Conectar
by Bing-Nan Zhao, Zi-Yang Xie, Jia-Ning Liu, Xiao-Ran Chen, Xin-Xin Wang, Jia-Yi Li, Rui Zhang, Chao Si
Fermented spent coffee grounds (FSCG) serve as a valuable soil amendment to improve soil structure and fertility, while earthworms play a well-established role in enhancing soil processes and plant growth. However, their combined effects on bioactive compound accumulation in medicinal plants remain unclear. This study investigated the individual and interactive effects of FSCG (0%, 10%, and 20%, v/v) and earthworms (with and without Pheretima guillelmi) on the growth and phytochemical content of Glechoma longituba, a common medicinal herb, under greenhouse conditions. Results showed that 10% FSCG generally promoted plant growth, whereas 20% FSCG generally enhanced the accumulation of total flavonoids, chlorogenic acid, and soluble protein. Earthworms enhanced aboveground biomass and node number but significantly reduced chlorogenic acid content. These findings highlight the potential of FSCG as a sustainable soil amendment in medicinal plant cultivation and underscore the need to consider earthworm activity when optimizing both plant biomass and phytochemical quality.
by Zihang Zhao, Xiang Zhang, Xi Hou, Zihan Liu, Zhiyong Hou, Lianxin Song, Ruipeng Zhang
Percutaneous Bunnell repair and open modified Kessler repair remain debated options for acute Achilles tendon rupture (AATR). We retrospectively compared a minimally invasive percutaneous Bunnell technique (Group A) with an open modified Kessler repair (Group B) within a standardized early functional rehabilitation (EFR) protocol at a single center. Fifty-five adults with closed AATR treated between January 2021 and December 2022 were analyzed (Group A, n = 25; Group B, n = 30). Between-group comparisons used Welch t tests for continuous variables and χ² or Fisher exact tests for categorical variables; American Orthopaedic Foot & Ankle Society (AOFAS) and Achilles Tendon Total Rupture Score (ATRS) were assessed at 12 and 24 weeks, with Holm adjustment applied within each scale. Compared with Group B, Group A had shorter operative time (56.6 ± 15.1 vs 68.2 ± 23.2 minutes; mean difference −11.6; 95% CI −22.05 to −1.15; P = 0.030), less intraoperative blood loss (28.4 ± 8.4 vs 74.7 ± 19.4 mL; −46.3; 95% CI −54.22 to −38.38; P
by Xianxiang Lu, Yangrui Duan
Resilience is a crucial ability of an economy to withstand sudden events and uncertain shocks. Using the entropy method, this study measures the economic resilience of 281 Chinese cities (prefecture-level and above) from 2017 to 2022, and empirically examines the impact of COVID-19 on this resilience, as well as its transmission channels. The results show that COVID-19 adversely affected overall urban economic resilience, with contrasting effects across its sub-dimensions: an insignificant negative impact on shock resistance, a significant negative impact on adaptive recovery, and an insignificant positive impact on innovative transformation. Transmission channels analysis reveals COVID-19 impaired urban economic resilience through the channels of employment structure, consumption, investment, and unrelated diversification, with consumption identified as the predominant one. Heterogeneity analysis reveals that the economic resilience of cities in both the high and low manufacturing specialization groups was more adversely affected by COVID-19 than that of cities in the medium group. Regarding services specialization, the economic resilience of cities with a medium degree of services specialization were more negatively affected by COVID-19 than that of cities with low services specialization. Furthermore, the economic resilience of cities with a higher degree of related diversification was less negatively affected by COVID-19. This study provides a replicable analytical framework and empirical evidence for enhancing urban economic resilience in China and other countries in post-pandemic era.
by Yizhe Yang, Ruifeng Liang, Yan Luo, Doudou Zhu, Yi Liu, Yuyan Guo, Jiafen Zhang, Qiao Niu
ObjectiveInvestigate the Knowledge-Attitude-Practice (KAP) of students from Medical College towards emerging infectious diseases, and assess their impact, can provide a scientific basis and practical guidance for enhancing medico’s prevention and control capabilities.
MethodsA total of 2,395 participants from various grades and majors at Medical University were randomly selected using a stratified cluster sampling method. This cross-sectional study was conducted between April 25 and May 31, 2020, using a self-administered questionnaire developed on the Wenjuanxing platform to assess COVID-19-related knowledge, attitudes, and practices (KAP) among medical students.
ResultsA total of 2,245 participants (aged 16–28 years) were included in the study, coming from five medical disciplines: Clinical Medicine, Preventive Medicine, Nursing, Clinical Pharmacy, Health Inspection and Quarantine. The average scores for the COVID-19 epidemiological knowledge and the control measures for the epidemic were 4.92 ± 1.03 and 4.50 ± 0.78, respectively. Among them, the scores of epidemiological knowledge exhibited significant differences in sex, nation, type of dwelling place, major, grade, annual per capita household income, and age. The scores of preventive knowledge significantly differed by sex, major, grade, physical condition, and age. Further, behavioral data indicated that 96.0% of the students thought the pandemic had severely affected their daily life, while >90% maintained consistent mask usage and >80% insisted on health-protective practices. Practice scores finally varied significantly by sex, family structure, and ethnicity.
ConclusionsAltogether, medical students possess certain basic knowledge in controlling emerging infectious diseases, but some still generally suffer from insufficient cognitive depth and anxiety. Colleges can systematically enhance students’ rational cognitive level which include offering specialized courses as well as promoting cutting-edge research achievements, and through standardized operations stabilize their psychological states.
by Michael C. Reed, Ayako Suzuki, Allison Cruikshank, Mizuki Suzuki, H. Frederik Nijhout
Homocysteine (Hcy), a sulfur-containing amino acid, is produced in prodigious quantities by the methionine cycle in the liver. Hcy is the major biomarker for cardio-vascular disorders and is associated with many other diseases. In previous work, we have explained why menstruating women have lower serum homocysteine than men due to higher concentrations of estradiol. In this study, we first present epidemiological evidence from NHANES data that synthetic estradiol supplementation lowers serum Hcy in post-menopausal women, but raises Hcy in pre-menopausal women. Secondly, we give an explanation of this puzzling phenomenon using previously developed mathematical models of one-carbon and glutathione metabolism. The simulation analysis demonstrated that the non-monotonic response of glutathione to rising estradiol levels may account for the differing Hcy responses to estradiol supplementation in postmenopausal versus premenopausal women, through activation of cystathionine β-synthase, a key enzyme regulating tissue homocysteine levels. Our findings further highlight the importance of considering menopausal status and synthetic hormone use when evaluating the health effects of homocysteine.
by Bing Wu, Pengli Wei, Jiaxiang Deng, Yuanyuan Rui
BackgroundThe atherogenic index of plasma (AIP) is a recognized marker of atherosclerosis and cardiovascular disease (CVD). However, the association between AIP and the risk of acute kidney injury (AKI) in critically ill patients with sepsis has not yet been investigated.
MethodsThe data used in this study were derived from the Medical Information Mart for Intensive Care (MIMIC-IV) database. The clinical outcome was the occurrence of AKI. Logistic regression was used to assess the association between AIP and the risk of AKI in sepsis patients. Restricted cubic spline (RCS) analysis was applied to explore potential non-linear relationships. Threshold analysis confirmed a turning point at this value. Subgroup analyses evaluated the consistency of the association across different strata. Mediation analysis was performed to explore potential intermediate variables.
ResultsAmong 1,874 sepsis patients, higher AIP levels were associated with increased AKI incidence. Logistic regression showed a significant association between AIP and AKI in unadjusted and partially adjusted models, but the association was no longer significant after full adjustment. RCS analysis revealed a nonlinear relationship with a peak AKI risk at AIP = 1.333. Threshold analysis confirmed a turning point at this value. Subgroup analyses showed consistent associations, while nonlinear effects were more evident in specific groups. Mediation analysis suggested that SOFA score, creatinine, WBC count, and respiratory rate partially mediated the AIP-AKI relationship.
ConclusionAIP was nonlinearly associated with AKI in sepsis, with a clear threshold effect. This relationship was partially mediated by SOFA score, creatinine, WBC, and respiratory rate. AIP may serve as a useful marker for AKI risk assessment.
by Ruixue Qin, Huijuan Zhao, Hui Gao, He Liu
BackgroundAlzheimer’s disease and other dementias (ADRD) are significant global health concerns, with rising incidence rates and substantial social and economic implications due to population aging.
MethodsWe investigated trends in ADRD incidence from 1992 to 2021 across age, sex, and socio-demographic index (SDI) regions, utilizing data from the Global Burden of Disease (GBD) 2021 platform. An age-period-cohort (APC) model was employed to analyze the effects of age, period, and birth cohort on ADRD incidence, and a Bayesian age-period-cohort (BAPC) model was used to predict future trends.
ResultsGlobally, the age-standardized incidence rates (ASIR) remained relatively steady. However, the total number of ADRD cases witnessed a remarkable 141.25% increase, with 9,837,056 cases (95% UI: 8,620,519–11,163,700) in 2021. High SDI regions exhibited higher ASIR, whereas high-middle SDI regions showed the greatest growth, particularly among females. The net drift of ADRD incidence ranged from 0.43% per year in China to −0.68% per year in Denmark. Age effect was consistent across SDI regions, increasing exponentially with age. The 60–64 age group experienced the fastest annual incidence growth. High-middle SDI regions faced unfavorable period and cohort effects.
ConclusionAlthough progress in ADRD globally, significant regional and sex disparities persist. Strengthened surveillance and management of adults over 60 are urgently needed. Targeted public health policies and interventions are essential to address the escalating global dementia burden.
by Jaime Carballedo-Pulido, Mariona Farrés-Tarafa, Juan Roldán-Merino, Marta Berenguer-Poblet, Montserrat Girabent-Farrés, Carla Otero-Arús, Susana Santos-Ruiz
BackgroundAlthough the SBAR framework is widely used in clinical and educational settings, there is a lack of validated Spanish-language tools that objectively assess its use by students in simulation. The adaptation and validation of the SBAR-LA rubric address this gap and provide a resource for training and evaluating structured communication.
ObjectiveTo conduct the cross-cultural adaptation and psychometric validation of the SBAR-LA rubric in Spanish for assessing structured communication skills in undergraduate nursing students during clinical simulation.
MethodsA two-phase cross-sectional psychometric validation study was conducted. Phase one involved cross-cultural adaptation, including forward and backward translation, expert panel review, and cognitive debriefing with nursing students. Phase two assessed inter-rater reliability using Krippendorff’s alpha based on 97 performance evaluations obtained in different simulation scenarios. The SBAR-LA-Sp rubric contains 10 dichotomous items across the four SBAR dimensions.
ResultsThe Spanish version of the SBAR-LA rubric demonstrated excellent inter-rater reliability, with a Krippendorff’s alpha of 0.933 (95% CI: 0.905–0.956). Internal consistency and agreement between raters were also high, confirming the instrument’s robustness.
ConclusionsThe Spanish version of the SBAR-LA rubric provides an objective measure of structured communication in nursing simulation. The findings support its use in academic training. Further research is needed to examine its effect on learning outcomes.
by Min Wang, Yushun Yan, Wanqiu Yang, Ruini He, Lingdan Zhao, Yikai Dou, Yuanmei Tao, Xiao Yang, Qingqing Xiang, Xiaohong Ma
Psychiatric nurses represent a high-stress occupational group that experiences elevated levels of suicidal ideation (SI), emphasizing the need for focused mental health interventions. The main purpose of this study was to examine the prevalence of SI among psychiatric nurses and to identify the psychological and occupational factors associated with SI. A total of 1,835 psychiatric nurses completed questionnaires on depressive symptoms (PHQ-9), SI, quality of work-related life (QWL), and burnout. Multivariate logistic regression and phenotypic network analyses were conducted to identify factors associated with SI and the potential pathways linking depressive symptoms, burnout, and QWL to SI. The results indicated that 11.33% of the participants had SI in the past two weeks. Multivariate logistic regression revealed that emotional exhaustion, depersonalization, personal accomplishment, stress at work, general well-being, and the home-work interface were significant predictors of SI. Network analysis further revealed that psychomotor changes, guilt, sad mood, low energy, and appetite changes were the symptoms most directly associated with SI. In addition, sad mood, general well-being, and work-home interface were linked to job and career satisfaction, whereas sad mood and low energy were associated with emotional exhaustion and SI. These findings contribute valuable large-scale evidence on the mental health challenges faced by psychiatric nurses and highlight the importance of addressing mood disturbances, energy loss, and work-related stress in SI prevention efforts for this vulnerable group.
by Ruilan Lin, Ru Qin, Yunlong Zhang, Yao Guan, Boheng Wu, Shangyang Li, Shenhong Qu, Yulin Yuan
BackgroundThis study aims to assess the diagnostic value of the Epstein-Barr virus (EBV) BNLF2b antibody(P85-Ab), alone or in combination with VCA-IgA, Rta-IgG, and Zta-IgA antibodies, in the context of nasopharyngeal carcinoma (NPC).
MethodsThe study included 100 NPC patients and 100 healthy controls. Chemiluminescent microparticle immunoassay was utilized to measure P85-Ab levels in the serum samples of both NPC patients and healthy controls. Additionally, the ELISA method was employed to detect serum levels of VCA-IgA, Rta-IgG, and Zta-IgA antibodies. The study analyzed the roles of serum P85-Ab in conjunction with VCA-IgA, Rta-IgG, and Zta-IgA antibodies in the diagnosis of NPC.
ResultsSerum levels of P85-Ab, VCA-IgA, Rta-IgG, and Zta-IgA antibodies in NPC patients were significantly higher than those in the normal control group (P Conclusion
The combined detection of P85-Ab with VCA-IgA, Rta-IgG, and Zta-IgA antibodies demonstrates high diagnostic value for nasopharyngeal carcinoma. Serum P85-Ab may serve as a potential marker for the diagnosis of NPC.
by Ruibo Sha, Zhifeng Zhang, Xiao Cui, Qingzheng Mu
Sewer pipeline defect detection is a critical task for ensuring the normal operation of urban infrastructure. However, the sewer environment often presents challenges such as multi-scale defects, complex backgrounds, lighting changes, and diverse defect morphologies. To address these issues, this paper proposes a lightweight cross-scale feature fusion model based on YOLOv8. First, the C2f module in the backbone network is replaced with the C2f-FAM module to enhance multi-scale feature extraction capabilities. Second, the HS-BiFPN module is adopted to replace the original structure, leveraging cross-layer semantic fusion and feature re-weighting mechanisms to improve the model’s ability to distinguish complex backgrounds and diverse defect morphologies. Finally, DySample is introduced to replace traditional sampling operations, enhancing the model’s ability to capture details in complex environments. This study uses the Sewer-ML dataset to train and evaluate the model, selecting 1,158 images containing six types of typical defects (CK, PL, SG, SL, TL, ZW), and expanding the dataset to 1,952 images through data augmentation. Experimental results show that compared to the YOLOv8n model, the improved model achieves a 3.8% increase in mAP, while reducing the number of parameters by 35%, floating-point operations by 21%, and model size by 33%. By improving detection accuracy while achieving model lightweighting, the model demonstrates potential for application in pipeline defect detection.
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