All three models used the same head mesh, electrodes and electric-field solver, allowing the researchers to compare how different representations of brain conductivity affected the predictions. White-matter conductivity was conventionally estimated from single-shell DTI, while q-space trajectory imaging supplied a mean tensor expected to have less kurtosis bias. The principal difference between the two anisotropic models was tensor orientation, which varied by 18 to 25 degrees across white matter. Despite those directional differences, their predicted electric-field magnitudes differed by 6.6% or less under the tested conditions.

An exploratory comparison found no significant differences in predicted electric fields between participants with Parkinson’s disease and controls in any brain region or across the four montages. The authors characterized this group comparison as underpowered, so the finding should not be interpreted as evidence that the two populations receive equivalent stimulation exposure. The small sample also did not provide ground-truth measurements of brain conductivity or tDCS electric fields. The study therefore characterized the sensitivity of model predictions rather than establishing improved dosimetric accuracy.

Whole-brain predicted electric field correlated with brain stiffness measured by magnetic resonance elastography, with a partial correlation of 0.58. After cerebrospinal fluid morphology was included in the statistical model, this relationship was no longer significant, and the partial correlations fell to 0.06–0.09. The result shows that the association weakened after statistical adjustment for cerebrospinal fluid morphology; it does not by itself establish a causal influence of that anatomy. Based on the findings, the authors concluded that Parkinson’s disease modeling efforts should emphasize cerebrospinal fluid- and atrophy-aware head models and dose normalization rather than automatically adopting a more complex diffusion tensor. Overall, the choice of diffusion tensor was a second-order influence on predicted electric fields compared with individual anatomy under the conditions examined.

Subject of Research: Comparison of multidimensional diffusion MRI and DTI models for predicting tDCS electric fields in Parkinson’s disease

Article Title: Anisotropic conductivity modeling for tDCS in Parkinson’s disease using multidimensional diffusion MRI

Article References: Osorio Jurado, S., Skorpil, M., Svenningsson, P., Moreno, R., & Olsson, C. (2026). Anisotropic conductivity modeling for tDCS in Parkinson’s disease using multidimensional diffusion MRI. Frontiers in Human Neuroscience, 20, Article 1972676. https://doi.org/10.3389/fnhum.2026.1972676

Image Credits: AI Generated

DOI: 10.3389/fnhum.2026.1972676

Keywords: tDCS, Parkinson’s disease, multidimensional diffusion MRI, q-space trajectory imaging, diffusion tensor imaging, electric-field modeling, brain conductivity, MRI elastography, cerebrospinal fluid, white-matter anisotropy, Anisotropic, conductivity

The review, published in Frontiers in Psychiatry, synthesized studies published from 2005 through 2026 that were identified in Medline/PubMed and Google Scholar. It focused particularly on cerebrospinal fluid (CSF) concentrations of 5-HIAA and HVA in relation to suicidal ideation, suicide attempts, attempt lethality and subsequent suicide-related outcomes. Studies in other biological matrices, along with clinical, genetic, inflammatory and metabolic research, were included only as context. The authors did not pool effect estimates, and their qualitative synthesis was complicated by small samples, differing diagnoses, inconsistent CSF collection procedures and multiple observational designs.

Across the evidence base, reduced CSF 5-HIAA was the more consistent neurochemical finding. In depressed patients with comorbid alcohol dependence, people whose attempts were classified as high lethality had about 23.5% lower 5-HIAA concentrations than those making low-lethality attempts. The difference remained after adjustment for age and sex, even though the groups did not differ in depression severity, suicidal ideation or impulsivity. HVA and 3-methoxy-4-hydroxyphenylglycol, a norepinephrine metabolite, did not differ between the two groups. This pattern suggests that low 5-HIAA may be more closely related to the medical severity of a suicidal act than to the presence of suicidal thoughts or depressive symptoms alone.

Prospective evidence adds an important qualification. In people with bipolar depression followed for up to two years, baseline CSF concentrations of 5-HIAA, HVA and MHPG did not distinguish patients who later attempted suicide from those who did not. Lower baseline concentrations of all three metabolites were instead associated with greater lethality of attempts occurring during follow-up. The authors interpret this as evidence that monoaminergic activity may relate more closely to the severity of suicidal behavior than to whether an attempt occurs. The distinction matters because suicidal ideation, attempts, non-suicidal self-injury and suicide death are not interchangeable outcomes, and attempts themselves vary greatly in intent, reversibility and medical severity.

Findings also depend on psychiatric diagnosis. Evidence for lower 5-HIAA was comparatively coherent in mood disorders, including depression with alcohol dependence and bipolar depression, but inconclusive in schizophrenia spectrum disorders. In a cohort of people with schizophrenia followed for approximately 25 years, absolute CSF 5-HIAA and HVA concentrations did not differ significantly between those who died by suicide and survivors. A lower HVA-to-5-HIAA ratio was associated with suicide, however, indicating a relative monoaminergic imbalance rather than a deficit in either metabolite alone. A separate long-term study found no significant relationship between CSF 5-HIAA and early mortality or suicidal history after adjustment for confounders. These findings argue against treating low 5-HIAA as a universal marker operating independently of psychiatric context.

The review also emphasizes that suicidal behavior probably reflects interacting systems rather than a single neurochemical defect. A principal-component analysis of 20 CSF biomarkers identified one profile combining higher 5-HIAA, HVA and interleukin-6 with lower orexin that was associated with violent attempts and greater suicide mortality during follow-up. This does not fit a simple model in which every suicidal state produces uniformly low monoamine concentrations. Other studies linked persistent kynurenine-pathway dysregulation, including higher quinolinic acid and lower kynurenic acid, to suicidal symptoms and depression severity, while elevated cortisol in attempters pointed to activity in the hypothalamic-pituitary-adrenal stress system. Genetic research in the contextual evidence also suggested that suicide-related traits share a highly polygenic architecture involving synaptic function, cellular stress and DNA repair, among other pathways.

Early-life adversity and sex may modify these neurochemical associations. In one study of people who had attempted suicide, greater childhood exposure to violence was associated with lower CSF 5-HIAA in women but not men; among trauma-exposed participants, lower 5-HIAA was also linked with greater adult expression of violent behavior. In another sample, lower CSF HVA was associated with more severe anxiety among female attempters, but HVA was not associated with depression, overall psychopathology or suicidal ideation. A long-term schizophrenia cohort found more childhood bullying among those who died by suicide, while the separate finding of a lower HVA-to-5-HIAA ratio connected this exposure with a relative neurochemical imbalance. These observational associations cannot establish whether early stress causes the measured changes or whether both reflect other vulnerabilities.

Postmortem findings further complicate a simple “low serotonin” interpretation. In brain tissue from suicide cases, serotonin and 5-HIAA concentrations were higher in the brainstem, but the 5-HIAA-to-serotonin ratio was lower, indicating reduced serotonergic turnover rather than uniformly low metabolite concentrations. No significant difference was detected in the prefrontal cortex. Such regional patterns are compatible with altered release, receptor regulation or compensatory changes, but they do not establish causality. Nor do they prove that increasing serotonergic transmission would prevent suicide. Clinical responses to selective serotonin reuptake inhibitors vary by diagnosis, age and treatment context, so the observational biomarker findings cannot be used to infer preventive or therapeutic effects.

Even if the associations were stronger, CSF testing is poorly suited to routine suicide-risk screening. Lumbar puncture is invasive, most commonly causes post-lumbar-puncture headache and requires trained personnel, specialized facilities, sample storage and chromatographic analysis. CSF metabolites also reflect cumulative neurotransmitter turnover rather than an acute state, limiting their value for identifying imminent risk. Peripheral alternatives have also performed inconsistently. A single plasma 5-HIAA measurement did not reliably infer an individual’s absolute CSF concentration, despite correlations in within-person changes over time. Salivary 5-HIAA showed no overall difference between drug-naive patients with first-episode major depression and controls, and platelet serotonin findings remain limited to particular populations. Broader biomarker panels may eventually prove more informative, but no threshold or assay has been validated for individual clinical decisions.

The review therefore treats CSF 5-HIAA and, to a lesser extent, HVA as research-level correlates of suicidal behavior rather than actionable biomarkers. Lower 5-HIAA has the strongest support as an association with high-lethality attempts in selected clinical groups, but prospective studies have not consistently shown that it forecasts future attempts or suicide. The evidence remains limited by small samples, heterogeneous diagnoses, residual confounding, differences in medication and substance use, and variation in CSF collection and assay methods. Larger longitudinal studies would need standardized protocols, diagnostic stratification, independent validation and assessment of false-positive and false-negative classifications before these measures could contribute to objective risk models. Even then, any future use would have to complement rather than replace clinical assessment of psychiatric history, previous attempts, intent, social circumstances and access to lethal means.

Subject of Research: Review of cerebrospinal fluid serotonin and dopamine metabolites as correlates of suicidal behavior and attempt lethality

Article Title: Neurobiological basis of suicidal behavior: a narrative review of cerebrospinal fluid monoamine metabolites

Article References: Stefani, L., Marsella, L. T., & Tittarelli, R. (2026). Neurobiological basis of suicidal behavior: a narrative review of cerebrospinal fluid monoamine metabolites. Frontiers in Psychiatry, 17, Article 1968256. https://doi.org/10.3389/fpsyt.2026.1968256

Image Credits: AI Generated

DOI: 10.3389/fpsyt.2026.1968256

Keywords: suicide risk, suicidal behavior, cerebrospinal fluid, 5-HIAA, serotonin, HVA, dopamine, attempt lethality, biomarkers, neurobiology, Neurobiological, basis

Researchers retrospectively reviewed cerebrospinal fluid samples sent to the hospital’s Central Virology Laboratory between January 2021 and May 2025. The samples were analyzed with the BIOFIRE FilmArray Meningitis/Encephalitis Panel. The study population comprised 2,645 patients with suspected central nervous system infections, and the investigators collected demographic, microbiological, cytological and biochemical data for analysis in Jamovi version 2.6.26. The study therefore provides a single-center clinical snapshot of syndromic panel findings over the specified period.

Viruses accounted for 49.6% of the 288 microorganism detections, bacteria for 43.4% and C. neoformans/gattii for 7.0%. Streptococcus pneumoniae was the most frequently detected bacterial microorganism, with 83 detections representing 66.4% of bacterial detections. Enterovirus was the leading viral agent, with 36 detections, or 25.2% of viral detections, followed by human herpesvirus 6 with 34 detections, or 23.8%. Herpes simplex virus 1 accounted for 25 viral detections, equivalent to 17.5% of the viral total.

The reported patterns differed by age and care setting. Viral detections were significantly more frequent in children than in adults, with reported proportions of 65.7% and 34.3%, respectively (p<0.001). S. pneumoniae detections were more frequent in intensive-care and emergency departments than in other care settings, at 61.4% and 38.6%, respectively (p=0.006). Cerebrospinal fluid associated with bacterial detections showed a typical pattern of neutrophilic pleocytosis, hypoglycorrhachia and hyperproteinorachia, while findings accompanying viral detections were more heterogeneous. Notably, 70 of the 143 viral detections, or 49.0%, occurred in samples with fewer than 10 white blood cells/mm³.

The authors interpreted the results as evidence that multiplex PCR may have a complementary role in the diagnostic work-up of suspected meningitis and meningoencephalitis, particularly because viral organisms were frequently detected in samples with limited inflammation. The results do not demonstrate improved clinical outcomes, treatment effects or population-wide disease burden. As a retrospective, single-hospital study based on syndromic panel testing, it is also limited in generalizability beyond the sampled patients and does not by itself establish each patient’s final clinical diagnosis or capture pathogens outside the panel’s detected spectrum.

Subject of Research: Epidemiological and etiological patterns detected by syndromic multiplex PCR in suspected meningitis and meningoencephalitis

Article Title: Syndromic multiplex PCR in meningitis and meningoencephalitis: epidemiological patterns and etiological spectrum in 2645 moroccan suspected cases

Article References: Touyar, N., Hafidi, N. E., Slaoui, M., Benchekroun, S., Mahraoui, C., Agarrab, N., Aminou, S., El-Amin, G., Zouaki, A., Siyar, H., Belhaj, N., Farissi, A., Belefquih, B., Harrak, S. E., Ed-Dafali, L., Hilali, S. E., Bnouhanna, W., Oukheda, N., Belkhettab, S., … Kabbaj, H. (2026). Syndromic multiplex PCR in meningitis and meningoencephalitis: epidemiological patterns and etiological spectrum in 2645 moroccan suspected cases. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14502-0

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14502-0

Keywords: meningitis, meningoencephalitis, multiplex PCR, cerebrospinal fluid, Morocco, pathogen detection, viral infections, bacterial meningitis, Syndromic, multiplex, epidemiological, patterns

The research focused on the isointense stage of infant brain development, when gray and white matter have similar intensities in both T1- and T2-weighted MRI. This low contrast, together with myelination, noise and motion-related errors, makes automated tissue separation difficult. The authors said the benchmark was particularly challenging because ongoing myelination causes substantial overlap between the intensity distributions of gray and white matter.

The study proposed a 3D patch-wise U-Net with weighted-average reconstruction. Each MRI volume was divided into fixed-size 64 × 64 × 64-voxel patches with a stride of 32 voxels along each dimension, creating 50% overlap between adjacent patches. Patch-level segmentation reduced the memory required to process a complete high-resolution volume while retaining local anatomical information.

The pipeline comprised MRI loading and depth-wise cropping, patch creation, intensity normalization and label mapping, patch-wise segmentation, and reconstruction of the complete 3D volume. Normalized image intensities were scaled to the range from zero to one by dividing each patch by its maximum voxel value. Labels were remapped to consecutive indices for cerebrospinal fluid, gray matter and white matter.

The U-Net had a four-level encoder-decoder structure with skip connections. Its encoder used paired 3 × 3 × 3 convolutions, batch normalization and ReLU activation, followed by 2 × 2 × 2 max pooling. Feature channels increased from 8 to 64 across the encoder, while a two-layer bottleneck operated at the lowest resolution. The decoder used 3D transposed convolutions to restore spatial resolution and concatenated encoder features through skip connections. A final 1 × 1 × 1 softmax layer produced probabilities for background, gray matter, white matter and cerebrospinal fluid.

After separate patch predictions were made, overlapping regions were combined with spatial weights based on each voxel’s distance from the center of the patches covering it. The paper states that voxels near patch centers received greater weight, while voxels near patch boundaries received less, producing smoother transitions and reducing stitching artifacts. This reconstruction method was designed to address boundary discontinuities that can arise when separately processed patches are joined.

Training and evaluation used co-registered T1- and T2-weighted MRI from six-month-old infants acquired on a Siemens 3T scanner at 1 mm isotropic resolution. The dataset contains 10 training participants and 13 official test subjects, with expert manual segmentations of the three tissues. The training participants were divided subject-wise into nine for training and one for validation, keeping all patches from each participant within a single set. Although both modalities were used in preprocessing, segmentation was conducted primarily on T1-weighted images.

The model was trained for 1,000 epochs with a combined Dice and cross-entropy loss, the AdamW optimizer and a cosine-annealed learning rate. Training used mixed-precision arithmetic on an NVIDIA GeForce RTX 4080 with 12 GB of memory. The reported training footprint was about 1.9 GB, rising to 4.2 GB when activations and gradients were included, and convergence took approximately 50 to 65 hours. Inference for a 256 × 256 × 192 volume took about 2.5 seconds, with another 0.5 seconds for patch reconstruction.

On the 13-subject test set, the model achieved 95% overall voxel-wise accuracy, a weighted-average F1 score of 0.95 and a macro-average F1 score of 0.87. Gray matter had precision of 0.93, recall of 0.90 and F1 of 0.92; white matter had precision of 0.80, recall of 0.82 and F1 of 0.81; and cerebrospinal fluid had precision of 0.75, recall of 0.73 and F1 of 0.74. The reported 95% confidence ranges for the tissue-specific F1 scores did not overlap, and the paper reported statistically significant differences for all pairwise comparisons at p < 0.05.

The results indicate a trade-off between volumetric overlap and boundary precision. Some comparison methods reported higher Dice scores for white matter and cerebrospinal fluid, but the proposed model produced smaller HD95 and average surface distances in the comparisons presented. Performance was weaker for cerebrospinal fluid, whose thin and irregular structures are affected by partial-volume effects and ambiguous boundaries. Generalizability remains untested beyond the benchmark’s single scanner, single age point and small cohort, with no direct validation in other age groups, scanners or multicenter data. The authors proposed future work on patch and stride sensitivity, interpretability, hybrid CNN-transformer models and workflow integration, but none of those extensions had been evaluated in this study.

Subject of Research: Automated segmentation of infant brain tissues in six-month-old MRI using a patch-wise 3D U-Net

Article Title: Deep learning model for infant brain tissue segmentation using 3D patch-wise U-Net with weighted-average reconstruction

Article References: Mhlanga, S., & Viriri, S. (2026). Deep learning model for infant brain tissue segmentation using 3D patch-wise U-Net with weighted-average reconstruction. Discover Artificial Intelligence, 6(1), Article 1277. https://doi.org/10.1007/s44163-026-01982-x

Image Credits: AI Generated

DOI: 10.1007/s44163-026-01982-x

Keywords: infant brain MRI, tissue segmentation, 3D U-Net, patch-wise learning, weighted reconstruction, iSeg-2017, gray matter, white matter, cerebrospinal fluid, boundary accuracy, Deep, learning

The patient initially experienced prolonged constitutional symptoms, including fever, weight loss and malaise. These symptoms were followed by progressive neurological deterioration, with headache, altered mental status and signs of raised intracranial pressure. The report notes that tuberculous meningitis and cryptococcal meningitis have overlapping clinical features, creating diagnostic and therapeutic challenges when both infections are present.

Cerebrospinal fluid analysis supported a dual diagnosis. A positive GeneXpert result identified Mycobacterium tuberculosis, while cryptococcal antigen testing was consistent with Cryptococcus neoformans infection. The patient was described as HIV-negative and had no known immunosuppressive condition. The report characterizes simultaneous central nervous system infections caused by these pathogens as exceedingly rare, particularly in immunocompetent individuals.

Following diagnosis, appropriate antituberculous therapy and antifungal treatment were initiated. Nevertheless, the woman’s clinical condition continued to worsen. The case report does not provide sufficient information in the supplied account to determine whether a particular treatment regimen, the concurrent infections or other factors contributed to the fatal outcome. It therefore should not be read as evidence that either infection was untreatable or that any specific treatment caused the outcome.

During the clinical course, the patient developed communicating hydrocephalus, accompanied by intracranial pressure that remained elevated. Her neurological deterioration ultimately progressed to brain herniation and death. Hydrocephalus and raised intracranial pressure are therefore documented features of this presentation, but the supplied report does not detail the imaging or clinical measurements used to characterize them.

The authors emphasize the need for a high index of suspicion for dual infections in settings where tuberculosis and cryptococcosis occur. The case illustrates that symptoms compatible with either form of meningitis may accompany coinfection, making laboratory evidence important for establishing the diagnosis. In this patient, cerebrospinal fluid testing supported the presence of both pathogens rather than a single infectious cause.

The report also identifies multidisciplinary management and timely neurosurgical intervention as potentially important in cases accompanied by hydrocephalus and raised intracranial pressure. This is presented as a general implication of the case, not as evidence that a particular coordinated team or intervention was delivered in this patient. The supplied account does not establish the timing, type or outcome of any neurosurgical procedure.

As a single-patient case report, the research has a narrow evidentiary scope. It cannot determine the incidence of concurrent tuberculous and cryptococcal meningitis, identify the immune mechanisms or predisposing factors that permit coinfection, or compare management strategies. Its principal reported value is to document severe dual CNS infection with fatal hydrocephalus in an HIV-negative patient without a known immunosuppressive condition, while showing the diagnostic difficulty created by overlapping clinical features.

Subject of Research: Fatal concurrent tuberculous and cryptococcal meningitis with hydrocephalus in an HIV-negative patient

Article Title: Concurrent tuberculous and cryptococcal meningitis with hydrocephalus in an HIV- negative patient: a fatal case report

Article References: Tesfaye, M. Z., Gebretekle, F. T., Mered, E. F., Talemahu, A. A., & Kassie, H. T. (2026). Concurrent tuberculous and cryptococcal meningitis with hydrocephalus in an HIV- negative patient: a fatal case report. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14455-4

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14455-4

Keywords: tuberculous meningitis, cryptococcal meningitis, concurrent infections, HIV-negative patient, hydrocephalus, intracranial pressure, cerebrospinal fluid, case report, Concurrent, tuberculous, cryptococcal, meningitis

The research, published in Annals of Clinical and Translational Neurology, evaluated two FDA-cleared capillary blood collection devices, TAPII and Tasso+, for measuring four key Alzheimer’s plasma biomarkers: the amyloid-beta 42/40 ratio, phosphorylated tau 217 (pTau217), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). These analytes tell complementary stories about the disease. The Aβ42/40 ratio reflects amyloid deposition, pTau217 is currently the strongest single plasma marker for discriminating autopsy-confirmed Alzheimer’s disease from other neurodegenerative conditions, NfL signals neuroaxonal injury, and GFAP marks astrocyte activation associated with the onset of amyloid pathology. The team, led by researchers at the Johns Hopkins Center for CSF Disorders, compared capillary plasma measurements to simultaneously collected venous plasma and cerebrospinal fluid from the same individuals.

The cohort comprised 192 patients examined between October 2021 and April 2024, with a mean age of 61 years and a clinically diverse mix of diagnoses. The group included 25 patients with Alzheimer’s disease, 42 with idiopathic normal pressure hydrocephalus, 28 with vascular dementia, 61 with other neurological conditions such as dementia with Lewy bodies, frontotemporal dementia, Parkinson’s disease and idiopathic intracranial hypertension, and 36 cognitively normal participants split into younger and older normal groups. Each patient who could provide samples underwent venipuncture on one arm and capillary collection on the other using either TAPII or Tasso+, both containing EDTA as an anticoagulant. Twenty patients provided samples with both devices. Cerebrospinal fluid was obtained by diagnostic large-volume lumbar puncture under sterile conditions.

The devices themselves are compact, single-use tools designed to collect small amounts of capillary whole blood painlessly from capillaries in the skin. TAPII, approved in 2019, uses an array of 16 microneedles, each 500 micrometers in length, and gentle vacuum to draw blood. Tasso+, cleared in 2022, uses a single lancet 5 millimeters long. Both are described by their manufacturers as suitable for use by a caregiver or the patient themselves, if able, from the comfort of home. In this study, Tasso+ collected a mean volume of 294.1 microliters and TAPII 266.94 microliters, with Tasso+ succeeding in collecting more than 50 microliters of whole blood in 90.3 percent of attempts and TAPII in 86 percent, differences that were not statistically significant. Both devices yielded sufficient blood for multi-biomarker immunoassays in more than 85 percent of collections.

All biomarker levels were measured in singlicate on a Simoa HD-X analyzer using commercially available kits, with inter-assay coefficients of variation below 12 percent for all analytes. The results for three of the four biomarkers were strikingly positive. Capillary concentrations of NfL, GFAP and Aβ42/40 from both devices correlated strongly with their venous plasma counterparts. TAPII-derived NfL showed a correlation coefficient of 0.86 with venous NfL, GFAP 0.84 and Aβ42/40 0.74, all highly significant. Tasso+ performed similarly, with NfL at 0.91, GFAP at 0.80 and Aβ42/40 at 0.75. Pairwise comparisons found no significant differences between TAPII, Tasso+ and venous measurements for these three analytes, and Bland-Altman analysis revealed minimal bias and tight agreement for Aβ42/40 across the range of values, with wider limits of agreement for NfL and particularly GFAP, which showed substantial variability and multiple outliers for both devices.

Then came the surprise. pTau217, the biomarker that has consistently outperformed other phosphorylated tau isoforms in distinguishing Alzheimer’s disease from other dementias and in predicting PET positivity, failed to replicate between capillary and venous samples. Tasso+ capillary pTau217 correlated only weakly with venous pTau217 (r = 0.23, p = 0.04), and TAPII pTau217 did not correlate significantly at all (p = 0.12). Bland-Altman analysis demonstrated a consistent positive bias for both devices, with mean biases of approximately 7 picograms per milliliter for TAPII and 3 picograms per milliliter for Tasso+, and this overestimation became more pronounced at higher pTau217 concentrations. Passing-Bablok regression confirmed substantial proportional bias, with slope estimates markedly deviating from one for both devices. The practical consequence was dramatic: over 95 percent of capillary pTau217 concentrations across all patient groups, even cognitively normal controls, exceeded the preliminary cutoff of 0.42 picograms per milliliter used in established literature to indicate significant brain amyloid pathology. In venous plasma, only the Alzheimer’s disease group and the mixed neurodegenerative Other group exceeded that threshold on average. The study reports a nearly 30-fold difference between TAPII and venous measurements, a 10-fold difference between Tasso+ and venous, and a 3-fold difference between the two capillary devices themselves.

The authors propose several hypotheses for this pTau217 anomaly. Phosphorylated tau species, including pTau217, as well as alpha-synuclein aggregates, have been shown to exist in peripheral nerve terminals of the skin, raising the plausible hypothesis that capillary collection devices may release peripheral pTau217 into the whole blood sample collected, thereby inflating the overall concentration. Matrix effects unique to the pTau217 assay may also be involved, since all the other analytes were run on a different assay kit. Differences in the dimensions and number of needles utilized by the two devices may explain variation in pTau217 concentration as well as hemolysis, which was significantly higher in capillary samples (TAPII 2.08 out of 4, Tasso+ 1.37 out of 4) compared with venous. Notably, hemolysis did not significantly alter the strong relationship between capillary and venous measurements of Aβ42/40, NfL and GFAP, suggesting the pTau217 problem is specific rather than a general quality issue with capillary specimens.

When the researchers compared capillary and venous plasma to cerebrospinal fluid, venous NfL, GFAP and pTau217 all correlated significantly with CSF analytes (NfL r = 0.73, GFAP r = 0.59, pTau217 r = 0.33), consistent with previous CSF-plasma studies. Capillary NfL and GFAP also correlated modestly with CSF measures, whereas capillary Aβ42/40 and pTau217 did not correlate significantly with CSF. Age-adjusted logistic regression models constructed separately for each sample type found comparable discrimination of Alzheimer’s disease status across venous and capillary measurements for all four biomarkers, with no statistically significant differences in AUC. Venous pTau217 demonstrated the highest individual biomarker performance (AUC 0.88, 95 percent CI 0.82-0.94), while GFAP and Aβ42/40 showed similar diagnostic performance across capillary and venous sample types.

Lasso-regularized logistic regression, used to account for the small number of clinically diagnosed Alzheimer’s cases (n = 25) and reduce overfitting, identified age and plasma GFAP as the most consistent predictors of Alzheimer’s disease across all sample types. Models incorporating these two variables yielded AUC values of 0.75 for TAPII-derived capillary plasma, 0.87 for Tasso+-derived capillary plasma and 0.83 for venous plasma. Remarkably, the Tasso+ model, built from just age and GFAP, exceeded both the TAPII and venous models and fell close to AUC values generated by plasma Alzheimer’s biomarker testing in larger studies. The authors suggest that capillary GFAP, particularly in combination with age or APOE genotype, could serve as a scalable screening tool for Alzheimer’s disease in primary care or decentralized research settings. NfL, while elevated in Alzheimer’s disease, is also elevated in many other neurodegenerative conditions present in the cohort, explaining its weak discriminatory power between Alzheimer’s and non-Alzheimer’s participants. The reduced predictive utility of capillary Aβ42/40 concurs with previous studies citing the plasma amyloid ratio’s greatest diagnostic power in preclinical and mild cognitive impairment stages, whereas this cohort primarily comprised clinical Alzheimer’s dementia.

Pain scores, measured on a Numeric Rating Scale from 0 to 10, were dramatically lower for capillary collections than for traditional venipuncture. Tasso+ scored a mean of 0.2 out of 10, TAPII 0.73 out of 10, and venous collection 2.24 out of 10, with all pairwise comparisons highly significant. The authors note that lower pain associated with capillary collection may improve patient compliance for blood draws, a finding consistent with other studies using capillary collection devices. The study was conducted in a supervised clinical setting, and the authors caution that findings may differ in unsupervised or at-home collection environments. The cohort was also not randomized between devices, which may introduce bias but reflects real-world clinical conditions, and the number of clinically diagnosed Alzheimer’s cases was relatively small, limiting statistical power.

The overall conclusion is a nuanced one. The findings support the feasibility of capillary biomarker testing and the use of capillary collection devices in decentralized Alzheimer’s clinical trials and studies, with minimal loss of diagnostic signal for NfL, GFAP and Aβ42/40 compared with venous plasma. But a clear need exists for specific guidelines and assay optimization for capillary biomarkers, particularly pTau217, due to significant technical or biological differences between TAPII, Tasso+ and venous plasma samples. The authors envision a future in which patients or caregivers could provide a small capillary sample at home or in a clinic, and clinicians could triage them for confirmatory CSF or PET testing based on algorithmic risk. Before that vision becomes reality, capillary blood biomarker tests will need to be thoroughly evaluated as CSF and venous plasma assays have been over the past decade, potentially necessitating separate cutoffs and guidelines for different plasma sample types to account for the measurement gap that this study has now exposed.

Subject of Research: Validation of two capillary blood collection devices for measuring Alzheimer's disease plasma biomarkers against venous plasma and cerebrospinal fluid

Article Title: Alzheimer's Disease Biomarkers Measured by Capillary Blood Collection Versus Venous Plasma and Cerebrospinal Fluid

Article References: Ho, S., Shen, Z., Lewis, A., Patel, M., Zheng, A., Proscino, G., Ho, T., Wang, J., Albert, M., & Moghekar, A. (2026). Alzheimer's Disease Biomarkers Measured by Capillary Blood Collection Versus Venous Plasma and Cerebrospinal Fluid. Annals of Clinical and Translational Neurology, Article acn3.70524. https://doi.org/10.1002/acn3.70524

Image Credits: AI Generated

DOI: 10.1002/acn3.70524

Keywords: Alzheimer's disease, blood biomarkers, capillary blood collection, pTau217, GFAP, neurofilament light chain, amyloid beta 42/40, cerebrospinal fluid, Tasso+, TAPII, decentralized clinical trials, plasma biomarkers

The core of the new methodology involves the use of a multi-affinity resin containing immobilized antibodies that target fourteen specific high-abundance plasma proteins. These proteins collectively constitute approximately 95% of the total protein content in plasma, creating a significant barrier to detecting lower-abundance molecules. The study, led by John Rönnholm and colleagues, systematically evaluated the conditions required for efficient depletion, including resin-to-plasma ratios and mixing speeds. The researchers found that a resin-to-plasma ratio of at least 75:1, combined with a mixing speed of 900 rpm on a plate shaker, ensured complete and reproducible depletion. This specific combination was critical for achieving consistent results in a 96-well plate format, which is essential for high-throughput laboratory workflows.

The impact of this depletion strategy on proteome coverage was substantial. In plasma samples, the number of identified protein groups increased by approximately 80%, rising from 707 to 1,269. Similarly, in cerebrospinal fluid, the number of identified proteins increased by about 65%. Beyond simply increasing the total count, the workflow significantly improved the detection of brain-enriched proteins in plasma. The number of such proteins tripled following depletion, providing a clearer window into central nervous system pathology through blood samples. This capability is crucial for developing blood-based biomarkers that can reflect brain health without the need for invasive lumbar punctures.

Optimizing the enzymatic digestion process was another key component of the study. The researchers compared different digestion protocols to determine the most effective approach for both plasma and CSF. For plasma, a two-step digestion strategy using a mixture of Lys-C and trypsin, followed by a second incubation with trypsin alone, yielded the highest reproducibility and detectability. The authors suggest that plasma’s higher protein concentration and endogenous protease inhibitors may explain why the second digestion step was beneficial. In contrast, CSF samples required only a single digestion step with the Lys-C/trypsin mixture, as the lower protein concentration and fewer inhibitors allowed for efficient proteolysis without additional treatment.

The study also investigated the role of the detergent sodium deoxycholate in the digestion process. While deoxycholate is commonly used to enhance enzymatic digestion by disrupting protein interactions, its inclusion in the workflow had mixed results. In CSF, the detergent had little effect on protein identification. In plasma, it only marginally improved proteome coverage while decreasing quantification precision and reducing throughput. The researchers concluded that the minor gains in coverage were outweighed by the loss of reproducibility and the added complexity of detergent removal, which is impractical for large-scale, label-free studies. Consequently, the final optimized workflow excludes the use of deoxycholate to maintain high analytical precision.

To validate the technical robustness of the workflow, the team applied it to a clinical cohort of 528 samples from patients with amyotrophic lateral sclerosis and healthy controls. The samples were analyzed using tandem mass tag-based quantification, a method that allows for the simultaneous comparison of multiple samples. Principal component analysis of the data showed that technical replicates from the same sample clustered tightly together, indicating that the variation introduced by the sample preparation and mass spectrometry analysis was substantially lower than the biological variation between individuals. This high level of technical reproducibility is essential for detecting subtle protein changes associated with disease progression in longitudinal studies.

The cost-effectiveness of the new workflow is a significant advantage over alternative methods. While commercial enrichment kits and nanoparticle-based approaches can achieve high proteome coverage, they often rely on proprietary reagents and specialized automation, with costs ranging from 80 to 90 USD per sample. In contrast, the authors report an immunodepletion cost of 3 to 4 USD per sample in their laboratory. This figure concerns that preparation step, not an all-inclusive diagnostic test or the cost of mass-spectrometry analysis. This drastic reduction in cost makes the workflow accessible to a wider range of laboratories and facilitates the analysis of large clinical cohorts that would otherwise be prohibitively expensive. The simplicity of the method, which relies on standard laboratory equipment such as plate shakers and centrifuges, further enhances its scalability and reproducibility.

The findings of this study have important implications for the field of clinical proteomics and the development of biomarkers for neurodegenerative diseases. By enabling deep and reproducible proteome profiling of both plasma and CSF, the workflow supports discovery of candidate biomarkers that would require separate clinical validation before use in diagnosis or monitoring. The ability to detect brain-enriched proteins in plasma supports research into less invasive, blood-based markers of central nervous system disease. As the demand for blood-based biomarkers grows, particularly for conditions like Alzheimer’s disease and ALS, scalable and cost-effective methods like this one will be crucial for translating proteomic discoveries into clinical practice.

The study establishes technical performance for a sample-preparation method, rather than validating a new diagnostic test. Its ALS cohort was used to assess reproducibility and scalability, not to establish disease-specific biomarker accuracy. The findings support further biomarker-discovery studies, while clinical sensitivity, specificity and utility remain separate questions. Laboratories adopting the workflow would also need to verify performance with their own samples, instruments and analytical procedures.

Subject of Research: Optimization of proteomic sample preparation for plasma and cerebrospinal fluid

Article Title: Shake and bake: a robust and cost-effective proteomic sample preparation workflow for plasma and cerebrospinal fluid

Article References: Rönnholm, J., Weiner, S., Fuchs, J., Thorsell, A., Sihlbom, C., Dugom, L., Easton, A., Zetterberg, H., & Gobom, J. (2026). Shake and bake: a robust and cost-effective proteomic sample preparation workflow for plasma and cerebrospinal fluid. Clinical Proteomics, 23(1), Article 12. https://doi.org/10.1186/s12014-026-09589-1

Image Credits: AI Generated

DOI: 10.1186/s12014-026-09589-1

Keywords: proteomics, plasma, cerebrospinal fluid, biomarkers, neurodegenerative diseases, sample preparation, mass spectrometry, clinical proteomics, protein depletion, amyotrophic lateral sclerosis

The research, conducted at two centers in Zhejiang Province, China, between June 2023 and June 2025, recruited 74 participants: 24 healthy controls and 50 adults with polymerase chain reaction-confirmed herpes simplex encephalitis. Within the patient group, trained clinicians used structured interviews based on DSM-5 criteria to identify 27 survivors without depression and 23 with depression. Depressive symptom severity was quantified with the 17-item Hamilton Depression Rating Scale, a continuous measure of current symptom burden rather than a standalone diagnostic tool. The researchers also assessed anxiety with the Hamilton Anxiety Rating Scale and cognition with the Mini-Mental State Examination and the Montreal Cognitive Assessment, allowing them to place depressive symptoms within each patient’s broader neuropsychiatric profile.

The central biological hypothesis concerned tumor necrosis factor-alpha, or TNF-alpha, a proinflammatory cytokine that participates in innate immune signaling among immune cells, endothelial cells, microglia, and astrocytes. Cerebrospinal fluid was obtained by lumbar puncture during the assessment visit, and TNF-alpha concentrations were measured in duplicate using a sandwich enzyme-linked immunosorbent assay. Before any analysis, the team prespecified TNF-alpha as the primary cytokine for the imaging, regression, and mediation analyses, while interleukin-6, IL-1beta, IL-10, and IL-8 were retained for secondary group comparisons and symptom correlations. This prespecification matters scientifically because it reduces the risk of cherry-picking among multiple measured biomarkers, a common pitfall in small observational studies.

The results showed a clear inflammatory gradient across the groups. Median CSF TNF-alpha concentrations were 14.9 picograms per milliliter in the depressed HSE group, 10.5 in the non-depressed HSE group, and 7.8 in healthy controls, a difference that reached statistical significance. In the pooled HSE cohort, CSF TNF-alpha correlated positively with Hamilton depression scores, with a Spearman rho of 0.345. CSF IL-6 also differed across groups and correlated with symptom severity, whereas IL-1beta, IL-10, and IL-8 showed no overall group differences. Notably, no measured cytokine correlated with cognitive scores, disease duration, or hospitalization duration, suggesting that the inflammatory signal was specifically tied to the affective phenotype rather than to general illness chronicity.

To capture the brain-side of the story, the researchers performed resting-state functional MRI on a 3.0-Tesla scanner and analyzed the data with a voxel-wise graph measure called degree centrality, or DC. Degree centrality quantifies how strongly each voxel’s spontaneous blood oxygen level-dependent signal correlates with the rest of the gray matter, without requiring a predefined seed region. The team computed Pearson correlations between every pair of voxels, retained connections above a threshold of r = 0.25, and counted each voxel’s positive connections with all other gray-matter voxels. Rigorous preprocessing included slice-timing correction, rigid-body realignment, nuisance regression with a 24-parameter motion model, and strict motion exclusion criteria, with mean framewise displacement and censored-volume counts included as covariates to reduce motion-related bias.

The primary whole-brain contrast comparing depressed with non-depressed HSE survivors, corrected for multiple comparisons using Gaussian random field methods, identified four clusters with significantly lower degree centrality in the depressed group: the right amygdala, the right insula, the left fusiform gyrus, and the left postcentral gyrus. These regions are functionally meaningful. The amygdala is central to emotional processing, and its resting-state connectivity is consistently altered in major depressive disorder. The insula supports salience detection and interoception, the integration of internal bodily signals with external information. The fusiform gyrus contributes to higher-order visual processing, while the postcentral gyrus handles somatosensory processing and bodily representation. In secondary regional comparisons, the differences between depressed and non-depressed survivors remained significant in the right amygdala and left postcentral gyrus but not in the fusiform or insula, which the authors therefore treated as exploratory candidate regions rather than depression-specific abnormalities.

The integration of the inflammatory and imaging data was the study’s most technically ambitious component. CSF TNF-alpha was inversely associated with degree centrality in the right amygdala, right insula, and left postcentral gyrus, with partial correlation coefficients of -0.355, -0.411, and -0.299 respectively. Regional degree centrality values, in turn, correlated negatively with depressive symptom severity across all four regions after adjustment for TNF-alpha. Because anxiety scores differed between the patient groups, the team added the Hamilton anxiety score to their models as a sensitivity analysis. The associations remained directionally consistent but were attenuated, indicating that anxiety symptoms partially overlap with, but do not fully explain, the observed relationships. The positive correlation between CSF TNF-alpha and depression scores also remained significant after adjustment for anxiety.

Hierarchical regression models built on these findings incrementally. A base model including age, sex, education, cognitive score, and disease duration explained 19.4 percent of the variance in depression scores. Adding log-transformed CSF TNF-alpha increased the explained variance to 30.2 percent, and further adding right amygdala and right insula degree centrality raised it to 42.1 percent. Within the final model, right amygdala centrality remained independently associated with symptom severity, but the TNF-alpha coefficient was attenuated and no longer significant, suggesting overlapping statistical information between the inflammatory marker and the imaging measure. Exploratory single-region mediation models, using 5,000 bias-corrected bootstrap resamples, yielded positive standardized indirect-effect estimates of 0.149 for the right amygdala, 0.081 for the left fusiform gyrus, 0.163 for the right insula, and 0.091 for the left postcentral gyrus. The authors emphasized that these estimates describe statistical associations and do not establish causal mediation.

The study’s limitations are substantial and honestly acknowledged. The cross-sectional design precludes any conclusion about temporal sequence, so it remains unknown whether inflammation drives network changes, whether network changes produce inflammation, or whether both reflect a third process. The sample of 74 participants is modest, limiting precision in multivariable and mediation models. The depressed group included heterogeneous DSM-5 categories, with only three cases of primary major depressive disorder, three of depressive disorder due to another medical condition, four of adjustment disorder, and thirteen other or unspecified depressive disorders. Longer hospitalization and poorer cognitive scores in the depressed group suggest greater neurological burden, raising the possibility of residual confounding by lesion location, acute disease severity, medication exposure, sleep disturbance, and shared symptom variance. Because all inflammatory biomarkers were measured in cerebrospinal fluid, the findings pertain specifically to the central compartment; no peripheral blood measurements were included, and prior systematic reviews indicate that blood and CSF cytokine relationships are dynamic and context-dependent.

Despite these caveats, the study points toward a multimodal framework for understanding post-encephalitic depression, in which central inflammatory signaling and altered functional network organization jointly accompany depressive symptoms. The authors suggest that neuropsychiatric follow-up after herpes simplex encephalitis should extend beyond seizure surveillance and cognitive testing to include systematic assessment of depression and anxiety, particularly after complicated acute courses. However, neither CSF TNF-alpha nor degree centrality is a validated diagnostic or prognostic biomarker, and clinical translation would require reproducibility across scanners, independent validation, and evidence that testing improves management or outcomes. Longitudinal studies with repeated CSF and peripheral sampling, prespecified or externally defined imaging regions, and dedicated trials testing whether modifying inflammatory pathways improves neuropsychiatric recovery are the necessary next steps. For now, the data do not support TNF-targeted treatment, but they do provide a hypothesis-generating biological scaffold for a population of survivors whose affective recovery has long been overshadowed by the fight to save their lives.

Subject of Research: Cerebrospinal fluid TNF-α, resting-state brain network centrality, and depressive symptoms in survivors of herpes simplex encephalitis

Article Title: Cerebrospinal fluid TNF-α, regional degree centrality, and depressive symptoms after herpes simplex encephalitis: a cross-sectional observational study

Article References: Ma, J., Li, Y., Zhang, Y., Yu, Y., Bai, Y., Chen, Y., Liao, Y., Zheng, C., Yan, J., Feng, Q., & Chen, C. (2026). Cerebrospinal fluid TNF-α, regional degree centrality, and depressive symptoms after herpes simplex encephalitis: a cross-sectional observational study. Frontiers in Neurology, 17, Article 1942369. https://doi.org/10.3389/fneur.2026.1942369

Image Credits: AI Generated

DOI: 10.3389/fneur.2026.1942369

Keywords: herpes simplex encephalitis, TNF-alpha, cerebrospinal fluid, degree centrality, resting-state fMRI, post-encephalitic depression, Cerebrospinal, fluid, TNF-, regional, degree, centrality

The challenge the team faced was a familiar one in animal research: how to measure posture continuously without attaching markers, sensors, or harnesses to the animal. Marker-based systems require extensive animal preparation and can interfere with natural behavior, while manual observation is too imprecise for rigorous analysis. Their solution was a custom pipeline built around a stereo camera that records the animal from two viewpoints simultaneously, feeding the footage into a deep learning system trained to detect fifteen anatomical landmarks on the sheep’s body. The result is a markerless record of how the animal’s body position shapes its internal pressure landscape.

The technical core of the system is a two-stage detection process. First, a custom object detector locates the sheep in each frame, isolating the animal from its surroundings. Second, a landmark detection network identifies fifteen anatomical points on the sheep’s body, from the head and neck to the limbs and hooves. The team trained this network on footage from six sheep, giving it enough appearance variability to handle the low inter-individual variation within the species. The pipeline was designed to work on animals it has never seen before, without requiring additional labeling or retraining.

Once the landmarks are detected, the system reconstructs the sheep’s three-dimensional body position from the two camera viewpoints. This reconstruction is then refined using a smoothing process that enforces temporal continuity, ensuring that the record of the animal’s movement is stable and reliable. The team evaluated this refinement against the raw detections, confirming that the smoothed record is more consistent than the unprocessed data. The result is a stable, three-dimensional record of how the animal moves through its environment.

The final stage of the pipeline classifies the sheep’s body position into predefined categories, such as standing, lying, and other postures. This classification allows the team to segment video sequences into meaningful intervals, facilitating retrospective analysis and simplifying future research. The team trained this classifier on footage from six sheep, giving it enough variability to handle the low inter-individual variation within the species. The result is a system that can automatically segment hours of footage into meaningful intervals.

The team paired this posture pipeline with eight simultaneously recorded pressure signals, selected because they were critical to investigations of cerebrospinal fluid dynamics. The pressure channels are treated generically throughout the system, allowing the number and type of measurements to change without intrinsically tying the pipeline to a specific set of signals. The team synchronized the pressure recordings with the stereo footage, creating a complete record of how the animal’s body position shapes its internal pressure landscape. The result is a system that can correlate posture with physiology in a living animal.

The team evaluated the pipeline on footage from six sheep, confirming that it works on animals it has never seen before without requiring additional labeling or retraining. The annotated landmarks encompass frames from six sheep, providing sufficient appearance variability to support generalization given the low inter-individual variation within the species. The pipeline was designed to be modular, supporting flexible integration of new detection networks and pressure signals. The result is a system that can adapt to future advances in animal research.

The team acknowledged that the pipeline has limitations. The system records eight pressure signals that were selected because they were critical to investigations of cerebrospinal fluid dynamics, but the pipeline is not intrinsically tied to this specific set of measurements. The team also noted that the pipeline was evaluated on a limited number of animals, and that future work should expand the evaluation to more subjects. The result is a system that can adapt to future advances in animal research.

The team concluded that their markerless pipeline offers a new way to correlate posture with physiology in a living animal. By pairing a simple stereo camera with eight simultaneously recorded pressure signals, the system can interpret how body position shapes the internal pressure landscape of a living sheep. The pipeline was designed to be modular, supporting flexible integration of future advances in detection networks and pressure signals. The result is a system that can adapt to future advances in animal research.

Subject of Research: Physiology

Article Title: Automated 3D sheep posture estimation and telemetric pressure synchronization via a markerless computer vision pipeline

Article References: Roncoroni, M., Podgoršak, A., Kaufmann, A., Flürenbrock, F., Trimmel, N. E., Oertel, M. F., Zeilinger, M., Weisskopf, M., & Schmid Daners, M. (2026). Automated 3D sheep posture estimation and telemetric pressure synchronization via a markerless computer vision pipeline. Frontiers in Veterinary Science, 13, Article 1933870. https://doi.org/10.3389/fvets.2026.1933870

Image Credits: AI Generated

DOI: 10.3389/fvets.2026.1933870

Keywords: sheep, stereo camera, posture, pressure signals, cerebrospinal fluid, markerless, animal model, physiology, Automated, estimation, telemetric, pressure

The research team, led by Audrey Delahaye and colleagues working across healthcare facilities in French Guiana, analyzed the records of 146 consecutive patients hospitalized with laboratory-confirmed or probable leptospirosis between 2015 and 2021. Because there has never been an agreed-upon definition of neurological leptospirosis, the investigators set a deliberately strict threshold: patients qualified only if they showed neurological symptoms together with objective abnormalities in the cerebrospinal fluid, the clear liquid bathing the brain and spinal cord, or on neuroimaging. This conservative approach was designed to separate true invasion of the central nervous system from the headache and confusion that can accompany severe systemic infection without direct brain involvement.

Using these criteria, the team identified 18 cases of neuroleptospirosis among the 146 patients, or roughly 12 percent of the cohort. That figure translates into a mean annual incidence of 0.88 cases per 100,000 inhabitants, with a 95 percent confidence interval ranging from 0.52 to 1.39. In a population of fewer than 300,000 people, this makes neuroleptospirosis a rare but persistent feature of the local epidemic landscape, one that emergency physicians and intensivists in the territory are likely to encounter every year.

The clinical spectrum fell into three recognizable patterns. The overwhelming majority of cases, 14 of 18 patients or 78 percent, presented as meningitis, an inflammation of the membranes covering the brain that typically produces fever, severe headache, and neck stiffness. Three patients, or 17 percent, developed encephalitis, in which the brain tissue itself becomes inflamed, while a single patient, about 6 percent, showed a combined meningoencephalitic picture. This distribution mirrors what has been reported anecdotally in other tropical settings, but the French Guiana study is among the first to quantify it systematically in an Amazonian context.

The laboratory findings offer important clues about how the disease behaves when it reaches the nervous system. Lumbar puncture, the procedure used to sample cerebrospinal fluid, was performed in only 28 of the 146 patients, reflecting how rarely clinicians suspect neurological involvement in leptospirosis. Yet among those who underwent the procedure, pleocytosis, an abnormal rise in white blood cells within the fluid, was detected in 64 percent of cases. The median leukocyte count in the cerebrospinal fluid was 42 cells per cubic millimeter, with an interquartile range of 13 to 240, and when differential counts were available, lymphocytes dominated in 62 percent of samples. Protein levels were only mildly elevated, with a median of 0.51 grams per liter, and, critically, glucose concentrations remained normal, a pattern the researchers describe as the absence of hypoglycorrhachia.

That combination, a modest lymphocytic pleocytosis with mild protein elevation and preserved glucose, is a signature that overlaps with viral meningitis rather than with bacterial pyogenic infection. For clinicians working in endemic areas, the implication is that neuroleptospirosis can masquerade as a viral central nervous system infection, and that a history of exposure to freshwater, mud, or rodents in the weeks before symptom onset should prompt consideration of leptospirosis even when the cerebrospinal fluid profile looks benign. Brain magnetic resonance imaging, performed in eight of the neuroleptospirosis patients, revealed abnormalities in only two: one cerebral infarction, suggesting that the infection can occasionally compromise blood vessels in the brain, and one case of pachymeningitis, an inflammation of the dura mater, the tough outer membrane surrounding the brain.

Perhaps the most striking findings of the study concern who develops neurological involvement and what happens to them. Statistical analysis identified three factors independently associated with neuroleptospirosis. Patients younger than 30 years had more than five times the odds of neurological involvement compared with older patients, with an odds ratio of 5.56 and a confidence interval of 1.72 to 18. The absence of leukocytosis, an elevated white blood cell count in the blood during hospitalization, nearly tripled the odds, with an odds ratio of 3.29, and the absence of thrombocytopenia, a low platelet count, more than quadrupled them, with an odds ratio of 4.46. In other words, neuroleptospirosis tended to strike younger patients whose systemic inflammatory response was comparatively muted.

This profile carries a paradoxical message. Leptospirosis is notorious for its most severe forms, including Weil disease, a fulminant syndrome of jaundice, kidney failure, and hemorrhage that can kill even previously healthy adults. Yet the patients in this study whose infection reached the nervous system fared better than their counterparts with purely systemic disease. Neuroleptospirosis was associated with significantly lower odds of sepsis, with an odds ratio of 0.28, and none of the 18 neurological cases required admission to the intensive care unit or resulted in death. Under the diagnostic criteria applied by the researchers, neuroleptospirosis emerged as a presentation associated with favorable outcomes, a finding that should reassure clinicians but also caution them against assuming that neurological symptoms in leptospirosis automatically signal catastrophic illness.

The authors are careful to note the limits of their work. Because the study was retrospective and relied on clinicians having ordered lumbar punctures or brain imaging in the first place, the true frequency of neurological involvement may be underestimated; only 19 percent of the cohort underwent spinal taps, and milder cases managed without hospitalization would never have entered the analysis. The absence of a consensus definition also means that comparisons with other regions are difficult, since different studies have used different thresholds for what counts as neurological leptospirosis. The researchers call for prospective studies incorporating systematic cerebrospinal fluid analysis and microbiological testing, including molecular methods capable of detecting leptospiral DNA directly in the fluid, to clarify the pathophysiology and standardize diagnostic pathways.

For now, the practical takeaway for physicians in tropical endemic settings is one of heightened awareness. In French Guiana, where leptospirosis is a re-emerging public health threat driven by a humid tropical climate, abundant wildlife reservoirs, and frequent human exposure to contaminated water, a young patient with fever, headache, and a lymphocytic meningitis picture, but without the leukocytosis and thrombocytopenia that usually accompany severe leptospirosis, should prompt consideration of neuroleptospirosis in the differential diagnosis. Recognizing the entity matters not only for appropriate antibiotic treatment but also for avoiding unnecessary interventions, since the prognosis, according to this first systematic characterization, appears to be distinctly favorable. As climate change and urbanization expand the footprint of leptospirosis worldwide, understanding its neurological face will become increasingly important for clinicians far beyond the borders of French Guiana.

Subject of Research: Neurological involvement in leptospirosis patients in French Guiana

Article Title: Clinical features and outcomes of neuroleptospirosis in French Guiana: Insights from a retrospective study (2015–2021)

Article References: Delahaye, A., Dequidt, T., Quet, F., Montagnac, C., Blaise, T., Kallel, H., Djossou, F., Nacher, M., Schepers, K., Coussement, J., Le Turnier, P., & Epelboin, L. (2026). Clinical features and outcomes of neuroleptospirosis in French Guiana: Insights from a retrospective study (2015–2021). PLOS Neglected Tropical Diseases, 20(10), e0014263. https://doi.org/10.1371/journal.pntd.0014263

Image Credits: AI Generated

DOI: 10.1371/journal.pntd.0014263

Keywords: leptospirosis, neuroleptospirosis, French Guiana, meningitis, encephalitis, cerebrospinal fluid, tropical medicine, PLOS Neglected Tropical Diseases, retrospective study, central nervous system infection, zoonotic disease, Clinical