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Abstract Numerous studies have reported that long-term sports training can affect inhibitory control and induce brain functional alterations. However, the influence of environmental dynamics in sports training on inter-cortical connectivity has not been well studied. In the current study, we used twin-coil transcranial magnetic stimulation to investigate the functional connectivity between dorsolateral prefrontal cortex (DLPFC) and ipsilateral primary motor cortex (M1) during proactive and reactive inhibition in participants with sports skills in dynamic environment (open-skill experts), stable environment (closed-skill experts), and no sports skills (controls). Using a modified stop signal task, proactive inhibition was measured by the response delay effect (RDE), and reactive inhibition was measured by the stop-signal reaction time (SSRT). Intra-hemispheric DLPFC-M1 interactions and single pulse motor-evoked potentials (MEPs) were measured during the task. A stronger inhibitory effect of the DLPFC over M1 was observed during early reactive control stages compared to baseline levels. In addition, this inhibitory effect was pronounced when comparing open-skill experts to non-athlete controls, a relationship that was significantly correlated with superior reactive control performance. Furthermore, DLPFC to M1 influencing direction shifted from late proactive control to reactive control. Behavioral results also demonstrated enhanced proactive control abilities in open-skill experts relative to controls. Such enhancement may be due to the combination of environmental complexity and physical fitness in long-term skill training.

Abstract Depression questionnaire cutoffs are calibrated for screening accuracy and not to assess prevalence, but the Geriatric Depression Scale (GDS-15) is often used to estimate diagnostic prevalence among older adults, most commonly with scores of ≥ 5. We conducted an individual participant data meta-analysis to compare depression prevalence based on GDS-15 ≥ 5 to Structured Clinical Interview for Diagnostic and Statistical Manual (SCID) diagnoses and assessed whether an alternative cutoff could be more accurate. We used generalized linear mixed models to estimate prevalence. Data from 14 studies (3602 participants, 434 SCID major depression) were included. Pooled GDS-15 ≥ 5 prevalence was 34.2% (95% confidence interval [CI] 27.5–41.6%), and pooled SCID prevalence was 14.8% (95% CI 10.0–21.5%; difference of 17.6%, 95% CI 11.6–23.6%). GDS-15 ≥ 8 provided the closest estimate to SCID with mean difference of − 0.3% (95% prediction interval − 17.0–16.5%). Prevalence estimate differences were not associated with study or participant characteristics. In sum, GDS-15 ≥ 5 substantially overestimated depression prevalence. A cutoff of ≥ 8 was accurate overall, but heterogeneity was too high for implementation in practice. Validated diagnostic interviews should be used to estimate major depression prevalence among older adults.

ObjectiveTo assess the efficacy and safety of anlotinib combined with immune checkpoint inhibitors (ICIs) in patients with advanced non-small-cell lung cancer (NSCLC).MethodsClinical data on patients with advanced NSCLC were collected from June 2019 to October 2022 at Hebei General Hospital, China. The efficacy and safety of anlotinib combined with ICIs and platinum-containing chemotherapy were retrospectively analyzed. The primary endpoint was progression-free survival (PFS). The secondary endpoint was the disease control rate (DCR) and overall survival (OS). Survival curves were created using the Kaplan–Meier method. The efficacy and adverse reactions were evaluated according to the RECIST 1.1 and CTCAE 5.0 standards.ResultsA total of 54 patients were enrolled in this study after propensity score matching (PSM), including 27 men and 17 women, with a median age of 59. A total of 26 patients received anlotinib + ICIs + platinum-containing chemotherapy (AIC), 15 patients received anlotinib + platinum-containing chemotherapy (AC), and 13 patients received ICIs + platinum-containing chemotherapy (IC). The PFS of the AIC group was 7.76 months (95% CI: 3.71–NC). The DCR was 65.38%. The OS endpoint had not been reached, The AIC combination regimen group had a significantly longer PFS than the IC group (mPFS, 7.76 vs. 2.33 months, p=0.012, HR=0.23, 95% CI: 0.06–0.8). There was no significant difference in the DCR between the two groups (65.38% vs. 53.85%, p=0.326). There was a statistically significant difference in PFS between the AC group and the IC group (mPFS, 9.2 vs. 2.33 months, p=0.02, HR=0.14, 95% CI: 0.03–0.65). There was no significant difference in the DCR between the two groups (40% vs. 53.85%, p=0.445). The common adverse reactions of the combination of anti-angiogenic agents, ICIs, and platinum-containing chemotherapy were anemia (34.62%), allergic reactions (19.23%), thrombocytopenia (11.54%), gastrointestinal reactions (15.38%), and hepatobiliary disorders (11.54%). Most of them were manageable.ConclusionsAnlotinib combined with immune checkpoint inhibitors and platinum-containing chemotherapy regimens offers a good survival benefit for patients with advanced non-small-cell lung cancer who fail to respond to standard therapy. When both efficacy and safety are considered, a combination of anti-angiogenic agents, ICIs, and platinum-containing chemotherapy can be used as a choice for the treatment of advanced NSCLC.

BackgroundOptimizing the diagnosis and treatment of hematological diseases is a challenging yet crucial research area. Effective treatment plans typically require the comprehensive integration of cell morphology, immunology, cytogenetics, and molecular biology. These plans also consider patient-specific factors such as disease stage, age, and genetic mutation status. With the advancement of artificial intelligence (AI), more “AI + medical” application models are emerging. In clinical practice, many AI-assisted systems have been successfully applied to the diagnosis and treatment of hematological diseases, enhancing precision and efficiency and offering valuable solutions for clinical practice.ObjectiveThis study summarizes the research progress of various AI-assisted systems applied in the clinical diagnosis and treatment of hematological diseases, with a focus on their application in morphology, immunology, cytogenetics, and molecular biology diagnosis, as well as prognosis prediction and treatment.MethodsUsing PubMed, Web of Science, and other network search engines, we conducted a literature search on studies from the past 5 years using the main keywords “artificial intelligence” and “hematological diseases.” We classified the clinical applications of AI systems according to the diagnosis and treatment. We outline and summarize the current advancements in AI for optimizing the diagnosis and treatment of hematological diseases, as well as the difficulties and challenges in promoting the standardization of clinical diagnosis and treatment in this field.ResultsAI can significantly shorten turnaround times, reduce diagnostic costs, and accurately predict disease outcomes through applications in image-recognition technology, genomic data analysis, data mining, pattern recognition, and personalized medicine. However, several challenges remain, including the lack of AI product standards, standardized data, medical–industrial collaboration, and the complexity and non-interpretability of AI systems. In addition, regulatory gaps can lead to data privacy issues. Therefore, more research and improvements are needed to fully leverage the potential of AI to promote standardization of the clinical diagnosis and treatment of hematological diseases.ConclusionOur results serve as a reference point for the clinical diagnosis and treatment of hematological diseases and the development of AI-assisted clinical diagnosis and treatment systems. We offer suggestions for further development of AI in hematology and standardization of clinical diagnosis and treatment.

BackgroundThe literature on whether physical activity (PA) and PA and diet (PA+Diet) mobile apps improve cardiovascular disease (CVD) risk factors is promising. ObjectiveThe aim of this meta-review is to provide an evidence synthesis of systematic reviews and meta-analyses examining the influence of PA and PA+Diet apps on the major CVD risk factors. MethodsWe systematically searched 5 databases until January 12, 2022. Included systematic reviews and meta-analyses (1) reported the CVD risk factor outcomes of BMI, waist circumference, body weight, blood pressure (BP), hemoglobin A1c (HbA1c), fasting blood glucose, blood lipids, or PA; (2) enrolled healthy participants ≥18 years who may or may not have the metabolic syndrome, diabetes mellitus, or preexisting CVD risk factors; (3) reviewed PA or PA+Diet app interventions integrating behavioral change techniques (BCT) to deliver their information; and (4) had a nonapp control. ResultsIn total, 17 reviews (9 systematic reviews and 8 meta-analyses) published between 2012 and 2021 qualified. Participants were middle-aged, mostly women ranging in number from 10 to 62,219. Interventions lasted from 1 to 24 months, with the most common behavioral strategies being personalized feedback (n=8), self-monitoring (n=7), and goal setting (n=5). Of the PA app systematic reviews (N=4), the following CVD risk factors improved: body weight and BMI (n=2, 50%), BP (n=1, 25%), HbA1c (n=1, 25%), and blood lipids (n=1, 25%) decreased, while PA (n=4, 100%) increased. Of the PA+Diet app systematic reviews (N=5), the following CVD risk factors improved: body weight and BMI (n=3, 60%), BP (n=1, 20%), and HbA1c (n=3, 60%) decreased, while PA (n=3, 60%) increased. Of the PA app meta-analyses (N=1), the following CVD risk factors improved: body weight decreased (–0.73 kg, 95% CI –1.45 to –0.01; P=.05) and PA increased by 25 minutes/week (95% CI 0.58-1.68; P

Abstract Venetoclax, a small molecule inhibitor of BCL‐2, has demonstrated efficacy in treating acute leukemias and has been recommended as one of the first‐line anti‐leukemia therapies. Although venetoclax has been suggested to probably possess the ability to penetrate the central nervous system (CNS), current data to elucidate the characteristics of venetoclax in cerebrospinal fluid (CSF), bone marrow (BM), and plasma are still lacking. This study investigated the real‐world characteristics of venetoclax concentrations in CSF, BM, and plasma in acute leukemia patients. Thirteen acute leukemia patients treated with venetoclax were included, with paired samples of CSF, BM, and plasma collected and venetoclax concentrations measured using LC–MS/MS. With the results, the median venetoclax concentrations were 2030 ng/mL in plasma, 16.7 ng/mL in CSF, and 1390 ng/mL in BM. The percentages of CSF/plasma and BM/plasma were 0.74% and 70.37%, respectively. While no direct correlation was observed between CSF and plasma venetoclax levels, there was a trend toward an improved CSF/plasma percentage over time following the last administration of venetoclax. In contrast, a strong correlation was found between BM and plasma levels. This study demonstrated that venetoclax could reach its effective concentration in most patients, suggesting its potential clinical utility in the management of CNS involvement in acute leukemia.

Objective: To provide a synthesis of randomized controlled trials (RCTs) investigating statin-associated muscle symptoms (SAMS) in adults who underwent exercise training intervention. Patients and Methods: We systematically searched 5 electronic databases for placebo-controlled RCTs through January 31, 2023. We included short-term and long-term exercise interventions that compared the efficacy and safety of exercise+statin vs exercise+placebo in healthy adults and reported SAMS preintervention and postintervention. Publication bias and methodological study quality assessments were performed. Results: Five of 454 potentially qualifying RCTs met the inclusion criteria, all short-term exercise RCTs. Participants were predominantly physically inactive young to middle-aged (M=37.2 y) men (57%), 252 (49%) who were on statin therapy, and 271 (53%) on placebo. Of the 3 RCTs providing qualitative SAMS results, 19 (9%) out of 220 participants reported SAMS on exercise+statin and 10 (4%) out of 234 reported SAMS on exercise+placebo. There was no difference between exercise+statin vs exercise+placebo for maximal oxygen consumption (d=−0.18; 95% CI, −0.37 to 0.00; P=.06) or creatine kinase after short-term exercise (d=0.59; 95% CI, −0.06 to 1.25; P=.08). Participants in the exercise+statin group reduced low-density lipoprotein cholesterol vs exercise+placebo (d=−1.84; 95% CI, −2.28 to −1.39; P

Abstract Background Air pollution poses a significant health risk to the human population, especially for vulnerable groups such as the elderly, potentially discouraging their engagement in physical activity. However, there is a lack of sufficient objective and longitudinal data in current research on how air pollution affects physical activity among older adults. With these gaps, we aimed to explore the relationship between air pollution and objective measurement-based physical activity among older adults by engaging in a longitudinal study design. Methods A total of 184 older adults were recruited from three cities with varying levels of air quality. Mean daily minutes of physical activity were measured with 7 consecutive days of accelerometer monitoring (ActiGraph GT3X-BT). Corresponding air pollution data including daily PM2.5 (µg/m3), PM10 (µg/m3) and air quality index (AQI) were sourced from the China National Environmental Monitoring Centre at monitor locations close to older adults’ addresses. Associations between air quality and physical activity were estimated using a fixed effect model, adjusting for average daytime temperature, rain, age and weight. Results AQI and PM2.5 were observed to exhibit significant, inverse, and linear associations with mean daily walk steps, minutes of light physical activity (LPA), moderate physical activity (MPA) and moderate-to-vigorous physical activity (MVPA) in the single variable models. A one-level increase in AQI corresponded to a decline in 550.04 steps (95% [CI] = -858.97, -241.10; p

Summary: The model of M2-like tumor-associated macrophages (TAMs) is an increasingly attractive model for the study of TAMs. However, the detailed process of M2-like TAMs polarization induced by lactic acid or conditioned medium from Lewis cells (LCM) and the identification of M2-like TAMs is not yet available. In this protocol, we present the detailed methods to induce M2-like TAMs polarization and verify its functionality in order to better carry out related research.For complete details on the use and execution of this protocol, please refer to Fang et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

In recent years, the rapid development of nanomaterials and nanoproducts has led to their widespread application in energy, aerospace, agriculture, industry, and biomedicine. However, carbon nanomaterials (CNMs) have been shown to possess toxic properties that negatively impact both the environment and human health. Then, toxicological risk assessment of CNMs are necessary to identify their potential adverse effects. This review examines the safety and sustainability of fullerenes, graphene, and carbon nanotubes in critical areas. First, the toxicity of CNMs in medicine, environmental engineering, energy, food, cosmetic and agriculture sectors using traditional detection methods is summarized. Then, the application of machine learning techniques for assessing the toxicity of these types of CNMs is reviewed. Finally, a comparative analysis of traditional and machine learning methods for detecting carbon nanomaterial toxicity is presented, highlighting key issues that need to be addressed in future research.

Abstract Ketone bodies serve as an energy source, especially in the absence of carbohydrates or in the extended exercise. Adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a crucial energy sensor that regulates lipid and glucose metabolism. However, whether AMPK regulates ketone metabolism in whole body is unclear even though AMPK regulates ketogenesis in liver. Prolonged resulted in a significant increase in blood and urine levels of ketone bodies in wild-type (WT) mice. Interestingly, fasting AMPKα2–/– and AMPKα1–/– mice exhibited significantly higher levels of ketone bodies in both blood and urine compared to fasting WT mice. BHB tolerance assays revealed that both AMPKα2–/– and AMPKα1–/– mice exhibited slower ketone consumption compared to WT mice, as indicated by higher blood BHB or urine BHB levels in the AMPKα2–/– and AMPKα1–/– mice even after the peak. Interestingly, fasting AMPKα2–/– and AMPKα1–/– mice exhibited significantly higher levels of ketone bodies in both blood and urine compared to fasting WT mice. . Specifically, AMPKα2ΔMusc mice showed approximately a twofold increase in blood BHB levels, and AMPKα2ΔMyo mice exhibited a 1.5-fold increase compared to their WT littermates after a 48-h fasting. However, blood BHB levels in AMPKα1ΔMusc and AMPKα1ΔMyo mice were as same as in WT mice. Notably, AMPKα2ΔMusc mice demonstrated a slower rate of BHB consumption in the BHB tolerance assay, whereas AMPKα1ΔMusc mice did not show such an effect. Declining rates of body weights and blood glucoses were similar among all the mice. Protein levels of SCOT, the rate-limiting enzyme of ketolysis, decreased in skeletal muscle of AMPKα2–/– mice. Moreover, SCOT protein ubiquitination increased in C2C12 cells either transfected with kinase-dead AMPKα2 or subjected to AMPKα2 inhibition. AMPKα2 physiologically binds and stabilizes SCOT, which is dependent on AMPKα2 activity.

Background: In March 2022, a severe outbreak of the SARS-CoV-2 Omicron variant occurred in Shanghai. This study aimed to determine disease severity, clinical features, clinical outcome in hospitalized patients with the Omicron variant and evaluate the effectiveness of one-dose, two-dose, and three-dose inactivated vaccines in reducing viral loads, disease course, ICU admissions and severe diseases. Methods: Retrospective cohort analysis was performed on 5,170 adult patients (≥18 years) identified as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction admitted at Shanghai Medical Center for Gerontology between March 2022 and June 2022. Demographic information, laboratory data, immunization status, clinical characteristics and outcomes were extracted from electronic medical records. Results: Among 5,170 enrolled patients, the median age was 53 years, and 2,861 (55.3 %) were male. 71.0 % were mild COVID-19 cases, and cough (1,137 [22.0 %]), fever (592 [11.5 %]), sore throat (510 [9.9 %]), and fatigue (334 [6.5 %]) were the most common symptoms on the patient’s first admission. The median length of hospital stay was 8.7 ± 4.5 days. In multivariate logistic analysis, booster vaccination can significantly reduce ICU admissions and decrease the severity of COVID-19 outcome when compared with less doses of vaccine (OR = 0.75, 95 %CI, 0.62–0.91, P ≤ 0.005; OR = 0.99, 95 %CI, 0.99–1.00, p

Climate change imposes tighter limits on carbon emissions, which require the development of more green electricity. Deep sea wind power has the advantages of high wind energy density, high power generation utilization hours, no land occupation, and near to power load centers for easy on-site consumption, which lead to a broad market prospect. In the foreseeable future, deep sea wind power will usher in large-scale construction and development. The initial investment and construction cost of deep sea wind power is high, subsidies are gradually decreasing, and there is a lack of full life cycle economic analysis combined with various market policies, resulting in a lack of guidance for its investment and construction. In order to promote the development of deep sea wind power, relevant cost recovery mechanisms must be found. This paper proposes a system cost allocation method based on the comparative difference method and load similarity with consideration of the transformation and operation costs of thermal power, demand-side response, and energy storage; a cost allocation method based on carbon trading and green certificate trading income is proposed; and a time sequence optimization operation simulation model is established to maximize the deep sea wind power income. A case study is proposed for a 300 MW deep sea wind farm, the results show that the cost allocation method and cost allocation model proposed in this paper have a significant effect on wind power cost recovery, and the effectiveness of the proposed method and model is verified.

In navigating the complexities of social life, humans have evolved to interpret invisible odorous chemical cues, with profound behavioural impacts often unbeknown to the conscious mind. The manifestation of this in humans is evident in the scent of androstadienone (androsta-4,16-dien-3-one), an odorous compound which is considered a putative human pheromone. The current study investigated the effect of androstadienone on social distance-dependent prosocial behaviour measured by a social discounting task, in which participants chose between selfish and generous options. Based on our pre-registration, we predicted a sex-specific effect, with males exposed to androstadienone exhibiting increased generosity, while females would choose more selfishly. Employing a double-blind, placebo-controlled, between-subject design, we recruited 170 participants who were randomly assigned to either the androstadienone or control condition. Olfactory stimuli were administered while participants completed the social discounting task. Inconsistent with our hypothesis, inhaling androstadienone did not impact social distance-dependent prosocial behaviour. This finding was supported by multiple estimates of prosociality, including model-free, model-based and maximum likelihood estimation. Further analyses indicated that androstadienone administration did not influence perceived social distance or bias participants towards being generous or selfish. Thus, our empirical findings provide no support for the hypothesis that androstadienone modulates generosity.

Background: Poria acid (PAC) is a triterpene compound found in Poria cocos, a traditional Chinese medicine (TCM). The current study aims to explore the therapeutic effects and potential mechanisms of PAC on the migration and proliferation of human renal cell carcinoma (RCC) cells as well as tumor growth in animal model. Methods: Cell viability and proliferative capacity of normal renal cells and RCC cells were investigated by MTT assay. In addition, 786-O cells were divided into four groups and treated with different concentrations of PAC (0, 20, 40, and 60 μM) for 48 h. Cell scratch test and cell invasion assay were performed to evaluate the effects of PAC on the invasion and migration of RCC cells, respectively. The effects of PAC on apoptosis of RCC cells and expression levels of PI3K/Akt/NF-kB signaling pathway-related biomarkers were investigated using TUNEL staining and Western blotting methods, respectively. Effects of PAC on the inhibitory activity of RCC tumor in mice were evaluated in a 786-O CDX model. Results: The study found that PAC inhibited the viability of RCC cells in a dose-dependent manner, as demonstrated by in vitro cell assays (p 0.05). PAC also significantly inhibited the migration and invasion of RCC via EMT/MMP signaling pathways (p

Precise nitrogen supply is crucial for ensuring the quality of cut chrysanthemums (Chrysanthemum morifolium Ramat.). The nitrogen nutrition index (NNI) serves as an important indicator for diagnosing crop nitrogen (N) nutrition. Hyperspectral remote sensing (HRS) technology has been widely used in monitoring crop N status due to its rapid, accurate, and non-destructive capabilities. However, its application in estimating the NNI of cut chrysanthemums has received limited attention. Therefore, this study aimed to use HRS to accurately determine the cut chrysanthemum NNI, thereby providing valuable guidance for managing N fertilization. During several key growth stages, a hyperspectral spectroradiometer was used to capture hyperspectral reflectance data (350–2500 nm) from three leaf layers. Subsequently, cut chrysanthemum canopies were sampled for aboveground biomass (AGB) and plant nitrogen concentration (PNC). The collected AGB and PNC data were then utilized to fit the critical N (Nc) dilution curve of cut chrysanthemums using a Bayesian hierarchical model, enabling the calculation of the NNI. Finally, spectral indices and partial least squares regression (PLSR) were used to establish the NNI estimation model for cut chrysanthemums. The results showed that the Nc dilution curve of the cut chrysanthemums was Nc = 5.401 × AGB−0.468. The first leaf layer (L1) proved to be optimal for estimating cut chrysanthemum NNI. Additionally, a newly proposed two-band spectral index, DVI-L1 (R1105, R700), demonstrated moderate predictive capabilities for the NNI of cut chrysanthemums (R2 = 0.5309, RMSE = 0.3210). Compared with the spectral index-based NNI estimation model, PLSR-L1 showed the best performance in estimating the cut chrysanthemum NNI (R2 = 0.8177, RMSE = 0.2000). Our results highlight the rapid NNI prediction potential of HRS and its significance in facilitating precise N management in cut chrysanthemums.

High-strength bolts play a crucial role in ultra-high-pressure equipment such as bridges and railway tracks. Effective monitoring of bolt conditions is of paramount importance for common fault repair and accident prevention. This paper aims to detect and classify bolt corrosion levels accurately. We design and implement a bolt corrosion classification system based on a Wireless Acoustic Emission Sensor Network (WASN). Initially, WASN nodes collect high-speed acoustic emission (AE) signals from bolts. Then, the ReliefF feature selection algorithm is applied to identify the optimal feature combination. Subsequently, the Extreme Learning Machine (ELM) model is utilized for bolt corrosion classification. Additionally, to achieve high prediction accuracy, an improved goose algorithm (GOOSE) is employed to ensure the most suitable parameter combination for the ELM model. Experimental measurements were conducted on five classes of bolt corrosion levels: 0%, 25%, 50%, 75%, and 100%. The classification accuracy obtained using the proposed method was at least 98.04%. Compared to state-of-the-art classification diagnostic models, our approach exhibits superior AE signal recognition performance and stronger generalization ability to adapt to variations in working conditions.

Abstract The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings.

Summary: Background: Frail elderly patients with newly diagnosed multiple myeloma (NDMM) have inferior survival and less benefit from high-dose therapies. This prospective study aimed to investigate the efficacy, safety, and quality of life (QoL) of induction treatment of ixazomib/lenalidomide/dexamethasone (IRd) and ixazomib/pegylated liposomal doxorubicin/dexamethasone (IDd) followed by ixazomib/dexamethasone (Id) maintenance therapy in frail, elderly patients with NDMM. Methods: From July 2019 to December 2021, this non-randomized concurrent controlled clinical study enrolled 120 NDMM patients aged ≥65 years with frailty defined by the International Myeloma Working Group (IMWG) frailty score or Mayo geriatric scoring system. The enrolled patients received 6–8 cycles of IRd or IDd followed by Id maintenance therapy for a minimum of 2 years at the discretion of physicians based on patient's clinical characteristics (chiCTR1900024917). Findings: The median age was 71 years and 55% of the patients were males. The overall response rate (ORR) was 82% and 77%, complete response (CR) rate was 25% and 12% for IRd and IDd groups, respectively. The difference in ORR of the Idd group minus the IRd group was −5.36% (95% CI: −18.9% to 8.19%), indicating that the ORR of the IDd group was neither inferior nor non-inferior to the IRd group. After a median follow-up of 34.3 months, the median progression-free survival (PFS) was 21.6 and 13.9 months, OS was not reached and 29.2 months in IRd and IDd groups, respectively. 28 and 33 patients discontinued induction therapy, 20 and 19 discontinued maintenance therapy in IRd and IDd groups, respectively. Cumulative Grade 3 or higher hematological adverse events (AEs) occurred in 10 of the 60 patients (17%) and non-hematological AEs occurred in 15 of the 60 patients (25%) in the IRd group, while 13 of the 60 patients (22%) and 21 of the 60 patients (35%) in the IDd group. Patients were observed with clinically significant improvement in QoL when compared with that at baseline in both IRd and IDd groups by evaluation per cycle (P

Fusarium wilt is a common fungal disease in sesame caused by Fusarium oxysporum f. sp. sesami (FOS). To determine the toxin production profiles of the FOS isolates with different pathogenicity levels under various culture conditions, we assessed the content variation of fusaric acid (FA) and 9, 10-dehydrofusaric acid (9, 10-DFA) produced by the four representative FOS isolates. Results indicated that the concentration of FA reached to a maximum of 2848.66 ​μg/mL in Czapek medium, while 9, 10-DFA was mainly produced in Richard and Low-carbon Richard medium. The concentration of 9, 10-DFA on Richard culture medium varied from 0 ​μg/mL to 716.89 ​μg/mL. Of the five culture media used in this study, Czapek culture medium was the most conductive to produce FA. FA production was significantly affected by culture medium, culture time, and their interactions. Results suggest that there is no correlation between toxin production and pathogenicity level of FOS isolates. These findings provide key information for the mechanism analysis of FOS- sesame interaction and pathogen control.

Abstract Background The present study intended to establish a predictive nomogram for early relapse (ER) ( UNL, and response less than very good partial response (VGPR) after ASCT. The calibration curve showed good fitness between the nomogram predictions and the actual observations and the nomogram was further validated by a clinical decision curve. The nomogram's C‐index achieved 0.75 (95% CI, 0.70–0.80), which was higher than that of the Revised International Staging System (R‐ISS) (0.62), ISS (0.59), and Durie–Salmon (DS) staging system (0.52). The discrimination ability of the nomogram in the validation cohort was superior to that of the other staging systems (C‐index: 0.73 vs. R‐ISS (0.54), ISS (0.55), and DS staging system (0.53)). DCA showed the prediction nomogram adds much more clinical utility. Different scores of the nomogram draw a distinction of OS. Conclusion The present nomogram could serve as a feasible and accurate prediction of ER in novel drug induction transplantation‐eligible MM patients, which could help modify the post‐ASCT strategy for patients at high risk of ER.

Abstract Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7–12 (difference range − 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13–15 (all differences − 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS and can be used when there are concerns about the implications of administering EPDS item 10. Trial registration: The original IPDMA was registered in PROSPERO (CRD42015024785).

Modern society increasingly recognizes brain fatigue as a critical factor affecting human health and productivity. This study introduces a novel, portable, cost-effective, and user-friendly system for real-time collection, monitoring, and analysis of physiological signals aimed at enhancing the precision and efficiency of brain fatigue recognition and broadening its application scope. Utilizing raw physiological data, this study constructed a compact dataset that incorporated EEG and ECG data from 20 subjects to index fatigue characteristics. By employing a Bayesian-optimized multi-granularity cascade forest (Bayes-gcForest) for fatigue state recognition, this study achieved recognition rates of 95.71% and 96.13% on the DROZY public dataset and constructed dataset, respectively. These results highlight the effectiveness of the multi-modal feature fusion model in brain fatigue recognition, providing a viable solution for cost-effective and efficient fatigue monitoring. Furthermore, this approach offers theoretical support for designing rest systems for researchers.

Background Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance.Methods We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies.Results Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types.Conclusions Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy.

ABSTRACT The marine methylotrophic OM43 clade is considered an important bacterial group in coastal microbial communities. OM43 bacteria, which are closely related to phytoplankton blooms, have small cell sizes and streamlined genomes. Bacteriophages profoundly shape the evolutionary trajectories, population dynamics, and physiology of microbes. The prevalence and diversity of several phages that infect OM43 bacteria have been reported. In this study, we isolated and sequenced two novel OM43 phages, MEP401 and MEP402. These phages share 90% of their open reading frames (ORFs) and are distinct from other known phage isolates. Furthermore, a total of 99 metagenomic viral genomes (MVGs) closely related to MEP401 and MEP402 were identified. Phylogenomic analyses suggest that MEP401, MEP402, and these identified MVGs belong to a novel subfamily in the family Zobellviridae and that they can be separated into two groups. Group I MVGs show conserved whole-genome synteny with MEP401, while group II MVGs possess the MEP401-type DNA replication module and a distinct type of morphogenesis and packaging module, suggesting that genomic recombination occurred between phages. Most members in these two groups were predicted to infect OM43 bacteria. Metagenomic read-mapping analysis revealed that the phages in these two groups are globally ubiquitous and display distinct biogeographic distributions, with some phages being predominant in cold regions, some exclusively detected in estuarine stations, and others displaying wider distributions. This study expands our knowledge of the diversity and ecology of a novel phage lineage that infects OM43 bacteria by describing their genomic diversity and global distribution patterns. IMPORTANCE OM43 phages that infect marine OM43 bacteria are important for host mortality, community structure, and physiological functions. In this study, two OM43 phages were isolated and characterized. Metagenomic viral genome (MVG) retrieval using these two OM43 phages as baits led to the identification of two phage groups of a new subfamily in the family Zobellviridae. We found that group I MVGs share similar genomic content and arrangement with MEP401 and MEP402, whereas group II MVGs only possess the MEP401-type DNA replication module. Metagenomic mapping analysis suggests that members in these two groups are globally ubiquitous with distinct distribution patterns. This study provides important insights into the genomic diversity and biogeography of the OM43 phages in the global ocean.

Asthma is a common disease that seriously threatens public health. With significant developments in bronchoscopy, different interventional pulmonology techniques for refractory asthma treatment have been developed. These technologies achieve therapeutic purposes by targeting diverse aspects of asthma pathophysiology. However, even though these newer techniques have shown appreciable clinical effects, their differences in mechanisms and mutual commonalities still deserve to be carefully explored. Therefore, in this review, we summarized the potential mechanisms of bronchial thermoplasty, targeted lung denervation, and cryoablation, and analyzed the relationship between these different methods. Based on available evidence, we speculated that the main pathway of chronic airway inflammation and other pathophysiologic processes in asthma is sensory nerve-related neurotransmitter release that forms a “neuro-immunity crosstalk” and amplifies airway neurogenic inflammation. The mechanism of completely blocking neuro-immunity crosstalk through dual-ablation of both efferent and afferent fibers may have a leading role in the clinical efficacy of interventional pulmonology in the treatment of asthma and deserves further investigation.

Abstract Objectives Optimal cutoff thresholds are selected to separate ‘positive’ from ‘negative’ screening results. We evaluated how depression screening tool studies select optimal cutoffs. Methods We included studies from previously conducted meta‐analyses of Patient Health Questionnaire‐9, Edinburgh Postnatal Depression Scale, or Hospital Anxiety and Depression Scale—Depression accuracy. Outcomes included whether an optimal cutoff was selected, method used, recommendations made, and reporting guideline and protocol citation. Results Of 212 included studies, 172 (81%) attempted to identify an optimal cutoff, and 147 of these 172 (85%) reported one or more methods. Methods were heterogeneous with Youden's J (N = 35, 23%) most common. Only 23 of 147 (16%) studies described a rationale for their method. Rationales focused on balancing sensitivity and specificity without describing why desirable. 131 of 172 studies (76%) identified an optimal cutoff other than the standard; most did not make use recommendations (N = 56; 43%) or recommended using a non‐standard cutoff (N = 53; 40%). Only 4 studies cited a reporting guideline, and 4 described a protocol with optimal cutoff selection methods, but none used the protocol method in the published study. Conclusions Research is needed to guide how selection of cutoffs for depression screening tools can be standardized and reflect clinical considerations.

Abstract High levels of reactive oxygen species (ROS) lead to progressive deterioration of mitochondrial function, resulting in tissue degeneration. In this study, ROS accumulation induced nucleus pulposus cells (NPCs) senescence is observed in degenerative human and rat intervertebral disc, suggesting senescence as a new therapeutic target to reverse intervertebral disc degeneration (IVDD). By targeting this, dual‐functional greigite nanozyme is successfully constructed, which shows the ability to release abundant polysulfides and presents strong superoxide dismutase and catalase activities, both of which function to scavenge ROS and maintain the tissue at physical redox level. By significantly lowering the ROS level, greigite nanozyme rescues damaged mitochondrial function in IVDD models both in vitro and in vivo, rescues NPCs from senescence and alleviated the inflammatory response. Furthermore, RNA‐sequencing reveals ROS‐p53‐p21 axis is responsible for cellular senescence‐induced IVDD. Activation of the axis abolishes greigite nanozyme rescued NPCs senescence phenotype, as well as the alleviated inflammatory response to greigite nanozyme, which confirms the role of ROS‐p53‐p21 axis in greigite nanozyme's function to reverse IVDD. In conclusion, this study demonstrates that ROS‐induced NPCs senescence leads to IVDD and the dual‐functional greigite nanozyme holds strong potential to reverse this process, providing a novel strategy for IVDD management.

Purpose: This study aimed to develop quality indicators for the care of older adults with disabilities in long-term care facilities (LTCFs) based on Maslow’s hierarchy of needs. Methods: The draft of the quality indicators was drawn up based on a literature review and research group discussion. The quality indicators were finalized by two rounds of expert consultation (involving 15 experts) using the Delphi method. The Analytic Hierarchy Process was applied to calculate the indicators’ weight. Results: The response rates of the two rounds of consultation were 100% and 93%, and the expert authority coefficients were 0.86 and 0.87. After two rounds of consultation, the expert opinion coordination coefficients of the first-, second- and third-level indicators were 0.42, 0.25, and 0.96, respectively (P

BackgroundThis study aimed to explore the potential effects of long non-coding RNAs (lncRNAs) in multiple myeloma (MM) patients using two detection methods: high-throughput sequencing and microarray.MethodsIn this study, lncRNAs were detected in 20 newly diagnosed MM patients, with 10 patients analyzed by whole transcriptome-specific RNA sequencing and 10 patients analyzed by microarray (Affymetrix Human Clariom D). The expression levels of lncRNAs, microRNAs, and messenger RNAs (mRNAs) were analyzed, and the differentially expressed lncRNAs identified by both methods were selected. The significant differentially expressed lncRNAs were further validated using PCR.ResultsThis study established the aberrant expression of certain lncRNAs involved in the occurrence of MM, with AC007278.2 and FAM157C showing the most significant differences. The top 5 common pathways identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were the chemokine signaling pathway, inflammatory mediator regulation, Th17 cell differentiation, apoptosis, and NF-kappa B signaling pathway. Furthermore, three microRNAs (miRNAs) (miR-4772-3p, miR-617, and miR-618) were found to constitute competing endogenous RNA (ceRNA) networks in both sequencing and microarray analyses.ConclusionsBy the combination analysis, our understanding of lncRNAs in MM will be increased significantly. More overlapping differentially expressed lncRNAs were found to predict therapeutic targets precisely.

Using data from the Chandra X-ray Observatory, we revisit the reverse shock in the supernova remnant (SNR) Cassiopeia A. Based on spectroscopy of a series of annuli in the northwest (NW) and southeast (SE), we get the radial profiles of the S/Si K α line flux ratio and Fe K α line centroid energy. They both show monotonic increase, confirming that the Si- and Fe-rich ejecta are heated by the reverse shock. The abrupt change of the S and Si line flux ratio is clearly observed in Cassiopeia A, leading to the determination of the reverse-shock location (∼1.′71 $\,\pm \,$ 0.′16 and ∼1.′35 $\,\pm \,$ 0.′18 in the NW and SE, with respect to the central source). By comparing the radial profiles of the S and Si line flux, we find that the reverse shock is moving outward in the frame of the observer, and the velocities are ∼3950 ± 210 km s ^−1 and ∼2900 ± 260 km s ^−1 in the NW and SE, respectively. In contrast, the velocities become ∼1150 km s ^−1 (NW) and ∼1300 km s ^−1 (SE) in the ejecta frame. Our measured reverse-shock velocities are quite consistent with those obtained from the X-ray and/or optical images. They therefore supply a cross-check of the accuracy for the two available methods for measuring the reverse-shock velocity in SNRs. Both the location and the velocity of the reverse shock show apparent asymmetry, suggesting that the asymmetric explosion of the progenitor plays a key role in the interaction between the reverse shock and the ejecta, ultimately shaping the complex features observed in SNRs.

The tropospheric Zenith Wet Delay (ZWD) is one of the primary sources of error in Global Navigation Satellite Systems (GNSS). Precise ZWD modeling is essential for GNSS positioning and Precipitable Water Vapor (PWV) retrieval. However, the ZWD modeling is challenged due to the high spatiotemporal variability of water vapor, especially in low latitudes and specific climatic regions. Traditional ZWD models make it difficult to accurately fit the nonlinear variations in ZWD in these areas. A hybrid deep learning algorithm is developed for high-precision ZWD modeling, which considers the spatiotemporal characteristics and influencing factors of ZWD. The Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) are combined in the proposed algorithm to make a novel architecture, namely, the hybrid CNN-LSTM (CL) algorithm, combining CNN for local spatial feature extracting and LSTM for complex sequence dependency training. Data from 46 radiosonde sites in South America spanning from 2015 to 2021 are used to develop models of ZWD under three strategies, i.e., model CL-A without surface parameters, model CL-B with surface temperature, and model CL-C introducing surface temperature and water vapor pressure. The modeling accuracy of the proposed models is validated using the data from 46 radiosonde sites in 2022. The results indicate that CL-A demonstrates slightly better accuracy compared to the Global Pressure and Temperature 3 (GPT3) model; CL-B shows a precision increase of 14% compared to the Saastamoinen model, and CL-C exhibits accuracy improvements of 30% and 12% compared to the Saastamoinen and Askne and Nordius (AN) model, respectively. Evaluating the models’ generalization capabilities at non-modeled sites in South America, data from six sites in 2022 were used. CL-A shows overall better performance compared to the GPT3 model; CL-B’s accuracy is 19% better than the Saastamoinen model, and CL-C’s accuracy is enhanced by 33% and 10% compared to the Saastamoinen and AN model, respectively. Additionally, the proposed hybrid algorithm demonstrates a certain degree of improvement in both modeling accuracy and generalization accuracy for the South American region compared to individual CNN and LSTM algorithm.

Abstract Sialic acid immunoglobulin-like lectin E (Siglec-E) is a subtype of pattern recognition receptors found on the surface of myeloid cells and functions as a key immunosuppressive checkpoint molecule. The engagement between Siglec-E and the ligand α2,8-linked disialyl glycans activates the immunoreceptor tyrosine-based inhibitory motif (ITIM) in its intracellular domain, mitigating the potential risk of autoimmunity amid innate immune attacks on parasites, bacteria, and carcinoma. Recent studies suggest that Siglec-E is also expressed in the CNS, particularly microglia, the brain-resident immune cells. However, the functions of Siglec-E in brain inflammation and injuries under many neurological conditions largely remain elusive. In this study, we first revealed an anti-inflammatory role for Siglec-E in lipopolysaccharide (LPS)-triggered microglial activation. We then found that Siglec-E was induced within the brain by systemic treatment with LPS in mice in a dose-dependent manner, while its ablation exacerbated hippocampal reactive microgliosis in LPS-treated animals. The genetic deficiency of Siglec-E also aggravated oxygen–glucose deprivation (OGD)-induced neuronal death in mouse primary cortical cultures containing both neurons and glial cells. Moreover, Siglec-E expression in ipsilateral brain tissues was substantially induced following middle cerebral artery occlusion (MCAO). Lastly, the neurological deficits and brain infarcts were augmented in Siglec-E knockout mice after moderate MCAO when compared to wild-type animals. Collectively, our findings suggest that the endogenous inducible Siglec-E plays crucial anti-inflammatory and neuroprotective roles following ischemic stroke, and thus might underlie an intrinsic mechanism of resolution of inflammation and self-repair in the brain.

Abstract Women and gender-diverse individuals have faced disproportionate socioeconomic burden during COVID-19. There have been reports of greater negative mental health changes compared to men based on cross-sectional research that has not accounted for pre-COVID-19 differences. We compared mental health changes from pre-COVID-19 to during COVID-19 by sex or gender. MEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator) were searched to August 30, 2021. Eligible studies included mental health symptom change data by sex or gender. 12 studies (10 unique cohorts) were included, all of which reported dichotomized sex or gender data. 9 cohorts reported results from March to June 2020, and 2 of these also reported on September or November to December 2020. One cohort included data pre-November 2020 data but did not provide dates. Continuous symptom change differences were not statistically significant for depression (standardized mean difference [SMD] = 0.12, 95% CI -0.09–0.33; 4 studies, 4,475 participants; I2 = 69.0%) and stress (SMD = − 0.10, 95% CI -0.21–0.01; 4 studies, 1,533 participants; I2 = 0.0%), but anxiety (SMD = 0.15, 95% CI 0.07–0.22; 4 studies, 4,344 participants; I2 = 3.0%) and general mental health (SMD = 0.15, 95% CI 0.12–0.18; 3 studies, 15,692 participants; I2 = 0.0%) worsened more among females/women than males/men. There were no significant differences in changes in proportions above cut-offs: anxiety (difference = − 0.05, 95% CI − 0.20–0.11; 1 study, 217 participants), depression (difference = 0.12, 95% CI -0.03–0.28; 1 study, 217 participants), general mental health (difference = − 0.03, 95% CI − 0.09–0.04; 3 studies, 18,985 participants; I2 = 94.0%), stress (difference = 0.04, 95% CI − 0.10–0.17; 1 study, 217 participants). Mental health outcomes did not differ or were worse by small amounts among women than men during early COVID-19.

The trafficking and sorting of proteins through the secretory-endolysosomal system is critical for the proper functioning of neurons. Defects in steps of these pathways are associated with neuronal toxicity in various neurodegenerative disorders. The prion protein (PrP) is a glycosylphosphatidylinositol (GPI)-anchored protein that follows the secretory pathway before reaching the cell surface. Following endocytosis from the cell surface, PrP sorts into endosomes and lysosomes for further recycling and degradation, respectively. A few detailed protocols using drug treatments and fluorescent dyes have previously allowed the tracking of PrP trafficking routes in real time in non-neuronal cells. Here, we present a protocol optimized for primary neurons that aims to monitor and/or manipulate the trafficking and sorting of PrP particles at several steps during their secretory-endolysosomal itineraries, including (a) ER export, (b) endocytosis, (c) lysosomal degradation, and (d) accumulation in axonal endolysosomes. These primary neuron live assays allow for the robust quantitation of accumulation and/or degradation of PrP or of other membrane-associated proteins that transition from the ER to the Golgi via the cell surface.Graphical abstract

Maintenance treatment is a pivotal part in the whole process management of multiple myeloma (MM), which further deepens response and improves survival. However, evidence of maintenance in non-transplant MM patients is inadequate in real-world practice. Here, we retrospectively analyzed the efficacy and survival of 375 non-transplant MM patients from 11 centers between 2010 and 2021 in north China. After a median of seven cycles of front-line regimens, there were 141, 79, and 155 patients receiving lenalidomide maintenance (L-MT), bortezomib maintenance (B-MT), or thalidomide maintenance (T-MT), respectively. Patients on L-MT and B-MT had significantly greater proportions of high-risk cytogenetic abnormalities (HRCAs) detected by fluorescence in situ hybridization (FISH), which was defined as 1q21 gain, 17p deletion, adverse immunoglobulin heavy chain (IgH) translocations. Although the progression-free survival (PFS) and overall survival (OS) were comparable among the three groups, L-MT and B-MT remedied the negative impact of HRCAs on survival (PFS of patients with HRCAs vs. patients without HRCAs: L-MT, 26.9 vs. 39.2 months, p=0.19; B-MT, 20.0 vs. 29.7 months, p=0.36; OS not reached in all groups). Patients with HRCAs in the T-MT group presented inferior clinical outcomes compared to standard-risk patients (PFS, 12.1 vs. 22.8 months, p=0.02, HR=1.8, 95% CI 1.0–3.4; OS, 54.9 months vs. NR, p

Objective: To conduct a systematic review to determine if there are exercise mobile applications (apps) that can produce evidence-based, individualized exercise plans. Materials and Methods: We searched the Apple Store and Google Play for exercise apps with terms related to exercise and health. Exercise apps were eligible if they: (1) had a ≥4 out of 5 overall rating with ≥1000 reviews; (2) were free to download; and (3) were not gender specific. Exercise apps were evaluated via the evidence-based exercise prescription (ExRx) standards of the American College of Sports Medicine (ACSM) and American Heart Association. For the exercise app evaluation criteria, an app was included if it (1) was evidence-based; (2) contained a preparticipation health screening protocol; (3) built a cardiovascular disease (CVD) risk factor profile; (4) prioritized one chronic disease or health condition to focus on; (5) framed the exercise plan by the frequency, intensity, time, and type principle (FITT) of ExRx; and (6) specified special considerations. Results: Of the 531 potentially qualifying apps, 219 qualified. The qualifying apps were rarely evidenced-based (0.5%) or had a preparticipation screening protocol (3.7%). Only 27.7% built CVD risk factor profiles. Most apps (64.8%) focused on body image and/or athletic performance. Only 4.3% focused on chronic diseases or health conditions, while the remainder (34.5%) did not disclose a focus. No app framed the exercise plans by the FITT of ExRx. Only 1.4% of the apps specified special considerations. Conclusion: There are no commercially available exercise apps that generate an evidence-based, individualized exercise plan for adults with CVD risk factors.

Applications of haloalkane dehalogenase DhaA in biocatalysis are limited by its unfavorable performance in organic solvents. Our previous work proved that mutations of surface positive-charged residues enhanced the organic solvent resistance of DhaA, which inspired us to explore the effect of cationic polymers on DhaA in organic solvents. Remarkably boosted performance was achieved in different organic solvent solutions by introducing cationic polymers, for example, there was a 6.1-fold activity increase with poly(allylamine hydrochloride) and a 5.5-fold activity increase with poly(ethylene imine) in 40 vol.% dimethylsulfoxide. The presence of cationic polymers protected DhaA from damage by organic solvents and increased the substrate concentration around the enzyme-polymer complex. Fluorescence spectroscopy and molecular dynamics simulations revealed that the binding of cationic polymers onto DhaA weakened the interactions between organic solvents and DhaA, decreased the organic solvent solvation level around DhaA, and enhanced the structural stability of DhaA in organic solvents. This comprehensive understanding of the effect of cationic polymers on DhaA can help to broaden the applications of DhaA in organic solvent-involved biocatalysis.

AIM:To evaluate the effect of Yangxue Runmu formula combined with sodium hyaluronate on dry eye after cataract surgery by ocular surface analyzer.METHODS: Totally 80 patients with dry eye after cataract surgery in our hospital from June 2019 to December 2020 were selected and divided into control group and observation group by random number table method, 40 cases in each group. The control group was treated with sodium hyaluronate eye drops, and the observation group was treated with Yangxue Runmu formula combined with sodium hyaluronate eye drops. The index levels of ocular surface analyzer and fluorescein staining(FL)score were compared between the two groups.RESULTS: After treatment, the wet length of tear film, first non-invasive tear break-up time(NIBUTf), average non-invasive tear break-up time(NIBUTav)and tear meniscus height(LTMH)in the two groups were markedly higher than those before treatment(all P

ObjectivesTo evaluate COVID-19 vaccines in primary prevention against infections and lessen the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai.Data sourcesData from 153,544 COVID-19 patients admitted to the Shanghai “Four-Leaf Clover” Fangcang makeshift shelter hospital were collected using a structured electronic questionnaire, which was then merged with electronic medical records of the hospital. For healthy controls, data on vaccination status and other information were obtained from 228 community-based residents, using the same structured electronic questionnaire.MethodsTo investigate whether inactivated vaccines were effective in protecting against SARS-CoV-2 virus, we estimated the odds ratio (OR) of the vaccination by comparing cases and matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied multivariate stepwise logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in the COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors.ResultsOf the 153,544 COVID-19 patients included in the analysis, the mean age was 41.59 years and 90,830 were males (59.2%). Of the study cohort, 118,124 patients had been vaccinated (76.9%) and 143,225 were asymptomatic patients (93.3%). Of the 10,319 symptomatic patients, 10,031 (97.2%), 281 (2.7%), and 7 (0.1%) experienced mild, moderate, and severe infections, respectively. Hypertension (8.7%) and diabetes (3.0%) accounted for the majority of comorbidities. There is no evidence that the vaccination helped protect from infections (OR = 0.82, p = 0.613). Vaccination, however, offered a small but significant protection against symptomatic infections (RR = 0.92, p

Summary: There are currently no effective therapies for COVID-19 or antivirals against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and vaccines appear less effective against new SARS-CoV-2 variants; thus, there is an urgent need to understand better the virulence mechanisms of SARS-CoV-2 and the host response to develop therapeutic agents. Herein, we show that host Neu1 regulates coronavirus replication by controlling sialylation on coronavirus nucleocapsid protein. Coronavirus nucleocapsid proteins in COVID-19 patients and in coronavirus HCoV-OC43-infected cells were heavily sialylated; this sialylation controlled the RNA-binding activity and replication of coronavirus. Neu1 overexpression increased HCoV-OC43 replication, whereas Neu1 knockdown reduced HCoV-OC43 replication. Moreover, a newly developed Neu1 inhibitor, Neu5Ac2en-OAcOMe, selectively targeted intracellular sialidase, which dramatically reduced HCoV-OC43 and SARS-CoV-2 replication in vitro and rescued mice from HCoV-OC43 infection-induced death. Our findings suggest Neu1 inhibitors could be used to limit SARS-CoV-2 replication in patients with COVID-19, making Neu1 a potential therapeutic target for COVID-19 and future coronavirus pandemics.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies to date. The impressively developed stroma that surrounds and modulates the behavior of cancer cells is one of the main factors regulating the PDAC growth, metastasis and therapy resistance. Here, we postulate that stromal and cancer cell compartments differentiate in protein/lipid glycosylation patterns and analyze differences in glycan fragments in those compartments with clinicopathologic correlates. Results We analyzed native glycan fragments in 109 human FFPE PDAC samples using high mass resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometric imaging (MALDI-FT-ICR-MSI). Our method allows detection of native glycan fragments without previous digestion with PNGase or any other biochemical reaction. With this method, 8 and 18 native glycans were identified as uniquely expressed in only stromal or only cancer cell compartment, respectively. Kaplan–Meier survival model identified glycan fragments that are expressed in cancer cell or stromal compartment and significantly associated with patient outcome. Among cancer cell region-specific glycans, 10 predicted better and 6 worse patient survival. In the stroma, 1 glycan predicted good and 4 poor patient survival. Using factor analysis as a dimension reduction method, we were able to group the identified glycans in 2 factors. Multivariate analysis revealed that these factors can be used as independent survival prognostic elements with regard to the established Union for International Cancer Control (UICC) classification both in tumor and stroma regions. Conclusion Our method allows in situ detection of naturally occurring glycans in FFPE samples of human PDAC tissue and highlights the differences among glycans found in stromal and cancer cell compartment offering a basis for further exploration on the role of specific glycans in cancer–stroma communication.

Current treatment of glioma is hampered due to the physical blood-brain barrier (BBB) and the resistance to traditional chemotherapeutic agents. Herein, we proposed a combined treatment strategy based on Cyclo (Arg-Gly-Asp-d-Phe-Lys) (cRGDfk) peptides-modified nanoparticle named cRGD-P in a self-assembly method for the co-delivery of doxorubicin (DOX) and BRD4 PROTAC degrader ARV-825 (ARV). Molecular dynamics simulations showed that cRGD-P could change its conformation to provide interaction sites for perfectly co-loading DOX and ARV. The cRGD-P/ARV-DOX exhibited an average size of 39.95 ​nm and a zeta potential of −0.25 ​mV. Increased expression of BRD4 in glioma cells was observed after being stimulated by cRGD-P/DOX, confirming one of the possible mechanisms of DOX resistance and the synergistic tumor inhibition effect of BRD4 degrading ARV combined with DOX. In the study, the combination of DOX and ARV in the cRGD-P nanoparticle system exhibited synergistic suppression of tumor growth in glioma cells on account of cell cycle arrest in the G2/M phase and the activation of tumor cells apoptosis-related pathways including triggering caspase cascade and downregulating Bcl-2 as well as upregulating Bax. The cRGD-P/ARV-DOX system could effectively suppress the heterotopic and orthotopic growth of glioma by increasing tumor apoptosis, inhibiting tumor proliferation, and decreasing tumor angiogenesis in vivo. Therefore, the cRGD-modified nanoparticle to co-deliver DOX and ARV provides a potential platform for exploiting a more effective and safer combination therapy for glioma.

The immunosuppressive tumor microenvironment (TME) of cancer strongly hinders the anti-tumor immune responses, thereby resulting in disappointing responses to immunotherapy. Chemoattractive and promotive traits of chemokines exerted on leukocytes have garnered interest in improving the efficiency of immunotherapy by increasing the infiltration of immune cells in the TME. In this study, a folic acid (FA) -modified gene delivery system based on the self-assembly of DOTAP, MPEG-PCL-MPEG, and FA-PEG-PCL-PEG-FA, namely F-PPPD, was developed to deliver plasmids encoding the immunostimulating chemokine CKb11. The delivery of plasmid CKb11 (pCKb11) by F-PPPD nanoparticles resulted in the high secretion of CKb11 from tumor cells, which successfully activated T cells, suppressed the M2 polarization of macrophages, promoted the maturation of dendritic cells (DCs), facilitated the infiltration of natural killer (NK) cells and inhibited the infiltration of immunosuppressive cells in tumor tissues. Administration of F-PPPD/pCKb11 also significantly suppressed the cancer progression. Our study demonstrated a nanotechnology-enabled delivery of pCKb11, that remodeled the immunosuppressive TME, for cancer treatment.

The rise of Internet of Things (IoT) technology has moved the digital world in a new direction and is considered the third wave of the information industry. To meet the current growing demand for food, the agricultural industry should adopt updated technologies and smart agriculture based on the IoT which will strongly enable farmers to reduce waste and increase productivity. This research presents a novel system for the application of IoT technology in agricultural soil measurements, which consists of multiple sensors (temperature and moisture), a micro-processor, a microcomputer, a cloud platform, and a mobile phone application. The wireless sensors can collect and transmit soil information in real time with a high speed, while the mobile phone app uses the cloud platform as a monitoring center. A low power consumption is specified in the hardware and software, and a modular power supply and time-saving algorithm are adopted to improve the energy effectiveness of the nodes. Meanwhile, a novel soil information prediction strategy was explored based on the deep Q network (DQN) reinforcement learning algorithm. Following the weighted combination of a bidirectional long short-term memory, online sequential extreme learning machine, and parallel extreme machine learning, the DQN Bi-OS-P prediction model was obtained. The proposed data acquisition system achieved a long-term stable and reliable collection of time-series soil data with equal intervals and provided an accurate dataset for the precise diagnosis of soil information. The RMSE, MAE, and MAPE of the DQN Bi-OS-P were all reduced, and the R2 was improved by 0.1% when compared to other methods. This research successfully implemented the smart soil system and experimentally showed that the time error between the value displayed on the mobile phone app and its exact acquisition moment was no more than 3 s, proving that mobile applications can be effectively used for the real-time monitoring of soil quality and conditions in wireless multi-sensing based on the Internet of Things.

Water plays an important role in various physiological activities of living trees. Measuring trunk moisture content (MC) in real-time without damage has important guiding significance for transpiration research in forest ecosystems. However, existing standing tree MC detection methods are either too cumbersome to install or cause different degrees of damage. Here, we propose a novel Internet of Things (IoT) monitoring system that includes wireless acoustic emission sensor nodes (WASNs) and underground soil MC sensor nodes to efficiently detect and diagnose the MC level of living tree trunks. After the characteristic parameters were collected by the two sensors, a feature selection and multi-sensory global fusion method for MC diagnosis was designed and developed and several statistical parameters were selected as the input variables to predict the heartwood MC level with a support vector machine (SVM) model. Moreover, to achieve the highest prediction accuracy, an improved sparrow search algorithm (ISSA) is applied to ensure the most suitable parameter combinations in a two-objective optimization model. Extensive experiments result in a fusion of the environment, and AE signals show that the proposed mechanism has better diagnostic performance than state-of-the-art methods and is more adaptable to the fluctuation of working conditions.

Objective Patients with Parkinson’s disease (PD) have an obvious motor inhibition disorder, which is closely related to their motor symptoms. Although previous studies have shown that exercise can improve their inhibition deficits, the effect of exercise on different types of inhibition (proactive and reactive inhibition) has not been addressed. Methods We used a behavioral paradigm combined with a series of questionnaires to explore the effect of long-term exercise on different types of motor inhibition in 59 patients with PD aged 55–75 years. According to the intensity and frequency of exercise, the participants were divided into regular-exercise and no-exercise groups. To obtain the average reference value for inhibition ability at the same age, we also recruited 30 healthy elderly people as controls. Results The main defect in the motor inhibition of PD is reactive inhibition, while proactive inhibition has no obvious differences compared with healthy controls. Additionally, compared with the non-exercise group, PD in the exercise group showed significantly better reaction speeds and reactive control ability, fewer motor symptoms and negative emotions. Conclusions Taken together, the motor inhibition defects of patients with PD affect only reactive inhibition. In addition, PD with exercise reported fewer negative emotions than that of the non-exercise group, indicating that exercise can relieve negative emotions and improve behavioral symptoms and quality of life in PD to a certain extent. We demonstrate for the first time that exercise has and can improve reactive inhibition in PD patients and has no effect on proactive inhibition.