A novel real-time model for predicting acute kidney injury in critically ill patients within 12 hours.

BACKGROUND: A major challenge in prevention and early treatment of acute kidney injury (AKI) is the lack of high-performance predictors in critically ill patients. Therefore, we innovatively constructed U-AKIpredTM for predicting AKI in critically ill patients within 12 h of panel measurement. METHODS: The prospective cohort study included 680 patients in the training set and 249 patients in the validation set. After performing inclusion and exclusion criteria, 417 patients were enrolled in the training set and 164 patients were enrolled in the validation set finally. AKI was diagnosed by Kidney Disease Improving Global Outcomes (KDIGO) criteria. RESULTS: Twelve urinary kidney injury biomarkers (mALB, IgG, TRF, α1MG, NAG, NGAL, KIM-1, L-FABP, TIMP2, IGFBP7, CAF22 and IL-18) exhibited good predictive performance for AKI within 12 h in critically ill patients. U-AKIpredTM, combined with three crucial biomarkers (α1MG, L-FABP and IGFBP7) by multivariate logistic regression analysis, exhibited better predictive performance for AKI in critically ill patients within 12 h than the other twelve kidney injury biomarkers. The area under the curve (AUC) of the U-AKIpredTM, as a predictor of AKI within 12 h, was 0.802 (95% CI: 0.771-0.833, P < 0.001) in the training set and 0.844 (95% CI: 0.792-0.896, P < 0.001) in validation cohort. A nomogram based on the results of the training and validation sets of U-AKIpredTM was developed which showed optimal predictive performance for AKI. The fitting effect and prediction accuracy of U-AKIpredTM was evaluated by multiple statistical indicators. To provide a more flexible predictive tool, the dynamic nomogram (https://www.xsmartanalysis.com/model/U-AKIpredTM) was constructed using a web-calculator. Decision curve analysis (DCA) and a clinical impact curve were used to reveal that U-AKIpredTM with the three crucial biomarkers had a higher net benefit than these twelve kidney injury biomarkers respectively. The net reclassification index (NRI) and integrated discrimination index (IDI) were used to improve the significant risk reclassification of AKI compared with the 12 kidney injury biomarkers. The predictive efficiency of U-AKIpredTM was better than the NephroCheck® when testing for AKI and severe AKI. CONCLUSION: U-AKIpredTM is an excellent predictive model of AKI in critically ill patients within 12 h and would assist clinicians in identifying those at high risk of AKI.

Motor-sparing peripatellar plexus block provides noninferior block duration and complete block area of the peripatellar region compared with femoral nerve block: a randomized, controlled, noninferiority study.

BACKGROUND: Developing adequate regional anaesthesia for knee surgeries without affecting lower limb mobilization is crucial to perioperative analgesia. However, reports in this regard are limited. We proposed a technique for ultrasound-guided peripatellar plexus (PP) block. Compared with the femoral nerve (FN) block, we hypothesized that this technique would provide a noninferior block duration and a complete cutaneous sensory block in the peripatellar region without affecting lower limb mobilization. An investigation was conducted to verify our hypothesis in cadavers and volunteers. METHODS: The study was designed in two parts. First, eight cadaveric lower limbs were dissected to verify the feasibility of PP block after methylene blue injection under ultrasound. Second, using a noninferiority study design, 50 healthy volunteers were randomized to receive either a PP block (PP group) or an FN block (FN group). The primary outcome was the duration of peripatellar cutaneous sensory block, with the prespecified noninferiority margin of -3.08 h; the secondary outcome was the area of peripatellar cutaneous sensory block; in addition, the number of complete anaesthesias of the incision line for total knee arthroplasty and the Bromage score 30 min after block were recorded. RESULTS: The PP was successfully dyed, whereas the FN and saphenous nerve were unstained in all cadaveric limbs. The mean difference of the block duration between the two groups was - 1.24 (95% CI, -2.81 - 0.33) h, and the lower boundary of the two-sided 95% CI was higher than the prespecified noninferiority margin (Pnoninferiority = 0.023), confirming the noninferiority of our technique over FN block. The cutaneous sensory loss covered the entire peripatellar region in the PP group. PP block achieved complete anaesthesia of the incision line used for total knee arthroplasty and a Bromage score of 0 in 25 volunteers, which differed significantly from that of volunteers who underwent FN block. CONCLUSION: Ultrasound-guided PP block is a feasible technique. Compared with FN block, PP block provides noninferior block duration and complete blocking of the peripatellar region without affecting lower limb mobilization. TRIAL REGISTRATION: This study was registered in the Chinese Clinical Trial Register (registration no. ChiCTR2000041547, registration date 28/12/2020).

Sleep characteristics and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in cognitively intact older adults: The CABLE study.

INTRODUCTION: This study tested the self-reported sleep characteristics associated with cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers in cognitively intact older adults. METHODS: The linear and non-linear regression analyses were conducted in 736 cognitively normal participants (mean [standard deviation; SD] age, 62.3 [10.5] years, range 40 to 88 years, 59% female) who had measurements of cerebrospinal fluid (CSF) amyloid beta (Aß) and tTau proteins and sleep characteristics, after adjusting for age, gender, education, apolipoprotein E gene (APOE) ε4 status, and general cognition. RESULTS: Greater daytime sleepiness was associated with higher CSF indicators of amyloid deposition in female patients. No significant associations were revealed for CSF tTau proteins after Bonferroni correction. A U-shaped relationship was revealed for nocturnal sleep habits, such that those with insufficient or excessive nocturnal sleep duration had greater CSF biomarkers of amyloid deposition (the reflection range: bedtime: around 10:00 p.m. and sleep duration: 6.0 to 6.5 hours). DISCUSSION: These findings consolidated the close relationship between sleep and AD.

Novel lumbar plexus block versus femoral nerve block for analgesia and motor recovery after total knee arthroplasty.

This study aimed to compare the postoperative analgesic efficacy and motor recovery of a novel lumbar plexus block (LPB) with that of a femoral nerve block (FNB) after total knee arthroplasty (TKA). Forty patients who underwent TKA were randomised equally into an lumbar plexus and sciatic nerve (LS) group (receiving novel LPB) and an femoral and sciatic nerves (FS) group (receiving FNB). The assessed variables were the onset time of pain, time to the first analgesic request, pain scores, motor block at 6, 12, and 24 h after TKA, and the number of patients receiving successful blockade for each branch of the lumbar plexus. In the LS group, the femoral, lateral femoral cutaneous, genitofemoral, iliohypogastric, ilioinguinal, and obturator nerves were blocked in 18, 20, 16, 18, 15, and 19 patients. Compared to the FS group, the LS group had a significantly shorter onset time of pain and time to the first analgesic request, a significantly larger total postoperative dose of sufentanil, significantly higher numeric rating scale scores for both rest and dynamic pain at 6, 12, and 24 h, and faster motor recovery. Novel ultrasound-guided LPB has a high blocking success rate and provides inferior postoperative analgesia, but faster motor recovery after TKA than FNB.

AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study.

BACKGROUND: Early recognition and timely intervention for AKI in critically ill patients were crucial to reduce morbidity and mortality. This study aimed to use biomarkers to construct a optimal machine learning model for early prediction of AKI in critically ill patients within seven days. METHODS: The prospective cohort study enrolled 929 patients altogether who were admitted in ICU including 680 patients in training set (Jiefang Campus) and 249 patients in external testing set (Binjiang Campus). After performing strict inclusion and exclusion criteria, 421 patients were selected in training set for constructing predictive model and 167 patients were selected in external testing for evaluating the predictive performance of resulting model. Urine and blood samples were collected for kidney injury associated biomarkers detection. Baseline clinical information and laboratory data of the study participants were collected. We determined the average prediction efficiency of six machine learning models through 10-fold cross validation. RESULTS: In total, 78 variables were collected when admission in ICU and 43 variables were statistically significant between AKI and non-AKI cohort. Then, 35 variables were selected as independent features for AKI by univariate logistic regression. Spearman correlation analysis was used to remove two highly correlated variables. Three ranking methods were used to explore the influence of 33 variables for further determining the best combination of variables. The gini importance ranking method was found to be applicable for variables filtering. The predictive performance of AKIMLpred which constructed by the XGBoost algorithm was the best among six machine learning models. When the AKIMLpred included the nine features (NGAL, IGFBP7, sCysC, CAF22, KIM-1, NT-proBNP, IL-6, IL-18 and L-FABP) with the highest influence ranking, its model had the best prediction performance, with an AUC of 0.881 and an accuracy of 0.815 in training set, similarly, with an AUC of 0.889 and an accuracy of 0.846 in validation set. Moreover, the performace was slightly outperformed in testing set with an AUC of 0.902 and an accuracy of 0.846. The SHAP algorithm was used to interpret the prediction results of AKIMLpred. The web-calculator of AKIMLpred was shown for predicting AKI with more convenient(https://www.xsmartanalysis.com/model/list/predict/model/html?mid=8065&symbol=11gk693982SU6AE1ms21). AKIMLpred was better than the optimal model built with only routine tests for predicting AKI in critically ill patients within 7 days. CONCLUSION: The model AKIMLpred constructed by the XGBoost algorithm with selecting the nine most influential biomarkers in the gini importance ranking method had the best performance in predicting AKI in critically ill patients within 7 days. This data-driven predictive model will help clinicians to make quick and accurate diagnosis.

STX16 exon 5-7 deletion in a patient with pseudohypoparathyroidism type 1B.

OBJECTIVES: Pseudohypoparathyroidism (PHP) comprises a cluster of heterogeneous diseases characterized by hypocalcemia and hyperphosphatemia due to parathyroid hormone (PTH) resistance. PHP type 1B (PHP1B) is caused by heterozygous maternal deletions within GNAS or STX16. STX16 exon 2-6 deletion is commonly observed in autosomal dominant (AD)-PHP1B, while sporadic PHP1B commonly results from methylation abnormalities of maternal differentially methylated regions and remains unclear at the molecular level. CASE PRESENTATION: A 39-year-old male patient with PHP1B, who had his first seizure at 15 years of age, presented to our hospital. The methylation-specific multiplex ligation-dependent probe amplification results showed a half-reduced copy number of STX16 exon 5-7 and loss of methylation at GNAS exon A/B. His mother also had a half-reduced copy number of STX16 exon 5-7 but with normal methylation of GNAS. His father has a normal copy number of STX16 and normal methylation of GNAS. CONCLUSIONS: For the recognition and early diagnosis of this kind of disease, here we report the clinical symptoms, auxiliary examinations, genetic testing characteristics, and treatment of the patient.

Re-evaluating the asymmetric economic policy uncertainty, conventional energy, and renewable energy consumption nexus for BRICS.

Economic policy uncertainty has increased throughout the world since the previous few decades. Moreover, economic policy uncertainty significantly influences economic activities that may also produce a strong effect on energy consumption. The objective of the study is to investigate the effect of economic policy uncertainty on renewable and non-renewable energy consumption in the case of BRICS countries, for the period 1991-2019. The outcome of the panel NARDL-PMG modeling technique demonstrates that a positive shock in economic policy uncertainty exerts a negative impact on renewable energy consumption and positive impact on non-renewable energy consumption in the short-run and long-run. However, a negative shock in economic policy uncertainty has a positive impact on renewable energy consumption and negative impact on non-renewable energy consumption in the long run, while this effect becomes statistically insignificant in the short run. Numerical elements of long-run results infer that economic policy uncertainty is more influence on renewable energy compared to non-renewable energy consumption in BRICS in long run. On the basis of findings, the study suggests that the authorities should launch such programs that result in shrinking uncertainties linked with economic policy.

Identification and Validation of Three Hub Genes Involved in Cell Proliferation and Prognosis of Castration-Resistant Prostate Cancer.

Background: The acquisition of castration resistance is lethal and inevitable in most prostate cancer patients under hormone therapy. However, effective biomarkers and therapeutic targets for castration-resistant prostate cancer remain to be defined. Methods: Comprehensive bioinformatics tools were used to screen hub genes in castration-resistant prostate cancer and were verified in androgen-dependent prostate cancer and castration-resistant prostate cancer in TCGA and the SU2C/PCF Dream Team database, respectively. Gene set enrichment analysis and in vitro experiments were performed to determine the potential functions of hub genes involved in castration-resistant prostate cancer progression. Results: Three hub genes were screened out by bioinformatics analysis: MCM4, CENPI, and KNTC1. These hub genes were upregulated in castration-resistant prostate cancer and showed high diagnostic and prognostic value. Moreover, the expression levels of the hub genes were positively correlated with neuroendocrine prostate cancer scores, which represent the degree of castration-resistant prostate cancer aggression. Meanwhile, in vitro experiments confirmed that hub gene expression was increased in castration-resistant prostate cancer cell lines and that inhibition of hub genes hindered cell cycle transition, resulting in suppression of castration-resistant prostate cancer cell proliferation, which confirmed the gene set enrichment analysis results. Conclusions: MCM4, CENPI, and KNTC1 could serve as candidate diagnostic and prognostic biomarkers of castration-resistant prostate cancer and may provide potential preventive and therapeutic targets.

Research on China's embodied carbon import and export trade from the perspective of value-added trade.

The development of globalization has separated the production and consumption of products spatially, and the international trade of products has become a carrier of embodied carbon trade. This paper adopted the perspective of value-added trade to calculate the amount of embodied carbon trade of China from 2006 to 2015 and perform a structural decomposition analysis of the changes in China's embodied carbon trade. This study found that: (1) China's embodied carbon exports are much larger than its embodied carbon imports, and there are differences between countries. China imported the largest amount of embodied carbon from South Korea, and it exported the largest amount of embodied carbon to the United States. (2) The structural decomposition analysis shows that changes in the value-added carbon emission coefficient during the study period would have caused China's embodied carbon trade to decrease, and changes in value-added trade would have caused China's embodied carbon trade to increase. Therefore, countries trading with China need to strengthen their cooperation with China in energy conservation, emission reduction, and product trade. In order to accurately reflect China's embodied carbon trade, it is necessary to calculate embodied carbon trade from the perspective of value-added trade.

Effects of propofol on sleep architecture and sleep-wake systems in rats.

Previous studies have shown that the synchronization of electroencephalogram (EEG) signals is found during propofol-induced general anesthesia, which is similar to that of slow-wave sleep (SWS). However, a complete understanding is lacking in terms of the characteristics of EEG changes in rats after propofol administration and whether propofol acts through natural sleep circuits. Here, we examined the characteristics of EEG patterns induced by intraperitoneal injection of propofol in rats. We found that high (10 mg/kg) and medium (5 mg/kg) doses of propofol induced a cortical EEG of low-frequency, high-amplitude activity with rare electromyographic activity and markedly shortened sleep latency. The high dose of propofol increased deep slow-wave sleep (SWS2) to 4 h, as well as the number of large SWS2 bouts (>480 s), their mean duration and the peak of the power density curve in the delta range of 0.75-3.25 Hz. After the medium dose of propofol, the total number of wakefulness, light slow-wave sleep (SWS1) and SWS2 episodes increased, whereas the mean duration of wakefulness decreased. The high dose of propofol significantly increased c-fos expression in the ventrolateral preoptic nucleus (VLPO) sleep center and decreased the number of c-fos-immunoreactive neurons in wake-related systems including the tuberomammillary nucleus (TMN), perifornical nucleus (PeF), lateral hypothalamic nucleus (LH), ventrolateral periaqueductal gray (vPAG) and supramammillary region (SuM). These results indicated that the high dose of propofol produced high-quality sleep by increasing SWS2, whereas the medium dose produced fragmented and low-quality sleep by disrupting the continuity of wakefulness. Furthermore, sleep-promoting effects of propofol are correlated with activation of the VLPO cluster and inhibition of the TMN, PeF, LH, vPAG and SuM.

NLRP3 inflammasome activation mediates sleep deprivation-induced pyroptosis in mice.

BACKGROUND: Sleep deprivation (SD) has many deleterious health effects, including cognitive decline, work ability decline, inadequate alertness, etc. Neuroinflammation plays an important role in sleep deprivation. However, the underlying mechanism is still unclear. METHODS: In the present study, we detected the activation of microglia and apoptosis of nerve cells in sleep deprivation (SD) mice model using IHC, HE staining and TUNEL apoptosis assay. RT-PCR array data were used to detect the expression of inflammatory bodies in hippocampal CA1 region after sleep deprivation, to explore how NLRP3 inflammasome regulates neuronal apoptosis and how specific signaling pathways are involved in SD-induced activation of NLRP3/pyrosis axis. RESULTS: We found the number of microglia significantly increased in SD mice, while this effect was blocked by sleep recovery. RT-PCR array data suggested that NLRP3 inflammasome, but not other inflammasomes, was obviously increased in hippocampus CA1 region after sleep deprivation. Mechanistically, we found that NLRP3 mediated the pyroptosis of neurocyte through GSDMD-dependent way , and P38 and ERK-MAPK signaling pathway is involved in SD-induced activation of NLRP3/pyroptosis axis. All these results suggested that MAPK/NLRP3 axis mediated SD-induced pyroptosis. CONCLUSION: NLRP3 plays an important role in SD-induced neuroinflammation. Thus, NLRP3 inflammasome is expected to be a potential therapeutic target for SD-induced neuroinflammation.

Identification of key sectors of water resource utilization in China from the perspective of water footprint.

We identified the key sectors of water resource use in China from the perspective of the water footprint to improve the use of water resources. The empirical results showed that there were six key sectors (including Crop Cultivation; Forestry; Livestock and Livestock Products; Fishery, Technical Services for Agriculture, Forestry, Livestock and Fishing; Other Food Products, and Scrap and Waste) for water consumption in China in 2015.We analyzed the use of green water, blue water, and grey water. These six sectors accounted for 66.15% of the total impact and 90.76% of the direct impact. Seven key sectors (the six sectors above plus Steel Processing)for the consumption of blue water in China can explain 59.70% of the total impact and 86.94% of the direct effect in 2015. Eight key sectors (Crop cultivation, Other food products, Scrap and Waste, Railway Freight Transport, Highway Freight and Passengers Transport, Water Freight and Passengers Transport, Pipeline Transport, and Health Services) responsible for the consumption of grey water in China in 2015 can explain 81.28% of the total impact and 95.73% of the direct impact. Therefore, the Chinese government should focus on the departments that manage water resources in these sectors when designing water-saving policies and improving water-use efficiency, such as promoting water-saving irrigation technology (including sprinkler irrigation and drip irrigation) in the agricultural sector.

Morphine inhibits sleep-promoting neurons in the ventrolateral preoptic area via mu receptors and induces wakefulness in rats.

Morphine is the most efficacious and widely prescribed treatment for pain. However, it decreases the total amount of deep sleep and rapid eye movement sleep in humans. Acute morphine administration at low doses causes wakefulness in animal models. To clarify the mechanism by which morphine affects sleep-wake behavior, we investigated the effects of morphine on the sleep-promoting neurons of the ventrolateral preoptic area (VLPO), a putative sleep-active nucleus, using in vitro brain slices by the patch-clamp technique. We also examined the effects of morphine on sleep-wake profiles after administration of opioid receptor antagonist to the VLPO using EEG and electromyogram recordings in freely moving rats. The results showed that morphine inhibited the firing rate of sleep-promoting neurons and hyperpolarized their membrane potentials without affecting interneurons in the VLPO. Morphine-induced hyperpolarization of membrane potentials could be reversed by, D-Phe-Cys-Thr-D-Trp-Orn-Thr-Pen-Thr-NH2 (CTOP), a mu receptor antagonist, in the presence of tetrodotoxin. However, after the mu receptors were blocked by CTOP, morphine still suppressed the firing of the sleep-promoting neurons. This effect was antagonized by nor-BIN, a kappa receptor antagonist. Activation of kappa receptor by U50488H inhibited the firing of the sleep-promoting neurons. These results indicate that morphine could inhibit the activity of sleep-promoting neurons in the VLPO through mu and kappa receptors. EEG recordings revealed that morphine injected subcutaneously induced arousal in a dose-dependent manner. CTOP microinjected into VLPO antagonized the arousal effects of morphine, but nor-BIN did not. However, CTOP alone was not associated with any changes in the physiological sleep-wake cycle. Taken together, these findings clearly indicate that morphine inhibits sleep-promoting neurons in the VLPO by affecting mu receptors and so induces wakefulness in rats.

Honokiol promotes non-rapid eye movement sleep via the benzodiazepine site of the GABA(A) receptor in mice.

BACKGROUND AND PURPOSE: Decoctions of the Chinese herb houpu contain honokiol and are used to treat a variety of mental disorders, including depression. Depression commonly presents alongside sleep disorders and sleep disturbances, which appear to be a major risk factor for depression. Here, we have evaluated the somnogenic effect of honokiol and the mechanisms involved. EXPERIMENTAL APPROACH: Honokiol was administered i.p. at 20:00 h in mice. Flumazenil, an antagonist at the benzodiazepine site of the GABA(A) receptor, was administered i.p. 15 min before honokiol. The effects of honokiol were measured by EEG and electromyogram (EMG), c-Fos expression and in vitro electrophysiology. KEY RESULTS: Honokiol (10 and 20 mg·kg⁻¹) significantly shortened the sleep latency to non-rapid eye movement (non-REM, NREM) sleep and increased the amount of NREM sleep. Honokiol increased the number of state transitions from wakefulness to NREM sleep and, subsequently, from NREM sleep to wakefulness. However, honokiol had no effect on either the amount of REM sleep or EEG power density of both NREM and REM sleep. Honokiol increased c-Fos expression in ventrolateral preoptic area (VLPO) neurons, as examined by immunostaining, and excited sleep-promoting neurons in the VLPO by whole-cell patch clamping in the brain slice. Pretreatment with flumazenil abolished the somnogenic effects and activation of the VLPO neurons by honokiol. CONCLUSION AND IMPLICATIONS: Honokiol promoted NREM sleep by modulating the benzodiazepine site of the GABA(A) receptor, suggesting potential applications in the treatment of insomnia, especially for patients who experience difficulty in falling and staying asleep.