Subtle Behavioral Changes Research Articles

Predecessors of Behavioural Initiatives by People With Profound Intellectual Disabilities During Their Interactions With Support Staff: An Exploratory Microanalytical Analysis

ABSTRACTBackgroundInitiating meaningful moments of interaction with people with profound intellectual disabilities can prove to be difficult for support staff. Exploring the behaviour of support staff that precedes the initiations of behaviour by people with profound intellectual disabilities helps to shed light upon the potential facilitating effects of staff behaviour.MethodsThree meaningful moments of interaction between support staff and people with profound intellectual disabilities that were recorded were then microanalytically coded, along with the initial onset of these moments. Each behaviour initiated by people with profound intellectual disabilities was examined to see what specific behaviour by the support staff began precedingly.FindingsThe most frequently displayed ‘staff–client’ behavioural sequences were ‘looking’, ‘moving with head’, ‘moving with arms’ or ‘vocalisation’ of support staff followed by the person with profound intellectual disabilities ‘moving with head’, the staff member ‘moving with arms’ followed by the person with profound intellectual disabilities ‘moving with arms’ and the staff member ‘touching’ followed by the person with profound intellectual disabilities ‘vocalising’. These behavioural sequences occurred less frequently during meaningful moments of interaction in comparison to their onset.ConclusionsIt is important that support staff are cognisant of all the (subtle) behavioural changes in people with profound intellectual disabilities (especially movements with their head) to discern potential behavioural responses. Moreover, they should be cognisant of their own behaviour, insofar as the conscious use of behaviour may facilitate the development of meaningful interactions.

Repeatability and predictability of lying and feeding behaviours in dairy cattle

Subtle changes in behaviour, which may be useful as early indicators of disease or stress in farm animals, can be detected using precision livestock technologies. However, as animals often display differences in their baseline behaviours from one another, individual variation needs to be measured and accounted for if we want to successfully detect abnormalities. In addition to consistent individual differences in their mean behaviour, which are called behavioural types and measured by repeatability, animals may differ in the amount of day-to-day variation around their own mean. This is known as predictability and it is very rarely measured in animals as it requires data with high granularity for extended periods of time, which is hard to obtain without precision technologies. Here we aim to quantify the repeatability and predictability of lying and feeding, two behaviours which have been investigated as potential indicators of disease with inconsistent results, in dairy cows. We used data on daily lying behaviours from leg-mounted sensors for 2183 cows and data on daily feeding behaviours from neck-mounted sensors for 2584 cows belonging to multiple herds to quantify the variation between individuals, the individual differences in predictability and any correlations between individual behaviour type and predictability of the same behaviour. Using multivariate double hierarchical generalised linear models, we were able to quantify individual variation in feeding and lying behaviours of adult cows for the first time. Consistent variation between individuals was present for all measures of lying and feeding with repeatability values of 0.38 for daily feeding time and 0.31 for daily lying time. Individuals also varied in their levels of predictability with coefficients of 0.46 and 0.29 for the daily lying and feeding time respectively. Lastly, there were significant positive correlations between several behaviours and the amount of residual intra-individual variation for the same behaviour (mean lying bout length: 0.93, mean feeding bout length: 0.88), indicating that cows with the longest bouts of the two behaviours were also more variable and unpredictable, perhaps due to an opportunistic strategy. These results highlight the importance of measuring individual variation in behaviour, supporting the evidence of personality traits in cattle, as well as differences in predictability, which must be taken into account in any use of behavioural indicators for early disease diagnosis.

Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments.

To deploy machine learning models on-device, practitioners use compression algorithms to shrink and speed up models while maintaining their high-quality output. A critical aspect of compression in practice is model comparison, including tracking many compression experiments, identifying subtle changes in model behavior, and negotiating complex accuracy-efficiency trade-offs. However, existing compression tools poorly support comparison, leading to tedious and, sometimes, incomplete analyses spread across disjoint tools. To support real-world comparative workflows, we develop an interactive visual system called COMPRESS AND COMPARE. Within a single interface, COMPRESS AND COMPARE surfaces promising compression strategies by visualizing provenance relationships between compressed models and reveals compression-induced behavior changes by comparing models' predictions, weights, and activations. We demonstrate how COMPRESS AND COMPARE supports common compression analysis tasks through two case studies, debugging failed compression on generative language models and identifying compression artifacts in image classification models. We further evaluate COMPRESS AND COMPARE in a user study with eight compression experts, illustrating its potential to provide structure to compression workflows, help practitioners build intuition about compression, and encourage thorough analysis of compression's effect on model behavior. Through these evaluations, we identify compression-specific challenges that future visual analytics tools should consider and COMPRESS AND COMPARE visualizations that may generalize to broader model comparison tasks..

Reversible Disulfide Bond Cross-Links as Tunable Levers of Phase Separation in Designer Biomolecular Condensates.

Biomolecular condensates (BCs) are membraneless hubs enriched with proteins and nucleic acids that have emerged as important players in many cellular functions. Uncovering the sequence determinants of proteins for phase separation is essential in understanding the biophysical and biochemical properties of BCs. Despite significant discoveries in the past decade, the role of cysteine residues in BC formation and dissolution has remained unknown. Here, to uncover the involvement of disulfide cross-links and their redox sensitivity in BCs, we designed a "stickers and spacers" model of phase-separating peptides interspersed with cysteines. Through biophysical investigations, we learned that cysteines promote liquid-liquid phase separation in oxidizing conditions and perpetuate liquid condensates through disulfide cross-links, which can be reversibly tuned with redox chemistry. By varying the composition of cysteines, subtle but distinct changes in the viscoelastic behavior of the condensates were observed. Empirically, we conclude that cysteines function neither as stickers nor spacers but as covalent nodes to lower the effective concentrations for sticker interactions and inhibit system-spanning percolation networks. Together, we unmask the possible role of cysteines in the formation of biomolecular condensates and their potential use as tunable covalent cross-linkers in developing redox-sensitive viscoelastic materials.

Highly Sensitive, Degradable, and Rapid Self-Healing Hydrogel Sensor with Semi-Interpenetrating Network for Recognition of Micro-Expressions.

Flexible conductive hydrogels have revolutionized the lives and are widely applied in health monitoring and wearable electronics as a new generation of sensing materials. However, the inherent low mechanical strength, sensitivity, and lack of rapid self-healing capacity results in their short life, poor detection accuracy, and environmental pollution. Inspired by the molecular structure of bone and its chemical characteristics, a novel fully physically cross-linked conductive hydrogel is fabricated by the introduction of nanohydroxyapatite (HAp) as the dynamic junction points. In detail, the dynamically cross-linked network, including multiple physical interactions, provides it with rapid self-healing ability and excellent mechanical properties (elongation at break (>1200%), tensile strength (174kPa), and resilience (92.61%)). Besides, the ions (Cl-, Li+, Ca2+) that move freely within the system impart outstanding electrical conductivity (2.46±0.15 S m-1), high sensitivity (gauge factor, GF>8), good antifreeze (-40.2°C), and humidity properties. The assembled sensor can be employed to sensitively detect various large human motions and subtle changes in behavior (facial expressions, speech recognition). Meanwhile, the hydrogel sensor can also degrade in phosphate-buffered saline solution without causing any environmental pollution. Therefore, the designed hydrogels may become a promising candidate material in the future potential applications for smart wearable sensors and electronic skin.

Reversible disulfide bond crosslinks as tunable levers of phase separation in designer biomolecular condensates.

Biomolecular condensates (BCs) are membraneless hubs enriched in proteins and nucleic acids that have become important players in many cellular functions. Uncovering the sequence determinants of proteins for phase separation is important in understanding the biophysical and biochemical properties of BCs. Despite significant discoveries in the last decade, the role of cysteine residues in BC formation and dissolution has remained unknown. Here, to determine the involvement of disulfide crosslinks and their redox sensitivity in BCs, we designed a 'stickers and spacers' model of phase-separating peptides interspersed with cysteines. Through biophysical investigations, we learned that cysteines promote liquid-liquid phase separation in oxidizing conditions and perpetuate liquid condensates through disulfide crosslinks, which can be reversibly tuned with redox chemistry. By varying the composition of cysteines, subtle but distinct changes in the viscoelastic behavior of the condensates were observed. Empirically, we conclude that cysteines are neither stickers nor spacers but function as covalent nodes to lower the effective concentrations for sticker interactions and inhibit system-spanning percolation networks. Together, we unmask the role of cysteines in protein phase behavior and the potential to develop tunable, redox-sensitive viscoelastic materials.

2024 AAFP intercat tension guidelines: recognition, prevention and management.

Social tension or conflict between household cats is common but, because it often manifests as subtle behavioral changes, it can go unnoticed; it is precisely because most signs are subtle and unrecognized that the term 'tension' is used. Where associated tension-related chronic fear-anxiety leads to more overt behavioral concerns and stress-associated disease, cats may face relinquishment by caregivers or even euthanasia if the tension is not relieved. The '2024 AAFP intercat tension guidelines: recognition, prevention and management' have been authored by a Task Force of board-certified veterinary and applied behaviorists and clinical experts in feline medicine and behavior convened by the American Association of Feline Practitioners. The aim is to support veterinary professionals in understanding social behavior between cats and, more specifically, in recognizing intercat tension, preventing or minimizing its occurrence and managing the stressors. In developing the Guidelines, the Task Force has modified the five pillars of a healthy feline environment to provide a framework to assist the prevention or management of intercat tension in households with two or more cats. Because feline social behavior is often misunderstood, the Guidelines debunk 10 common myths that have the potential to negatively impact the wellbeing of companion cats. Extensively illustrated with visual examples of intercat tension and an Appendix detailing a number of case studies, the Guidelines also include a comprehensive table of psychotherapeutic medications, and a detailed algorithm that outlines a systematic approach to preventing, recognizing and resolving intercat tension. A step-by-step approach to introducing a new cat into a household with one or more resident cats is included to further support veterinarians, and a range of management tools to promote client education accompany the Guidelines.

"Notification! You May Have Cancer." Could Smartphones and Wearables Help Detect Cancer Early?

This viewpoint paper considers the authors' perspectives on the potential role of smartphones, wearables, and other technologies in the diagnosis of cancer. We believe that these technologies could be valuable additions in the pursuit of early cancer diagnosis, as they offer solutions to the timely detection of signals or symptoms and monitoring of subtle changes in behavior that may otherwise be missed. In addition to signal detection, technologies could assist symptom interpretation and guide and facilitate access to health care. This paper aims to provide an overview of the scientific rationale as to why these technologies could be valuable for early cancer detection, as well as outline the next steps for research and development to drive investigation into the potential for smartphones and wearables in this context and optimize implementation. We draw attention to potential barriers to successful implementation, including the difficulty of the development of signals and sensors with sufficient utility and accuracy through robust research with the target group. There are regulatory challenges; the potential for innovations to exacerbate inequalities; and questions surrounding acceptability, uptake, and correct use by the intended target group and health care practitioners. Finally, there is potential for unintended consequences on individuals and health care services including unnecessary anxiety, increased symptom burden, overinvestigation, and inappropriate use of health care resources.

On the tourists’ cognitive image network and its evolution: a case of Guizhou province of China

ABSTRACT Tourist’s cognitive image network unveils the relationship among the touring cognitive experiences. The cognitive image network evolution reflects the tourists’ destination image change, which further implicates the subtle changes in behavior. The tourists’ online reviews and experience sharing could effectively help management build the cognitive image network of tourism destinations. Based on crawled travelogues in Guizhou, China from Ctrip.com, with LDA topic mining techniques, this study first constructs the image of a tourism destination, then constructs the tourist’s cognitive image network that explores the evolution of the network before and after the COVID-19 pandemic. Research results show that the cognitive image network in Guizhou mainly consists of 10 dimensions: Accommodation, diet, natural landscapes, social environment, and culture dimensions, followed by entertainment, natural environment, history, infrastructure, and economic environment. The cognitive image network evolution shows that tourists have different preferences before and after the COVID-19 pandemic. The study provides a new perspective for the study of destination image theory, which can help destination tourism enterprises to identify the tourist’s behavior choices and develop unique marketing strategies.

Mice Mutated in the First Fibronectin Domain of Adhesion Molecule L1 Show Brain Malformations and Behavioral Abnormalities.

The X-chromosome-linked cell adhesion molecule L1 (L1CAM), a glycoprotein mainly expressed by neurons in the central and peripheral nervous systems, has been implicated in many neural processes, including neuronal migration and survival, neuritogenesis, synapse formation, synaptic plasticity and regeneration. L1 consists of extracellular, transmembrane and cytoplasmic domains. Proteolytic cleavage of L1's extracellular and transmembrane domains by different proteases generates several L1 fragments with different functions. We found that myelin basic protein (MBP) cleaves L1's extracellular domain, leading to enhanced neuritogenesis and neuronal survival in vitro. To investigate in vivo the importance of the MBP-generated 70 kDa fragment (L1-70), we generated mice with an arginine to alanine substitution at position 687 (L1/687), thereby disrupting L1's MBP cleavage site and obliterating L1-70. Young adult L1/687 males showed normal anxiety and circadian rhythm activities but enhanced locomotion, while females showed altered social interactions. Older L1/687 males were impaired in motor coordination. Furthermore, L1/687 male and female mice had a larger hippocampus, with more neurons in the dentate gyrus and more proliferating cells in the subgranular layer, while the thickness of the corpus callosum and the size of lateral ventricles were normal. In summary, subtle mutant morphological changes result in subtle behavioral changes.

Navigating the diagnostic and therapeutic complexities of autoimmune encephalitis

Characterized by immune-mediated inflammation of the brain, autoimmune encephalitis (AE) encompasses a diverse array of disorders, each presenting with unique as well as overlapping clinical manifestations, and underlying autoantibodies targeting neuronal and glial surface antigens. The clinical spectrum can range from subtle cognitive and behavioural changes to severe seizures, movement disorders, and altered consciousness. However, what truly sets AE apart from other encephalitides is its potential reversibilitywhen identified early and managed appropriately. The identification of N-methyl-D-aspartate receptor (NMDAR) antibody encephalitis in 2007 heralded the discovery of a spectrum of immunotherapy-responsive AE. However, misdiagnosis remains prevalent despite diagnostic algorithms, resulting in unnecessary immunotherapies and delayed treatment of the correct diagnosis. AE diagnosis requires a judicious blend of diagnostic algorithms, antibody testing, and clinical acumen. Testing for antibodies against neuronal surface antigens, preferably in cerebrospinal fluid, is essential, but should be contextual to clinical relevance.Treatment guidelines are largely based on retrospective studies due to a dearth of randomized and prospective data. However, early immunotherapy initiation has proven to be pivotal for optimal outcomes. The therapeutic landscape in AE continues to evolve with the introduction of novel targeted immunotherapies.This review highlights the complexities, and proposes a systematic approach, to the diagnosis and treatment of AE.

Mild Behavioral Impairment

Abstract: Socially inappropriate behavior accompanies and modulates delinquency across the lifespan. In contrast to young people, the emergence of such traits among older individuals could indicate incipient neurodegenerative disease. Before developing a neurocognitive disorder, subtle behavioral changes may reflect a disintegration of neural networks involved in impulse control or social cognition. Whereas psychiatric evaluation often considers a comprehensive cognitive assessment, unremarkable results may discourage clinicians from recognizing brain disease underlying behavioral disturbance. We first provide an overview of its manifestations and neural correlates and the interrelations with mild cognitive impairment (MCI) before demonstrating how to investigate and diagnose mild behavioral impairment (MBI). Finally, we show how to appreciate MBI in geriatric forensic psychiatry.

Aspartame Safety as a Food Sweetener and Related Health Hazards.

Aspartame is the methyl-ester of the aspartate-phenylalanine dipeptide. Over time, it has become a very popular artificial sweetener. However, since its approval by the main food safety agencies, several concerns have been raised related to neuropsychiatric effects and neurotoxicity due to its ability to activate glutamate receptors, as well as carcinogenic risks due to the increased production of reactive oxygen species. Within this review, we critically evaluate reports concerning the safety of aspartame. Some studies evidenced subtle mood and behavioral changes upon daily high-dose intake below the admitted limit. Epidemiology studies also evidenced associations between daily aspartame intake and a higher predisposition for malignant diseases, like non-Hodgkin lymphomas and multiple myelomas, particularly in males, but an association by chance still could not be excluded. While the debate over the carcinogenic risk of aspartame is ongoing, it is clear that its use may pose some dangers in peculiar cases, such as patients with seizures or other neurological diseases; it should be totally forbidden for patients with phenylketonuria, and reduced doses or complete avoidance are advisable during pregnancy. It would be also highly desirable for every product containing aspartame to clearly indicate on the label the exact amount of the substance and some risk warnings.

Functional activity level reported by an informant is an early predictor of Alzheimer’s disease

BackgroundLoss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer’s disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these changes are given medical attention. In the present study, we ask if such subtle changes should be given weight as an early predictor of a future AD diagnosis.MethodsLongitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used to define a group of adults with a mild cognitive impairment (MCI) diagnosis remaining stable across several visits (sMCI, n=360; 55-91 years at baseline), and a group of adults who over time converted from having an MCI diagnosis to an AD diagnosis (cAD, n=320; 55-88 years at baseline). Eleven features were used as input in a Random Forest (RF) binary classifier (sMCI vs. cAD) model. This model was tested on an unseen holdout part of the dataset, and further explored by three different permutation-driven importance estimates and a comprehensive post hoc machine learning exploration.ResultsThe results consistently showed that measures of daily life functioning, verbal memory function, and a volume measure of hippocampus were the most important predictors of conversion from an MCI to an AD diagnosis. Results from the RF classification model showed a prediction accuracy of around 70% in the test set. Importantly, the post hoc analyses showed that even subtle changes in everyday functioning noticed by a close informant put MCI patients at increased risk for being on a path toward the major cognitive impairment of an AD diagnosis.ConclusionThe results showed that even subtle changes in everyday functioning should be noticed when reported by relatives in a clinical evaluation of patients with MCI. Information of these changes should also be included in future longitudinal studies to investigate different pathways from normal cognitive aging to the cognitive decline characterizing different stages of AD and other neurodegenerative disorders.

Markov Models for Malware and Intrusion Detection: A Survey

Malicious attacks are one of the main threats facing today's most used Android and Windows operating systems, as well as the Internet of Things (IoT) and web environments. Markov models and hidden Markov models have been used successfully over the past few decades to identify a variety of malicious activity, including as viruses, worms, Trojan horses, rootkits, ransomware, and phishing assaults. But they have their limits. One of their main limitations is that they are unable to detect subtle changes in malicious behaviour. This paper presents Markov models and hidden Markov models as a tool for detecting malicious attacks and briefly reviews different studies from the past five years that use these models as a detection tool. This review, based on publications drawn from three databases, outlines the continuing interest of security researchers in these models. Most of the chosen research papers show that these models are applied to create systems that have a detection accuracy of malicious attacks above 94%. This study can be helpful to beginners who are interested in starting their research in the field of detecting malicious attacks.

Investigating behavioral phenotypes related to autism spectrum disorder in a gene-environment interaction model of Cntnap2 deficiency and Poly I:C maternal immune activation.

Autism Spectrum Disorder (ASD) has been associated with a wide variety of genetic and environmental risk factors in both human and preclinical studies. Together, findings support a gene-environment interaction hypothesis whereby different risk factors independently and synergistically impair neurodevelopment and lead to the core symptoms of ASD. To date, this hypothesis has not been commonly investigated in preclinical ASD models. Mutations in the Contactin-associated protein-like 2 (Cntnap2) gene and exposure to maternal immune activation (MIA) during pregnancy have both been linked to ASD in humans, and preclinical rodent models have shown that both MIA and Cntnap2 deficiency lead to similar behavioral deficits. In this study, we tested the interaction between these two risk factors by exposing Wildtype, Cntnap2+/- , and Cntnap2 -/- rats to Polyinosinic: Polycytidylic acid (Poly I:C) MIA at gestation day 9.5. Our findings showed that Cntnap2 deficiency and Poly I:C MIA independently and synergistically altered ASD-related behaviors like open field exploration, social behavior, and sensory processing as measured through reactivity, sensitization, and pre-pulse inhibition (PPI) of the acoustic startle response. In support of the double-hit hypothesis, Poly I:C MIA acted synergistically with the Cntnap2 -/- genotype to decrease PPI in adolescent offspring. In addition, Poly I:C MIA also interacted with the Cntnap2+/- genotype to produce subtle changes in locomotor hyperactivity and social behavior. On the other hand, Cntnap2 knockout and Poly I:C MIA showed independent effects on acoustic startle reactivity and sensitization. Together, our findings support the gene-environment interaction hypothesis of ASD by showing that different genetic and environmental risk factors could act synergistically to exacerbate behavioral changes. In addition, by showing the independent effects of each risk factor, our findings suggest that ASD phenotypes could be caused by different underlying mechanisms.

LabGym: Quantification of user-defined animal behaviors using learning-based holistic assessment

Quantifying animal behavior is important for biological research. Identifying behaviors is the prerequisite of quantifying them. Current computational tools for behavioral quantification typically use high-level properties such as body poses to identify the behaviors, which constrains the information available for a holistic assessment. Here we report LabGym, an open-source computational tool for quantifying animal behaviors without this constraint. In LabGym, we introduce "pattern image" to represent the animal's motion pattern, in addition to "animation" that shows all spatiotemporal details of a behavior. These two pieces of information are assessed holistically by customizable deep neural networks for accurate behavior identifications. The quantitative measurements of each behavior are then calculated. LabGym is applicable for experiments involving multiple animals, requires little programming knowledge to use, and provides visualizations of behavioral datasets.We demonstrate its efficacy in capturing subtle behavioral changes in diverse animal species.

PARIN5, a Novel Thrombin Receptor Antagonist Modulates a Streptozotocin Mice Model for Diabetic Encephalopathy.

Diabetic encephalopathy (DE) is an inflammation-associated diabetes mellitus (DM) complication. Inflammation and coagulation are linked and are both potentially modulated by inhibiting the thrombin cellular protease-activated receptor 1 (PAR1). Our aim was to study whether coagulation pathway modulation affects DE. Diabetic C57BL/6 mice were treated with PARIN5, a novel PAR1 modulator. Behavioral changes in the open field and novel object recognition tests, serum neurofilament (NfL) levels and thrombin activity in central and peripheral nervous system tissue (CNS and PNS, respectively), brain mRNA expression of tumor necrosis factor α (TNF-α), Factor X (FX), prothrombin, and PAR1 were assessed. Subtle behavioral changes were detected in diabetic mice. These were accompanied by an increase in serum NfL, an increase in central and peripheral neural tissue thrombin activity, and TNF-α, FX, and prothrombin brain intrinsic mRNA expression. Systemic treatment with PARIN5 prevented the appearance of behavioral changes, normalized serum NfL and prevented the increase in peripheral but not central thrombin activity. PARIN5 treatment prevented the elevation of both TNF-α and FX but significantly elevated prothrombin expression. PARIN5 treatment prevents behavioral and neural damage in the DE model, suggesting it for future clinical research.

The importance of laboratory-based neoichnological experiments for aquatic palaeoecological analyses

Neoichnological analyses are essential for the accurate assessment and interpretation of ancient, trace-bearing sedimentary successions. Behaviours exemplified by modern organisms are diverse and commonly complex. Direct observation is most easily accomplished in shallow aquatic and subaerially exposed settings, with sustained observation limited primarily to the latter. Laboratory-based neoichnological experimentation fills the void left by the limitations on field based-studies. It also allows for the standardization of behaviour-influencing variables such as substrate parameters, water characteristics and resource availability. By altering these variables, subtle changes in behaviour and trace-making can be observed, enhancing our ability to interpret the rock record.

Primary CNS Lymphoma in an Immunocompetent Patient: An Unusual Case Illustrating the Usual Problems Facing Brain Tumour Management in a Lower-Middle-Income Country

Primary central nervous system lymphoma (PCNSL) is a rare extra-nodal non-Hodgkin lymphoma (NHL). It primarily affects the immunocompromised but is rarely seen in immunocompetent individuals. The pitfalls in the healthcare system of lower-middle-income countries produce many obstacles, impeding timely diagnosis, timely treatment, and optimal quality of care. A 57-year-old immunocompetent, diabetic female presented with progressive generalised fatiguability, forgetfulness, and subtle behavioural changes for the last one and a half years. MRI revealed an area of gyri from dense post-contrast enhancement in the right posterior parietal region. Her symptoms kept aggravating with periods of partial remission as steroids were being administered. Reasons for delays in diagnosis and hence timely treatment include lack of primary care referral, conflicting neurosurgical opinion, and absence of multidisciplinary team management. A right posterior parietal parasagittal craniotomy was performed to excise the lesion. The patient was subsequently referred for adjuvant therapy. We use our patient's clinical journey to exemplify the structural barriers to providing optimal and timely care for brain tumour patients in a developing country. Primary CNS Lymphomas in immunocompetent patients are rare. Poor infrastructure and referral pathways contribute to delayed diagnosis. Lack of multi-disciplinary care owing to organisational issues is a major problem faced by brain tumour patients in a lower-middle-income country like ours. Brain tumour management requires a specialist multidisciplinary team approach to ensure timely diagnosis and optimal treatment