[Thinking on the classification of non-invasive brain stimulation as neuromodulation technique].

Neuromodulation techniques have gradually evolved from electrical or chemical methods to various physical stimulation techniques including electricity, magnetism, sound, light, heat, and more. However, the clinical efficacy and mechanisms of each stimulation technique or paradigm vary greatly. To facilitate the understanding of the therapeutic effects and mechanisms of different neuromodulation techniques, combined with current clinical practice, the author takes the classification of non-invasive transcranial electrical stimulation as an example and proposes the idea of using energy magnitude as the primary classification and different media/stimulation routes as the secondary classification. This classification emphasizes the energy essence of various physical stimuli, followed by the transmission carriers of physical stimuli. This classification method helps to guide and design neuromodulation paradigms for different target symptoms in various brain disorders, which is beneficial for better serving clinical diagnosis and treatment. The Expert Forum also discusses the advantages and disadvantages of various neuromodulation technologies and their clinical applications.

Comparison of clinicopathological features between cerebral cystic and alveolar echinococcosis: analysis of 27 cerebral echinococcosis cases in Xinjiang, China.

BACKGROUND: Cerebral echinococcosis is relatively rare, and it is important to distinguish cerebral cystic echinococcosis (CCE) from cerebral alveolar echinococcosis (CAE) in terms of pathological diagnosis. We aim to describe the different clinicopathological features among patients with CCE and CAE. METHODS: We collected 27 cases of cerebral echinococcosis which were diagnosed in the Department of Pathology of the First Affiliated Hospital of Xinjiang Medical University from January 1, 2012, to June 30, 2023. We compared the patients' clinical characteristics, MRI features, and pathologic manifestations of CCE and CAE. RESULTS: Among 27 cases of cerebral echinococcosis, 23 cases were CAE and 4 cases were CCE. The clinical manifestations of both CCE and CAE patients mainly included headache (21 patients, 77.78%), limb movement disorders (6 patients, 22.22%), epileptic seizures (4 patients, 14.81%) and visual disturbances (2 patients, 7.41%). The average onset age of CAE cases was 34.96 ± 11.11 years, which was 9.00 ± 7.26 years in CCE cases. All CAE patients presented with multiple involvements in the brain and extracranial organs while all CCE patients observed a solitary lesion in the brain and 3 CCE cases had no extracranial involvement. Lesions of CCE in MRI showed a single isolated circular, which was well demarcated from the surrounding tissues and with no obvious edema around the lesions, whereas CAE lesions presented as multiple intracranial lesions, with blurred edges and edema around the lesions, and multiple small vesicles could be observed in the lesions. The edge of CAE lesions could be enhanced, while CCE lesions have no obvious enhancement. CCE foci were clear cysts with a wall of about 0.1 cm. Microscopically, the walls of the cysts were characterized by an eosinophilic keratin layer, which was flanked on one side by basophilic germinal lamina cells, which were sometimes visible as protocephalic nodes. While the CAE lesion was a nodular structure with a rough and uneven nodule surface, and the cut section was cystic and solid; microscopically, the CAE lesion had areas of coagulative necrosis, and the proto-cephalic nodes were barely visible. Inflammatory cell areas consisting of macrophages, lymphocytes, epithelioid cells, plasma cells, eosinophils, and fibroblasts can be seen around the lesion. Brain tissues in the vicinity of the inflammatory cell areas may show apoptosis, degeneration, necrosis, and cellular edema, while brain tissues a little farther away from the lesion show a normal morphology. CONCLUSIONS: With the low incidence of brain echinococcosis, the diagnosis of echinococcosis and the differential diagnosis of CAE and CCE are challenging for pathologists. Grasping the different clinical pathology characteristics of CAE and CCE is helpful for pathologists to make accurate diagnoses.

Pediatric Cranial Ultrasound Revisited: A Comprehensive Review.

ABSTRACT: Cranial ultrasound (CUS) is an indispensable tool in the evaluation of intracranial pathology in premature and term neonates and older infants. Familiarity with standard cranial ultrasound techniques and parameters, normal anatomy, and commonly encountered abnormalities is crucial for providing appropriate care for these patients. This review provides a comprehensive overview of cranial ultrasound in clinical practice.

Single-centre real-life observational study on mortality and outcomes: decompressive craniectomy and brain death in traumatic brain injury, haemorrhage, and other cerebral diseases.

BACKGROUND: Decompressive hemicraniectomy (DHC) is used after severe brain damages with elevated, refractory intracranial pressure (ICP). In a non age-restricted population, mortality rates and long-term outcomes following DHC are still unclear. This study's objectives were to examine both, as well as to identify predictors of unfavourable outcomes. METHODS: We undertook a retrospective observational analysis of patients aged 18 years and older who underwent DHC at the University Hospital of Bonn between 2018 and 2020, due to traumatic brain injury (TBI), haemorrhage, tumours or infections. Patient outcomes were assessed by conducting telephone interviews, utilising questionnaires for modified Rankin Scale (mRS) and extended Glasgow Outcome scale (GOSE). We evaluated the health-related quality of life using the EuroQol (EQ-5D-5L) scale. RESULTS: A total of 144 patients with a median age of 58.5 years (range: 18 to 85 years) were evaluated. The mortality rate was 67%, with patients passing away at a median of 6.0 days (IQR [1.9-37.6]) after DHC. Favourable outcomes, as assessed by the mRS and GOSE were observed in 10.4% and 6.3% of patients, respectively. Cox regression analysis revealed a 2.0% increase in the mortality risk for every year of age (HR = 1.017; 95% CI [1.01-1.03]; p = 0.004). Uni- and bilateral fixed pupils were associated with a 1.72 (95% CI [1.03-2.87]; p = 0.037) and 3.97 (95% CI [2.44-6.46]; p < 0.001) times higher mortality risk, respectively. ROC-analysis demonstrated that age and pupillary reactivity predicted 6-month mortality with an AUC of 0.77 (95% CI [0.69-0.84]). The only parameter significantly associated with a better quality of life was younger age. CONCLUSIONS: Following DHC, mortality remains substantial, and favourable outcomes occur rarely. Particularly in elderly patients and in the presence of clinical signs of herniation, mortality rates are notably elevated. Hence, the indication for DHC should be set critically.

Difficulties in the Diagnostics and Treatment of Hashimoto's Encephalopathy-A Systematic and Critical Review.

Hashimoto's encephalopathy (HE) has been a poorly understood disease. It has been described in all age group, yet, there is no specific HE marker. Additionally, the treatment data in the available studies are frequently divergent and contradictory. Therefore, the aim of our systematic and critical review is to evaluate the diagnosis and treatment of HE in view of the latest findings. The databases browsed comprised PubMed, Scopus, and Google Scholar as well as Cochrane Library, and the search strategy included controlled vocabulary and keywords. A total of 2443 manuscripts were found, published since the beginning of HE research until February 2024. In order to determine validity of the data collected from studies, bias assessment was performed using RoB 2 tool. Ultimately, six studies were included in our study. HE should be considered in the differential diagnosis in patients with psychiatric and neurological symptoms. According to our findings, negative thyroid peroxidase antibodies (anti-TPOs) may represent a valuable parameter in ruling out HE. Nonetheless, this result cannot be used to confirm HE. Furthermore, the proposed anti NH2-terminal-α-enolase (anti-NAE) is non-specific for HE. The effectiveness of glucocorticoid therapy is 60.94%, although relapse occurs in 31.67% of patients following the treatment. Our review emphasizes the significance of conducting further large-scale research and the need to take into account the potential genetic factor.

A novel splicing mutation DNAH5 c.13,338 + 5G > C is involved in the pathogenesis of primary ciliary dyskinesia in a family with primary familial brain calcification.

BACKGROUND: Primary ciliary dyskinesia (PCD) is an autosomal recessive hereditary disease characterized by recurrent respiratory infections. In clinical manifestations, DNAH5 (NM_001361.3) is one of the recessive pathogenic genes. Primary familial brain calcification (PFBC) is a neurodegenerative disease characterized by bilateral calcification in the basal ganglia and other brain regions. PFBC can be inherited in an autosomal dominant or recessive manner. A family with PCD caused by a DNAH5 compound heterozygous variant and PFBC caused by a MYORG homozygous variant was analyzed. METHODS: In this study, we recruited three generations of Han families with primary ciliary dyskinesia combined with primary familial brain calcification. Their clinical phenotype data were collected, next-generation sequencing was performed to screen suspected pathogenic mutations in the proband and segregation analysis of families was carried out by Sanger sequencing. The mutant and wild-type plasmids were constructed and transfected into HEK293T cells instantaneously, and splicing patterns were detected by Minigene splicing assay. The structure and function of mutations were analyzed by bioinformatics analysis. RESULTS: The clinical phenotypes of the proband (II10) and his sister (II8) were bronchiectasis, recurrent pulmonary infection, multiple symmetric calcifications of bilateral globus pallidus and cerebellar dentate nucleus, paranasal sinusitis in the whole group, and electron microscopy of bronchial mucosa showed that the ciliary axoneme was defective. There was also total visceral inversion in II10 but not in II8. A novel splice variant C.13,338 + 5G > C and a frameshift variant C.4314delT (p. Asn1438lysfs *10) were found in the DNAH5 gene in proband (II10) and II8. c.347_348dupCTGGCCTTCCGC homozygous insertion variation was found in the MYORG of the proband. The two pathogenic genes were co-segregated in the family. Minigene showed that DNAH5 c.13,338 + 5G > C has two abnormal splicing modes: One is that part of the intron bases where the mutation site located is translated, resulting in early translation termination of DNAH5; The other is the mutation resulting in the deletion of exon76. CONCLUSIONS: The newly identified DNAH5 splicing mutation c.13,338 + 5G > C is involved in the pathogenesis of PCD in the family, and forms a compound heterozygote with the pathogenic variant DNAH5 c.4314delT lead to the pathogenesis of PCD.

Incidence of seizures in ICU patients with diffuse encephalopathy and its predictors.

Encephalopathy is a diffuse brain dysfunction that results from systemic disorder. Patients with diffuse encephalopathy are at risk of developing clinical and electrographic seizures. The aim of this study is to assess the prevalence of electrographic seizures in a setting of encephalopathy and the clinical and electroencephalogram predictors. We retrospectively reviewed all continuous electroencephalograms done between 2019 and 2022. Continuous electroencephalograms with diffuse encephalopathy were included in the study. A total of 128 patients with diffuse encephalopathy were included in this study. Patients' ages ranged from 18 to 96 years old with a mean age of 55.3 ±â€…19.2 years old. Nine out of 128 patients had seizures with an incidence of 7%. Sixty-six point six percent were nonconvulsive electrographic seizures. Fourteen point three percent of the female patients with diffuse encephalopathy had seizures as compared to none of the male patients (P = .002). Also, 12% of patients with a history of epilepsy experienced seizures versus 5.8% of patients without this history (P = .049). Among electrographic features, 25% of patients with delta background had seizures versus 2.3% of the other patients (P = .048). Likewise, 90% of patients with periodic discharges developed seizures in comparison with none of the patients without (P = .001). Seizures are seen in 7% of patients with diffuse encephalopathy. Female gender, past history of epilepsy, delta background and periodic discharges are significant predictors of seizure development in patients with diffuse encephalopathy.

Association of non-steroidal anti-inflammatory drug use with encephalopathy development: An analysis using the United States Food and Drug Administration Adverse Event Reporting System (FAERS) and Japanese Adverse Drug Event Report (JADER) databases.

Encephalopathy is the most severe complication of various common infections, including influenza and herpes, and it often results in death or severe neurological disability. The risk factors for viral encephalopathy include non-steroidal anti-inflammatory drug (NSAID) use; however, studies on NSAID-related encephalopathy are limited. In this study, we aimed to investigate the characteristics of NSAID-related encephalopathy. We investigated the incidence of NSAID-related encephalopathy using data from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) and Japanese Adverse Drug Event Report (JADER) databases containing reports on spontaneous adverse effects (AEs) published by the Pharmaceuticals and Medical Devices Agency. We used these databases to detect AEs based on reported odds ratios. By separating suspicious drugs, concomitant drugs, and drug interactions involving NSAIDs, we investigated the relationship between encephalopathy pathology and AEs of NSAIDs. Significant encephalopathy signals were detected for loxoprofen and etodolac in the FAERS database and loxoprofen in the JADER database. In the JADER database, significant encephalopathy signals in loxoprofen-treated patients were detected in 70-79-year-old, ≥80-year-old, influenza viral infection, and herpes virus infection groups. Significant encephalopathy signals in patients with herpes virus infection were detected in the ≥80-year-old and loxoprofen-treated groups. Regarding the involvement of loxoprofen in the development of encephalopathy, the JADER database listed loxoprofen as a suspect drug, without indicating any concomitant drug interactions. In conclusion, our findings suggest that loxoprofen and etodolac may be associated with viral encephalopathy. Accordingly, prudence is recommended when using loxoprofen in older individuals with viral infections.

Clinical performance of automated machine learning: A systematic review.

Introduction: Automated machine learning (autoML) removes technical and technological barriers to building artificial intelligence models. We aimed to summarise the clinical applications of autoML, assess the capabilities of utilised platforms, evaluate the quality of the evidence trialling autoML, and gauge the performance of autoML platforms relative to conventionally developed models, as well as each other. Method: This review adhered to a prospectively registered protocol (PROSPERO identifier CRD42022344427). The Cochrane Library, Embase, MEDLINE and Scopus were searched from inception to 11 July 2022. Two researchers screened abstracts and full texts, extracted data and conducted quality assessment. Disagreement was resolved through discussion and if required, arbitration by a third researcher. Results: There were 26 distinct autoML platforms featured in 82 studies. Brain and lung disease were the most common fields of study of 22 specialties. AutoML exhibited variable performance: area under the receiver operator characteristic curve (AUCROC) 0.35-1.00, F1-score 0.16-0.99, area under the precision-recall curve (AUPRC) 0.51-1.00. AutoML exhibited the highest AUCROC in 75.6% trials; the highest F1-score in 42.3% trials; and the highest AUPRC in 83.3% trials. In autoML platform comparisons, AutoPrognosis and Amazon Rekognition performed strongest with unstructured and structured data, respectively. Quality of reporting was poor, with a median DECIDE-AI score of 14 of 27. Conclusion: A myriad of autoML platforms have been applied in a variety of clinical contexts. The performance of autoML compares well to bespoke computational and clinical benchmarks. Further work is required to improve the quality of validation studies. AutoML may facilitate a transition to data-centric development, and integration with large language models may enable AI to build itself to fulfil user-defined goals.

Mechanobiological insight into brain diseases based on mechanosensitive channels: Common mechanisms and clinical potential.

BACKGROUND: As physical signals, mechanical cues regulate the neural cells in the brain. The mechanosensitive channels (MSCs) perceive the mechanical cues and transduce them by permeating specific ions or molecules across the plasma membrane, and finally trigger a series of intracellular bioelectrical and biochemical signals. Emerging evidence supports that wide-distributed, high-expressed MSCs like Piezo1 play important roles in several neurophysiological processes and neurological disorders. AIMS: To systematically conclude the functions of MSCs in the brain and provide a novel mechanobiological perspective for brain diseases. METHOD: We summarized the mechanical cues and MSCs detected in the brain and the research progress on the functional roles of MSCs in physiological conditions. We then concluded the pathological activation and downstream pathways triggered by MSCs in two categories of brain diseases, neurodegenerative diseases and place-occupying damages. Finally, we outlined the methods for manipulating MSCs and discussed their medical potential with some crucial outstanding issues. RESULTS: The MSCs present underlying common mechanisms in different brain diseases by acting as the "transportation hubs" to transduce the distinct signal patterns: the upstream mechanical cues and the downstream intracellular pathways. Manipulating the MSCs is feasible to alter the complicated downstream processes, providing them promising targets for clinical treatment. CONCLUSIONS: Recent research on MSCs provides a novel insight into brain diseases. The common mechanisms mediated by MSCs inspire a wide range of therapeutic potentials targeted on MSCs in different brain diseases.

Unveiling brain disorders using liquid biopsy and Raman spectroscopy.

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

Severe non-hepatic hyperammonaemic encephalopathy in an immunocompromised adolescent with enterocolitis.

Non-hepatic causes of hyperammonaemia are uncommon relative to hepatic aetiologies. An adolescent female was admitted to the hospital with a diagnosis of very severe aplastic anaemia. During her treatment with immunosuppressive therapy, she developed neutropenic enterocolitis, pseudomonal bacteraemia and hyperammonaemia. A combination of intermittent haemodialysis and high-volume continuous veno-venous haemodiafiltration (CVVHDF) was required to manage the hyperammonaemia. Despite a thorough investigation, there were no hepatic, metabolic or genetic aetiologies identified that explained the hyperammonaemia. The hyperammonaemia resolved only after the surgical resection of her inflamed colon, following which she was successfully weaned off from the renal support. This is a novel case report of hyperammonaemia of non-hepatic origin secondary to widespread inflammation of the colon requiring surgical resection in an immunocompromised patient. This case also highlights the role of high-volume CVVHDF in augmenting haemodialysis in the management of severe refractory hyperammonaemia.

Brain Disorder Detection and Diagnosis using Machine Learning and Deep Learning - A Bibliometric Analysis.

BACKGROUND AND OBJECTIVE: Brain disorders are one of the major global mortality issues, and their early detection is crucial for healing. Machine learning, specifically deep learning, is a technology that is increasingly being used to detect and diagnose brain disorders. Our objective is to provide a quantitative bibliometric analysis of the field to inform researchers about trends that can inform their Research directions in the future. METHODS: We carried out a bibliometric analysis to create an overview of brain disorder detection and diagnosis using machine learning and deep learning. Our bibliometric analysis includes 1550 articles gathered from the Scopus database on automated brain disorder detection and diagnosis using machine learning and deep learning published from 2015 to May 2023. A thorough bibliometric análisis is carried out with the help of Biblioshiny and the VOSviewer platform. Citation analysis and various measures of collaboration are analyzed in the study. RESULTS: According to a study, maximum research is reported in 2022, with a consistent rise from preceding years. The majority of the authors referenced have concentrated on multiclass classification and innovative convolutional neural network models that are effective in this field. A keyword analysis revealed that among the several brain disorder types, Alzheimer's, autism, and Parkinson's disease had received the greatest attention. In terms of both authors and institutes, the USA, China, and India are among the most collaborating countries. We built a future research agenda based on our findings to help progress research on machine learning and deep learning for brain disorder detection and diagnosis. CONCLUSION: In summary, our quantitative bibliometric analysis provides useful insights about trends in the field and points them to potential directions in applying machine learning and deep learning for brain disorder detection and diagnosis.

In and out: Benchmarking in vitro, in vivo, ex vivo, and xenografting approaches for an integrative brain disease modeling pipeline.

Human cellular models and their neuronal derivatives have afforded unprecedented advances in elucidating pathogenic mechanisms of neuropsychiatric diseases. Notwithstanding their indispensable contribution, animal models remain the benchmark in neurobiological research. In an attempt to harness the best of both worlds, researchers have increasingly relied on human/animal chimeras by xenografting human cells into the animal brain. Despite the unparalleled potential of xenografting approaches in the study of the human brain, literature resources that systematically examine their significance and advantages are surprisingly lacking. We fill this gap by providing a comprehensive account of brain diseases that were thus far subjected to all three modeling approaches (transgenic rodents, in vitro human lineages, human-animal xenografting) and provide a critical appraisal of the impact of xenografting approaches for advancing our understanding of those diseases and brain development. Next, we give our perspective on integrating xenografting modeling pipeline with recent cutting-edge technological advancements.