Browse Articles

Cooper-pair density modulation state in an iron-based superconductor

Global engineering effects of soil invertebrates on ecosystem functions

Microsatellite-based real-time quantum key distribution

A systems-level, semi-quantitative landscape of metabolic flux in C. elegans

Systems-level design principles of metabolic rewiring in an animal

Time-restricted feeding reduced blood pressure and improved cardiac structure and function by regulating both circulating and local renin-angiotensin systems in spontaneously hypertensive rat model

Objective To investigate whether time-restricted feeding (TRF) can reduce blood pressure (BP) and improve cardiac structure and function in spontaneously hypertensive rats (SHRs) by regulating the renin-angiotensin system (RAS). Methods Wistar Kyoto rats and SHR underwent 16 weeks of TRF intervention, with daily feeding restricted to 9 am–5 pm. The effects of TRF on systolic BP, diastolic BP, mean BP, body weight (BW), heart weight (HW), HW/BW ratio, cardiac structure and function, and RAS activity in the circulating and left ventricular (LV) tissues were investigated. Results TRF effectively reduced systolic BP, mean BP, diastolic BP, and BW; improved hypertension-induced cardiac structural and functional damage; and inhibited the ACE-Ang-II-AT1 axis in circulating and LV tissues. Conclusion TRF effectively inhibits RAS activity in both circulating and LV tissues, thereby lowering BP and mitigating structural and functional cardiac damage associated with hypertension.

Characteristics of Dutch ED patients and their journey through the acute care chain: A province-wide flash-mob study

Background Insight in characteristics and journey of patients in the Acute Care Chain (ACC) who visit the Emergency Department (ED) is lacking. Existing studies focus on prespecified (time-sensitive) complex conditions like major trauma and stroke, and on the hospital phase. This study provides a representative overview of adult ED patients and their journey through the ACC with focus on differences between those with and without prespecified complex conditions. Methods A prospective 72-hour flash-mob study was conducted in 2022 across all six EDs in the province of Limburg, the Netherlands, encompassing unselected adult patients. Baseline characteristics, journey, and time within ACC were collected. Patients with a prespecified complex condition (stroke, myocardial infarction, aortic syndrome and major trauma) were compared to those without. Results Out of 794 adult ED patients, 585 (73.7%) were included. Patients reported symptoms for a median of 1 day (IQR 0-4) before their ED visit; 56.3% encountered ≥ 1 healthcare provider. General practitioners referred 56.1% of patients, and emergency medical services transported 32.9%. The median time in ACC was 5.0 hours (IQR 3.5-6.9), with 3.0 hours (IQR 2.0-4.2) spent in the ED. The three most prevalent presenting complaints were minor trauma (28.5%), abdominal pain (14.6%) and dyspnoea (12.5%), while 9.3% presented with prespecified complex conditions. Patients with a prespecified complex condition were more often triaged highly urgent (53.6% vs 13.9%, p < 0.001) and received a complex work-up (79.6% vs 41.2%, p < 0.001). Conclusion In our province-wide study, ED patients had symptoms for 1 day and over half of them already contacted a healthcare provider. Time in ACC was 5 hours, with a substantial proportion of time spent prehospitally. Prespecified complex conditions accounted for less than 1 in 10 ED patients. These findings highlight that, to optimise care and care policy, it is essential to examine the entire ACC for unselected patients. Trial registration ClinicalTrials.gov NCT06079099

Effect of opioid-free anesthesia combined with pectoral nerve block on the quality of recovery in patients after mastectomy: A randomized, controlled trial

Objective To evaluate the impact of opioid-free anesthesia (OFA) combined with regional blocks on the quality of recovery (QoR) in patients who underwent mastectomy. Methods This randomized controlled trial involved 132 mastectomy patients who were randomized to receive either OFA combined with PECS block or opioid-based anesthesia (OBA) combined with PECS block. The QoR was assessed using the QoR-15 global score at 24 h post-surgery. Secondary outcomes included postoperative sufentanil consumption, incidence of postoperative nausea and vomiting (PONV), Numerical Rating Scale (NRS) scores at 1, 4, and 24 h, incidence of postoperative adverse events, extubation, incidence of severe bradycardia and intraoperative mean artrial pressure (MAP) and heart rate (HR) at after entering the operating room (T0, baseline value), after intubation (T1), after skin incision (T2), and after extubation (T3). Results The QoR-15 global score at 24 h was not significantly different between groups (MD = -0.4, 95% CI [-3.8 to 4.7], P = 0.67). Postoperative sufentanil consumptions (P = 0.075), the incidence of PONV (P = 0.12), NRS scores at 1 h (P = 0.36), 4 h (P = 0.53), and 24 h (P = 0.02) were not significantly different. Incidence of adverse events (OR = 0, 95% CI [0 to 0.44], P = 0.0063) were lower in Group OFA than that in Group OBA. Extubation time was significantly longer in Group OFA than in Group OBA (MD = 15, 95%CI [10–18], P <  0.001). MAPs at T1 and T2 were significantly higher in Group OFA than in Group OBA (P <  0.0125), while MAP and HR at T3 were significantly lower in Group OFA than in Group OBA(P <  0.0125). Incidence of severe bradycardia were not significantly different (P = 0.67). Conclusion In conclusion, while OFA contributes to a reduction in adverse events, its integration with PECS blocks does not improve QoR or postoperative analgesia at 24 h post-mastectomy. Moreover, OFA was associated with a prolonged extubation time. Trial registration chictr.org; registration number: ChiCTR2100043575.

RETRACTED: Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model

Enterprise risk management is a key element to ensure the sustainable and steady development of enterprises. However, traditional risk management methods have certain limitations when facing complex market environments and diverse risk events. This study introduces a deep learning-based risk management model utilizing the XGBoost-CNN-BiLSTM framework to enhance the prediction and detection of risk events. This model combines the structured data processing capabilities of XGBoost, the feature extraction capabilities of CNN, and the time series processing capabilities of BiLSTM to more comprehensively capture the key characteristics of risk events. Through experimental verification on multiple data sets, our model has achieved significant advantages in key indicators such as accuracy, recall, F1 score, and AUC. For example, on the S&P 500 historical data set, our model achieved a precision rate of 93.84% and a recall rate of 95.75%, further verifying its effectiveness in predicting risk events. These experimental results fully demonstrate the robustness and superiority of our model. Our research is of great significance, not only providing a more reliable risk management method for enterprises, but also providing useful inspiration for the application of deep learning in the field of risk management.

Passive compliance or active innovation: The diffusion of public sport policies in China

As an important tool for governing, regulating, and safeguarding national sports, sports policy not only centralizes and expresses the state’s vision for sports but also advances the development of the sports economy, and distributes the benefits of social sports. Accordingly, we collect policy samples from 31 provinces of China. Adopting the central–local relationship perspective, we use the grey correlation analysis method to explore the intrinsic relationship between the factors influencing the diffusion of public sports policies and the degree of policy text reproduction by provincial governments. We aim to encourage provincial governments to innovate policy texts based on local development needs, geographic position, and resource capabilities, This will enhance the diffusion of public sports policies and contribute to national and global sports governance. The diffusion of China’s public sports policies is influenced by six secondary indicators: economic level, population size, sports organizations, public sports demand, central government policy pressure, and learning effect. The policy environment, shaped primarily by central government policy pressure and the learning effect, has the greatest influence on the reproduction of provincial public sports policy texts.

Correction: CDC2 Mediates Progestin Initiated Endometrial Stromal Cell Proliferation: A PR Signaling to Gene Expression Independently of Its Binding to Chromatin

Cognitive cerebellum dominates motor cerebellum in functional decline of older adults with mild cognitive impairment

Objectives The present study aims to investigate the role that cognitive cerebellar lobules, compared to the motor ones, could have on performance abilities control in older individuals with Mild Cognitive Impairment (MCI). Methods Thirty-six participants with MCI were retrospectively recruited from the outpatient clinic for Cognitive Decline and Dementia at Geriatric Clinic and Regional Center for Brain Aging. Cognition was assessed through a reaction time (RT) task in which a mere cognitive (COG) component (RT/S1 COG, RT/S3 COG) has been isolated from a motor (MOT) component (RT/S1 MOT, RT/S3 MOT). Performance abilities were evaluated using Short Physical Performance Battery (SPPB), Tinetti Scale, and Activities of Daily Living (ADL). Finally, structural neuroimaging was conducted using magnetic resonance imaging at 3T. Results Left_Crus_I showed a correlation with SPPB, ADL%, and RT/S3 COG. Vermis_VI and Right_VI were correlated to ADL%, and RT/S3 COG with the entire lobule VI. ADL% showed negative correlations with RT/S1 COG, RT/S3 COG, and RT/S3 MOT. In the regression analysis, the strongest associations were found between RT/S3 COG and SPPB gait speed (R2 = 0.44, p = 0.03), Tinetti gait speed (R2 = 0.62, p < 0.001), and ADL% (R2 = 0.78, p < 0.001). Regarding cerebellar volumes, Right_Crus_I was associated with all SPPB tests, while Left_VI was associated with functional autonomy (ADL%: R2 = 0.78, p = 0.04). No associations were found between performance variables and total intracranial volume. Conclusions This study highlights that the cognitive cerebellar component dominates over the motor one even in the control of physical and functional capabilities of older adults with MCI.

Author Correction: Endocytosis in the axon initial segment maintains neuronal polarity

Integrating bulk and single-cell RNA sequencing reveals SH3D21 promotes hepatocellular carcinoma progression by activating the PI3K/AKT/mTOR pathway

As a novel genetic biomarker, the potential role of SH3D21 in hepatocellular carcinoma remains unclear. Here, we decipher the expression and function of SH3D21 in human hepatocellular carcinoma. The expression level and clinical significance of SH3D21 in hepatocellular carcinoma patients, the relationship between SH3D21 and the features of tumor microenvironment (TME) and role of SH3D21 in promoting hepatocellular carcinoma progression were analyzed based on the bulk samples obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Single-cell sequencing samples from Gene Expression Omnibus (GEO) database were employed to verify the prediction mechanism. Additionally, different biological effects of SH3D21 on hepatocellular carcinoma cells were investigated by qRT-PCR, CCK-8 assay, colony forming assay and Western blot analysis. Bioinformatics analysis and in vitro experiments revealed that the expression level of SH3D21 was up-regulated in hepatocellular carcinoma and correlated with the poor prognosis in hepatocellular carcinoma patients. SH3D21 effectively promoted the proliferation, invasion, and migration as well as the formation of immunosuppressive microenvironment of hepatocellular carcinoma. In addition, SH3D21 can activate the PI3K/AKT/mTOR signaling pathway. SH3D21 stimulates the progression of hepatocellular carcinoma by activating the PI3K/AKT/mTOR signaling pathway, and SH3D21 can serve as a prognostic biomarker and therapeutic target for hepatocellular carcinoma.

Identification of the co-regulatory siRNAs of “miRNA→target” in Oryza sativa

The current “small interfering RNA(siRNA)→Target” mining tools can only search for targets of known siRNAs, and cannot discover co-regulatory siRNAs of unknown sequences that may exist, which means that the “microRNA(miRNA)→Target” database obtained by these mining tools is incomplete. Using the previously developed sRNATargetDigger, we re-mined the rice “miRNA→Target” database supported by the degradome and found 86.2% of the target genes were co-regulated by one or more miRNAs\siRNAs. Besides the known miRNAs, 30 miRNA isoforms (isomiRs) and 12 siRNAs were identified to be involved in co-regulation, which play important roles in rice response to external auxin regulation, rice blast resistance, adventitious root formation, cold resistance, and tillering etc. Some isomiRs even have higher expression levels than miRNAs. In addition, we also found that the regulatory relationship between 51 miRNAs and 48 target genes in the original database could not be verified due to the low expression levels of miRNA, poor complementarity between miRNA and target, or no specific cleavage signal detected by degradome in the middle of the miRNA binding site in the targets. Four miRNAs (osa-miR530-5p,osa-miR319b,osa-miR172c and osa-miR395a) only found isomiRs involved in regulation. In addition, we also found a number of miRNA→target regulatory relationships missed in the database. This study improved the rice “miRNA→target” database which will contribute to the research of rice miRNA and molecular breeding.

A compendium of human gene functions derived from evolutionary modelling

Abstract A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms1,2. Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

Prevalence of detectable viral load and its associated factors among adult patients receiving ART in Choma District, Zambia

Background Africa accounts for two-thirds of the global HIV infection and a disproportionate burden is in sub-Saharan Africa. In 2017, the Zambian government launched the U = U campaign which has proven to be key in the prevention of HIV. However, there is a paucity of empirical evidence on the magnitude of detectable viral load in Choma district. This study aimed to estimate the proportion of detectable viral load and identify the associated factors among adults living with HIV receiving antiretroviral therapy (ART) in Choma District, Zambia. Methods This was a cross-sectional study among adults aged 15 years and older on ART ≥ 12 months. Sociodemographic, clinical and laboratory data were collected through a structured questionnaire and data collection form for secondary data from medical records. Detectable Viral load (primary outcome) and Virological failure (secondary outcome) were defined as viral load (VL) > 200cp/ml and VL > 1000cp/ml respectively. The data collected was then analysed using STATA version XII. Descriptive statistics, chi-square test, Wilcoxon rank sum test, and logistic regression were the statistical methods used. Results There was a total of 448 participants. The median (interquartile range (IQR)) age was 41 years (32, 49) of whom 284 (63.2%) were females. The prevalence of detectable and virological failure were 10.3% (n = 46; 95% confidence interval (CI) 7.6, 13.5) and 5.4% (n = 24; 95%CI 3.5, 7.9) respectively. In multivariable analysis, detectable VL was significantly associated with young age (16 – 24 years) (odds ratio (OR) 3.38; 95%CI 1.04, 10.94; p = 0.042), no formal education (OR 3.32; 95%CI 1.06, 10.40; p = 0.040), missing medication (OR 3.99; 95%CI 1.83, 8.73; p = 0.001) and problem taking medication (OR 2.74; 95%CI 1.10; 6.84; p < 0.030); while factors associated with virological failure were being in age group 16 – 24 years (OR 7.28; 95%CI 1.62, 32.68, p = 0.009), male gender (OR 3.12; 95%CI 1.25, 7.76; p = 0.014), Missing taking medication (OR 8.28; 95%CI 2.59, 26.40; p < 0.001) and taking dolutegravir-based regimen with zidovudine/lamivudine backbone (OR 17.80 95% CI 2.29 - 132.31; p = 0.005). Conclusion Detectable VL and virological failure were prevalent among adults receiving ART for ≥ 12 months and were significantly associated with sociodemographic and clinical factors. There is a need for targeted interventions, especially among young people and males to accelerate the attaining of the last 95 of the UNAIDS target; which is imperative in the prevention of HIV transmission. Qualitative research which aims to get an in-depth understanding of why men and young people do not attain optimal viral suppression is encouraged.

Prognostic implications of MUC1 and XBP1 concordant expression in multiple myeloma: A retrospective study

Multiple myeloma (MM) is a disease of malignant plasma cells (PC) with poor survival. Disease progression and treatment relapse are attributed to MM cancer stem cells (CSCs) and signaling molecules such as MUC1 and XBP1. The study aimed to determine the prognostic value of expression of CSC-associated biomarkers, MUC1 and XBP1 in MM, which has not been explored previously. In this study, we determined the immunohistochemical expression of CSC markers (ALDH1, CD117, and CD34), MUC1, and XBP1 in 128 MM formalin-fixed paraffin-embedded bone marrow archival blocks. The expression of biomarkers was assessed for association with clinicopathological variables and patient survival. Descriptive analysis, survival plots and crude association between outcome and independent variables were assessed using Kaplan Meier and Log rank test. Univariate and multivariable analyses were performed using simple and multiple Cox regression models. The results are reported as crude and adjusted hazard ratios with 95% confidence intervals. Expression of ALDH1 and CD117 was found in 51% and 48% of the tumors, respectively. ALDH1 expression was associated with 1.83 years of reduced survival for patients with CD56-negative tumors. MUC1 expression was observed in 62%, whereas XBP1 was expressed in 48% of tumors. Combinatorial group analysis of XBP1 and MUC1 stratified patients into two prognostic groups. Cases with tumors negative for expression of MUC1 and XBP1 (XBP1-/ MUC1-) were categorized as a good prognostic group with increased survival of 3.42 years compared to cases with tumors expressing both (Worst prognosis, XBP1 + /MUC1+). Concordant expression of MUC1 and XBP1 in MM defines a subset of patients with adverse outcomes. The adjusted hazard ratio showed a four-fold increased risk of mortality associated with the concordant expression of MUC1 and XBP1 in patients > 65 years of age.

The look of a leader

Women and minorities are underrepresented in top leadership roles. Besides “supply-side” explanations that focus on the applicant pool, we offer a novel “demand-side” explanation through perceptual imprinting. Using the reverse correlation method, we found that people’s visual templates of leaders are perceptually imprinted by White male leaders. Across 15 studies (N = 3929), we examine what people expect leaders to look like. As demonstrated by the reverse correlation method, compared to followers, people expected leaders to look more White and male. Across all social categories, people also expected leaders to look more dominant, competent, and powerful. But to look like a leader, Black and female leaders also needed to look likable. Additional differences were observed by participant gender. Thus, in addition to having biased perceptual representations of leaders, people also have different perceptual standards for different social groups, as expressed by different expectations for how leaders of different races and genders should look. (151 words).

Using deep learning artificial intelligence for sex identification and taxonomy of sand fly species

Sandflies are vectors for several tropical diseases such as leishmaniasis, bartonellosis, and sandfly fever. Moreover, sandflies exhibit species-specificity in transmitting particular pathogen species, with females being responsible for disease transmission. Thus, effective classification of sandfly species and the corresponding sex identification are important for disease surveillance and control, managing breeding/populations, research and development, and conducting epidemiological studies. This is typically performed manually by observing internal morphological features, which maybe an error-prone tedious process. In this work, we developed a deep learning artificial intelligence system to determine the gender and to differentiate between three species of two sandfly subgenera (i.e., Phlebotomus alexandri, Phlebotomus papatasi, and Phlebotomus sergenti). Using locally field-caught and prepared samples over a period of two years, and based on convolutional neural networks, transfer learning, and early fusion of genital and pharynx images, we achieved exceptional classification accuracy (greater than 95%) across multiple performance metrics and using a wide range of pre-trained convolutional neural network models. This study not only contributes to the field of medical entomology by providing an automated and accurate solution for sandfly gender identification and taxonomy, but also establishes a framework for leveraging deep learning techniques in similar vector-borne disease research and control efforts.