Fully and Weakly Supervised Deep Learning for Meniscal Injury Classification, and Location Based on MRI.

Meniscal injury is a common cause of knee joint pain and a precursor to knee osteoarthritis (KOA). The purpose of this study is to develop an automatic pipeline for meniscal injury classification and localization using fully and weakly supervised networks based on MRI images. In this retrospective study, data were from the osteoarthritis initiative (OAI). The MR images were reconstructed using a sagittal intermediate-weighted fat-suppressed turbo spin-echo sequence. (1) We used 130 knees from the OAI to develop the LGSA-UNet model which fuses the features of adjacent slices and adjusts the blocks in Siam to enable the central slice to obtain rich contextual information. (2) One thousand seven hundred and fifty-six knees from the OAI were included to establish segmentation and classification models. The segmentation model achieved a DICE coefficient ranging from 0.84 to 0.93. The AUC values ranged from 0.85 to 0.95 in the binary models. The accuracy for the three types of menisci (normal, tear, and maceration) ranged from 0.60 to 0.88. Furthermore, 206 knees from the orthopedic hospital were used as an external validation data set to evaluate the performance of the model. The segmentation and classification models still performed well on the external validation set. To compare the diagnostic performances between the deep learning (DL) models and radiologists, the external validation sets were sent to two radiologists. The binary classification model outperformed the diagnostic performance of the junior radiologist (0.82-0.87 versus 0.74-0.88). This study highlights the potential of DL in knee meniscus segmentation and injury classification which can help improve diagnostic efficiency.

Lipidomic signatures in patients with early-onset and late-onset Preeclampsia.

BACKGROUND: Preeclampsia is a pregnancy-specific clinical syndrome and can be subdivided into early-onset preeclampsia (EOPE) and late-onset preeclampsia (LOPE) according to the gestational age of delivery. Patients with preeclampsia have aberrant lipid metabolism. This study aims to compare serum lipid profiles of normal pregnant women with EOPE or LOPE and screening potential biomarkers to diagnose EOPE or LOPE. METHODS: Twenty normal pregnant controls (NC), 19 EOPE, and 19 LOPE were recruited in this study. Untargeted lipidomics based on ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to compare their serum lipid profiles. RESULTS: The lipid metabolism profiles significantly differ among the NC, EOPE, and LOPE. Compared to the NC, there were 256 and 275 distinct lipids in the EOPE and LOPE, respectively. Furthermore, there were 42 different lipids between the LOPE and EOPE, of which eight were significantly associated with fetal birth weight and maternal urine protein. The five lipids that both differed in the EOPE and LOPE were DGTS (16:3/16:3), LPC (20:3), LPC (22:6), LPE (22:6), PC (18:5e/4:0), and a combination of them were a potential biomarker for predicting EOPE or LOPE. The receiver operating characteristic analysis revealed that the diagnostic power of the combination for distinguishing the EOPE from the NC and for distinguishing the LOPE from the NC can reach 1.000 and 0.992, respectively. The association between the lipid modules and clinical characteristics of EOPE and LOPE was investigated by the weighted gene co-expression network analysis (WGCNA). The results demonstrated that the main different metabolism pathway between the EOPE and LOPE was enriched in glycerophospholipid metabolism. CONCLUSIONS: Lipid metabolism disorders may be a potential mechanism of the pathogenesis of preeclampsia. Lipid metabolites have the potential to serve as biomarkers in patients with EOPE or LOPE. Furthermore, lipid metabolites correlate with clinical severity indicators for patients with EOPE and LOPE, including fetal birth weight and maternal urine protein levels.

Verapamil increases susceptibility of colistin-resistant Acinetobacter baumannii to colistin.

Acinetobacter baumannii, which is predominantly responsible for hospital-acquired infections, presents a tremendous clinical challenge due to its increasing antibiotic resistance to colistin (COL), a last-line antibiotic. As a result, the combination of antimicrobial and non-antimicrobial agents is emerging as a more popular treatment approach against infections caused by COL-resistant A. baumannii. This study administered COL and verapamil (VER), that is an antihypertensive and antiarrhythmic agent. We found that the susceptibility of A. baumannii to COL was restored both in vitro and in vivo. Scanning electron microscope and Crystal violet staining showed inhibition of the VER/COL combination on bacterial biofilm formation. Cytotoxicity assay and haemolysis test were used to confirm in vitro safety evaluation. Further experiments using propidium iodide staining revealed that the VER/COL combination improved the therapeutic efficacy of COL by modifying the permeability of bacterial membranes. As demonstrated by reactive oxygen species experiments, the drug combination caused the accumulation of bacterial reactive oxygen species and their eventual death. Additionally, VER/COL treatment significantly reduced the efflux of Rhodamine 123 (Rh123). For the first time, this study identifies the anti-hypertensive drug VER as a COL potentiator against A. baumannii, providing a potential treatment approach against A. baumannii infections and improving patient outcomes.

Design, Synthesis and Bioactivities of Novel Pyridyl Containing Pyrazole Oxime Ether Derivatives.

In this research, with an aim to develop novel pyrazole oxime ether derivatives possessing potential biological activity, thirty-two pyrazole oxime ethers, including a substituted pyridine ring, have been synthesized and structurally identified through 1H NMR, 13C NMR, and HRMS. Bioassay data indicated that most of these compounds owned strong insecticidal properties against Mythimna separata, Tetranychus cinnabarinus, Plutella xylostella, and Aphis medicaginis at a dosage of 500 µg/mL, and some title compounds were active towards Nilaparvata lugens at 500 µg/mL. Furthermore, some of the designed compounds had potent insecticidal effects against M. separata, T. cinnabarinus, or A. medicaginis at 100 µg/mL, with the mortalities of compounds 8a, 8c, 8d, 8e, 8f, 8g, 8o, 8s, 8v, 8x, and 8z against A. medicaginis, in particular, all reaching 100%. Even when the dosage was lowered to 20 µg/mL, compound 8s also expressed 50% insecticidal activity against M. separata, and compounds 8a, 8e, 8f, 8o, 8v, and 8x displayed more than 60% inhibition rates against A. medicaginis. The current results provided a significant basis for the rational design of biologically active pyrazole oxime ethers in future.

Microbiological Mechanisms of Collaborative Remediation of Cadmium-Contaminated Soil with Bacillus cereus and Lawn Plants.

Severe cadmium contamination poses a serious threat to food security and human health. Plant-microbial combined remediation represents a potential technique for reducing heavy metals in soil. The main objective of this study is to explore the remediation mechanism of cadmium-contaminated soil using a combined approach of lawn plants and microbes. The target bacterium Bacillus cereus was selected from cadmium-contaminated soil in mining areas, and two lawn plants (Festuca arundinacea A'rid III' and Poa pratensis M'idnight II') were chosen as the target plants. We investigated the remediation effect of different concentrations of bacterial solution on cadmium-contaminated soil using two lawn plants through pot experiments, as well as the impact on the soil microbial community structure. The results demonstrate that Bacillus cereus promotes plant growth, and the combined action of lawn plants and Bacillus cereus improves soil quality, enhancing the bioavailability of cadmium in the soil. At a bacterial suspension concentration of 105 CFU/mL, the optimal remediation treatment was observed. The removal efficiency of cadmium in the soil under Festuca arundinacea and Poa pratensis treatments reached 33.69% and 33.33%, respectively. Additionally, the content of bioavailable cadmium in the rhizosphere soil increased by up to 13.43% and 26.54%, respectively. Bacillus cereus increased the bacterial diversity in the non-rhizosphere soil of both lawn plants but reduced it in the rhizosphere soil. Additionally, the relative abundance of Actinobacteriota and Firmicutes, which have potential for heavy metal remediation, increased after the application of the bacterial solution. This study demonstrates that Bacillus cereus can enhance the potential of lawn plants to remediate cadmium-contaminated soil and reshape the microbial communities in both rhizosphere and non-rhizosphere soils.

Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions.

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the A n-I, g s-I, T r-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of A n, g s, T r, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R 2 values for A n-I, g s-I, and T r-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, A n, g s, and T r of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum A n, g s, and T r but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum A n saturated at current atmospheric CO2 levels, with no significant gains under 550 µmol mol-1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated g s and T r reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.

Facial adult female acne in China: An analysis based on artificial intelligence over one million.

BACKGROUND: To further clarify the acne profile of Chinese adult women, we included 1,156,703 adult women. An artificial intelligence algorithm was used to analyze images taken by high-resolution mobile phones to further explore acne levels in Chinese adult women. METHOD: In this study, we assessed the severity of acne by evaluating patients' selfies through a smartphone application. Furthermore, we gathered basic user information through a questionnaire, including details such as age, gender, skin sensitivity, and dietary habits. RESULTS: This study showed a gradual decrease in acne severity from the age of 25 years. A trough was reached between the ages of 40 and 44, followed by a gradual increase in acne severity. In terms of skin problems and acne severity, we have found that oily skin, hypersensitive skin, frequent makeup application and unhealthy dietary habits can affect the severity of acne. For environment and acne severity, we observed that developed city levels, cold seasons and high altitude and strong radiation affect acne severity in adult women. For the results of the AI analyses, the severity of blackheads, pores, dark circles and skin roughness were positively associated with acne severity in adult women. CONCLUSIONS: AI analysis of high-res phone images in Chinese adult women reveals acne severity trends. Severity decreases after 25, hits a low at 40-44, then gradually rises. Skin type, sensitivity, makeup, diet, urbanization, seasons, altitude, and radiation impact acne. Blackheads, pores, dark circles, and skin roughness are linked to acne severity. These findings inform personalized skincare and public health strategies for adult women.

Alterations in gut microbiota contribute to cognitive deficits induced by chronic infection of Toxoplasma gondii.

Chronic infection with Toxoplasma gondii (T. gondii) emerges as a risk factor for neurodegenerative diseases in animals and humans. However, the underlying mechanisms are largely unknown. We aimed to investigate whether gut microbiota and its metabolites play a role in T. gondii-induced cognitive deficits. We found that T. gondii infection induced cognitive deficits in mice, which was characterized by synaptic ultrastructure impairment and neuroinflammation in the hippocampus. Moreover, the infection led to gut microbiota dysbiosis, barrier integrity impairment, and inflammation in the colon. Interestingly, broad-spectrum antibiotic ablation of gut microbiota attenuated the adverse effects of the parasitic infection on the cognitive function in mice; cognitive deficits and hippocampal pathological changes were transferred from the infected mice to control mice by fecal microbiota transplantation. In addition, the abundance of butyrate-producing bacteria and the production of serum butyrate were decreased in infected mice. Interestingly, dietary supplementation of butyrate ameliorated T. gondii-induced cognitive impairment in mice. Notably, compared to the healthy controls, decreased butyrate production was observed in the serum of human subjects with high levels of anti-T. gondii IgG. Overall, this study demonstrates that gut microbiota is a key regulator of T. gondii-induced cognitive impairment.

Response of bacterial community structure to different phosphorus additions in a tobacco-growing soil.

Introduction: Phosphorus (P), which plays a vital role in plant growth, is continually added to soil to maximize biomass production, leading to excessive P accumulation and water eutrophication. Results: In this study, a pot experiment using a subtropical tobacco-growing soil fertilized with four P levels-no P, low P, medium P, and high P-was conducted and rhizosphere and bulk soils were analyzed. Results: P addition significantly increased tobacco biomass production (except under low P input) and total soil P and available P content (P<0.05), whereas total nitrogen content decreased in the rhizosphere soils, although this was only significant with medium P application. P fertilization also significantly altered the bacterial communities of rhizosphere soils (P<0.05), but those of bulk soils were unchanged (P>0.05). Moreover, a significant difference was found between rhizosphere soils with low (LR) and high (HR) P inputs (P<0.05). Additionally, compared with rhizosphere soils with no P (CKR), Shannon diversity showed a declining trend, which was significant with LR and HR (P<0.05), whereas an increasing tendency was observed for Chao1 diversity except in LR (P>0.05). Functional prediction revealed that P application significantly decreased the total P and N metabolism of microorganisms in rhizosphere soils (P<0.05). Discussion: Collectively, our results indicate that maintaining sustainable agricultural ecosystems under surplus P conditions requires more attention to be directed toward motivating the potential of soil functional microbes in P cycling, rather than just through continual P input.

Enhancing phytoremediation of cadmium and arsenic in alkaline soil by Miscanthus sinensis: A study on the synergistic effect of endophytic fungi and biochar.

Endophytic fungi (Trichoderma harzianum (TH) and Paecilomyces lilacinus (PL)) showed potential in phytoremediation for soils contaminated with potentially toxic elements (PTEs (Cd and As)). However, their efficiency is limited, which can be enhanced with the assistance of biochar. This study sought to investigate the effects of TH at two application rates (T1: 4.5 g m-2; T2: 9 g m-2), PL at two application rates (P1: 4.5 g m-2; P2: 9 g m-2), in conjunction with biochar (BC) at 750 g m-2 on the phytoremediation of PTEs by Miscanthus sinensis (M. sinensis). The results showed that the integration of endophytic fungi with biochar notably enhanced the accumulation of Cd and As in M. sinensis by 59.60 %-114.38 % and 49.91 %-134.60 %, respectively. The treatments T2BC and P2BC emerged as the most effective. Specifically, the P2BC treatment significantly enhanced the soil quality index (SQI > 0.55) across all examined soil layers, markedly improving the overall soil condition. It was observed that T2BC treatment could elevate the SQI to 0.56 at the 0-15 cm depth. The combined amendment shifted the primary influences on plant PTEs accumulation from fungal diversity and soil nutrients to bacterial diversity and the availability of soil PTEs. Characteristic microorganisms identified under the combined treatments were RB41 and Pezizaceae, indicating an increase in both bacterial and fungal diversity. This combination altered the soil microbial community, influencing key metabolic pathways. The combined application of PL and biochar was superior to the TH and biochar combination for the phytoremediation of M. sinensis. This approach not only enhanced the phytoremediation potential but also positively impacted soil health and microbial community, suggesting that the synergistic use of endophytic fungi and biochar is an effective strategy for improving the condition of alkaline soils contaminated with PTEs.

Effects of micro-nano bubble water addition on maturation degree and microbial community during aerobic composting.

In order to explore the effects of micro-nano bubble water (MNBW) on compost maturation and the microbial community in cow manure and straw during aerobic composting, we conducted composting tests using tap water with 12 mg/L (O12), 15 mg/L (O15), 18 mg/L (O18), and 21 mg/L (O21) dissolved oxygen in MNBW, as well as tap water with 9 mg/L dissolved oxygen as a control (CK). The results showed that O21 increased the maximum compost temperature to 64 °C, which was higher than the other treatments. All treatments met the harmless standards for compost. The seed germination index (GI) was largest under O21 and 15.1% higher than that under CK, and the non-toxic compost degree was higher. Redundancy analysis showed that the temperature, C/N, pH, and GI were important factors that affected the microbial community composition. The temperature, C/N, and pH were significantly positively correlated with Firmicutes and Actinobacteria (p < 0.05). Firmicutes was the dominant phylum in the mesophilic stage (2-6 days) and it accounted for a large proportion under O21, where the strong thermophilic metabolism increased the production of heat and prolonged the high temperature period. The bacterial genus Ammoniibacillus in Firmicutes accounted for a large proportion under O21 and it accelerated the decomposition of substrates. Therefore, the addition of MNBW changed the microbial community to affect the maturation of the compost, and the quality of the compost was higher under O21.

Spatiotemporal patterns and evolutionary trends of eco-environmental quality in arid regions of Northwest China.

The arid regions of northwest China suffer from water shortages, low land quality, and a fragile ecological environment, while social and economic development has increased the ecological and environmental load. The spatiotemporal pattern and evolutionary trend of ecological environmental quality were investigated by constructing a remote sensing-based ecological environmental index (EQI) evaluation model incorporating four indicators: drought index (DI), soil erosion index (SEI), greenness index (GI), and carbon exchange index (CEI). The study found that between 2001 and 2020, the DI, the SEI, and the CEI in the northwest arid region exhibited a downward trend with reduction rates of - 3e-05, -0.0006, and -0.0018, respectively. However, the GI demonstrated an upward trend, with a growth rate of 0.002. The average EQI in 2020 was 0.315, indicating a fair grade, with only 11.56% falling above the medium level. A general increasing trend was observed throughout the study period in EQI, with an incremental rate of 0.0002. Areas with future improvements in EQI accounted for 57.547% and were principally located in the eastern part of Inner Mongolia, Qinghai, and the northern and southern portions of Xinjiang. Notably, land use was significantly correlated with EQI (p < 0.01), with a hierarchy of effects that ran: forest land (0.678) > cultivated land (0.422) > grassland (0.382) > wasteland (0.138). The highly robust findings presented here offer innovative methods for ecological and environmental monitoring in the arid region of the northwest, with potential implications at an international scale.

Multiparametric MRI-based fusion radiomics for predicting telomerase reverse transcriptase (TERT) promoter mutations and progression-free survival in glioblastoma: a multicentre study.

PURPOSE: This study evaluated the performance of multiparametric magnetic resonance imaging (MRI)-based fusion radiomics models (MMFRs) to predict telomerase reverse transcriptase (TERT) promoter mutation status and progression-free survival (PFS) in glioblastoma patients. METHODS: We retrospectively analysed 208 glioblastoma patients from two hospitals. Quantitative imaging features were extracted from each patient's T1-weighted, T1-weighted contrast-enhanced, and T2-weighted preoperative images. Using a coarse-to-fine feature selection strategy, four radiomics signature models were constructed based on the three MRI sequences and their combination for TERT promoter mutation status and PFS; model performance was subsequently evaluated. Subgroup analyses were performed by the radiomics signature of TERT promoter mutation status and PFS to distinguish patients who could benefit from prolonged temozolomide chemotherapy cycles. RESULTS: TERT promoter mutation status was best predicted by MMFR, with an area under the curve (AUC) of 0.816 and 0.812 for the training and internal validation sets, respectively. The external test set also achieved stable and optimal prediction results (AUC, 0.823). MMFR better predicted patient PFS compared with the single-sequence radiomics signature in the test set (C-index, 0.643 vs 0.561 vs 0.620 vs 0.628). Subgroup analyses showed that more than six cycles of postoperative temozolomide chemotherapy were associated with improved PFS for patients in class 2 (high TERT promoter mutation and high survival rates; HR, 0.222; 95% CI, 0.054 - 0.923; p = 0.025). CONCLUSION: MMFR is an effective method to predict TERT promoter mutations and PFS in patients with glioblastoma. Moreover, subgroup analysis could differentiate patients who may benefit from prolonged TMZ chemotherapy cycles.

Clinical application of blood purification in polymyositis/dermatomyositis.

INTRODUCTION: We investigated the clinical efficacy and safety of blood purification technology in patients with polymyositis/dermatomyositis. METHODS: In a study of 22 patients, 10 cases received blood purification treatment (5 cases received plasma exchange, 5 cases received plasma HA280 immunoadsorption), and 12 cases served as the control group. A 3-month follow-up was conducted to compare the clinical manifestations and laboratory examination. RESULTS: Symptoms and signs of patients in treatment group were significantly improved, and the hormone usage was lower than the control group. For patients with normal creatine kinase level and ferritin level below three times the upper limit of normal, there was a positive correlation between their N/L values and MDAAT scores. CONCLUSION: The results of this study suggest that blood purification therapy, including plasma HA280 immunoadsorption and plasma exchange, is an effective and safe treatment for patients with polymyositis/dermatomyositis, offering assistance in reducing hormone usage in the long-term.

Peritumoral Radiomics for Identification of Telomerase Reverse Transcriptase Promoter Mutation in Patients With Glioblastoma Based on Preoperative MRI.

Purpose: To evaluate the value of intra- and peritumoral deep learning (DL) features based on multi-parametric magnetic resonance imaging (MRI) for identifying telomerase reverse transcriptase (TERT) promoter mutation in glioblastoma (GBM). Methods: In this study, we included 229 patients with GBM who underwent preoperative MRI in two hospitals between November 2016 and September 2022. We used four 2D Convolutional Neural Networks (GoogLeNet, DenseNet121, VGG16, and MobileNetV3-Large) to extract intra- and peritumoral DL features. The Mann-Whitney U test, Pearson correlation analysis, least absolute shrinkage and selection operator, and logistic regression analysis were used for feature selection and construction of DL radiomics (DLR) signatures in different regions. These multi-parametric and multi-region signatures were combined to identify TERT promoter mutation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effects of the signatures. Results: The signatures based on the DL features from the peritumoral regions with expansion distances of 2 mm, 8 mm, and 10 mm using the GoogLeNet architecture correlated with the optimal AUC values (test set: .823, .753, and .768) in the T2-weighted, T1-weighted contrast-enhanced, and T1-weighted images. Using the stacking fusion method, DLR with multi-parameter and multi-region fusion achieved the best discrimination with AUC values of .948 and .902 in the training and test sets, respectively. Conclusions: The radiomics model based on the fusion of multi-parameter MRI intra- and peritumoral DLR signatures may help to identify TERT promoter mutation in patients with GBM.

Evaluation of gadolinium deposition in cortical bone using three-dimensional ultrashort echo time quantitative susceptibility mapping: A preliminary study.

The aim of the current study was to investigate the feasibility of three-dimensional ultrashort echo time quantitative susceptibility mapping (3D UTE-QSM) for the assessment of gadolinium (Gd) deposition in cortical bone. To this end, 40 tibial bovine cortical bone specimens were divided into five groups then soaked in phosphate-buffered saline (PBS) solutions with five different Gd concentrations of 0, 0.4, 0.8, 1.2, and 1.6 mmol/L for 48 h. Additionally, eight rabbits were randomly allocated into three groups, consisting of a normal-dose macrocyclic gadolinium-based contrast agent (GBCA) group (n = 3), a high-dose macrocyclic GBCA group (n = 3), and a control group (n = 2). All bovine and rabbit tibial bone samples underwent magnetic resonance imaging (MRI) on a 3-T clinical MR system. A 3D UTE-Cones sequence was utilized to acquire images with five different echo times (i.e., 0.032, 0.2, 0.4, 0.8, and 1.2 ms). The UTE images were subsequently processed with the morphology-enabled dipole inversion algorithm to yield a susceptibility map. The average susceptibility was calculated in three regions of interest in the middle of each specimen, and the Pearson's correlation between the estimated susceptibility and Gd concentration was calculated. The bone samples soaked in PBS with higher Gd concentrations exhibited elevated susceptibility values. A mean susceptibility value of -2.47 ± 0.23 ppm was observed for bovine bone soaked in regular PBS, while the mean QSM value increased to -1.75 ± 0.24 ppm for bone soaked in PBS with the highest Gd concentration of 1.6 mmol/L. A strong positive correlation was observed between Gd concentrations and QSM values. The mean susceptibility values of rabbit tibial specimens in the control group, normal-dose GBCA group, and high-dose GBCA group were -4.11 ± 1.52, -3.85 ± 1.33, and -3.39 ± 1.35 ppm, respectively. In conclusion, a significant linear correlation between Gd in cortical bone and QSM values was observed. The preliminary results suggest that 3D UTE-QSM may provide sensitive noninvasive assessment of Gd deposition in cortical bone.

Noninvasive Detection of Salt Stress in Cotton Seedlings by Combining Multicolor Fluorescence-Multispectral Reflectance Imaging with EfficientNet-OB2.

Salt stress is considered one of the primary threats to cotton production. Although cotton is found to have reasonable salt tolerance, it is sensitive to salt stress during the seedling stage. This research aimed to propose an effective method for rapidly detecting salt stress of cotton seedlings using multicolor fluorescence-multispectral reflectance imaging coupled with deep learning. A prototyping platform that can obtain multicolor fluorescence and multispectral reflectance images synchronously was developed to get different characteristics of each cotton seedling. The experiments revealed that salt stress harmed cotton seedlings with an increase in malondialdehyde and a decrease in chlorophyll content, superoxide dismutase, and catalase after 17 days of salt stress. The Relief algorithm and principal component analysis were introduced to reduce data dimension with the first 9 principal component images (PC1 to PC9) accounting for 95.2% of the original variations. An optimized EfficientNet-B2 (EfficientNet-OB2), purposely used for a fixed resource budget, was established to detect salt stress by optimizing a proportional number of convolution kernels assigned to the first convolution according to the corresponding contributions of PC1 to PC9 images. EfficientNet-OB2 achieved an accuracy of 84.80%, 91.18%, and 95.10% for 5, 10, and 17 days of salt stress, respectively, which outperformed EfficientNet-B2 and EfficientNet-OB4 with higher training speed and fewer parameters. The results demonstrate the potential of combining multicolor fluorescence-multispectral reflectance imaging with the deep learning model EfficientNet-OB2 for salt stress detection of cotton at the seedling stage, which can be further deployed in mobile platforms for high-throughput screening in the field.

Estradiol-mediated small GTP-binding protein GDP dissociation stimulator induction contributes to sex differences in resilience to ferroptosis in takotsubo syndrome.

BACKGROUND: Declining beneficial cardiovascular actions of estradiol (E2) have been associated with disproportionate susceptibility to takotsubo syndrome (TTS) in postmenopausal women. However, the underlying mechanisms between E2 and this marked disproportion remain unclear. SmgGDS (small GTP-binding protein GDP dissociation stimulator), as a key modulator of cardiovascular disease, plays protective roles in reducing oxidative stress and exerts pleiotropic effects of statins. Whether SmgGDS levels are influenced by E2 status and the effect of SmgGDS on sex differences in TTS are poorly understood. METHODS: Clinical data were reviewed from TTS inpatients. Echocardiography, immunofluorescence, and immunohistochemistry were performed together with expression analysis to uncover phenotypic and mechanism changes in sex differences in TTS-like wild-type (WT) and SmgGDS± mice. HL-1 cardiomyocytes were used to further examine and validate molecular mechanisms. RESULTS: In 14 TTS inpatients, TTS had a higher incidence in postmenopausal women as compared to premenopausal women and men. In murine TTS, female WT mice exhibited higher cardiac SmgGDS levels than male WT mice. Ovariectomy reduced SmgGDS expression in female WT mice similar to that observed in male mice, whereas E2 replacement in these ovariectomized (OVX) female mice reversed this effect. The physiological importance of this sex-specific E2-mediated SmgGDS response is underscored by the disparity in cardiac adaptation to isoproterenol (ISO) stimulation between both sexes of WT mice. E2-mediated SmgGDS induction conferred female protection against TTS-like acute cardiac injury involving ferritinophagy-mediated ferroptosis. No such cardioprotection was observed in male WT mice and OVX female. A causal role for SmgGDS in this sex-specific cardioprotective adaptation was indicated, inasmuch as SmgGDS deficiency abolished E2-modulated cardioprotection against ferritinophagy and aggravates TTS progression in both sexes. Consistently, knockdown of SmgGDS in HL-1 cardiomyocytes exacerbated ferroptosis in a ferritinophagy-dependent manner and abrogated the protective role of E2 against ferritinophagy. Mechanistically, our findings revealed that SmgGDS regulated E2-dependent cardioprotective effects via AMPK/mTOR signaling pathway. SmgGDS deficiency abolished E2-conferred protection against ferritinophagy through activating AMPK/mTOR pathway, while treatment with recombinant SmgGDS in HL-1 cells significantly mitigated this pathway-associated ferritinophagy activity. CONCLUSIONS: These results demonstrate that SmgGDS is a central mediator of E2-conferred female cardioprotection against ferritinophagy-mediated ferroptosis in TTS.

Artificial intelligence analysis of over a million Chinese men and women reveals level of dark circle in the facial skin aging process.

BACKGROUND: To better compare the progression of dark circles and the aging process in Chinese skin. A total of 100 589 Chinese males and 1 838 997 Chinese females aged 18 to 85, without facial skin conditions, and who had access to a smartphone with a high-resolution camera all took selfies. METHOD: Using a smartphone application with a built-in artificial intelligence algorithm, facial skin diagnostic evaluated the selfies and score the severity of the dark circles with four other facial indicators (including skin type, Pores, Acne vulgaris, and Blackheads). Basic information was collected with online questionnaire, including their age, gender, skin sensitivity, and dietary habits. RESULTS: In users between the age of 18 and 59, the prevalence of comprehensive, pigmented, and structural type of dark circles all rose with age. However, between the age of 60 and 85, the intensity of all types of dark circles diminished. Besides, vascular dark circles progressively worsen from the age of 18 to their peak at 39, and then gradually decline with age. Females typically have more pronounced black circles under their eyes than males in China. Bad eating habits, urbanization, regular cosmetics use, and sensitive skin positively correlate with severe dark circles. Vascular, comprehensive dark circles were worse in spring. Both pigmented and structural dark circles were worse in the summer. The results indicated that the intensity of dark circles was influenced by oily skin, wide pores, severe blackheads, and severe acne. CONCLUSIONS: Chinese men and women differed noticeably in the prevalence of each face aging indicator and the appearance of aging dark circles. Selfies could be automatically graded and examined by artificial intelligence, which is a quick and private method for quantifying signs of facial aging and identifying major problems for different populations. Artificial intelligence would assist in the development of individualized preventive and therapeutic interventions.

An Optimization Method of Deep Transfer Learning for Vegetation Segmentation under Rainy and Dry Season Differences in a Dry Thermal Valley.

Deep learning networks might require re-training for different datasets, consuming significant manual labeling and training time. Transfer learning uses little new data and training time to enable pre-trained network segmentation in relevant scenarios (e.g., different vegetation images in rainy and dry seasons); however, existing transfer learning methods lack systematicity and controllability. So, an MTPI method (Maximum Transfer Potential Index method) was proposed to find the optimal conditions in data and feature quantity for transfer learning (MTPI conditions) in this study. The four pre-trained deep networks (Seg-Net (Semantic Segmentation Networks), FCN (Fully Convolutional Networks), Mobile net v2, and Res-Net 50 (Residual Network)) using the rainy season dataset showed that Res-Net 50 had the best accuracy with 93.58% and an WIoU (weight Intersection over Union) of 88.14%, most worthy to transfer training in vegetation segmentation. By obtaining each layer's TPI performance (Transfer Potential Index) of the pre-trained Res-Net 50, the MTPI method results show that the 1000-TDS and 37-TP were estimated as the best training speed with the smallest dataset and a small error risk. The MTPI transfer learning results show 91.56% accuracy and 84.86% WIoU with 90% new dataset reduction and 90% iteration reduction, which is informative for deep networks in segmentation tasks between complex vegetation scenes.