Blood Profiles of Community-Dwelling People with Sarcopenia: Analysis Based on the China Health and Retirement Longitudinal Study.

INTRODUCTION: Routine blood factors can be economical and easily accessible candidates for sarcopenia screening and monitoring. The associations between sarcopenia and routine blood factors remain unclear. This study aimed to examine sarcopenia and blood factor associations based on a nation-wide cohort in China. METHODS: A total of 1,307 participants and 17 routine blood indices were selected from two waves (year 2011 and year 2015) of the China Health and Retirement Longitudinal Study (CHARLS). The diagnosis of sarcopenia was based on the criteria proposed by the Asian Working Group for Sarcopenia (AWGS 2019). Generalized mixed-effects models were performed for association analyses. A logistic regression (LR) model was conducted to examine the predictive power of identifying significant blood factors for sarcopenia. RESULTS: A higher sarcopenia risk was cross-sectionally associated with elevated blood concentrations of high-sensitivity C-reactive protein (hsCRP) (OR = 1.030, 95% CI [1.007, 1.053]), glycated hemoglobin (HbA1c) (OR = 1.407, 95% CI [1.126, 1.758]) and blood urea nitrogen (BUN) (OR = 1.044, 95% CI [1.002, 1.089]), and a decreased level of glucose (OR = 0.988, 95% CI [0.979, 0.997]). A higher baseline hsCRP value (OR = 1.034, 95% CI [1.029, 1.039]) and a greater over time change in hsCRP within 4 years (OR = 1.034, 95% CI [1.029, 1.039]) were associated with a higher sarcopenia risk. A higher BUN baseline value was related to a decreased sarcopenia risk over time (OR = 0.981, 95% CI [0.976, 0.986]), while a greater over time changes in BUN (OR = 1.034, 95% CI [1.029, 1.040]) and a smaller over time change in glucose (OR = 0.992, 95% CI [0.984, 0.999]) within 4 years were also related to a higher sarcopenia risk. LR based on significant blood factors (i.e., hsCRP, HbA1c, BUN, and glucose), and sarcopenia status in year 2015 yielded an area under the curve of 0.859 (95% CI: 0.836-0.882). CONCLUSION: Routine blood factors involved in inflammation, protein metabolism, and glucose metabolism are significantly associated with sarcopenia. In clinical practice, plasma hsCRP, BUN, blood sugar levels, sex, age, marital status, height, and weight might be helpful for sarcopenia evaluation and monitoring.

Sleep quality and psychological health in patients with pelvic and acetabulum fractures: a cross-sectional study.

BACKGROUND AND OBJECTIVES: It is known that difficulty sleeping after a fracture can have negative effects on both mental and physical health and may prolong the recovery process. The objective of this study is to explore how sleep quality and psychological health are linked in patients with pelvic and acetabulum fractures. METHODS: A study was conducted on 265 patients between 2018 and 2022 who had suffered pelvic and acetabulum fractures. The study examined various factors, including age, gender, cause of injury, post-operative complications, and injury severity. The study employed ordinal logistic regression to examine the relationship between various pelvic fractures and seven subscales of the Majeed Pelvic Score (MPS), as well as the Sleep Disorder Questionnaire (SDQ) and Beck Depression Inventory (BDI). The study focused on the postoperative outcome one year after surgery, and each patient was assessed at the one-year mark after surgical intervention. Additionally, the study evaluated the functional outcome, sleep quality, and psychological disorders of the patients. RESULTS: From 2018 to 2022, a total of 216 patients suffered from pelvic and acetabulum fractures. Among them, 6.6% experienced borderline clinical depression, and 45.2% reported mild mood disturbances. Anxiety was found to be mild to moderate in 46% of Tile C and posterior acetabulum wall fracture patients. About 24.8% of patients reported insomnia, while 23.1% reported sleep movement disorders. However, no significant correlation was found between fracture types and sleep disorders. The mean Majeed pelvic score (MPS) was 89.68. CONCLUSIONS: Patients with pelvic and acetabular fractures typically experience functional improvement, but may also be at increased risk for insomnia and sleep movement disorders, particularly for certain types of fractures. Psychological well-being varies between fracture groups, with signs of borderline clinical depression observed in some cases. However, anxiety levels do not appear to be significantly correlated with pelvic and acetabular fractures.

The Association Between Allostatic Load and Frailty Trajectories Among Adults Aged 50+ Years: Mediating Role of Physical Activity.

OBJECTIVES: To identify frailty trajectories and examine its association with allostatic load (AL) and mediating effect of physical activity (PA). METHODS: This study included 8,082 adults from the English Longitudinal Study of Aging over Waves 4-9. AL was calculated by 14 biological indicators, and a 53-item frailty index was used to evaluate frailty. Frailty trajectories were classified by group-based trajectory modeling, and the mediated effect of PA was tested by causal mediation analysis. RESULTS: Four frailty trajectories were identified: "Robustness" (n = 4,437, 54.9%), "Incident prefrailty" (n = 2,061, 25.5%), "Prefrailty to frailty" (n = 1,136, 14.1%), and "Frailty to severe frailty" (n = 448, 5.5%). High baseline AL was associated with increased odds of "Incident prefrailty," "Prefrailty to frailty," and "Frailty to severe frailty" trajectories. PA demonstrated significant mediated effects in aforementioned associations. CONCLUSIONS: AL is significantly associated with the onset and progression of frailty, and such associations are partially mediated by PA.

Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques.

OBJECTIVES: Our aim was to explore the possibility of using machine learning (ML) in predicting the onset and trajectories of depressive symptom in home-based older adults over a 7-year period. METHODS: Depressive symptom data (collected in the year 2011, 2013, 2015 and 2018) of home-based older Chinese (n = 2650) recruited in the China Health and Retirement Longitudinal Study (CHARLS) were included in the current analysis. The latent class growth modeling (LCGM) and growth mixture modeling (GMM) were used to classify different trajectory classes. Based on the identified trajectory patterns, three ML classification algorithms (i.e. gradient boosting decision tree, support vector machine and random forest) were evaluated with a 10-fold cross-validation procedure and a metric of the area under the receiver operating characteristic curve (AUC). RESULTS: Four trajectories were identified for the depressive symptoms: no symptoms (63.9%), depressive symptoms onset {incident increasing symptoms [new-onset increasing (16.8%)], chronic symptoms [slowly decreasing (12.5%), persistent high (6.8%)]}. Among the analyzed baseline variables, the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score, cognition, sleep time, self-reported memory were the top five important predictors across all trajectories. The mean AUCs of the three predictive models had a range from 0.661 to 0.892. CONCLUSIONS: ML techniques can be robust in predicting depressive symptom onset and trajectories over a 7-year period with easily accessible sociodemographic and health information.Supplemental data for this article is available online at http://dx.doi.org/10.1080/13607863.2022.2031868.

Development and validation of a risk assessment scale for pathological scarring.

To develop a risk assessment scale for pathological scarring and validate its psychometric properties. This was a methodological study. Researchers developed the scale based on a literature review, qualitative study and Delphi expert consultation. Subsequently, 409 patients participated in the study to test the psychometric properties of the scale. We evaluated construct validity, content validity, internal consistency reliability, and interrater reliability. The researchers developed a scale consisting of three dimensions and 12 items. Factor analysis extracted a total of four common factors that accounted for 62.22% of the total variance. The results revealed that the item-content validity index (I-CVI) ranged from 0.67 to 1, while the scale-content validity index (S-CVI) was 0.82. Internal consistency reliability: Cronbach's α of the items ranged from 0.67 to 0.76, while Cronbach's α of the whole scale was 0.74. Interrater reliability: the Kappa number was 0.73. The final scale showed adequate construct validity, content validity, and reliability. It is appropriate for use in research and clinical practice settings to identify patients with a risk of pathological scarring. Further study is needed to confirm the scale's validity and reliability in other settings and populations.

Nursing allocation in isolation wards of COVID-19 designated hospitals: a nationwide study in China.

BACKGROUND: Appropriate allocation of nursing staff is key to ensuring efficient nursing in hospitals, and is significantly correlated with patient safety, nursing quality, and nurse job satisfaction. However, there are few studies on nursing workforce allocation in the isolation wards of COVID-19 designated hospitals globally. This study aims to better understand the nursing workforce allocation in the isolation wards of COVID-19 designated hospitals in China, and provide a theoretical basis for efficiently deploying first-line nurses in China and across the world in the future. METHODS: An online survey was conducted among the head nurses (n = 229) and nurses (n = 1378) in the isolation wards of 117 hospitals (selected by stratified sampling), using a self-reported human resource allocation questionnaire. RESULTS: The average bed-to-nurse ratios of different isolation wards were different (Z = 36.742, P = 0.000). The bed-to-nurse ratios of the ICU, suspected COVID-19 cases ward, and confirmed COVID-19 cases ward, were 1:1.88, 1:0.56, and 1:0.45, respectively. The nurse work hours per shift in different isolation wards were also different (Z = 8.468, P = 0.014), with the specific values of the ICU, suspected COVID-19 cases ward, and confirmed COVID-19 cases ward, being 5, 6, and 6 h, respectively. A correlation analysis showed that the average work hours per shift was proportional to the overtime work of nurses (rs = 0.146), the proportion of nurse practitioners was proportional to the overall utilization rate of nursing human resources in the wards (rs = 0.136), and the proportion of nurses with college degrees was proportional to teamwork (rs = 0.142). The proportion of nurses above grade 10 was inversely proportional to teamwork and psychological problems (rs = 0.135, rs = 0.203). The results of multiple stepwise regression analyses showed that the work hours of nurses per shift was the main factor affecting nurse satisfaction and that the proportion of nurses and the work hours of nurses per shift were both independent factors affecting the length of stay (LOS) of patients. CONCLUSION: Hospitals in China have made good nursing workforce allocations during the COVID-19 pandemic, but there are certain shortcomings. Therefore, scientific and efficient nursing workforce allocation practice plans should be established to improve the ability of hospitals to deal with public health emergencies and are urgent problems that need to be addressed soon.

The Grading of Recommendations, assessment, development, and evaluation approach was rarely followed and inconsistently applied in pressure injury prevention guidelines development: A cross-sectional survey.

INTRODUCTION: The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach was developed to assess the certainty (or quality) of evidence and strength of recommendations in guidelines and endorsed internationally as a standard. Some guidelines had been developed to promote pressure injury prevention. AIMS: We explored whether and to what extent the development of pressure injury prevention guidelines had followed or been informed by the GRADE approach. If this approach was not used, we examined which other methods were used instead. METHODS: A cross-sectional study of pressure injury prevention guidelines was conducted. PubMed, Embase, CINAHL, and Chinese databases as well as guideline repositories and websites of professional bodies were searched for guidelines from 1990 to 2020. The grading systems of the certainty (or quality) of evidence and strength of recommendations of included guidelines were extracted. For the GRADE approach guidelines, compliance was assessed with the GRADE application criteria. RESULTS: Twenty guidelines were identified. Among them, four guidelines (20%) indicated the use of the GRADE approach. The compliance rate ranged from 33.3%-94.4%. Other approaches, such as the Scottish Intercollegiate Guidelines Network (SIGN) approach, were also used. CONCLUSION: The GRADE approach is rarely followed and inconsistently applied in pressure injury prevention guidelines. Other systems, such as the SIGN approach, are being used despite being outdated or inconsistent. Strategies for further uptake and appropriate application of the GRADE approach among guideline developers are needed in the future.

Questionnaires measuring patient participation in patient safety-A systematic review.

AIM: The purpose of this review was to evaluate the content, validity and reliability of patient-reported questionnaires on patient participation in patient safety. BACKGROUND: Patient participation in patient safety is one of the key strategies that are increasingly regarded as a critical intervention to improve the quality of safety care. EVALUATION: A systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The content, reliability and validity of patient-reported questionnaires on patient participation in patient safety were assessed. KEY ISSUES: Twenty-seven studies were included for data extraction and synthesis. The questionnaire contents most commonly used to describe patient participation in patient safety were 'attitudes and perceptions', 'experience', 'information and feedback' and 'willingness'. Internal consistency was evaluated for 17 questionnaires, and test-retest reliability was tested for four questionnaires. Content validity was assessed among all included questionnaires, and structural validity was evaluated for 12 questionnaires. CONCLUSIONS: Future research targeting the different safety issues is still indispensable for developing patient-reported questionnaires with great psychometric quality in validity, reliability, feasibility and usability in patient participation in patient safety. IMPLICATIONS FOR NURSING MANAGEMENT: Clinical nurses should consider the internal consistency, test-retest reliability, content validity and structural validity of the questionnaires that have been positively appraised for methodological quality before use.

Perspectives of nursing directors on emergency nurse deployment during the pandemic of COVID-19: A nationwide cross-sectional survey in mainland China.

AIMS: The aim of this study is to investigate the situation and perceptions of nursing directors about emergency nursing staff deployment in designated hospitals during the pandemic of COVID-19 in mainland China. BACKGROUND: The pandemic of COVID-19 has significantly depleted health care resources, leading to increased burden of nursing care and staffing and exacerbating the crisis in health care facilities. Currently, how to effectively plan and schedule nursing staffing in the pandemic still remains unknown. METHODS: From 14 July 2020 to 8 September 2020, 62 nursing directors of designated hospitals in mainland China were invited to participate in a cross-sectional online survey for their perceptions of nursing human-resource allocation during the pandemic of COVID-19. RESULTS: A total of 55 valid questionnaires were collected, showing that 96.36% of the hospitals had emergency nursing organizations and management systems during the pandemic, 96.36% had well-established scheduling principles for nursing human resources and 54.55% of hospitals had human-resource scheduling platforms. All the hospitals had trained emergency nursing staff in infection control (55, 100%), work process (51, 92.73%) and emergency skills (50, 90.91%). Most of the participants were satisfied with the nursing staffing deployments at their institutions (52, 94.55%). However, more than two thirds of them believed that their human-resource deployment plans need further improvements (39, 70.91%). CONCLUSIONS: Most of the designated hospitals investigated had established emergency nursing organizations, and management systems, and related regulations for the epidemic. However, the contents mentioned above still need to be further standardized. IMPLICATIONS FOR NURSING MANAGEMENT: The surge of patients in the epidemic was considerable challenge for the emergency capacity of hospitals. In the future, we should pay more attention to the following aspects: building emergency nursing staffing platforms, increasing emergency human-resource reserves, establishing reliable communication channels for emergency response teams, improving the rules and regulations of emergency human-resource management, offering more training and drills for emergency-related knowledge and skills and giving more focus on bio-psycho-social wellbeing of nurses.

RNA sequencing reveals transcriptomic changes in tobacco (Nicotiana tabacum) following NtCPS2 knockdown.

BACKGROUND: Amber-like compounds form in tobacco (Nicotiana tabacum) during leaf curing and impact aromatic quality. In particular, cis-abienol, a polycyclic labdane-related diterpenoid, is of research interest as a precursor of these compounds. Glandular trichome cells specifically express copalyl diphosphate synthase (NtCPS2) at high levels in tobacco, which, together with NtABS, are major regulators of cis-abienol biosynthesis in tobacco. RESULTS: To identify the genes involved in the biosynthesis of cis-abienol in tobacco, we constructed transgenic tobacco lines based on an NtCPS2 gene-knockdown model using CRISPR/Cas9 genome-editing technology to inhibit NtCPS2 function in vitro. In mutant plants, cis-abienol and labdene diol contents decreased, whereas the gibberellin and abscisic acid (ABA) contents increased compared with those in wild-type tobacco plants. RNA sequencing analysis revealed the presence of 9514 differentially expressed genes (DEGs; 4279 upregulated, 5235 downregulated) when the leaves of wild-type and NtCPS2-knockdown tobacco plants were screened. Among these DEGs, the genes encoding cis-abienol synthase, ent-kaurene oxidase, auxin/ABA-related proteins, and transcription factors were found to be involved in various biological and physiochemical processes, including diterpenoid biosynthesis, plant hormone signal transduction, and plant-pathogen interactions. CONCLUSIONS: The present study provides insight into the unique transcriptome profile of NtCPS2 knockdown tobacco, allowing for a better understanding of the biosynthesis of cis-abienol in tobacco.

Static one-leg standing balance test as a screening tool for low muscle mass in healthy elderly women.

BACKGROUND: Identification of simple screening tools for detecting lower skeletal muscle mass may be beneficial for planning effective interventions in the elderly. AIMS: We aimed to (1) establish a threshold for one-leg standing balance test (OLST) time for low muscle mass, and (2) test the ability of that threshold to assess muscular impairments in a poor balance group. METHODS: Eyes-open OLST (maximum duration 30 s) was performed with right and left legs in 291 women (age 71 ± 6 years). OLST time was calculated as the sum of the OLST time of right and left legs. Fat-free mass (FFM), skeletal muscle mass (SMM), fat mass, biceps brachii and vastus lateralis sizes; handgrip strength (HGS), elbow flexion maximum torque (MVCEF) and knee extension maximum torque (MVCKE) were measured. Muscle quality was calculated as MVCKE/FFM and physical activity was assessed by questionnaire. Low muscle mass was defined as SMMrelative of 22.1%, a previously established threshold for pre-sarcopenia. RESULTS: The OLST threshold time to detect low muscle mass was 55 s (sensitivity: 0.63; specificity: 0.60). The poor balance group (OLST < 55 s) had higher fat mass (3.0%, p < 0.001), larger VL thickness (5.1%, p = 0.016), and lower HGS (- 10.2%, p < 0.001), MVCEF (- 8.2%, p = 0.003), MVCKE (- 9.5%, p = 0.012), MVCKE/FFM (- 11.0%, p = 0.004) and physical activity (- 8.0%, p = 0.024) compared to the normal balance group. While after adjusting age, the differences exist for HGS, fat mass and VL thickness only. DISCUSSION: An OLST threshold of 55 s calculated as the summed score from both legs discriminated pre-sarcopenic characteristics among active, community-dwelling older women with limited potential (sensitivity 0.63, specificity 0.60). CONCLUSION: OLST, which can be performed easily in community settings without the need for more complex muscle mass measurement, may help identify women at risk of developing sarcopenia.

Predicting venous thromboembolism in hospitalized trauma patients: a combination of the Caprini score and data-driven machine learning model.

BACKGROUND: Venous thromboembolism (VTE) is a common complication of hospitalized trauma patients and has an adverse impact on patient outcomes. However, there is still a lack of appropriate tools for effectively predicting VTE for trauma patients. We try to verify the accuracy of the Caprini score for predicting VTE in trauma patients, and further improve the prediction through machine learning algorithms. METHODS: We retrospectively reviewed emergency trauma patients who were admitted to a trauma center in a tertiary hospital from September 2019 to March 2020. The data in the patient's electronic health record (EHR) and the Caprini score were extracted, combined with multiple feature screening methods and the random forest (RF) algorithm to constructs the VTE prediction model, and compares the prediction performance of (1) using only Caprini score; (2) using EHR data to build a machine learning model; (3) using EHR data and Caprini score to build a machine learning model. True Positive Rate (TPR), False Positive Rate (FPR), Area Under Curve (AUC), accuracy, and precision were reported. RESULTS: The Caprini score shows a good VTE prediction effect on the trauma hospitalized population when the cut-off point is 11 (TPR = 0.667, FPR = 0.227, AUC = 0.773), The best prediction model is LASSO+RF model combined with Caprini Score and other five features extracted from EHR data (TPR = 0.757, FPR = 0.290, AUC = 0.799). CONCLUSION: The Caprini score has good VTE prediction performance in trauma patients, and the use of machine learning methods can further improve the prediction performance.

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes.

Effects of In Vitro Digestion on the Content and Biological Activity of Polyphenols from Acacia mearnsii Bark.

The stability and bioaccessibility of polyphenol from Acacia mearnsii bark were measured at various stages during in vitro simulated digestion. Subsequently, the changes in the total polyphenol content (TPC) and biological activity were studied. The results showed that the phenolic compounds from A. mearnsii remained stable, and TPC underwent few changes during gastric digestion. Nonetheless, intestinal digestion led to the degradation of proanthocyanidins (PAs) and a significant decrease in TPC (26%). Degradation was determined by normal-phase HPLC and gel permeation chromatography. Only monomers, dimers, and trimers of flavan-3-ols were identified in the serum-accessible fraction for characterization of their bioaccessibility. The results also indicated the obvious antioxidant capacity of PAs from A. mearnsii bark, and ~53% of the α-glucosidase⁻inhibitory effect was preserved. All these findings show that PAs from A. mearnsii bark as a native plant source may be particularly beneficial for human health as a natural nutritional supplement.

Longitudinal analysis on inflammatory markers and frailty progression: based on the English longitudinal study of aging.

PURPOSE: Frailty is a common health state that is closely linked to adverse health outcomes in aging society. Although many inflammatory biomarkers have been cross-sectionally associated with frailty, knowledge on the longitudinal association is still limited. This study investigated the associations between inflammatory factors in clinical practice and frailty progression over time. METHODS: To investigate the associations of three common inflammatory markers (hypersensitive C-reactive protein [hsCRP], white blood cell [WBC] and fibrinogen) with the progression of frailty. METHODS: Data of 2316 participants (age 67.9 ± 6.1 years) were obtained from the English longitudinal study of aging (wave 4, 6 and 8) over an 8-year follow-up. The frailty index (FI) was calculated from 52 items. Mixed-effects models and Cox proportional hazards (Cox-PH) models were used to analyze the associations of hsCRP, WBC and fibrinogen with frailty progression. Values of inflammatory biomarkers were log-transformed. Age, sex and gross wealth were controlled. RESULTS: Mixed-effects models showed that at a cross-sectional level, higher levels of hsCRP (ß: 0.007, 95% CI 0.004-0.010), WBC (ß: 0.021, 95% CI 0.010-0.032) and fibrinogen (ß: 0.022, 95% CI 0.005-0.038) were associated with greater FI values while no significant time interaction was found. Cox-PH models showed that higher baseline levels of hsCRP (HR: 1.10, 95% CI 1.03-1.17) and WBC (HR: 1.23, 95% CI 1.10-1.37) were linked to a greater risk of developing frailty within 8 years. CONCLUSIONS: We concluded that hsCRP, WBC and fibrinogen can reflect frailty status at a cross-sectional level while only hsCRP and WBC are associated with frailty progression over an 8-year period.

High deposition and precise stimulus-response release performance of lignin-coated dendritic mesoporous organosilica nanoparticles for efficient pesticide utilization.

The inefficient and improper use of conventional pesticides has prompted the development of targeted and cost-effective pesticide delivery systems, which aim to optimize the efficient utilization of pesticides while minimizing environmental pollution in surrounding areas. In this paper, a dual-stimuli-responsive pesticide slow-release nanopesticide system (NES@DMONs@LGN) was designed in this study, utilizing mesoporous silica (DMONs) as a nanocarrier and lignin (LGN) as a capping agent to encapsulate the pesticide molecules within DMONs. This system enables intelligent release of pesticide molecules while preventing environmental pollution caused by leakage. Additionally, NES@DMONs@LGN exhibit excellent specific loading efficiency. The abundant hydrophilic functional groups in the lignin layer on the surface of NES@DMONs@LGN can establish hydrogen bonds with advanced fatty acids and fatty alcohols present in the waxy epidermis of plants, thereby significantly enhancing carrier wettability and adhesion. Typically, phytophagous lepidopteran pests have an alkaline midgut and possess lignin-degrading enzymes. The NES@DMONs@LGN developed in this study are capable of rapid release under high temperature and alkaline conditions. Therefore, the precise release of pesticide molecules in the target pests can be achieved, thus increasing the actual utilization rate of pesticides. The experimental results demonstrated that NES@DMONs@LGN effectively prevented photodegradation of the active ingredient after 48 h of UV irradiation, resulting in a 3.7-fold improvement in photostability and providing robust UV protection. By encapsulating pesticide molecules with nanocarriers, the release of pesticides in non-targeted environments can be prevented, thereby significantly reducing toxicity to zebrafish. Thus, this study provides a promising solution for sustainable greening of agriculture.

Comparing the effects of pulsed and radiofrequency catheter ablation on quality of life, anxiety, and depression of patients with paroxysmal supraventricular tachycardia: a single-center, randomized, single-blind, standard-controlled trial.

BACKGROUND: Radiofrequency catheter ablation (RFCA) may lead to decreased quality of life (QOL) and increased anxiety and depression in patients with paroxysmal supraventricular tachycardia (PSVT), possibly due to the lack of selectivity of the ablation tissue and the long ablation time. In recent years, pulsed field ablation (PFA) has been used for the first time in China to treat PSVT patients because of its ability to ablate abnormal tissue sites in a precise and transient manner. This study was conducted to compare the effects of PFA and RFCA on QOL and psychological symptoms of PSVT patients. METHODS: We have designed a single-center, randomized, single-blind, standard-controlled trial. A total of 50 participants who met the eligibility criteria would be randomly allocated into the PFA group or RFCA group in a 1:1 ratio. All participants were assessed using the 36-Item Short-Form Health Survey (SF-36) and the Hospital Anxiety and Depression Scale (HADS) at pre-procedure (T0), post-procedure (T1), and 3 months post-procedure (T2). The SPSS 21.0 software was used to analyze the data through Wilcoxon and Fisher's exact tests and repeated measures ANOVA. RESULTS: Twenty-five in the PFA group and 24 in the RFCA group completed the trial. SF-36: (1) Between-group comparison: At T1, PFA group had significantly higher SF-36 scores on physiological function (PF) and general health (GH) than RFCA group, with a treatment difference of 5.61 points and 18.51 points(P < 0.05). (2) Within-group comparison: We found that in the PFA and RFCA groups, T2 showed significant improvement in the remaining 6 subscales of the SF-36 scale compared to T1 and T0 (P < 0.05), except for body pain (BP) and social function (SF) scores. HADS: (1) Between-group comparison: no significant difference (P > 0.05). (2) Within-group comparison: The HADS scores of the PFA and RFCA groups were statistically significant at T2 compared to T0 and T1 (P < 0.05). CONCLUSIONS: Our study provided new and meaningful evidence that PFA was effective in significantly improving QOL and decreasing anxiety and depression in PFA patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2200060272.

MRI spectrum of avascular necrosis of femoral head in patients treated for COVID-19.

BACKGROUND AND PURPOSE: This prospective observational study aimed to investigate the occurrence of avascular necrosis (AVN) of the femoral head in COVID-19 patients through MRI scans. The study examined the patterns of AVN in 110 individuals who had undergone conventional COVID-19 therapy and reported hip discomfort. This study highlights the importance of considering AVN as a potential complication of COVID-19 therapy, particularly in younger patients who experience hip discomfort. METHODS: Individuals who had corticosteroid treatment for COVID-19 and experienced hip discomfort during 6 months between January 2022 and August 2022 were included in this study, and an MRI scan was done to observe changes in the hip joint. RESULTS: The results were classified using the Ficat and Arlet classification system. The analysis revealed that AVN was not present in 91.81% of cases. However, Stage I AVN was detected in 4.54% of cases, Stage II AVN in 2.72% of cases, and Stage III AVN in 1.1% of cases. No cases of Stage IV AVN were observed. CONCLUSIONS: The study concludes that AVN occurred in 6% of individuals who underwent conventional therapy for COVID-19 and experienced hip discomfort. In these settings (post COVID-19), normal MRI results were more typical, and mild AVN (Stage I) was a frequent finding in MRI scans that were positive.

Factors affecting patient activation among patients with systemic lupus erythematosus.

There are limited published studies on patient activation among patients with systemic lupus erythematosus (SLE) in China. Disease activity can significantly influence a patient's perception of their condition, subsequently impacting patient activation. However, the mechanisms through which disease activity influences patient activation remain poorly understood. This study aimed to investigate patient activation among patients with SLE in China and explore the influencing factors. We conducted a cross-sectional study from June to December 2021 at a rheumatology and immunology department of a tertiary hospital in Chengdu, China. Data were collected by questionnaire, including general information, disease activity, quality of chronic illness care, health literacy, self-efficacy, motivation, social support, and patient activation. A patient activation model was constructed based on the conceptual framework derived from the individual and family self-management theory. To evaluate the moderating effect of disease activity on patient activation model, participants were divided into two subgroups (low disease activity group and high disease activity group). 426 SLE patients were included. The mean score of patient activation among SLE patients was 63.28 ± 11.82, indicating that most SLE patients lacked skills and confidence to stick with health-promoting behaviors. Health literacy, social support, and self-efficacy had the greatest effect on patient activation. In the multi-group analysis, social support and health literacy contributed more to patient activation in SLE patients with high and low disease activity, respectively. Patient activation among SLE patients in China was at the third level. Healthcare professionals should help them adhere to health-promoting behaviors. Health literacy, social support, and self-efficacy are vital factors for patient activation. These factors should be prioritized based on disease activity when developing individually tailored interventions for patient activation.

Estimation of soybean yield based on high-throughput phenotyping and machine learning.

Introduction: Soybeans are an important crop used for food, oil, and feed. However, China's soybean self-sufficiency is highly inadequate, with an annual import volume exceeding 80%. RGB cameras serve as powerful tools for estimating crop yield, and machine learning is a practical method based on various features, providing improved yield predictions. However, selecting different input parameters and models, specifically optimal features and model effects, significantly influences soybean yield prediction. Methods: This study used an RGB camera to capture soybean canopy images from both the side and top perspectives during the R6 stage (pod filling stage) for 240 soybean varieties (a natural population formed by four provinces in China: Sichuan, Yunnan, Chongqing, and Guizhou). From these images, the morphological, color, and textural features of the soybeans were extracted. Subsequently, feature selection was performed on the image parameters using a Pearson correlation coefficient threshold ≥0.5. Five machine learning methods, namely, CatBoost, LightGBM, RF, GBDT, and MLP, were employed to establish soybean yield estimation models based on the individual and combined image parameters from the two perspectives extracted from RGB images. Results: (1) GBDT is the optimal model for predicting soybean yield, with a test set R2 value of 0.82, an RMSE of 1.99 g/plant, and an MAE of 3.12%. (2) The fusion of multiangle and multitype indicators is conducive to improving soybean yield prediction accuracy. Conclusion: Therefore, this combination of parameters extracted from RGB images via machine learning has great potential for estimating soybean yield, providing a theoretical basis and technical support for accelerating the soybean breeding process.