Pipeline Embolization Device (PED) and Flow Re-Direction Endoluminal Device (FRED) for Intracranial Aneurysms; A Comparative Systematic Review and Meta-Analysis Study.

BACKGROUND: When it comes to intracranial aneurysms, the quest for more effective treatments is ongoing. Flow diversion represents a growing advancement in this field. This review seeks to compare two variants of the endovascular flow diversion method: the Flow Re-Direction Endoluminal Device (FRED) and the Pipeline Embolization Device (PED). METHODS: A systematic review was conducted according to the PRISMA guideline using PubMed, Scopus, Web of Science, and Embase, using appropriate terms to compare PED and FRED in double-arm studies from conception until October 8th, 2023. RESULTS: The meta-analysis encompassed 1,769 patients, with a predominance of females (75.5%), among whom 973 patients underwent FRED procedures, while 651 received PED interventions. At six months, complete occlusion rates were 0.62 for FRED and 0.68 for PED (P = 0.68). At one year and the last follow-up, no significant differences were observed between FRED and PED, respectively. Adequate occlusion rates were similar between FRED and PED (0.82 vs 0.79, P = 0.68). FRED showed a statistically significant higher rate of good mRS scores at follow-up (1.00 vs. 0.97, P = 0.03). Hemorrhage and re-treatment rates were higher in PED (P < 0.01) without considering the rupture status of the aneurysms due to the lack of data. CONCLUSION: This meta-analysis suggests comparable efficacy but different safety profiles between FRED and PED in treating intracranial aneurysms. FRED demonstrated a higher rate of good mRS scores, while PED showed increased hemorrhage and re-treatment rates. Understanding these differences is crucial for informed decision-making in clinical practice.

Investigating the Safety and Efficacy of Therapeutic Hypothermia in Pediatric Severe Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

BACKGROUND: Prior guidelines recommended maintaining normothermia following traumatic brain injury (TBI), but recent studies suggest therapeutic hypothermia as a viable option in pediatric cases. However, some others demonstrated a higher mortality rate. Hence, the impact of hypothermia on neurological symptoms and overall survival remains contentious. METHODS: We conducted a systematic review and meta-analysis to evaluate the effects of hypothermia on neurological outcomes in pediatric TBI patients. The PubMed/Medline, Scopus, and Web of Science databases were searched until 1 January 2024 and data were analyzed using appropriate statistical methods. RESULTS: A total of eight studies, comprising nine reports, were included in this analysis. Our meta-analysis did not reveal significant differences in mortality (RR = 1.58; 95% CI = 0.89-2.82, p = 0.055), infection (RR = 0.95: 95% CI = 0.79-1.1, p = 0.6), arrhythmia (RR = 2.85: 95% CI = 0.88-9.2, p = 0.08), hypotension (RR = 1.54: 95% CI = 0.91-2.6, p = 0.10), intracranial pressure (SMD = 5.07: 95% CI = -4.6-14.8, p = 0.30), hospital length of stay (SMD = 0.10; 95% CI = -0.13-0.3, p = 0.39), pediatric intensive care unit length of stay (SMD = 0.04; 95% CI = -0.19-0.28, p = 0.71), hemorrhage (RR = 0.86; 95% CI = 0.34-2.13, p = 0.75), cerebral perfusion pressure (SMD = 0.158: 95% CI = 0.11-0.13, p = 0.172), prothrombin time (SMD = 0.425; 95% CI = -0.037-0.886, p = 0.07), and partial thromboplastin time (SMD = 0.386; 95% CI = -0.074-0.847, p = 0.10) between the hypothermic and non-hypothermic groups. However, the heart rate was significantly lower in the hypothermic group (-1.523 SMD = -1.523: 95% CI = -1.81--1.22 p < 0.001). CONCLUSIONS: Our findings challenge the effectiveness of therapeutic hypothermia in pediatric TBI cases. Despite expectations, it did not significantly improve key clinical outcomes. This prompts a critical re-evaluation of hypothermia's role as a standard intervention in pediatric TBI treatment.

The effects of tumor-derived supernatants (TDS) on cancer cell progression: A review and update on carcinogenesis and immunotherapy.

Tumors can produce bioactive substances called tumor-derived supernatants (TDS) that modify the immune response in the host body. This can result in immunosuppressive effects that promote the growth and spread of cancer. During tumorigenesis, the exudation of these substances can disrupt the function of immune sentinels in the host and reinforce the support for cancer cell growth. Tumor cells produce cytokines, growth factors, and proteins, which contribute to the progression of the tumor and the formation of premetastatic niches. By understanding how cancer cells influence the host immune system through the secretion of these factors, we can gain new insights into cancer diagnosis and therapy.

An in situ forming gelatin-based hydrogel loaded with soluble amniotic membrane promotes full-thickness wound regeneration in rats.

Objectives: Early effective treatment and appropriate coverage are vital for full-thickness wounds. Amnion membrane-derived products have recently emerged in tissue engineering. However, the optimal concentration, carrier for controlled release, and handling have remained challenges. This study aims to develop and optimize an in situ forming, amniotic-based hydrogel for wound healing. Materials and Methods: Here, a composite matrix was fabricated with gelatin hydrogel modified with methacrylate functional group conjugated (GelMA) and keratose (wt.1%), loaded with mesenchymal stem cells (MSCs, 1×105 cell/ml) and optimized soluble amniotic membrane (SAM, 0.5 mg/ml). The physicochemical properties of the final subject were evaluated in vitro and in vivo environments. Results: The results of the in vitro assay demonstrated that conjugation of the methacryloyl group with gelatin resulted in the formation of GelMA hydrogel (26.7±1.2 kPa) with higher mechanical stability. Modification of GelMA with a glycosaminoglycan sulfate (Keratose) increased controlled delivery of SAM (47.3% vs. 84.3%). Metabolic activity (93%) and proliferation (21.2 ± 1.5 µg/ml) of MSCs encapsulated in hydrogel improved by incorporation of SAM (0.5 mg/ml). Furthermore, the migration of fibroblasts was facilitated in the scratched assay by SAM (0.5 mg/ml)/MSCs (1×105 cell/ml) conditioned medium. The GelMA hydrogel groupes revealed regeneration of full-thickness skin defects in rats after 3 weeks due to the high angiogenesis (6.3 ± 0.3), cell migration, and epithelialization. Conclusion: The results indicated in situ forming and tunable GelMA hydrogels containing SAM and MSCs could be used as efficient substrates for full-thickness wound regeneration.

Prognostic risk factors for early outcomes of patients with myelomeningocele: a prospective study.

INTRODUCTION: Myelomeningocele (MMC) is a prevalent form of neural tube defect. Despite advancements in treatment, MMC still poses significant health risks, including complications leading to chronic disability and mortality. Identifying prognostic risk factors for early outcomes is crucial for tailored intervention strategies. METHODS: This prospective study involved newborns and infants diagnosed with MMC who underwent surgery between 2020 and 2023 at Urmia University of Medical Sciences. Demographic data and surgical outcomes were collected, and participants were followed up for six months. Statistical analyses were conducted using descriptive statistics, Chi-Square, and independent t-test. RESULTS: The study included 29 MMC cases, with an incidence rate of 1.4 per 10,000 live births. Lesions were predominantly located in the lumbar spine. Although mortality rates appeared to increase with ascending lesion sites, this trend was not statistically significant. Short-term outcomes revealed high morbidity and mortality rates, with neurological deficits being the most prevalent complication. Multivariable analysis identified head circumference as a significant predictor of adverse outcomes (IRR = 1.37, 95% CI = 1.02 to 1.86, p = 0.04). Furthermore, an increase in birth weight was associated with a reduction in the incidence of requiring a ventriculoperitoneal shunt (IRR = 0.99, 95% CI = 0.998 to 0.999, p = 0.02). CONCLUSION: This prospective study highlights prognostic risk factors for early outcomes in MMC patients, emphasizing the need for personalized intervention strategies. By addressing modifiable risk factors and implementing targeted interventions, healthcare providers can strive to improve outcomes and enhance the quality of life for MMC patients.

Predicting the Outcome and Survival of Patients with Spinal Cord Injury Using Machine Learning Algorithms: A Systematic Review.

BACKGROUND: Spinal cord injury (SCI) is a significant public health issue, leading to physical, psychological, and social complications. Machine learning (ML) algorithms have shown potential in diagnosing and predicting the functional and neurologic outcomes of subjects with SCI. ML algorithms can predict scores for SCI classification systems and accurately predict outcomes by analyzing large amounts of data. This systematic review aimed to examine the performance of ML algorithms for diagnosing and predicting the outcomes of subjects with SCI. METHODS: The literature was comprehensively searched for the pertinent studies from inception to May 25, 2023. Therefore, electronic databases of PubMed, Embase, Scopus, and Web of Science were systematically searched with individual search syntax. RESULTS: A total of 9424 individuals diagnosed with SCI across multiple studies were analyzed. Among the 21 studies included, 5 specifically aimed to evaluate diagnostic accuracy, while the remaining 16 focused on exploring prognostic factors or management strategies. CONCLUSIONS: ML and deep learning (DL) have shown great potential in various aspects of SCI. ML and DL algorithms have been employed multiple times in predicting and diagnosing patients with SCI. While there are studies on diagnosing acute SCI using DL algorithms, further research is required in this area.

Repeat single-session stereotactic radiosurgery for arteriovenous malformation: a systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery is the preferred option for treating brain arteriovenous malformation (AVM) when the risks associated with surgery outweigh the potential benefits. However, some patients require repeat radiosurgery due to residual AVM after the first procedure. This systematic review and meta-analysis aimed to investigate the safety and efficacy of repeated procedure of radiosurgery for AVM. METHOD: A systematic review was conducted according to the PRISMA guideline. The search was conducted on PubMed, Scopus, Embase, and Web of Science, using a pre-designed search string. Studies investigating the efficacy of repeat radiosurgery for residual AVM following initial single session radiosurgery were included. The risk of bias was assessed using the JBI tool. Meta-analysis and met-regression were performed to pool and inspect data. RESULTS: Our meta-analysis, with a mean follow-up of 45.57 months, reveals repeat radiosurgery as a viable option for arteriovenous malformations (AVMs), achieving a 60.82% obliteration rate with a mean time to obliteration of 33.18 months. Meta-regression identifies AVM volume and Spetzler-Martin (SM) grade as factors influencing obliteration, with smaller volume and lower SM grades associated with higher rates. Complications include 10.33% radiation-induced changes, 5.26% post-radiosurgery hemorrhage, 2.56% neurologic deficits, and 0.67% cyst formation. Heterogeneity in complications is primarily attributed to male proportion and SM grade, while factors influencing post-radiosurgery hemorrhage remain unclear. The type of radiosurgery, whether Gamma Knife Radiosurgery (GKRS) or LINAC, does not significantly impact outcomes. CONCLUSION: Repeat radiosurgery is a feasible, effective, and safe treatment for AVMs following failure of initial radiosurgery. When utilized in appropriate patient subgroups, it provides an acceptable risk-to-benefit profile. Feature studies are required to clarify its clear indications.

Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs?

Background and Aim: Staging liver fibrosis is important, and liver biopsy is the gold standard diagnostic tool. We aim to design and evaluate an artificial neural network (ANN) method by taking advantage of the Teaching Learning-Based Optimization (TLBO) algorithm for the prediction of liver fibrosis stage in blood donors and hepatitis C patients. Methods: We propose a method based on a selection of machine learning classification methods including multilayer perceptron (MLP) neural network, Naive Bayesian (NB), decision tree, and deep learning. Initially, the synthetic minority oversampling technique (SMOTE) is performed to address the imbalance in the dataset. Afterward, the integration of MLP and TLBO is implemented. Results: We propose a novel algorithm that reduces the number of required patient features to seven inputs. The accuracy of MLP using 12 features is 0.903, while that of the proposed MLP with TLBO is 0.891. Besides, the diagnostic accuracy of all methods, except the model designed with the Bayesian network, increases when the SMOTE balancer is applied. Conclusion: The decision tree-based deep learning methods show the highest levels of accuracy with 12 features. Interestingly, with the use of TLBO and seven features, MLP reached an accuracy rate of 0.891, which is quite satisfactory when compared with those of similar studies. The proposed model provides high diagnostic accuracy, while reducing the required number of properties from the samples. The results of our study show that the recruited algorithm of our study is more straightforward, with a smaller number of required properties and similar accuracy.

The safety and efficacy of bevacizumab in treatment of recurrent low-grade glioma: a systematic review and meta-analysis.

BACKGROUND: Central nervous system (CNS) tumors are among the most common malignancies in various age ranges. Low-grade glioma (LGG) can account for nearly 30% of pediatric CNS malignancies. Progression or recurrence after the first-line treatments is common among these patients. Therefore, more treatments are required. Bevacizumab as an anti-VEGF antibody has come into the spotlight recently and is especially used in relapse or recurrence settings. This review aims to study the safety and efficacy of bevacizumab for patients with recurrent LGG. METHODS: This study was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PubMed, Scopus, Web of Science, and Embase were comprehensively searched using the relevant key terms until 24th August 2023 to retrieve the studies that investigated clinical outcomes of bevacizumab in patients with recurrent LGG. All statistical analysis was performed by STATA v.17. RESULTS: A total of 1306 papers were gathered, out of which 13 were incorporated in the meta-analysis. The pooled incidence rate of treatment according to the RANO scale was 70% (95% CI = 43-98%) for objective response rate, 26% (95% CI = 58-96%) for partial response, 21% (95% CI = 15-28%) for minor response, 14% (95% CI = 3-24%) for complete response, 48% (95% CI = 37-59%) for stable disease, and 8% (95% CI = 4-11%) for progressive disease. Furthermore, according to progressive survival after treatment, it was 4% (95% CI = -1 to 9%) for 6-month PFS, 41% (95% CI = 32-50%) for 2-year PFS, and 29% (95% CI = 22-35%) for 3-year PFS. CONCLUSION: According to the RANO scale and PFS, clinicians should be aware that Bevacizumab could be a favorable alternative therapy for recurrent LGG. Furthermore, bevacizumab exhibits minimal toxicity and high tolerability in recurrent LGG.

Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide local control, symptom relief, and improved survival rates, but it poses challenges in selecting optimal candidates, determining dose and fractionation, monitoring for toxicity, and integrating with other modalities. Practical tools to predict patient outcomes are also needed. Machine learning (ML) is currently used to predict treatment outcomes. We aim to investigate the accuracy of ML in predicting treatment response and local failure of brain metastasis treated with SRS. METHODS: PubMed, Scopus, Web of Science (WoS), and Embase were searched until April 16th, which was repeated on October 17th, 2023 to find possible relevant papers. The study preparation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The statistical analysis was performed by the MIDAS package of STATA v.17. RESULTS: A total of 17 articles were reviewed, of which seven and eleven were related to the clinical use of ML in predicting local failure and treatment response. The ML algorithms showed sensitivity and specificity of 0.89 (95% CI: 0.84-0.93) and 0.87 (95% CI: 0.81-0.92) for predicting treatment response. The positive likelihood ratio was 7.1 (95% CI: 4.5-11.1), the negative likelihood ratio was 0.13 (95% CI: 0.08-0.19), and the diagnostic odds ratio was 56 (95% CI: 25-125). Moreover, the pooled estimates for sensitivity and specificity of ML algorithms for predicting local failure were 0.93 (95% CI: 0.76-0.98) and 0.80 (95% CI: 0.53-0.94). The positive likelihood ratio was 4.7 (95% CI: 1.6-14.0), the negative likelihood ratio was 0.09 (95% CI: 0.02-0.39), and the diagnostic odds ratio was 53 (95% CI: 5-606). CONCLUSION: ML holds promise in predicting treatment response and local failure in brain metastasis patients receiving SRS. However, further studies and improvements in the treatment process can refine the models and effectively integrate them into clinical practice.

Using mobile health in primiparous women: effect on awareness, attitude and choice of delivery type, semi-experimental.

BACKGROUND: One of the reasons for the increase in cesarean section is the lack of knowledge of mothers in choosing the type of delivery. The present study aimed to determine the effect of education through pregnancy application during pregnancy on awareness and attitude and choice of delivery type in primiparous women at Shahid Alavi Specialized Medical Center clinic in Mashhad. METHODS: This study was a semi-experimental type. Seventy primiparous pregnant women who had no restrictions for birth was selected. Sampling was randomized and purpose-based. The data collection tool was a questionnaire. The starting time of the training was considered from the end of the 27th week of pregnancy and continued with regular intervals until the end of the pregnancy. The questionnaires were completed once before the training and once after the training as a pre-test and post-test by the research units. SPSS software (version 26) and MacNemar test and descriptive statistics were used for data analysis. RESULTS: According to the results of the MacNemar test, a significant statistical difference was seen between women's knowledge and attitude after the training compared to before (p-value < 0.01). Choosing the type of birth was preferred before and after the training. But following the performance of women showed that only 62.86% of them chose natural birth. In fact, before the training, 40% and after 72.86% of women had chosen birth. CONCLUSION: Pregnancy education and application during pregnancy is effective in reducing the choice of cesarean section, so this application with the topic of birth and cesarean section has improved the level of attitude and also the positive attitude of pregnant women towards birth. Creation of facilities and promotion of different methods of painless childbirth and training of maternity staff to perform birth is expected.

Machine learning-enhanced drug testing for simultaneous morphine and methadone detection in urinary biofluids.

The simultaneous identification of drugs has considerable difficulties due to the intricate interplay of analytes and the interference present in biological matrices. In this study, we introduce an innovative electrochemical sensor that overcomes these hurdles, enabling the precise and simultaneous determination of morphine (MOR), methadone (MET), and uric acid (UA) in urine samples. The sensor harnesses the strategically adapted carbon nanotubes (CNT) modified with graphitic carbon nitride (g-C3N4) nanosheets to ensure exceptional precision and sensitivity for the targeted analytes. Through systematic optimization of pivotal parameters, we attained accurate and quantitative measurements of the analytes within intricate matrices employing the fast Fourier transform (FFT) voltammetry technique. The sensor's performance was validated using 17 training and 12 test solutions, employing the widely acclaimed machine learning method, partial least squares (PLS), for predictive modeling. The root mean square error of cross-validation (RMSECV) values for morphine, methadone, and uric acid were significantly low, measuring 0.1827 µM, 0.1951 µM, and 0.1584 µM, respectively, with corresponding root mean square error of prediction (RMSEP) values of 0.1925 µM, 0.2035 µM, and 0.1659 µM. These results showcased the robust resiliency and reliability of our predictive model. Our sensor's efficacy in real urine samples was demonstrated by the narrow range of relative standard deviation (RSD) values, ranging from 3.71 to 5.26%, and recovery percentages from 96 to 106%. This performance underscores the potential of the sensor for practical and clinical applications, offering precise measurements even in complex and variable biological matrices. The successful integration of g-C3N4-CNT nanocomposites and the robust PLS method has driven the evolution of sophisticated electrochemical sensors, initiating a transformative era in drug analysis.

Woven endo bridge device for recurrent intracranial aneurysms: A systematic review and meta-analysis.

BACKGROUND: Recurrent intracranial aneurysms present a significant clinical challenge, demanding innovative and effective treatment approaches. The Woven EndoBridge (WEB) device has emerged as a promising endovascular solution for managing these intricate cases. This study aims to assess the safety and efficacy of the WEB device in treating recurrent intracranial aneurysms. METHODS: We conducted a comprehensive search across multiple databases, including PubMed, Scopus, Embase, and Web of Science, from inception to June 5, 2023. Eligible studies focused on evaluating WEB device performance and included a minimum of five patients with recurrent intracranial aneurysms. The complete and adequate occlusion rates, neck remnant rates, and periprocedural complication rates were pooled using SATA V.17. RESULTS: Our analysis included five studies collectively enrolling 73 participants. Participant ages ranged from 52.9 to 65 years, with 64.4% being female. Aneurysms were wide-necked and predominantly located in the middle cerebral artery, basilar artery, and anterior cerebral artery. Previous treatments encompassed coiling, clipping, and the use of WEB devices. Our study found an overall adequate occlusion rate of 0.80 (95% CI 0.71-0.89), a complete occlusion rate of 0.39 (95% CI 0.28-0.50), and a neck remnant rate of 0.38 (95% CI 0.27-0.48). Periprocedural complications were reported at a rate of 0%, although heterogeneity was observed in this data. Notably, evidence of publication bias was identified in the reporting of periprocedural complication rates. CONCLUSION: Our findings suggest that the WEB device is associated with favorable outcomes for treating recurrent wide-neck intracranial aneurysms.

Acute spinal cord injury serum biomarkers in human and rat: a scoping systematic review.

STUDY DESIGN: Scoping systematic review. OBJECTIVES: To summarize the available experimental clinical and animal studies for the identification of all CSF and serum-derived biochemical markers in human and rat SCI models. SETTING: Tehran, Iran. METHODS: In this scoping article, we systematically reviewed the electronic databases of PubMed, Scopus, WOS, and CENTRAL to retrieve current literature assessing the levels of different biomarkers in human and rat SCI models. RESULTS: A total of 19,589 articles were retrieved and 6897 duplicated titles were removed. The remaining 12,692 studies were screened by their title/abstract and 12,636 were removed. The remaining 56 were considered for full-text assessment, and 11 papers did not meet the criteria, and finally, 45 studies were included. 26 studies were human observational studies comprising 1630 patients, and 19 articles studied SCI models in rats, including 832 rats. Upon reviewing the literature, we encountered a remarkable heterogeneity in terms of selected biomarkers, timing, and method of measurement, studied models, extent, and mechanism of injury as well as outcome assessment measures. CONCLUSIONS: The specific expression and distribution patterns of biomarkers in relation to spinal cord injury (SCI) phases, and their varied concentrations over time, suggest that cerebrospinal fluid (CSF) and blood biomarkers are effective measures for assessing the severity of SCI.

Low-Protein Diets Differentially Regulate Energy Balance during Thermoneutral and Heat Stress in Cobb Broiler Chicken (Gallus domesticus).

The objective was to assess whether low-protein (LP) diets regulate food intake (FI) and thermogenesis differently during thermoneutral (TN) and heat stress (HS) conditions. Two-hundred-day-old male broiler chicks were weight-matched and assigned to 36 pens with 5-6 chicks/pen. After 2 weeks of acclimation, birds were subjected into four groups (9 pens/group) including (1) a normal-protein diet under TN (ambient temperature), (2) an LP diet under TN, (3) a normal-protein diet under HS (35 °C for 7 h/day), and (4) an LP diet under HS, for 4 weeks. During HS, but not TN, LP tended to decrease FI, which might be associated with a lower mRNA abundance of duodenal ghrelin and higher GIP during HS. The LP group had a higher thermal radiation than NP under TN, but during HS, the LP group had a lower thermal radiation than NP. This was linked with higher a transcript of muscle ß1AR and AMPKα1 during TN, but not HS. Further, LP increased the gene expression of COX IV during TN but reduced COX IV and the sirtuin 1 abundance during HS. The dietary protein content differentially impacted plasma metabolome during TN and HS with divergent changes in amino acids such as tyrosine and tryptophan. Compared to NP, LP had increased abundances of p_Tenericutes, c_Mollicutes, c_Mollicutes_RF9, and f_tachnospiraceae under HS. Overall, LP diets may mitigate the negative outcome of heat stress on the survivability of birds by reducing FI and heat production. The differential effect of an LP diet on energy balance during TN and HS is likely regulated by gut and skeletal muscle and alterations in plasma metabolites and cecal microbiota.

The effect of machine learning algorithms in the prediction, and diagnosis of meningitis: A systematic review.

Background and Aims: This systematic review aimed to evaluating the effectiveness of machine learning (ML) algorithms for the prediction and diagnosis of meningitis. Methods: On November 12, 2022, a systematic review was carried out using a keyword search in the reliable scientific databases PubMed, EMBASE, Scopus, and Web of Science. The recommendations of Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) were adhered to. Studies conducted in English that employed ML to predict and identify meningitis were deemed to match the inclusion criteria. The eligibility requirements were used to independently review the titles and abstracts. The whole text was then obtained and independently reviewed in accordance with the eligibility requirements. Results: After all the research matched the inclusion criteria, a total of 16 studies were added to the systematic review. Studies on the application of ML algorithms in the three categories of disease diagnosis ability (8.16) and disease prediction ability (8.16) (including cases related to identifying patients (50%), risk of death in patients (25%), the consequences of the disease in childhood (12.5%), and its etiology [12.5%]) were placed. Among the ML algorithms used in this study, logistic regression (LR) (4.16, 25%) and multiple logistic regression (MLR) (4.16, 25%) were the most used. All the included studies indicated improvements in the processes of diagnosis, prediction, and disease outbreak with the help of ML algorithms. Conclusion: The results of the study showed that in all included studies, ML algorithms were an effective approach to facilitate diagnosis, predict consequences for risk classification, and improve resource utilization by predicting the volume of patients or services as well as discovering risk factors. The role of ML algorithms in improving disease diagnosis was more significant than disease prediction and prevalence. Meanwhile, the use of combined methods can optimize differential diagnoses and facilitate the decision-making process for healthcare providers.

Acute Ischemic Stroke in a Patient with Multiple Sclerosis after Initiating Teriflunomide Treatment: A Challenging Case.

Multiple sclerosis is an autoimmune disease of the central nervous system, during which vascular events, including atherosclerosis, are more common and progress faster. Teriflunomide (TFN) is an oral drug that studies have indicated has low side effects alongside high efficiency. In this article, a middle-aged woman with multiple sclerosis was introduced, whose medication was changed to TFN. Thirty-five days later, she presented with focal neurologic symptoms, and investigations reported a lacunar infarction. Having excluded potential causes of acute ischemic stroke, such as vascular and rheumatologic factors, the only identifiable factor was the introduction of a new medication. The process of conclusively attributing TFN as the causative agent requires further clarification in future studies.

Effects of Auriculotherapy on Gestational Hypertension: Randomized Controlled Trial Study.

Background: This study aims to observe how auriculotherapy acts as a nonpharmacological treatment for pregnant women's gestational hypertension. Materials and Methods: This study was a randomized controlled trial. Eighty patients were with gestational hypertension recruited and divided into control (n = 40) and intervention (n = 40) groups. The control group just received the usual perinatal care. The intervention group received one month of auriculotherapy in addition to the usual care. Blood pressure was measured before and 15 minutes after rest in both groups twice a week. The data were analyzed using descriptive statistics and inferential tests. Results: The mean systolic blood pressure, based on the Mann-Whitney test, was not statistically significant between the two groups before the intervention and in the first two weeks after the intervention (p >0.05); however, after the third week of intervention, the mean systolic blood pressure in the intervention group was significantly lower than that in the control group (p <0.001). As per the Mann-Whitney test, the mean diastolic blood pressure was not statistically significant between the two groups before the intervention and the first week after the intervention (p <0.05). However, after the second week of intervention, the mean diastolic blood pressure in the intervention group was significantly lower than that in the control group, and this decrease was highest in the fourth week of the intervention (p <0.001). Conclusions: This study demonstrated that auriculotherapy would reduce blood pressure in pregnant women suffering from hypertension.

Disruption of hepatic mitochondrial pyruvate and amino acid metabolism impairs gluconeogenesis and endurance exercise capacity in mice.

Exercise robustly increases the glucose demands of skeletal muscle. This demand is met by not only muscle glycogenolysis but also accelerated liver glucose production from hepatic glycogenolysis and gluconeogenesis to fuel mechanical work and prevent hypoglycemia during exercise. Hepatic gluconeogenesis during exercise is dependent on highly coordinated responses within and between muscle and liver. Specifically, exercise increases the rate at which gluconeogenic precursors such as pyruvate/lactate or amino acids are delivered from muscle to the liver, extracted by the liver, and channeled into glucose. Herein, we examined the effects of interrupting hepatic gluconeogenic efficiency and capacity on exercise performance by deleting mitochondrial pyruvate carrier 2 (MPC2) and/or alanine transaminase 2 (ALT2) in the liver of mice. We found that deletion of MPC2 or ALT2 alone did not significantly affect time to exhaustion or postexercise glucose concentrations in treadmill exercise tests, but mice lacking both MPC2 and ALT2 in hepatocytes (double knockout, DKO) reached exhaustion faster and exhibited lower circulating glucose during and after exercise. Use of 2H/1³C metabolic flux analyses demonstrated that DKO mice exhibited lower endogenous glucose production owing to decreased glycogenolysis and gluconeogenesis at rest and during exercise. Decreased gluconeogenesis was accompanied by lower anaplerotic, cataplerotic, and TCA cycle fluxes. Collectively, these findings demonstrate that the transition of the liver to the gluconeogenic mode is critical for preventing hypoglycemia and sustaining performance during exercise. The results also illustrate the need for interorgan cross talk during exercise as described by the Cahill and Cori cycles.NEW & NOTEWORTHY Martino and colleagues examined the effects of inhibiting hepatic gluconeogenesis on exercise performance and systemic metabolism during treadmill exercise in mice. Combined inhibition of gluconeogenesis from lactate/pyruvate and alanine impaired exercise endurance and led to hypoglycemia during and after exercise. In contrast, suppressing either pyruvate-mediated or alanine-mediated gluconeogenesis alone had no effect on these parameters. These findings provide new insight into the molecular nodes that coordinate the metabolic responses of muscle and liver during exercise.

The safety and efficacy of dabrafenib and trametinib in patients with glioma: A systematic review and meta-analysis.

BACKGROUND: Dabrafenib and trametinib represent targeted therapy options under investigation for treatment of gliomas harboring BRAF V600 mutations. We systematically reviewed the literature and conducted meta-analyses to assess the efficacy and safety of these agents. METHODS: PubMed, Embase, and Scopus were searched from inception to September 2023 for studies examining dabrafenib and/or trametinib for gliomas. Outcomes included response rates (ORR, CR, PR), progression rates (PD), 6- and 12-month PFS, adverse events, and dosing modifications. Meta-analyses were conducted using random effect models. RESULTS: Nine studies met the inclusion criteria. Meta-analysis demonstrated overall response rates (ORR) of 50% (95% confidence interval (CI): 35-65%) for low-grade gliomas (LGG) and 40% (95% CI: 29-51%) for high-grade gliomas (HGG). Pooled ORR was 45% (95% CI: 36-54%) for both glioma grades. The complete response rate was 13% (95% CI: 05-27%) for HGG and 5% (95% CI: 1-10%) for both LGG and HGG. Six-month progression-free survival (PFS) rates reached 87% in LGG and 67% in HGG and a pooled 6-month PFS 78% (95% CI: 58-98%), declining at 12 months to 67% and 44%, respectively, with a pooled 12-month PFS 56% (95% CI: 34-79%). Grade 1-4 adverse events occurred in 100% of LGG and 63% of HGG patients. CONCLUSIONS: Dabrafenib and trametinib demonstrate promising anti-tumor efficacy in gliomas, particularly low-grade tumors, achieving durable disease stabilization in many patients. However, toxicity significantly limited tolerability. Additional research should further examine efficacy and refine safe administration protocols across glioma subtypes.