ultrasound-measured-optic-nerve-sheath-diameter-predicts-cognitive

Ultrasound-Measured Optic Nerve Sheath Diameter Predicts Cognitive Dysfunction After Resuscitation: A Retrospective Study

Optic nerve sheath diameter (ONSD) measured by bedside ultrasonography has emerged as a promising non-invasive surrogate marker of intracranial pressure ...

The Third Hospital of Wuhan

As a severe public health problem, methamphetamine (METH) abuse places a heavy burden on families and society. A growing amount of evidence has indicated communication between gut microbiota and the CNS in drug addiction, with associations to neural, endocrine and immune pathways. Thus, we searched for alterations in the gut microbiota and their potential effects in METH users through 16S rRNA gene sequencing. A decreased Shannon index indicated lower bacterial diversity in the METH users than in the age-matched control group. The gut microbial community composition in the METH users was also altered, including reductions in Deltaproteobacteria and Bacteroidaceae abundances and increases in Sphingomonadales, Xanthomonadales, Romboutsia and Lachnospiraceae abundances. Moreover, the Fusobacteria abundance was correlated with the duration of METH use. Enterobacteriaceae, Ruminococcaceae, Bacteroides, and Faecalibacterium had statistically significant correlations with items related to the positive and negative symptoms of schizophrenia and to general psychopathology in the METH users, and all have previously been reported to be altered in individuals with psychotic syndromes, especially depression. Abstraction, one of the items of the cognitive assessment, was positively related to Blautia. These findings revealed alterations in the gut microbiota of METH users, and these alterations may play a role in psychotic syndrome and cognitive impairment. Although the mechanisms behind the links between these disorders and METH abuse are unknown, the relationships may indicate similarities in the pathogenesis of psychosis induced by METH abuse and other causes, providing a new paradigm for addiction and METH use disorder treatment.

Altered fecal microbiota composition in individuals who abuse methamphetamine.

Accumulation of impaired mitochondria and energy metabolism disorders are non-negligible features of both aging and age-related neurodegeneration, including Alzheimer's disease (AD). A growing number of studies suggest that mitophagy disorders play an important role in AD occurrence and development. The interaction between mitophagy deficits and Aβ or Tau pathology may form a vicious cycle and cause neuronal damage and death. Elucidating the molecular mechanism of mitophagy and its role in AD may provide insights into the etiology and mechanisms of AD. Defective mitophagy is a potential target for AD prevention and treatment.

Defective mitophagy and the etiopathogenesis of Alzheimer's disease.

Compare Zcalc with other formulas on spherical equivalent prediction errors (PE) and explore the relationship between PE and ocular parameters. Optimize 709 IOL power calculation. 114 eyes with age-related cataract and preoperative regular corneal astigmatism of more than 1.5D were included. They underwent cataract surgery followed by implantation of a toric intraocular lens (Zeiss Torbi 709 M) calculated by Zcalc formula. The prediction errors of spherical equivalent (SE) were analysed 3 months post-surgery. The refractive prediction errors of Zcalc, Barrett Universal II, Kane, and K6 formulas were 0.07 ± 0.63D, - 0.36 ± 0.65D, - 0.41 ± 0.67D, and - 0.31 ± 0.66D, respectively. Statistically significant difference were observed between Zcalc and other formulas. The Zcalc was prone to positive deviation, Barrett Universal II, Kane and K6 were prone to negative deviation. When the axial length is greater than 29.0 mm, the prediction errors of Kane is higher, and prone to negative deviation. Prediction errors of Zcalc are small in all eyes and prone to positive deviation. For more accurate prediction, we recommend Barrett Universal II formula for 709 IOL power calculation.

Predicting accuracy of spherical equivalent after cataract surgery using the online Zcalc calculator for toric IOLs.

This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status among glioblastoma patients.

Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions.

Accurately predicting synergistic drug combinations is critical for complex disease therapy. However, the vast search space of potential drug combinations poses significant challenges for identification through biological experiments alone. Nowadays, deep learning is widely applied in this field. However, most methods overlook the important role of protein-protein interaction networks formed by gene expression products and the pharmacophore information of drugs in predicting drug synergy.

Accurate prediction of synergistic drug combination using a multi-source information fusion framework.

Mitochondria produce adenosine triphosphate (ATP), the main source of cellular energy. To maintain normal function, cells rely on a complex mitochondrial quality control (MQC) system that regulates mitochondrial homeostasis, including mitochondrial dynamics, mitochondrial dynamic localization, mitochondrial biogenesis, clearance of damaged mitochondria, oxygen radical scavenging, and mitochondrial protein quality control. The MQC system also involves coordination of other organelles, such as the endoplasmic reticulum, lysosomes, and peroxisomes. In this review, we discuss various ways by which the MQC system maintains mitochondrial homeostasis, highlight the relationships between these pathways, and characterize the life cycle of individual mitochondria under the MQC system.

Molecular mechanisms of mitochondrial quality control.

The sensation of ear fullness is a prevalent symptom encountered in clinical practice at ear clinics. It can manifest in various conditions, including external auditory canal diseases, middle ear diseases, inner ear diseases, as well as non-ear related disorders such as autonomic nervous dysfunction and temporomandibular joint dysfunction. Despite extensive research efforts, the underlying mechanism of ear fullness remains complex and not fully elucidated. Furthermore, the mechanism of ear fullness varies depending on the specific anatomical site and associated disease pathology. In this article, we have conducted a comprehensive literature review to explore the mechanisms underlying ear fullness across different sites of the auditory conduction pathway. By focusing on these lesions and their correlation with ear fullness, we aim to provide an updated understanding on the etiology, diagnosis, and therapy for ear fullness-related diseases.

The advancements in understanding the pathogenesis of ear fullness.

To investigate the influence of ocular biological parameters on visual range following the implantation of extended depth of focus intraocular lens (EDOF IOLs).

The influence of ocular biological parameters on visual range after implantation of extended depth of focus intraocular lens.

Accurate ocular biometry is crucial for the success of refractive cataract surgery. This study aims to assess the consistency and differences of a new biometer, the ZW-30, compared with the mainstream devices IOLMaster 700 and Sirius in patients with cataracts. A total of 307 patients with cataracts (603 eyes) were included. The anterior chamber depth (ACD), central corneal thickness (CCT), white-to-white (WTW) distance, pupil diameter (PD), flat K (K1), steep K (K2), corneal astigmatism (ΔK), total keratometry (TK), total corneal astigmatism (TCA), astigmatism axis, kappa angle (κ), axial length (AL), and lens thickness (LT) were measured using the ZW-30, IOLMaster 700, and Sirius. The consistency between devices was evaluated using Bland-Altman analysis, the correlation of parameters was assessed using Spearman correlation analysis, and inter-device agreement equations were established. Strong correlations (r ≥ 0.7) and no statistically significant differences in mean values (p > 0.05) were found for ACD, CCT, AL, LT, and anterior corneal curvature (K1/K2) among the three devices, but the 95% limits of agreement (LoA) exceeded the clinical threshold. Total corneal parameters (TK/TCA) and κ angle showed strong correlations (r ≥ 0.5) among the three devices, with significant inter-device differences in mean values (p < 0.05) and 95%LoA exceeding the clinical threshold. Corneal diameter (WTW) had a weak correlation (r = 0.48) between the ZW-30 and Sirius, and differences in PD measurement methods led to systematic bias. The ZW-30 is consistent with the IOLMaster 700 and Sirius in terms of group trends for basic biometric parameters (ACD/CCT/anterior corneal curvature), but significant individual differences exist (95%LoA exceeding the threshold). Total corneal parameters (TK/TCA) and κ angle require cross-validation with Sirius. WTW and PD are not interchangeable between devices due to differences in measurement principles. Cross-device parameter conversion should be avoided in clinical practice to ensure the accuracy of refractive surgery.

Ocular biometry agreement among ZW-30, IOLMaster 700, and sirius in cataract patients.

To compare the refractive-prediction error (the difference between the predicted post-operative spherical equivalent and the actual spherical equivalent) of IOLMaster 700 and Sirius when their biometric data are fed into the Barrett Universal II formula.

Article	Year
Altered fecal microbiota composition in individuals who abuse methamphetamine. Scientific reports\| PubMed ID: 34518605	2021
Defective mitophagy and the etiopathogenesis of Alzheimer's disease. Translational neurodegeneration\| PubMed ID: 35655270	2022
Predicting accuracy of spherical equivalent after cataract surgery using the online Zcalc calculator for toric IOLs. Scientific reports\| PubMed ID: 39528710	2024
Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions. Cancer imaging : the official publication of the International Cancer Imaging Society\| PubMed ID: 39716317	2024
Accurate prediction of synergistic drug combination using a multi-source information fusion framework. BMC biology\| PubMed ID: 40611149	2025
Molecular mechanisms of mitochondrial quality control. Translational neurodegeneration\| PubMed ID: 40887660	2025
The advancements in understanding the pathogenesis of ear fullness. Journal of otology\| PubMed ID: 41069692	2025
The influence of ocular biological parameters on visual range after implantation of extended depth of focus intraocular lens. BMC ophthalmology\| PubMed ID: 41339819	2025
Ocular biometry agreement among ZW-30, IOLMaster 700, and sirius in cataract patients. Scientific reports\| PubMed ID: 41796175	2026
Comparing Refractive Prediction Accuracy of IOL Master 700 and Sirius Utilizing the Barrett Universal II Formula. Clinical ophthalmology (Auckland, N.Z.)\| PubMed ID: 41858984	2026

Xuan Yu

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