Improving the accuracy of cotton seedling emergence rate estimation by fusing UAV-based multispectral vegetation indices.

Timely and accurate estimation of cotton seedling emergence rate is of great significance to cotton production. This study explored the feasibility of drone-based remote sensing in monitoring cotton seedling emergence. The visible and multispectral images of cotton seedlings with 2 - 4 leaves in 30 plots were synchronously obtained by drones. The acquired images included cotton seedlings, bare soil, mulching films, and PE drip tapes. After constructing 17 visible VIs and 14 multispectral VIs, three strategies were used to separate cotton seedlings from the images: (1) Otsu's thresholding was performed on each vegetation index (VI); (2) Key VIs were extracted based on results of (1), and the Otsu-intersection method and three machine learning methods were used to classify cotton seedlings, bare soil, mulching films, and PE drip tapes in the images; (3) Machine learning models were constructed using all VIs and validated. Finally, the models constructed based on two modeling strategies [Otsu-intersection (OI) and machine learning (Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)] showed a higher accuracy. Therefore, these models were selected to estimate cotton seedling emergence rate, and the estimates were compared with the manually measured emergence rate. The results showed that multispectral VIs, especially NDVI, RVI, SAVI, EVI2, OSAVI, and MCARI, had higher crop seedling extraction accuracy than visible VIs. After fusing all VIs or key VIs extracted based on Otsu's thresholding, the binary image purity was greatly improved. Among the fusion methods, the Key VIs-OI and All VIs-KNN methods yielded less noises and small errors, with a RMSE (root mean squared error) as low as 2.69% and a MAE (mean absolute error) as low as 2.15%. Therefore, fusing multiple VIs can increase crop image segmentation accuracy. This study provides a new method for rapidly monitoring crop seedling emergence rate in the field, which is of great significance for the development of modern agriculture.

Dynamic monitoring of radiation-induced white matter microstructure injury in nasopharyngeal carcinoma via high-angular resolution diffusion imaging.

PURPOSE: To investigate white matter microstructural abnormalities caused by radiotherapy in nasopharyngeal carcinoma (NPC) patients using MRI high-angular resolution diffusion imaging (HARDI). METHODS: We included 127 patients with pathologically confirmed NPC: 36 in the pre-radiotherapy group, 29 in the acute response period (post-RT-AP), 23 in the early delayed period (post-RT-ED) group, and 39 in the late-delayed period (post-RT-LD) group. HARDI data were acquired for each patient, and dispersion parameters were calculated to compare the differences in specific fibre bundles among the groups. The Montreal Neurocognitive Assessment (MoCA) was used to evaluate neurocognitive function, and the correlations between dispersion parameters and MoCA were analysed. RESULTS: In the right cingulum frontal parietal bundles, the fractional anisotropy value decreased to the lowest level post-RT-AP and then reversed and increased post-RT-ED and post-RT-LD. The mean, axial, and radial diffusivity were significantly increased in the post-RT-AP (p < 0.05) and decreased in the post-RT-ED and post-RT-LD groups to varying degrees. MoCA scores were decreased post-radiotherapy than those before radiotherapy (p = 0.005). MoCA and mean diffusivity exhibited a mild correlation in the left cingulum frontal parahippocampal bundle. CONCLUSIONS: White matter tract changes detected by HARDI are potential biomarkers for monitoring radiotherapy-related brain damage in NPC patients.

C1q enables influenza hemagglutinin stem binding antibodies to block viral attachment and broadens the antibody escape repertoire.

Antigenic drift, the gradual accumulation of amino acid substitutions in the influenza virus hemagglutinin (HA) receptor protein, enables viral immune evasion. Antibodies (Abs) specific for the drift-resistant HA stem region are a promising universal influenza vaccine target. Although anti-stem Abs are not believed to block viral attachment, here we show that complement component 1q (C1q), a 460-kilodalton protein with six Ab Fc-binding domains, confers attachment inhibition to anti-stem Abs and enhances their fusion and neuraminidase inhibition. As a result, virus neutralization activity in vitro is boosted up to 30-fold, and in vivo protection from influenza PR8 infection in mice is enhanced. These effects reflect increased steric hindrance and not increased Ab avidity. C1q greatly expands the anti-stem Ab viral escape repertoire to include residues throughout the HA, some of which cause antigenic alterations in the globular region or modulate HA receptor avidity. We also show that C1q enhances the neutralization activity of non-receptor binding domain anti-SARS-CoV-2 spike Abs, an effect dependent on spike density on the virion surface. These findings demonstrate that C1q can greatly expand Ab function and thereby contribute to viral evolution and immune escape.

Photo-production of excited triplet-state of dissolved organic matters in inland freshwater and coastal seawater.

The excited triplet-state of dissolved organic matter (3DOM*) is a major reactive intermediate in sunlit waters. Its quantum yield is important in understanding the fate of organic micropollutants. The degradation efficiency of its chemical probe, 2,4,6-trimeythlphenol (fTMP), is generally used as a proxy of the quantum yield. However, fTMP has been described and modelled only for freshwater systems. Therefore, this study quantified fTMP in inland freshwater and coastal seawater sampled in Japan by conducting steady-state photochemical experiments. Optical properties of water were then used to model fTMP. Results indicated that the inland freshwater DOM originated mainly from terrestrial sources, while the coastal seawater DOM were microbial-dominated. On average, inland freshwater exhibited lower fTMP (61.2 M-1) than coastal seawater (79.7 M-1) and the coastal seawater exhibited significant variations in the proportion of high-energy 3DOM* (> 250 kJ/mol). In addition, E2:E3 (ratio of absorbance at 254 to 365 nm) was positively correlated with fTMP of inland freshwater, coastal seawater, and the overall dataset. Catchment conditions such as forest coverage also influenced the production of 3DOM* and high-energy 3DOM* in inland freshwater. Furthermore, the developed models estimated fTMP based on the optical properties of both freshwater and seawater, providing valuable insights about 3DOM* photochemistry in the aquatic environment.

Omicron Spike confers enhanced infectivity and interferon resistance to SARS-CoV-2 in human nasal tissue.

Omicron emerged following COVID-19 vaccination campaigns, displaced previous SARS-CoV-2 variants of concern worldwide, and gave rise to lineages that continue to spread. Here, we show that Omicron exhibits increased infectivity in primary adult upper airway tissue relative to Delta. Using recombinant forms of SARS-CoV-2 and nasal epithelial cells cultured at the liquid-air interface, we show that mutations unique to Omicron Spike enable enhanced entry into nasal tissue. Unlike earlier variants of SARS-CoV-2, our findings suggest that Omicron enters nasal cells independently of serine transmembrane proteases and instead relies upon metalloproteinases to catalyze membrane fusion. Furthermore, we demonstrate that this entry pathway unlocked by Omicron Spike enables evasion from constitutive and interferon-induced antiviral factors that restrict SARS-CoV-2 entry following attachment. Therefore, the increased transmissibility exhibited by Omicron in humans may be attributed not only to its evasion of vaccine-elicited adaptive immunity, but also to its superior invasion of nasal epithelia and resistance to the cell-intrinsic barriers present therein.

Improving the estimation accuracy of rapeseed leaf photosynthetic characteristics under salinity stress using continuous wavelet transform and successive projections algorithm.

Soil salinization greatly restricts crop production in arid areas for salinity stress can inhibit crop photosynthesis and growth. Chlorophyll fluorescence and photosynthetic gas exchange (CFPGE) parameters are important indicators of crop photosynthesis and have been widely used to evaluate the impacts of salinity stress on crop photosynthesis and growth. Remote sensing technology can quickly and non-destructively obtain crop information under salinity stress, however, at present, the distribution of spectral features of CFPGE parameters in different regions is still unclear. In this study (2019-2020), under salinity stress conditions, the spectral data of rapeseed leaves were acquired and the CFPGE parameters were simultaneously determined. Then, continuous wavelet transformation (CWT) and standard normal variate (SNV) transformation were utilized to preprocess the raw spectral data. After that, a CFPGE parameter estimation model was constructed by using the partial least squares regression (PLSR) algorithm and the support vector machines (SVM) algorithm based on the spectral features in the red region (600-800 nm) and those in the red, blue-green (350-600 nm), and near-infrared (800-2500 nm) regions. The results showed that the spectral features of CFPGE parameters could be extracted by successive projections algorithm (SPA) based on the CWT preprocessing. The CFPGE parameter estimation model constructed based on the spectral features in the red region (675 nm, 680 nm, 688 nm, 749 nm, and 782 nm) had the highest Fv/Fm estimation accuracy on day 30, with R2c, R2p, and RPD of 0.723, 0.585, and 1.68, respectively. Based on this, the spectral features (578 nm, 976 nm, 1088 nm, 1476 nm, and 2250 nm) in the blue-green and near-infrared regions were added in the variables for modeling, which significantly improved the accuracy and stability of the model, with R2c, R2p, and RPD of 0.886, 0.815, and 2.58, respectively. Therefore, the fusion of the spectral features in the red, blue-green, and near-infrared regions could improve the estimation accuracy of rapeseed leaf CFPGE parameters. This study will provide technical reference for rapid estimation of photosynthetic performance of crops under salinity stress in arid and semi-arid areas.

Role of stress granules in tumorigenesis and cancer therapy.

Stress granules (SGs) are membrane-less organelles that cell forms via liquid-liquid phase separation (LLPS) under stress conditions such as oxidative stress, ER stress, heat shock and hypoxia. SG assembly is a stress-responsive mechanism by regulating gene expression and cellular signaling pathways. Cancer cells face various stress conditions in tumor microenvironment during tumorigenesis, while SGs contribute to hallmarks of cancer including proliferation, invasion, migration, avoiding apoptosis, metabolism reprogramming and immune evasion. Here, we review the connection between SGs and cancer development, the limitation of SGs on current cancer therapy and promising cancer therapeutic strategies targeting SGs in the future.

Dynamic functional connectivity changes associated with decreased memory performance in betel quid dependence.

The temporal variability of the dynamic functional connectivity (dFC) has been suggested as a useful metric for studying abnormal cognitive function. This study aimed to explore the associations between the temporal properties of dFC and memory performance in betel quid dependence (BQD). Sixty-four BQD individuals and 47 gender- and age-matched healthy controls (HCs) underwent functional magnetic resonance imaging and a series of neuropsychological assessments. The dFC was constructed by calculating the Pearson correlation coefficients within a sliding window and was clustered into three functional connectivity states using k-means clustering. The dFC temporal properties derived from the cluster results were compared between the BQD and HC groups. The results showed that States 1 and 3 featured more frequent and weak connectivity, and State 2 featured less frequent and strong connectivity. There were significant differences for mean dwell time (MDT) in State 3 (p = 0.022) and fraction of time in State 2 (p = 0.018) between the BQD and HC groups. Pearson correlation analyses showed that the MDT in State 1 was negatively correlated with long delay free recall and short delay free recall, and the MDT in State 3 was positively correlated with false positive of long delay recall. Our findings provide strong evidence that MDT match the memory performance and suggest new insights into the pathophysiological mechanism of memory disorders in BQD individuals.

The DUBA-SLC7A11-c-Myc axis is critical for stemness and ferroptosis.

Ferroptosis is characterized by the accumulation of lipid peroxidation as a unique iron-dependent cell death. However, the interplay between stemness and ferroptosis remains unknown. Here, we demonstrate that undifferentiated cells are more sensitive to ferroptosis than differentiated cells, and cystine transporter SLC7A11 protein is highly up-regulated by deubiquitinase DUBA in differentiated cells. Additionally, DUBA promotes stemness by deubiquitinating SLC7A11. Moreover, SLC7A11 drastically increases the expression of c-Myc through cysteine, the combination of sorafenib and c-Myc inhibitor EN4 has a synergetic effect on cancer therapy. Together, our results reveal that enhanced stemness increases the susceptibility to ferroptosis, and the DUBA-SLC7A11-c-Myc axis is pivotal for differentiated cancer stem cells (CSCs) resistant to ferroptosis, providing a promised targets to eradicate CSCs through ferroptosis.

Gasdermins and cancers.

The identification of gasdermin as the executor of pyroptosis has opened new avenues for the study of this process. Although pyroptosis research has mainly focused on immune cells since it was discovered three decades ago, accumulating evidence suggests that pyroptosis plays crucial roles in many biological processes. One example is the discovery of gasdermin-mediated cancer cell pyroptosis (CCP) which has become an important and frontier field in oncology. Recent studies have shown that CCP induction can heat tumor microenvironment (TME) and thereby elicit the robust anti-tumor immunity to suppress tumor growth. As a newly discovered form of tumor cell death, CCP offers promising opportunities for improving tumor treatment and developing new drugs. Nevertheless, the research on CCP is still in its infancy, and the molecular mechanisms underlying the expression, regulation and activation of gasdermins are not yet fully understood. In this review, we summarize the recent progress of gasdermin research in cancer area, and propose that the anti-tumor effect of immune cell pyroptosis (ICP) and CCP depends on their duration, intensity, and the type of cells undergoing pyroptosis within TME.

Omicron Spike confers enhanced infectivity and interferon resistance to SARS-CoV-2 in human nasal tissue.

Omicron emerged following COVID-19 vaccination campaigns, displaced previous SARS-CoV-2 variants of concern worldwide, and gave rise to lineages that continue to spread. Here, we show that Omicron exhibits increased infectivity in primary adult upper airway tissue relative to Delta. Using recombinant forms of SARS-CoV-2 and nasal epithelial cells cultured at the liquid-air interface, enhanced infectivity maps to the step of cellular entry and evolved recently through mutations unique to Omicron Spike. Unlike earlier variants of SARS-CoV-2, Omicron enters nasal cells independently of serine transmembrane proteases and instead relies upon metalloproteinases to catalyze membrane fusion. This entry pathway unlocked by Omicron Spike enables evasion of constitutive and interferon-induced antiviral factors that restrict SARS-CoV-2 entry following attachment. Therefore, the increased transmissibility exhibited by Omicron in humans may be attributed not only to its evasion of vaccine-elicited adaptive immunity, but also to its superior invasion of nasal epithelia and resistance to the cell-intrinsic barriers present therein.

One-step electrodeposited Ni3S2/Co9S8/NiS composite on Ni foam as high-performance electrode for supercapacitors.

Transition metal sulfides (TMSs) are considered as one of the promising electrode materials due to their fascinating redox reversibility and electronic conductivity. However, volume expansion during the charge/discharge process impedes their practical applications. The reasonable design of TMS electrode materials with unique morphology can improve the energy storage performance. Herein, we prepared the Ni3S2/Co9S8/NiS composite that is in situ grown on Ni foam (NF) via a one-step electrodeposition process. The optimized Ni3S2/Co9S8/NiS-7 shows a superhigh specific capacity of 2785.3 F g-1 at 1 A g-1 and remarkable rate capability. Furthermore, the as-assembled device displays a high energy density of 40.1 W h kg-1 at a power density of 799.3 W kg-1 and a satisfactory stability of 96.6% retention after 5000 cycles. This work provides a facile way to fabricate new TMS electrode materials for high-performance supercapacitors.

GINS4 suppresses ferroptosis by antagonizing p53 acetylation with Snail.

Ferroptosis is an iron-dependent oxidative, nonapoptotic form of regulated cell death caused by the destruction of redox homeostasis. Recent studies have uncovered complex cellular networks that regulate ferroptosis. GINS4 is a promoter of eukaryotic G1/S-cell cycle as a regulator of initiation and elongation of DNA replication, but little is known about its impact on ferroptosis. Here, we found that GINS4 was involved in the regulation of ferroptosis in lung adenocarcinoma (LUAD). CRISPR/Cas9-mediated GINS4 KO facilitated ferroptosis. Interestingly, depletion of GINS4 could effectively induce G1, G1/S, S, and G2/M cells to ferroptosis, especially for G2/M cells. Mechanistically, GINS4 suppressed p53 stability through activating Snail that antagonized the acetylation of p53, and p53 lysine residue 351 (K351 for human p53) was the key site for GINS4-suppressed p53-mediated ferroptosis. Together, our data demonstrate that GINS4 is a potential oncogene in LUAD that functions to destabilize p53 and then inhibits ferroptosis, providing a potential therapeutic target for LUAD.

Survival rate prediction of nasopharyngeal carcinoma patients based on MRI and gene expression using a deep neural network.

To achieve a better treatment regimen and follow-up assessment design for intensity-modulated radiotherapy (IMRT)-treated nasopharyngeal carcinoma (NPC) patients, an accurate progression-free survival (PFS) time prediction algorithm is needed. We propose developing a PFS prediction model of NPC patients after IMRT treatment using a deep learning method and comparing that with the traditional texture analysis method. One hundred and fifty-one NPC patients were included in this retrospective study. T1-weighted, proton density and dynamic contrast-enhanced magnetic resonance (MR) images were acquired. The expression level of five genes (HIF-1α, EGFR, PTEN, Ki-67, and VEGF) and infection of Epstein-Barr (EB) virus were tested. A residual network was trained to predict PFS from MR images. The output as well as patient characteristics were combined using a linear regression model to provide a final PFS prediction. The prediction accuracy was compared with that of the traditional texture analysis method. A regression model combining the deep learning output with HIF-1α expression and Epstein-Barr infection provides the best PFS prediction accuracy (Spearman correlation R2  = 0.53; Harrell's C-index = 0.82; receiver operative curve [ROC] analysis area under the curve [AUC] = 0.88; log-rank test hazard ratio [HR] = 8.45), higher than a regression model combining texture analysis with HIF-1α expression (Spearman correlation R2  = 0.14; Harrell's C-index =0.68; ROC analysis AUC = 0.76; log-rank test HR = 2.85). The deep learning method does not require a manually drawn tumor region of interest. MR image processing using deep learning combined with patient characteristics can provide accurate PFS prediction for nasopharyngeal carcinoma patients and does not rely on specific kernels or tumor regions of interest, which is needed for the texture analysis method.

Roles of Phosphorylation of N-Methyl-D-Aspartate Receptor in Chronic Pain.

Phosphorylation of N-methyl-D-aspartate receptor (NMDAR) is widely regarded as a vital modification of synaptic function. Various protein kinases are responsible for direct phosphorylation of NMDAR, such as cyclic adenosine monophosphate-dependent protein kinase A, protein kinase C, Ca2+/calmodulin-dependent protein kinase II, Src family protein tyrosine kinases, cyclin-dependent kinase 5, and casein kinase II. The detailed function of these kinases on distinct subunits of NMDAR has been reported previously and contributes to phosphorylation at sites predominately within the C-terminal of NMDAR. Phosphorylation underlies both structural and functional changes observed in chronic pain, and studies have demonstrated that inhibitors of kinases are significantly effective in alleviating pain behavior in different chronic pain models. In addition, the exploration of drugs that aim to disrupt the interaction between kinases and NMDAR is promising in clinical research. Based on research regarding the modulation of NMDAR in chronic pain models, this review provides an overview of the phosphorylation of NMDAR-related mechanisms underlying chronic pain to elucidate molecular and pharmacologic references for chronic pain management.

Cotton straw biochar and compound Bacillus biofertilizer reduce Cd stress on cotton root growth by regulating root exudates and antioxidant enzymes system.

Introduction: Cotton straw biochar (biochar) and compound Bacillus biofertilizer (biofertilizer) have attracted wide attentions in the remediation of heavy metal-contaminated soils in recent years. However, few studies have explored the metabolomics of lateral roots of Cd-stressed cotton to determine the mechanism of biochar and biofertilizer alleviating Cd stress. Methods: In this pot experiment, biochar and biofertilizer were applied to the soils with different Cd contamination levels (1, 2, and 4 mg kg-1). Then, the responses of cotton root morphology, vitality, Cd content, and antioxidant enzyme activities were analyzed, and the mechanism of biochar and biofertilizer alleviating Cd stress was determined by metabolomic analysis. Results: The results showed that exogenous Cd addition decreased the SOD and POD activities in cotton taproot and lateral root. Besides, with the increase of soil Cd content, the maximum Cd content in taproot (0.0250 mg kg-1) and lateral root (0.0288 mg kg-1) increased by 89.11% and 33.95%, respectively compared with those in the control (p< 0.05). After the application of biochar and biofertilizer, the SOD and POD activities in cotton taproot and lateral root increased. The Cd content of cotton taproot in biochar and biofertilizer treatments decreased by 16.36% and 19.73%, respectively, and that of lateral root decreased by 13.99% and 16.68%, respectively. The metabolomic analysis results showed that the application of biochar and biofertilizer could improve the resistance of cotton root to Cd stress through regulating the pathways of ABC transporters and phenylalanine metabolism. Discussion: Therefore, the application of biochar and biofertilizer could improve cotton resistance to Cd stress by increasing antioxidant enzyme activities, regulating root metabolites (phenols and amino acids), and reducing Cd content, thus promoting cotton root growth.

Dynamic contrast-enhanced magnetic resonance imaging-based radiomics for the prediction of progression-free survival in advanced nasopharyngeal carcinoma.

To establish a multidimensional nomogram model for predicting progression-free survival (PFS) and risk stratification in patients with advanced nasopharyngeal carcinoma (NPC). This retrospective cross-sectional study included 156 patients with advanced NPC who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Radiomic features were extracted from the efflux rate constant (Ktrans ) and extracellular extravascular volume (Ve ) mapping derived from DCE-MRI. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied for feature selection. The Radscore was constructed using the selected features with their respective weights in the LASSO Cox regression analysis. A nomogram model combining the Radscore and clinical factors was built using multivariate Cox regression analysis. The C-index was used to assess the discrimination power of the Radscore and nomogram. The Kaplan-Meier method was used for survival analysis. Of the 360 radiomic features, 28 were selected (7, 6, and 15 features extracted from Ktrans , Ve, and Ktrans +Ve images, respectively). The combined Radscore k trans +Ve (C-index, 0.703, 95% confidence interval [CI]: 0.571-0.836) showed higher efficacy in predicting the prognosis of advanced NPC than Radscore k trans (C-index, 0.693; 95% CI, 0.560-0.826) and Radscore Ve (C-index, 0.614; 95% CI, 0.481-0.746) did. Multivariable Cox regression analysis revealed clinical stage, T stage, and treatment with nimotuzumab as risk factors for PFS. The nomogram established by Radscore k trans +Ve and risk factors (C-index, 0.732; 95% CI: 0.599-0.864) was better than Radscore k trans +Ve in predicting PFS in patients with advanced NPC. A lower Radscore k trans +Ve (HR 3.5584, 95% CI 2.1341-5.933), lower clinical stage (hazard ratio [HR] 1.5982, 95% CI 0.5262-4.854), lower T stage (HR 1.4365, 95% CI 0.6745-3.060), and nimotuzumab (NTZ) treatment (HR 0.7879, 95% CI 0.4899-1.267) were associated with longer PFS. Kaplan-Meier analysis showed a lower PFS in the high-risk group than in the low-risk group (p<0.0001). The nomogram based on combined pretreatment DCE-MRI radiomics features, NTZ, and clinicopathological risk factors may be considered as a noninvasive imaging marker for predicting individual PFS in patients with advanced NPC.

CuCoNi-S anchored CoMoO4/MoO3 forming core-shell structure for high-performance asymmetric supercapacitors.

Although the preparation of transition metal sulfides/oxides electrodes has been relatively perfected, it is still challenging to fabricate multi-component transition metal sulfides/oxides core-shell structure electrodes with excellent electrochemical performance. Herein, CoMoO4/MoO3@CuCoNi-S grown on nickel foam (NF) is first synthesized via facile hydrothermal and electrodeposition methods. The CoMoO4/MoO3@CuCoNi-S electrode presents an exceptional specific capacitance (2600.0 F g-1 at 1 A g-1) and 68.3% of its initial capacitance at 10 A g-1. Moreover, a CoMoO4/MoO3@CuCoNi-S//active carbon (AC) device is assembled for determining its electrochemical application. It reveals a high energy density of 42.1 W h kg-1 at a power density of 800.2 W kg-1, an extended voltage window of 1.6 V and excellent stability with 96.9% retention after 5000 cycles at 2 A g-1. This work offers a reference case for the development of multi-component transition metal sulfides/oxides core-shell structure composites for energy storage.

Rapalogs downmodulate intrinsic immunity and promote cell entry of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in immunocompromised individuals is associated with prolonged virus shedding and evolution of viral variants. Rapamycin and its analogs (rapalogs, including everolimus, temsirolimus, and ridaforolimus) are FDA approved as mTOR inhibitors for the treatment of human diseases, including cancer and autoimmunity. Rapalog use is commonly associated with an increased susceptibility to infection, which has been traditionally explained by impaired adaptive immunity. Here, we show that exposure to rapalogs increased susceptibility to SARS-CoV-2 infection in tissue culture and in immunologically naive rodents by antagonizing the cell-intrinsic immune response. We identified 1 rapalog (ridaforolimus) that was less potent in this regard and demonstrated that rapalogs promote spike-mediated entry into cells, by triggering the degradation of the antiviral proteins IFITM2 and IFITM3 via an endolysosomal remodeling program called microautophagy. Rapalogs that increased virus entry inhibited mTOR-mediated phosphorylation of the transcription factor TFEB, which facilitated its nuclear translocation and triggered microautophagy. In rodent models of infection, injection of rapamycin prior to and after virus exposure resulted in elevated SARS-CoV-2 replication and exacerbated viral disease, while ridaforolimus had milder effects. Overall, our findings indicate that preexisting use of certain rapalogs may elevate host susceptibility to SARS-CoV-2 infection and disease by activating lysosome-mediated suppression of intrinsic immunity.

A machine-learning approach using pubic CT based on radiomics to estimate adult ages.

PURPOSE: Adult skeletal age estimation is an active research field. To evaluate the performance of a pubic CT radiomics-based machine learning model for estimating age, we established a multiple linear regression model based on radiomics and machine learning methods. METHODS: A total of 355 subjects were enrolled in this retrospective study from August 2016 to August 2021, and divided into a training cohort (N = 325) and a testing cohort (N = 30). Computerized texture analysis of the semi-automatically segmentation was performed and 107 texture features were extracted from the regions. Then we used univariate linear regression and multivariate stepwise regression to assess correlations of texture parameters with age. The most vital features were used to make the best predictive model. Eventually, the established radiomics model was tested with an additional 30 patients. RESULTS: Clinical characteristics include age, sex, height, weight and BMI were not statistically significant different between training and testing cohort (p = 0.098-0.888). Through a multivariate regression analysis using stepwise regression, six texture parameters were found to have significant correlations with age. The regression formula estimating the age was constructed. CONCLUSIONS: The radiomics model using machine learning is considered as a new approach forage estimation frompubic symphysis CT features.Digital osteology is obtained in a non-invasive way so that it can be an ideal collection for anthropological studies.