Many people with neurological disorders are at high risk of osteoporosis and fragility fractures. Such fractures are a leading cause of disability and premature mortality. There are various underlying mechanisms, including reduced bone mineral density from biomechanical factors (eg, reduced muscle strength), inflammation and/or medications such as glucocorticoids, together with an increased risk of falls. Neurologists are well placed to initiate measures to protect bone health. In this review, we address the epidemiological associations between bone health, fracture risk and different neurological disorders and elucidate the potential underlying mechanisms. We set out overarching principles for managing bone health in the context of neurological disorders, together with guidance for specific diseases.

Recent evidence suggests that systemic conditions, particularly those associated with inflammation, can affect erythrocyte deformability in the absence of haematological conditions. In this exploratory study, we investigated the relationship between systemic inflammatory status and erythrocyte deformability (using osmotic gradient ektacytometry) in a heterogenous study population consisting of individuals with no medical concerns, chronic conditions, and acute illness, providing a wide range of systemic inflammation severity. 22 participants were included in a prospective observational study. Maximum Elongation Index (EI) in ektacytometry served as the readout for erythrocyte deformability. Inflammatory status was assessed using C-reactive protein (CRP) and self-reported symptoms associated with inflammatory activation (Sickness Questionnaire Scores, SicknessQ). In a univariate linear regression, both CRP and SicknessQ scores significantly predicted EI (CRP: F(1,20) = 7.751, p < 0.05 (0.011), R = 0.279; SicknessQ: F(1,18) = 4.831, p < 0.05 (0.041), R = 0.212). Sensitivity analyses with multivariable linear regression correcting for age showed concordant findings. Results suggest a linear relationship between erythrocyte deformability and biochemical and clinical markers of systemic inflammation. Replication of findings in a larger study, and mechanisms and clinical consequences need further in investigation.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify the blood-brain barrier (BBB) permeability-surface area product. Serial measurements can indicate changes in BBB health, of interest to the study of normal physiology, neurological disease, and the effect of therapeutics. We performed a scan-rescan study to inform both sample size calculation for future studies and an appropriate reference change value for patient care. The final dataset included 28 healthy individuals (mean age 53.0 years, 82% female) scanned twice with mean interval 9.9 weeks. DCE-MRI was performed at 3T using a 3D gradient echo sequence with whole brain coverage, T1 mapping using variable flip angles, and a 16-min dynamic sequence with a 3.2-s time resolution. Segmentation of white and grey matter (WM/GM) was performed using a 3D magnetization-prepared gradient echo image. The influx constant K was calculated using the Patlak method. The primary outcome was the within-subject coefficient of variation (CV) of K in both WM and GM. K values followed biological expectations in relation to known GM/WM differences in cerebral blood volume (CBV) and consequently vascular surface area. Subject-derived arterial input functions showed marked within-subject variability which were significantly reduced by using a venous input function (CV of area under the curve 46 vs. 12%, p < 0.001). Use of the venous input function significantly improved the CV of K in both WM (30 vs. 59%, p < 0.001) and GM (21 vs. 53%, p < 0.001). Further improvement was obtained using motion correction, scaling the venous input function by the artery, and using the median rather than the mean of individual voxel data. The final method gave CV of 27% and 17% in WM and GM, respectively. No further improvement was obtained by replacing the subject-derived input function by one standard population input function. CV of K was shown to be highly sensitive to dynamic sequence duration, with shorter measurement periods giving marked deterioration especially in WM. In conclusion, measurement variability of 3D brain DCE-MRI is sensitive to analysis method and a large precision improvement is obtained using a venous input function.

There is growing evidence that inflammation impairs erythrocyte structure and function. We assessed the impact of mild systemic inflammation on erythrocyte fragility in three different settings. In order to investigate causation, erythrocyte osmotic fragility was measured in mice challenged with a live attenuated bacterial strain to induce low-grade systemic inflammation; a significant increase in erythrocyte osmotic fragility was observed. To gather evidence that systemic inflammation is associated with erythrocyte fragility in humans, two observational studies were conducted. First, using a retrospective study design, the relationship between reticulocyte-based surrogate markers of haemolysis and high-sensitivity C-reactive protein was investigated in 9292 healthy participants of the UK Biobank project. Secondly, we prospectively assessed the relationship between systemic inflammation (measured by the urinary neopterin/creatinine ratio) and erythrocyte osmotic fragility in a mixed population (n = 54) of healthy volunteers and individuals with long-term medical conditions. Both human studies were in keeping with a relationship between inflammation and erythrocyte fragility. Taken together, we conclude that mild systemic inflammation increases erythrocyte fragility and may contribute to haemolysis. Further research is needed to assess the molecular underpinnings of this pathway and the clinical implications in inflammatory conditions.

Detecting multiple sclerosis (MS) relapses remains challenging due to symptom variability and confounding factors, such as flare-ups and infections. Methylprednisolone (MP) is used for severe relapses, decreasing the number of contrast-enhancing lesions on MRI. The influx constant (K) derived from dynamic contrast-enhanced MRI (DCE-MRI), a marker of blood-brain barrier (BBB) permeability, has shown promise as a predictor of disease activity in relapsing-remitting MS (RRMS).

A position paper released by the European Association of Nuclear Medicine emphasised the need for multidisciplinary engagement to establish dosimetry-based personalised treatment in Radionuclide therapy (RNT). The uncertainty analysis results often ignored in routine clinical practice should be incorporated into the dose calculations to improve the efficacy and accuracy of treatment. In this study, patients with haematological malignancies undergoing radioimmunotherapy were evaluated. Our study aimed to calculate the uncertainties associated with each parameter of the single time point (STP) dosimetry chain and compare the with multiple time points (MTP) in the bone marrow and liver results.

BackgroundDementia diagnosis is challenging and often delayed. Brain imaging techniques such as single-photon emission computed tomography (SPECT) imaging can help identify subtle changes in brain perfusion. Artificial intelligence methods may support results interpretation for early diagnosis.ObjectiveTo develop and validate multivariate models for the early diagnosis of Alzheimer's disease (AD), using brain perfusion SPECT imaging and interpretable artificial intelligence methods in a real-world clinical setting.MethodsTwo logistic regression models were developed using a training dataset of 420 SPECT scans and tested on an independent clinical dataset of 443 scans. Model 1 was designed to identify abnormal perfusion patterns, while Model 2 identified perfusion changes associated with AD. Input features were extracted from anatomical volumes of interest, with feature selection performed using the Minimum Redundancy Maximum Relevance (MRMR) algorithm.ResultsThe models demonstrated good classification performance using real-world clinical data. Model 1 achieved an area under receiver operator characteristic (AUROC) Curve of 0.89 (Sensitivity 76%, Specificity 87%) in identifying abnormal brain perfusion. Model 2 achieved an AUROC of 0.86 (Sensitivity 87%, Specificity 72%) in identifying AD.ConclusionsMultivariate logistic regression models trained on real-world clinical data show promise as clinical decision support tools for the diagnosis of AD from brain perfusion SPECT imaging. The models use features from clinically relevant brain regions, which enhances interpretability. Future research should focus on expanding model applicability to other dementia types and on prospective evaluation of their utility in improving diagnostic accuracy, consistency, and care pathways in diverse clinical environments.

Disease-modifying treatments such as monoclonal antibodies can be highly effective in chronic inflammatory diseases such as COPD, but often fail in clinical trials due to heterogeneity of inflammation and imperfect tools to stratify patients to select optimal therapeutic approaches. Molecular imaging provides the potential to transform precision medicine in this field.

There is a critical unmet need for scalable, accessible and objective diagnostic tests for stratification in dementia. Biofluid Raman spectroscopy (RS) due to its simplicity, holistic and label-free nature, is a powerful approach that has the potential to offer differential diagnosis across dementia types including Alzheimer's disease (AD). RS is a laser-based optical method that can rapidly provide chemically rich information ('spectral biomarkers') from biofluids but its utility for AD diagnosis has not been established in a 'real-world' context, specifically from a clinically heterogenous cohort of patients. We carried out RS measurements on cerebrospinal fluid (CSF) samples of patients from a mixed clinical cohort (N = 143). All patients reported cognitive complaints and were clinically diagnosed over 2 years with conditions including AD and other neurodegenerative diseases, as well as developmental and long-term chronic conditions. Machine-learning algorithms were trained, optimised and evaluated on Raman spectra to classify AD from non-AD. AD was classified with 93% accuracy for patients in the testing set. Time from sample to classification was < 1 h. Spectral biomarkers explaining AD classification were identified and primarily assigned to protein-derived aromatic amino acids, representing a difference in proteome signature between AD and non-AD groups. Signals from a subset of spectral biomarkers directly correlated with pathological CSF biomarker concentrations including amyloid-β 42, phosphorylated-tau 181, and total tau. This pre-clinical study is a first step towards realising the real-world application of RS for dementia diagnosis. Compared to current and emerging methods, RS does not require sophisticated instrumentation or specialised labs. It is reagentless and simple, offering unprecedented rapidity, scalability, accessibility for dementia diagnosis.

Low-grade chronic inflammation is associated with many age-related conditions. Non-invasive methods to monitor low-grade chronic inflammation may improve the management of older people at risk of poorer outcomes. This longitudinal cohort study has determined baseline inflammation using neopterin volatility in monthly urine samples of 45 independent older adults (aged 65-75 years). Measurement of neopterin, an inflammatory metabolite, enabled stratification of individuals into risk categories based on how often in a 12-month period their neopterin level was raised. Hearing was measured (pure-tone audiometry) at baseline, 1 year and 3 years of the study. Results show that those in the highest risk category (neopterin raised greater than 50% of the time) saw greater deterioration, particularly in high-frequency, hearing. A one-way Welch's ANOVA showed a significant difference between the risk categories for change in high-frequency hearing (W (3, 19.6) = 9.164, p = 0.0005). Despite the study size and duration individuals in the highest risk category were more than twice as likely to have an additional age-related morbidity than those in the lowest risk category. We conclude that volatility of neopterin in urine may enable stratification of those at greatest risk of progression of hearing loss.

ALL_EARS@UoS is a patient and public involvement and engagement (PPIE) group for people with lived experience of hearing loss. The purpose of the group is to share experiences of hearing loss and hearing healthcare, inform research and improve services for patients at University of Southampton Auditory Implant Service. A year after inception, we wanted to critically reflect on the value and challenges of the group. Four members of ALL_EARS@UoS were recruited to an evaluation steering group. This paper reports the evaluation of the group using the UK Standards for Public Involvement.

A small but persistent proportion of individuals do not gain the expected benefit from cochlear implants(CI). A step-change in the understanding of factors affecting outcomes could come through data science. This study evaluates clinical data capture to assess the quality and utility of CI user's health records for data science, by assessing the recording of otitis media. Otitis media was selected as it is associated with the development of sensorineural hearing loss and may affect cochlear implant outcomes.

Tauopathy is characterized by neuronal dysfunction and degeneration occurring as a result of changes to the microtubule-associated protein tau. The neuronal changes evident in tauopathy bear striking morphological resemblance to those reported in models of Wallerian degeneration. The mechanisms underpinning Wallerian degeneration are not fully understood although it can be delayed by the expression of the slow Wallerian degeneration (Wld) protein, which has also been demonstrated to delay axonal degeneration in some models of neurodegenerative disease. Given the morphological similarities between tauopathy and Wallerian degeneration, this study investigated whether tau-mediated phenotypes can be modulated by co-expression of Wld. In a model of tauopathy in which expression of human 0N3R tau protein leads to progressive age-dependent phenotypes, Wld was expressed with and without activation of the downstream pathway. The olfactory receptor neuron circuit was used for these studies in adults, and the larval motor neuron system was employed in larvae. Tau phenotypes studied included neurodegeneration, axonal transport, synaptic deficits and locomotor behaviour. Impact on total tau was ascertained by assessing total, phosphorylated and misfolded tau levels by immunohistochemistry. Activation of the pathway downstream of Wld completely suppressed tau-mediated degeneration. This protective effect was evident even if the pathway downstream of Wld was activated several weeks after tau-mediated degeneration had become established. Though total tau levels were not altered, the protected neurons displayed significantly reduced MC1 immunoreactivity suggestive of clearance of misfolded tau, as well as a trend for a decline in tau species phosphorylated at the AT8 and PHF1 epitopes. In contrast, Wld expression without activation of the downstream protective pathway did not rescue tau-mediated degeneration in adults or improve tau-mediated neuronal dysfunction including deficits in axonal transport, synaptic alterations and locomotor behaviour in tau-expressing larvae. This collectively implies that the pathway mediating the protective effect of Wld intersects with the mechanism(s) of degeneration initiated by tau and can effectively halt tau-mediated degeneration at both early and late stages. Understanding the mechanisms underpinning this protection could identify much-needed disease-modifying targets for tauopathies.

To test the hypothesis that pulsing of intracranial pressure has an association with cognition, we measured cognitive score and pulsing of the tympanic membrane in 290 healthy subjects. This hypothesis was formed on the assumptions that large intracranial pressure pulses impair cognitive performance and tympanic membrane pulses reflect intracranial pressure pulses.290 healthy subjects, aged 20–80 years, completed the Montreal Cognitive Assessment Test. Spontaneous tympanic membrane displacement during a heart cycle was measured from both ears in the sitting and supine position. We applied multiple linear regression, correcting for age, heart rate, and height, to test for an association between cognitive score and spontaneous tympanic membrane displacement. Significance was set at P < 0.0125 (Bonferroni correction.)

A significant association was seen in the left supine position (p = 0.0076.) The association was not significant in the right ear supine (p = 0.28) or in either ear while sitting. Sub-domains of the cognitive assessment revealed that executive function, language and memory have been primarily responsible for this association.

In conclusion, we have found that spontaneous pulses of the tympanic membrane are associated with cognitive performance and believe this reflects an association between cognitive performance and intracranial pressure pulses.

Microplastic pollution is a serious threat to marine organisms, including reef-building corals. Corals are known to incorporate microplastics, which could potentially provide an archive of information to trace present and past microplastic pollution. In this study, a label-free chemical analytical method for rapid visualization of microplastics incorporated in coral tissue and skeletons is proposed by using a coherent anti-Stokes Raman scattering (CARS) microscope combined with two-photon excited fluorescence (TPEF) detection. was maintained in an environment with a high concentration of polyethylene (PE) beads ranging from 0.7 to 5 μm in size. PE beads were successfully visualized, and the number of incorporated beads per skeleton area was quantitatively analyzed using the proposed technique. Notably, plastic beads were only found in the skeleton of coral colonies showing signs of localized tissue loss. Further CARS analysis of tissue found that a number of microplastics were trapped in the areas where tissue loss was observed due to bleaching or physical tissue removal, whereas minimal amounts were observed within healthy tissue. These results suggest that unhealthy conditions which lead to tissue loss and bleaching may accelerate microplastic incorporation into coral tissue and further into skeletons. Our study shows the ability of our CARS-based method to help understand how microplastics are incorporated into corals and will lead to improved tracking of their accumulation in coral reefs.

Antibiotic susceptibility tests (ASTs) often fail to predict treatment outcomes because they do not account for biofilm-specific tolerance mechanisms. In the present study, we explored alternative approaches to predict tobramycin susceptibility of Pseudomonas aeruginosa biofilms that were experimentally evolved in physiologically relevant conditions. To this end, we used four analytical methods - whole-genome sequencing (WGS), matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), isothermal microcalorimetry (IMC) and multi-excitation Raman spectroscopy (MX-Raman). Machine learning models were trained on data outputs from these methods to predict tobramycin susceptibility of our evolved strains and validated with a collection of clinical isolates. For minimal inhibitory concentration (MIC) predictions of the evolved strains, the highest accuracy was achieved with MALDI-TOF MS (97.83%), while for biofilm prevention concentration (BPC) predictions, Raman spectroscopy performed best with an accuracy of 80.43%. Overall, all analytical methods demonstrated comparable predictive performance, showing their potential for improving biofilm AST.

Cysteine-bound sulfane sulfur atoms in proteins have received much attention as key factors in cellular redox homeostasis. However, the role of sulfane sulfur in zinc regulation has been underinvestigated. In this study, we identified growth inhibitory factor (GIF)/metallothionein-3 (MT-3) as a sulfane sulfur-binding protein from mouse brain. We also report here that cysteine-bound sulfane sulfur atoms serve as ligands to hold and release zinc ions in GIF/MT-3 with an unexpected C-S-S-Zn structure. Oxidation of such a zinc/persulfide cluster in ZnGIF/MT-3 results in the release of zinc ions, and intramolecular tetrasulfide bridges in apo-GIF/MT-3 efficiently undergo S-S bond cleavage by thioredoxin to regenerate ZnGIF/MT-3. Three-dimensional molecular modeling confirmed the critical role of the persulfide group in the thermostability and Zn-binding affinity of GIF/MT-3. The present discovery raises the fascinating possibility that the function of other Zn-binding proteins is controlled by sulfane sulfur.

There is a critical unmet need for scalable, accessible and objective diagnostic tests for stratification in dementia. Biofluid Raman spectroscopy (RS) due to its simplicity, holistic and label-free nature, is a powerful approach that has the potential to offer differential diagnosis across dementia types including Alzheimer's disease (AD). RS is a laser-based optical method that can rapidly provide chemically rich information ('spectral biomarkers') from biofluids but its utility for AD diagnosis has not been established in a 'real-world' context, specifically from a clinically heterogenous cohort of patients. We carried out RS measurements on cerebrospinal fluid (CSF) samples of patients from a mixed clinical cohort (N = 143). All patients reported cognitive complaints and were clinically diagnosed over 2 years with conditions including AD and other neurodegenerative diseases, as well as developmental and long-term chronic conditions. Machine-learning algorithms were trained, optimised and evaluated on Raman spectra to classify AD from non-AD. AD was classified with 93% accuracy for patients in the testing set. Time from sample to classification was < 1 h. Spectral biomarkers explaining AD classification were identified and primarily assigned to protein-derived aromatic amino acids, representing a difference in proteome signature between AD and non-AD groups. Signals from a subset of spectral biomarkers directly correlated with pathological CSF biomarker concentrations including amyloid-β 42, phosphorylated-tau 181, and total tau. This pre-clinical study is a first step towards realising the real-world application of RS for dementia diagnosis. Compared to current and emerging methods, RS does not require sophisticated instrumentation or specialised labs. It is reagentless and simple, offering unprecedented rapidity, scalability, accessibility for dementia diagnosis.

The gut microbiota plays a key role in shaping individual responses to drugs, but current tools have limited potential to probe drug-microbe interactions within the complex, individualised gut environment. This study employed bioorthogonal labelling to track and identify gut microbial taxa and molecular mechanisms involved in the bioaccumulation of entacapone, a Parkinson's disease drug. We synthesised alkyne-tagged derivatives of entacapone and evaluated their suitability as molecular probes in incubations with faecal communities or different () strains. Following incubation, tagged drugs were conjugated to a fluorescently labelled azide via click chemistry. Labelled cells were visualised, quantified, sorted via fluorescence-activated cell sorting (FACS), and identified via 16S ribosomal RNA (rRNA) gene amplicon sequencing. Entacapone alkyne derivatives retained the biological activity and effects of the original drug on the microbiota, significantly reducing microbial loads and shifting community composition across the three donors tested. Conjugation of alkyne-entacapone with a labelled azide revealed that between 80% to 96% of all microbial cells in a donor's faecal sample accumulate entacapone. Nearly all taxa detected in incubations were recovered in labelled FACS fractions, confirming widespread uptake of the drug. Finally, we demonstrate that different strains exhibit varying levels of entacapone accumulation and identify a siderophore transporter that plays a role in this process. Our findings reveal that entacapone is widely bioaccumulated by the gut microbiota across three donors and identify a key molecular mediator of this accumulation. This study expands the toolkit for investigating drug-microbiome interactions and holds significant potential to advance our understanding of drug-microbiome dynamics and therapeutic outcomes.

Type 2 diabetes (T2D) is associated with cognitive impairment, with executive functions such as cognitive flexibility being particularly vulnerable. Growing evidence suggests that chronic inflammatory and metabolic stress contributes to diabetes -related brain dysfunction, yet behavioral assessment in animal models is often confounded by anxiety, altered motivation, and reduced response vigor. In this study, we used a translational touchscreen-based operant platform to distinguish associative learning from executive cognitive flexibility in db/db mice, a well-established genetic model of T2D, and to evaluate the effects of the non-erythropoietic erythropoietin derived peptide ARA 290. Male db/db mice and age matched db/m heterozygote lean controls were tested using pairwise visual discrimination to assess associative learning and reversal learning to probe cognitive flexibility. Metabolic function was evaluated using glucose and insulin tolerance tests, while immune and metabolic effects of ARA 290 were evaluated by flow cytometry and RNA-seq. Db/db mice displayed delayed task engagement and longer response latencies during pretraining and acquisition, yet maintained intact associative learning accuracy. In contrast, they exhibited pronounced impairments in cognitive flexibility during reversal learning, characterized by increased perseveration and reduced adaptation to changed reward contingencies. Treatment with ARA 290 improved insulin sensitivity and altered circulating monocyte proportions but did not rescue deficits in executive cognitive flexibility. RNA-seq of the hippocampus revealed enrichment of immune pathways consistent with chronic low-grade inflammation, providing molecular context for the observed behavioral phenotype. Together, these findings demonstrate that T2D selectively impairs executive cognitive flexibility while sparing basic associative learning, and that improvement in peripheral metabolic function and altered monocyte proportions are insufficient to restore executive cognition. This work highlights the value of touchscreen-based paradigms for resolving distinct cognitive domains in metabolic disease and highlights the need to target brain specific immunometabolic mechanisms to address diabetes-associated cognitive dysfunction.

A novel class of active immunotherapy, consisting of proprietary T-helper peptide linked to a B-cell epitope, is being developed to target tau in Alzheimer's disease (AD). These experimental therapies generate antibodies that have demonstrated binding to pathological tau in vitro, and efficacy in cell-based tau aggregation assays comparable to monoclonal antibodies. Here, we report the ability of one such tau-targeting immunotherapy, p5555kb, to prevent the progression of tau pathology using two distinct mouse models. P301L mice were immunized with p5555kb and showed greater survival rates at 210 days than saline-inoculated control mice. The efficacy of p5555kb against tau seeding in vivo was assessed by injecting C57BL6 mice with tau fibrils purified from post-mortem human AD brain tissue. Immunization with p5555kb significantly reduced the amount of tau inclusions detected by immunohistochemistry at 9 months post-injection, as compared to saline inoculation. This study demonstrates that p5555kb is effective at inducing functional tau-targeting antibodies, which prevented the onset of adverse phenotypes associated with tau pathology in vitro and in vivo.

Vascular basement membranes (BMs), composed of laminins, collagen IV, fibronectin, and perlecan, are secreted by endothelial cells, pericytes, smooth muscle cells (SMCs), and astrocytes. In the brain, amyloid beta (Aβ) is eliminated along cerebrovascular BMs of capillaries and arteries as intramural periarterial drainage (IPAD). Ageing modifies vascular BMs, impairing IPAD and leading to Aβ deposition as cerebral amyloid angiopathy. To better understand the molecular determinants of IPAD in ageing, we quantified the relative abundance of BMs secreted by human-derived cerebral endothelial cells, pericytes, brain vascular SMCs, and astrocytes in vitro. We then assessed BM protein levels in SMCs under hypercapnia (8% CO) as a model of vascular ageing, with and without Aβ exposure. Of the four cell types, we found SMCs secreted the highest levels of fibronectin, laminin, and perlecan, whilst pericytes secreted the highest levels of collagen IV. Hypercapnia increased the expression of collagen IV and fibronectin in SMCs but decreased the expression of laminin. The expression of perlecan increased under hypercapnia, but only in the presence of Aβ. This work highlights the varying compositions of vascular BMs and the dynamic differential responses of SMCs to Aβ and hypercapnia, helping to elucidate the age-related changes that impair IPAD in cerebral vessels.

One of the hallmarks of Alzheimer's disease (AD) is the deposition of amyloid-β (Aβ) within the extracellular spaces of the brain as plaques and along the blood vessels in the brain, a condition also known as cerebral amyloid angiopathy (CAA). Clusterin (CLU), or apolipoprotein J (APOJ), is a multifunctional glycoprotein that has a role in many physiological and neurological conditions, including AD. The apolipoprotein E (APOE) is a significant genetic factor in AD, and while the primary physiological role of APOE in the brain and peripheral tissues is to regulate lipid transport, it also participates in various other biological processes, having three basic human forms: APOE2, APOE3, and APOE4. Notably, the APOE4 allele substantially increases the risk of developing late-onset AD. The main purpose of this review is to examine the roles of CLU and APOE in AD pathogenesis in order to acquire a better understanding of AD pathogenesis from which to develop targeted therapeutic approaches.

•AI-driven tools and multimodal biomarkers emerged as key for early VCID detection.•Novel neuroimaging, fluid, and retinal markers show promise for precision diagnostics.•BBB leakage and inflammation could early drive small vessel disease and VCID.•Clinical trials explore drug repurposing and hybrid lifestyle-pharmacological interventions.•Genetic insights into CADASIL reveal shared pathways with sporadic SVD.

Aberrant iron homeostasis is increasingly recognized as a key pathological feature in progressive multiple sclerosis (MS). Although the source of excess brain iron remains unclear, haemoglobin is one possible source. To test this hypothesis, we conducted a case-control study to determine whether erythrocytes are more fragile in people with progressive MS (PwPMS) and examined associations between erythrocyte fragility and brain atrophy.

Elderly patients with subarachnoid hemorrhage (SAH) experience long-term disability and persistent cognitive and psychosocial sequelae, with poor patient-reported outcomes (PROs). However, China currently lacks tools to assess PROs in elderly SAH patients. This study aims to translate the Subarachnoid Hemorrhage Outcomes Tool (SAHOT) into Chinese and evaluate its psychometric properties among elderly SAH patients in China.

Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF-restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real-world cohort and the 2024 McDonald criteria; (2) equivalence to OCB in the specific clinical scenario when demonstration of intrathecal immunoglobulin synthesis is essential for MS diagnosis; (3) which KFLC metric has the best diagnostic performance.

Deep vein thrombosis (DVT) refers to the formation of a blood clot within a deep vein, most often in the lower extremities, which can partially or completely obstruct venous blood flow. This case discusses a 93-year-old female nursing home resident who developed extensive left lower limb swelling with a laboratory D-dimer level of 316 ng/mL (normal range for a 93-year-old: 0-930 ng/mL). Based on her age-adjusted D-dimer threshold of 930 ng/mL, thrombosis would ordinarily be considered unlikely. However, given her predominantly wheelchair-bound status and a Wells score of 3, the clinical suspicion for DVT remained high. Doppler ultrasound subsequently confirmed extensive proximal thrombosis with complete occlusion of the left popliteal and femoral veins. This case illustrates the limitations of relying solely on D-dimer testing to exclude DVT in elderly patients and underscores the importance of clinical judgment.

Despite the success of immune modulation in the treatment of relapsing multiple sclerosis, disability progression is a major problem driven by multiple mechanisms. Comorbidities (eg, vascular risk) and ageing are thought to augment these neurodegenerative pathologies. In the phase 2b MS-STAT trial of simvastatin (80 mg) versus placebo in secondary progressive multiple sclerosis (SPMS), the adjusted difference in brain atrophy rate between groups was -0·254% per year: a 43% reduction. In this phase 3 MS-STAT2 trial, we aimed to assess the efficacy of simvastatin versus placebo in slowing the progression of disability in SPMS.

Lecanemab, an antibody directed at Aβ-protofibrils and plaque, showed meaningful delay in disease progression and biological effects consistent with disease modification in the phase 3 Clarity AD trial.

BackgroundDementia diagnosis is challenging and often delayed. Brain imaging techniques such as single-photon emission computed tomography (SPECT) imaging can help identify subtle changes in brain perfusion. Artificial intelligence methods may support results interpretation for early diagnosis.ObjectiveTo develop and validate multivariate models for the early diagnosis of Alzheimer's disease (AD), using brain perfusion SPECT imaging and interpretable artificial intelligence methods in a real-world clinical setting.MethodsTwo logistic regression models were developed using a training dataset of 420 SPECT scans and tested on an independent clinical dataset of 443 scans. Model 1 was designed to identify abnormal perfusion patterns, while Model 2 identified perfusion changes associated with AD. Input features were extracted from anatomical volumes of interest, with feature selection performed using the Minimum Redundancy Maximum Relevance (MRMR) algorithm.ResultsThe models demonstrated good classification performance using real-world clinical data. Model 1 achieved an area under receiver operator characteristic (AUROC) Curve of 0.89 (Sensitivity 76%, Specificity 87%) in identifying abnormal brain perfusion. Model 2 achieved an AUROC of 0.86 (Sensitivity 87%, Specificity 72%) in identifying AD.ConclusionsMultivariate logistic regression models trained on real-world clinical data show promise as clinical decision support tools for the diagnosis of AD from brain perfusion SPECT imaging. The models use features from clinically relevant brain regions, which enhances interpretability. Future research should focus on expanding model applicability to other dementia types and on prospective evaluation of their utility in improving diagnostic accuracy, consistency, and care pathways in diverse clinical environments.

People living with neurological conditions have needs that require an integrated care approach. Existing models of integrated care have often emphasized system structures but neglected the micro-level interactions that matter most to people.

To examine stakeholder experiences of remote neurology outpatient care and to co-produce an evidence-based framework to support safe, equitable and sustainable service delivery.