The effect of perineural dexamethasone on nerve injury and recovery of nerve function after surgery: A randomized controlled trial.

Background: While numerous studies have examined the influence of perineural dexamethasone on nerve block duration, its potential impact on postoperative nerve injury has not been adequately addressed. Objective: This study aims to elucidate the effect of perineural dexamethasone on nerve injury and nerve function recovery after surgery. Design: A prospective randomized double-blinded trial. Setting: The First Affiliated Hospital of Chengdu Medical College, Chengdu, China. The study was conducted between 14 June and 30 December 2022. Participants: Patients aged 18 - 80 years, ASA I - II, scheduled for elective orthopedic or burn and plastic surgery. Interventions: Patients were randomized to receive either perineural dexamethasone (D group) or no dexamethasone (ND group). Main outcome measures: Primary outcomes were the incidence and recovery of nerve injury. Secondary outcomes included postoperative pain scores, analgesic consumption, and adverse events. Results: Initial postoperative nerve injury rates were similar between groups (D: 30.4 %, ND: 33.3 %, P > 0.05). At 12 weeks post-discharge, significantly more patients in the ND group recovered from nerve deficits (78.8 % vs 60.3 %; OR = 2.45, 95 % CI = 1.05 - 5.72, P < 0.05). No significant differences were observed in postoperative hyperglycemia or surgical site infection rates. Conclusion: Perineural dexamethasone may impede nerve function recovery, suggesting caution in its use, particularly for patients with pre-existing nerve damage or diabetes. Further research is needed to elucidate the long-term effects of dexamethasone on nerve tissue recovery. Trial registration: chictr.org.cn, ChiCTR2200059424.

Precise Control of Two-Dimensional Hexagonal Platelets via Scalable, One-Pot Assembly Pathways Using Block Copolymers with Crystalline Side Chains.

Crystallization-driven self-assembly (CDSA) of block copolymers (BCPs) in selective solvents provides a promising route for direct access to two-dimensional (2D) platelet micelles with excellent uniformity, although significant limitations also exist for this robust approach, such as tedious, multistep procedures, and low yield of assembled materials. Herein, we report a facile strategy for massively preparing 2D, highly symmetric hexagonal platelets with precise control over their dimensions based on BCPs with crystalline side chains. Mechanistic studies unveiled that the formation of hexagonal platelets was subjected to a hierarchical self-assembly process, involving an initial stage of formation of kinetically trapped spheres upon cooling driven by solvophobic interactions, and a second stage of fusion of such spheres to the 2D nuclei to initiate the lateral growth of hexagonal platelets via sequential particle attachments driven by thermodynamically ordered reorganization of the BCP upon aging. Moreover, the size of the developed 2D hexagonal platelets could be finely regulated by altering the copolymer concentration over a broad concentration range, enabling scale-up to a total solids concentration of at least 6% w/w. Our work reveals a new mechanism to create uniform 2D core-shell nanoparticles dictated by crystallization and particle fusion, while it also provides an alternative facile strategy for the design of soft materials with precise control of their dimensions, as well as for the scalability of the derived nanostructures.

Perioperative management of a patient with morbid obesity and severe cardiomyopathy: a case report and literature review.

As the obesity epidemic continues to escalate, the need for bariatric surgery will increase. Patients with severe cardiomyopathy and heart failure have historically been considered at high risk for perioperative complications and thus excluded from bariatric surgery. We herein describe a patient with morbid obesity, severe cardiomyopathy, and heart failure who successfully and safely underwent bariatric surgery and achieved significant weight loss and overall cardiac function improvement 1 year later. Although data are sparse, there is certainly evidence to suggest that significant weight reduction may confer a mechanism of ventricular reverse remodeling and subsequent clinical improvement.

Electropress Needle Stimulation for the Prevention of Postoperative Nausea and Vomiting in Patients Undergoing Laparoscopic Sleeve Gastrectomy: A Prospective, Randomized Controlled Trial.

BACKGROUND: Being overweight or obese is becoming increasingly prevalent worldwide and seriously endangers human health. Laparoscopic sleeve gastrectomy (LSG) has been successfully used for the treatment of severe obesity, but the incidence of postoperative nausea and vomiting (PONV) is high. However, traditional antiemetics have limited effects on PONV. Electropress needle therapy, which can be enhanced with electrical stimulation, is a promising therapy for the prevention and treatment of PONV. However, whether the electropress needle is effective for PONV in patients with LSG remains uncertain. METHODS: This was a prospective, randomized controlled trial. A total of 106 patients who planned to undergo elective LSG between October 2021 and July 2022 were randomly allocated to receive electropress needle stimulation combined with dexamethasone and granisetron (group A) or dexamethasone plus granisetron (group B). The primary outcome was the incidence of PONV 48 h after surgery. The secondary outcomes were PONV severity score, time to first flatus, length of hospital stay, visual analogue scale (VAS) score, and postoperative remedial medication use. RESULTS: Compared with dexamethasone plus granisetron, electropress needle stimulation combined with dexamethasone and granisetron significantly decreased the incidence and severity of PONV (P<0.001). Patients in Group A consumed less antiemetics postoperatively (P<0.05) and had a much shorter length of postoperative hospital stay (P<0.05). There was no difference in the time to first flatus between the two groups (P > 0.05). CONCLUSION: Electropress needle acupoint stimulation can reduce the incidence and severity of PONV in patients undergoing LSG.

Anesthesia management of an aged patient with giant abdominal tumor and large hiatal hernia: A case report and literature review.

Introduction: A giant abdominal tumor with a large hiatal hernia remains a rare disease with few studies regarding its implications in anesthesia. A large hiatal hernia may compress the heart and cause arrhythmia and even cardiac arrest, which greatly increases the risks and challenges of anesthesia management. Case description: We present a case in which a patient with a giant abdominal desmoid tumor and large hiatal hernia experienced a critical situation during anesthesia and surgery. Conclusions: It is a great challenge for anesthesiologists to manage a patient's respiratory system and circulation. Careful perioperative management and optimized multidisciplinary teams are the key factors in the successful management of this rare condition. In addition, awake endotracheal intubation, ventilation preserving spontaneous breathing and target-directed fluid therapy play an essential role in anesthesia management.

Risk Factors for Postoperative Pneumonia: A Case-Control Study.

Background: Postoperative pneumonia is a preventable complication associated with adverse outcomes, that greatly aggravates the medical expenses of patients. The goal of our study is to identify risk factors and outcomes of postoperative pneumonia. Methods: A matched 1:1 case-control study, including adult patients who underwent surgery between January 2020 and June 2020, was conducted in the Second Affiliated Hospital of Kunming Medical University in China. Cases included all patients developing postoperative pneumonia within 30 days after surgery, defined using consensus criteria. Controls were selected randomly from the matched eligible population. Results: Out of 17,190 surgical patients, 264 (1.54%) experienced postoperative pneumonia. Increased age, chronic obstructive pulmonary disease, emergency surgery, postoperative reduced albumin, prolonged ventilation, and longer duration of bed rest were identified as significant risk factors independently associated with postoperative pneumonia. Regarding prognostic implications, postoperative pneumonia was associated with longer length of hospital stay, higher ICU occupancy rate, higher unplanned re-operation rate, and higher in-hospital mortality rate. Postoperative pneumonia was most commonly caused by Gram-negative pathogens, and multidrug resistant bacteria accounted for approximately 16.99% of cases. Conclusions: Postoperative pneumonia is associated with severe clinical outcomes. We identified six independent risk factors that can aid in risk stratification and management of patients at risk of postoperative pneumonia, and the distribution of causative pathogens can also help in the implementation of effective interventions. Clinical Trial Registration: www.chictr.org.cn, identifier: chiCTR2100045986.

Successful prolonged cardiopulmonary resuscitation after intraoperative cardiac arrest due to povidone-iodine allergy: A case report.

BACKGROUND: Iodophor (povidone-iodine) is widely used clinically because of its broad-spectrum antibacterial effects. Although extremely rare, it may cause anaphylactic shock, which itself carries the life-threatening risk of cardiac arrest. CASE SUMMARY: We present a case in which a patient with postoperative infection went into anaphylactic shock and cardiac arrest caused by povidone-iodine during secondary surgery. The patient was successfully resuscitated by 2 h of cardiopulmonary resuscitation. CONCLUSION: This is the first known case of cardiac arrest caused by povidone-iodine allergy.

Effects of desflurane and sevoflurane on somatosensory-evoked and motor-evoked potential monitoring during neurosurgery: a randomized controlled trial.

BACKGROUND: Better protection can be provided during neurosurgery due to the establishment of somatosensory-evoked potential (SEP) and motor-evoked potential (MEP) monitoring technologies. However, some studies have showed that inhaled halogenated anesthetics have a significant impact on neurophysiological monitoring. METHODS: A total of 40 consecutive patients undergoing neurosurgery were randomly assigned to two groups receiving inhaled anesthetics, either desflurane or sevoflurane. Multiples levels (concentrations of 0.3, 0.6 and 0.9) of anesthetics were administered at minimum alveolar concentration (MAC), and then the latencies and amplitudes of SEPs and MEPs were recorded. RESULTS: SEP and MEP signals were well preserved in patients who underwent neurosurgery under general anesthesia supplemented with desflurane or sevoflurane at concentrations of 0.3, 0.6 and 0.9 MAC. In each desflurane or sevoflurane group, the amplitudes of SEPs and MEPs decreased and the latencies of SEPs were prolonged significantly as the MAC increased (P < 0.05). The SEP latencies of both the upper and lower limbs in the desflurane group were significantly longer, and the SEP amplitudes were significantly lower than those in the sevoflurane group (P < 0.05). The MEP amplitudes in the desflurane group were significantly lower than those in the sevoflurane group (P < 0.05), only the amplitudes of the upper limbs at 0.3 MAC did not vary significantly. CONCLUSIONS: SEPs and MEPs were inhibited in a dose-dependent manner by both desflurane and sevoflurane. At the same MAC concentration, desflurane appeared to have a stronger inhibitory effect than sevoflurane. All patients studied had normal neurological examination findings, hence, these results may not be applicable to patients with preexisting deficits. TRIAL REGISTRATION: The study registered on the Chinese Clinical Trial Registry ( www.chictr.org.cn ), Clinical Trials identifier ChiCTR2100045504 (18/04/2021).

An improved belief propagation algorithm for detecting mesoscale structure in complex networks.

The framework of statistical inference has been successfully used to detect the mesoscale structures in complex networks such as community structure and core-periphery (CP) structure. The main principle is that the stochastic block model is used to fit the observed network and the learned parameters indicating the group assignment, in which the parameters of model are often calculated via an expectation-maximization algorithm and a belief propagation (BP) algorithm, is implemented to calculate the decomposition itself. In the derivation process of the BP algorithm, some approximations were made by omitting the effects of node's neighbors, the approximations do not hold if the degrees of some nodes are extremely large. As a result, for example, the BP algorithm cannot detect the CP structure in networks and even yields a wrong detection because the nodal degrees in the core group are very large. In doing so, we propose an improved BP algorithm to solve the problem in the original BP algorithm without increasing any computational complexity. We find that the original and the improved BP algorithms yield a similar performance regarding the community detection; however, our improved BP algorithm is much better and more stable when the CP structure becomes more dominant. The improved BP algorithm may help us correctly partition different types of mesoscale structures in networks.

Detection of core-periphery structure in networks based on 3-tuple motifs.

Detecting mesoscale structure, such as community structure, is of vital importance for analyzing complex networks. Recently, a new mesoscale structure, core-periphery (CP) structure, has been identified in many real-world systems. In this paper, we propose an effective algorithm for detecting CP structure based on a 3-tuple motif. In this algorithm, we first define a 3-tuple motif in terms of the patterns of edges as well as the property of nodes, and then a motif adjacency matrix is constructed based on the 3-tuple motif. Finally, the problem is converted to find a cluster that minimizes the smallest motif conductance. Our algorithm works well in different CP structures: including single or multiple CP structure, and local or global CP structures. Results on the synthetic and the empirical networks validate the high performance of our method.

A unified method of detecting core-periphery structure and community structure in networks.

The core-periphery structure and the community structure are two typical meso-scale structures in complex networks. Although community detection has been extensively investigated from different perspectives, the definition and the detection of the core-periphery structure have not received much attention. Furthermore, the detection problems of the core-periphery and community structure were separately investigated. In this paper, we develop a unified framework to simultaneously detect the core-periphery structure and community structure in complex networks. Moreover, there are several extra advantages of our algorithm: our method can detect not only single but also multiple pairs of core-periphery structures; the overlapping nodes belonging to different communities can be identified; different scales of core-periphery structures can be detected by adjusting the size of the core. The good performance of the method has been validated on synthetic and real complex networks. So, we provide a basic framework to detect the two typical meso-scale structures: the core-periphery structure and the community structure.

Reconstructing signed networks via Ising dynamics.

Revealing unknown network structure from observed data is a fundamental inverse problem in network science. Current reconstruction approaches were mainly proposed to infer the unsigned networks. However, many social relationships, such as friends and foes, can be represented as signed social networks that contain positive and negative links. To the best of our knowledge, the method of reconstructing signed networks has not yet been developed. To this purpose, we develop a statistical inference approach to fully reconstruct the signed network structure (positive links, negative links, and nonexistent links) based on the Ising dynamics. By the theoretical analysis, we show that our approach can transfer the problem of maximum likelihood estimation into the problem of solving linear systems of equations, where the solution of the linear system of equations uncovers the neighbors and the signs of links of each node. The experimental results on both synthetic and empirical networks validate the reliability and efficiency of our method. Our study moves the first step toward reconstructing signed networks.

Fluorescent detection of copper(II) based on DNA-templated click chemistry and graphene oxide.

A novel DNA-templated click chemistry strategy for homogenous fluorescent detection of Cu(2+) has been developed based on click ligation-dependent DNA structure switch and the selective quenching ability of graphene oxide (GO) nanosheet. The clickable duplex probe consists of two DNA strands with alkyne and azide group, respectively, and Cu(+)-catalyzed alkyne-azide cycloaddition (CuAAC) reaction can chemically ligate these two strands. Toehold sequence displacement was consequently exploited to achieve DNA structure transformation bearing fluorescent tag FAM. Cu(2+)-induced chemical ligation caused the probe transfer to hybrid structure with single stranded DNA (ssDNA) tail, while only duplex structure was obtained without Cu(2+). This structural difference can be probed by GO-based fluorescence detection due to the preferential binding of GO to ssDNA. Under the optimum conditions, this sensor can sensitively and specifically detect Cu(2+) with a low detection limit of 58 nM and a linear range of 0.1-10 µM. This new strategy is highly sensitive and selective for Cu(2+) detection because of the great specificity of click chemistry and super-quenching ability of GO. Moreover, with the aid of high efficient DNA templated synthesis, the detection process requires only about half an hour which is much quicker than previous click-chemistry-based Cu(2+) sensors.