Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the u...Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.展开更多
The objectives of this work were to evaluate the surgical activities carried out in the general surgery department of the Reference Health Center of Commune I of Bamako, to describe the sociodemographic characteristic...The objectives of this work were to evaluate the surgical activities carried out in the general surgery department of the Reference Health Center of Commune I of Bamako, to describe the sociodemographic characteristics of the operated patients, to determine the main pathologies encountered and to evaluate qualitatively the result of the treatment. In order to improve performance, and the quality of care, and to identify common pathologies in the surgical department, we undertook a retrospective study on surgical activities from January 2009 to December 2010. At the end of this study, out of 474 men and 187 women (equal sex ratio 2.53);we were able to determine the frequency of surgical pathologies. Farmers, housewives and pupils/students were the most represented with 25.9% respectively;20% and 13.3%. The most frequently observed pathologies were wall hernia (44.8%), prostate adenoma (12%) and acute appendicitis (10.5%). The average length of hospitalization was 3.43 days. Infectious complications affected 25 patients (3.8% of cases) and a death rate of 0.45% (i.e. 3 patients). The average cost of care was 53,500 FCFA. Indeed, the reality of surgical practice in health centers was not the same because of the level of skills of practicing surgeons.展开更多
Introduction: Superior mesenteric artery syndrome (SMAS), a rare diagnosis due to compression of the third duodenum between the superior mesenteric artery (SMA) and the aorta resulting in bowel obstruction, may lead t...Introduction: Superior mesenteric artery syndrome (SMAS), a rare diagnosis due to compression of the third duodenum between the superior mesenteric artery (SMA) and the aorta resulting in bowel obstruction, may lead to severe malnutrition. We report two cases of patients hospitalised in the Internal Medicine, Endocrinology, Diabetology, and Nutrition Department of the National Hospital Center (NHC) of Pikine. Observations: Patient 1: A 35-year-old female was referred for an aetiological diagnosis due to a rapid weight loss of 15 kilograms in one month, accompanied by persistent vomiting, following an appendectomy performed a month before admission. Upon clinical examination, she presented severe malnutrition (Buzby index of 76%), early post-prandial chronic vomiting, and a poor general condition. An abdominal CT scan revealed aortomesenteric clamp syndrome (AMCS) with an angulation between the aorta and the SMA of 13˚. The underlying cause in this patient was severe malnutrition. Fortunately, her condition improved with medical treatment. Patient 2: We report the case of a 30-year-old female hospitalized due to unusual weight-bearing post-prandial epigastric pain and intermittent vomiting over the past six months. Upon physical examination at admission, she exhibited severe malnutrition with a body mass index (BMI) of 14 kg/m<sup>2</sup>, a Buzby index of 71%, trophic disorders, and a stage IV general condition assessment according to the World Health Organization (WHO). An abdominal CT scan revealed AMCS with an angle between the aorta and the SMA of 22˚ and an aortomesenteric space of 4 mm. The outcome was poor with medical treatment failure and, unfortunately, the patient died before surgery. Conclusion: SMAS is rarely evoked in clinical practice despite the presence of contributing factors and suggestive clinical signs. The prognosis depends on management time.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of user...The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.展开更多
Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhance...Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.展开更多
Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive s...Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.展开更多
This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary order.The HIV i...This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary order.The HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered class.The total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,respectively.The proposed model is tested separately for unique solutions and existence on bi intervals.The numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons Polynomial.The proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler Law.The cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said disease.This study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered 1000.The obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.展开更多
Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronar...Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.展开更多
Background: The incidence of intracranial metastases (ICMET) has been steadily rising, and its frequency with respect to primary brain tumours is relatively high. Objective: The objectives of this study were to elucid...Background: The incidence of intracranial metastases (ICMET) has been steadily rising, and its frequency with respect to primary brain tumours is relatively high. Objective: The objectives of this study were to elucidate the current epidemiology and describe the clinical, diagnostic and therapeutic features of ICMET in Yaounde. Method and findings: A descriptive cross-sectional study was done in the neurosurgery departments of the General and Central Hospitals of Yaounde during the period from January 2016 to December 2022. We included all medical booklets of patients admitted for a tumoral intracranial expansive process with our target population being patients with histological evidence of ICMET, and did a retrospective inclusion of data using a pre-established technical form aimed at collecting sociodemographic data, clinical data, paraclinical data, and the treatment procedures. Analysis was done using the SPSS statistical software. A total of 614 cases of intracranial tumors were included among whom 35 presented histological evidence of ICMET. This gives a frequency of 5.7%. The sex ratio was 0.94, the mean age was 55.68 +/- 14.4 years, extremes 28 and 86 years and the age range 50 - 59 was affected in 28.57% of cases. The clinical presentation included signs of raised intracranial pressure (headache, blurred vision, vomiting) in 26 cases (74.3%), motor deficit 48.6%, seizures 17.1%. The mode of onset was metachronous in 71.4% and synchronous in 28.6%. The imaging techniques were cerebral CT scan in 82.9%, cerebral MRI in 40%, TAP scan in 22.9%. The metastatic lesions were supratentorial in 94.3% and single in 62.9%. The primary cancers found were breast cancer (31.4%), lung cancer (25.7%), prostate cancer (17.1%), thyroid cancer (5.7%), colon cancer (2.9%), and melanoma (2.9%). The therapeutic modalities were total resection (68.6%), radiotherapy (37.1%). Conclusion: Intracranial metastases are relatively frequent. There is a female sex predominance and the age group 50 - 59 years is the most affected. Brain metastases mostly occur in patients with a history of known primary tumor. The clinical signs mainly include signs of raised intracranial pressure, motor deficit, seizures and mental confusion. Cerebral CT Scan is the main imaging technique used. Most of the lesions are single and supratentorially located. The primary cancers most represented include breast cancer, lung cancer and prostate cancer. Surgery is the main treatment procedure. The adjuvant treatment (radiotherapy, chemotherapy) was limited.展开更多
BACKGROUND Small cell lung cancer(SCLC)is the most malignant type of lung cancer.Even in the latent period and early stage of the tumor,SCLC is prone to produce distant metastases with complex and diverse clinical man...BACKGROUND Small cell lung cancer(SCLC)is the most malignant type of lung cancer.Even in the latent period and early stage of the tumor,SCLC is prone to produce distant metastases with complex and diverse clinical manifestations.SCLC is most closely related to paraneoplastic syndrome,and some cases present as paraneoplastic peripheral neuropathy(PPN).PPN in SCLC appears early,lacks specificity,and often occurs before diagnosis of the primary tumor.It is easy to be misdiagnosed as a primary disease of the nervous system,leading to missed diagnosis and delayed diagnosis and treatment.CASE SUMMARY This paper reports two cases of SCLC with limb weakness as the first symptom.The first symptoms of one patient were rash,limb weakness,and abnormal electromyography.The patient was repeatedly referred to the hospital for limb weakness and rash for>1 year,during which time,treatment with hormones and immunosuppressants did not lead to significant improvement,and the condition gradually aggravated.The patient was later diagnosed with SCLC,and the dyskinesia did not worsen as the dermatomyositis improved after antineoplastic and hormone therapy.The second case presented with limb numbness and weakness as the first symptom,but the patient did not pay attention to it.Later,the patient was diagnosed with SCLC after facial edema caused by tumor thrombus invading the vein.However,he was diagnosed with extensive SCLC and died 1 year after diagnosis.CONCLUSION The two cases had PPN and abnormal electromyography,highlighting its correlation with early clinical indicators of SCLC.展开更多
BACKGROUND This manuscript describes the first known cases of sick sinus syndrome(SSS)associated with the use of anlotinib in non-small cell lung cancer patients,highlighting the need for increased vigilance and cardi...BACKGROUND This manuscript describes the first known cases of sick sinus syndrome(SSS)associated with the use of anlotinib in non-small cell lung cancer patients,highlighting the need for increased vigilance and cardiac monitoring.CASE SUMMARY Two patients with non-small cell lung cancer developed SSS after 15 months and 5 months of anlotinib treatment,respectively,presenting with syncope and palpit-ations.Electrocardiogram confirmed SSS,and different treatment approaches were taken for each patient.One patient received a dual-chamber permanent pacemaker,while the other discontinued the medication and experienced symptom resolution.CONCLUSION Anlotinib can induce SSS,suggesting that cardiac monitoring is crucial during anlotinib treatment.Individualized management strategies are necessary for affected individuals.展开更多
BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery ...BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.展开更多
Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mou...Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mouse model of insomnia was established by intraperitoneal injection of para-chlorophenylalanine.Forty-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive days.The open field test and pentobarbital-induced sleeping test were conducted.LC-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating insomnia.Finally,key targets were validated using RT-qPCR.Results:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep duration.Metabolomics and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of SXLJF.Specifically,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,respectively.RT-qPCR results supported the role of TH in the mechanism of SXLJF in treating insomnia.Conclusion:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.展开更多
The article concluded that network pharmacology provides new ideas and insights into the molecular mechanism of traditional Chinese medicine(TCM)treatment of cancer.TCM is a new choice and hot spot in the field of can...The article concluded that network pharmacology provides new ideas and insights into the molecular mechanism of traditional Chinese medicine(TCM)treatment of cancer.TCM is a new choice and hot spot in the field of cancer treatment.We have also previously published studies on TCM and network pharmacology.In this letter,we summarize the new paradigm of network pharmacology in cancer treatment mechanisms.展开更多
This study examines the pivotal findings of the network meta-analysis of Zhou et al,which evaluated the efficacy of hepatic arterial infusion chemotherapy and combination therapies for advanced hepatocellular carcinom...This study examines the pivotal findings of the network meta-analysis of Zhou et al,which evaluated the efficacy of hepatic arterial infusion chemotherapy and combination therapies for advanced hepatocellular carcinoma(HCC).This meta-analysis suggests that therapeutic combinations have greater efficacy than do standard treatments.The article highlights the key insights that have the potential to shift current clinical practice and enhance outcomes for patients with advanced HCC.Additionally,this article discusses further research that can be conducted to optimize these treatments and achieve personalized care for patients with HCC.展开更多
BACKGROUND Microvascular invasion(MVI)is a significant risk factor for recurrence and metastasis following hepatocellular carcinoma(HCC)surgery.Currently,there is a paucity of preoperative evaluation approaches for MV...BACKGROUND Microvascular invasion(MVI)is a significant risk factor for recurrence and metastasis following hepatocellular carcinoma(HCC)surgery.Currently,there is a paucity of preoperative evaluation approaches for MVI.AIM To investigate the predictive value of texture features and radiological signs based on multiparametric magnetic resonance imaging in the non-invasive preoperative prediction of MVI in HCC.METHODS Clinical data from 97 HCC patients were retrospectively collected from January 2019 to July 2022 at our hospital.Patients were classified into two groups:MVI-positive(n=57)and MVI-negative(n=40),based on postoperative pathological results.The correlation between relevant radiological signs and MVI status was analyzed.MaZda4.6 software and the mutual information method were employed to identify the top 10 dominant texture features,which were combined with radiological signs to construct artificial neural network(ANN)models for MVI prediction.The predictive performance of the ANN models was evaluated using area under the curve,sensitivity,and specificity.ANN models with relatively high predictive performance were screened using the DeLong test,and the regression model of multilayer feedforward ANN with backpropagation and error backpropagation learning method was used to evaluate the models’stability.RESULTS The absence of a pseudocapsule,an incomplete pseudocapsule,and the presence of tumor blood vessels were identified as independent predictors of HCC MVI.The ANN model constructed using the dominant features of the combined group(pseudocapsule status+tumor blood vessels+arterial phase+venous phase)demonstrated the best predictive performance for MVI status and was found to be automated,highly operable,and very stable.CONCLUSION The ANN model constructed using the dominant features of the combined group can be recommended as a noninvasive method for preoperative prediction of HCC MVI status.展开更多
BACKGROUND Wilson's disease(WD)is a rare metabolic disorder of copper accumulation in organs such as liver,brain,and cornea.Diagnoses and treatments are challenging in settings,where advanced diagnostic tests are ...BACKGROUND Wilson's disease(WD)is a rare metabolic disorder of copper accumulation in organs such as liver,brain,and cornea.Diagnoses and treatments are challenging in settings,where advanced diagnostic tests are unavailable,copper chelating agents are frequently scarce,healthcare professionals lack disease awareness,and medical follow-ups are limited.Prompt diagnoses and treatments help prevent complications,improve patients’quality of life,and ensure a normal life expectancy.The clinical presentations and outcomes of WD can vary within a single family.CASE SUMMARY We present the cases of two siblings(19 and 27 years)from a consanguineous family in rural Ecuador,diagnosed as having WD during a family screening.The male patient,diagnosed at age 19 after his brother’s death from acute liver failure,presented with compensated cirrhosis,neurological symptoms,and bilateral Kayser-Fleischer rings.He developed progressive neurological deterioration during an irregular treatment with D-penicillamine due to medication shortages.His condition improved upon switching to trientine tetrahydrochloride,and his neurological symptoms improved over an 8-year period of follow-ups.The female patient,diagnosed at age 10,exhibited only biochemical alterations.Her treatment history was similar;however,she remained asymptomatic without disease progression over the same follow-up period.We discuss the potential influence of epigenetic mechanisms and modifier genes on the various phenotypes,emphasizing the need for research in these areas to optimize therapeutic strategies.CONCLUSION Our patients’medical histories show how early diagnosis and treatment can prevent disease progression;and,how suboptimal treatments impact disease outcomes.展开更多
This editorial discusses a case report recently published in the World Journal of Clinical Cases.The report describes the clinical presentation,imaging,diagnosis,and treatment of a patient with tuberous sclerosis comp...This editorial discusses a case report recently published in the World Journal of Clinical Cases.The report describes the clinical presentation,imaging,diagnosis,and treatment of a patient with tuberous sclerosis complex(TSC)combined with primary lymphedema(PLE).Additionally,it retrospectively analyzes the data of 16 previously reported cases of children with TSC combined with PLE to summarize the epidemiology,genetic diagnosis,and current main treatments of these patients.The report also speculates on the pathological and physiological mechanisms underlying TSC combined with PLE.TSC combined with PLE is rare;therefore,the report provides a theoretical basis for understanding the pathophysiological mechanisms and treatment options for patients with TSC and PLE.Comprehensive clinical management of TSC is essential due to the diverse and multiorgan nature of its manifestations,often requiring a multidisciplinary approach for newly diagnosed cases.展开更多
文摘Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.
文摘The objectives of this work were to evaluate the surgical activities carried out in the general surgery department of the Reference Health Center of Commune I of Bamako, to describe the sociodemographic characteristics of the operated patients, to determine the main pathologies encountered and to evaluate qualitatively the result of the treatment. In order to improve performance, and the quality of care, and to identify common pathologies in the surgical department, we undertook a retrospective study on surgical activities from January 2009 to December 2010. At the end of this study, out of 474 men and 187 women (equal sex ratio 2.53);we were able to determine the frequency of surgical pathologies. Farmers, housewives and pupils/students were the most represented with 25.9% respectively;20% and 13.3%. The most frequently observed pathologies were wall hernia (44.8%), prostate adenoma (12%) and acute appendicitis (10.5%). The average length of hospitalization was 3.43 days. Infectious complications affected 25 patients (3.8% of cases) and a death rate of 0.45% (i.e. 3 patients). The average cost of care was 53,500 FCFA. Indeed, the reality of surgical practice in health centers was not the same because of the level of skills of practicing surgeons.
文摘Introduction: Superior mesenteric artery syndrome (SMAS), a rare diagnosis due to compression of the third duodenum between the superior mesenteric artery (SMA) and the aorta resulting in bowel obstruction, may lead to severe malnutrition. We report two cases of patients hospitalised in the Internal Medicine, Endocrinology, Diabetology, and Nutrition Department of the National Hospital Center (NHC) of Pikine. Observations: Patient 1: A 35-year-old female was referred for an aetiological diagnosis due to a rapid weight loss of 15 kilograms in one month, accompanied by persistent vomiting, following an appendectomy performed a month before admission. Upon clinical examination, she presented severe malnutrition (Buzby index of 76%), early post-prandial chronic vomiting, and a poor general condition. An abdominal CT scan revealed aortomesenteric clamp syndrome (AMCS) with an angulation between the aorta and the SMA of 13˚. The underlying cause in this patient was severe malnutrition. Fortunately, her condition improved with medical treatment. Patient 2: We report the case of a 30-year-old female hospitalized due to unusual weight-bearing post-prandial epigastric pain and intermittent vomiting over the past six months. Upon physical examination at admission, she exhibited severe malnutrition with a body mass index (BMI) of 14 kg/m<sup>2</sup>, a Buzby index of 71%, trophic disorders, and a stage IV general condition assessment according to the World Health Organization (WHO). An abdominal CT scan revealed AMCS with an angle between the aorta and the SMA of 22˚ and an aortomesenteric space of 4 mm. The outcome was poor with medical treatment failure and, unfortunately, the patient died before surgery. Conclusion: SMAS is rarely evoked in clinical practice despite the presence of contributing factors and suggestive clinical signs. The prognosis depends on management time.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
基金funding from King Saud University through Researchers Supporting Project number(RSP2024R387),King Saud University,Riyadh,Saudi Arabia.
文摘The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.
文摘Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.
文摘Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-RP23066).
文摘This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary order.The HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered class.The total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,respectively.The proposed model is tested separately for unique solutions and existence on bi intervals.The numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons Polynomial.The proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler Law.The cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said disease.This study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered 1000.The obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.
基金the Research Grant of Kwangwoon University in 2024.
文摘Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.
文摘Background: The incidence of intracranial metastases (ICMET) has been steadily rising, and its frequency with respect to primary brain tumours is relatively high. Objective: The objectives of this study were to elucidate the current epidemiology and describe the clinical, diagnostic and therapeutic features of ICMET in Yaounde. Method and findings: A descriptive cross-sectional study was done in the neurosurgery departments of the General and Central Hospitals of Yaounde during the period from January 2016 to December 2022. We included all medical booklets of patients admitted for a tumoral intracranial expansive process with our target population being patients with histological evidence of ICMET, and did a retrospective inclusion of data using a pre-established technical form aimed at collecting sociodemographic data, clinical data, paraclinical data, and the treatment procedures. Analysis was done using the SPSS statistical software. A total of 614 cases of intracranial tumors were included among whom 35 presented histological evidence of ICMET. This gives a frequency of 5.7%. The sex ratio was 0.94, the mean age was 55.68 +/- 14.4 years, extremes 28 and 86 years and the age range 50 - 59 was affected in 28.57% of cases. The clinical presentation included signs of raised intracranial pressure (headache, blurred vision, vomiting) in 26 cases (74.3%), motor deficit 48.6%, seizures 17.1%. The mode of onset was metachronous in 71.4% and synchronous in 28.6%. The imaging techniques were cerebral CT scan in 82.9%, cerebral MRI in 40%, TAP scan in 22.9%. The metastatic lesions were supratentorial in 94.3% and single in 62.9%. The primary cancers found were breast cancer (31.4%), lung cancer (25.7%), prostate cancer (17.1%), thyroid cancer (5.7%), colon cancer (2.9%), and melanoma (2.9%). The therapeutic modalities were total resection (68.6%), radiotherapy (37.1%). Conclusion: Intracranial metastases are relatively frequent. There is a female sex predominance and the age group 50 - 59 years is the most affected. Brain metastases mostly occur in patients with a history of known primary tumor. The clinical signs mainly include signs of raised intracranial pressure, motor deficit, seizures and mental confusion. Cerebral CT Scan is the main imaging technique used. Most of the lesions are single and supratentorially located. The primary cancers most represented include breast cancer, lung cancer and prostate cancer. Surgery is the main treatment procedure. The adjuvant treatment (radiotherapy, chemotherapy) was limited.
基金Supported by Science and Technology Plan Project of Jiaxing,No.2021AD30044Supporting Discipline of Neurology in Jiaxing,No.2023-ZC-006Affiliated Hospital of Jiaxing University,No.2020-QMX-16.
文摘BACKGROUND Small cell lung cancer(SCLC)is the most malignant type of lung cancer.Even in the latent period and early stage of the tumor,SCLC is prone to produce distant metastases with complex and diverse clinical manifestations.SCLC is most closely related to paraneoplastic syndrome,and some cases present as paraneoplastic peripheral neuropathy(PPN).PPN in SCLC appears early,lacks specificity,and often occurs before diagnosis of the primary tumor.It is easy to be misdiagnosed as a primary disease of the nervous system,leading to missed diagnosis and delayed diagnosis and treatment.CASE SUMMARY This paper reports two cases of SCLC with limb weakness as the first symptom.The first symptoms of one patient were rash,limb weakness,and abnormal electromyography.The patient was repeatedly referred to the hospital for limb weakness and rash for>1 year,during which time,treatment with hormones and immunosuppressants did not lead to significant improvement,and the condition gradually aggravated.The patient was later diagnosed with SCLC,and the dyskinesia did not worsen as the dermatomyositis improved after antineoplastic and hormone therapy.The second case presented with limb numbness and weakness as the first symptom,but the patient did not pay attention to it.Later,the patient was diagnosed with SCLC after facial edema caused by tumor thrombus invading the vein.However,he was diagnosed with extensive SCLC and died 1 year after diagnosis.CONCLUSION The two cases had PPN and abnormal electromyography,highlighting its correlation with early clinical indicators of SCLC.
文摘BACKGROUND This manuscript describes the first known cases of sick sinus syndrome(SSS)associated with the use of anlotinib in non-small cell lung cancer patients,highlighting the need for increased vigilance and cardiac monitoring.CASE SUMMARY Two patients with non-small cell lung cancer developed SSS after 15 months and 5 months of anlotinib treatment,respectively,presenting with syncope and palpit-ations.Electrocardiogram confirmed SSS,and different treatment approaches were taken for each patient.One patient received a dual-chamber permanent pacemaker,while the other discontinued the medication and experienced symptom resolution.CONCLUSION Anlotinib can induce SSS,suggesting that cardiac monitoring is crucial during anlotinib treatment.Individualized management strategies are necessary for affected individuals.
基金Supported by Joint Funds for the Innovation of Science and Technology,Fujian Province,No.2023Y9187 and No.2021Y9057.
文摘BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.
基金Science Foundation of Hunan Province(2021JJ40510)General Guidance Project of Hunan Health Commission(202203074169)+1 种基金Clinical Medical Technology Innovation Guidance Project of Hunan Province(2021SK51901)and Key Guiding Projects of Hunan Health Commission(20201918)for supporting this study.
文摘Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mouse model of insomnia was established by intraperitoneal injection of para-chlorophenylalanine.Forty-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive days.The open field test and pentobarbital-induced sleeping test were conducted.LC-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating insomnia.Finally,key targets were validated using RT-qPCR.Results:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep duration.Metabolomics and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of SXLJF.Specifically,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,respectively.RT-qPCR results supported the role of TH in the mechanism of SXLJF in treating insomnia.Conclusion:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.
文摘The article concluded that network pharmacology provides new ideas and insights into the molecular mechanism of traditional Chinese medicine(TCM)treatment of cancer.TCM is a new choice and hot spot in the field of cancer treatment.We have also previously published studies on TCM and network pharmacology.In this letter,we summarize the new paradigm of network pharmacology in cancer treatment mechanisms.
文摘This study examines the pivotal findings of the network meta-analysis of Zhou et al,which evaluated the efficacy of hepatic arterial infusion chemotherapy and combination therapies for advanced hepatocellular carcinoma(HCC).This meta-analysis suggests that therapeutic combinations have greater efficacy than do standard treatments.The article highlights the key insights that have the potential to shift current clinical practice and enhance outcomes for patients with advanced HCC.Additionally,this article discusses further research that can be conducted to optimize these treatments and achieve personalized care for patients with HCC.
基金Supported by the National Natural Science Foundation of China,No.81560278the Health Commission of Guangxi Zhuang Autonomous Region,No.Z20200953,No.G201903023,and No.Z-A20221157Scientific Research and Technology Development Project of Nanning,No.20213122.
文摘BACKGROUND Microvascular invasion(MVI)is a significant risk factor for recurrence and metastasis following hepatocellular carcinoma(HCC)surgery.Currently,there is a paucity of preoperative evaluation approaches for MVI.AIM To investigate the predictive value of texture features and radiological signs based on multiparametric magnetic resonance imaging in the non-invasive preoperative prediction of MVI in HCC.METHODS Clinical data from 97 HCC patients were retrospectively collected from January 2019 to July 2022 at our hospital.Patients were classified into two groups:MVI-positive(n=57)and MVI-negative(n=40),based on postoperative pathological results.The correlation between relevant radiological signs and MVI status was analyzed.MaZda4.6 software and the mutual information method were employed to identify the top 10 dominant texture features,which were combined with radiological signs to construct artificial neural network(ANN)models for MVI prediction.The predictive performance of the ANN models was evaluated using area under the curve,sensitivity,and specificity.ANN models with relatively high predictive performance were screened using the DeLong test,and the regression model of multilayer feedforward ANN with backpropagation and error backpropagation learning method was used to evaluate the models’stability.RESULTS The absence of a pseudocapsule,an incomplete pseudocapsule,and the presence of tumor blood vessels were identified as independent predictors of HCC MVI.The ANN model constructed using the dominant features of the combined group(pseudocapsule status+tumor blood vessels+arterial phase+venous phase)demonstrated the best predictive performance for MVI status and was found to be automated,highly operable,and very stable.CONCLUSION The ANN model constructed using the dominant features of the combined group can be recommended as a noninvasive method for preoperative prediction of HCC MVI status.
文摘BACKGROUND Wilson's disease(WD)is a rare metabolic disorder of copper accumulation in organs such as liver,brain,and cornea.Diagnoses and treatments are challenging in settings,where advanced diagnostic tests are unavailable,copper chelating agents are frequently scarce,healthcare professionals lack disease awareness,and medical follow-ups are limited.Prompt diagnoses and treatments help prevent complications,improve patients’quality of life,and ensure a normal life expectancy.The clinical presentations and outcomes of WD can vary within a single family.CASE SUMMARY We present the cases of two siblings(19 and 27 years)from a consanguineous family in rural Ecuador,diagnosed as having WD during a family screening.The male patient,diagnosed at age 19 after his brother’s death from acute liver failure,presented with compensated cirrhosis,neurological symptoms,and bilateral Kayser-Fleischer rings.He developed progressive neurological deterioration during an irregular treatment with D-penicillamine due to medication shortages.His condition improved upon switching to trientine tetrahydrochloride,and his neurological symptoms improved over an 8-year period of follow-ups.The female patient,diagnosed at age 10,exhibited only biochemical alterations.Her treatment history was similar;however,she remained asymptomatic without disease progression over the same follow-up period.We discuss the potential influence of epigenetic mechanisms and modifier genes on the various phenotypes,emphasizing the need for research in these areas to optimize therapeutic strategies.CONCLUSION Our patients’medical histories show how early diagnosis and treatment can prevent disease progression;and,how suboptimal treatments impact disease outcomes.
文摘This editorial discusses a case report recently published in the World Journal of Clinical Cases.The report describes the clinical presentation,imaging,diagnosis,and treatment of a patient with tuberous sclerosis complex(TSC)combined with primary lymphedema(PLE).Additionally,it retrospectively analyzes the data of 16 previously reported cases of children with TSC combined with PLE to summarize the epidemiology,genetic diagnosis,and current main treatments of these patients.The report also speculates on the pathological and physiological mechanisms underlying TSC combined with PLE.TSC combined with PLE is rare;therefore,the report provides a theoretical basis for understanding the pathophysiological mechanisms and treatment options for patients with TSC and PLE.Comprehensive clinical management of TSC is essential due to the diverse and multiorgan nature of its manifestations,often requiring a multidisciplinary approach for newly diagnosed cases.
