Association between serum sodium trajectory and mortality in patients with acute kidney injury: a retrospective cohort study.

INTRODUCTION: Dysnatremia is strongly associated with poor prognosis in acute kidney injury (AKI); however, the impact of sodium trajectories on the prognosis of patients with AKI has not yet been well elucidated. This study aimed to assess the association between sodium trajectories in patients with AKI and mortality at 30-day and 1-year follow-up. METHODS: This retrospective cohort study used data from Medical Information Mart for Intensive Care (MIMIC)-IV database, and patients diagnosed with AKI within 48 h after admission were enrolled. Group-based trajectory models (GBTM) were applied to map the developmental course of the serum sodium fluctuations. Kaplan-Meier survival curve was used to compare differences in mortality in AKI patients with distinct serum sodium trajectories. Hazard ratios (HRs) were calculated to determine the association between trajectories and prognosis using Cox proportional hazard models. RESULTS: A total of 9,314 AKI patients were enrolled. Three distinct sodium trajectories were identified including: (i) stable group (ST, in which the serum sodium levels remained relatively stable, n = 4,935; 53.0%), (ii) descending group (DS, in which the serum sodium levels declined, n = 2,994; 32.15%) and (iii) ascending group (AS, in which the serum sodium levels were elevated, n = 1,383; 14.85%). There was no significant difference in age and gender distribution among the groups. The 30-day mortality rates were 7.9% in ST, 9.5% in DS and 16.6% in AS (p < 0.001). The results of 1-year mortality rates were similar (p < 0.001). In adjusted analysis, patients in the DS (HR = 1.22, 95% confidence interval [CI], 1.04-1.43, p = 0.015) and AS (HR = 1.68, 95% CI, 1.42-2.01, p = 0.013) groups had higher risks of 30-day mortality compared to those in the ST group. CONCLUSION: In patients with AKI, the serum sodium trajectories were independently associated with 30-day and 1-year mortality. Association between serum sodium level trajectories and prognosis in patients with AKI deserve further study.

Development and validation of machine learning models to predict frailty risk for elderly.

AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to predict frailty risk in the elderly. DESIGN: A prospective cohort study. METHODS: We collected data on 6997 elderly people from Chinese Longitudinal Healthy Longevity Study wave 6-7 surveys (2011-2012, 2014). After the baseline survey in 1998 (wave 1), the project conducted follow-up surveys (wave 2-8) in 2000-2018. The osteoporotic fractures index was used to assess frailty. Four ML algorithms (random forest [RF], support vector machine, XGBoost and logistic regression [LR]) were used to develop models to identify the risk factors of frailty and predict the risk of frailty. Different ML models were used for the prediction of frailty risk in the elderly and frailty risk was trained on a cohort of 4385 elderly people with frailty (split into a training cohort [75%] and internal validation cohort [25%]). The best-performing model for each study outcome was tested in an external validation cohort of 6997 elderly people with frailty pooled from the surveys (wave 6-7). Model performance was assessed by receiver operating curve and F2-score. RESULTS: Among the four ML models, the F2-score values were similar (0.91 vs. 0.91 vs. 0.88 vs. 0.90), and the area under the curve (AUC) values of RF model was the highest (0.75), followed by LR model (0.74). In the final two models, the AUC values of RF and LR model were similar (0.77 vs. 0.76) and their accuracy was identical (87.4% vs. 87.4%). CONCLUSION: Our study developed a preliminary prediction model based on two different ML approaches to help predict frailty risk in the elderly. IMPACT: The presented models from this study can be used to inform healthcare providers to predict the frailty probability among older adults and maybe help guide the development of effective frailty risk management interventions. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Detecting frailty at an early stage and implementing timely targeted interventions may help to improve the allocation of health care resources and to reduce frailty-related burden. Identifying risk factors for frailty could be beneficial to provide tailored and personalized care intervention for older adults to more accurately prevent or improve their frail conditions so as to improve their quality of life. REPORTING METHOD: The study has adhered to STROBE guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

NIR-switchable local hydrogen generation by tandem bimetallic MOFs nanocomposites for enhanced chemodynamic therapy.

The inadequate quantity of hydrogen peroxide (H2O2) in cancer cells promptly results in the constrained success of chemodynamic therapy (CDT). Significant efforts made throughout the years; nevertheless, researchers are still facing the great challenge of designing a CDT agent and securing H2O2 supply within the tumor cell. In this study, taking advantage of H2O2 level maintenance mechanism in cancer cells, a nanozyme-based bimetallic metal-organic frameworks (MOFs) tandem reactor is fabricated to elevate intracellular H2O2 levels, thereby enhancing CDT. In addition, under near-infrared excitation, the upconversion nanoparticles (UCNPs) loaded into the MOFs can perform photocatalysis and generate hydrogen, which increases cellular susceptibility to radicals induced from H2O2, inhibits cancer cell energy, causes DNA damages and induces tumor cell apoptosis, thus improving CDT therapeutic efficacy synergistically. The proposed nanozyme-based bimetallic MOFs-mediated CDT and UCNPs-mediated hydrogen therapy act as combined therapy with high efficacy and low toxicity.

Detection of Hybrid Fusion Transcripts, Aberrant Transcript Expression, and Specific Single Nucleotide Variants in Acute Leukemia and Myeloid Disorders with Recurrent Gene Rearrangements.

INTRODUCTION: A variety of gene rearrangements and molecular alterations are key drivers in the pathobiology of acute leukemia and myeloid disorders; current classification systems increasingly incorporate these findings in diagnostic algorithms. Therefore, clinical laboratories require versatile tools, which can detect an increasing number and variety of molecular and cytogenetic alterations of clinical significance. METHODS: We validated an RNA-based next-generation sequencing (NGS) assay that enables the detection of: (i) numerous hybrid fusion transcripts (including rare/novel gene partners), (ii) aberrantly expressed EVI1 (MECOM) and IKZF1 (Del exons 4-7) transcripts, and (iii) hotspot variants in KIT, ABL1, NPM1 (relevant in the context of gene rearrangement status). RESULTS: For hybrid fusion transcripts, the assay showed 98-100% concordance for known positive and negative samples, with an analytical sensitivity (i.e., limit of detection) of approximately 0.8% cells. Samples with underlying EVI1 (MECOM) translocations demonstrated increased EVI1 (MECOM) expression. Aberrant IKZF1 (Del exons 4-7) transcripts detectable with the assay were also present on orthogonal reverse transcription PCR. Specific hotspot mutations in KIT, ABL1, and NPM1 detected with the assay showed 100% concordance with orthogonal testing. Lastly, several illustrative samples are included to highlight the assay's clinically relevant contributions to patient workup. CONCLUSION: Through its ability to simultaneously detect various gene rearrangements, aberrantly expressed transcripts, and hotspot mutations, this RNA-based NGS assay is a valuable tool for clinical laboratories to supplement other molecular and cytogenetic methods used in the diagnostic workup and in clinical research for patients with acute leukemia and myeloid disorders.

Effects of blended learning on undergraduate nursing students' knowledge, skills, critical thinking ability and mental health: A systematic review and meta-analysis.

AIM: This study aimed to evaluate the effects of blended learning on nursing students. The primary outcomes include knowledge and skills, and the secondary outcomes include critical thinking ability, mental health, blended learning design, and nursing students' attitudes toward blended learning. BACKGROUND: Blended learning combines the advantages of online learning and traditional face-to-face learning, and makes up for the disadvantages of simple online learning or traditional learning. The effects of blended learning on the knowledge, skills, critical thinking ability, and mental health of nursing students were unknown. DESIGN: Systematic review and meta-analysis. METHODS: The present systematic review and meta-analysis was applied according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Publications were searched in PubMed, Web of Science, EMBASE, ERIC, CINAHL and the Cochrane's Library before February 2023. Two researchers independently retrieved articles and evaluated quality. The meta-analysis was performed using Stata 12.0 software according to PRISMA guidelines. The risk of bias in the selected studies was evaluated using the Revised Cochrane risk-of-bias tool for randomized trials. Heterogeneity was assessed by I2 and P statistics. Standardized mean difference (SMD) and 95% confidence intervals (CIs) were used as effective indicators. RESULTS: A total of 26 studies involving 2823 nursing students were included in the present study. The results showed that blended learning courses were designed based on learning theory. Blended learning was more effective on the knowledge (SMD = 0.73, 95%CI [0.37, 1.09]) and skills (SMD = 0.86, 95% CI [0.35, 1.37]) compared with non-blended learning for nursing students. Critical thinking ability improved significantly through BL (SMD = 2.23, 95% CI [0.85, 3.61]). In addition, blended learning had a positive impact on nursing students' mental health. Nursing students were very satisfied with blended learning. CONCLUSIONS: The results of this study indicated that blended learning had a positive impact on nursing students. In the future, the optimal ratio of online to offline learning in blended learning should also be explored.

Effects of reminiscence therapy combined with memory specificity training (RT-MeST) on depressive symptoms in older adults: a randomized controlled trial protocol.

BACKGROUND: Geriatric depression has become a serious public health problem, and reduced autobiographical memory and increased overgeneral memory, as the main cognitive markers of depression, are not only associated with current depressive symptoms but also associated with the onset and course of depression, which can lead to a range of harms. Economic and effective psychological interventions are urgently needed. The aim of this study is to confirm the effectiveness of reminiscence therapy combined with memory specificity training in improving autobiographical memory and depressive symptoms in older adults. METHODS: In this multicentre, single-blind, three-arm parallel randomized controlled study, we aim to enrol 78 older adults aged 65 years or older with a score of ≥ 11 on the Geriatric Depression Scale, and participants will be randomly assigned to either a reminiscence therapy group, a reminiscence therapy with memory specificity training group or a usual care group. Assessments will be conducted at baseline (T0) as well as immediately post-intervention (T1) and 1 (T2), 3 (T3) and 6 (T4) months post-intervention. The primary outcome measure is self-reported depressive symptoms, measured using the GDS. Secondary outcome measures include measures of autobiographical memory, rumination, and social engagement. DISCUSSION: We believe that the intervention will play a positive role in improving autobiographical memory and depressive symptoms in older adults. Poor autobiographical memory is a predictor of depression and a major cognitive marker, and improving autobiographical memory is of great significance in alleviating depressive symptoms in older people. If our program is effective, it will provide a convenient and feasible strategy for further promoting healthy ageing. TRIAL REGISTRATION: ChiCTR2200065446.

Proteomics and transcriptomics explore the effect of mixture of herbal extract on diabetic wound healing process.

BACKGROUND: The annual incidence of diabetic foot ulcers (DFUs) has been reported to vary from 0.2% to 11% in diabetes-specific clinical settings and less than 0.1% to 8% in community- and population-based cohorts. According to the International Diabetes Foundation, approximately 40 million to 60 million people worldwide are affected by DFUs, and a recent meta-analysis indicates a global prevalence of 6.3% among adults with diabetes, or about 33 million individuals. The cost of diabetes care is significant, amounting to $273 billion in direct and $90 billion in indirect expenses annually, in America. Foot complications in diabetes care excess annual expenditures ranging from 50% to 200% above the baseline cost of diabetes-related care. The cost of advanced-stage ulcers can be more than $50,000 per wound episode, and the direct expenses of major amputation are even higher. DFUs can be treated using various methods, including wound dressings, antibiotics, pressure-off loading, skin substitutes, stem cells, debridement, topical oxygen therapy, gene therapy and growth factors. For severe DFUs patients are at risk of amputation if treatment is not timely or appropriate. Amputating limbs not only causes physical pain to patients, but also brings economic burden due to lost productivity, and decreased employment linked to DFUs. Currently, long-term use of local antibiotics in clinical practice is prone to induce drug resistance, while growth factors do not effectively inhibit bacterial growth and control inflammation in wounds. Stem cell and gene therapies are still in the experimental stage. The method of local debridement combined with negative pressure therapy is expensive. Therefore, we urgently need an affordable, non-surgical method to treat diabetic ulcers. Extracts of bark of Bauhinia purpurea, Paeoniae rubrae, Angelica dahurica (Hoffm.) Benth. & Hook.f. ex Franch. & Sav. (Hoffm.) Benth. & Hook.f. ex Franch. & Sav., Acorus calamus L, and Radix Angelicae biseratae have been used as traditional remedies to treat inflammation-related diseases and cutaneous wounds due to their anti-inflammatory properties and their ability to promote vascular renewal. However, there have been few studies on the mixture of these five herbal extracts on diabetic wound healing. PURPOSE: This study was designed to assess the healing effect of a mixture of five aforementioned herbal extracts on diabetic ulcer wounds in rats, and to reveal the potential mechanisms behind any potential wound healing using transcriptomics and proteomics. STUDY DESIGN: We designed the experiment to explore the effects of five herbal extracts on diabetic wound healing process through in vivo experiments and to investigate the underlying mechanisms through proteomics and transcriptomics. METHODS: We used a mixture of five aforementioned herbal extract to treat rat model of diabetic established by intraperitoneal injection of streptozotocin, and a 2 × 2 cm round full-thickness skin defect was created on the back of the rat. Staphylococcus aureus (1 ml of 1.5 × 109 cfu/ml) was evenly applied to the wound. The wound was then observed for 72 h. The infected ulcer model of diabetic rats was considered to be successfully established if the wound was found to be infected with S. aureus. According to different medications, the rats were divided into three groups, namely mixture of herbal extract (MHE), Kangfuxin solution (KFS) and control (Ctrl). The effects of the medicine on wound healing were observed. HE staining and Masson staining were performed to evaluate the histopathological changes and collagen synthesis. IHC staining was used to assess the neovascularization, and M2 macrophage proliferation was determined by immunofluorescence staining. Proteomic and transcriptomic studies were performed to explore potential mechanism of five herbal extracts to promote wound healing. UHPLC-QE-MS was performed to identify the chemical composition of mixture of herbal extract. RESULTS: The study show that the mixed herbal extract promotes angiogenesis, proliferation of M2 macrophages, and collagen synthesis. Transcriptomics showed that rno-miR-1298, rno-miR-144-5p, and rno-miR-92a-1-5p are vital miRNAs which also play a significant role in role in regulating wound healing. Proteomics results showed that the following proteins were important in wounds treated with MHE: Rack1, LOC100362366, Cops2, Cops6, Eif4e, Eif3c, Rpl12, Srp54, Rpl13 and Lsm7. Autophagy, PI3-Akt and mTOR signaling pathways were enriched after treatment with MHE compared to other groups. CONCLUSION: Herein, we have shown that MHE containing extracts of bark of Bauhinia purpurea, P. rubrae, A. dahurica (Hoffm.) Benth. & Hook.f. ex Franch. & Sav., A. calamus L, and R. A. biseratae has significant wound healing effects in the diabetic ulcer wound rat model. These results suggest that local application of MHE in diabetic wounds can accelerate the wound healing process. Moreover, in vivo experiments revealed that the diabetic wound healing process was primarily mediated by angiogenesis and M2 macrophage transition. Therefore, this study may provide a promising and non-surgical therapeutic strategy to accelerate diabetic wound healing, thereby decreasing the number of limb amputations in diabetic patients.

Effects of group reminiscence interventions on depressive symptoms and life satisfaction in older adults with intact cognition and mild cognitive impairment: A systematic review.

OBJECTIVE: Reminiscence interventions have been extensively used to improve the psychological health of people with dementia. However, there is uncertainty about the effectiveness of group reminiscence interventions for older adults with intact cognition and mild cognitive impairment. Based on the large number of older adults and strained health care resources in China, we conducted a systematic review of the evidence on the effectiveness of group reminiscence interventions for older adults with intact cognition or mild cognitive impairment. MATERIALS AND METHODS: Five English databases were searched from inception to 21 August 2022. The quality of the included articles was assessed by using the Cochrane Risk of Bias Scale or Criteria (2020) and the Australian Evidence-Based Health Care Centre (2020). Data related to study and intervention characteristics were extracted. RESULTS: Twenty-four articles were included, of which eight were quasiexperimental studies and sixteen were randomized controlled studies. The overall study quality was high, but most studies did not blind the participants. Group reminiscence interventions were beneficial in improving depressive symptoms and life satisfaction in older adults with intact cognition or mild cognitive impairment, but no valid conclusions could be drawn about the effect on quality of life. CONCLUSIONS: Group reminiscence interventions are an effective type of psychological intervention to improve the psychological health of older people. In addition, group reminiscence interventions are simple and easy to implement and can be considered a routine care activity to meet the spiritual needs of cognitively intact and mildly cognitively impaired older people.

An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.

RESEARCH QUESTION: Can a multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical parameters provide personalized evaluation of endometrial receptivity and predict the occurrence of clinical pregnancy after frozen embryo transfer (FET)? DESIGN: Prospective cohort study of women (n = 326) who underwent FET between August 2019 and December 2021. Input quantitative variables and input image data for radiomic feature extraction were collected to establish a multi-modal fusion prediction model. An additional independent dataset of 453 ultrasound endometrial images was used to establish the segmentation model to determine the endometrial region on ultrasound images for analysis. The performance of different algorithms and different input data for prediction of FET outcome were compared. RESULTS: A total of 240 patients with complete data were included in the final cohort. The proposed multi-modal fusion model performed significantly better than the use of either image or quantitative variables alone to predict the occurrence of clinical pregnancy after FET (P ≤ 0.034). Its area under the curve, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the proposed model were 0.825, 72.5%, 96.2%, 58.3%, 72.3% and 89.5%, respectively. The Dice coefficient of the multi-task endometrial ultrasound segmentation model was 0.89. Use of endometrial segmentation features significantly improved the prediction performance of the model (P = 0.041). CONCLUSIONS: The multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical quantitative variables offers a favourable and rapid non-invasive approach for personalized prediction of FET outcome.

Surgical methods influence on the risk of anastomotic fistula after pancreaticoduodenectomy: a systematic review and network meta-analysis.

BACKGROUND: Pancreaticoduodenectomy is the first choice surgical intervention for the radical treatment of pancreatic tumors. However, an anastomotic fistula is a common complication after pancreaticoduodenectomy with a high mortality rate. With the development of minimally invasive surgery, open pancreaticoduodenectomy (OPD), laparoscopic pancreaticoduodenectomy (LPD), and robotic pancreaticoduodenectomy (RPD) are gaining interest. But the impact of these surgical methods on the risk of anastomosis has not been confirmed. Therefore, we aimed to integrate relevant clinical studies and explore the effects of these three surgical methods on the occurrence of anastomotic fistula after pancreaticoduodenectomy. METHODS: A systematic literature search was conducted for studies reporting the RPD, LPD, and OPD. Network meta-analysis of postoperative anastomotic fistula (Pancreatic fistula, biliary leakage, gastrointestinal fistula) was performed. RESULTS: Sixty-five studies including 10,026 patients were included in the network meta-analysis. The rank of risk probability of pancreatic fistula for RPD (0.00) was better than LPD (0.37) and OPD (0.62). Thus, the analysis suggests the rank of risk of the postoperative pancreatic fistula for RPD, LPD, and OPD. The rank of risk probability for biliary leakage was similar for RPD (0.15) and LPD (0.15), and both were better than OPD (0.68). CONCLUSIONS: This network meta-analysis provided ranking for three different types of pancreaticoduodenectomy. The RPD and LPD can effectively improve the quality of surgery and are safe as well as feasible for OPD.

Development and Validation of a Nomogram for Predicting Tigecycline-Related Coagulopathy: A Retrospective Cohort Study.

Background: Although tigecycline is an effective drug against drug-resistant bacteria, it demonstrated a higher all-cause mortality than comparator antibiotics and a high incidence of coagulation disorders which can be accompanied by severe bleeding. At present, a predictive model for tigecycline-related coagulopathy is not readily available, and the prognostic value of coagulopathy in tigecycline-administered patients has not been elucidated. In this paper, we investigate the association between tigecycline-related coagulopathy and in-hospital mortality to develop a nomogram for the prediction of tigecycline-related coagulopathy. Methods: This retrospective cohort study includes 311 adults prescribed with tigecycline from 2018 to 2020. The primary cohort and validation cohort were constructed by dividing the participants in a ratio of 7:3. The endpoint is tigecycline-related coagulopathy, defined as a condition with no abnormality in coagulation prior to tigecycline application but developed the following symptoms upon prescription: activated partial thromboplastin time (APTT) extended by >10 s than the upper limit of normal (ULN), prothrombin time (PT) prolonged for >3 s than the ULN or reduced serum level of fibrinogen to <2.0 g/L. A predictive nomogram based on logistic regression was subsequently constructed. Results: Tigecycline intake for over 7 days, combined other antibiotics, initial PT, initial fibrinogen and estimated glomerular filtration rate (eGFR), are independent prognostic factors of tigecycline-related coagulopathy. The primary and validation cohort each has an area under the receiver operating characteristic curve (AUC) of 0.792 (0.732-0.851) and 0.730 (0.629-0.832) for nomogram, respectively. Furthermore, the fitted calibration curve illustrated adequate fit of the model, while the decision curve analysis demonstrated good clinical value. Survival curves showed a high mortality rate among patients with tigecycline-related coagulopathy. Conclusion: This nomogram exhibited helpful clinical value in predicting tigecycline-related coagulopathy that could reduce the high mortality rate of patients prescribed with tigecycline.

Effect of one-time high load exercise on skeletal muscle injury in rats of different genders: oxidative stress and mitochondrial responses.

PURPOSE: To evaluate the impact of one-time high load exercise on skeletal muscle injury and analysis its mechanism in different genders. METHODS: Twenty-four male and 24 female rats were divided randomly into four groups respectively: control, 0 h, 6 h, and 24 h after exercise. The activities of creatine kinase (CK), lactate dehydrogenase (LDH), and myohemoglobin (MYO) in serum, the expression level of oxidative stress markers, mitochondrial respiratory chain complex enzyme, and the apoptosis related protein in quadriceps were detected. RESULTS: The results showed that the activities of CK, LDH and MYO in serum increased immediately after exercise and restored faster in female rats. More obvious structural disorder and apoptosis in male rats were showed. Malondialdehyde (MDA) and superoxide dismutase (SOD) were increased while catalase (CAT) and glutathione (GSH) were decreased in male rats. SOD, CAT and GSH were increased in female rats. Mitochondrial complex enzyme activity was decreased in males and increased in females. CONCLUSIONS: The skeletal muscle injury in both genders of rat could be induced by one-time high load exercise due to the mitochondrial respiratory enzyme dysfunction and oxidative stress, which was relatively mild and recovered quicker in female rats.

Synergistic chemo-/photothermal therapy based on supercritical technology-assisted chitosan-indocyanine green/luteolin nanocomposites for wound healing.

Despite the success, it is highly challenging to battle against pathogenic biofilms-based chronic bacterial infections by conventional antibiotic therapy. Herein, we report a near-infrared (NIR)/acid-induced nanoplatform based on chitosan (CS)-coated indocyanine green (ICG, photosensitizer)/luteolin (LUT, a natural quorum sensing inhibitor) nanocomposites (ICG/LUT-CS) as antibacterial and antibiofilm agents for skin wound healing. Initially, the ICG/LUT nanoplatforms are prepared by the supercritical antisolvent technology and coated with the CS layer. The obtained ICG/LUT-CS with ultra-high encapsulation efficiency exhibited more favorable photothermal conversion effects and improved NIR laser/acid dual-induced drug release behavior than individual modalities, achieving exceptional bacteria-killing and biofilm elimination effects. Moreover, the ICG/LUT-CS realized the synergetic effects of chemotherapy and photothermal therapy outcomes for wound healing. Together, our findings provided an appealing strategy for the rapid preparation and future translational application of ICG/LUT-CS as an ideal agent for fighting against biofilm infections.

The Mediating Role of Alexithymia: Social Support and Depression among Colorectal Cancer Patients.

Purpose: The purpose of this study was to investigate the relationship among depression, alexithymia, and social support and examine the main influence factors of depression in patients with colorectal cancer (CRC). In addition, the mediating role of alexithymia between social support and depression was analyzed. Methods: Patients with CRC were recruited in two tertiary hospitals in Changchun via a convenience sampling method. All survivors were asked to complete self-report questionnaires assessing medical and demographic variables, depression, alexithymia, and social support. Results: A total of 183 patients with CRC were included. The results showed that education level and family monthly income were the main factors affecting depression patients with in CRC. Alexithymia was positively correlated with depression (r = 0.389, P < 0.01). Social support was negatively correlated with alexithymia (r = -0.322, P < 0.01) and depression (r = -0.316, P < 0.01). Moreover, alexithmia partially mediated the relationship between social support and depression, and the ratio of mediating effect with total effect was 23.82%. Conclusions: To sum up, there is a correlation between depression, social support, and alexithymia in patients with CRC; alexithymia plays a partially intermediary role in the impact of social support on depression. Our findings remind clinicians to treat the depression of patients with CRC from multiple perspectives, such as by increasing social support and reducing alexithymia.

Evaluation of oocyte maturity using artificial intelligence quantification of follicle volume biomarker by three-dimensional ultrasound.

RESEARCH QUESTION: Can a novel deep learning-based follicle volume biomarker using three-dimensional ultrasound (3D-US) be established to aid in the assessment of oocyte maturity, timing of HCG administration and the individual prediction of ovarian hyper-response? DESIGN: A total of 515 IVF cases were enrolled, and 3D-US scanning was carried out on HCG administration day. A follicle volume biomarker established by means of a deep learning-based segmentation algorithm was used to calculate optimal leading follicle volume for predicting number of mature oocytes retrieved and optimizing HCG trigger timing. Performance of the novel biomarker cut-off value was compared with conventional two-dimensional ultrasound (2D-US) follicular diameter measurements in assessing oocyte retrieval outcome. Moreover, demographics, infertility work-up and ultrasound biomarkers were used to build models for predicting ovarian hyper-response. RESULTS: On the basis of the deep learning method, the optimal cut-off value of the follicle volume biomarker was determined to be 0.5 cm3 for predicting number of mature oocytes retrieved; its performance was significantly better than the conventional method (two-dimensional diameter measurement ≥10 mm). The cut-off value for leading follicle volume to optimize HCG trigger timing was determined to be 3.0 cm3 and was significantly associated with a higher number of mature oocytes retrieved (P = 0.01). Accuracy of the multi-layer perceptron model was better than two-dimensional diameter measurement (0.890 versus 0.785) and other multivariate classifiers in predicting ovarian hyper-response (P < 0.001). CONCLUSIONS: Deep learning segmentation methods and multivariate classifiers based on 3D-US were found to be potentially effective approaches for assessing mature oocyte retrieval outcome and individual prediction of ovarian hyper-response.

Protective effect of low-dose radiation on doxorubicin-induced brain injury in mice.

BACKGROUND: To investigate the protective effect of low-dose radiation (LDR) on brain injury in mice induced by doxorubicin (DOX). METHODS: Sixty female BALB/C mice were randomly divided into the control (CTR) group, low-dose radiation (LDR) group, doxorubicin treatment (DOX) group and low-dose radiation before doxorubicin treatment (COM) group. After 72 h of exposure to 75 mGy, the mice were intraperitoneally injected with 7.5 mg/kg of doxorubicin and sacrificed 5 days later. Neuron-specific enolase (NSE), lactate dehydrogenase (LDH), adenosine triphosphate (ATP), neurotransmitters, inflammatory mediators, apoptosis- and oxidative stress-related mediators as well as mitochondrial dysfunction were examined. RESULTS: Compared to the DOX group, the concentrations of DA, 5-HT, EPI and GABA in the COM group were significantly decreased, and the number of TUNEL-positive cells was decreased. In addition, the expression of proapoptotic proteins was downregulated in the COM group compared to the DOX group. Low-dose radiation in advance reduced reactive oxygen species and activated the SOD antioxidant defense system as indicated by significantly reduced GSH expression, increased GSSG expression, increased GPx expression and activation of the Nrf2 redox pathway. After low-dose radiation, the expression levels of ATP5f1, NDUFV1 and CYC1 were close to normal, and the mitochondrial respiratory control rate (RCR) and activity of respiratory chain complex enzymes also tended to be normal. Low-dose radiation upregulated the expression levels of IL-2 and IL-4 but downregulated the expression levels of IL-10 and TGF-ß. CONCLUSION: LDR has a protective effect on brain injury in mice treated with DOX. The mechanism is related to LDR alleviating mitochondrial dysfunction and oxidative stress, which promotes the production of antioxidant damage proteins, thus exerting an adaptive protective effect on cells.

3D Printing of Ultrathin MXene toward Tough and Thermally Resistant Nanocomposites.

Liquid crystal display (LCD)-based 3D printing, a facile and cost-effective manufacturing technique, is often applied when fabricating objects with porcelain structures using photosensitive resins (PSRs). Currently, 3D printed constructions are typically used as models for demonstration purposes rather than industrial applications because of their poor performance. In this study, we prepared nanocomposites by incorporating Ti3C2 MXene nanosheets to enhance the overall characteristics of a PSR, including mechanical properties and thermal resistance. Notably, the designed nanocomposites showed optimum performance at an MXene loading of 0.5% w/w. The mechanical properties of the designed nanocomposites confirmed the enhanced ultimate tensile and flexural strengths (by 32.1% and 42.7%, respectively), at 0.5% w/w MXene loading. Moreover, the incorporated MXene presented no substantial influence on the toughness of the PSR. The glass transition and thermal degradation temperatures at 5% weight loss increased by 7.4 and 10.6 °C, respectively, resulting predominantly from the hydrogen bonding between the PSR and MXene. Together, the experimental results indicate that the designed PSR/MXene nanocomposites are expected to replace pristine resins for LCD printing in various practical applications.

Colchicine Inhibits NETs and Alleviates Cardiac Remodeling after Acute Myocardial Infarction.

PURPOSE: Colchicine, a multipotent anti-inflammatory drug, has been reported to alleviate cardiac remodeling and improve cardiac function after acute myocardial infarction (AMI). However, the underlying mechanism remains incompletely understood. Because neutrophils extracellular traps (NETs) enhance inflammation and participate in myocardial ischemia injury, and colchicine can inhibit NETosis, we thus aimed to determine whether colchicine exerts cardioprotective effects on AMI via suppressing NETs. METHODS: Adult C57BL/6 mice were subjected to permanent ligation of the left anterior descending coronary artery and treated with colchicine (0.1 mg/kg/day) or Cl-amidine (10 mg/kg/day) for 7 or 28 days after AMI. Cardiac function was evaluated by echocardiography, and NETs detected by immunofluorescence. ROS production was detected using 2',7'-dichlorodihydrofluorescein diacetates (DCFH-DA) fluorometry. Intracellular Ca2+ concentration was assessed by a fluorometric ratio technique. RESULTS: We found that colchicine treatment significantly increased mice survival (89.8% in the colchicine group versus 67.9% in control, n = 32 per group; log-rank test, p < 0.05) and improved cardiac function at day 7 (left ventricular ejection fraction (LVEF): 28.0 ± 9.2% versus 12.6 ± 3.9%, n = 8 per group; p < 0.001) and at day 28 (LVEF: 26.2 ± 7.2% versus 14.8 ± 6.7%, n = 8 per group; p < 0.001) post-AMI. In addition, the administration of colchicine inhibited NETs formation and inflammation. Furthermore, colchicine inhibited NETs formation by reducing NOX2/ROS production and Ca2+ influx. Moreover, prevention of NETs formation with Cl-amidine significantly alleviated AMI-induced cardiac remodeling. CONCLUSIONS: Colchicine inhibited NETs and cardiac inflammation, and alleviated cardiac remodeling after acute myocardial infarction.

A LASSO-derived clinical score to predict severe acute kidney injury in the cardiac surgery recovery unit: a large retrospective cohort study using the MIMIC database.

OBJECTIVES: We aimed to develop an effective tool for predicting severe acute kidney injury (AKI) in patients admitted to the cardiac surgery recovery unit (CSRU). DESIGN: A retrospective cohort study. SETTING: Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database, consisting of critically ill participants between 2001 and 2012 in the USA. PARTICIPANTS: A total of 6271 patients admitted to the CSRU were enrolled from the MIMIC-III database. PRIMARY AND SECONDARY OUTCOME: Stages 2-3 AKI. RESULT: As identified by least absolute shrinkage and selection operator (LASSO) and logistic regression, risk factors for AKI included age, sex, weight, respiratory rate, systolic blood pressure, diastolic blood pressure, central venous pressure, urine output, partial pressure of oxygen, sedative use, furosemide use, atrial fibrillation, congestive heart failure and left heart catheterisation, all of which were used to establish a clinical score. The areas under the receiver operating characteristic curve of the model were 0.779 (95% CI: 0.766 to 0.793) for the primary cohort and 0.778 (95% CI: 0.757 to 0.799) for the validation cohort. The calibration curves showed good agreement between the predictions and observations. Decision curve analysis demonstrated that the model could achieve a net benefit. CONCLUSION: A clinical score built by using LASSO regression and logistic regression to screen multiple clinical risk factors was established to estimate the probability of severe AKI in CSRU patients. This may be an intuitive and practical tool for severe AKI prediction in the CSRU.

Effects of Remotely Supervised Physical Activity on Health Profile in Frail Older Adults: A Randomized Controlled Trial Protocol.

Background: Frailty is considered a major public health challenge of the 21st century, characterized by the decline of multiform body functions. Physical activity may be the most effective intervention to delay frailty. This study aims to verify the effect of remotely supervised physical activity on health profile in community-dwelling frail older adults. Design: This is a multicenter, three-blind, two-arm, and cohort randomized controlled study. Methods: The intelligent exercise rehabilitation management system (IERMS) is an integrated digital platform that involves evaluation, guidance, monitoring, and feedback. A total of 120 participants aged ≥ 65 years and diagnosed as frailty on the FRAIL scale will be recruited and randomly divided into two groups. Group 1 will receive a 12-week IERMS-based intervention, and Group 2 will receive the usual care. Data will be collected at baseline, 12 and 24 weeks. The primary outcome is the physical function, and secondary outcomes include gait parameters, psychology, and cognition measurements. Analyses will be performed using DSS statistics, version 25. P < 0.05 will be considered statistically significant. Conclusion: We believe that intervention plays a positive role in delaying the frailty. If our program is effective, we will provide a viable means to promote healthy aging in primary healthcare. Trial registration number: ChiCTR2100052286; Pre-results.