Adjuvants to local anesthetics: Current understanding and future trends

Although beneficial in acute and chronic pain management, the use of local anaesthetics is limited by itsduration of action and the dose dependent adverse effects on the cardiac and central nervous system. Adjuvants or additives are often used with local anaesthetics for its synergistic effect by prolonging the duration of sensory-motor block and limiting the cumulative dose requirement of local anaesthetics. The armamentarium of local anesthetic adjuvants have evolved over time from classical opioids to a wide array of drugs spanning several groups and varying mechanisms of action. A large array of opioids ranging from morphine, fentanyl and sufentanyl to hydromorphone, buprenorphine and tramadol has been used with varying success. However, their use has been limited by their adverse effect like respiratory depression, nausea, vomiting and pruritus, especially with its neuraxial use. Epinephrine potentiates the local anesthetics by its antinociceptive properties mediated by alpha-2 adrenoreceptor activation along with its vasoconstrictive properties limiting the systemic absorption of local anesthetics. Alpha 2 adrenoreceptor antagonists like clonidine and dexmedetomidine are one of the most widely used class of local anesthetic adjuvants. Other drugs like steroids(dexamethasone), anti-inflammatory agents(parecoxib and lornoxicam), midazolam, ketamine, magnesium sulfate and neostigmine have also been used with mixed success. The concern regarding the safety profile of these adjuvants is due to its potential neurotoxicity and neurological complications which necessitate further research in this direction. Current research is directed towards a search for agents and techniques which would prolong local anaesthetic action without its deleterious effects. This includes novel approaches like use of charged molecules to produce local anaesthetic action(tonicaine and n butyl tetracaine), new age delivery mechanisms for prolonged bioavailability(liposomal, microspheres and cyclodextrin systems) and further studies with other drugs(adenosine, neuromuscular blockers, dextrans).

Why Labor Epidural Causes Fever and Why Lidocaine Burns on Injection? Role of TRPV 1 Receptor in Hyperthermia: Possible Explanation of Mechanism of Hyperthermia during Labor Epidural and Burning Sensation on Injection of Local Anesthetics

The mechanisms of epidural-associated fever remain incompletely understood [1-3]. We propose that action of local anesthetic on TPRV1. The transient receptor potential cation channel subfamily V member 1 (TRPV1), also known as the capsaicin receptor and the vanilloid receptor can explain this effect and explain mechanism of burning sensation on local anesthetic injected subcutaneously or intramuscular. Role of TRPV1 receptor was not discussed previously in Obstetric Anesthesia literature. Based on available data, we propose that Local Anesthetics work as agonist/antagonist on TPRV1 receptors. Antagonist action may cause hyperthermia through modifying thermoregulation [4], agonist action may cause hyperthermia thru release of IL-6 and other mediators of inflammation [5-10]. Agonist action may explain burning sensation on injection of Local Anesthetics. Burning sensation can be diminished by increasing pH of Local Anesthetic solution, because vanillin receptors are stimulated by acidification through lower pH [11,12].

Different Volumes of Local Anesthetics in Ultrasound-Guided Combined Interscalene-Supraclavicular Block for Traumatic Humeral Fracture

Background: Procedures that require anesthesia of entire length of the arm should have combined Interscalene block (ISB) and Supraclavicular block (SCB) to ensure adequate block. However, dual block requires high dose of local anesthetic (LA). We examined if Ultrasound (U/S) guided block helps to decrease the required volume of LA by visualizing trunks, so we only need injection of LA toward cervical nerve roots C5 and C6 aiming to block branches escaped from supraclavicular block. Patients and methods: Ninety-three patients were randomly allocated into one of three equal groups, each included 31 patients. All patients received SCB 20 ml (10 ml Bupivacaine 0.5% plus 10 ml lidocaine 2%) and ISB with different volumes of LA according to the group as follow: group A: 20 ml, group B: 15 ml, and group C: 10 ml. Result: No significant difference in onset of block (sensory and motor) and duration of block (motor only) between the three groups (P value > 0.05). The duration of sensory block was significantly longer in group A (760.65 ± 30.87 minutes) than in either group B (740.48 ± 21.15 minutes, P value P value P value P value P value P value < 0.001). Conclusion: A reduced volume of LA can be used in ultra sound guided ISB in combined with SCB to give satisfactory level of anesthesia to entire length of the arm, but the sensory block duration and duration of post-operative analgesia will be decreased significantly with decreasing the volume.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations,along with the appraisal of relevant uncertainties,is paramount in monitoring both natural and human-induced micro-seismicity.For this purpose,a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks.In this study,we first review different sources of errors relevant to the localization of seismic events,how they propagate through localization algorithms,and their impact on outcomes.We then propose a quantitative method,based on a Monte Carlo approach,to estimate the uncertainty in earthquake locations that is suited to the design,optimization,and assessment of the performance of a local seismic monitoring network.To illustrate the performance of the proposed approach,we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout.The results expand,quantitatively,the qualitative indications derived from purely geometrical parameters(azimuthal gap(AG))and classical detectability maps.The proposed method enables the systematic design,optimization,and evaluation of local seismic monitoring networks,enhancing monitoring accuracy in areas proximal to hydrocarbon production,geothermal fields,underground natural gas storage,and other subsurface activities.This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties,which are crucial for assessing and mitigating seismic risks,thereby enabling the implementation of proactive measures to minimize potential hazards.From an operational perspective,reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

Can repeated scorpion bite lead to development of resistance to the effect of local anesthetics? Maybe it does!

An 80 years old, bronchial asthmatic, male was posted for left cataract extraction with intra ocular lens implantation. He was administered peribulbar block/left facial nerve block. There was no sensory or motor block. Thereafter peribulbar block was repeated. Only partial akinesia was achieved, so under intermittent intra venous sedation, the surgery continued for 40 minutes. In the post-operative period, no signs of any residual/delayed block were noted. On specific enquiry, patient gave history of scorpion bite thrice, at the age of 27 years on his right foot, about 8-9 years back and again about 6-7 months back on his right hand. On 4th post-operative day after obtaining informed consent, local infiltration of the skin on the ventral aspect of the forearm, using, 6 mL, 2% lignocaine with adrenaline, was carried out. Confirming the suspicion, there was no sensory block after the injection, confirmed by pin prick method. Peribulbar block produces adequate intra-operative analgesia for cataract extraction. The cause of the failures may be due to technical inability to achieve block. However failure that occurs despite of technically correct injection of the correct drug can be mystifying. As the scorpion venom is known to affect the pumping mechanism of sodium channels in the nerve fibres, which are involved in the mechanism of action of local anaesthetic drugs, it may be responsible for the development of “resistance” to the action of local anaesthetic agents.

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

In situations when the precise position of a machine is unknown,localization becomes crucial.This research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based technique.In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based algorithm.Received signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout building.The noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI measurement.This study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference point.The findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Local dimming原理及在车载中的应用

Local dimming(局部调光)是一种低成本提升车载显示器对比度和清晰度的技术。在目前OLED技术尚无法突破严苛的汽车环境要求的状况下,局部调光是一种首选的成本和性能兼顾的技术。在满足汽车环境要求的同时,大幅提升了显示器的清晰度,提高了显示内容的辨识度,同时成本的上升也在合理范围内。它能给客户带来更好的体验,使驾驶更为安全。本文对它的工作原理以及如何应用进行了阐述,给读者提供了一种思路和方法来提升车载显示器的对比度。

Genome-wide investigation to assess copy number variants in the Italian local chicken population

Background Copy number variants(CNV)hold significant functional and evolutionary importance.Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock.High-density chips have enabled the detection of CNV with increased resolution,leading to the identification of even small CNV.This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.Results Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV.The majority of CNV in the investigated breeds were of types 0 and 1,and the minimum length of CNV was significantly larger than that reported in previous studies.Interestingly,a high proportion of the length of chromosome 16 was covered by copy number variation regions(CNVR),with the major histocompatibility complex being the likely cause.Among the genes identified within CNVR,only those present in at least five animals across breeds(n=95)were discussed to reduce the focus on redundant CNV.Some of these genes have been associated to functional traits in chickens.Notably,several CNVR on different chromosomes harbor genes related to muscle development,tissue-specific biological processes,heat stress resistance,and immune response.Quantitative trait loci(QTL)were also analyzed to investigate potential overlapping with the identified CNVR:54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size,carcass characteristics,egg production,egg components,fat deposition,and feed intake.Conclusions The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Present situation and prospect of immunotherapy for unresectable locally advanced esophageal cancer during peri-radiotherapy

Four major studies(Checkmate577,Keynote-590,Checkmate649 and Attraction-4)of locally advanced esophageal cancer published in 2020 have established the importance of immunotherapy,represented by anti-programmed death protein(PD)-1 in postoperative adjuvant treatment and advanced first-line treatment of locally advanced or advanced esophageal cancer and esophagogastric junction cancer,from the aspects of proof of concept,long-term survival,overall survival rate and progression-free survival.For unresectable or inoperable nonmetastatic esophageal cancer,concurrent radiotherapy and chemotherapy is the standard treatment recommended by various guidelines.Because its curative effect is still not ideal,it is necessary to explore radical radiotherapy and chemotherapy in the future,and it is considered to be promising to combine them with immunotherapeutic drugs such as anti-PD-1.This paper mainly discusses how to combine radical concurrent radiotherapy and chemotherapy with immunotherapy for unresectable local advanced esophageal cancer.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Deep brain implantable microelectrode arrays for detection and functional localization of the subthalamic nucleus in rats with Parkinson’s disease

The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.

A study of the effect of local scour on the flow field near the spur dike

The flow field near a spur dike such as down flow and horseshoe vortex system(HVS)are susceptible to the topographic changes in the local scouring process,resulting in variation of the sediment transport with time.In this study,large eddy simulations with fixed-bed at different scouring stages were conducted to investigate the changes in flow field.The results imply that the bed deformation leads to an increase in flow rate per unit area,which represent the capability of sediment transportation by water,in the scour hole.Moreover,the intensity of turbulent kinetic energy and bimodal motion near the sand bed induced by the HVS were also varied.However,the peak moments between the two sediment transport mechanisms were different.Hence,understanding the complex feedback mechanism between topography and flow field is essential for the local scour problem.

Numerical study on local scour characteristics around submarine pipelines in the Yellow River Delta silty sandy soil under waves and currents

Due to their high reliability and cost-efficiency,submarine pipelines are widely used in offshore oil and gas resource engineering.Due to the interaction of waves,currents,seabed,and pipeline structures,the soil around submarine pipelines is prone to local scour,severely affecting their operational safety.With the Yellow River Delta as the research area and based on the renormalized group(RNG)k-εturbulence model and Stokes fifth-order wave theory,this study solves the Navier-Stokes(N-S)equation using the finite difference method.The volume of fluid(VOF)method is used to describe the fluid-free surface,and a threedimensional numerical model of currents and waves-submarine pipeline-silty sandy seabed is established.The rationality of the numerical model is verified using a self-built waveflow flume.On this basis,in this study,the local scour development and characteristics of submarine pipelines in the Yellow River Delta silty sandy seabed in the prototype environment are explored and the influence of the presence of pipelines on hydrodynamic features such as surrounding flow field,shear stress,and turbulence intensity is analyzed.The results indicate that(1)local scour around submarine pipelines can be divided into three stages:rapid scour,slow scour,and stable scour.The maximum scour depth occurs directly below the pipeline,and the shape of the scour pits is asymmetric.(2)As the water depth decreases and the pipeline suspension height increases,the scour becomes more intense.(3)When currents go through a pipeline,a clear stagnation point is formed in front of the pipeline,and the flow velocity is positively correlated with the depth of scour.This study can provide a valuable reference for the protection of submarine pipelines in this area.

Local dose-dense chemotherapy for triple-negative breast cancer via minimally invasive implantation of 3D printed devices

Dose-dense chemotherapy is the preferred first-line therapy for triple-negative breast cancer(TNBC),a highly aggressive disease with a poor prognosis.This treatment uses the same drug doses as conventional chemotherapy but with shorter dosing intervals,allowing for promising clinical outcomes with intensive treatment.However,the frequent systemic administration used for this treatment results in systemic toxicity and low patient compliance,limiting therapeutic efficacy and clinical benefit.Here,we report local dose-dense chemotherapy to treat TNBC by implanting 3D printed devices with timeprogrammed pulsatile release profiles.The implantable device can control the time between drug releases based on its internal microstructure design,which can be used to control dose density.The device is made of biodegradable materials for clinical convenience and designed for minimally invasive implantation via a trocar.Dose density variation of local chemotherapy using programmable release enhances anti-cancer effects in vitro and in vivo.Under the same dose density conditions,device-based chemotherapy shows a higher anticancer effect and less toxic response than intratumoral injection.We demonstrate local chemotherapy utilizing the implantable device that simulates the drug dose,number of releases,and treatment duration of the dose-dense AC(doxorubicin and cyclophosphamide)regimen preferred for TNBC treatment.Dose density modulation inhibits tumor growth,metastasis,and the expression of drug resistance-related proteins,including p-glycoprotein and breast cancer resistance protein.To the best of our knowledge,local dose-dense chemotherapy has not been reported,and our strategy can be expected to be utilized as a novel alternative to conventional therapies and improve anti-cancer efficiency.

Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.

Anesthesia,Anesthetics,and Postoperative Cognitive Dysfunction in Elderly Patients

Postoperative cognitive dysfunction(POCD)remains a major issue that worsens the prognosis of elderly surgery patients.This article reviews the current research on the effect of different anesthesia methods and commonly utilized anesthetics on the incidence of POCD in elderly patients,aiming to provide an understanding of the underlying mechanisms contributing to this condition and facilitate the development of more reasonable anesthesia protocols,ultimately reducing the incidence of POCD in elderly surgery patients.

Seropositivity and Other Determinants Associated with Toxoplasmosis in Local Buffalo in Iraq

A cross-sectional study was conducted to determine the Seropositivity of Toxoplasma gondii in water buffalo in three Iraqi governorates (Baghdad, Dhi Qar, and Maysan) and to estimate the risk aspects related to infestation throughout the period from January to December 2019. A total of 430 serum samples were inspected with a commercial ELISA (Enzyme linked immunosorbent assay) kit. Indirect multi-species kit. The overall Seropositivity of T. gondii in the examined local buffalo was 7.4%, and the highest rate (9.3%) was in Baghdad Governorate. A multivariate regression analysis revealed that adult buffalo (OR = 7.10;95% CI: 0.87-57.68;P = 0.067) and young herds (OR = 8.42;95% CI: 1.07-66.02;P = 0.043) were more subject to infestation from young buffalo and large herds. Furthermore, the hazard of toxoplasmosis was increased in winter especially among animals in contact with cats. It is therefore requisite to determine risk aspects to evaluate which mitigation, control, prevention and procedures should be carried out to diminish, control and prevent infestation with T. gondii and its propagation.