The relationship between Geriatric Nutritional Risk Index (GNRI) and in-hospital mortality in critically ill patients with Acute Kidney Injury (AKI).

BACKGROUND: The role of the geriatric nutritional risk index (GNRI) as a prognostic factor in intensive care unit (ICU) patients with acute kidney injury (AKI) remains uncertain. OBJECTIVES: The aim of this study was to investigate the impact of the GNRI on mortality outcomes in critically ill patients with AKI. METHODS: For this retrospective study, we included 12,058 patients who were diagnosed with AKI based on ICD-9 codes from the eICU Collaborative Research Database. Based on the values of GNRI, nutrition-related risks were categorized into four groups: major risk (GNRI < 82), moderate risk (82 ≤ GNRI < 92), low risk (92 ≤ GNRI < 98), and no risk (GNRI ≥ 98). Multivariate analysis was used to evaluate the relationship between GNRI and outcomes. RESULTS: Patients with higher nutrition-related risk tended to be older, female, had lower blood pressure, lower body mass index, and more comorbidities. Multivariate analysis showed GNRI scores were associated with in-hospital mortality. (Major risk vs. No risk: OR, 95% CI: 1.90, 1.54-2.33, P < 0.001, P for trend < 0.001). Moreover, increased nutrition-related risk was negatively associated with the length of hospital stay (Coefficient: -0.033; P < 0.001) and the length of ICU stay (Coefficient: -0.108; P < 0.001). The association between GNRI scores and the risks of in-hospital mortality was consistent in all subgroups. CONCLUSIONS: GNRI serves as a significant nutrition assessment tool that is pivotal to predicting the prognosis of critically ill patients with AKI.

Efficacy and Safety of Early Treatment with Glibenclamide in Patients with Aneurysmal Subarachnoid Hemorrhage: A Randomized Controlled Trial.

BACKGROUND: This study aims to investigate the efficacy and safety of glibenclamide treatment in patients with acute aneurysmal subarachnoid hemorrhage (aSAH). METHODS: The randomized controlled trial was conducted from October 2021 to May 2023 at two university-affiliated hospitals in Beijing, China. The study included patients with aSAH within 48 h of onset, of whom were divided into the intervention group and the control group according to the random number table method. Patients in the intervention group received glibenclamide tablet 3.75 mg/day for 7 days. The primary end points were the levels of serum neuron-specific enolase (NSE) and soluble protein 100B (S100B) between the two groups. Secondary end points included evaluating changes in the midline shift and the gray matter-white matter ratio, as well as assessing the modified Rankin Scale scores during follow-up. The trial was registered at ClinicalTrials.gov (identifier NCT05137678). RESULTS: A total of 111 study participants completed the study. The median age was 55 years, and 52% were women. The mean admission Glasgow Coma Scale was 10, and 58% of the Hunt-Hess grades were no less than grade III. The baseline characteristics of the two groups were similar. On days 3 and 7, there were no statistically significant differences observed in serum NSE and S100B levels between the two groups (P > 0.05). The computer tomography (CT) values of gray matter and white matter in the basal ganglia were low on admission, indicating early brain edema. However, there were no significant differences found in midline shift and gray matter-white matter ratio (P > 0.05) between the two groups. More than half of the patients had a beneficial outcome (modified Rankin Scale scores 0-2), and there were no statistically significant differences between the two groups. The incidence of hypoglycemia in the two groups were 4% and 9%, respectively (P = 0.439). CONCLUSIONS: Treating patients with early aSAH with oral glibenclamide did not decrease levels of serum NSE and S100B and did not improve the poor 90-day neurological outcome. In the intervention group, there was a visible decreasing trend in cases of delayed cerebral ischemia, but no statistically significant difference was observed. The incidence of hypoglycemia did not differ significantly between the two groups.

A systematic evaluation of computational methods for cell segmentation.

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation and instance segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including image channels, choice of training data, and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, substantially reducing the time and effort for training cell segmentation models.

Biomechanical evaluation of Gamma 3 nail with anti-rotation screw fixation for unstable femoral neck fractures: a biomechanical study.

This study aims to evaluate the biomechanical performance of the Gamma 3 nail with an anti-rotation screw (GNS) and compare it to two established gold-standard methods for treating unstable femoral neck fractures (UFNFs). Synthetic bone models were prepared with Pauwels' type III osteotomy and an additional posterior wedge. Three different implant configurations were tested: three cannulated crews (3CS) in an inverted triangle configuration, a dynamic hip screw with an anti-rotation screw (DHSS), and GNS. Non-destructive cyclic axial loading was applied at 7° adduction, with 1000 cycles ranging from 100 to 1000 N. Subsequently, a construct failure test was conducted using progressive axial compression, and fracture reduction loss was recorded. The average axial stiffness was 321 ± 52 N/mm for 3CS, 430 ± 71 N/mm for DHSS, and 519 ± 104 N/mm for GNS. The average ultimate failure loads were 2699.3 N for 3CS, 3427.1 N for DHSS, and 3758.9 N for GNS. GNS demonstrated significantly greater axial stiffness compared to the other two groups (P < 0.05). Both DHSS and GNS exhibited similar failure loading, which were greater than those of 3CS (P < 0.05). GNS offers the advantages of a minimally invasive and intramedullary implant with comparable stability to the DHSS system. Moreover, GNS demonstrated superior biomechanical performance compared to 3 CS configuration.

Inspector for Face Forgery Detection: Defending Against Adversarial Attacks From Coarse to Fine.

The emergence of face forgery has raised global concerns on social security, thereby facilitating the research on automatic forgery detection. Although current forgery detectors have demonstrated promising performance in determining authenticity, their susceptibility to adversarial perturbations remains insufficiently addressed. Given the nuanced discrepancies between real and fake instances are essential in forgery detection, previous defensive paradigms based on input processing and adversarial training tend to disrupt these discrepancies. For the detectors, the learning difficulty is thus increased, and the natural accuracy is dramatically decreased. To achieve adversarial defense without changing the instances as well as the detectors, a novel defensive paradigm called Inspector is designed specifically for face forgery detectors. Specifically, Inspector defends against adversarial attacks in a coarse-to-fine manner. In the coarse defense stage, adversarial instances with evident perturbations are directly identified and filtered out. Subsequently, in the fine defense stage, the threats from adversarial instances with imperceptible perturbations are further detected and eliminated. Experimental results across different types of face forgery datasets and detectors demonstrate that our method achieves state-of-the-art performances against various types of adversarial perturbations while better preserving natural accuracy. Code is available on https://github.com/xarryon/Inspector.

Kidney transplantation from a systemic lupus erythematosus donor and 1-year follow-up: A case report.

Systemic lupus erythematosus (SLE) is usually regarded as a relative contraindication for deceased kidney donation. The pathological variations because of the changes in the immune environment after kidney transplantation (KT) are unclear, and the recovery of renal function is poorly understood. We present a case of KT from a deceased donor with SLE who was followed-up for one year. Although SLE-related hemangioma developed during the perioperative period, it was cured after interventional treatment. A pre-planned biopsy was performed one year after KT, and it was found that most of the pathological changes and immunofluorescent markers of lupus had resolved. Renal function was stable, and urinary protein and occult blood levels reduced one year after KT.

Predictive factors of postoperative complications related to free flap reconstruction in head and neck cancer patients admitted to intensive care unit: a retrospective cohort study.

BACKGROUND: The epidemiology and risk factors for postoperative complications related to free flap reconstruction in head and neck cancer patients admitted to the Intensive Care Unit (ICU) are unknown. METHODS: We performed a retrospective cohort study of patients with free flap reconstruction of head and neck cancer between September 2015 and April 2023 admitted to the ICU of Beijing Tongren Hospital. The univariate and multivariate analyses were used to explore the risk factors for postoperative complications related to free flap reconstruction admitted to ICU, including flap necrosis, bleeding, fistula, and infection. RESULTS: A total of 239 patients were included in this study, and 38 (15.9%) patients had postoperative complications related to free flap reconstruction. The median length of ICU stay was 1 day (interquartile range, 1-2 days). Multivariate analysis found that low BMI (P < 0.001), high postoperative CRP (P = 0.005), low hemoglobin (P = 0.012), and inadequate fluid intake (P < 0.05) were independent risk factors for complications. CONCLUSIONS: Postoperative complications related to free flap reconstruction were common in this ICU population. Careful fluid management and monitoring of CRP and hemoglobin levels may reduce complications.

Protecting Prostate Cancer Classification From Rectal Artifacts via Targeted Adversarial Training.

Magnetic resonance imaging (MRI)-based deep neural networks (DNN) have been widely developed to perform prostate cancer (PCa) classification. However, in real-world clinical situations, prostate MRIs can be easily impacted by rectal artifacts, which have been found to lead to incorrect PCa classification. Existing DNN-based methods typically do not consider the interference of rectal artifacts on PCa classification, and do not design specific strategy to address this problem. In this study, we proposed a novel Targeted adversarial training with Proprietary Adversarial Samples (TPAS) strategy to defend the PCa classification model against the influence of rectal artifacts. Specifically, based on clinical prior knowledge, we generated proprietary adversarial samples with rectal artifact-pattern adversarial noise, which can severely mislead PCa classification models optimized by the ordinary training strategy. We then jointly exploited the generated proprietary adversarial samples and original samples to train the models. To demonstrate the effectiveness of our strategy, we conducted analytical experiments on multiple PCa classification models. Compared with ordinary training strategy, TPAS can effectively improve the single- and multi-parametric PCa classification at patient, slice and lesion level, and bring substantial gains to recent advanced models. In conclusion, TPAS strategy can be identified as a valuable way to mitigate the influence of rectal artifacts on deep learning models for PCa classification.

Class-Incremental Learning: A Survey.

Deep models, e.g., CNNs and Vision Transformers, have achieved impressive achievements in many vision tasks in the closed world. However, novel classes emerge from time to time in our ever-changing world, requiring a learning system to acquire new knowledge continually. Class-Incremental Learning (CIL) enables the learner to incorporate the knowledge of new classes incrementally and build a universal classifier among all seen classes. Correspondingly, when directly training the model with new class instances, a fatal problem occurs - the model tends to catastrophically forget the characteristics of former ones, and its performance drastically degrades. There have been numerous efforts to tackle catastrophic forgetting in the machine learning community. In this paper, we survey comprehensively recent advances in class-incremental learning and summarize these methods from several aspects. We also provide a rigorous and unified evaluation of 17 methods in benchmark image classification tasks to find out the characteristics of different algorithms empirically. Furthermore, we notice that the current comparison protocol ignores the influence of memory budget in model storage, which may result in unfair comparison and biased results. Hence, we advocate fair comparison by aligning the memory budget in evaluation, as well as several memory-agnostic performance measures. The source code is available at https://github.com/zhoudw-zdw/CIL_Survey/.

The bioproduction of astaxanthin: A comprehensive review on the microbial synthesis and downstream extraction.

Astaxanthin is a valuable orange-red carotenoid with wide applications in agriculture, food, cosmetics, pharmaceuticals and nutraceuticals areas. At present, the biological synthesis of astaxanthin mainly relies on Haematococcus pluvialis and Xanthophyllomyces dendrorhous. With the rapid development of synthetic biology, more recombinant microbial hosts have been genetically constructed for astaxanthin production including Escherichia coli, Saccharomyces cerevisiae and Yarrowia lipolytica. As multiple genes (15) were involved in the astaxanthin synthesis, it is particularly important to adopt different strategies to balance the metabolic flow towards the astaxanthin synthesis. Furthermore, astaxanthin is a fat-soluble compound stored intracellularly, hence efficient extraction methods are also essential for the economical production of astaxanthin. Several efficient and green extraction methods of astaxanthin have been reported in recent years, including the superfluid extraction, ionic liquid extraction and microwave-assisted extraction. Accordingly, this review will comprehensively introduce the advances on the astaxanthin production and extraction by using different microbial hosts and strategies to improve the astaxanthin synthesis and extraction efficiency.