Machine-Learning-Assisted Design of Deep Eutectic Solvents Based on Uncovered Hydrogen Bond Patterns

Non-ionic deep eutectic solvents(DESs)are non-ionic designer solvents with various applications in catalysis,extraction,carbon capture,and pharmaceuticals.However,discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation.The search for DES relies heavily on intuition or trial-and-error processes,leading to low success rates or missed opportunities.Recognizing that hydrogen bonds(HBs)play a central role in DES formation,we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning(ML)models to discover new DES systems.We first analyze the HB properties of 38 known DES and 111 known non-DES systems using their molecular dynamics(MD)simulation trajectories.The analysis reveals that DES systems have two unique features compared to non-DES systems:The DESs have①more imbalance between the numbers of the two intra-component HBs and②more and stronger inter-component HBs.Based on these results,we develop 30 ML models using ten algorithms and three types of HB-based descriptors.The model performance is first benchmarked using the average and minimal receiver operating characteristic(ROC)-area under the curve(AUC)values.We also analyze the importance of individual features in the models,and the results are consistent with the simulation-based statistical analysis.Finally,we validate the models using the experimental data of 34 systems.The extra trees forest model outperforms the other models in the validation,with an ROC-AUC of 0.88.Our work illustrates the importance of HBs in DES formation and shows the potential of ML in discovering new DESs.

Grindability Evaluation of Ultrasonic Assisted Grinding of Silicon Nitride Ceramic Using Minimum Quantity Lubrication Based SiO_(2)Nanofluid

Minimum quantity Lubrication(MQL)is a sustainable lubrication system that is famous in many machining systems.It involve the spray of an infinitesimal amount of mist-like lubricants during machining processes.The MQL system is affirmed to exhibit an excellent machining performance,and it is highly economical.The nanofluids are understood to exhibit excellent lubricity and heat evacuation capability,compared to pure oil-based MQL system.Studies have shown that the surface quality and amount of energy expended in the grinding operations can be reduced considerably due to the positive effect of these nanofluids.This work presents an experimental study on the tribological performance of SiO_(2)nanofluid during grinding of Si_(3)N_(4)ceramic.The effect different grinding modes and lubrication systems during the grinding operation was also analyzed.Different concentrations of the SiO_(2)nanofluid was manufactured using canola,corn and sunflower oils.The quantitative evaluation of the grinding process was done based on the amount of grinding forces,specific grinding energy,frictional coefficient,and surface integrity.It was found that the canola oil exhibits optimal lubrication performance compared to corn oil,sunflower oil,and traditional lubrication systems.Additionally,the introduction of ultrasonic vibrations with the SiO_(2)nanofluid in MQL system was found to reduce the specific grinding energy,normal grinding forces,tangential grinding forces,and surface roughness by 65%,57%,65%,and 18%respectively.Finally,regression analysis was used to obtain an optimum parameter combinations.The observations from this work will aid the smooth transition towards ecofriendly and sustainable machining of engineering ceramics.

Research on Multi-modal In-Vehicle Intelligent Personal Assistant Design

Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.

Improving fatigue properties of normal direction ultrasonic vibration assisted face grinding Inconel 718 by regulating machined surface integrity

Fatigue properties are crucial for critical aero-engine components in extreme serviceenvironments,which are significantly affected by surface integrity(SI)indexes(especially surface topography,residual stressσ_(res),and microhardness)after machining processes.Normal-direction ultrasonic vibration-assisted face grinding(ND-UVAFG)has advantages in improving the machinability of Inconel 718,but there is a competitive relationship between higher compressiveσ_(res)and higher surface roughness R_(a)in affecting fatigue strength.The lack of a quantitative relationship between multiple SI indexes and fatigue strength makes theindeterminacy of a regulatory strategy for improving fatigue properties.In this work,a model of fatigue strength(σ_f)_(sur)considering multiple SI indexes was developed.Then,high-cycle fatigue tests were carried out on Inconel 718 samples with different SI characteristics,and the influence of ND-UVAFG process parameters on SI was analyzed.Based on SI indexes data,the(σ_f)_(sur)distribution in the grinding surface layer for ND-UVAFG Inconel 718 samples was determined using the developed model,and then the fatigue crack initiation(FCI)sites were furtherpredicted.The predicted FCI sites corresponded well with the experimental results,therebyverifying this model.A strategy for improving the fatigue life was proposed in this work,which was to transfer the fatigue source from the machined surface to the bulk material by controlling the SI indexes.Finally,a critical condition of SI indexes that FCI sites appeared on the surface or in bulk material was given by fitting the predicted results.According to the critical condition,an SI field where FCI sites appeared in the bulk material could be obtained.In this field,thefatigue life of Inconel 718 samples could be improved by approximately 140%.

Advances in machine learning-and artificial intelligence-assisted material design of steels

With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science.Machine learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data points.Compared with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials.This review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model evaluation.Then,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and performance.The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed.Finally,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed.

Deterministic tools to predict gas assisted gravity drainage recovery factor

Naturally fractured rocks contain most of the world's petroleum reserves.This significant amount of oil can be recovered efficiently by gas assisted gravity drainage(GAGD).Although,GAGD is known as one of the most effective recovery methods in reservoir engineering,the lack of available simulation and mathematical models is considerable in these kinds of reservoirs.The main goal of this study is to provide efficient and accurate methods for predicting the GAGD recovery factor using data driven techniques.The proposed models are developed to relate GAGD recovery factor to the various parameters including model height,matrix porosity and permeability,fracture porosity and permeability,dip angle,viscosity and density of wet and non-wet phases,injection rate,and production time.In this investigation,by considering the effective parameters on GAGD recovery factor,three different efficient,smart,and fast models including artificial neural network(ANN),least square support vector machine(LSSVM),and multi-gene genetic programming(MGGP)are developed and compared in both fractured and homogenous porous media.Buckinghamπtheorem is also used to generate dimensionless numbers to reduce the number of input and output parameters.The efficiency of the proposed models is examined through statistical analysis of R-squared,RMSE,MSE,ARE,and AARE.Moreover,the performance of the generated MGGP correlation is compared to the traditional models.Results demonstrate that the ANN model predicts the GAGD recovery factor more accurately than the LSSVM and MGGP models.The maximum R^(2)of 0.9677 and minimum RMSE of 0.0520 values are obtained by the ANN model.Although the MGGP model has the lowest performance among the other used models(the R2 of 0.896 and the RMSE of 0.0846),the proposed MGGP correlation can predict the GAGD recovery factor in fractured and homogenous reservoirs with high accuracy and reliability compared to the traditional models.Results reveal that the employed models can easily predict GAGD recovery factor without requiring complicate governing equations or running complex and time-consuming simulation models.The approach of this research work improves our understanding about the most significant parameters on GAGD recovery and helps to optimize the stages of the process,and make appropriate economic decisions.

Clinical Study of Tianji Robotic-Assisted Surgery for Upper Cervical Spine Fractures

Object: To compare the safety, clinical efficacy, and complication rate of “Tianji” robot-assisted surgery with traditional open surgery in the treatment of cervical vertebrae fracture. Methods: 60 patients with upper cervical vertebrae fracture admitted to Baise People’s Hospital between November 2018 and April 2024 were retrospectively analyzed. Among these patients, 29 underwent “Tianji” robot-assisted surgery (Robot group), and 31 underwent traditional C-arm fluoroscopy-assisted open surgery (Open group). Statistical analysis of the data was performed using SPSS 27.0 software to compare general data (gender, age, BMI), preoperative and postoperative visual analogue scale (VAS) scores, neck disability index (NDI), intraoperative blood loss, accuracy of screw placement on imaging, and the number of complications in both groups for comprehensive evaluation. A P value < 0.05 was deemed to have achieved statistical significance. Results: There was no significant difference in preoperative VAS scores between the two groups (Robot group: 8.34 ± 0.61;Open group: 8.26 ± 0.68, P = 0.317). There was also no significant difference in VAS scores at 1 week postoperatively (Robot group: 6.90 ± 0.31;Open group: 6.94 ± 0.36, P = 0.3237). Preoperative NDI scores showed no significant difference between the two groups (Robot group: 43.31 ± 2.67;Open group: 43.84 ± 2.67, P = 0.2227), and the difference in NDI scores at 1 week postoperatively was also not significant (Robot group: 35.69 ± 4.24;Open group: 37.35 ± 3.48, P = 0.0509). Intraoperative blood loss in the Robot group was significantly lower than in the Open group (246.21 ± 209 ml vs 380.65 ± 328.04 ml, P = 0.0308), with a statistically significant difference. The operation time was longer in the Robot group (3.75 ± 0.74 h) compared to the Open group (2.74 ± 0.86 h). In terms of screw placement accuracy, the Robot group had a higher accuracy rate for Class A screws compared to the Open group (102 screws vs 94 screws, P = 0.0487), and the accuracy rate for Class B screws was also higher in the Robot group (13 screws vs 29 screws, P = 0.0333), with both differences being statistically significant. There was no significant difference in the number of complications between the two groups (Robot group: 8 cases;Open group: 10 cases, P = 0.6931). Conclusion: Patients treated with “Tianji” robot-assisted surgery for upper cervical vertebrae fracture had lower intraoperative blood loss and higher screw placement accuracy compared to those undergoing traditional C-arm fluoroscopy-assisted open surgery, indicating that this robot-assisted surgery can effectively reduce intraoperative blood loss and improve screw placement accuracy.

Microcavity assisted graphene pressure sensor for single-vessel local blood pressure monitoring

Dynamic monitoring of blood pressure (BP) is beneficial to obtain comprehensive cardiovascular information of patients throughout the day. However, the clinical BP measurement method relies on wearing a bulky cuff, which limits the long-term monitoring and control of BP. In this work, a microcavity assisted graphene pressure sensor (MAGPS) for single-vessel local BP monitoring is designed to replace the cuff. The microcavity structure increases the working range of the sensor by gas pressure buffering. Therefore, the MAGPS achieves a wide linear response of 0–1050 kPa and sensitivity of 15.4 kPa^(−1). The large working range and the microcavity structure enable the sensor to fully meet the requirements of BP detection at the radial artery. A database of 228 BP data (60-s data fragment detected by MAGPS) and 11,804 pulse waves from 9 healthy subjects and 5 hypertensive subjects is built. Finally, the BP was detected and analyzed automatically by combining MAGPS and a two-stage convolutional neural network algorithm. For the BP detection method at local radial artery, the first stage algorithm first determines whether the subject has hypertension by the pulse wave. Then, the second stage algorithm can diagnose systolic and diastolic BP with the accuracy of 93.5% and 97.8% within a 10 mmHg error, respectively. This work demonstrates a new BP detection method based on single vessel, which greatly promotes the efficiency of BP detection.

Comparison efficacy and safety of total laparoscopic gastrectomy and laparoscopically assisted total gastrectomy in treatment of gastric cancer

BACKGROUND The development of laparoscopic technology has provided a new choice for surgery of gastric cancer(GC),but the advantages and disadvantages of laparoscopic total gastrectomy(LTG)and laparoscopic-assisted total gastrectomy(LATG)in treatment effect and safety are still controversial.The purpose of this study is to compare the efficacy and safety of the two methods in the treatment of GC,and to provide a basis for clinical decision-making.AIM To compare the efficacy of totally LTG(TLTG)and LATG in the context of radical gastrectomy for GC.Additionally,we investigated the safety and feasibility of the total laparoscopic esophagojejunostomy technique.METHODS Literature on comparative studies of the above two surgical methods for GC(TLTG group and LATG group)published before September 2022 were searched in the PubMed,Web of Science,Wanfang Database,CNKI,and other Chinese and English databases.In addition,the following search keywords were used:Gastric cancer,total gastrectomy,total laparoscopy,laparoscopy-assisted,esophagojejunal anastomosis,gastric/stomach cancer,total gastrectomy,totally/completely laparoscopic,laparoscopic assisted/laparoscopy assisted/laparoscopically assisted,and esophagojejunostomy/esophagojejunal anastomosis.Review Manager 5.3 software was used for the meta-analysis after two researchers independently screened the literature,extracted the data,and evaluated the risk of bias in the included studies.RESULTS After layer-by-layer screening,258 pieces of literature were recovered,and 11 of those pieces were eventually included.This resulted in a sample size of 2421 instances,with 1115 cases falling into the TLTG group and 1306 cases into the LATG group.Age or sex differences between the two groups were not statistically significant,according to the meta-analysis,however the average body mass index of the TLTG group was considerably higher than that of the LATG group(P=0.01).Compared with those in the LATG group,the incision length in the TLTG group was significantly shorter(P<0.001),the amount of intraoperative blood loss was significantly lower(P=0.003),the number of lymph nodes removed was significantly greater(P=0.04),and the time of first postoperative feeding and postoperative hospitalization were also significantly shorter(P=0.03 and 0.02,respectively).There were no significant differences in tumor size,length of proximal incisal margin,total operation time,anastomotic time,postoperative pain score,postoperative anal exhaust time,postoperative anastomosis-related complications(including anastomotic fistula,anastomotic stenosis,and anastomotic hemorrhage),or overall postoperative complication rate(P>0.05).CONCLUSION TLTG and esophagojejunostomy are safe and feasible.Compared with LATG,TLTG has the advantages of less trauma,less bleeding,easier access to lymph nodes,and faster postoperative recovery,and TLTG is also suitable for obese patients.

Ab Initio Design of Ni-Rich Cathode Material with Assistance of Machine Learning for High Energy Lithium-Ion Batteries

With the widespread use of lithium-ion batteries in electric vehicles,energy storage,and mobile terminals,there is an urgent need to develop cathode materials with specific properties.However,existing material control synthesis routes based on repetitive experiments are often costly and inefficient,which is unsuitable for the broader application of novel materials.The development of machine learning and its combination with materials design offers a potential pathway for optimizing materials.Here,we present a design synthesis paradigm for developing high energy Ni-rich cathodes with thermal/kinetic simulation and propose a coupled image-morphology machine learning model.The paradigm can accurately predict the reaction conditions required for synthesizing cathode precursors with specific morphologies,helping to shorten the experimental duration and costs.After the model-guided design synthesis,cathode materials with different morphological characteristics can be obtained,and the best shows a high discharge capacity of 206 mAh g^(−1)at 0.1C and 83%capacity retention after 200 cycles.This work provides guidance for designing cathode materials for lithium-ion batteries,which may point the way to a fast and cost-effective direction for controlling the morphology of all types of particles.

High performance micromachining of sapphire by laser induced plasma assisted ablation(LIPAA)using GHz burst mode femtosecond pulses

GHz burst-mode femtosecond(fs)laser,which emits a series of pulse trains with extremely short intervals of several hundred picoseconds,provides distinct characteristics in materials processing as compared with the conventional irradiation scheme of fs laser(single-pulse mode).In this paper,we take advantage of the moderate pulse interval of 205 ps(4.88 GHz)in the burst pulse for high-quality and high-efficiency micromachining of single crystalline sapphire by laser induced plasma assisted ablation(LIPAA).Specifically,the preceding pulses in the burst generate plasma by ablation of copper placed behind the sapphire substrate,which interacts with the subsequent pulses to induce ablation at the rear surface of sapphire substrates.As a result,not only the ablation quality but also the ablation efficiency and the fabrication resolution are greatly improved compared to the other schemes including single-pulse mode fs laser direct ablation,single-pulse mode fs-LIPAA,and nanosecond-LIPAA.

Endoscopic vacuum assisted closure therapy for esophagopericardial fistula in a 16-year-old male:A case report

BACKGROUND Esophagopericardial fistula(EPF)is a rare,life-threatening condition with limited scientific literature and no established management guidelines.This case report highlights a successful multidisciplinary approach and the innovative use of endoscopic vacuum assisted closure(endoVAC)therapy in treating this complex condition.CASE SUMMARY A 16-year-old male with a history of esophageal atresia and colon interposition presented with progressive chest pain,fever,and dyspnea.Imaging revealed an EPF with associated pleural and pericardial effusions.Initial management with an esophageal stent failed,prompting the use of an endoVAC system.The patient underwent multiple endoVAC device changes and received broad-spectrum antibiotics and nutritional support.The fistula successfully closed,and the patient recovered,demonstrating no new symptoms at a 6-month follow-up.CONCLUSION EndoVAC therapy can effectively manage EPF,providing a minimally invasive treatment option.

Safety and Effectiveness of Stent-Assisted Coil Embolization for Ruptured Intracranial Aneurysm

Background: It has been conclusively established that intracranial aneurysms measuring a diameter below 7 mm pose a minimal risk of rupture. Conversely, those exhibiting irregular morphology or featuring the presence of a sac necessitate a more stringent and rigorous management approach. Objective: The primary aim of this study is to delve into the morphological features of ruptured aneurysms situated in distinct regions of the brain. Furthermore, we endeavor to assess the degree of safety and efficacy associated with stent-assisted embolization as a treatment modality for these ruptured aneurysms. Methods: This retrospective study encompassed a cohort of 467 patients who presented with intracranial ruptured aneurysms and were diagnosed through a combination of computed tomography (CT) and digital subtraction angiography (DSA) at Nanfang Hospital of Southern Medical University, spanning from January 2009 to December 2019. The following clinical parameters were meticulously recorded: aneurysm height, width, neck measurements, immediate Raymond grade assessments, and any perioperative complications experienced. Results: Within the study population, the average dimensions of ruptured aneurysms were found to be 4.26 ± 2.10 mm (width), 4.86 ± 2.38 mm (height), and 4.04 ± 1.87 mm (neck). Categorically, the most prevalent types of aneurysms were 170 cases of anterior communicating artery aneurysms (accounting for 36.4%), followed by 161 cases of posterior communicating artery aneurysms (34.5%), 56 cases of middle cerebral artery aneurysms (12.0%), 13 cases of anterior cerebral artery aneurysms (2.8%), 45 cases of paraclinoid aneurysms (9.6%), 6 cases of superior pituitary artery aneurysms (1.3%), 7 cases of anterior choroidal artery aneurysms (1.5%), and 9 cases of vertebrobasilar artery aneurysms (2.0%). Notably, 18 patients (3.9%) presented with ruptured aneurysms coexisting with ascus. Regarding treatment approaches, 228 cases (48.8%) underwent stent-assisted embolization, 234 cases (50.1%) received coils embolization, and 5 cases (1.1%) were treated with the dual-catheter technique. Immediately post-treatment, 422 patients (90.4%) attained a Raymond Class I status, with a procedure-related complication rate of 0.9%. Importantly, no statistically significant differences were observed in the incidence of perioperative complications across the three distinct treatment groups (P = 0.505). Conclusion: The outcomes of this study affirm the safety and efficacy of stent-assisted embolization as a treatment modality for ruptured aneurysms.

Research progress in CALPHAD assisted metal additive manufacturing

Metal additive manufacturing(MAM)technology has experienced rapid development in recent years.As both equipment and materials progress towards increased maturity and commercialization,material metallurgy technology based on high energy sources has become a key factor influencing the future development of MAM.The calculation of phase diagrams(CALPHAD)is an essential method and tool for constructing multi-component phase diagrams by employing experimental phase diagrams and Gibbs free energy models of simple systems.By combining with the element mobility data and non-equilibrium phase transition model,it has been widely used in the analysis of traditional metal materials.The development of CALPHAD application technology for MAM is focused on the compositional design of printable materials,the reduction of metallurgical imperfections,and the control of microstructural attributes.This endeavor carries considerable theoretical and practical significance.This paper summarizes the important achievements of CALPHAD in additive manufacturing(AM)technology in recent years,including material design,process parameter optimization,microstructure evolution simulation,and properties prediction.Finally,the limitations of applying CALPHAD technology to MAM technology are discussed,along with prospective research directions.

The Impact of Seasonal Variation on Clinical Pregnancy and Live Birth Rates in Assisted Reproductive Technology: A Retrospective Cohort Study in Hainan

Objective:To investigate the influence of season on live birth and clinical pregnancy rates,as well as assisted reproductive technology(ART)outcomes,in the Hainan region.Methods:Patients were categorized into four groups based on the dates of artificial insemination and transplantation:spring,summer,autumn,or winter.The main outcome measures were clinical pregnancy rates and live birth rates.Secondary outcomes included body mass index(BMI),oocyte number,two pronuclei(2PN)cleavage rate,total gonadotropin(Gn)dosage and days,age,2PN fertilization rate,sperm concentration,sperm PR rate,anti-Müllerian hormone(AMH),and endometrial thickness.Outpatient semen quality indicators included sperm PR rate,total sperm count,sperm concentration,and total sperm motility.Results:This retrospective cohort study analyzed 2,016 artificial insemination cycles and 1,783 ovarian retrieval cycles from January 2017 to October 2022,and assessed the semen quality of 6,651 outpatients from May 2017 to October 2022.In artificial insemination cycles,sperm PR rate and clinical pregnancy rate were highest in winter,with a statistically significant difference between groups(P<0.05).Clinical pregnancy rate was influenced by both age and sperm PR rate(P<0.05).In ovarian retrieval cycles,the winter group had significantly higher clinical pregnancy,2PN fertilization,and 2PN cleavage rates than the other groups.The autumn group had higher live birth rates,though not significantly different.Additionally,winter months showed higher total sperm concentration and total sperm number compared to other seasons.Conclusion:Seasonality affected clinical pregnancy and live birth rates in artificial insemination cycles but not in ovarian retrieval cycles in the Hainan region.These findings suggest that while there is no need to choose a specific season for ovarian retrieval cycles,artificial insemination in winter may be preferable for patients.

Artificial intelligence-assisted chiral nanophotonic designs

Chiral nanostructures can enhance the weak inherent chiral effects of biomolecules and highlight the important roles in chiral detection.However,the design of the chiral nanostructures is challenged by extensive theoretical simulations and explorative experiments.Recently,Zheyu Fang’s group proposed a chiral nanostructure design method based on reinforcement learning,which can find out metallic chiral nanostructures with a sharp peak in circular dichroism spectra and enhance the chiral detection signals.This work envisions the powerful roles of artificial intelligence in nanophotonic designs.

Mass-Based Environmental Factor and Energy Assessment of Microwave-Assisted Synthesized Transition Metal Nanostructures

This paper describes mass-based energy phase-space projection of microwave-assisted synthesis of transition metals (zinc oxide, palladium, silver, platinum, and gold) nanostructures. The projection uses process energy budget (measured in kJ) on the horizontal axes and process density (measured in kJg−1) on the vertical axes. These two axes allow both mass usage efficiency (Environmental-Factor) and energy efficiency to be evaluated for a range of microwave applicator and metal synthesis. The metrics are allied to the: second, sixth and eleventh principle of the twelve principle of Green Chemistry. This analytical approach to microwave synthesis (widely considered as a useful Green Chemistry energy source) allows a quantified dynamic environmental quotient to be given to renewable plant-based biomass associated with the reduction of the metal precursors. Thus allowing a degree of quantification of claimed “eco-friendly” and “sustainable” synthesis with regard to waste production and energy usage.

Impact of the Rapid Recovery Concept on Complications and Patient Quality of Life in the Perioperative Nursing of Robot-Assisted Radical Oesophageal Cancer

Aim: This study evaluates the impact of Enhanced Recovery After Surgery (ERAS) nursing on postoperative complications and quality of life in patients undergoing robot-assisted minimally invasive esophagectomy (RAMIE). Methods: A total of 150 patients who underwent RAMIE from January 2020 to January 2022 at our hospital were randomly assigned to either the observation group or the control group, with 75 patients in each. The control group received standard perioperative management and nursing care, while the observation group was treated with ERAS nursing strategies. Interventions continued until discharge, and outcomes such as postoperative complications, quality of life, and nutritional status were compared between the groups. Results: The observation group exhibited a significantly lower incidence of postoperative adverse reactions compared to the control group (P ionally, all dimension scores of the Short-Form 36 Health Survey (SF-36), including the total score, were higher in the observation group (P < 0.05). Furthermore, the Nutritional Risk Screening (NRS) scores for impaired nutritional status and disease severity, along with the total NRS score, were significantly lower in the observation group compared to the control group (P Conclusion: Implementing ERAS nursing in the perioperative care of patients undergoing RAMIE is associated with reduced postoperative complications and enhanced postoperative quality of life and nutritional status. .

Evaluation of Functional and Radiological Outcome of Arthroscopic-Assisted Anatomical Coracoclavicular (CC) and Acromioclavicular (AC) Ligament Reconstruction in Chronic AC Joint Dislocation

Introduction: Acromioclavicular (AC) joint dislocation is a common shoulder injury, comprising 9% - 12% of shoulder girdle injuries. Optimal management remains challenging, with treatment decisions guided by the Rockwood classification system. Controversies surround grade III injuries, necessitating further classification. Non-operative treatment has shown favorable outcomes, while surgical interventions vary. Anatomical coracoclavicular reconstruction (ACCR) has demonstrated biomechanical advantages over traditional methods. Arthroscopic techniques offer advantages, minimizing deltoid detachment and allowing concurrent pathology identification. This study evaluates the outcomes of arthroscopic-assisted ACCR in chronic AC joint dislocation. Surgical Technique: Arthroscopic-assisted ACCR involves meticulous portal placement, tendon graft harvesting, diagnostic arthroscopy, and coracoid exposure. The clavicle tunnels were made to mimic the conoid and trapezoid ligament positions, using FibreTape#2 loop and Dog Bone Button for correct placement against the coracoid base, and passing the semitendinosus graft through to reconstruct the conoid ligament, reduction done and graft follow through for anatomical reconstruction. Methods: A retrospective cohort study at Hospital Kuala Lumpur analyzed 35 patients undergoing arthroscopic-assisted ACCR for Rockwood grade III - V AC joint dislocations. Inclusion criteria encompassed trauma ≥ 3 weeks prior, no prior shoulder injuries, and ≥12-month follow-up. Functional and radiological assessments utilized ASES scores and coracoclavicular distances, respectively. Statistical analysis employed descriptive statistics and logistic regression. Results: The mean age was 38.9 years (SD 11.26), and 34 of 35 patients were male. Grade IV injuries were predominant (37.1%). Waiting time for surgery averaged 234.9 days. Functional improvement was substantial postoperatively (ASES: 55.5 to 88.9). Radiological outcomes demonstrated reduced coracoclavicular distances and maintained reduction. No significant correlation was observed between injury grade and outcomes. Conclusion: Arthroscopic-assisted ACCR for chronic AC joint dislocation yields significant functional and radiological improvement, irrespective of injury grade. Waiting time for surgery exhibits minor impact on outcomes, emphasizing the procedure’s efficacy. Concomitant injuries do not impede success, highlighting the versatility of this approach in managing shoulder instability. The study contributes valuable insights into the nuanced management of chronic AC joint dislocations and supports the adoption of arthroscopic-assisted ACCR as a viable treatment option.

Catheter-Assisted Interlaminar Approach for Cervical Epidural Steroid Injection in Patient with Cervical Stenosis Caused by Ossification of Posterior Longitudinal Ligament: A Case Report

We present the case of a 64-year-old man with cervical ossification of the posterior longitudinal ligament (OPLL) experiencing chronic neck pain and radiculopathy for 6 months. A catheter-assisted interlaminar Cervical Epidural Steroid Injection (CESI) was performed under fluoroscopic guidance, targeting the affected C2-C6 levels. Significant improvement was observed after this procedure, with decreased pain scores (visual analogue scale (VAS) 8 to 2) and improved mobility. This technique not only enhances the effectiveness of CESI but also reduces the likelihood of complications such as stroke or epidural hematoma and thus provides an alternative treatment option for patients with multiple stenotic levels who are unsuitable for surgery or are unresponsive to conservative therapy such as medication or physical therapy.