The Prevalence and Risk Factors for Postoperative Thirst: A Systematic Review and Meta-analysis.

PURPOSE: Thirst is a symptom of dehydration and one of the main complications affecting postoperative outcomes and comfort. Persistent water scarcity can have a detrimental effect on the cognitive function and psychology of patients. However, the current evidence about the prevalence and risk factors for postoperative thirst is not fully understood. Therefore, this study aims to investigate the prevalence and risk factors of postoperative thirst and provide guidance for clinical practice. DESIGN: Systematic review and meta-analysis. METHODS: We searched PubMed, Cochrane Library, Web of Science, Embase, Clinicaltrials.gov, China National Knowledge Infrastructure, and Wanfang Database. Eligible studies were evaluated using the Agency for Healthcare Research and Quality. The collected data were pooled and analyzed using Stata15.0. FINDINGS: A total of 11 cross-sectional studies were included involving 20,612 patients. Eight studies reported prevalence and the pooled prevalence of postoperative thirst was 76.8% (95% confidence interval [CI]: 0.664 to 0.858). Five studies contributed to meta-syntheses of risk factors for postoperative thirst. The results indicated that sex (odds ratio [OR] = 1.44, 95% CI = 1.13 to 1.84, I2 = 80.2%, P = .006), anesthesia drug (OR = 1.48, 95% CI = 1.06 to 2.06, I2 = 94.8%, P < .001), surgical type (OR = 0.66, 95% CI = 0.49 to 0.9, I2 = 77.9%, P = .004) were statistically associated with postoperative thirst. CONCLUSIONS: Our study shows a high prevalence of postoperative thirst. Sex, anesthesia drug, and surgical type are risk factors that influence postoperative thirst. Nurses and other health care professionals should routinely assess the postoperative thirst of patients and perform targeted interventions to alleviate their distressing symptoms and improve the quality of care.

Field Implementation of Precision Livestock Farming: Selected Proceedings from the 2nd U.S. Precision Livestock Farming Conference.

Precision Livestock Farming (PLF) involves the real-time monitoring of images, sounds, and other biological, physiological, and environmental parameters to assess and improve animal health and welfare within intensive and extensive production systems [...].

Evaluating broiler welfare and behavior as affected by growth rate and stocking density.

This study evaluated the welfare and behaviors of Cobb 700 broilers as affected by growth rate (GR) and stocking density (SD). Slower-growth (weight gain < 50 g/d) and medium-growth (weight gain = 50-60 g/d) broilers were produced by providing 57.1% and 78.6% of the feed intake listed in the Cobb 700 production manual for standard (fed ad libitum) broilers (weight gain > 60 g/d). Broilers at all 3 GRs were reared at 2 SDs of 30 and 40 kg/m2. Broiler welfare indicators, including gait score, tibia strength, feather coverage, and footpad condition were evaluated when birds reached 1, 2, and 3 kg of body weight. The activity index was determined by overhead cameras and image processing, and the time spent at feeders was recorded using the radio-frequency identification (RFID) systems. The results show that it took 45 d for standard, 52 d for medium-growth, and 62 d for slower-growth broilers to reach a 3 kg market body weight. Feed conversion ratios (FCR, kg/kg) were 1.57 for standard, 1.67 for medium-growth, and 1.80 for slower-growth broilers. Growth rate and SD had an interaction effect on feather cleanliness (P = 0.03), and belly feather coverage (P = 0.02). Slower-growth broilers were more active and had better feather coverage and gait scores than medium-growth and standard broilers (all P < 0.01) but may feel hungry and depressed, medium-growth broilers spent the most time at the feeder among the 3 growth groups (P = 0.02), and standard broilers showed the best production performance. Broilers at 30 kg/m2 showed better bone strength (P = 0.04), and footpad condition (P < 0.01) compared to those at 40 kg/m2. In conclusion, reducing GR and SD may slightly improve broiler leg health at the high expense of compromised production performance and prolonged production cycles.

Analysis of the Drinking Behavior of Beef Cattle Using Computer Vision.

Monitoring the drinking behavior of animals can provide important information for livestock farming, including the health and well-being of the animals. Measuring drinking time is labor-demanding and, thus, it is still a challenge in most livestock production systems. Computer vision technology using a low-cost camera system can be useful in overcoming this issue. The aim of this research was to develop a computer vision system for monitoring beef cattle drinking behavior. A data acquisition system, including an RGB camera and an ultrasonic sensor, was developed to record beef cattle drinking actions. We developed an algorithm for tracking the beef cattle's key body parts, such as head-ear-neck position, using a state-of-the-art deep learning architecture DeepLabCut. The extracted key points were analyzed using a long short-term memory (LSTM) model to classify drinking and non-drinking periods. A total of 70 videos were used to train and test the model and 8 videos were used for validation purposes. During the testing, the model achieved 97.35% accuracy. The results of this study will guide us to meet immediate needs and expand farmers' capability in monitoring animal health and well-being by identifying drinking behavior.

Broiler Mobility Assessment via a Semi-Supervised Deep Learning Model and Neo-Deep Sort Algorithm.

Mobility is a vital welfare indicator that may influence broilers' daily activities. Classical broiler mobility assessment methods are laborious and cannot provide timely insights into their conditions. Here, we proposed a semi-supervised Deep Learning (DL) model, YOLOv5 (You Only Look Once version 5), combined with a deep sort algorithm conjoined with our newly proposed algorithm, neo-deep sort, for individual broiler mobility tracking. Initially, 1650 labeled images from five days were employed to train the YOLOv5 model. Through semi-supervised learning (SSL), this narrowly trained model was then used for pseudo-labeling 2160 images, of which 2153 were successfully labeled. Thereafter, the YOLOv5 model was fine-tuned on the newly labeled images. Lastly, the trained YOLOv5 and the neo-deep sort algorithm were applied to detect and track 28 broilers in two pens and categorize them in terms of hourly and daily travel distances and speeds. SSL helped in increasing the YOLOv5 model's mean average precision (mAP) in detecting birds from 81% to 98%. Compared with the manually measured covered distances of broilers, the combined model provided individual broilers' hourly moved distances with a validation accuracy of about 80%. Eventually, individual and flock-level mobilities were quantified while overcoming the occlusion, false, and miss-detection issues.

Estimating the Feeding Time of Individual Broilers via Convolutional Neural Network and Image Processing.

Feeding behavior is one of the critical welfare indicators of broilers. Hence, understanding feeding behavior can provide important information regarding the usage of poultry resources and insights into farm management. Monitoring poultry behaviors is typically performed based on visual human observation. Despite the successful applications of this method, its implementation in large poultry farms takes time and effort. Thus, there is a need for automated approaches to overcome these challenges. Consequently, this study aimed to evaluate the feeding time of individual broilers by a convolutional neural network-based model. To achieve the goal of this research, 1500 images collected from a poultry farm were labeled for training the You Only Look Once (YOLO) model to detect the broilers' heads. A Euclidean distance-based tracking algorithm was developed to track the detected heads, as well. The developed algorithm estimated the broiler's feeding time by recognizing whether its head is inside the feeder. Three 1-min labeled videos were applied to evaluate the proposed algorithm's performance. The algorithm achieved an overall feeding time estimation accuracy of each broiler per visit to the feeding pan of 87.3%. In addition, the obtained results prove that the proposed algorithm can be used as a real-time tool in poultry farms.

Mitigating Silica Fouling and Improving PPCP Removal by Modified NF90 Using In Situ Radical Graft Polymerization.

This study in-situ modified a commercial nanofiltration membrane, NF90, through the concentration-polymerization-enhanced radical graft polarization method by applying two agents of 3-sulfopropyl methacrylate potassium salt (SPM) and 2-hydroxyethyl methacrylate (HEMA) with different dosages. Surface characterization revealed that the modified membranes became rougher and more hydrophilic compared with the pristine membrane. The modified membranes exhibited considerably enhanced separation performance with 5.8-19.6% higher NaCl rejection and 17.2-19.9% higher pharmaceuticals and personal care products (PPCPs) rejection than the pristine membrane. When treating the feedwater with high silica concentration, the modified membranes exhibited relatively less flux decline with high percentage of reversible fouling, especially the ones modified using a lower monomer concentration (0.01 M SPM and 0.01 M HEMA). Moreover, membrane modification enhanced the PPCP rejection (1.3-5.4%) after silica fouling by mitigating foulant deposition on the membrane surface. The fouling mechanism was confirmed to be intermediate blocking of membrane pores. Therefore, the in-situ modification technique with a low monomer concentration proved to be effective for mitigating silica fouling and improving PPCP rejection, which can be easily performed and cost-effective in practical application.

Stress analysis of the thoracolumbar junction in the process of backward fall: An experimental study and finite element analysis.

The aim of the present study was to evaluate the biomechanical mechanism of injuries of the thoracolumbar junction by the methods of a backward fall simulation experiment and finite element (FE) analysis (FEA). In the backward fall simulation experiment, one volunteer was selected to obtain the contact force data of the sacrococcygeal region during a fall. Utilizing the fall data, the FEA simulation of the backward fall process was given to the trunk FE model to obtain the stress status of local bone structures of the thoracolumbar junction during the fall process. In the fall simulation test, the sacrococcygeal region of the volunteer landed first; the total impact time was 1.14±0.58 sec, and the impact force was up to 4,056±263 N. The stress of thoracic (T)11 was as high as 42 MPa, that of the posterior margin and the junction of T11 was as high as 70.67 MPa, and that of the inferior articular process and the superior articular process was as high as 128 MPa. The average stress of T12 and the anterior margin of lumbar 1 was 25 MPa, and that of the endplate was as high as 21.7 MPa, which was mostly distributed in the back of the endplate and the surrounding cortex. According to the data obtained from the fall experiment as the loading condition of the FE model, the backward fall process can be simulated to improve the accuracy of FEA results. In the process of backward fall, the front edge of the vertebral body and the root of vertebral arch in the thoracolumbar junction are stress concentration areas, which have a greater risk of injury.

The chain-like Au/carbon dots nanocomposites with peroxidase-like activity and their application for glucose detection.

The nanocomposites with highly synergistic effect show important potential application as nanozymes. Herein, the chain-like Au/carbon dots (CDs) (GCDs) nanocomposites were prepared by self-assembly method. The negatively charged Au nanoparticles (NPs) and positively charged CDs were connected by the electrostatic interaction. Then, the electron transfer between Au and CDs induces the strong catalytic effect of GCDs nanocomposites. The cross-linking reaction occurred between amino groups and carboxyl groups on the surface of CDs, which led to form the chain-like Au aggregation surrounded by carbon shells. By FDTD simulation, the aggregation of Au NPs may enhance the electromagnetic field so that the surface-enhanced Raman scattering (SERS) signal can be increased based on GCDs nanocomposites as substrate. Otherwise, the GCDs nanocomposites can also be used to catalyze the oxidation of colourless3,3',5,5'-tetramethylbenzidine (TMB) to blue oxTMB in the presence of H2O2, which displays the enhanced peroxidase-like activity compared with alone Au NPs or CDs. The obvious oxidation process of TMB molecules may be monitored by the change of SERS signal during the catalytic reaction. On this basis, GCDs nanocomposites can be further used for detection of glucose. The detection level of glucose is obtained as low as 5 × 10-7 M. Therefore, this provides a method to detect the glucose based on GCDs nanocomposites as an enzyme mimic.

Targeting self-assembled F127-peptide polymer with pH sensitivity for release of anticancer drugs.

The treatment of breast cancer mainly relies on chemotherapy drugs, which present significant side effects. The most typical example is the cardiotoxicity and bone marrow suppression associated with doxorubicin (DOX). Therefore, this drug is not the first choice in clinical treatment. We designed ATN-FFPFF-ATN, a new targeted antitumor drug carrier, polymerized from phenylalanine dipeptide (FF), ATN-161 peptide, and Pluronic® F-127. The peptide and Pluronic® F-127 are linked with acetal and are, therefore, acid-sensitive. As cancer can reduce pH through complex mechanisms and subsequently maintain acid ambience, our vehicle can smartly unravel at a peculiar position, through which the drug can specifically accumulate inside the tumor. ATN-161 is a protein ligand of integrin α5ß1, which is highly expressed on the surface of some breast cancer cells. This targeting peptide sequence can play a role in the selective delivery of DOX to tumor cells. The DOX-carrying vector was able to significantly inhibit cell proliferation and promote cell apoptosis in MDA-MB-231 cells. Based on these results, ATN-FFPFF-ATN with pH response is a promising vehicle for DOX delivery.

Inflammatory infiltration is associated with AR expression and poor prognosis in hormone naïve prostate cancer.

BACKGROUND: Tumor microenvironment inflammatory infiltration is proposed as a protumorigenic mechanism for prostate cancer with proinflammatory cytokines stimulating androgen receptor (AR) activity. However, association with patient prognosis remains unclear. This study derives an inflammatory gene signature associated with AR expression and investigates CD3+ and CD8+ T-lymphocyte infiltration association with AR and prognosis. METHODS: Gene profiling of inflammatory related genes was performed on 71 prostate biopsies. Immunohistochemistry on 243 hormone-naïve prostate cancers was performed for CD3, CD8, AR, and phosphorylated AR tumor expression. RESULTS: Multiple proinflammatory genes were differentially expressed in association with high AR expression compared with low AR expression including PI3KCA and MAKP8 (adjusted P < .05). High CD3+ and high CD8+ infiltration associated with reduced cancer-specific survival (P = .018 and P = .020, respectively). High CD3+ infiltration correlated with high tumor cytoplasmic AR expression and if assessed together, they associated with reduced cancer-specific and 5-year survival from 90% to 56% (P = .000179). High CD8+ cytotoxic infiltration associated with high androgen-independent tumor nuclear AR serine 213 phosphorylation (correlation coefficient = 0.227; P = .003) and when assessed together associated with poor clinico-pathological features including perineural invasion (P = .001). Multiple genes involved in proinflammatory signaling pathways are upregulated in high AR expressing prostate samples. CONCLUSION: T-lymphocyte infiltration in hormone-naïve disease associates with androgen-independent driven disease and provides possible therapeutic targets to reduce transformation from hormone-naïve to castrate-resistant disease.

Development of a method to analyze the complexes of enoxaparin and platelet factor 4 with size-exclusion chromatography.

Heparin, a highly sulfated glycosaminoglycan, has been used as a clinical anticoagulant over 80 years. However, heparin-induced thrombocytopenia and thrombosis (HITT) is a serious side effect of heparin therapy, resulting in relatively high risk of amputation and even death. HITT is caused by forming of complexes between heparin and platelet factor 4 (PF4). Enoxaparin, one of the most commonly used low molecular weight heparin (LMWH), were developed in 1980's. The lower molecular weight of enoxaparin reduces the risk of HITT by binding to less PF4. To detect the binding capacity between enoxaparin and PF4 could be an effect way to control this risk before it goes to patients. In this work, a size exclusion chromatography (SEC) method was developed to analyze the patterns of complexes formed between PF4 and enoxaparin. The chromatographic condition was optimized to separate PF4, enoxaparin, ultra-large complexes and small complexes. The linearity and stability of this method were confirmed. The impacts of PF4/enoxaparin mixture ratios and incubation time on the forming complexes were investigated. Four enoxaparin samples were analyzed with this method to verify its practicability. It is a robust, accurate and practicable method, and provides an easy way to monitor the capacity of enoxaparin forming complexes with PF4, suggesting the HITT related quality of enoxaparin.

Qualitative and quantitative analysis of 2, 5-anhydro-d-mannitol in low molecular weight heparins with high performance anion exchange chromatography hyphenated quadrupole time of flight mass spectrometry.

Low molecular weight heparins (LMWHs), derived from unfractionated heparin (UFH) by chemical or enzymatic degradation, have lower side effects than that of heparin. Enoxaparin, nadroparin, and dalteparin are the most widely used LMWHs. Nadroparin and dalteparin are prepared through nitrous acid degradation followed by a subsequent reduction process, in which specific residue, 2,5-anhydro-d-mannitol (An-Man), is formed at the reducing terminals of generated sugar chains. However, few practicable analytical method was available to analyze An-Man qualitatively and quantitatively. In this work, a HPAEC-PAD-MS method was developed to analyze monosaccharides in heparin and LMWHs, especially An-Man. An ion suppressor is set up between HPAEC and MS to remove the nonvolatile salts from HPAEC and make the elute compatible to MS. Various monosaccharides were separated well with HPAEC. Online MS and MS/MS confirmed all sugar residues in the hydrolysates of heparin samples. The specific residue, An-Man, was only observed in the hydrolysates of LMWHs prepared with nitrous acid degradation and reduction. In addition, major glucosamine and minor arabinose/galactose were observed in all heparin samples. The amounts of these sugar residues were quantitated with PAD, simultaneously. The ratio of glucosamine to An-Man could be used to calculate the molecular weight of LMWHs. The calculated values are comparable to the value measured with size-exclusion chromatography-multiple angle laser scattering detection. Higher the ratio of glucosamine to An-Man higher the molecular weight. The HPAEC-PAD-MS platform is an accurate, precise and efficient way to identify LMWHs by determination of An-Man. It is also an alternative method to detect the MWs of LMWHs having An-Man for quality control purposes.

An efficient anticoagulant candidate: Characterization, synthesis and in vivo study of a fondaparinux analogue Rrt1.17.

Fondaparinux, a synthetic pentasaccharide anticoagulant based on heparin antithrombin-binding domain, is derived from a chemical synthesis with more than 50 steps. Herein, we identified nine analogues separated from commercially available crude fondaparinux sodium, and tested their anticoagulant activity in vitro. Based on the activity results, the most active derivative Rrt1.17 was chemically synthesized. Biological properties in vitro and in vivo indicated that the well-defined derivative Rrt1.17 was a more efficient anticoagulant candidate compared with fondaparinux.

Sensitive immunosensor for tumor necrosis factor α based on dual signal amplification of ferrocene modified self-assembled peptide nanowire and glucose oxidase functionalized gold nanorod.

Sensitive electrochemical immunosensor for the detection of protein biomarker tumor necrosis factor α (TNF-α) was reported that uses ferrocene carboxylic acid (Fc) functionalized self-assembled peptide nanowire (Fc-PNW) as sensor platform and glucose oxidase (GOx) modified gold nanorod (GNR) as label. Greatly enhanced sensitivity is achieved based on a dual signal amplification strategy: first, the synthesized Fc-PNW used as the sensor platform increased the loading of primary anti-TNF-α antibody (Ab(1)) onto electrode surface due to its large surface area. At the same time, the Fc moiety on the nanowire is used as a mediator for GOx to catalyze the glucose reaction. Second, multiple GOx and secondary anti-TNF-α antibody (Ab(2)) molecules are bounded onto each GNR to increase the sensitivity of the immunosensor. After the preparation of the immunosensor based on the traditional sandwich protocol, the response of the immunosensor towards glucose was used as a signal to differentiate various concentrations of TNF-α. The resulting immunosensor has high sensitivity, wide linear range (0.005-10ng/mL) and good selectivity. This immunosensor preparation strategy is a promising platform for clinical screening of protein biomarkers.

WITHDRAWN: Eight new C21 steroidal glycosides from Cynanchum wilfordii.

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