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Abstract Objective This study aimed to assess the efficacy and safety of bilateral superselective adrenal arterial embolization (SAAE) in patients with bilateral idiopathic hyperaldosteronism (IHA), a subtype of PA. Methods Ninety-eight patients with bilateral IHA underwent bilateral SAAE between August 2022 and August 2023. Sixty-eight patients were followed up for up to 12 months. The study outcomes were evaluated using the criteria provided by the Primary Aldosteronism Surgical Outcome (PASO) guidelines. Results The mean reductions in systolic and diastolic blood pressure were 27.4 ± 21.3 mmHg and 23.1 ± 17.4 mmHg, respectively (p

Abstract Background Aging is an inevitable biological process. Accelerated aging renders adults more susceptible to chronic diseases and increases their mortality rates. Previous studies have reported the relationship between lifestyle factors and phenotypic aging. However, the relationship between intrinsic factors, such as reproductive factors, and phenotypic aging remains unclear. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES), spanning from 1999 to 2010 and 2015–2018, with 14,736 adult women. Random forest imputation was used to handle missing covariate values in the final cohort. Weighted linear regression was utilized to analyze the relationship between women-specific reproductive factors and PhenoAgeAccel. Considering the potential impact of menopausal status on the results, additional analyses were conducted on premenopausal and postmenopausal participants. Additionally, the Life’s Essential 8 (LE8) was used to investigate the impact of healthy lifestyle and other factors on the relationship between women-specific reproductive factors and PhenoAgeAccel. Stratified analyses were conducted based on significant interaction p-values. Results In the fully adjusted models, delayed menarche and gynecological surgery were associated with increased PhenoAgeAccel, whereas pregnancy history were associated with a decrease. Additionally, early or late ages of menopause, first live birth, and last live birth can all negatively impact PhenoAgeAccel. The relationship between women-specific reproductive factors and PhenoAgeAccel differs between premenopausal and postmenopausal women. High LE8 scores positively impacted the relationship between certain reproductive factors (age at menarche, age at menopause, age at first live birth, and age at last live birth) and phenotypic age acceleration. Stratified analysis showed significant interactions for the following variables: BMI with age at menarche, pregnancy history, and age at menopause; ethnicity with age at menopause, age at first live birth, and parity; smoking status with use of contraceptive pills and gynecologic surgery; hypertension with use of contraceptive pills, pregnancy history, and age at menopause. Conclusion Delayed menarche, gynecological surgery, and early or late ages of menopause, first live birth, and last live birth are associated with accelerated phenotypic aging. High LE8 score may alleviate the adverse effects of reproductive factors on phenotypic aging.

Abstract Background Epimedin A (EA) has been shown to suppress extensive osteoclastogenesis and bone resorption, but the effects of EA remain incompletely understood. The aim of our study was to investigate the effects of EA on osteoclastogenesis and bone resorption to explore the corresponding signalling pathways. Methods Rats were randomly assigned to the sham operation or ovariectomy group, and alendronate was used for the positive control group. The therapeutic effect of EA on osteoporosis was systematically analysed by measuring bone mineral density and bone biomechanical properties. In vitro, RAW264.7 cells were treated with receptor activator of nuclear factor kappa-B ligand (RANKL) and macrophage colony-stimulating factor (M-CSF) to induce osteoclast differentiation. Cell viability assays, tartrate-resistant acid phosphatase (TRAP) staining, and immunofluorescence were used to elucidate the effects of EA on osteoclastogenesis. In addition, the expression of bone differentiation-related proteins or genes was evaluated using Western blot analysis or quantitative polymerase chain reaction (PCR), respectively. Results After 3 months of oral EA intervention, ovariectomized rats exhibited increased bone density, relative bone volume, trabecular thickness, and trabecular number, as well as reduced trabecular separation. EA dose-dependently normalized bone density and trabecular microarchitecture in the ovariectomized rats. Additionally, EA inhibited the expression of TRAP and NFATc1 in the ovariectomized rats. Moreover, the in vitro results indicated that EA inhibits osteoclast differentiation by suppressing the TRAF6/PI3K/AKT/NF-κB pathway. Further studies revealed that the effect on osteoclast differentiation, which was originally inhibited by EA, was reversed when the TRAF6 gene was overexpressed. Conclusions The findings indicated that EA can negatively regulate osteoclastogenesis by inhibiting the TRAF6/PI3K/AKT/NF-κB axis and that ameliorating ovariectomy-induced osteoporosis in rats with EA may be a promising potential therapeutic strategy for the treatment of osteoporosis.

Abstract Background To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images. Methods A total of 683 intraoral clinical images acquired from 134 volunteers were used to construct the database and evaluate the models. Four deep ConvNet models were developed using ensemble learning and outperformed a single model. The performances of the different models were evaluated by comparing the accuracy and sensitivity for recognizing the existence of gingivitis from intraoral images. Results The ResNet model achieved an area under the curve (AUC) value of 97%, while the AUC values for the GoogLeNet, AlexNet, and VGG models were 94%, 92%, and 89%, respectively. Although the ResNet and GoogLeNet models performed best in classifying gingivitis from images, the sensitivity outcomes were not significantly different among the ResNet, GoogLeNet, and Alexnet models (p>0.05). However, the sensitivity of the VGGNet model differed significantly from those of the other models (p

The World Health Organization (WHO) 2017 classifications for neuroendocrine neoplasms (NENs) subdivided grade 3 pancreatic neuroendocrine neoplasms (pNENs) into G3 well-differentiated pancreatic neuroendocrine tumors (G3 pNETs) and poorly differentiated pancreatic neuroendocrine carcinomas (pNECs), according to the mitotic count, Ki-67 index, and cell differentiation. As a new category, G3 pNETs remain a challenging group of tumors to manage by lacking large randomized trials and consensus to support its clinical practice. Therefore, the Chinese Pancreatic Surgery Association, Chinese Society of Surgery, Chinese Medical Association gathered experts in this field to formulate this consensus for the diagnosis and treatment of G3 pNETs.

Abstract Objective To investigate the extent of knowledge about breastfeeding and attitudes towards infant feeding among spouses of puerperas at the time of discharge from hospital, and explore the factors influencing spousal attitudes toward breastfeeding. Methods We conducted a questionnaire survey among 204 spouses of puerperas who were admitted in the maternity wards at a tertiary hospital in Shaanxi Province between October 2021 and December 2021. Respondents who fulfilled the inclusion criteria were identified using convenient sampling. Results (1) The score of breastfeeding knowledge among spouses prior to discharge from the hospital was (10.56 ± 3.78), with an accuracy rate of 59.6%, and the lowest accuracy rate was for Item 1 “Newborns should be fed on time, not on demand” (42.6%) and Item 5 “Breastfeeding can prevent infant rickets” (49.5%). (2) The average score of spouses’ infant feeding attitudes was (58.15 ± 5.55), and the lowest scoring was for Item 17 “Daily urine volume of infants is a reliable indicator to judge whether they get enough breast milk” (1.99 ± 1.14). (3) Generalized linear model analysis showed a more positive attitude (higher score) among spousal attitudes towards infant feeding in those who had received breastfeeding education [OR = 4.588, 95% CI (0.160 ∼ 3.598)] and those with a master’s degree or above [OR = 18.278, 95% CI (3.471 ∼ 9.346)]. Conclusion (1) Spouses that received breastfeeding education and those that had a Masters Degree and above had more positive attitude towards infant feeding. (2) Medical staff should focus on puerperas’spouses with degrees below master’s level who had not received breastfeeding education. We recommend using a variety of education methods to enable them to acquire more knowledge on breastfeeding and develop a more positive attitude towards breastfeeding, which will further enhance spousal support for breastfeeding, thus positivizing postpartum co-parenting attitudes and improving the rate of exclusive breastfeeding.

Abstract Although patients with alpha-fetoprotein-negative hepatocellular carcinoma (AFPNHCC) have a favorable prognosis, a high risk of postoperative recurrence remains. We developed and validated a novel liver fibrosis assessment index, the direct bilirubin-gamma-glutamyl transpeptidase-to-platelet ratio (DGPRI). DGPRI was calculated for each of the 378 patients with AFPNHCC who underwent hepatic resection. The patients were divided into high- and low-score groups using the optimal cutoff value. The Lasso-Cox method was used to identify the characteristics of postoperative recurrence, followed by multivariate Cox regression analysis to determine the independent risk factors associated with recurrence. A nomogram model incorporating the DGPRI was developed and validated. High DGPRI was identified as an independent risk factor (hazard ratio = 2.086) for postoperative recurrence in patients with AFPNHCC. DGPRI exhibited better predictive ability for recurrence 1–5 years after surgery than direct bilirubin and the gamma-glutamyl transpeptidase-to-platelet ratio. The DGPRI-nomogram model demonstrated good predictive ability, with a C-index of 0.674 (95% CI 0.621–0.727). The calibration curves and clinical decision analysis demonstrated its clinical utility. The DGPRI nomogram model performed better than the TNM and BCLC staging systems for predicting recurrence-free survival. DGPRI is a novel and effective predictor of postoperative recurrence in patients with AFPNHCC and provides a superior assessment of preoperative liver fibrosis.

Abstract Background The antiviral drug Nirmatrelvir was found to be a key drug in controlling the progression of pneumonia during the infectious phase of COVID-19. However, there are very few options for effective treatment for cancer patients who have viral pneumonia. Glucocorticoids is one of the effective means to control pneumonia, but there are many adverse events. EGCG is a natural low toxic compound with anti-inflammatory function. Thus, this study was designed to investigate the safety and efficacy of epigallocatechin-3-gallate (EGCG) aerosol to control COVID-19 pneumonia in cancer populations. Methods The study was designed as a prospective, single-arm, open-label phase I/II trial at Shandong Cancer Hospital and Institute, between January 5, 2023 to March 31,2023 with viral pneumonia on radiographic signs after confirmed novel coronavirus infection. These patients were treated with EGCG nebulization 10 ml three times daily for at least seven days. EGCG concentrations were increased from 1760-8817umol/L to 4 levels with dose escalation following a standard Phase I design of 3–6 patients per level. Any grade adverse event caused by EGCG was considered a dose-limiting toxicity (DLT). The maximum tolerated dose (MTD) is defined as the highest dose with less than one-third of patients experiencing dose limiting toxicity (DLT) due to EGCG. The primary end points were the toxicity of EGCG and CT findings, and the former was graded by Common Terminology Criteria for Adverse Events (CTCAE) v. 5.0. The secondary end point was the laboratory parameters before and after treatment. Result A total of 60 patients with high risk factors for severe COVID-19 pneumonia (factors such as old age, smoking and combined complications)were included in this phase I-II study. The 54 patients in the final analysis were pathologically confirmed to have tumor burden and completed the whole course of treatment. A patient with bucking at a level of 1760 umol/L and no acute toxicity associated with EGCG has been reported at the second or third dose gradients. At dose escalation to 8817umol/L, Grade 1 adverse events of nausea and stomach discomfort occurred in two patients, which resolved spontaneously within 1 hour. After one week of treatment, CT showed that the incidence of non-progression of pneumonia was 82% (32/39), and the improvement rate of pneumonia was 56.4% (22/39). There was no significant difference in inflammation-related laboratory parameters (white blood cell count, lymphocyte count, IL-6, ferritin, C-reactive protein and lactate dehydrogenase) before and after treatment. Conclusion Aerosol inhalation of EGCG is well tolerated, and preliminary investigation in cancer population suggests that EGCG may be effective in COVID-19-induced pneumonia, which can promote the improvement of patients with moderate pneumonia or prevent them from developing into severe pneumonia. Trial registration ClinicalTrials.gov Identifier: NCT05758571. Date of registration: 8 February 2023.

Abstract Chorus waves are intense electromagnetic emissions critical in modulating electron dynamics. In this study, we perform two‐dimensional particle‐in‐cell simulations to investigate self‐consistent wave‐particle interactions with oblique chorus waves. We first analyze the electron dynamics sampled from cyclotron and Landau resonances with waves, and then quantify the advection and diffusion coefficients through statistical studies. It is found that phase‐trapped cyclotron resonant electrons satisfy the second‐order resonance condition and gain energy from waves. While phase‐bunched cyclotron resonant electrons cannot remain in resonance for long periods. They transfer energy to waves and are scattered to smaller pitch angles. Landau resonant electrons are primarily energized by waves. For both types of resonances, advection coefficients are greater than diffusion coefficients when the wave amplitude is large. Our study highlights the important role of advection in electron dynamics modulation resulting from nonlinear wave‐particle interactions.

Abstract Vasculogenic mimicry (VM) describes a process by which tumor cells formed a novel microcirculation pattern in an endothelial cell‐free manner. Clinically, VM is associated with aggressive phenotype and poor patient survival. However, the current models for investigating VM include 2D monolayer cultures, Matrigel‐based cultures, and animal models, each of which has limitations. Matrigel‐based models often exhibit batch‐to‐batch variations, while in vivo tumor models currently produce insufficient amounts of VM. There is currently no suitable tumor model to discover new therapeutic targets against VM. Herein, we establish an extracellular matrix (ECM)‐based engineered tumor model in vivo and in vitro. In this study, we demonstrate that matrix proteins enhanced the VM formation in the engineered xenograft model. Furthermore, we also investigated the role of collagen/fibronectin (FN) in melanoma progression and VM formation. Compared with cells cultured on TCPS plates, the B16F10 cells cultured on collagen/FN coated plates showed increased proliferation and stemness, and significantly enhanced invasion and formation of VM networks. Molecular mechanism analysis showed that Integrin/VE‐cadherin/EphA2/PI3K/MMP‐2 signaling pathways are responsible for VM formation. Our results indicate that collagen/FN matrix plays an important role in VM formation in melanoma, suggesting that ECM protein is a potential therapeutic target for anti‐VM therapy for melanoma.

Background & Aims: Hepatic recompensation may be achieved in patients with decompensated cirrhosis due to chronic hepatitis B (CHB) upon effective suppression of viral replication by nucleos(t)ide analogues (NAs). However, the optimal timing and predictors of recompensation and the subsequent clinical course of patients with CHB with vs. without recompensation are not well-defined. Methods: This study was a retrospective extension of a multi-centre prospective cohort, focusing on patients with CHB and decompensated cirrhosis treated with entecavir. We followed patients beyond treatment week 120 until a second decompensation event or June 2023. We identified the optimal timing and predictors of recompensation by week 120, evaluated durability of recompensation in patients fulfilling recompensation criteria by week 120 and examined late recompensation in those who did not fulfil it by week 120. Results: At treatment week 24, serum albumin ≥34 g/L predicted recompensation by week 120. The Brec-PAS model offered good predictive ability for recompensation by week 120. Of the 283 patients who finished 120 weeks of therapy, 175 were followed beyond week 120 (median follow-up: 240 weeks). Among the 106 patients achieving recompensation by week 120, 92 (86.8%) maintained recompensation for another 120 (72-168) weeks. Among the 69 patients without recompensation by week 120, 40.6% attained late recompensation during the subsequent 120 (72-168) weeks. Additionally, hepatocellular carcinoma incidence was lower in the recompensated group (5.0% vs. 16.13%, p = 0.002). Conclusions: A serum albumin ≥34 g/L at treatment week 24 predicted recompensation by week 120. Recompensation achieved by week 120 of NA treatment is maintained in >80% of patients in the long term. Some patients may achieve recompensation only after >120 weeks of NA treatment. The incidence of hepatocellular carcinoma was reduced but not completely abolished after recompensation. Impact and implications: Our research provides a meaningful contribution to understanding the long-term prognosis of recompensation in patients with chronic hepatitis B and decompensated cirrhosis, as well as to evaluating the predictive value of serum albumin levels, offering a comprehensive view of clinical outcomes after recompensation. The significance of early biomarkers in guiding therapeutic decisions is highlighted, shedding light on the continued benefits and possible risks after recompensation. This enhances the capability for more precise prognostic evaluations and informed therapeutic strategies. For healthcare providers, these insights afford a detailed perspective on patient monitoring and intervention planning, underscoring the need for ongoing assessment past the initial recompensation phase.

Abstract To enhance the DC electrical performance of cross‐linked polyethylene (XLPE), the graftable antioxidant methacrylic acid 2‐hydroxy‐3‐(4‐anilinoanilino) propyl ester (GA), which contains carbonyl and amino groups, and the crosslinking coagent trimethylolpropane trimethacrylate (TMPTMA), which contains carbonyl groups, are individually or co‐grafted onto XLPE. The slightly higher deep trap density introduced by higher grafting concentration of TMPTMA results in more significant suppression effect of conductance current and enhanced breakdown strength at a lower temperature, while the suppression effect for the conductance current at 90°C becomes weakened due to limited trap energy. Meanwhile, the deeper energy level introduced by GA suppresses the conductance current and improves the electrical strength of XLPE at 90°C more significantly. By co‐grafting, the conductance current of XLPE in a wide range temperature can be significantly reduced, especially for the temperature dependence of conductance current, which is beneficial to suppress the field strength reversal. The results of thermally stimulated current and molecular simulation show that the polar groups of two monomers introduce deep charge traps in XLPE. The co‐grafting system ensures the rationality of the crosslinking reaction kinetics and does not affect the cable manufacturing.

Recent advancements in text-to-image generation have demonstrated significant progress, especially with diffusion-based models conditioned on textual prompts, which excel in image quality and diversity. However, these methods often encounter a semantic gap between image and text modalities and suffer from imprecise localization during text-based image editing. To address these challenges, we propose the Diffusion-based Knowledge-enhanced Mask Transformer (Diff-KT) text-to-image model. Diff-KT leverages knowledge enhancement strategies to incorporate fine-grained textual and visual knowledge of key scene elements, thereby improving the fidelity and textual consistency of generated images. Furthermore, it enhances the controllability of textual influences on image generation by using masks to precisely target areas in the image for editing. To facilitate deeper fusion of visual and textual information, we introduce a multimodal pre-trained model CoCa, to extract joint representations of images and text, enhancing the detailed expression in generated images. Diff-KT improves the correlation between text and generated images and enhances image localization precision within the diffusion model, resulting in high-quality images. Experimental results validate the advantages of the Diff-KT model, demonstrating higher correlation between generated images and text prompts, as well as more accurate localization during text-guided image editing, underscoring its practical value.

In addressing the Flexible Job Shop Scheduling Problem (FJSP), deep reinforcement learning eliminates the need for mathematical modeling of the problem, requiring only interaction with the real environment to learn effective strategies. Using disjunctive graphs as the state representation has proven to be a particularly effective method. Additionally, attention mechanisms enable rapid focus on relevant features. However, due to the unique structure of attention mechanisms, current methods fail to provide effective strategies after changes in scale. To resolve this issue, we propose an end-to-end deep reinforcement learning framework for the FJSP. Initially, we introduce a lightweight attention model, the Graph Gated Channel Transformation (GGCT), to identify the characteristics of the workpieces being scheduled at the current decision-making moment, while suppressing redundant features. Subsequently, to address the inability to provide effective strategies after changes in scale, we modify the expression of disjunctive graph features, channeling global features into different channels to capture relevant information at the current moment effectively. Comparative analysis on generated and classical datasets shows our model reduces the average makespan significantly, from 8.243% to 7.037% and from 10.08% to 8.69%, respectively.

Abstract Purpose Previous randomized studies have shown a survival benefit of using regorafenib but a high rate of adverse events in unresectable colorectal cancer patients. To reduce these adverse events and improve the tolerability, we examined the appropriate dose of regorafenib based on body weight. Methods We used a nationwide claims database in Japan and examined the efficacy and safety of regorafenib for patients with metastatic colorectal cancer between groups divided by body weight (60 kg) and median average dose (120 mg) between 2013 and 2018. We also assessed overall survival (OS) and adverse events between these groups. Results We identified 2530 Japanese patients (heavy weight/high dose: 513, light weight/low dose: 921, heavy weight/low dose: 452, and light weight/high dose: 644). There was no significant difference in the adverse events and OS after inverse probability treatment weighting (IPTW) adjustment between heavy weight/high dose group and light weight/low dose group (hazard ratio, HR=0.97). Among the light-weight patients, higher average dose was associated with shorter OS (IPTW adjusted HR=1.21, 95% CI 1.05 – 1.39, Table 3) while among the heavy-weight patients, there was no significant difference in OS between high and low dose groups (IPTW adjusted HR=1.14, 95% CI 0.95 – 1.37). Conclusion The findings suggest that a low dose of regorafenib for light-weight patients may be as safe and effective as high doses for heavy-weight patients. Further studies should be conducted to identify an appropriate dose based on each patient's physique and condition.

Many management strategies are available for pancreatic neuroendocrine neoplasms with liver metastases. However, a lack of biological, molecular, and genomic information and an absence of data from rigorous trials limit the validity of these strategies. This review presents the viewpoints from an international conference consisting of several expert working groups. The working groups reviewed a series of questions of particular interest to clinicians taking care of patients with pancreatic neuroendocrine neoplasms with liver metastases by reviewing the existing management strategies and literature, evaluating the evidence on which management decisions were based, developing internationally acceptable recommendations for clinical practice, and making recommendations for clinical and research endeavors. The review for each question will be followed by recommendations from the panel.

Abstract CD8+ T cells are the executor in adaptive immune response, especially in anti-tumor immunity. They are the subset immune cells that are of high plasticity and multifunction. Their development, differentiation, activation and metabolism are delicately regulated by multiple factors. Stimuli from the internal and external environment could remodel CD8+ T cells, and correspondingly they will also make adjustments to the microenvironmental changes. Here we describe the most updated progresses in CD8+ T biology from transcriptional regulation to metabolism mechanisms, and also their interactions with the microenvironment, especially in cancer and immunotherapy. The expanding landscape of CD8+ T cell biology and discovery of potential targets to regulate CD8+ T cells will provide new viewpoints for clinical immunotherapy.

In this paper, a dual deep Q-network (DDQN) energy management model based on long-short memory neural network (LSTM) speed prediction is proposed under the model predictive control (MPC) framework. The initial learning rate and neuron dropout probability of the LSTM speed prediction model are optimized by the genetic algorithm (GA). The prediction results show that the root-mean-square error of the GA-LSTM speed prediction method is smaller than the SVR method in different speed prediction horizons. The predicted demand power, the state of charge (SOC), and the demand power at the current moment are used as the state input of the agent, and the real-time control of the control strategy is realized by the MPC method. The simulation results show that the proposed control strategy reduces the equivalent fuel consumption by 0.0354 kg compared with DDQN, 0.8439 kg compared with ECMS, and 0.742 kg compared with the power-following control strategy. The difference between the proposed control strategy and the dynamic planning control strategy is only 0.0048 kg, 0.193%, while the SOC of the power battery remains stable. Finally, the hardware-in-the-loop simulation verifies that the proposed control strategy has good real-time performance.

Ischemic stroke (IS) is one of the leading causes of death and disability. Complicated mechanisms are involved in the pathogenesis of IS. Immunomodulatory mechanisms are crucial to IS. Acupuncture is a traditional non-drug treatment that has been extensively used to treat IS. The exploration of neuroimmune modulation will broaden the understanding of the mechanisms underlying acupuncture treatment. This review summarizes the immune response of immune cells, immune cytokines, and immune organs after an IS. The immunomodulatory mechanisms of acupuncture treatment on the central nervous system and peripheral immunity, as well as the factors that influence the effects of acupuncture treatment, were summarized. We suggest prospects and future directions for research on immunomodulatory mechanisms of acupuncture treatment for IS based on current progress, and we hope that these will provide inspiration for researchers. Additionally, acupuncture has shown favorable outcomes in the treatment of immune-based nervous system diseases, generating new directions for research on possible targets and treatments for immune-based nervous system diseases.

Federated Learning (FL) is a distributed machine learning technique for training machine learning models across multiple clients collaboratively. It allows multiple local devices to cooperatively train global models without compromising data privacy or necessitating extensive data transfer. However, the inherent data heterogeneity across clients poses a challenge, as a single global model trained through FL struggles to adapt to the diverse distributions present in individual client data. This discrepancy leads to a marked decline in model accuracy, slows down FL convergence, and even makes FL divergent. To this end, this paper proposes a method termed Residual Attention for Federated Learning (RAFL), aimed at personalized federated learning (PFL) by applying a residual multi-head attention mechanism to enrich personalized feature information. Additionally, it leverages a global category embedding layer to learn global feature information. In order to evaluate our proposed method's effectiveness, we perform extensive experiments on three benchmark datasets, comparing it with eight benchmark methods. The experimental results demonstrate that RAFL has better personalized learning capability compared to the other benchmark methods. On three benchmark datasets, RAFL achieves the highest accuracy. Notably, the accuracy is about two and a half percentage points higher than the current sota PFL methods.

IntroductionMalnutrition is prevalent among individuals with gastric cancer and notably decreases their quality of life (QOL). However, the factors impacting QOL are yet to be clearly defined. This study aimed to identify essential factors impacting QOL in malnourished patients suffering from gastric cancer.MethodsBy using the Patient-Generated Subjective Global Assessment (PG-SGA) to assess the nutritional status (≥4 defined malnutrition) of hospitalized cancer patients, 4,586 gastric cancer patients were ultimately defined as malnourished. Spearman method was used to calculate the relationship between clinical features and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Then, univariate and multivariate logistic regression were used to observe which factors affected QOL, and subgroup analysis was performed in young and old population respectively. In addition, we used univariate and multivariate logistic regression to explore whether and how self-reported frequent symptoms in the last 2 weeks of the PG-SGA score affected QOL.ResultsIn multivariate logistic regression analysis of clinical features of patients with malnourished gastric cancer, women, stage II, stage IV, WL had an independent correlation with a low global QOL scores. However, BMI, secondary education, higher education, surgery, chemotherapy, HGS had an independent correlation with a high global QOL scores. In multivariate logistic regression analysis of symptoms in self-reported PG-SGA scores in patients with malnourished gastric cancer, having no problem eating had an independent correlation with a high global QOL scores. However, they have no appetite, nausea, vomiting, constipation and pain had an independent correlation with a lower global QOL scores. The p values of the above statistical results are both < 0.05.ConclusionThis study demonstrates that QOL in malnourished patients with gastric cancer is determined by female sex, stage II, stage IV, BMI, secondary and higher education or above, surgery, chemotherapy, WL, and HGS. Patients’ self-reported symptoms of nearly 2 weeks, obtained by using PG-SGA, are also further predictive of malnourished gastric cancer patients. Detecting preliminary indicators of low QOL could aid in identifying patients who might benefit from an early referral to palliative care and assisted nursing.

PurposeTo explore the efficacy and safety of FOLFOXIRI plus cetuximab regimen as conversion therapy for patients with unresectable RAS/BRAF wild-type colorectal liver-limited metastases (CLM).Patients and methodsThis was a dual-center, phase II trial with the rate of no evidence of disease (NED) achieved as the primary endpoint. All enrolled patients with initially unresectable left-sided RAS/BRAF wild-type colorectal liver-limited metastases received a modified FOLFOXIRI plus cetuximab regimen as conversion therapy.ResultsBetween October 2019 and October 2021, fifteen patients were enrolled. Nine patients (60%) achieved NED. The overall response rate (ORR) was 92.9%, and the disease control rate (DCR) was 100%. The median relapse‐free survival (RFS) was 9 (95% CI: 0–20.7) months. The median progression-free survival (PFS) was 13.0 months (95% CI: 5.7-20.5), and the median overall survival (OS) was not reached. The most frequently occurring grade 3-4 adverse events were neutropenia (20%), peripheral neurotoxicity (13.3%), diarrhea (6.7%), and rash acneiform (6.7%).ConclusionThe FOLFOXIRI plus cetuximab regimen displayed tolerable toxicity and promising anti-tumor activity in terms of the rate of NED achieved and response rate in patients with initially unresectable left-sided RAS/BRAF wild-type CLM. This regimen merits further investigation.

In order to figure out the effects of charge-attracting molecules on the direct current electrical performance of crosslinked polyethylene (XLPE), the molecules with different structures and functional groups were grafted onto XLPE, and their space charge, volume resistivity and thermal stimulated depolarization current were investigated. Based on density function theory, the trap distribution and charge-attracting properties of the grafted XLPE were calculated. For the charge-attracting groups, the results indicate that with the grafted of trap molecules containing polar groups CO and N-H, the electron and hole traps are introduced and the ability of attracting negative charges and positive charges are extremely improved, respectively, resulting in the enhanced space charge hindering and suppressed resistivity. The benzene ring can form both electron and hole traps with relatively shallower energy level, and results in an improved space charge dissipation and decreased resistivity. For the combination of charge-attracting groups, the continuous arrangement of homogeneous charge-attracting groups can achieve an enhanced modification effect, and heterogeneous charge-attracting groups will attenuate the modification ability. For the molecule structure, the grafting of compact cyclic molecular can affect the electrostatic potential distribution on XLPE’s chain, and exhibits a stronger modification effect.

However, it is still difficult for clinicians to establish prognostic stratifications and therapeutic strategies because of the lack of tools for predicting the survival of triple-negative breast cancer patients with liver metastases (TNBC-LM). Based on clinical data from large populations, a sensitive and discriminative nomogram was developed and validated to predict the prognosis of TNBC patients with LM at initial diagnosis or at the later course. Introduction/background: Liver metastasis (LM) in TNBC patients is associated with significant morbidity and mortality. The objective of this study was to construct a clinical model to predict the survival of TNBC-LM patients. Materials and methods: Clinicopathologic data were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and the Fifth Affiliated Hospital of Sun Yat-Sen University (FAFSYU). Based on patients with newly diagnosed TNBC with LM (nTNBC-LM) from the SEER database, a predictive nomogram was established and validated. Its predictive effect on TNBC patients with LM at later disease course by enrolling TNBC patients from FAFSYU who developed LM later. The prognostic effect of different treatment for nTNBC-LM was further assessed. Results: A prognostic model was developed and validated to predict the prognosis of TNBC-LM patients. For LM patients diagnosed at the initial or later treatment stage, the C-index (0.712, 0.803 and 0.699 in the training, validation and extended groups, respectively) and calibration plots showed the acceptable prognostic accuracy and clinical applicability of the nomogram. Surgical resection on the primary tumour and chemotherapy were found to be associated with significantly better overall survival (OS). Conclusion: A sensitive and discriminative model was developed to predict OS in TNBC-LM patients both at and after initial diagnosis.

Background: Scarce evidence exists for clinical target volume (CTV) definitions of regional lymph nodes (LNs) in intrahepatic cholangiocarcinoma (iCCA) or combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We investigated the mapping pattern of nodal recurrence after surgery for iCCA and cHCC-CCA and provided evidence for the nodal CTV definition. Methods: We retrospectively reviewed the medical records of patients with iCCA or cHCC-CCA who underwent surgery between 2010 and 2020. Eligibility criteria included patients pathologically diagnosed with iCCA or cHCC-CCA after surgery and a first recurrent event in regional LNs during follow-up. All recurrent LNs were registered onto reference computed tomography images based on the vascular structures to reconstruct the node mapping. Fifty-three patients were eligible. LN regions were classified into four risk groups. Results: Hepatic hilar and portal vein-vena cava were the most common recurrent regions, with recurrence rates of 62.3 % and 39.6 % (high-risk regions), respectively. Recurrence rates in the left gastric, diaphragmatic, common hepatic, superior mesenteric vessels, celiac trunk, and paracardial regions ranged from 15.1 % to 30.2 % (intermediate-risk regions). There were fewer recurrences in the para-aortic (16a1, a2, b1) and splenic artery and hilum regions, with rates

Abstract Background The triglyceride glucose-body mass (TyG-BMI) index is acknowledged as both a reliable indicator of the risk of cardiovascular disease and an accurate surrogate biomarker for evaluating insulin resistance (IR). The importance of the TyG-BMI index among people with heart failure (HF), however, requires more investigation. The objective of this study was to inquire about the relationship between HF patients’ TyG-BMI index and their risk of 360-day mortality. Methods The Medical Information Mart for Intensive Care (MIMIC-IV) database provided the study’s patient data, which were divided into quartiles according to their TyG-BMI index. The endpoint was mortality from all causes within 360 days. Kaplan-Meier analysis was used to compare this primary endpoint amongst the four groups indicated above. The association between the TyG-BMI index and the endpoint was investigated using restricted cubic splines and Cox proportional hazards analysis. Results The study enrolled a total of 423 patients with HF (59.2% male), of whom 70 patients (16.9%) died within 360 days. Patients with higher TyG-BMI indexes had significantly lower mortality risks, according to the Kaplan-Meier analysis (log-rank P = 0.003). Furthermore, the restricted cubic spline analysis illustrated a decrease in the risk of all-cause mortality with an increasing TyG-BMI index. Additionally, multivariable Cox proportional hazards analyses showed that the risk of 360-day death from all causes was considerably higher in the lowest quartile of TyG-BMI. In comparison to the lowest TyG-BMI group, the fully adjusted Cox model yielded a hazard ratio (HR) of 0.24 (95% CI: 0.10, 0.59; p = 0.002) for 360-day mortality. Conclusions In patients diagnosed with HF, a lower TyG-BMI index is strongly related to a higher risk of 360-day mortality. This index can be employed to categorize the risk levels of patients with HF and predict their one-year all-cause mortality .

Materials that generate structural color may be promising alternatives to dyes and pigments due to their relative long-term stability and environmentally benign properties. Liquid crystal (LC) mixtures of cholesteryl esters demonstrate structural color due to light reflected from the helical structure of the self-assembled molecules. The apparent color depends on the pitch length of the liquid crystal. While a wide range of colors have been achieved with such LC formulations, the nature of the pitch–concentration relationship has been difficult to define. In this work, various machine learning approaches to predict the reflected wavelength, i.e., the position of the selective reflection band, based on LC composition are compared to a Scheffe cubic model. The neural network regression model had a higher root mean squared error (RMSE) than the Scheffe cubic model with improved predictions for formulations not included in the dataset. Decision tree regression provided the best overall performance with the lowest RMSE and predicted position of the selective reflection band within 0.8% of the measured values for LC formulations not included in the dataset. The predicted values using the decision tree were over two-fold more accurate than the Scheffe cubic model. These results demonstrate the utility of machine learning models for predicting physical properties of LC formulations.

Background: Mother-to-child transmission (MTCT) of human immunodeficiency virus (HIV) can occur intrauterine, intrapartum, and postpartum. Currently, infants with confirmed positive results in virological tests before 48 h of age are defined as having intrauterine infection. Aim: We herein review the literature that identifies emerging challenges in diagnosing intrauterine HIV infection to rethink the current diagnostic criteria. Findings: A number of reports have shown that some infants who were diagnosed with intrauterine HIV infection after birth became negative for HIV in the subsequent follow-ups, including negative HIV antibodies at the age of 12–18 months. Such ''clearance'' of HIV was attributed to various reasons: neonatal antiretroviral treatment (ART), false positivity, strong host immune response, or unknown factors in maternal breast milk. Discussions: Positive HIV tests in newborn infants shortly after birth do not necessarily indicate HIV infection, because maternal HIV can enter fetal circulation intrapartum due to the repetitive, strong uterine contractions. The infants are therefore exposed to, but may not yet be infected with HIV at that time. The current diagnostic criteria cannot differentiate HIV exposure from HIV infection, leading to so-called “challenges in diagnosing intrauterine HIV infection”. Those infants diagnosed with intrauterine infection who cleared HIV later were less likely to have been truly infected with HIV, but more likely to have been exposed to HIV. Moreover, we suggest that the determination of HIV antibody titers in infants’ serial serum samples can provide valuable information to distinguish intrapartum exposure from intrauterine infection.

Abstract Purpose To predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics. Patients and methods A total of 116 ICC patients were included (training: 86; external validation: 30). The enhanced CT images were performed for the radiomics model. The logistic regression analysis was applied for the clinical model. The combined model was based on the clinical and radiomics models. Results A total of 107 radiomics features were extracted, and after being eliminated and selected, six features were combined to establish a radiomics model for TLSs prediction. Arterial phase diffuse hyperenhancement and AJCC 8th stage were combined to construct a clinical model. The combined (radiomics nomogram) model outperformed both the independent radiomics model and clinical model in the training cohort (AUC, 0.85 vs. 0.82 and 0.75, respectively) and was validated in the external validation cohort (AUC, 0.88 vs. 0.86 and 0.71, respectively). Patients in the rad-score no less than −0.76 (low-risk) group showed significantly better RFS than those in the less than −0.76 (high-risk) group (p

Abstract Objective To predict the very early recurrence (VER) of patients with intrahepatic cholangiocarcinoma (ICC) based on TLSs and MVI status, and further perform prognosis stratifications. Methods A total of 160, 51 ICC patients from two institutions between May 2012 and July 2022 were retrospectively included as training, external validation cohort. Clinical, radiological and pathological variables were evaluated and collected. Univariate and multivariate analysis were applied to select the significant factors related to VER of ICC. The factors selected were combined to perform stratification of overall survival (OS) using the Kaplan-Meier method with the log-rank test. Results Overall, 39 patients (24.4%) had VER, whereas 121 (75.6%) did not (non-VER group). In the training cohort, the median OS was 40.5 months (95% CIs: 33.2–47.7 months). The VER group showed significantly worse OS than the non-VER group (median OS: 14.8, 95% CI:11.6–18.0 months vs. 53.4, 34.3–72.6 months; p

Abstract Background Anthracyclines including doxorubicin are essential components of many cancer chemotherapy regimens, but their cardiotoxicity severely limits their use. New strategies for treating anthracycline-induced cardiotoxicity (AIC) are still needed. Anthracycline-induced DNA double-strand break (DSB) is the major cause of its cardiotoxicity. However, DSB-based drug screening for AIC has not been performed possibly due to the limited throughput of common assays for detecting DSB. To discover new therapeutic candidates for AIC, here we established a method to rapidly visualize and accurately evaluate the intranuclear anthracycline-induced DSB, and performed a screening for DSB inhibitors. Results First, we constructed a cardiomyocyte cell line stably expressing EGFP-53BP1, in which the formation of EGFP-53BP1 foci faithfully marked the doxorubicin-induced DSB, providing a faster and visible approach to detecting DSB. To quantify the DSB, we used a deep learning-based image analysis method, which showed the better ability to distinguish different cell populations undergoing different treatments of doxorubicin or reference compounds, compared with the traditional threshold-based method. Subsequently, we applied the deep learning-assisted high-content screening method to 315 compounds and found three compounds (kaempferol, kaempferide, and isoliquiritigenin) that exert cardioprotective effects in vitro. Among them, the protective effect of isoliquiritigenin is accompanied by the up-regulation of HO-1, down-regulation of peroxynitrite and topo II, and the alleviation of doxorubicin-induced DSB and apoptosis. The results of animal experiments also showed that isoliquiritigenin maintained the myocardial tissue structure and cardiac function in vivo. Moreover, isoliquiritigenin did not affect the killing of HeLa and MDA-MB-436 cancer cells by doxorubicin and thus has the potential to be a lead compound to exert cardioprotective effects without affecting the antitumor effect of doxorubicin. Conclusions Our findings provided a new method for the drug discovery for AIC, which combines phenotypic screening with artificial intelligence. The results suggested that isoliquiritigenin as an inhibitor of DSB may be a promising drug candidate for AIC.

Abstract Background Explaining contrasting patterns of distribution between related species is crucial for understanding the dynamics of biodiversity. Despite instances where hybridization and whole genome duplication (WGD) can yield detrimental outcomes, a role in facilitating the expansion of distribution range has been proposed. The Vitaceae genus Causonis exhibits great variations in species’ distribution ranges, with most species in the derived lineages having a much wider range than those in the early-diverged lineages. Hybridization and WGD events have been suggested to occur in Causonis based on evidence of phylogenetic discordance. The genus, therefore, provides us with an opportunity to for explore different hybridization and polyploidization modes in lineages with contrasting species’ distribution ranges. However, the evolutionary history of Causonis incorporating potential hybridization and WGD events remains to be explored. Results With plastid and nuclear data from dense sampling, this study resolved the phylogenetic relationships within Causonis and revealed significant cyto-nuclear discordance. Nuclear gene tree conflicts were detected across the genus, especially in the japonica-corniculata clade, which were mainly attributed to gene flow. This study also inferred the allopolyploid origin of the core Causonis species, which promoted the accumulation of stress-related genes. Causonis was estimated to have originated in continental Asia in the early Eocene, and experienced glaciation in the early Oligocene, shortly after the divergence of the early-divergent lineages. The japonica-corniculata clade mainly diversified in the Miocene, followed by temperature declines that may have facilitated secondary contact. Species distribution modeling based on current climate change predicted that the widespread C. japonica tends to be more invasive, while the endemic C. ciliifera may be at risk of extinction. Conclusions This study presents Causonis, a genus with complex reticulate evolutionary history, as a model of how hybridization and WGD modes differ in lineages of contrasting species’ geographic ranges. It is important to consider specific evolutionary histories and genetic properties of the focal species within conservation strategies.

Abstract Background Acute coronary syndrome (ACS) remains the leading cause of death and disability worldwide, especially when combined with type 2 diabetes mellitus (T2DM). Many multicenter randomized controlled trials have established the cardiovascular benefits of Sodium-Glucose cotransporter 2 inhibitors (SGLT-2i) in patients with T2DM at high cardiovascular risk. However, these studies did not include patients in the early stages of acute coronary events. This study investigated the cardiovascular protective effects of SGLT-2i in patients with ACS and T2DM. Methods A total of 232 hospitalized patients with ACS and T2DM were enrolled and divided into two groups based on their hypoglycemic drug treatment: the SGLT-2i and the non-SGLT-2i groups. Kaplan–Meier analysis and Cox regression were used to compare adverse cardiovascular outcomes in both groups. Results There were no significant differences in the hospital clinical outcomes between the SGLT-2i and non-SGLT-2i groups. The adverse cardiovascular outcomes did not significantly differ between both groups (hazard ratio (HR) 0.66, 95% confidence interval (CI) 0.35–1.25, P = 0.195). Moreover, the rehospitalization rates for ACS or heart failure (HF) were not significantly different between both groups (adjusted HR 0.56, 95%CI 0.28–1.10, P = 0.093). When analyzed separately, there was no significant difference in rehospitalizations for ACS (HR 0.87, 95% CI 0.40–1.87, P = 0.713). However, the SGLT-2i group showed lower rates of rehospitalizations for HF (adjusted HR 0.20, 95% CI 0.04–0.96, P = 0.045). Additionally, there was no significant difference in cardiovascular mortality between both groups (HR 1.75, 95% CI 0.28–10.97, P = 0.543). Notably, the SGLT-2i group exhibited a higher angina symptom control rate than the non-SGLT-2i group (adjusted odd ration (OR) 0.45, 95%CI 0.21–0.93, P = 0.031). Conclusion In recently diagnosed patients with ACS, who have T2DM, early initiation of SGLT-2i was associated with a lower risk of rehospitalization for HF and a higher rate of angina symptom control.

Abstract video captioning is a more challenging task that aims to generate abundant natural language descriptions, and it has become a promising direction for artificial intelligence. However, most existing methods are prone to ignore the problems of visual information redundancy and scene information omission due to the limitation of the sampling strategies. To address this problem, a semantic guidance network for video captioning is proposed. More specifically, a novel scene frame sampling strategy is first proposed to select key scene frames. Then, the vision transformer encoder is applied to learn visual and semantic information with a global view, alleviating information loss of modeling long-range dependencies caused in the encoder’s hidden layer. Finally, a non-parametric metric learning module is introduced to calculate the similarity value between the ground truth and the prediction result, and the model is optimized in an end-to-end manner. Experiments on the benchmark MSR-VTT and MSVD datasets show that the proposed method can effectively improve the description accuracy and generalization ability.

Human pancreatic neuroendocrine tumors (PanNETs) are a rare, deadly tumor type that is sporadic or arises in the background of a hereditary syndrome. A critical genetic event in sporadic tumors is inactivation of the gene menin 1 (MEN1) on chromosome 11, and indeed, PanNETs occur in patients with the hereditary syndrome multiple endocrine neoplasia type 1 (MEN1) due to germline mutations in the gene. Here, we review the recent progress in the field of molecular genetics and therapeutic targets of PanNETs. The key genomic alterations, including MEN1, ATRX/DAXX, mammalian target of rapamycin (mTOR), DNA damage and repair associated genes, vascular endothelial growth factor receptor (VEGFR) and SSTRs, and epigenetic aberrations in PanNETs are discussed. In addition, the commonly used preclinical models for PanNETs are enumerated.

Due to our lack of understanding of the host-pathogen epidemiology and the absence of effective control measures, tea leaf spot, caused by the fungus Epicoccum sorghinum, continues to reduce the productivity and quality of tea leaves in plantations in Guizhou Province, southwestern China. Here, samples of tea (Camellia sinensis [L.] O Kuntze) leaves either infected or uninfected by E. sorghinum were used as the study model. The mRNA and microRNA (miRNA) sequences in tea leaves from the two treatments were determined using the Illumina NovaSeq 6000 and the Illumina HiSeq 2500 platforms, respectively. In total, 33,932 genes or transcripts from tea leaves were annotated. In response to infection by E. sorghinum, 1,068 or 467 of the differentially expressed mRNAs (DEmRNAs) were up- or downregulated, respectively, and the DEmRNAs containing peroxidase 21 and LRR receptor-like serine/threonine-protein kinase ERECTA were enriched in terms of defense response. Meanwhile, 1,889 miRNAs were identified from infected or uninfected leaves. Nine or seven of the differentially expressed miRNAs (DEmiRNAs) were up- or downregulated, respectively. The DEmiRNAs MIR5303j-p5, MIR6173-p5, miR858-3p, and novel-miR0377-3p were predicted to bind to DEmRNAs. Fifteen DEmRNAs annotated into transcription factor proteins enriched with respect to the plant-pathogen interaction pathway were predicted to be bound by the DEmiRNA miR858-3p. The sequences and abundances of the mRNAs and miRNAs from tea leaves infected by E. nigrum, and the prediction of the interaction between DEmiRNAs and DEmRNAs could contribute to our understanding of this plant-pathogen interaction. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

To address the issues of decreased detection accuracy, false detections, and missed detections caused by scale differences between near and distant targets and environmental factors (such as lighting and water waves) in surface target detection tasks for uncrewed vessels, the YOLOv8-MSS algorithm is proposed to be used to optimize the detection of water surface targets. By adding a small target detection head, the model becomes more sensitive and accurate in recognizing small targets. To reduce noise interference caused by complex water surface environments during the downsampling process in the backbone network, C2f_MLCA is used to enhance the robustness and stability of the model. The lightweight model SENetV2 is employed in the neck component to improve the model’s performance in detecting small targets and its anti-interference capability. The SIoU loss function enhances detection accuracy and bounding box regression precision through shape awareness and geometric information integration. Experiments on the publicly available dataset FloW-Img show that the improved algorithm achieves an mAP@0.5 of 87.9% and an mAP@0.5:0.95 of 47.6%, which are improvements of 5% and 2.6%, respectively, compared to the original model.

Pipeline maintenance technology based on pipeline intelligent plugging robot (PIPR) has become an effective method for failure accident prevention of high-pressure subsea oil and gas pipelines. However, during the plugging operation, the vortexes and pressure fluctuation are presented under turbulent flow field excitation, which may lead to vortex-induced vibration and failure of the plugging operation. Therefore, in order to ensure the reliability of pipeline plugging, the vibration characteristics are analyzed using numerical simulation, providing guidance on the structural optimization of PIPR’s end face. Firstly, the flow field characteristics under different PIPR’s end faces are investigated. Secondly, an experimental scheme is designed based on Latin Hypercube Sampling Design (LHSD) optimized by greedy strategy. A mathematical model of the end face’s parameters and pressure gradient is established using a back propagation (BP) neural network. Then, an improved whale optimization algorithm (IWOA) is proposed to optimize the end face’s parameters to minimize the pressure gradient of the flow field. Finally, the experimental study is performed to observe the turbulent flow field and pressure fluctuation to validate the optimization results. The results demonstrate that the PIPR’s end face has a great influence on the vortex-induced vibration response. After structural optimization, the average pressure gradient of the optimal PIPR’s end face has decreased by 84.69% and 54.55% before and after the plugging process, compared to the original end face. This study can provide a reference for pipeline plugging operations, which is significant for preventing pipeline failure accidents.

Polysaccharides have been assessed as a potential natural active component in Chinese herbal medicine with anti-inflammatory properties. However, the complex and indefinite structures of polysaccharides limit their applications. This study explains the structures and anti-inflammatory potentials of three neutral polysaccharides, RIP-A1 (Mw 1.8 × 104 Da), RIP-B1 (Mw 7.4 × 104 Da) and RIP-B2 (Mw 9.3 × 104 Da), which were isolated from the roots of Isatis indigotica Fort. with sequenced ultrafiltration membrane columns, DEAE-52 and Sephadex G-100. The planar structures and microstructures of RIP-A1, RIP-B1 and RIP-B2 were further determined by HPGPC, GC–MS, methylation analysis, FT-IR, SEM and AFM, in which the structure of RIP-A1 was elucidated in detail using 1D/2D NMR. The Raw 264.7 cells were used for the anti-inflammatory activity in vitro. The results showed that RIP-A1, RIP-B1 and RIP-B2 are all neutral polysaccharides, with RIP-A1 having the smallest Mw and the simplest monosaccharide composition of the three. RIP-A1 is mainly composed of Ara and Gal, except for a small quantity of Rha. Its main structure is covered with glycosidic linkages of T-α-Araf, 1,2-α-Rhap, 1,5-α-Araf, T-β-Galp, 1,2,4-α-Rhap, 1,3,5-α-Araf and 1,6-β-Galp with 0.33:0.12:1.02:0.09:0.45:11.41:10.23. RIP-A1 significantly inhibited pro-inflammatory cytokines (NO, TNF-α, IL-6 and IL-1β) and increased anti-inflammatory cytokines (IL-4) in LPS-stimulated RAW 264.7 cells. Moreover, RIP-A1 could significantly inhibit the mRNA expression of TNF-α, IL-6 and L-1β. It could also activate IKK, p65 and IκBα (the components of the NF-κB signaling pathway). In conclusion, the above results show the structural characterization and anti-inflammatory potentials of RIP-A1 as an effective natural anti-inflammatory drug.

Abstract CIRBE (Colorado Inner Radiation Belt Experiment), a 3U CubeSat, was launched on 15 April 2023 into a sun synchronous orbit (97.4° inclination and 509 km altitude). The sole science payload onboard is REPTile‐2 (Relativistic Electron and Proton Telescope integrated little experiment—2), an advanced version of REPTile which operated in space between 2012 and 2014. REPTile‐2 has 60 channels for electrons (0.25–6 MeV) and 60 channels for protons (6.5–100 MeV). It has been working well, capturing detailed dynamics of the radiation belt electrons, including several orders of magnitude enhancements of the outer belt electrons after an intense magnetic storm, multiple “wisps”‐ an electron precipitation phenomenon associated with human‐made very low frequency (VLF) waves in the inner belt, and “drift echoes” of 0.25–1.4 MeV electrons across the entire inner belt and part of the outer belt. These new observations provide opportunities to test the understanding of the physical mechanisms responsible for these features.

Objective: This study explored the potential association between the Prognostic Nutritional Index (PNI) and the incidence of non-alcoholic fatty liver disease (NAFLD) and advanced liver fibrosis (AF) in the adult population of the United States. Methods: Information on 6409 participants ≥18 years old was downloaded from the U.S. National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Multivariate analysis was combined with demographic factors to assess the relationships between PNI, NAFLD, and AF. A restricted cubic spline (RCS) was used to characterise the nonlinear association between the PNI and NAFLD and AF. Results: Patients without NAFLD had substantially lower mean values for parameters such as age, lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), total cholesterol, triglycerides, HbA1c, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) than patients with NAFLD. Interestingly, non-NAFLD patients showed a pronounced increase in serum albumin levels compared to their NAFLD counterparts. In the subset without AF, there were discernibly lower measures of NLR, age, AST, ALT, γ-glutamyl transferase, triglycerides, neutrophil count, and body mass index (BMI) than in patients with AF. It was evident that those without AF had markedly elevated mean albumin and PNI levels in comparison to AF-affected individuals. In the comprehensive multivariable framework, a direct correlation was observed between PNI and NAFLD (adjusted odds ratio[aOR] = 1.07, 95% confidence interval [CI]: 1.05–1.09; p

BackgroundAn increase in deaths has been perceived during the pandemic, which cannot be explained only by COVID-19. The actual number of deaths far exceeds the recorded data on deaths directly related to SARS-CoV-2 infection. Data from early and short-lived pandemic studies show a dramatic shift in cardiovascular mortality. Grounded in the post-pandemic era, macroscopic big data on cardiovascular mortality during the pandemic need to be further reviewed and studied, which is crucial for cardiovascular disease prevention and control.MethodsWe retrieved and collected data associated with cardiovascular disease mortality from the National Vital Statistic System from the Center for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) platform based on the ICD-10 codes. We applied regression analysis to characterize overall cardiovascular disease mortality trends from 2010 to 2023 and built a time series model to predict mortality for 2020–2023 based on mortality data from 2010 to 2019 in order to affirm the existence of the excess deaths by evaluating observed vs. predicted mortality. We also conducted subgroup analyses by sex, age and race/ethnicity for the purpose of obtaining more specific sociodemographic information.ResultsAll-cause age-standardised mortality rates (ASMRs) for CVD dramatically increased between 2019 and 2021[annual percentage change (APC) 11.27%, p

Summary: Background: Infectious diseases and antimicrobial resistance (AMR) has become pressing concerns in China. We aimed to comprehensively investigate the burden of them. Methods: Data on infectious diseases and AMR were collected by the Global Antimicrobial Resistance Burden study 2019. Multinomial network meta-regression, logistic regression, and ensemble Spatiotemporal Gaussian process regression were used to fit the number and rate in DisMod-MR 2.1 modelling framework. We reported the number and rates of the disease burdens of 12 infectious syndromes by age and sex; described the burden caused by 43 pathogens; estimated the AMR burden of 22 bacteria and bacteria–antibiotics combinations. Findings: There were an estimated 1.3 million (95% uncertainty intervals, UI 0.8–1.9) infection-related deaths, accounting for 12.1% of the total deaths in China 2019. Males were 1.5 times more affected than females. Bloodstream infections (BSIs) were most lethal infectious syndrome, associating with 521,392 deaths (286,307–870,583), followed by lower respiratory infections (373,175), and peritoneal and intra-abdominal infections (152,087). These five leading pathogens were S aureus, A baumannii, E coli, S pneumoniae, and E spp., which were associated with 41.2% (502,658/1,218,693) of all infection-related deaths. The pathogens of different infectious syndromes exhibited significant heterogeneity. In 2019, more than 600 thousand deaths were associated with AMR, including 145 thousand deaths attributable to AMR. The top 3 AMR attributable to death were carbapenems-resistance A baumannii (18,143), methicillin-resistance S aureus (16,933) and third-generation cephalosporins-resistance E coli (8032). Interpretation: Infectious diseases and bacterial antimicrobial resistance were serious threat to public health in China, related to 1.3 million and more than 600 thousand deaths per-year, respectively. Antimicrobial stewardship was urgent. Funding: This work was supported by National Natural Science Foundation of China (82270626); China Mega-Project for Infectious Diseases (2017ZX10203202, 2013ZX10002005); the Project of Beijing Science and Technology Committee (Z191100007619037).

With the increasing demand for electric vehicles, further development of Li+ batteries require more comprehensive studies and advanced techniques to analyze various battery material and mechanisms. Determining the concentration of Li+ and electric potential inside batteries can effectively reveal and predict the electrochemical performance, understanding the charge/discharge processes and failure mechanisms. Recently, in situ observation of Li+ movement have been reported by utilizing optical microscopy, neutron imaging (NI), neutron depth profiling (NDP), and transmission electron microscopy (TEM)-based electron energy-loss spectroscopy (EELS). These extensive works suggest their broad potential applications, including revealing the spatial distribution of Li+, mapping electrode elements, and indicating degradation mechanisms. Moreover, direct visualization of potential changes through TEM-based electron holography (EH) and Kelvin probe force microscopy (KPFM) can discover and validate more valuable information. This perspective paper summarizes the current development of advanced in situ techniques for observing Li+ and potential distribution inside batteries for the first time. Additionally, we address the key challenges faced by these techniques along with their possible solutions. The aim of this paper is to provide a comprehensive discussion of in situ methods for analyzing reaction mechanisms, optimizing electrochemical performance, and potentially supporting the further development of battery simulation.

Objective and Impact Statement: High-intensity focused ultrasound (HIFU) therapy is a promising noninvasive method that induces coagulative necrosis in diseased tissues through thermal and cavitation effects, while avoiding surrounding damage to surrounding normal tissues. Introduction: Accurate and real-time acquisition of the focal region temperature field during HIFU treatment marked enhances therapeutic efficacy, holding paramount scientific and practical value in clinical cancer therapy. Methods: In this paper, we initially designed and assembled an integrated HIFU system incorporating diagnostic, therapeutic, and temperature measurement functionalities to collect ultrasound echo signals and temperature variations during HIFU therapy. Furthermore, we introduced a novel multimodal teacher–student model approach, which utilizes the shared self-expressive coefficients and the deep canonical correlation analysis layer to aggregate each modality data, then through knowledge distillation strategies, transfers the knowledge from the teacher model to the student model. Results: By investigating the relationship between the phantoms, in vitro, and in vivo ultrasound echo signals and temperatures, we successfully achieved real-time reconstruction of the HIFU focal 2D temperature field region with a maximum temperature error of less than 2.5 °C. Conclusion: Our method effectively monitored the distribution of the HIFU temperature field in real time, providing scientifically precise predictive schemes for HIFU therapy, laying a theoretical foundation for subsequent personalized treatment dose planning, and providing efficient guidance for noninvasive, nonionizing cancer treatment.