index in Chinese herbaceous and woody dicotyledonous plants.

The stomatal index (SI, %) and its response to climate factors (temperature and precipitation) can help our understanding of terrestrial carbon and water cycling and plant adaptation in the ecosystem, however, consensus has not yet been reached in this regard. In this study, we compiled an extensive dataset from the Chinese flora to investigate the response of SI to environmental change, including 891 herbaceous and woody species from 188 published papers. The results showed that mean values of the adaxial SI and abaxial SI for all species were 14.06 and 19.22, respectively, and the ratio of adaxial to abaxial SI was 0.84. For the adaxial SI, abaxial SI, and the ratio of adaxial to abaxial SI, the range of these values varied between 0.05-43.67, 0.01-48.17, and 0.03-4.31, respectively. Compared with woody plants, herbaceous plants showed higher values in both adaxial and abaxial SI. In terms of the impact of climate factors, the abaxial SI of herbaceous plants changed slower than the adaxial SI, while woody plants showed the opposite trend. Threshold effects of increased temperature and precipitation on SI were observed, indicating that SI responded differently to changes in climate factors at different levels. Climate factors play a crucial role in driving the adaxial SI than abaxial SI. Our findings highlight the significant challenges posed by divergent responses of SI in forecasting future water and carbon cycles associated with climatic and environmental change.

The link between gut microbiome and Alzheimer's disease: From the perspective of new revised criteria for diagnosis and staging of Alzheimer's disease.

Over the past decades, accumulating evidence suggests that the gut microbiome exerts a key role in Alzheimer's disease (AD). The Alzheimer's Association Workgroup is updating the diagnostic criteria for AD, which changed the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." Previously, most of studies focus on the correlation between the gut microbiome and amyloid beta deposition ("A"), the initial AD pathological feature triggering the "downstream" tauopathy and neurodegeneration. However, limited research investigated the interactions between the gut microbiome and other AD pathogenesis ("TNIVS"). In this review, we summarize current findings of the gut microbial characteristics in the whole spectrum of AD. Then, we describe the association of the gut microbiome with updated biomarker categories of AD pathogenesis. In addition, we outline the gut microbiome-related therapeutic strategies for AD. Finally, we discuss current key issues of the gut microbiome research in the AD field and future research directions. HIGHLIGHTS: The new revised criteria for Alzheimer's disease (AD) proposed by the Alzheimer's Association Workgroup have updated the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." The associations of the gut microbiome with updated biomarker categories of AD pathogenesis are described. Current findings of the gut microbial characteristics in the whole spectrum of AD are summarized. Therapeutic strategies for AD based on the gut microbiome are proposed.

Population-level exploration of alternative splicing and its unique role in controlling agronomic traits of rice.

Alternative splicing (AS) plays crucial roles in regulating various biological processes in plants. However, the genetic mechanisms underlying AS and its role in controlling important agronomic traits in rice (Oryza sativa) remain poorly understood. In this study, we explored AS in rice leaves and panicles using the rice minicore collection. Our analysis revealed a high level of transcript isoform diversity, with approximately one fifth of potential isoforms acting as major transcripts in both tissues. Regarding the genetic mechanism of AS, we found that the splicing of 833 genes in the leaf and 1,230 genes in the panicle was affected by cis-genetic variation. Twenty-one percent of these AS events could only be explained by large structural variations. Approximately 77.5% of genes with significant splicing quantitative trait loci (sGenes) exhibited tissue-specific regulation, and AS can cause 26.9% (leaf) and 23.6% (panicle) of sGenes to have altered, lost or gained functional domains. Additionally, through splicing-phenotype association analysis, we identified phosphate-starvation induced RING-type E3 ligase (OsPIE1; LOC_Os01g72480), whose splicing ratio was significantly associated with plant height. In summary, this study provides an understanding of AS in rice and its contribution to the regulation of important agronomic traits.

Postweaning sodium citrate exposure induces long-lasting and sex-dependent effects on social behaviours in mice.

BACKGROUND: Postweaning is a pivotal period for brain development and individual growth. As an important chemical used in medicines, foods and beverages, sodium citrate (SC) is commonly available. Although some effects of SC exposure on individual physiology have been demonstrated, the potential long-lasting effects of postweaning dietary SC exposure on social behaviours are still elusive. METHODS: Both postweaning male and female C57BL/6 mice were exposed to SC through drinking water for a total of 3 weeks. A series of behavioural tests, including social dominance test (SDT), social interaction test (SIT), bedding preference test (BPT) and sexual preference test (SPT), were performed in adolescence and adulthood. After these tests, serum oxytocin (OT) levels and gut microbiota were detected. RESULTS: The behavioural results revealed that postweaning SC exposure decreased the social dominance of male mice in adulthood and female mice in both adolescence and adulthood. SC exposure also reduced the sexual preference rates of both males and females, while it had no effect on social interaction behaviour. ELISA results indicated that SC exposure decreased the serum OT levels of females but not males. 16S rRNA sequencing analysis revealed a significant difference in ß-diversity after SC exposure in both males and females. The correlation coefficient indicated the correlation between social behaviours, OT levels and dominant genera of gut microbiota. CONCLUSION: Our findings suggest that postweaning SC exposure may have enduring and sex-dependent effects on social behaviours, which may be correlated with altered serum OT levels and gut microbiota composition.

Auditory Effects of Acoustic Noise From 3-T Brain MRI in Neonates With Hearing Protection.

BACKGROUND: Neonates with immature auditory function (eg, weak/absent middle ear muscle reflex) could conceivably be vulnerable to noise-induced hearing loss; however, it is unclear if neonates show evidence of hearing loss following MRI acoustic noise exposure. PURPOSE: To explore the auditory effects of MRI acoustic noise in neonates. STUDY TYPE: Prospective. SUBJECTS: Two independent cohorts of neonates (N = 19 and N = 18; mean gestational-age, 38.75 ± 2.18 and 39.01 ± 1.83 weeks). FIELD STRENGTH/SEQUENCE: T1-weighted three-dimensional gradient-echo sequence, T2-weighted fast spin-echo sequence, single-shot echo-planar imaging-based diffusion-tensor imaging, single-shot echo-planar imaging-based diffusion-kurtosis imaging and T2-weighted fluid-attenuated inversion recovery sequence at 3.0 T. ASSESSMENT: All neonates wore ear protection during scan protocols lasted ~40 minutes. Equivalent sound pressure levels (SPLs) were measured for both cohorts. In cohort1, left- and right-ear auditory brainstem response (ABR) was measured before (baseline) and after (follow-up) MRI, included assessment of ABR threshold, wave I, III and V latencies and interpeak interval to determine the functional status of auditory nerve and brainstem. In cohort2, baseline and follow-up left- and right-ear distortion product otoacoustic emission (DPOAE) amplitudes were assessed at 1.2 to 7.0 kHz to determine cochlear function. STATISTICAL TEST: Wilcoxon signed-rank or paired t-tests with Bonferroni's correction were used to compare the differences between baseline and follow-up ABR and DPOAE measures. RESULTS: Equivalent SPLs ranged from 103.5 to 113.6 dBA. No significant differences between baseline and follow-up were detected in left- or right-ear ABR measures (P > 0.999, Bonferroni corrected) in cohort1, or in DPOAE levels at 1.2 to 7.0 kHz in cohort2 (all P > 0.999 Bonferroni corrected except for left-ear levels at 3.5 and 7.0 kHz with corrected P = 0.138 and P = 0.533). DATA CONCLUSION: A single 40-minute 3-T MRI with equivalent SPLs of 103.5-113.6 dBA did not result in significant transient disruption of auditory function, as measured by ABR and DPOAE, in neonates with adequate hearing protection. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 5.

Habitat differentiation and environmental adaptability contribute to leaf size variations globally in C3 and C4 grasses.

The grass family (Poaceae) dominates ~43 % of Earth's land area and contributes 33 % of terrestrial primary productivity that is critical to naturally regulating atmosphere CO2 concentration and global climate change. Currently grasses comprise ~11,780 species and ~50 % of them (~6000 species) utilize C4 photosynthetic pathway. Generally, grass species have smaller leaves under colder and drier environments, but it is unclear whether the primary drivers of leaf size differ between C3 and C4 grasses on a global scale. Here, we analyzed 34 environmental variables, such as latitude, elevation, mean annual temperature, mean annual precipitation, and solar radiation etc., through a comparatively comprehensive database of ~3.0 million occurrence records from 1380 C3 and 978 C4 grass species (2358 species in total). Results from this study confirm that C4 grasses have occupied habitats with lower latitudes and elevations, characterized by warmer, sunnier, drier and less fertile environmental conditions. Grass leaf size correlates positively with mean annual temperature and precipitation as expected. Our results also demonstrate that the mean temperature of the wettest quarter of the year is the primary control for C3 leaf size, whereas C4 leaf size is negatively correlated with the difference between summer and winter temperatures. For C4 grasses, phylogeny exerts a significant effect on leaf size but is less important than environmental factors. Our findings highlight the importance of evolutionarily contrasting variations in leaf size between C3 and C4 grasses for shaping their geographical distribution and habitat suitability at the global scale.

Plant height as an indicator for alpine carbon sequestration and ecosystem response to warming.

Growing evidence indicates that plant community structure and traits have changed under climate warming, especially in cold or high-elevation regions. However, the impact of these warming-induced changes on ecosystem carbon sequestration remains unclear. Using a warming experiment on the high-elevation Qinghai-Tibetan Plateau, we found that warming not only increased plant species height but also altered species composition, collectively resulting in a taller plant community associated with increased net ecosystem productivity (NEP). Along a 1,500 km transect on the Plateau, taller plant community promoted NEP and soil carbon through associated chlorophyll content and other photosynthetic traits at the community level. Overall, plant community height as a dominant trait is associated with species composition and regulates ecosystem C sequestration in the high-elevation biome. This trait-based association provides new insights into predicting the direction, magnitude and sensitivity of ecosystem C fluxes in response to climate warming.

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

Objective.In Magnetic Resonance (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 Auto-Calibration Signals (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 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.