Search

Introduction: Post-exercise heart rate recovery (PEHRR) is the measure of parasympathetic function of heart which decreases the heart rate as the person stops exercising. The post exercise heart rate recovery is easily measurable index of heart parasympathetic activity. The post – exercise heart rate recovery is computed as peak heart rate minus the heart rate measured after 1 min of termination of exercise. The risk of cardiovascular disease in individual with African background is greater as compared to Caucasians and Asian population. The aim of this study was to analyze the difference in post exercise heart rate recovery in individuals from different ethnic backgrounds. Methods: A thorough literature search was carried out on PubMed, Google Scholar and PakMediNet with articles published between 2007 till 2021. The articles with post – exercise heart rate recovery in male adults with different ethnic backgrounds were included. A total of 8 studies were included after meeting the inclusion criteria for the meta-analysis. The studies that measured heart rate recovery after 1 minute of termination of exercise were included. Results: Out of 174 subjects 51 individuals were Africans, 104 were Asians and 19 were Caucasians. The post exercise heart raterecovery was not found to be statistically significant between the individuals from different ethnic groups (p value-0.258). Conclusion: The post – exercise heart rate recovery is not influenced by the racial differences. Further research on larger scale assessing the impact of parasympathetic activity in terms of heart rate recovery in individual from different ethnic background is required as very limited data is available till date.

Oxidative stress (OS) in simple words is defined as a state of imbalance between antioxidant and pro-oxidants defenses. The purpose of this article is to find out the connection of oxidative stress and free radical species with different aspects of human health. Owing to its harmful effects on proteins and nucleic acids, oxidative stress causes chronic diseases such as cardiovascular and neurodegenerative diseases, diabetes and cancer. It highlights the impacts of antioxidants and pro-oxidants particularly on fertility and infertility. It also focuses on the adverse effects caused by the long-term exposure to pro-oxidant factors leading to structural defects of mitochondrial DNA. As modern life style consists of more reliance on the processed foods and lack of physical activity, a nutrition deficiency, which is common in the present lifestyle, is also one of the reasons for oxidative stress to cause inflammation. However, this review also focuses on how diet affects and triggers inflammation. Redox mechanism with potential threats to health of mankind is discussed, how mere stress can provoke biological stress responses leading to development of disease or metabolic errors. Methods for reduction of oxidative stress are discussed in this review. It also highlights mitochondria as an aging factor as many ROS, particularly mitochondria ROS contribute directly to aging in human body. We will be discussing the recent findings in the oxidative stress field and its negative and positive impacts on human health.

Functional connectivity, as estimated using resting state functional MRI, has shown potential in bridging the gap between pathophysiology and cognition. However, clinical use of functional connectivity biomarkers is impeded by unreliable estimates of individual functional connectomes and lack of generalizability of models predicting cognitive outcomes from connectivity. To address these issues, we combine the frameworks of connectome predictive modeling and differential identifiability. Using the combined framework, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. Using a comprehensive spectrum of cognitive outcomes associated to Alzheimer's disease (AD), we identify and characterize functional networks associated to specific cognitive deficits exhibited in AD. This combined framework is an important step in making individual level predictions of cognition from resting state functional connectomes and in understanding the relationship between cognition and connectivity., Using differential identifiability and connectome predictive modeling, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. The framework allows us to more robustly identify and characterize functional networks associated to specific cognitive outcomes exhibited in AD.

Author Summary Understanding and measuring the ways in which human brain connectivity changes to accommodate a broad range of cognitive and behavioral goals is an important undertaking. We put forth a mesoscopic framework that captures such changes by tracking the topology and integration of information within and between functional networks (FNs) of the brain. Canonically, when FNs are characterized, they are separated from the rest of the brain network. The two metrics proposed in this work, trapping efficiency and exit entropy, quantify the topological and information integration characteristics of FNs while they are still embedded in the overall brain network. Trapping efficiency measures the module's ability to preserve an incoming signal from escaping its local topology, relative to its total exiting weights. Exit entropy measures the module's communication preferences with other modules/networks using information theory. When these two metrics are plotted in a 2D graph as a function of different brain states (i.e., cognitive/behavioral tasks), the resulting morphospace characterizes the extent of network reconfiguration between tasks (functional reconfiguration), and the change when moving from rest to an externally engaged "task-positive" state (functional preconfiguration), to collectively define network configural breadth. We also show that these metrics are sensitive to subject, task, and functional network identities. Overall, this method is a promising approach to quantify how human brains adapt to a range of tasks, and potentially to help improve precision clinical neuroscience., The quantification of human brain functional (re)configurations across varying cognitive demands remains an unresolved topic. We propose that such functional configurations may be categorized into three different types: (a) network configural breadth, (b) task-to task transitional reconfiguration, and (c) within-task reconfiguration. Such functional reconfigurations are rather subtle at the whole-brain level. Hence, we propose a mesoscopic framework focused on functional networks (FNs) or communities to quantify functional (re)configurations. To do so, we introduce a 2D network morphospace that relies on two novel mesoscopic metrics, trapping efficiency (TE) and exit entropy (EE), which capture topology and integration of information within and between a reference set of FNs. We use this framework to quantify the network configural breadth across different tasks. We show that the metrics defining this morphospace can differentiate FNs, cognitive tasks, and subjects. We also show that network configural breadth significantly predicts behavioral measures, such as episodic memory, verbal episodic memory, fluid intelligence, and general intelligence. In essence, we put forth a framework to explore the cognitive space in a comprehensive manner, for each individual separately, and at different levels of granularity. This tool that can also quantify the FN reconfigurations that result from the brain switching between mental states.

Objectives: To determine the role of 800 mg oral gabapentin in attenuating cardiovascular response to laryngoscopy and tracheal intubation. Study Design: Double Blind Randomized Control Trial. Setting: Independent University Hospital/Independent Medical College, Faisalabad, Pakistan. Period: Six months from January1st 2019 to June 30th 2019. Material & Methods: This study included 60 patients which were divided into two equal groups. 800 mg oral gabapentin was given to group I while capsule placebo was administrated to group II patients in pre-operative area one hour prior to surgery. Heart rate, systolic, diastolic and mean arterial blood pressure were taken after induction of anesthesia at base line and then 1,2,3,4,5,10 and 15 minutes after endotracheal intubation. SPSS version 11 was used to analyze the data. Heart rate systolic, diastolic and mean arterial blood pressure were dependent variables while placebo and gabapentin were independent variables. Results: Out of total 60 patients there were 36 (60 %) males and 24 (40 %) females. In group I mean age was 37.1 while in group II it was 36.3. As compare to group II there was decreased cardiovascular response in group I. There was a significant decrease in systolic blood pressure at 1,2 and 10 minutes; diastolic blood pressure at 3 minutes; heart rate at 10 and 15 minutes and mean arterial blood pressure at 3 minutes after induction in group I. Conclusion: Cardiovascular response to laryngoscopy and intubation is significantly reduced with oral gabapentin.

The identifiability framework (𝕀f) has been shown to improve differential identifiability (reliability across-sessions and -sites, and differentiability across-subjects) of functional connectomes for a variety of fMRI tasks. But having a robust single session/subject functional connectome is just the starting point to subsequently assess network properties for characterizing properties of integration, segregation, and communicability, among others. Naturally, one wonders whether uncovering identifiability at the connectome level also uncovers identifiability on the derived network properties. This also raises the question of where to apply the 𝕀f framework: on the connectivity data or directly on each network measurement? Our work answers these questions by exploring the differential identifiability profiles of network measures when 𝕀f is applied (a) on the functional connectomes, and (b) directly on derived network measurements. Results show that improving across-session reliability of functional connectomes (FCs) also improves reliability of derived network measures. We also find that, for specific network properties, application of 𝕀f directly on network properties is more effective. Finally, we discover that applying the framework, either way, increases task sensitivity of network properties. At a time when the neuroscientific community is focused on subject-level inferences, this framework is able to uncover FC fingerprints, which propagate to derived network properties., Author Summary Functional connectome (FC) fingerprinting recently became a topic of great interest in network neuroscience. We recently proposed a framework to improve brain fingerprint (i.e., identifiability) of FCs, which improves not only test-retest reliability but also the correlation of FCs with fluid intelligence. However, does this improvement in FC fingerprints propagate to the derived network measures? In this work we found that improving the fingerprint (differential identifiability) of the functional connectome also improves the “fingerprint” of its network properties. Furthermore, when using the identifiability framework on the network properties directly, certain network properties like search information and communicability add to the FC fingerprint. Finally, we show that enhancement of the fingerprint in the network measures, in a wide range of cognitive tasks, using the identifiability framework also improves task sensitivity in these measures. We show that regardless of whether you are using functional connectomes or the network properties derived from them, using the 𝕀f framework on the functional connectomes would be a beneficial first step.

Objectives: To observe the frequency of spinal hypotension in patients undergoing Elective Lower Segment Caesarean Section receiving pre-operative preload compared with intramuscular ephedrine. Study Design: Cross Sectional study. Setting: Department of Anesthesia, Independent Medical College, Faisalabad. Period: July 1st 2018 to December 31st 2018. Material & Methods: This study included fifty-two female patients, aged 20-35 years, undergoing elective C/section under spinal anesthesia with ASA physical status I & II, pre-operatively preloaded and given prophylactic intramuscular ephedrine. Hemodynamic changes were recorded in both groups after receiving spinal anesthesia. Results: Compared with the prophylactic ephedrine group, frequency of Post spinal hypotension was higher significantly in pre-load group (p=0.019). Conclusion: It has been concluded that there is the use of prophylactic intra muscular ephedrine is associated with low incidence of post spinal hypotension.

Ultrasound (U/S) imaging has a broad spectrum of applications in medical practice. The earthquake of October 8, 2005 was one of the most severe in the history of Pakistan, claiming around 80,000 lives in the region of Azad Kashmir. U/S imaging was the only diagnostic radiological investigation available in the region. The study was aimed to evaluate the role of U/S in diagnosing internal injuries among victims of the earthquake. All the patients referred for U/S imaging at Abbas Institute of Medical Sciences (AIMS) were accordingly examined and the data was recorded on a proforma. The procedures included examination of chest, abdomen, pelvis, extremities and fetal wellbeing (FWB). U/S findings were correlated with clinical, laboratory or surgical exploratory findings. A total of 87 patients, 22 males and 65 females, were examined. Definitive diagnoses were established in 16.8% of abdominal examination cases, 76.6% of abdomen/pelvis examinations and 78.6% of Gynae & Obstetric examination cases. The course of management was changed completely using U/S observations in 36% of the cases of chest examinations, 71.9% of the cases of abdominal & pelvic examination and 75.8% of the cases of Gynae & Obstetrics. It was concluded that U/S is a useful diagnostic modality in the settings of a natural disaster. Head and spine injuries, however, cannot be assessed with this diagnostic modality and needs special consideration.

The concept of the brain has shifted to a complex system where different subnetworks support the human cognitive functions. Neurodegenerative diseases would affect the interactions among these subnetworks and, the evolution of impairment and the subnetworks involved would be unique for each neurodegenerative disease. In this study, we seek for structural connectivity traits associated with the family history of Alzheimer’s disease, that is, early signs of subnetworks impairment due to Alzheimer’s disease. The sample in this study consisted of 123 first-degree Alzheimer’s disease relatives and 61 nonrelatives. For each subject, structural connectomes were obtained using classical diffusion tensor imaging measures and different resolutions of cortical parcellation. For the whole sample, independent structural-connectome-traits were obtained under the framework of connICA. Finally, we tested the association of the structural-connectome-traits with different factors of relevance for Alzheimer’s disease by means of a multiple linear regression. The analysis revealed a structural-connectome-trait obtained from fractional anisotropy associated with the family history of Alzheimer’s disease. The structural-connectome-trait presents a reduced fractional anisotropy pattern in first-degree relatives in the tracts connecting posterior areas and temporal areas. The family history of Alzheimer’s disease structural-connectome-trait presents a posterior–posterior and posterior–temporal pattern, supplying new evidences to the cascading network failure model.

Background: Functional connectomes (FCs) have been shown to provide a reproducible individual fingerprint, which has opened the possibility of personalized medicine for neuro/psychiatric disorders. Thus, developing accurate ways to compare FCs is essential to establish associations with behavior and/or cognition at the individual level., Methods: Canonically, FCs are compared using Pearson's correlation coefficient of the entire functional connectivity profiles. Recently, it has been proposed that the use of geodesic distance is a more accurate way of comparing FCs, one which reflects the underlying non-Euclidean geometry of the data. Computing geodesic distance requires FCs to be positive-definite and hence invertible matrices. As this requirement depends on the functional magnetic resonance imaging scanning length and the parcellation used, it is not always attainable and sometimes a regularization procedure is required., Results: In the present work, we show that regularization is not only an algebraic operation for making FCs invertible, but also that an optimal magnitude of regularization leads to systematically higher fingerprints. We also show evidence that optimal regularization is data set-dependent and varies as a function of condition, parcellation, scanning length, and the number of frames used to compute the FCs., Discussion: We demonstrate that a universally fixed regularization does not fully uncover the potential of geodesic distance on individual fingerprinting and indeed could severely diminish it. Thus, an optimal regularization must be estimated on each data set to uncover the most differentiable across-subject and reproducible within-subject geodesic distances between FCs. The resulting pairwise geodesic distances at the optimal regularization level constitute a very reliable quantification of differences between subjects.

Many approaches and tools have been utilized throughout the globe by public and private sector organizations to curtail the deprivations and enhance welfare of the poor. Islamic Microfinance is one of them and is rapidly getting popular in Muslims as well as non-Muslims majority population countries. This study was conducted to gauge the impact of Islamic microfinance on the household welfare of the target clients by observing its impact on health, education, income, expenditures and assets of the poor who took loan from Islamic Microfinance institutions (IMFIs). Study is based on primary data and assessment was made rendering pre and post project approach by employing paired sample t-test and Regressionanalysis as statistical tools. Respondents were selected from three microfinance institutions, namely Akhuwat Foundation, Farz Foundation and NAYMET. Results delineate statistically significant differences in Pre and Post borrowing scenarios in the welfare indicators of the target households. It has been observed that borrowing from Islamic Microfinance institutions has not only significantly raised monthly income; expenditures on food, education and health; and incremented households’ assetsbut also surprisingly raised borrowed amount of loan which negatively affected income. This requires some further investigation and it is recommended that practitioners and policy makers must keep IMF on its top agenda to enhanceliving standards of the poor in developing countries.

It has been well established that Functional Connectomes (FCs), as estimated from functional MRI (fMRI) data, have an individual fingerprint that can be used to identify an individual from a population (subject-identification). Although identification rate is high when using resting-state FCs, other tasks show moderate to low values. Furthermore, identification rate is task-dependent, and is low when distinct cognitive states, as captured by different fMRI tasks, are compared. Here we propose an embedding framework, GEFF (Graph Embedding for Functional Fingerprinting), based on group-level decomposition of FCs into eigenvectors. GEFF creates an eigenspace representation of a group of subjects using one or more task FCs (Learning Stage). In the Identification Stage, we compare new instances of FCs from the Learning subjects within this eigenspace (validation dataset). The validation dataset contains FCs either from the same tasks as the Learning dataset or from the remaining tasks that were not included in Learning. Assessment of validation FCs within the eigenspace results in significantly increased subject-identification rates for all fMRI tasks tested and potentially task-independent fingerprinting process. It is noteworthy that combining resting-state with one fMRI task for GEFF Learning Stage covers most of the cognitive space for subject identification. In addition to subject-identification, GEFF was also used for identification of cognitive states, i.e. to identify the task associated to a given FC, regardless of the subject being already in the Learning dataset or not (subject-independent task-identification). In addition, we also show that eigenvectors from the Learning Stage can be characterized as task-dominant, subject dominant or neither, providing a deeper insight into the extent of variance in functional connectivity across individuals and cognitive states., 30 pages; 6 figures; 5 supplementary figures

Background: Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional magnetic resonance imaging (fMRI) blood-oxygenation-level dependent time series. The network representation of functional connectivity, called a functional connectome (FC), has been shown to contain an individual fingerprint allowing participants identification across consecutive testing sessions. Recently, researchers have focused on the extraction of these fingerprints, with potential applications in personalized medicine., Materials and Methods: In this study, we show that a mathematical operation denominated degree-normalization can improve the extraction of FC fingerprints. Degree-normalization has the effect of reducing the excessive influence of strongly connected brain areas in the whole-brain network. We adopt the differential identifiability framework and apply it to both original and degree-normalized FCs of 409 individuals from the Human Connectome Project, in resting-state and 7 fMRI tasks., Results: Our results indicate that degree-normalization systematically improves three fingerprinting metrics, namely differential identifiability, identification rate, and matching rate. Moreover, the results related to the matching rate metric suggest that individual fingerprints are embedded in a low-dimensional space., Discussion: The results suggest that low-dimensional functional fingerprints lie in part in weakly connected sub-networks of the brain and that degree-normalization helps uncovering them. This work introduces a simple mathematical operation that could lead to significant improvements in future FC fingerprinting studies.

Objectives: To assess serum Neopterin levels in blood donors of local population and to study its relationship with transfusion transmitted infections (TTIs) including syphilis. Study Design: Descriptive cross-sectional study. Place and Duration of Study: This study was carried out in the Department of Physiology LNMC in collaboration with Basic Medical Sciences Institute, (BMSI), and Jinnah Post Graduate Medical Centre (J.P.M.C.) Karachi, from Jan to July 2015.”Methods: Total 174 blood donors were included in the study through random sampling technique. They were screen through the standard procedures used for screening at the JPMC blood bank for WHO recommended diseases. Neopterin was estimated using ELISA. Data analysis was performed using SPSS version 21. Chi square and ANOVA were applied at a confidence level of 95%.”Results: Neopterin level in the sera of syphilis positive blood donors was 5.86 ± 0.78 nmol/l which was within normal range below the cutoff value of 10 nmol/l. Neopterin content in the serum of blood donors who were negative for transfusion transmitted infections was 6.23± 2.19 nmol/l as compared to blood donors testing positive for transfusion transmitted viral infections showing high Neopterin level of 15.10 ± 4.93 nmol/l. (P value 0.001).”Conclusion: Neopterin levels were found to be within normal limits in blood donors testing positive for syphilis However in blood donors with transfusion transmitted viral infections serum neopterin levels were elevated.

Unemployment is a syndrome which is a common feature of all developing nations. Masses are either unemployed or self-employed due to lack of opportunities and distorted public policies regarding employment generation in these countries. Microenterprises financing through microfinance institutions are playing a pivotal role in creating employment opportunities for their target households. This study observes the impact of Islamic microfinance on self, family and community employment generation activities. In this regard, data were collected from 168 clients of three pioneering Islamic microfinance institutions working in Lahore, Pakistan. The study uses descriptive analysis and probability econometric modeling to achieve its objectives. The results show that the Islamic microfinance played a significant role in starting and extending existing businesses of the target households. Moreover, it also helps households and community members to get absorbed in the microenterprises apart from borrowers themselves. Therefore, it is concluded that Islamic microfinance does go beyond self-employability.

Cerebrovascular reactivity (CVR) is impaired following brain injury, increasing susceptibility to subsequent injury. CVR was tracked in football and non-collision athletes throughout one season. CVR transiently decreased in football athletes during the first half of the season. Results indicate the brain adapts slowly to increases in loading, increasing risk for injury.

Visual working memory deficits have been observed in at-risk athletes. This study uses a visual N-back working memory functional magnetic resonance imaging task to longitudinally assess asymptomatic football athletes for abnormal activity. Athletes were increasingly "flagged" as the season progressed. Flagging may provide early detection of injury.

Sub-concussive head impacts are identified as a source of accrued damage. Football athletes experience hundreds of such blows each season. Resting state functional magnetic resonance imaging was used to prospectively study changes in Default Mode Network connectivity for clinically asymptomatic high school football athletes. Athletes exhibited short-term changes relative to baseline and across sessions.

Magnetic resonance spectroscopy and helmet telemetry were used to monitor the neural metabolic response to repetitive head collisions in 25 high school American football athletes. Specific hit characteristics were determined highly predictive of metabolic alterations, suggesting that sub-concussive blows can produce biochemical changes and potentially lead to neurological problems.

Microfinance is a general term that entails the provision of financial services to micro- entrepreneurs or to those who do not have access to banking facilities. The current issues faced by micro-entrepreneurs are difficulties in seeking financing from financial institutions due to lack of sufficient collateral, no credit history, irregular or uneasily verified sources of income. Consequently, they often rely on relatives or local moneylender s who charge high interest rates. Thus, on grounds of equity and justice, Islamic microfinance seems to provide an alternative needed by them. This research deals with the perceptions of micro-entrepreneurs and petty traders towards conventional and Islamic microfinance in Pakistan. It further investigates the intention to use Islamic microfinance and challenges for the micro-entrepreneurs. A total of 270 people were surveyed by means of self- administered questionnaire. The sample comprises 81 percent males and 19 percent females in three major cities; Rawalpindi, Lahore and Peshawar. Results of this study indicate that Islamic microfinance is a preferred choice as compared to conventional microfinance and best answer to poverty eradication. Although, Islamic microfinance is a new concept but majority of respondents had some understanding of this concept. However, the respondents also expressed their dissatisfaction to the management of Islamic banks.

Objective For both subconcussive impacts and traditionally-defined concussion, neither the number of head impacts nor the magnitude has had a strong correlation to the incidence or severity of injury. Recent modelling work has suggested that impulse may be an important biomechanical factor, and therefore it is hypothesised that it may be a good predictor of subconcussive neurophysiological changes. Design Observational study. Setting American high school football team. Participants Nine male high school football athletes (mean age=16.4, range=15–17) volunteered. All participants were enrolled with parental consent. Assessment of risk factors Head impacts were monitored at all practices and games with the Head Impact Telemetry System. Baseline neurophysiology was measured prior to contact activity using a functional magnetic resonance imaging (fMRI) visual n-back task protocol. Subjects returned throughout the season and were re-evaluated according to the same protocol. Outcome measures Kinematic impulse was computed from head impact telemetry. Changes in neurophysiology were determined as the difference in the 2 vs. 1-back contrast. This contrast was determined for 116 anatomically defined regions of interest (ROI). Main results Stepwise regressions (P=0.05) relating kinematic impulse to ROI-specific changes in neurophysiology yielded significant correlations for 57/116 ROIs. 22/116 ROIs had an R2 value greater than 0.70. Correlations were found bilaterally for 16 anatomical ROIs, including the executive pre-frontal regions, basal ganglia, and thalamus. Conclusions The relationship between kinematic impulse and fMRI changes reported here are the strongest correlations to subconcussive changes reported to date. Correlations were observed bilaterally in regions associated with concussion symptoms. Competing interests None.

Long-term neurological damage as a result of head trauma while playing sports is a major concern for football athletes today. Repetitive concussions have been linked to many neurological disorders. Recently, it has been reported that repetitive subconcussive events can be a significant source of accrued damage. Since football athletes can experience hundreds of subconcussive hits during a single season, it is of utmost importance to understand their effect on brain health in the short and long term. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was used to study changes in the default mode network (DMN) after repetitive subconcussive mild traumatic brain injury. Twenty-two high school American football athletes, clinically asymptomatic, were scanned using the rs-fMRI for a single season. Baseline scans were acquired before the start of the season, and follow-up scans were obtained during and after the season to track the potential changes in the DMN as a result of experienced trauma. Ten noncollision-sport athletes were scanned over two sessions as controls. Overall, football athletes had significantly different functional connectivity measures than controls for most of the year. The presence of this deviation of football athletes from their healthy peers even before the start of the season suggests a neurological change that has accumulated over the years of playing the sport. Football athletes also demonstrate short-term changes relative to their own baseline at the start of the season. Football athletes exhibited hyperconnectivity in the DMN compared to controls for most of the sessions, which indicates that, despite the absence of symptoms typically associated with concussion, the repetitive trauma accrued produced long-term brain changes compared to their healthy peers.

With growing evidence of long-term neurological damage in individuals enduring repetitive head trauma, it is critical to detect lower-level damage accumulation for the early diagnosis of injury in at-risk populations. Proton magnetic resonance spectroscopic scans of the dorsolateral prefrontal cortex and primary motor cortex were collected from high school American (gridiron) football athletes, prior to and during their competition seasons. Although no concussions were diagnosed, significant metabolic deviations from baseline and non-collision sport controls were revealed. Overall the findings indicate underlying biochemical changes, consequential to repetitive hits, which have previously gone unnoticed due to a lack of traditional neurological symptoms.