Paradoxes of Cellular SUMOylation Regulation: A Role of Biomolecular Condensates?

Protein SUMOylation is a major post-translational modification essential for maintaining cellular homeostasis. SUMOylation has long been associated with stress responses as a diverse array of cellular stress signals are known to trigger rapid alternations in global protein SUMOylation. In addition, while there are large families of ubiquitination enzymes, all small ubiquitin-like modifiers (SUMOs) are conjugated by a set of enzymatic machinery comprising one heterodimeric SUMO-activating enzyme, a single SUMO-conjugating enzyme, and a small number of SUMO protein ligases and SUMO-specific proteases. How a few SUMOylation enzymes specifically modify thousands of functional targets in response to diverse cellular stresses remains an enigma. Here we review recent progress toward understanding the mechanisms of SUMO regulation, particularly the potential roles of liquid-liquid phase separation/biomolecular condensates in regulating cellular SUMOylation during cellular stresses. In addition, we discuss the role of protein SUMOylation in pathogenesis and the development of novel therapeutics targeting SUMOylation. SIGNIFICANCE STATEMENT: Protein SUMOylation is one of the most prevalent post-translational modifications and plays a vital role in maintaining cellular homeostasis in response to stresses. Protein SUMOylation has been implicated in human pathogenesis, such as cancer, cardiovascular diseases, neurodegeneration, and infection. After more than a quarter century of extensive research, intriguing enigmas remain regarding the mechanism of cellular SUMOylation regulation and the therapeutic potential of targeting SUMOylation.

Protein SUMOylation promotes cAMP-independent EPAC1 activation.

Protein SUMOylation is a prevalent stress-response posttranslational modification crucial for maintaining cellular homeostasis. Herein, we report that protein SUMOylation modulates cellular signaling mediated by cAMP, an ancient and universal stress-response second messenger. We identify K561 as a primary SUMOylation site in exchange protein directly activated by cAMP (EPAC1) via site-specific mapping of SUMOylation using mass spectrometry. Sequence and site-directed mutagenesis analyses reveal that a functional SUMO-interacting motif in EPAC1 is required for the binding of SUMO-conjugating enzyme UBC9, formation of EPAC1 nuclear condensate, and EPAC1 cellular SUMOylation. Heat shock-induced SUMO modification of EPAC1 promotes Rap1/2 activation in a cAMP-independent manner. Structural modeling and molecular dynamics simulation studies demonstrate that SUMO substituent on K561 of EPAC1 promotes Rap1 interaction by increasing the buried surface area between the SUMOylated receptor and its effector. Our studies identify a functional SUMOylation site in EPAC1 and unveil a novel mechanism in which SUMOylation of EPAC1 leads to its autonomous activation. The findings of SUMOylation-mediated activation of EPAC1 not only provide new insights into our understanding of cellular regulation of EPAC1 but also will open up a new field of experimentation concerning the cross-talk between cAMP/EPAC1 signaling and protein SUMOylation, two major cellular stress response pathways, during cellular homeostasis.

A multi-parametric prognostic model based on clinicopathologic features: vessels encapsulating tumor clusters and hepatic plates predict overall survival in hepatocellular carcinoma patients.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) is a newly described vascular pattern that is distinct from microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Despite its importance, the current pathological diagnosis report does not include information on VETC and hepatic plates (HP). We aimed to evaluate the prognostic value of integrating VETC and HP (VETC-HP model) in the assessment of HCC. METHODS: A total of 1255 HCC patients who underwent radical surgery were classified into training (879 patients) and validation (376 patients) cohorts. Additionally, 37 patients treated with lenvatinib were studied, included 31 patients in high-risk group and 6 patients in low-risk group. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to establish a prognostic model for the training set. Harrell's concordance index (C-index), time-dependent receiver operating characteristics curve (tdROC), and decision curve analysis were utilized to evaluate our model's performance by comparing it to traditional tumor node metastasis (TNM) staging for individualized prognosis. RESULTS: A prognostic model, VETC-HP model, based on risk scores for overall survival (OS) was established. The VETC-HP model demonstrated robust performance, with area under the curve (AUC) values of 0.832 and 0.780 for predicting 3- and 5-year OS in the training cohort, and 0.805 and 0.750 in the validation cohort, respectively. The model showed superior prediction accuracy and discrimination power compared to TNM staging, with C-index values of 0.753 and 0.672 for OS and disease-free survival (DFS) in the training cohort, and 0.728 and 0.615 in the validation cohort, respectively, compared to 0.626 and 0.573 for TNM staging in the training cohort, and 0.629 and 0.511 in the validation cohort. Thus, VETC-HP model had higher C-index than TNM stage system(p < 0.01).Furthermore, in the high-risk group, lenvatinib alone appeared to offer less clinical benefit but better disease-free survival time. CONCLUSIONS: The VETC-HP model enhances DFS and OS prediction in HCC compared to traditional TNM staging systems. This model enables personalized temporal survival estimation, potentially improving clinical decision-making in surveillance management and treatment strategies.

NPTX2 in Cerebrospinal Fluid Predicts the Progression From Normal Cognition to Mild Cognitive Impairment.

OBJECTIVE: This study examined whether cerebrospinal fluid (CSF) baseline levels of the synaptic protein NPTX2 predict time to onset of symptoms of mild cognitive impairment (MCI), both alone and when accounting for traditional CSF Alzheimer's disease (AD) biomarker levels. Longitudinal NPTX2 levels were also examined. METHODS: CSF was collected longitudinally from 269 cognitively normal BIOCARD Study participants (mean baseline age = 57.7 years; mean follow-up = 16.3 years; n = 77 progressed to MCI/dementia). NPTX2 levels were measured from 3 correlated peptides using quantitative parallel reaction monitoring mass spectrometry. Levels of Aß42 /Aß40 , p-tau181 , and t-tau were measured from the same CSF specimens using Lumipulse automated electrochemiluminescence assays. RESULTS: In Cox regression models, lower baseline NPTX2 levels were associated with an earlier time to MCI symptom onset (hazard ratio [HR] = 0.76, SE = 0.09, p = 0.023). This association was significant for progression within 7 years (p = 0.036) and after 7 years from baseline (p = 0.001). Baseline NPTX2 levels improved prediction of time to MCI symptom onset after accounting for baseline AD biomarker levels (p < 0.01), and NPTX2 did not interact with the CSF AD biomarkers or APOE-ε4 genetic status. In linear mixed effects models, higher baseline p-tau181 and t-tau levels were associated with higher baseline levels of NPTX2 (both p < 0.001) and greater rates of NPTX2 declines over time. INTERPRETATION: NPTX2 may be a valuable prognostic biomarker during preclinical AD that provides additive and independent prediction of MCI onset among individuals who are cognitively normal. We hypothesize that NPTX2-mediated circuit homeostasis confers resilience during the early phase of AD. ANN NEUROL 2023;94:620-631.

Immune cell patterns before and after neoadjuvant immune checkpoint blockade combined with chemoradiotherapy in locally advanced esophageal squamous cell carcinoma.

BACKGROUND: Neoadjuvant immune checkpoint blockade (ICB) combined with chemoradiotherapy offers high pathologic complete response (pCR) rate for patients with locally advanced esophageal squamous cell carcinomas (ESCC). But the dynamic tumor immune microenvironment modulated by such neoadjuvant therapy remains unclear. PATIENTS AND METHODS: A total of 41 patients with locally advanced ESCC were recruited. All patients received neoadjuvant toripalimab combined with concurrent chemoradiotherapy. Matched pre- and post-treatment tissues were obtained for fluorescent multiplex immunohistochemistry (mIHC) and IHC analyses. The densities and spatial distributions of immune cells were determined by HALO modules. The differences of immune cell patterns before and after neoadjuvant treatment were investigated. RESULTS: In the pre-treatment tissues, more stromal CD3 + FoxP3 + Tregs and CD86+/CD163 + macrophages were observed in patients with residual tumor existed in the resected lymph nodes (pN1), compared with patients with pCR. The majority of macrophages were distributed in close proximity to tumor nest in pN1 patients. In the post-treatment tissues, pCR patients had less CD86 + cell infiltration, whereas higher CD86 + cell density was significantly associated with higher tumor regression grades (TRG) in non-pCR patients. When comparing the paired pre- and post-treatment samples, heterogeneous therapy-associated immune cell patterns were found. Upon to the treatment, CD3 + T lymphocytes were slightly increased in pCR patients, but markedly decreased in non-pCR patients. In contrast, a noticeable increase and a less obvious decrease of CD86 + cell infiltration were respectively depicted in non-pCR and pCR patients. Furthermore, opposite trends of the treatment-induced alterations of CD8 + and CD15 + cell infiltrations were observed between pN0 and pN1 patients. CONCLUSIONS: Collectively, our data demonstrate a comprehensive picture of tumor immune landscape before and after neoadjuvant ICB combined with chemoradiotherapy in ESCC. The infiltration of CD86 + macrophage may serve as an unfavorable indicator for neoadjuvant toripalimab combined with chemoradiotherapy.

Diclofenac sodium effectively inhibits the biofilm formation of Staphylococcus epidermidis.

Staphylococcus epidermidis is an opportunistic pathogen commonly implicated in medical device-related infections. Its propensity to form biofilms not only leads to chronic infections but also exacerbates the issue of antibiotic resistance, necessitating high-dose antimicrobial treatments. In this study, we explored the use of diclofenac sodium, a non-steroidal anti-inflammatory drug, as an anti-biofilm agent against S. epidermidis. In this study, crystal violet staining and confocal laser scanning microscope analysis showed that diclofenac sodium, at subinhibitory concentration (0.4 mM), significantly inhibited biofilm formation in both methicillin-susceptible and methicillin-resistant S. epidermidis isolates. MTT assays demonstrated that 0.4 mM diclofenac sodium reduced the metabolic activity of biofilms by 25.21-49.01% compared to untreated controls. Additionally, the treatment of diclofenac sodium resulted in a significant decrease (56.01-65.67%) in initial bacterial adhesion, a crucial early phase of biofilm development. Notably, diclofenac sodium decreased the production of polysaccharide intercellular adhesin (PIA), a key component of the S. epidermidis biofilm matrix, in a dose-dependent manner. Real-time quantitative PCR analysis revealed that diclofenac sodium treatment downregulated biofilm-associated genes icaA, fnbA, and sigB and upregulated negative regulatory genes icaR and luxS, providing potential mechanistic insights. These findings indicate that diclofenac sodium inhibits S. epidermidis biofilm formation by affecting initial bacterial adhesion and the PIA synthesis. This underscores the potential of diclofenac sodium as a supplementary antimicrobial agent in combating staphylococcal biofilm-associated infections.

Interfacial Engineering of MoS2@CoS2 Heterostructure Electrocatalysts for Effective pH-Universal Hydrogen Evolution Reaction.

The practical utilization of the hydrogen evolution reaction (HER) necessitates the creation of electrocatalysts that are both efficient and abundant in earth elements, capable of operating effectively within a wide pH range. However, this objective continues to present itself as an arduous obstacle. In this research, we propose the incorporation of sulfur vacancies in a novel heterojunction formed by MoS2@CoS2, designed to exhibit remarkable catalytic performances. This efficacy is attributed to the advantageous combination of the low work function and space charge zone at the interface between MoS2 and CoS2 in the heterojunction. The MoS2@CoS2 heterojunction manifests outstanding hydrogen evolution activity over an extensive pH range. Remarkably, achieving a current density of 10 mA cm-2 in aqueous solutions 1.0 M KOH, 0.5 M H2SO4, and 1.0 M phosphate-buffered saline (PBS), respectively, requires only an overpotential of 48, 62, and 164 mV. The Tafel slopes for each case are 43, 32, and 62 mV dec-1, respectively. In this study, the synergistic effect of MoS2 and CoS2 is conducive to electron transfer, making the MoS2@CoS2 heterojunction show excellent electrocatalytic performance. The synergistic effects arising from the heterojunction and sulfur vacancy not only contribute to the observed catalytic prowess but also provide a valuable model and reference for the exploration of other efficient electrocatalysts. This research marks a significant stride toward overcoming the challenges associated with developing electrocatalysts for practical hydrogen evolution applications.

Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

Role of Ultrasound and Ultrasound-Based Prediction Model in Differentiating Follicular Thyroid Carcinoma From Follicular Thyroid Adenoma.

OBJECTIVES: This study aims to identify distinct ultrasound (US) characteristics for distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA), and construct a user-friendly preoperative risk stratification model for thyroid follicular neoplasms. METHODS: In this retrospective study, patients diagnosed with pathologically confirmed FTA or FTC and undergoing US examinations between July 2017 and June 2021 were designated as the training cohort, and those from July 2021 to June 2023 were enrolled as the external validation set. We systematically assessed and compared the sonographic and clinical characteristics of FTC and FTA. Univariable and multivariable logistic regression analyses were used to assess the association of US features with FTC in the training set. A prediction nomogram model, incorporating US features independently associated with FTC, was developed and validated externally to assess its performance. RESULTS: A total of 645 patients (FTA/FTC = 530/115) were included in the training set, while 197 patients (FTA/FTC = 165/32) constituted the validation set. In the training set, solid composition, hypo-echogenicity, irregular margin, calcification, protrusion sign, trabecular formation, absent or thick halo, and mainly central hypervascularity were identified as independent factors associated with FTC. The prediction nomogram model constructed using these variables showed good performance in differentiating FTC from FTA with an area under the curve of 0.948 in the training set and 0.915 in the validation set. CONCLUSIONS: The preoperative nomogram model constructed based on US features serves as an effective tool for the risk stratification of thyroid follicular neoplasms.

Dihydroartemisinin-driven TOM70 inhibition leads to mitochondrial destabilization to induce pyroptosis against lung cancer.

Enhancement of malignant cell immunogenicity to relieve immunosuppression of lung cancer microenvironment is essential in lung cancer treatment. In previous study, we have demonstrated that dihydroartemisinin (DHA), a kind of phytopharmaceutical, is effective in inhibiting lung cancer cells and boosting their immunogenicity, while the initial target of DHA's intracellular action is poorly understood. The present in-depth analysis aims to reveal the influence of DHA on the highly expressed TOM70 in the mitochondrial membrane of lung cancer. The affinity of DHA and TOM70 was analyzed by microscale thermophoresis (MST), pronase stability, and thermal stability. The functions and underlying mechanism were investigated using western blots, qRT-PCR, flow cytometry, and rescue experiments. TOM70 inhibition resulted in mtDNA damage and translocation to the cytoplasm from mitochondria due to the disruption of mitochondrial homeostasis. Further ex and in vivo findings also showed that the cGAS/STING/NLRP3 signaling pathway was activated by mtDNA and thereby malignant cells underwent pyroptosis, leading to enhanced immunogenicity of lung cancer cells in the presence of DHA. Nevertheless, DHA-induced mtDNA translocation and cGAS/STING/NLRP3 mobilization were synchronously attenuated when TOM70 was replenished. Finally, DHA was demonstrated to possess potent anti-lung cancer efficacy in vitro and in vivo. Taken together, these data confirm that TOM70 is an important target for DHA to disturb mitochondria homeostasis, which further activates STING and arouses pyroptosis to strengthen immunogenicity against lung cancer thereupon. The present study provides vital clues for phytomedicine-mediated anti-tumor therapy.

Structural equation modeling of dispositional mindfulness, internal environmental factors, external environmental factors, and self-care behaviors in people with type 2 diabetes.

BACKGROUND: To achieve suitable diabetes care, understanding the factors that affect self-care behaviors is necessary. OBJECTIVE: To construct a model of dispositional mindfulness, internal environmental factors, external environmental factors, and self-care behaviors in people with diabetes. DESIGN AND METHODS: This cross-sectional study analyzed a convenience sample of 311 people with type 2 diabetes in Taiwan. Data were collected through questionnaires, including the Diabetes Symptoms Checklist, Emotional Distress Scale, Empowerment Process Scale, Interpersonal Communication Scale and Self-Care Behavior scale. RESULTS: Structural equation modeling indicated that a model of dispositional mindfulness, internal environmental factors, external environmental factors, and self-care behaviors in the patients with diabetes best fit the data. Dispositional mindfulness (ß = 0.39), internal environmental factors (ß = 0.52), and external environmental factors (ß = 0.71) directly influenced self-care behaviors in the patients with diabetes. Dispositional mindfulness significantly indirectly affected self-care behaviors via internal and external environmental factors. CONCLUSIONS: To improve self-care behaviors, interventions should consider mindfulness training, and also include internal environmental factors and external environmental factors in the mindfulness training.

Middle-aged and older people's preference for medical-elderly care integrated institutions in China: a discrete choice experiment study.

BACKGROUND: With the continuing impact of the aging population, medical-elderly care integrated institutions, as a way to bear the pressure of medical and elderly care, effectively ensure the quality of life of the elderly in their later years. OBJECTIVES: To explore the preferences of medical-elderly care integrated institutions among Chinese middle-aged and older people and to provide a reference for establishing elderly-oriented development of medical-elderly care integrated institutions. METHODS: In this study, a discrete choice experiment (DCE) was used to investigate the preferences of people aged 45 years and older in medical-elderly care integrated institutions in China from October 20, 2022, to November 10, 2022. A mixed logit regression model was used to analyze the DCE data. Participants' willingness to pay for each attribute was also calculated. RESULTS: Data from 420 participants who provided valid responses were included in the analysis. In terms of the choice preference, moderate service quality (vs. poor service quality: ß = 1.707, p < 0.001, 95% CI 1.343 ~ 2.071) and high medical technology level (vs. low medical technology level: ß = 1.535, p < 0.001, 95% CI 1.240 ~ 1.830) were the most important attributes to middle-aged and older people, followed by monthly cost, environmental facilities, the convenience of transportation, and entertainment activities. Regarding the willingness to pay, participants were more willing to pay for service quality and medical technology level than for other attributes. They were willing to pay $3156 and $2838 more for "poor service quality" and "low medical technology level," respectively, to receive "moderate service quality " (p = 0.007, 95% CI 963 ~ 5349) and "high medical technology level" (p = 0.005, 95% CI 852 ~ 4824). CONCLUSIONS: The state should attach great importance to the development of medical-elderly care integrated services industry, actively optimize the model of the medical-elderly care integrated service, improve the facilities, and create a healthy environment. At the same time, give full play to the role of medical insurance, long-term care insurance, and commercial insurance, so as to improve the comprehensive quality of life of the elderly. PUBLIC CONTRIBUTION: The design of the experimental selection was guided by 10 experts in the field, 5 Chinese government officials, and interviews and focus group discussions, without whose participation this study would not have been possible.

The effect of a bone-preserving board game program on the knowledge, attitudes and preventive behaviors of osteoporosis in older adults.

Osteoporosis predisposes to fractures, which affect the quality of life and can be life-threatening. However, the knowledge, attitudes and preventive behaviors of osteoporosis in older adults are insufficient. The aim of this paper was to develop and test the effect of a bone-preserving board game program among older adults. A convenience sample of 85 older adults recruited from two community activity centers in southern Taiwan were assigned to either an experimental group or a control group. The experimental group played a bone-preserving board game for 4 weeks, and the control group participated in routine community center activities. The generalized estimating equation showed significantly larger improvements in knowledge, attitudes, and preventive behaviors in the experimental group than in the control group. Board games designed for older adults can support public health education and help prevent osteoporosis. Our results provide a reference for educators, clinical practitioners and researchers.

Neuronal pentraxin 2 correlates with neurodegeneration but not cognition in idiopathic normal pressure hydrocephalus (iNPH).

AIM OF THE STUDY: Neuronal pentraxin-2 (NPTX2) is a synaptic protein responsible for modulating plasticity at excitatory synapses. While the role of NPTX2 as a novel synaptic biomarker in cognitive disorders has been elucidated recently, its role in idiopathic normal pressure hydrocephalus (iNPH) is not yet understood. CLINICAL RATIONALE FOR STUDY: To determine if NPTX2 predicts cognition in patients with iNPH, and whether it could serve as a predictive marker for shunt outcomes. MATERIAL AND METHODS: 354 iNPH patients underwent cerebrospinal fluid drainage (CSF) as part of the tap test or extended lumbar drainage. Demographic and clinical measures including age, Evans Index (EI), Montreal Cognitive Assessment (MoCA) score, Functional Activities Questionnaire (FAQ) score, and baseline and post-shunt surgery Timed Up and Go (TUG) test scores were ascertained. CSF NPTX2 concentrations were measured using an ELISA. CSF ß-amyloid 1-40 (Aß1-40), ß-amyloid 1-42 (Aß1-42), and phosphorylated tau-181 (pTau-181) were measured by chemiluminescent assays. Spearman's correlation was used to determine the correlation between CSF NPTX2 concentrations and age, EI, MoCA and FAQ, TUG, Aß1-40/Aß1-42 ratio, and pTau-181 concentrations. Logistic regression was used to determine if CSF NPTX2 values were a predictor of short-term improvement post-CSF drainage or long-term improvement post-shunt surgery. RESULTS: There were 225 males and 129 females with a mean age of 77.7 years (± 7.06). Average CSF NPTX2 level in all iNPH patients was 559.97 pg/mL (± 432.87). CSF NPTX2 level in those selected for shunt surgery was 505.61 pg/mL (± 322.38). NPTX2 showed modest correlations with pTau-181 (r = 0.44, p < 0.001) with a trend for Aß42/Aß40 ratio (r = -0.1, p = 0.053). NPTX2 concentrations did not correlate with age (r = -0.012, p = 0.83) or MoCA score (r = 0.001, p = 0.87), but correlated negatively with FAQ (r = -0.15, p = 0.019). CONCLUSIONS: While CSF NPTX2 values correlate with neurodegeneration, they do not correlate with cognitive or functional measures in iNPH. CSF NPTX2 cannot serve as a predictor of either short-term or long-term improvement after CSF drainage. CLINICAL IMPLICATIONS: These results suggest that synaptic degeneration is not a core feature of iNPH pathophysiology.

[A new cucurbitane glycoside from Picrorhiza scrophulariiflora].

Chemical constituents from the ethanol extract of Picrorhiza scrophulariiflora were isolated and purified by column chromatography. Their structures were identified by HR-MS, 1D and 2D-NMR, and their cytotoxicity was assessed by CCK-8 assay. Four compounds were isolated and identified as follows: 2ß-D-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosterol-5,25-diene-22-one(1), 2ß-D-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5,24-diene-22-one(2), 25-acetoxy-2ß-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5-ene-22-one(3) and 25-acetoxy-2ß-glucosyloxy-3ß,16α,20ß-trihydroxy-9-methyl-19-norlanosta-5,23-(E)-diene-22-one(4). Compound 1 represents a new cucurbitane glycoside. The half inhibitory concentrations of the 4 compounds exceeded 100 µmol·L~(-1) against four tumor cell lines, indicating no significant cytotoxicity.

The first homosporous lycophyte genome revealed the association between the recent dynamic accumulation of LTR-RTs and genome size variation.

The contrasting genome size between homosporous and heterosporous plants is fascinating. Different from the heterosporous seed plants and mainly homosporous ferns, the lycophytes are either heterosporous (Isoetales and Selaginellales) or homosporous (Lycopodiales). Many lycophytes are the resource plants of Huperzine A (HupA) which is invaluable for treating Alzheimer's disease. For the seed-free vascular plants, several high-quality genomes of heterosporous Selaginella, homosporous ferns (maidenhair fern, monkey spider tree fern), and heterosporous ferns (Azolla) have been published and provided important insights into the origin and evolution of early land plants. However, the homosporous lycophyte genome has not been decoded. Here, we assembled the first homosporous lycophyte genome and conducted comparative genomic analyses by applying a reformed pipeline for filtering out non-plant sequences. The obtained genome size of Lycopodium clavatum is 2.30 Gb, distinguished in more than 85% repetitive elements of which 62% is long terminal repeat (LTR). This study disclosed a high birth rate and a low death rate of the LTR-RTs in homosporous lycophytes, but the opposite occurs in heterosporous lycophytes. we propose that the recent activity of LTR-RT is responsible for the immense genome size variation between homosporous and heterosporous lycophytes. By combing Ks analysis with a phylogenetic approach, we discovered two whole genome duplications (WGD). Morover, we identified all the five recognized key enzymes for the HupA biosynthetic pathway in the L. clavatum genome, but found this pathway incomplete in other major lineages of land plants. Overall, this study is of great importance for the medicinal utilization of lycophytes and the decoded genome data will be a key cornerstone to elucidate the evolution and biology of early vascular land plants.

Discovery of the covalent SARS-CoV-2 Mpro inhibitors from antiviral herbs via integrating target-based high-throughput screening and chemoproteomic approaches.

The main proteases (Mpro ) are highly conserved cysteine-rich proteins that can be covalently modified by numerous natural and synthetic compounds. Herein, we constructed an integrative approach to efficiently discover covalent inhibitors of Mpro from complex herbal matrices. This work begins with biological screening of 60 clinically used antiviral herbal medicines, among which Lonicera japonica Flos (LJF) demonstrated the strongest anti-Mpro effect (IC50 = 37.82 µg/mL). Mass spectrometry (MS)-based chemical analysis and chemoproteomic profiling revealed that LJF extract contains at least 50 constituents, of which 22 exhibited the capability to covalently modify Mpro . We subsequently verified the anti-Mpro effects of these covalent binders. Gallic acid and quercetin were found to potently inhibit severe acute respiratory syndrome coronavirus 2 Mpro in dose- and time- dependent manners, with the IC50 values below 10 µM. The inactivation kinetics, binding affinity and binding mode of gallic acid and quercetin were further characterized by fluorescence resonance energy transfer, surface plasmon resonance, and covalent docking simulations. Overall, this study established a practical approach for efficiently discovering the covalent inhibitors of Mpro from herbal medicines by integrating target-based high-throughput screening and MS-based assays, which would greatly facilitate the discovery of key antiviral constituents from medicinal plants.

High-normal unconjugated bilirubin is associated with decreased risk of chronic kidney disease in type 2 diabetes: A real-world study.

OBJECTIVE: To investigate the association between serum unconjugated bilirubin (UCB) within normal limits and chronic kidney disease (CKD) in T2DM patients. METHOD: This cross-sectional, real-world study was performed in 8661 hospitalised T2DM patients. The subjects were stratified into quintiles based on serum UCB levels. The clinical characteristics and CKD prevalence were compared among the UCB quantile groups. The associations of serum UCB levels and quintiles with CKD were also analysed by binary logistic regression. RESULTS: After controlling for age, sex, and diabetes duration (DD), the CKD prevalence (20.4%, 12.2%, 10.6%, 8.3%, and 6.4% for the first, second, third, fourth, and fifth quintiles, respectively, p < 0.001 for trend) was significantly decreased across the serum UCB quintiles. The fully adjusted regression model showed negative associations of serum UCB levels (OR: 0.660, 95% CI: 0.585-0.744; p < 0.001 for trend) and quintiles (p < 0.001) with the presence of CKD. Compared with the subjects in the lowest UCB quintile, the risk of CKD decreased by 36.2%, 54.3%, 53.8%, and 62.1%, respectively, in those from the second to the highest UCB quintile. Additionally, C-reactive protein (CRP) levels were significantly higher in the subjects with CKD than in those without CKD (p < 0.001), and significantly decreased across the UCB quintiles (p < 0.001 for trend). CONCLUSIONS: Serum UCB levels within the normal range were significantly and negatively linked to CKD in T2DM patients. High-normal UCB may be an independent protective factor for CKD by its antioxidant and the following anti-inflammatory activities through its signalling activity, which was indicated by clearly decreased CRP levels across the UCB quintiles.

Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.

PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have depended on polar maps, required manual correction, and normal database. In this study, we propose a polar map-free 3D DL algorithm to predict obstructive disease. METHODS: We included 1861 subjects who underwent MPI using cadmium-zinc-telluride camera and subsequent coronary angiography. The subjects were divided into parameterization and external validation groups. We implemented a fully automatic algorithm to segment myocardium, perform registration, and apply normalization. We further flattened the image based on spherical coordinate system transformation. The proposed model consisted of a component to predict patent arteries and a component to predict disease in each vessel. The model was cross-validated in the parameterization group, and then further tested using the external validation group. The performance was assessed by area under receiver operating characteristic curves (AUCs) and compared with TPD. RESULTS: Our algorithm preprocessed all images accurately as confirmed by visual inspection. In patient-based analysis, the AUC of the proposed model was significantly higher than that for stress-TPD (0.84 vs 0.76, p < 0.01). In vessel-based analysis, the proposed model also outperformed regional stress-TPD (AUC = 0.80 vs 0.72, p < 0.01). The addition of quantitative images did not improve the performance. CONCLUSIONS: Our proposed polar map-free 3D DL algorithm to predict obstructive CAD from MPI outperformed TPD and did not require manual correction or a normal database.

Computational redesign of taxane-10ß-hydroxylase for de novo biosynthesis of a key paclitaxel intermediate.

Paclitaxel (Taxol®) is the most popular anticancer diterpenoid predominantly present in Taxus. The core skeleton of paclitaxel is highly modified, but researches on the cytochrome P450s involved in post-modification process remain exceedingly limited. Herein, the taxane-10ß-hydroxylase (T10ßH) from Taxus cuspidata, which is the third post-modification enzyme that catalyzes the conversion of taxadiene-5α-yl-acetate (T5OAc) to taxadiene-5α-yl-acetoxy-10ß-ol (T10OH), was investigated in Escherichia coli by combining computation-assisted protein engineering and metabolic engineering. The variant of T10ßH, M3 (I75F/L226K/S345V), exhibited a remarkable 9.5-fold increase in protein expression, accompanied by respective 1.3-fold and 2.1-fold improvements in turnover frequency (TOF) and total turnover number (TTN). Upon integration into the engineered strain, the variant M3 resulted in a substantial enhancement in T10OH production from 0.97 to 2.23 mg/L. Ultimately, the titer of T10OH reached 3.89 mg/L by fed-batch culture in a 5-L bioreactor, representing the highest level reported so far for the microbial de novo synthesis of this key paclitaxel intermediate. This study can serve as a valuable reference for further investigation of other P450s associated with the artificial biosynthesis of paclitaxel and other terpenoids. KEY POINTS: • The T10ßH from T. cuspidata was expressed and engineered in E. coli unprecedentedly. • The expression and activity of T10ßH were improved through protein engineering. • De novo biosynthesis of T10OH was achieved in E. coli with a titer of 3.89 mg/L.