The single-cell opioid responses in the context of HIV (SCORCH) consortium.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

The miR6445-NAC029 module regulates drought tolerance by regulating the expression of glutathione S-transferase U23 and reactive oxygen species scavenging in Populus.

MicroRNAs are essential in plant development and stress resistance, but their specific roles in drought stress require further investigation. Here, we have uncovered that a Populus-specific microRNAs (miRNA), miR6445, targeting NAC (NAM, ATAF, and CUC) family genes, is involved in regulating drought tolerance of poplar. The expression level of miR6445 was significantly upregulated under drought stress; concomitantly, seven targeted NAC genes showed significant downregulation. Silencing the expression of miR6445 by short tandem target mimic technology significantly decreased the drought tolerance in poplar. Furthermore, 5' RACE experiments confirmed that miR6445 directly targeted NAC029. The overexpression lines of PtrNAC029 (OE-NAC029) showed increased sensitivity to drought compared with knockout lines (Crispr-NAC029), consistent with the drought-sensitive phenotype observed in miR6445-silenced strains. PtrNAC029 was further verified to directly bind to the promoters of glutathione S-transferase U23 (GSTU23) and inhibit its expression. Both Crispr-NAC029 and PtrGSTU23 overexpressing plants showed higher levels of PtrGSTU23 transcript and GST activity while accumulating less reactive oxygen species (ROS). Moreover, poplars overexpressing GSTU23 demonstrated enhanced drought tolerance. Taken together, our research reveals the crucial role of the miR6445-NAC029-GSTU23 module in enhancing poplar drought tolerance by regulating ROS homeostasis. This finding provides new molecular targets for improving the drought resistance of trees.

Characterization of primary small intestinal lymphoma: a retrospective study based on double balloon endoscopy.

BACKGROUND: The diagnosis of primary small intestinal lymphoma (PSIL) is difficult. This study aimed to evaluate the clinical, radiological and endoscopic characteristics of PSIL and provide clue for diagnosis. METHODS: A total of 30 patients diagnosed with PSIL who underwent double balloon endoscopy (DBE) in the First Affiliated Hospital of Zhejiang University were retrospectively analyzed. Clinical, radiological and endoscopic data were collected. Univariate analysis was used to determine significant indicators for differentiating three main subtypes of PSIL. Cox regression analysis was performed to assess the risk factors for survival. RESULTS: In this study, 10 patients were pathologically diagnosed as diffuse large B-cell lymphoma (DLBCL), 11 were indolent B-cell lymphoma (BCL) and 9 were T-cell lymphoma (TCL). Compared with DLBCL patients, the body mass index (BMI) of TCL patients was significantly lower (p = 0.004). Meanwhile, compared with patients with DLBCL, the patients with indolent BCL had lower levels of C-reactive protein, lactate dehydrogenase (LDH), fibrinogen and D-Dimer (p = 0.004, p = 0.004, p = 0.006, and p = 0.002, respectively), and lower proportion of thicker intestinal wall and aneurysmal dilation in CT scan (p = 0.003 and p = 0.020, respectively). In terms of ulcer morphology, patients with DLBCL had significantly higher proportion of deep ulcers than patients with indolent BCL (p = 0.020, respectively). Cox regression analysis showed that drink (p = 0.034), concomitant colonic ulcers (p = 0.034) and elevated LDH (p = 0.043) are risk factors for mortality in patients with PSIL. CONCLUSIONS: This study provides clinical characteristics of patients with PSIL. Thicker intestinal wall and aneurismal dilation detected on CT scan and deeper ulcer on DBE examination helps to establish a diagnosis of DLBCL.

HIV Infection Drives Foam Cell Formation via NLRP3 Inflammasome Activation.

Persistent immune activation is linked to an increased risk of cardiovascular disease (CVD) in people with HIV (PWH) on antiretroviral therapy (ART). The NLRP3 inflammasome may contribute to elevated CVD risk in PWH. This study utilized peripheral blood mononuclear cells (PBMCs) from 25 PWH and 25 HIV-negative controls, as well as HIV in vitro infections. Transcriptional changes were analyzed using RNAseq and pathway analysis. Our results showed that in vitro HIV infection of macrophages and PBMCs from PWH had increased foam cell formation and expression of the NLRP3 inflammasome components and downstream cytokines (caspase-1, IL-1ß, and IL-18), which was reduced with inhibition of NLRP3 activity using MCC950. Transcriptomic analysis revealed an increased expression of multiple genes involved in lipid metabolism, cholesterol storage, coronary microcirculation disorders, ischemic events, and monocyte/macrophage differentiation and function with HIV infection and oxLDL treatment. HIV infection and NLRP3 activation increased foam cell formation and expression of proinflammatory cytokines, providing insights into the mechanisms underlying HIV-associated atherogenesis. This study suggests that HIV itself may contribute to increased CVD risk in PWH. Understanding the involvement of the inflammasome pathway in HIV atherosclerosis can help identify potential therapeutic targets to mitigate cardiovascular risks in PWH.

Quality prediction of whole-grain rice noodles using backpropagation artificial neural network.

BACKGROUND: Whole-grain rice noodles are a kind of healthy food with rich nutritional value, and their product quality has a notable impact on consumer acceptability. The quality evaluation model is of great significance to the optimization of product quality. However, there are few methods that can establish a product quality prediction model with multiple preparation conditions as inputs and various quality evaluation indexes as outputs. In this study, an artificial neural network (ANN) model based on a backpropagation (BP) algorithm was used to predict the comprehensive quality changes of whole-grain rice noodles under different preparation conditions, which provided a new way to improve the quality of extrusion rice products. RESULTS: The results showed that the BP-ANN using the Levenberg-Marquardt algorithm and the optimal topology (4-11-8) gave the best performance. The correlation coefficients (R2) for the training, validation, testing, and global data sets of the BP neural network were 0.927, 0.873, 0.817, and 0.903, respectively. In the validation test, the percentage error in the quality prediction of whole-grain rice noodles was within 10%, indicating that the BP-ANN could accurately predict the quality of whole-grain rice noodles prepared under different conditions. CONCLUSION: This study showed that the quality prediction model of whole-grain rice noodles based on the BP-ANN algorithm was effective, and suitable for predicting the quality of whole-grain rice noodles prepared under different conditions. © 2024 Society of Chemical Industry.

Antiretroviral Therapy Ameliorates Simian Immunodeficiency Virus-Associated Myocardial Inflammation by Dampening Interferon Signaling and Pathogen Response in the Heart.

People with human immunodeficiency virus have an increased risk of developing cardiovascular disease. RNA-Seq was performed on hearts from simian immunodeficiency virus (SIV)-infected rhesus macaques with or without antiretroviral therapy (ART). SIV infection led to high plasma viral load with very little myocardial viral RNA. SIV infection promoted an inflammatory environment in the heart through interferon and pathogen signaling, in the absence of myocardial viral RNA. While ART dampened interferon and cytokine response in the heart, SIV-infected animals receiving ART had deficits in the expression of genes directly involved in fatty acid metabolism relative to SIV-uninfected animals.

Aspartyl tRNA-synthetase (AspRS) gene family enhances drought tolerance in poplar through BABA-PtrIBIs-PtrVOZ signaling module.

BACKGROUND: Drought stress is a prevalent abiotic stress that significantly hinders the growth and development of plants. According to studies, ß-aminobutyric acid (BABA) can influence the ABA pathway through the AtIBI1 receptor gene to enhance cold resistance in Arabidopsis. However, the Aspartate tRNA-synthetase (AspRS) gene family, which acts as the receptor for BABA, has not yet been investigated in poplar. Particularly, it is uncertain how the AspRS gene family (PtrIBIs)r can resist drought stress after administering various concentrations of BABA to poplar. RESULTS: In this study, we have identified 12 AspRS family genes and noted that poplar acquired four PtrIBI pairs through whole genome duplication (WGD). We conducted cis-action element analysis and found a significant number of stress-related action elements on different PtrIBI genes promoters. The expression of most PtrIBI genes was up-regulated under beetle and mechanical damage stresses, indicating their potential role in responding to leaf damage stress. Our results suggest that a 50 mM BABA treatment can alleviate the damage caused by drought stress in plants. Additionally, via transcriptome sequencing, we observed that the partial up-regulation of BABA receptor genes, PtrIBI2/4/6/8/11, in poplars after drought treatment. We hypothesize that poplar responds to drought stress through the BABA-PtrIBIs-PtrVOZ coordinated ABA signaling pathway. Our research provides molecular evidence for understanding how plants respond to drought stress through external application of BABA. CONCLUSIONS: In summary, our study conducted genome-wide analysis of the AspRS family of P. trichocarpa and identified 12 PtrIBI genes. We utilized genomics and bioinformatics to determine various characteristics of PtrIBIs such as chromosomal localization, evolutionary tree, gene structure, gene doubling, promoter cis-elements, and expression profiles. Our study found that certain PtrIBI genes are regulated by drought, beetle, and mechanical damage implying their crucial role in enhancing poplar stress tolerance. Additionally, we observed that external application of low concentrations of BABA increased plant drought resistance under drought stress. Through the BABA-PtrIBIs-PtrVOZ signaling module, poplar plants were able to transduce ABA signaling and regulate their response to drought stress. These results suggest that the PtrIBI genes in poplar have the potential to improve drought tolerance in plants through the topical application of low concentrations of BABA.

MyD88 in myofibroblasts regulates aerobic glycolysis-driven hepatocarcinogenesis via ERK-dependent PKM2 nuclear relocalization and activation.

Hepatic stellate cells (HSCs) and cancer-associated fibroblasts (CAFs) play critical roles in liver fibrosis and hepatocellular carcinoma (HCC). MyD88 controls the expression of several key modifier genes in liver tumorigenesis; however, whether and how MyD88 in myofibroblasts contributes to the development of fibrosis-associated liver cancer remains elusive. Here, we used an established hepatocarcinogenesis mouse model involving apparent liver fibrogenesis in which MyD88 was selectively depleted in myofibroblasts. Myofibroblast MyD88-deficient (Fib-MyD88 KO) mice developed significantly fewer and smaller liver tumor nodules. MyD88 deficiency in myofibroblasts attenuated liver fibrosis and aerobic glycolysis in hepatocellular carcinoma tissues. Mechanistically, MyD88 signaling in myofibroblasts increased the secretion of CCL20, which promoted aerobic glycolysis in cancer cells. This process was dependent on the CCR6 receptor and ERK/PKM2 signaling. Furthermore, liver tumor growth was greatly relieved when the mice were treated with a CCR6 inhibitor. Our data revealed a critical role for MyD88 in myofibroblasts in the promotion of hepatocellular carcinoma by affecting aerobic glycolysis in cancer cells and might provide a potential molecular therapeutic target for HCC. © 2021 The Pathological Society of Great Britain and Ireland.

Critical contributions of protein cargos to the functions of macrophage-derived extracellular vesicles.

BACKGROUND: Macrophages are highly plastic innate immune cells that play key roles in host defense, tissue repair, and homeostasis maintenance. In response to divergent stimuli, macrophages rapidly alter their functions and manifest a wide polarization spectrum with two extremes: M1 or classical activation and M2 or alternative activation. Extracellular vesicles (EVs) secreted from differentially activated macrophages have been shown to have diverse functions, which are primarily attributed to their microRNA cargos. The role of protein cargos in these EVs remains largely unexplored. Therefore, in this study, we focused on the protein cargos in macrophage-derived EVs. RESULTS: Naïve murine bone marrow-derived macrophages were treated with lipopolysaccharide or interlukin-4 to induce M1 or M2 macrophages, respectively. The proteins of EVs and their parental macrophages were subjected to quantitative proteomics analyses, followed by bioinformatic analyses. The enriched proteins of M1-EVs were involved in proinflammatory pathways and those of M2-EVs were associated with immunomodulation and tissue remodeling. The signature proteins of EVs shared a limited subset of the proteins of their respective progenitor macrophages, but they covered many of the typical pathways and functions of their parental cells, suggesting their respective M1-like and M2-like phenotypes and functions. Experimental examination validated that protein cargos in M1- or M2-EVs induced M1 or M2 polarization, respectively. More importantly, proteins in M1-EVs promoted viability, proliferation, and activation of T lymphocytes, whereas proteins in M2-EVs potently protected the tight junction structure and barrier integrity of epithelial cells from disruption. Intravenous administration of M2-EVs in colitis mice led to their accumulation in the colon, alleviation of colonic inflammation, promotion of M2 macrophage polarization, and improvement of gut barrier functions. Protein cargos in M2-EVs played a key role in their protective function in colitis. CONCLUSION: This study has yielded a comprehensive unbiased dataset of protein cargos in macrophage-derived EVs, provided a systemic view of their potential functions, and highlighted the important engagement of protein cargos in the pathophysiological functions of these EVs.

Clinical-radiomics predictors to identify the suitability of transarterial chemoembolization treatment in intermediate-stage hepatocellular carcinoma: A multicenter study.

BACKGROUND: Although transarterial chemoembolization (TACE) is the first-line therapy for intermediate-stage hepatocellular carcinoma (HCC), it is not suitable for all patients. This study aimed to determine how to select patients who are not suitable for TACE as the first treatment choice. METHODS: A total of 243 intermediate-stage HCC patients treated with TACE at three centers were retrospectively enrolled, of which 171 were used for model training and 72 for testing. Radiomics features were screened using the Spearman correlation analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, a radiomics model was established using extreme gradient boosting (XGBoost) with 5-fold cross-validation. The Shapley additive explanations (SHAP) method was used to visualize the radiomics model. A clinical model was constructed using univariate and multivariate logistic regression. The combined model comprising the radiomics signature and clinical factors was then established. This model's performance was evaluated by discrimination, calibration, and clinical application. Generalization ability was evaluated by the testing cohort. Finally, the model was used to analyze overall and progression-free survival of different groups. RESULTS: A third of the patients (81/243) were unsuitable for TACE treatment. The combined model had a high degree of accuracy as it identified TACE-unsuitable cases, at a sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 0.759, 0.885, 0.906 [95% confidence interval (CI): 0.859-0.953] in the training cohort and 0.826, 0.776, and 0.894 (95% CI: 0.815-0.972) in the testing cohort, respectively. CONCLUSIONS: The high degree of accuracy of our clinical-radiomics model makes it clinically useful in identifying intermediate-stage HCC patients who are unsuitable for TACE treatment.

Genome-Wide Analysis of the FBA Subfamily of the Poplar F-Box Gene Family and Its Role under Drought Stress.

F-box proteins are important components of eukaryotic SCF E3 ubiquitin ligase complexes, which specifically determine protein substrate proteasomal degradation during plant growth and development, as well as biotic and abiotic stress. It has been found that the FBA (F-box associated) protein family is one of the largest subgroups of the widely prevalent F-box family and plays significant roles in plant development and stress response. However, the FBA gene family in poplar has not been systematically studied to date. In this study, a total of 337 F-box candidate genes were discovered based on the fourth-generation genome resequencing of P. trichocarpa. The domain analysis and classification of candidate genes revealed that 74 of these candidate genes belong to the FBA protein family. The poplar F-box genes have undergone multiple gene replication events, particularly in the FBA subfamily, and their evolution can be attributed to genome-wide duplication (WGD) and tandem duplication (TD). In addition, we investigated the P. trichocarpa FBA subfamily using the PlantGenIE database and quantitative real-time PCR (qRT-PCR); the results showed that they are expressed in the cambium, phloem and mature tissues, but rarely expressed in young leaves and flowers. Moreover, they are also widely involved in the drought stress response. At last, we selected and cloned PtrFBA60 for physiological function analysis and found that it played an important role in coping with drought stress. Taken together, the family analysis of FBA genes in P. trichocarpa provides a new opportunity for the identification of P. trichocarpa candidate FBA genes and elucidation of their functions in growth, development and stress response, thus demonstrating their utility in the improvement of P. trichocarpa.

Population pharmacokinetics of valproic acid in adult Chinese patients with bipolar disorder.

PURPOSE: To develop and validate a population pharmacokinetic (PPK) model of valproic acid (VPA) in adult Chinese patients with bipolar disorder, and provide guidance for individualized therapy in this population. METHODS: A total of 1104 serum concentrations from 272 patients were collected in this study. The data analysis was performed using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, biological characteristics, and concomitant medications. Bootstrap validation (1000 runs), normalized prediction distribution error (NPDE), and external validation of 50 patients were employed to evaluate the final model. RESULTS: A one-compartment model with first-order absorption and elimination was developed for VPA extended-release tablets. VPA clearance was significantly influenced by three variables: sex (12% higher in male patients), daily dose (increasing with the 0.13 exponent), and body weight (increasing with the 0.56 exponent). Typical values for the absorption rate constant (Ka), apparent clearance (CL/F), and apparent distribution volume (V/F) for a female patient weighing 70 kg administered VPA 1000 mg/day were 0.18 h-1, 0.46 L/h, and 12.84 L, respectively. The results of model evaluation indicated a good stable and precise performance of the final model. CONCLUSIONS: A qualified PPK model of VPA was developed in Chinese patients with bipolar disorder. This model could be used as a suitable tool for the personalization of VPA dosing for bipolar patients.

Reversing the immunosuppressive microenvironment with reduced redox level by microwave-chemo-immunostimulant Ce-Mn MOF for improved immunotherapy.

BACKGROUNDS: Reversing the immunosuppressive tumor microenvironment (TME) in the tumor is widely deemed to be an effective strategy to improve immune therapy. In particular, the redox balance in TME needs to be well controlled due to its critical role in mediating the functions of various cells, including cancer cells and immune-suppressive cells. RESULTS: Here, we propose an efficient strategy to reshape the redox homeostasis to reverse immunosuppressive TME. Specifically, we developed a microwave-chemo-immunostimulant CMMCP to promote the infiltration of the tumor-T cells by simultaneously reducing the reactive oxygen species (ROS) and glutathione (GSH) and improving the oxygen (O2) levels in TME. The CMMCP was designed by loading chemotherapy drugs cisplatin into the bimetallic Ce-Mn MOF nanoparticles coated with polydopamine. The Ce-Mn MOF nanoparticles can effectively improve the catalytic decomposition of ROS into O2 under microwave irradiation, resulting in overcoming hypoxia and limited ROS generation. Besides, the activity of intracellular GSH in TME was reduced by the redox reaction with Ce-Mn MOF nanoparticles. The reprogrammed TME not only boosts the immunogenic cell death (ICD) induced by cisplatin and microwave hyperthermia but also gives rise to the polarization of pro-tumor M2-type macrophages to the anti-tumor M1-type ones. CONCLUSION: Our in vivo experimental results demonstrate that the microwave-chemo-immunostimulant CMMCP significantly enhances the T cell infiltration and thus improves the antitumor effect. This study presents an easy, safe, and effective strategy for a whole-body antitumor effect after local treatment.

A New Self-Calibration and Compensation Method for Installation Errors of Uniaxial Rotation Module Inertial Navigation System.

Calibration and compensation techniques are essential to improve the accuracy of the strap-down inertial navigation system. Especially for the new uniaxial rotation module inertial navigation system (URMINS), replacing faulty uniaxial rotation modules introduces installation errors between modules and reduces navigation accuracy. Therefore, it is necessary to calibrate these systems effectively and compensate for the installation error between modules. This paper proposes a new self-calibration and compensation method for installation errors without additional information and equipment. Using the attitude, velocity, and position differences between the two sets of navigation information output from URMINS as measurements, a Kalman filter is constructed and the installation error is estimated. After URMINS is compensated for the installation error, the average of the demodulated redundant information is taken to calculate the carrier's navigation information. The simulation results show that the proposed method can effectively assess the installation error between modules with an estimation accuracy better than 5". Experimental results for static navigation show that the accuracy of heading angle and positioning can be improved by 73.12% and 81.19% after the URMINS has compensated for the estimated installation errors. Simulation and experimental results further validate the effectiveness of the proposed self-calibration and compensation method.

Molecular and structural characterization of a promiscuous chalcone synthase from the fern species Stenoloma chusanum.

The key enzymes involved in the flavonoid biosynthesis pathway have been extensively studied in seed plants, but relatively less in ferns. In this study, two 4-Coumarate: coenzyme A ligases (Sc4CL1 and Sc4CL2) and one novel chalcone synthase (ScCHS1) were functionally characterized by mining the Stenoloma chusanum transcriptome database. Recombinant Sc4CLs were able to esterify various hydroxycinnamic acids to corresponding acyl-coenzyme A (CoA). ScCHS1 could catalyze p-coumaroyl-CoA, cinnamoyl-CoA, caffeoyl-CoA, and feruloyl-CoA to form naringenin, pinocembrin, eriodictyol, and homoeriodictyol, respectively. Moreover, enzymatic kinetics studies revealed that the optimal substrates of ScCHS1 were feruloyl-CoA and caffeoyl-CoA, rather than p-coumaroyl-CoA, which was substantially different from the common CHSs. Crystallographic and site-directed mutagenesis experiments indicated that the amino acid residues, Leu87, Leu97, Met165, and Ile200, located in the substrate-binding pocket near the B-ring of products, could exert a significant impact on the unique catalytic activity of ScCHS1. Furthermore, overexpression of ScCHS1 in tt4 mutants could partially rescue the mutant phenotypes. Finally, ScCHS1 and Sc4CL1 were used to synthesize flavanones and flavones with multi-substituted hydroxyl and methoxyl B-ring in Escherichia coli, which can effectively eliminate the need for the cytochrome P450 hydroxylation/O-methyltransferase from simple phenylpropanoid acids. In summary, the identification of these important Stenoloma enzymes provides a springboard for the future production of various flavonoids in E. coli.

In Situ Activatable Ratiometric NIR-II Fluorescence Nanoprobe for Quantitative Detection of H2S in Colon Cancer.

As key characteristic molecules, several H2S-activated probes have been explored for colon cancer studies. However, a few ratiometric fluorescence (FL) probes with NIR-II emissions have been reported for the quantitative detection of H2S in colon cancer in vivo. Here, we developed an in situ H2S-activatable ratiometric nanoprobe with two NIR-II emission signals for the detection of H2S and intelligently lighting up colon cancer. The nanoprobe comprised a down conversion nanoparticle (DCNP), which emitted NIR-II FL at 1550 nm on irradiation with a 980 nm laser (F1550Em, 980Ex). Further, human serum albumin (HSA) was combined with Ag+ on the surface of DCNP to form a DCNP@HSA-Ag+ nanoprobe. In the presence of H2S, Ag2S quantum dots (QDs) were formed in coated HSA, which emitted FL at approximately 1050 nm on irradiation with an 808 nm laser (F1050Em, 808Ex) through an H2S-induced chemical reaction between H2S and Ag+; however, the FL signal of DCNP was stable at 1550 nm (F1550Em, 980Ex), generating a H2S concentration-dependent ratiometric F1050Em, 808Ex/F1550Em, 980Ex signal. The NIR-II ratiometric nanoprobe was successfully used for the accurate quantitative detection of H2S and the detection of the precise location of colon cancer through an endogenous H2S-induced in situ reduction reaction to form Ag2S QDs. Thus, these findings provide a new strategy for the specific detection of targeted molecules and diagnosis of disease based on the in situ-activatable NIR-II ratiometric FL nanoprobe.

Mapping developmental trajectories and subtype diversity of normal and glaucomatous human retinal ganglion cells by single-cell transcriptome analysis.

Glaucoma is characterized by a progressive degeneration of retinal ganglion cells (RGCs), leading to irreversible vision loss. Currently, there is no effective treatment for RGC degeneration. We used a disease-in-a-dish stem cell model to examine the developmental susceptibility of RGCs to glaucomatous degeneration, which may inform on the formulation of therapeutic approaches. Here, we used single-cell transcriptome analysis of SIX6 risk allele (SIX6risk allele ) primary open angle glaucoma patient-specific and control hRGCs to compare developmental trajectories in terms of lineage- and stage-specific transcriptional signature to identify dysregulated stages/genes, and subtype composition to estimate the relative vulnerability of RGCs to degeneration because their ability to regenerate axons are subtype-specific. The developmental trajectories, beginning from neural stem cells to RGCs, were similar between SIX6risk allele and control RGCs. However, the differentiation of SIX6risk allele RGCs was relatively stalled at the retinal progenitor cell stage, compromising the acquisition of mature phenotype and subtype composition, compared with controls, which was likely due to dysregulated mTOR and Notch signaling pathways. Furthermore, SIX6risk allele RGCs, as compared with controls, expressed fewer genes corresponding to RGC subtypes that are preferentially resistant to degeneration. The immature phenotype of SIX6risk allele RGCs with underrepresented degeneration-resistant subtypes may make them vulnerable to glaucomatous degeneration.

Genome-Wide Comprehensive Analysis of the GASA Gene Family in Populus.

Gibberellic acid-stimulated Arabidopsis (GASA) proteins, as cysteine-rich peptides (CRPs), play roles in development and reproduction and biotic and abiotic stresses. Although the GASA gene family has been identified in plants, the knowledge about GASAs in Populus euphratica, the woody model plant for studying abiotic stress, remains limited. Here, we referenced the well-sequenced Populus trichocarpa genome, and identified the GASAs in the whole genome of P. euphratica and P. trichocarpa. 21 candidate genes in P. trichocarpa and 19 candidate genes in P. euphratica were identified and categorized into three subfamilies by phylogenetic analysis. Most GASAs with signal peptides were located extracellularly. The GASA genes in Populus have experienced multiple gene duplication events, especially in the subfamily A. The evolution of the subfamily A, with the largest number of members, can be attributed to whole-genome duplication (WGD) and tandem duplication (TD). Collinearity analysis showed that WGD genes played a leading role in the evolution of GASA genes subfamily B. The expression patterns of P. trichocarpa and P. euphratica were investigated using the PlantGenIE database and the real-time quantitative PCR (qRT-PCR), respectively. GASA genes in P. trichocarpa and P. euphratica were mainly expressed in young tissues and organs, and almost rarely expressed in mature leaves. GASA genes in P. euphratica leaves were also widely involved in hormone responses and drought stress responses. GUS activity assay showed that PeuGASA15 was widely present in various organs of the plant, especially in vascular bundles, and was induced by auxin and inhibited by mannitol dramatically. In summary, this present study provides a theoretical foundation for further research on the function of GASA genes in P. euphratica.

A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis.

Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with worse prognosis for early prevention and medical resource optimisation is important. Here, we proposed a fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis by routinely used computed tomography.We retrospectively collected 5372 patients with computed tomography images from seven cities or provinces. Firstly, 4106 patients with computed tomography images were used to pre-train the deep learning system, making it learn lung features. Following this, 1266 patients (924 with COVID-19 (471 had follow-up for >5 days) and 342 with other pneumonia) from six cities or provinces were enrolled to train and externally validate the performance of the deep learning system.In the four external validation sets, the deep learning system achieved good performance in identifying COVID-19 from other pneumonia (AUC 0.87 and 0.88, respectively) and viral pneumonia (AUC 0.86). Moreover, the deep learning system succeeded to stratify patients into high- and low-risk groups whose hospital-stay time had significant difference (p=0.013 and p=0.014, respectively). Without human assistance, the deep learning system automatically focused on abnormal areas that showed consistent characteristics with reported radiological findings.Deep learning provides a convenient tool for fast screening of COVID-19 and identifying potential high-risk patients, which may be helpful for medical resource optimisation and early prevention before patients show severe symptoms.

Radiomics in liver diseases: Current progress and future opportunities.

Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have become an increasingly significant health problem worldwide. Noninvasive imaging plays a critical role in the clinical workflow of liver diseases, but conventional imaging assessment may provide limited information. Accurate detection, characterization and monitoring remain challenging. With progress in quantitative imaging analysis techniques, radiomics emerged as an efficient tool that shows promise to aid in personalized diagnosis and treatment decision-making. Radiomics could reflect the heterogeneity of liver lesions via extracting high-throughput and high-dimensional features from multi-modality imaging. Machine learning algorithms are then used to construct clinical target-oriented imaging biomarkers to assist disease management. Here, we review the methodological process in liver disease radiomics studies in a stepwise fashion from data acquisition and curation, region of interest segmentation, liver-specific feature extraction, to task-oriented modelling. Furthermore, the applications of radiomics in liver diseases are outlined in aspects of diagnosis and staging, evaluation of liver tumour biological behaviours, and prognosis according to different disease type. Finally, we discuss the current limitations of radiomics in liver disease studies and explore its future opportunities.