Effective dose of intranasal remimazolam for preoperative sedation in preschool children: a dose-finding study using Dixon's up-and-down method.

Background: Most preschool children are distressed during anesthesia induction. While current pharmacological methods are useful, there is a need for further optimization to an "ideal" standard. Remimazolam is an ultra-short-acting benzodiazepine, and intranasal remimazolam for pre-induction sedation may be promising. Methods: This study included 32 preschool children who underwent short and minor surgery between October 2022 and January 2023. After pretreatment with lidocaine, remimazolam was administered to both nostrils using a mucosal atomizer device. The University of Michigan Sedation Score (UMSS) was assessed for sedation 6, 9, 12, 15, and 20 min after intranasal atomization. We used Dixon's up-and-down method, and probit and isotonic regressions to determine the 50% effective dose (ED50) and 95% effective dose (ED95) of intranasal remimazolam for pre-induction sedation. Results: Twenty-nine pediatric patients were included in the final analysis. The ED50 and ED95 of intranasal remimazolam for successful pre-induction sedation, when processed via probit analysis, were 0.65 (95% confidence interval [CI], 0.59-0.71) and 0.78 mg/kg (95% CI, 0.72-1.07), respectively. In contrast, when processed by isotonic regression, they were 0.65 (95% CI: 0.58-0.72 mg/kg) and 0.78 mg/kg (95% CI: 0.69-1.08 mg/kg), respectively. At 6 min after intranasal remimazolam treatment, 81.2% (13/16) of "positive" participants were successfully sedated with a UMSS ≧ 1. All the "positive" participants were successfully sedated within 9 min. Conclusion: Intranasal remimazolam is feasible for preschool children with a short onset time. For successful pre-induction sedation, the ED50 and ED95 of intranasal remimazolam were 0.65 and 0.78 mg/kg, respectively.

Soil properties constrain forest understory plant distributions along an elevation gradient.

Projections of spatial biodiversity dynamics under climate warming are often based on models including only climate variables, and when non-climatic factors (e.g. soil) are included, data are often at much coarser spatial resolutions than those experienced by plants. Field studies along elevation gradients permit the gathering of detailed soil data, while still covering a wide climatic gradient. Here, an intensive field survey of four spring forest herbs along an elevation gradient showed that soil properties had substantial impacts on the occurrence/abundance of all species, and that soil effects were more pronounced at higher elevations. For Trillium erectum and Claytonia caroliniana, very infrequent occurrences at high elevation were strongly associated with rare microsites with high pH or nutrients. In a seven-year transplant experiment with T. erectum, we found that individuals grew to much smaller sizes at high than low elevation, suggesting that environmental factors rather than dispersal limitation constrain the species' upper range limit, despite substantial warming in recent decades. Our study demonstrates that soil factors interact strongly with climate to determine plant range limits along climatic gradients. Unsuitable soils for plants at high elevations or latitudes may represent an important constraint on future plant migration and biodiversity change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Non-traumatic osteonecrosis of the femoral head induced by steroid and alcohol exposure is associated with intestinal flora alterations and metabolomic profiles.

OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives. METHODS: Utilizing fecal samples from 68 NONFH patients (32 steroid-induced, 36 alcohol-induced), high-throughput 16 S rDNA sequencing and liquid chromatography with tandem mass spectrometry (LC-MS/MS) metabolomics analyses were conducted. Univariate and multivariate analyses were applied to the omics data, employing linear discriminant analysis effect size to identify potential biomarkers. Additionally, functional annotation of differential metabolites and associated pathways was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Subsequently, Spearman correlation analysis was employed to assess the potential correlations between differential gut microbiota and metabolites. RESULTS: High-throughput 16 S rDNA sequencing revealed significant gut microbial differences. At the genus level, the alcohol group had higher Lactobacillus and Roseburia, while the steroid group had more Megasphaera and Akkermansia. LC-MS/MS metabolomic analysis indicates significant differences in fecal metabolites between steroid- and alcohol-induced ONFH patients. Alcohol-induced ONFH (AONFH) showed elevated levels of L-Lysine and Oxoglutaric acid, while steroid-induced ONFH(SONFH) had increased Gluconic acid and Phosphoric acid. KEGG annotation revealed 10 pathways with metabolite differences between AONFH and SONFH patients. Correlation analysis revealed the association between differential gut flora and differential metabolites. CONCLUSIONS: Our results suggest that hormones and alcohol can induce changes in the gut microbiota, leading to alterations in fecal metabolites. These changes, driven by different pathways, contribute to the progression of the disease. The study opens new research directions for understanding the pathogenic mechanisms of hormone- or alcohol-induced NONFH, suggesting that differentiated preventive and therapeutic approaches may be needed for NONFH caused by different triggers.

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs-A Preliminary Study.

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (DLIR) algorithm in different image sets derived from carotid dual-energy computed tomography angiography (DECTA) for evaluating cervical intervertebral discs (IVDs) and compare them with those reconstructed using adaptive statistical iterative reconstruction-Veo (ASiR-V). Forty-two patients who underwent carotid DECTA were included in this retrospective analysis. Three types of image sets (70 keV, water-iodine, and water-calcium) were reconstructed using 50% ASiR-V and DLIR at medium and high levels (DLIR-M and DLIR-H). The diagnostic acceptability and conspicuity of IVDs were assessed using a 5-point scale. Hounsfield Units (HU) and water concentration (WC) values of the IVDs; standard deviation (SD); and coefficient of variation (CV) were calculated. Measurement parameters of the 50% ASIR-V, DLIR-M, and DLIR-H groups were compared. The DLIR-H group showed higher scores for diagnostic acceptability and conspicuity, as well as lower SD values for HU and WC than the ASiR-V and DLIR-M groups for the 70 keV and water-iodine image sets (all p < .001). However, there was no significant difference in scores and SD among the three groups for the water-calcium image set (all p > .005). The water-calcium image set showed better diagnostic accuracy for evaluating IVDs compared to the other image sets. The inter-rater agreement using ASiR-V, DLIR-M, and DLIR-H was good for the 70 keV image set, excellent for the water-iodine and water-calcium image sets. DLIR improved the visualization of IVDs in the 70 keV and water-iodine image sets. However, its improvement on color-coded water-calcium image set was limited.

UPLC-ESI-MS/MS-Based Analysis of Various Edible Rosa Fruits Concerning Secondary Metabolites and Evaluation of Their Antioxidant Activities.

The genus Rosa is globally popular with well-established applications since it has a high edible and medicinal value. However, relatively limited research has been conducted on the composition and quality of wild Rosa fruits. The present study aimed to compare the properties and chemical components of five wild edible Rosa fruits, Rosa roxburghii, Rosa sterilis, Rosa laevigata, Rosa davurica, and Rosa sericea. The UPLC-ESI-MS/MS approach identified the key metabolites among the five Rosa fruits as flavonoids, phenolic acids, and organic acids. The main differential metabolites among the five fruits are flavonoids (22.29-45.13%), phenolic acids (17-22.27%), and terpenoids (7.7-24%), respectively. In total, 125 compounds served as potential markers for the five Rosa species. Differential metabolic pathways of five Rosa fruits were analyzed using the KEGG approach. Rosa laevigata fruits showed the highest total polysaccharide (TPS) content of 64.48 g/100 g. All the five Rosa extracts effectively decreased the levels of malondialdehyde while increasing the activities of superoxide dismutase and glutathione peroxidase in the H2O2-induced HaCaT cell model, demonstrating high potential for antioxidant development. Our findings suggest that the five studied Rosa fruits exhibit biological activity and edible value worth further exploration.

Pilot validation of on-field STR typing and human identity testing by MinION nanopore sequencing.

Nanopore sequencing technology has broad application prospects in forensic medicine due to its small size, portability, fast speed, real-time result analysis capabilities, single-molecule sequencing abilities, and simple operation. Here, we demonstrate for the first time that nanopore sequencing platforms can be used to identify individuals in the field. Through scientific and reasonable design, a nanopore MinION MK1B device and other auxiliary devices are integrated into a portable detection box conducive to individual identification at the accident site. Individual identification of 12 samples could be completed within approximately 24 h by jointly detecting 23 short tandem repeat (STR) loci. Through double-blinded experiments, the genotypes of 49 samples were successfully determined, and the accuracy of the STR genotyping was verified by the gold standard. Specifically, the typing success rate for 1150 genotypes was 95.3%, and the accuracy rate was 86.87%. Although this study focused primarily on demonstrating the feasibility of full-process testing, it can be optimistically predicted that further improvements in bioinformatics workflows and nanopore sequencing technology will help enhance the feasibility of Oxford Nanopore Technologies equipment for real-time individual identification at accident sites.

Loss of macrophage TSC1 exacerbates sterile inflammatory liver injury through inhibiting the AKT/MST1/NRF2 signaling pathway.

Tuberous sclerosis complex 1 (TSC1) plays important roles in regulating innate immunity. However, the precise role of TSC1 in macrophages in the regulation of oxidative stress response and hepatic inflammation in liver ischemia/reperfusion injury (I/R) remains unknown. In a mouse model of liver I/R injury, deletion of myeloid-specific TSC1 inhibited AKT and MST1 phosphorylation, and decreased NRF2 accumulation, whereas activated TLR4/NF-κB pathway, leading to increased hepatic inflammation. Adoptive transfer of AKT- or MST1-overexpressing macrophages, or Keap1 disruption in myeloid-specific TSC1-knockout mice promoted NRF2 activation but reduced TLR4 activity and mitigated I/R-induced liver inflammation. Mechanistically, TSC1 in macrophages promoted AKT and MST1 phosphorylation, and protected NRF2 from Keap1-mediated ubiquitination. Furthermore, overexpression AKT or MST1 in TSC1-knockout macrophages upregulated NRF2 expression, downregulated TLR4/NF-κB, resulting in reduced inflammatory factors, ROS and inflammatory cytokine-mediated hepatocyte apoptosis. Strikingly, TSC1 induction in NRF2-deficient macrophages failed to reverse the TLR4/NF-κB activity and production of pro-inflammatory factors. Conclusions: Macrophage TSC1 promoted the activation of the AKT/MST1 signaling pathway, increased NRF2 levels via reducing Keap1-mediated ubiquitination, and modulated oxidative stress-driven inflammatory responses in liver I/R injury. Our findings underscore the critical role of macrophage TSC1 as a novel regulator of innate immunity and imply the therapeutic potential for the treatment of sterile liver inflammation in transplant recipients. Schematic illustration of macrophage TSC1-mediated AKT/MST1/NRF2 signaling pathway in I/R-triggered liver inflammation. Macrophage TSC1 can be activated in I/R-stressed livers. TSC1 activation promotes phosphorylation of AKT and MST1, which in turn increases NRF2 expression and inhibits ROS production and TLR4/NF-κB activation, resulting in reduced hepatocellular apoptosis in I/R-triggered liver injury.

A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging.

BACKGROUND: Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM. METHODS: Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing uncompressed segments of CSM patients. CSM patients and volunteers were matched by age and spinal location. The differences in dMRI parameters between groups were assessed by the paired t-test, the multicollinearity of the dMRI parameters was evaluated by the variance inflation factor (VIF), and the value of dMRI parameters in distinguishing controls from CSM patients was determined by logistic regression. The univariate t-test was used to analyse differences between CSM patients and volunteers in adjacent uncompressed areas. RESULTS: In total, 56 CSM patients and 56 control volunteers were included. Paired t-tests revealed significant differences in nine dMRI parameters between groups. Multicollinearity calculated through VIF and combined with logistic regression showed that the orientation division index (ODI) was significantly positively correlated (r = 2.12, p = 0.035), and the anisotropic water fraction (AWF) was significantly negatively correlated (r = -0.98, p = 0.015). The fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (ISOVF), ODI, and AWF were significantly different in the upper and lower uncompressed areas at all ages. CONCLUSION: dMRI can noninvasively identify early CSM patients and potentially identify the extent of CSM lesions involving the cervical spinal cord. CRITICAL RELEVANCE STATEMENT: Diffusion MRI (dMRI) can identify early cervical spondylotic myelopathy (CSM) and has the potential to help determine the extent of CSM involvement. The application of dMRI can help screen for early CSM and develop clinical surgical and rehabilitation treatment plans. KEY POINTS: • Diffusion MRI can differentiate between normal and early-stage cervical spondylotic myelopathy patients. • Diffusion MRI has the ability to identify the extent of spinal cord involvement in cervical spondylotic myelopathy. • Diffusion MRI enables the early screening of cervical spondylotic myelopathy and helps guide clinical treatment.

Association between genetic variants of transmembrane transporters and susceptibility to anthracycline-induced cardiotoxicity: Current understanding and existing evidence.

Anthracyclines remain the cornerstone of numerous chemotherapeutic protocols, with beneficial effects against haematological malignancies and solid tumours. Unfortunately, the clinical usefulness of anthracyclines is compromised by the development of cardiotoxic side effects, leading to dose limitations or treatment discontinuation. There is no absolute linear correlation between the incidence of cardiotoxicity and the threshold dose, suggesting that genetic factors may modify the association between anthracyclines and cardiotoxicity risk. And the majority of single nucleotide polymorphisms (SNPs) associated with anthracycline pharmacogenomics were identified in the ATP-binding cassette (ABC) and solute carrier (SLC) transporters, generating increasing interest in the pharmacogenetic implications of their genetic variations for anthracycline-induced cardiotoxicity (AIC). This review focuses on the influence of SLC and ABC polymorphisms on AIC and highlights the prospects and clinical significance of pharmacogenetics for individualised preventive approaches.

Prevalence, contemporary trends and associated factors of potentially inappropriate prescription of edoxaban in real-world clinical practice: A subanalysis of the SUNSHINE registry.

AIM: As the direct oral anticoagulant most recently approved in China, data pertaining to clinical edoxaban use are still scarce. This study investigated the prevalence of and contemporary trends in edoxaban prescription among Chinese patients as well as factors associated with its inappropriate use in a multicentre registry of patients treated in real-world clinical practice. METHODS: This real-world, prospective, multicentre and non-interventional study included 1005 inpatients treated with edoxaban. According to National Medical Products Administration and European Heart Rhythm Association guidelines, edoxaban therapy was determined to be appropriate or inappropriate in each case. RESULTS: The median patient age was 70.0 years (interquartile range 61.0-78.0 years) and 46.3% were women. Overall, 456 (45.4%) patients received inappropriate edoxaban therapy, and common issues included an inappropriately low dosage (183, 18.2%) or wrong drug selection (109, 10.8%), high dosage (73, 7.3%), unreasonable off-label use (49, 4.9%), contraindicated medication combinations (27, 2.7%) and incorrect administration timing (16, 1.6%). Several factors, such as age ≥75 years (odds ratio [OR] = 1.921, 95% confidence interval [CI] 1.355-2.723, P < 0.001), weight >60 kg (OR = 2.657, 95%CI 1.970-3.583, P < 0.001), severe renal insufficiency (OR = 1.988, 95% CI 1.043-3.790, P = 0.037), current anaemia (OR = 1.556, 95% CI 1.151-2.102, P = 0.004) and history of bleeding (OR = 2.931, 95% CI 1.605-5.351, P < 0.001) were associated with an increased risk of inappropriate edoxaban therapy, whereas factors associated with cardiovascular specialties, such as admission to a cardiovascular department (OR = 0.637, 95% CI 0.464-0.873, P = 0.005), dronedarone use (OR = 0.065, 95% CI 0.026-0.165, P < 0.001) and amiodarone use (OR = 0.365, 95% CI 0.209-0.637, P < 0.001) decreased this risk. CONCLUSION: In this real-world study, 45.4% of patients received an inappropriate treatment with edoxaban. Multiple clinical characteristics can help identify patients who should receive edoxaban. Further development and implantation of educational activities and management strategies are needed to ensure the correct use of edoxaban.

Resting-state cortico-limbic functional connectivity pattern in panic disorder: Relationships with emotion regulation strategy use and symptom severity.

Cognitive reappraisal is an effective emotion regulation strategy involving prefrontal cortex (PFC) control of the amygdala. Its aberrant functioning is closely associated with panic disorder (PD). However, the resting-state functional connectivity (rsFC) between the PFC, implicated in cognitive reappraisal, and the amygdala in PD has not been studied. Thus, this study aims to investigate the rsFC patterns and their association with cognitive reappraisal and PD. This study involved 51 participants, including 26 untreated patients with PD and 25 healthy controls (HC). We evaluated the habit of cognitive reappraisal assessment and the severity of PD using neuropsychological and clinical measures. Resting-state fMRI was utilized to evaluate the rsFC pattern between the PFC, engaged in cognitive reappraisal, and the amygdala. Mediation analysis was performed to explore the role of this rsFC in the relationship between cognitive reappraisal and PD severity. PD patients showed reduced rsFC between the PFC and the amygdala compared to HC. This weakened rsFC was associated with the severity of PD symptoms. Moreover, cognitive reappraisal was negatively correlated with PD severity, and mediation analysis indicated that the rsFC of the PFC-amygdala played a mediating role in this association. Abnormal PFC-amygdala rsFC may play a pivotal role in PD development and/or manifestation and mediate the association between cognitive reappraisal and PD severity, potentially serving as a clinical indicator for monitoring and intervention.

A Smartphone Application-Based Remote Rehabilitation System for Post-Total Knee Arthroplasty Rehabilitation: A Randomized Controlled Trial.

BACKGROUND: Remote rehabilitation after total knee arthroplasty has gradually gained popularity in recent years. This study aimed to determine whether smartphone application-based remote rehabilitation could outperform home-based rehabilitation and outpatient guidance in terms of 12-week outcomes following primary unilateral total knee arthroplasty. METHODS: Patients who underwent primary unilateral total knee arthroplasty were recruited and randomly divided into a telerehabilitation group and a control group. A total of 100 patients were examined, with 50 each assigned to the telerehabilitation and control groups. In the telerehabilitation group, a telerehabilitation application was installed on the smartphones of the participants to allow postdischarge guidance. The primary outcomes were knee range of motion (ROM) at 12 weeks postoperatively. Secondary outcomes included the Western Ontario and McMaster Universities Osteoarthritis Index, Knee Society Score, The Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), Five Times Sit-to-Stand Test (5xSST), Single-Leg Stance Test (SLST), satisfaction, rehabilitation costs, complication rate, and 90-day readmission rate. All outcomes were collected at 2, 6, and 12 weeks after surgery. RESULTS: At 12 weeks postoperatively, the telerehabilitation patients significantly outperformed the controls in terms of knee ROM (124 ± 8.7 versus 119 ± 5.5 P = .01), SF-36 (physiological function) (61.5 ± 20.3 versus 45.5 ± 18.1 P = .000), SF-36 (role-physical) (49.3 ± 41.5 versus 27.7 ± 28.9 P = .012), SLST (13.0 ± 9.1 versus 9.1 ± 5.9 P = .026), and 5xSST (17.7 ± 4.3 versus 19.4 ± 3.5 P = .043). No significant differences were found between groups in the Western Ontario and McMaster Universities Osteoarthritis Index score, Knee Society Score, rehabilitation costs, 90-day readmission rate, or incidence of adverse events. CONCLUSION: Our study showed that smartphone app-based remote rehabilitation worked better than home-based rehabilitation with outpatient guidance in terms of short-term results in ROM, SLST, and 5xSST.

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning was used to facilitate the preliminary identification of SLAP lesions and compared with radiologists of different seniority. METHODS: MRA data from 636 patients were retrospectively collected, and all patients were classified as having/not having SLAP lesions according to shoulder arthroscopy. The SLAP-Net model was built and tested on 514 patients (dataset 1) and independently tested on data from two other MRI devices (122 patients, dataset 2). Manual diagnosis was performed by three radiologists with different seniority levels and compared with SLAP-Net outputs. Model performance was evaluated by the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), etc. McNemar's test was used to compare performance among models and between radiologists' models. The intraclass correlation coefficient (ICC) was used to assess the radiologists' reliability. p < 0.05 was considered statistically significant. RESULTS: SLAP-Net had AUC = 0.98 and accuracy = 0.96 for classification in dataset 1 and AUC = 0.92 and accuracy = 0.85 in dataset 2. In dataset 1, SLAP-Net had diagnostic performance similar to that of senior radiologists (p = 0.055) but higher than that of early- and mid-career radiologists (p = 0.025 and 0.011). In dataset 2, SLAP-Net had similar diagnostic performance to radiologists of all three seniority levels (p = 0.468, 0.289, and 0.495, respectively). CONCLUSIONS: Deep learning can be used to identify SLAP lesions upon initial MR arthrography examination. SLAP-Net performs comparably to senior radiologists.

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy.

BACKGROUND: Diffusion magnetic resonsance imaging (dMRI) can potentially predict the postoperative outcome of cervical spondylotic myelopathy (CSM). PURPOSE: To explore preoperative dMRI parameters to predict the postoperative outcome of CSM through multifactor correlation analysis. STUDY TYPE: Prospective. POPULATION: Post-surgery CSM patients; 102 total, 73 male (52.42 ± 10.60 years old) and 29 female (52.0 ± 11.45 years old). FIELD STRENGTH/SEQUENCE: 3.0 T/Turbo spin echo T1/T2-weighted, T2*-weighted multiecho gradient echo and dMRI. ASSESSMENT: Spinal cord function was evaluated using modified Japanese Orthopedic Association (mJOA) scoring at different time points: preoperative and 3, 6, and 12 months postoperative. Single-factor correlation and t test analyses were conducted based on fractional anisotropy (FA), mean diffusivity, intracellular volume fraction, isotropic volume fraction, orientation division index, increased signal intensity, compression ratio, age, sex, symptom duration and operation method, and multicollinearity was calculated. The linear quantile mixed model (LQMM) and the linear mixed-effects regression model (LMER) were used for multifactor correlation analysis using the combinations of the above variables. STATISTICAL TESTS: Distance correlation, Pearson's correlation, multiscale graph correlation and t tests were used for the single-factor correlation analyses. The variance inflation factor (VIF) was used to calculate multicollinearity. LQMM and LMER were used for multifactor correlation analyses. P < 0.05 was considered statistically significant. RESULTS: The single-factor correlation between all variables and the postoperative mJOA score was weak (all r < 0.3). The linear relationship was stronger than the nonlinear relationship, and there was no significant multicollinearity (VIF = 1.10-1.94). FA values in the LQMM and LMER models had a significant positive correlation with the mJOA score (r = 5.27-6.04), which was stronger than the other variables. DATA CONCLUSION: The FA value based on dMRI significantly positively correlated with CSM patient postoperative outcomes, helping to predict the surgical outcome and formulate a treatment plan before surgery. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Soil properties constrain predicted poleward migration of plants under climate change.

Many plant species are predicted to migrate poleward in response to climate change. Species distribution models (SDMs) have been widely used to quantify future suitable habitats, but they often neglect soil properties, despite the importance of soil for plant fitness. As soil properties often change along latitudinal gradients, higher-latitude soils might be more or less suitable than average conditions within the current ranges of species, thereby accelerating or slowing potential poleward migration. In this study, we built three SDMs - one with only climate predictors, one with only soil predictors, and one with both - for each of 1870 plant species in Eastern North America, in order to investigate the relative importance of soil properties in determining plant distributions and poleward shifts under climate change. While climate variables were the most important predictors, soil properties also had a substantial influence on continental-scale plant distributions. Under future climate scenarios, models including soil predicted much smaller northward shifts in distributions than climate-only models (c. 40% reduction). Our findings strongly suggest that high-latitude soils are likely to impede ongoing plant migration, and they highlight the necessity of incorporating soil properties into models and predictions for plant distributions and migration under environmental change.

Automatic synthesis of 18F-AV-45 and its clinical application in Alzheimer's disease.

OBJECTIVE: To investigate the automatic synthesis of ß-amyloid (Aß) positron emission tomography (PET) imaging agent (E) -4- (2- (6- (2- (2-18F fluoroethoxy) ethoxy) ethoxy) pyridine-3-yl) vinyl) - N-methylaniline (18F-AV-45) for the diagnosis of Alzheimer's disease (AD) and its clinical application in AD patients. MATERIALS AND METHODS: Fluorine-18-AV-45 was synthesized with AV-105 as the precursor, and the factors affecting the synthesis efficiency, such as the amount of precursor, nucleophilic reaction temperature were studied. At the same time, 18F-AV-45 PET/computed tomography (CT) brain scanning was performed in 15 patients with dementia to determine whether AD was the cause of the dementia. RESULTS: After optimizing the parameters, it was discovered that the highest synthesis efficiency was achieved with a AV-105 dosage of 2mg, a reaction temperature of 130oC, and 1mL of DMSO. The radiochemical yield (RCP) was greater than 98, and the uncorrected synthesis efficiency was about 31.0%±2.8%. Ten of the 15 patients with dementia showed positive Aß protein deposition, and the main deposition site of the imaging agent was the gray matter area of the brain, which was consistent with AD diagnosis, while the other 5 patients showed negative Aß protein deposition, suggesting non-AD dementia. CONCLUSION: ß-amyloid protein 18F-AV-45 imaging agent can be easily and quickly prepared by the All in One radiochemical synthesis module. Our preliminary results offer hope that it can effectively detect ß-amyloid deposition in the brain of AD patients in order to determine the etiology of dementia.

Protocol for SNOTOB study: radical prostatectomy without prostate biopsy following 18F-PSMA-1007 PET/CT based on a diagnostic model: a single-centre, single-arm, open-label study.

INTRODUCTION: Nowadays, invasive prostate biopsy is the standard diagnostic test for patients with suspected prostate cancer (PCa). However, it has some shortcomings such as perioperative complications, economic and psychological burden on patients, and some patients may undergo repeated prostate biopsy. In this study protocol, our aim is to provide a non-invasive diagnostic strategy we call the 'prostate-specific membrane antigen (PSMA) combined model' for the diagnosis of PCa. If patients are diagnosed with PCa using PSMA combined model, we want to prove these patients can receive radical prostatectomy directly without prior prostate biopsies. METHODS: The SNOTOB trial adopts a prospective, single-centre, single-arm, open-label study design. The PSMA combined model consists of a diagnostic model based on what we previously reported and 18F-PSMA-1007 positron emission tomography/CT (18F-PSMA-1007 PET/CT) examinations in series. First, patients use the diagnostic model (online address: https://ustcprostatecancerprediction.shinyapps.io/dynnomapp/) to calculate the risk probability of clinically significant PCa (csPCa). When the risk probability of csPCa is equal or greater than 0.60, 18F-PSMA-1007 PET/CT will be applied for further diagnosis. If patients are still considered as csPCa after 18F-PSMA-1007 PET/CT examinations, we define this condition as positive results of PSMA combined model. Subsequently, we will recommend these patients to accept radical prostatectomy without prostate biopsy directly. Finally, the diagnostic performance of PSMA combined model will be verified with the pathological results. Totally, 57 patients need to be enrolled in this clinical trial. ETHICS AND DISSEMINATION: This study was approved by the ethics committee of The First Affiliated Hospital of USTC (No. 2022KY-142). The results of this study will be published in peer-reviewed journals and reported at academic conferences. TRIAL REGISTRATION NUMBER: NCT05587192.

Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography.

PURPOSES: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT). MATERIALS AND METHODS: Two VB-Net-based DL models for cervical vertebra segmentation and key-point detection were developed. Four-points and line-fitting methods were used to calculate the sagittal Cobb angle automatically. The average value of the sagittal Cobb angle was manually measured by two doctors as the reference standard. The percentage of correct key points (PCK), matched samples t test, intraclass correlation coefficient (ICC), Pearson correlation coefficient, mean absolute error (MAE), and Bland‒Altman plots were used to evaluate the performance of the DL model and the robustness and generalization of the model on the external test set. RESULTS: A total of 991 patients were included in the internal data set, and 112 patients were included in the external data set. The PCK of the DL model ranged from 78 to 100% in the test set. The four-points method, line-fitting method, and reference standard measured sagittal Cobb angles were - 1.10 ± 18.29°, 0.30 ± 13.36°, and 0.50 ± 12.83° in the internal test set and 4.55 ± 20.01°, 3.66 ± 18.55°, and 1.83 ± 12.02° in the external test set, respectively. The sagittal Cobb angle calculated by the four-points method and the line-fitting method maintained high consistency with the reference standard (internal test set: ICC = 0.75 and 0.97; r = 0.64 and 0.94; MAE = 5.42° and 3.23°, respectively; external test set: ICC = 0.74 and 0.80, r = 0.66 and 0.974, MAE = 5.25° and 4.68°, respectively). CONCLUSIONS: The DL model can accurately measure the sagittal Cobb angle of the cervical spine on CT. The line-fitting method shows a higher consistency with the doctors and a minor average absolute error.

Application research of AI-assisted compressed sensing technology in MRI scanning of the knee joint: 3D-MRI perspective.

OBJECTIVE: To investigate the potential applicability of AI-assisted compressed sensing (ACS) in knee MRI to enhance and optimize the scanning process. METHODS: Volunteers and patients with sports-related injuries underwent prospective MRI scans with a range of acceleration techniques. The volunteers were subjected to varied ACS acceleration levels to ascertain the most effective level. Patients underwent scans at the determined optimal 3D-ACS acceleration level, and 3D compressed sensing (CS) and 2D parallel acquisition technology (PAT) scans were performed. The resultant 3D-ACS images underwent 3.5 mm/2.0 mm multiplanar reconstruction (MPR). Experienced radiologists evaluated and compared the quality of images obtained by 3D-ACS-MRI and 3D-CS-MRI, 3.5 mm/2.0 mm MPR and 2D-PAT-MRI, diagnosed diseases, and compared the results with the arthroscopic findings. The diagnostic agreement was evaluated using Cohen's kappa correlation coefficient, and both absolute and relative evaluation methods were utilized for objective assessment. RESULTS: The study involved 15 volunteers and 53 patients. An acceleration factor of 10.69 × was identified as optimal. The quality evaluation showed that 3D-ACS provided poorer bone structure visualization, and improved cartilage visualization and less satisfactory axial images with 3.5 mm/2.0 mm MPR than 2D-PAT. In terms of objective evaluation, the relative evaluation yielded satisfactory results across different groups, while the absolute evaluation revealed significant variances in most features. Nevertheless, high levels of diagnostic agreement (κ: 0.81-0.94) and accuracy (0.83-0.98) were observed across all diagnoses. CONCLUSION: ACS technology presents significant potential as a replacement for traditional CS in 3D-MRI knee scans, allowing thinner MPRs and markedly faster scans without sacrificing diagnostic accuracy. CLINICAL RELEVANCE STATEMENT: 3D-ACS-MRI of the knee can be completed in the 160 s with good diagnostic consistency and image quality. 3D-MRI-MPR can replace 2D-MRI and reconstruct images with thinner slices, which helps to optimize the current MRI examination process and shorten scanning time. KEY POINTS: • AI-assisted compressed sensing technology can reduce knee MRI scan time by over 50%. • 3D AI-assisted compressed sensing MRI and related multiplanar reconstruction can replace traditional accelerated MRI and yield thinner 2D multiplanar reconstructions. • Successful application of 3D AI-assisted compressed sensing MRI can help optimize the current knee MRI process.

MRI-based automated multitask deep learning system to evaluate supraspinatus tendon injuries.

OBJECTIVE: To establish an automated, multitask, MRI-based deep learning system for the detailed evaluation of supraspinatus tendon (SST) injuries. METHODS: According to arthroscopy findings, 3087 patients were divided into normal, degenerative, and tear groups (groups 0-2). Group 2 was further divided into bursal-side, articular-side, intratendinous, and full-thickness tear groups (groups 2.1-2.4), and external validation was performed with 573 patients. Visual geometry group network 16 (VGG16) was used for preliminary image screening. Then, the rotator cuff multitask learning (RC-MTL) model performed multitask classification (classifiers 1-4). A multistage decision model produced the final output. Model performance was evaluated by receiver operating characteristic (ROC) curve analysis and calculation of related parameters. McNemar's test was used to compare the differences in the diagnostic effects between radiologists and the model. The intraclass correlation coefficient (ICC) was used to assess the radiologists' reliability. p < 0.05 indicated statistical significance. RESULTS: In the in-group dataset, the area under the ROC curve (AUC) of VGG16 was 0.92, and the average AUCs of RC-MTL classifiers 1-4 were 0.99, 0.98, 0.97, and 0.97, respectively. The average AUC of the automated multitask deep learning system for groups 0-2.4 was 0.98 and 0.97 in the in-group and out-group datasets, respectively. The ICCs of the radiologists were 0.97-0.99. The automated multitask deep learning system outperformed the radiologists in classifying groups 0-2.4 in both the in-group and out-group datasets (p < 0.001). CONCLUSION: The MRI-based automated multitask deep learning system performed well in diagnosing SST injuries and is comparable to experienced radiologists. CLINICAL RELEVANCE STATEMENT: Our study established an automated multitask deep learning system to evaluate supraspinatus tendon (SST) injuries and further determine the location of SST tears. The model can potentially improve radiologists' diagnostic efficiency, reduce diagnostic variability, and accurately assess SST injuries. KEY POINTS: • A detailed classification of supraspinatus tendon tears can help clinical decision-making. • Deep learning enables the detailed classification of supraspinatus tendon injuries. • The proposed automated multitask deep learning system is comparable to radiologists.