Plasma Concentration of Posaconazole in Septic Shock Patients with Continuous Renal Replacement Therapy: A Case Report.

Objective: This study aims to evaluate the impact of continuous renal replacement therapy (CRRT) on the plasma concentrations of Posaconazole in critically ill patients. Case presentation: In this study, we reported a patient with septic shock, cardiac arrest, and Multiple Organ Dysfunction Syndrome showed improvement following anti-infective treatment with Posaconazole. The patient's condition improved after Posaconazole was administered for anti-infective treatment. The concentration of Posaconazole was measured during CRRT. The results showed that the trough concentrations of Posaconazole were 1.9mg/L and 0.8mg/L on the 7th and 11th days of CRRT, respectively. The peak concentrations of Posaconazole were 6.6 mg/L and 4.3 mg/L on the 7th and 11th days of CRRT. On the first and second day after the discontinuation of CRRT, the trough concentrations of Posaconazole were 0.7 mg/L and 0.8 mg/L, and the peak concentrations were 2.6 mg/L and 2.2 mg/L. These results indicated that the trough and peak concentrations of Posaconazole were not significantly different before and after CRRT. No adverse reactions occurred during the follow-up. Conclusion: Posaconazole plasma concentrations remained stable during and after CRRT, suggesting that dose adjustments are not necessary in these clinical settings.

[Research progress of ICU-acquired weakness].

ICU-acquired weakness (ICU-AW) is a common complication in the intensive care unit (ICU). The occurrence of ICU-AW directly leads to prolonged ICU stays for critically ill patients, and in severe cases, it continues to affect their quality of life even after discharge. This article provides a comprehensive review of the research progress on ICU-AW based on domestic and foreign studies, aiming to provide a scientific overview of ICU-AW, including its definition, pathophysiology, diagnosis, screening tools, influencing factors, and potential intervention strategies, so as to promote timely planning and implementation of relevant screening and intervention measures.

Automatic recognition of cephalometric landmarks via multi-scale sampling strategy.

The identification of head landmarks in cephalometric analysis significantly contributes in the anatomical localization of maxillofacial tissues for orthodontic and orthognathic surgery. However, the existing methods face the limitations of low accuracy and cumbersome identification process. In this pursuit, the present study proposed an automatic target recognition algorithm called Multi-Scale YOLOV3 (MS-YOLOV3) for the detection of cephalometric landmarks. It was characterized by multi-scale sampling strategies for shallow and deep features at varied resolutions, and especially contained the module of spatial pyramid pooling (SPP) for highest resolution. The proposed method was quantitatively and qualitatively compared with the classical YOLOV3 algorithm on the two data sets of public lateral cephalograms, undisclosed anterior-posterior (AP) cephalograms, respectively, for evaluating the performance. The proposed MS-YOLOV3 algorithm showed better robustness with successful detection rates (SDR) of 80.84% within 2 mm, 93.75% within 3 mm, and 98.14% within 4 mm for lateral cephalograms, and 85.75% within 2 mm, 92.87% within 3 mm, and 96.66% within 4 mm for AP cephalograms, respectively. It was concluded that the proposed model could be robustly used to label the cephalometric landmarks on both lateral and AP cephalograms for the clinical application in orthodontic and orthognathic surgery.

Efficacy and safety of colistin sulfate in the treatment of infections caused by carbapenem-resistant organisms: a multicenter retrospective cohort study.

Background: Polymyxins have become an important treatment option for carbapenem-resistant organisms (CRO) infections. However, there is a rare of clinical studies on colistin sulfate. This study sought to investigate the rate of clinical improvement and adverse reactions of colistin sulfate in the treatment of severe infections caused by CRO in critically ill patients and assess the factors associated with 28-day all-cause mortality. Methods: This multicenter retrospective cohort study included intensive care unit (ICU) patients who received colistin sulfate due to CRO infections during July 2021 and May 2022. The primary endpoint was clinical improvement at end of therapy. Secondary endpoints included adverse reactions bacterial clearance rate and 28-day all-cause mortality. Results: A total of 122 patients, who were included between July 2021 and May 2022, were included in this study, of whom 86 (70.5%) showed clinical improvement and 36 (29.5%) showed clinical failure. The comparison of the clinical data of the patients showed that the median sequential organ failure assessment (SOFA) score was higher in the failure group than the improvement group {9.5 [7, 11] vs. 7 [4, 9], P=0.002}, the proportion of patients receiving extracorporeal membrane oxygenation (ECMO) was higher in the failure group than the improvement group (27.8% vs. 12.8%, P=0.046), and the median duration of treatment was longer in the improvement group than the failure group {12 [8, 15] vs. 5.5 [4, 9.75], P<0.001}. A total of 5 (4.1%) patients suffered from acute kidney injury due to increases in creatinine during colistin sulfate treatment. The Cox regression survival analysis showed that the SOFA score [hazards ratio (HR) =1.198, P=0.001], ECMO treatment (HR =2.373, P=0.029), and duration of treatment (HR =0.736, P<0.001) were independently associated with 28-day all-cause mortality. Conclusions: Colistin sulfate is a reasonable choice for the treatment of CRO infections in the current treatment options are limited. The possible kidney injury caused by the colistin sulfate requires intensive monitoring.

The porous hollow cobalt-based oxides encapsulated with bimetallic PdAu Nanoparticles of electrochemical biosensor for highly sensitive pesticides detection.

Efficient and portable electrochemical biosensors are received to evaluation of pesticides in the environment, which can make great significance for food safety. In this study, the Co-based oxides with a kind of hierarchical porous hollow and nanocages were constructed, in which the materials (Co3O4-NC) were encapsulated with PdAu nanoparticles (NPs). Due to the unique porous structure, the changeable valence state of cobalt and the synergistic effect of bimetallic PdAuNPs, PdAu@Co3O4-NC possessed excellent electron pathways, and showed more exposed active sites. Accordingly, the porous Co-based oxides have been applied to construct an acetylcholinesterase (AChE) electrochemical biosensor, which showed good performance for organophosphorus pesticides (OPs) detection. The optimum biosensing platform based on nanocomposites was applied to exhibit highly sensitive determination of omethoate and chlorpyrifos, with the relative low detection limit of 6.125 × 10-15M and 5.10 × 10-13M, respectively. And a wide detection range of 6.125 × 10-15∼ 6.125 × 10-6M and 5.10 × 10-13∼ 5.10 × 10-6M for these two pesticides were achieved. Therefore, the PdAu@Co3O4-NC may represent a powerful tool for ultrasensitive sensing of OPs, and have great potential application.

In-situ growth of SnO2 nanoparticles on Nb2CTx nanosheets as highly sensitive electrochemical sensing platform for organophosphorus pesticide detection.

In this study, the SnO2/Nb2CTx MXene nanocomposite containing 0D/2D interfaces was prepared by situ growth strategy of one-step hydrothermal method. A SnO2/Nb2CTx MXene based acetylcholinesterase (AChE) biosensor was constructed for pesticide detection. Highly conductive Nb2CTx MXene, acting as substrate material, restrained the agglomeration of nanoparticles (NPs) and accelerated electron migration due to the confinement effect and well-known accordion-like layered structure. In addition, SnO2 anchored on both sides of the Nb2CTx MXene nanosheets effectively provided a large surface area, abundant surface groups and active sites, which preserved numbers of electrons at the interface of the heterojunction. The SnO2/Nb2CTx MXene hybrids with outstanding conductivity, good biocompatibility and structural stability were beneficial for AChE immobilization. Under the optimized conditions, as-fabricated electrochemical biosensor demonstrated superior performance with linear detection range of 5.1 × 10-14 - 5.1 × 10-7 M for chlorpyrifos, along with the limit of detection (LOD) down to 5.1 × 10-14 M (calculated for 10% inhibition). Furthermore, it is highly expected that this biosensor can be applied for the detection of other organophosphorus pesticides in the environment, providing an effective nanoplatform in biosensing field.

Classification of white blood cells using weighted optimized deformable convolutional neural networks.

BACKGROUND: Machine learning (ML) algorithms have been widely used in the classification of white blood cells (WBCs). However, the performance of ML algorithms still needs to be addressed for being short of gold standard data sets, and even the implementation of the proposed algorithms. METHODS: In this study, the method of two-module weighted optimized deformable convolutional neural networks (TWO-DCNN) was proposed for WBC classification. Our algorithm is characterized as two-module transfer learning and deformable convolutional (DC) layers for the betterment of robustness. To validate the performance, our method was compared with classical MLs of VGG16, VGG19, Inception-V3, ResNet-50, support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT) and random forest (RF) on our undisclosed WBC data set and public BCCD data set. RESULTS: TWO-DCNN achieved the best performance with the precisions (PREs) of 95.7%, 94.5% and 91.6%, recalls (RECs) of 95.7%, 94.5% and 91.6%, F1-scores (F1s) of 95.7%, 94.5% and 91.6%, area under curves (AUCs) of 0.98, 0.97 and 0.95 for low-resolution and noisy undisclosed data sets, BCCD data set, respectively. CONCLUSIONS: With accurate feature extraction and optimized network weights, the proposed TWO-DCNN showed the best performance in WBC classification for low-resolution and noisy data sets. It could be used as an alternative method for clinical applications.