Biology subjects

Hussain, S. A.

Publications and source records attributed to Hussain, S. A..

12 recordsLinked to original sources

bioRxiv2025

Prediction of treatment response in infantile epileptic spasms syndrome using EEG phase-amplitude coupling

ObjectiveTreatment selection for infantile epileptic spasms syndrome (IESS) is complex and multifaceted, and currently no EEG biomarkers can guide this decision by predicting treatment response. We tested the predictive value of phase-amplitude coupling (PAC), as IESS patients are known to have elevated PAC. MethodsWe analyzed retrospective EEG recordings from 40 IESS patients, before and after treatment, and 20 healthy controls. Patients were classified as responders (n=25) or non-responders (n=15) based on short-term treatment outcomes. We measured PAC in each EEG using modulation index (MI) and mean vector length (MVL) and analyzed the relationship between pre- and post-treatment values and the ability of pre-treatment values to predict response. ResultsMI and MVL values decreased with treatment in almost all subjects. However, non-responders had significantly higher pre-treatment MI than responders (P<0.05), suggesting utility for predicting treatment response. Logistic regression modeling suggested that a 0.5 unit decrease in log(MI), which is approximately one IQR of the pre-treatment log(MI) values, results in a 6-fold increase in odds of positive treatment response. SignificanceMI reflects short-term treatment response and is a candidate predictive EEG biomarker for IESS. MI may offer individualized insights for treatment selection and management strategies for IESS. Key Points BoxO_LIInfantile epileptic spasms syndrome (IESS) is associated with high phase-amplitude coupling (PAC) that decreases with treatment C_LIO_LILow pre-treatment values of EEG PAC are predictive of positive short-term treatment response for IESS C_LIO_LIThe results were strongest when PAC was measured using the modulation index, as this method is known to be robust to noise C_LI

neuroscience↗

bioRxiv2025

EEG Functional Connectivity as a Marker of Evolution from Infantile Epileptic Spasms Syndrome to Lennox-Gastaut Syndrome

Background and ObjectivesTimely diagnosis and effective treatment of Lennox-Gastaut Syndrome (LGS) improve prognosis and lower healthcare costs, but the transition from infantile epileptic spasms syndrome (IESS) to LGS is highly variable and insidious. Objective biomarkers are needed to monitor this progression and guide clinical decision making. MethodsWe retrospectively collected longitudinal EEG data at the Childrens Hospital of Orange County from fifteen children who were diagnosed with IESS and later with LGS between 2012 and 2021. EEGs were from IESS and LGS diagnoses, between the two diagnoses, and following LGS diagnosis. Functional connectivity networks were calculated using a cross-correlation-based method and assessed relative to diagnostic timepoint, treatment response, presence of clinical markers of disease, age, and amplitude of interictal spikes. ResultsConnectivity strength was high at LGS diagnosis and decreased after favorable response to treatment, but it remained stable or increased when response was unfavorable. In all subjects, connectivity strength was higher at the time of LGS diagnosis than at the preceding timepoint. Presence of clinical markers of LGS were associated with high connectivity strength, but no single marker predicted connectivity strength. DiscussionComputational EEG analysis can be used to map the evolution from IESS to LGS. Changes in connectivity may enable prediction of impending LGS and treatment response monitoring, thus facilitating earlier LGS treatment and guiding medical management. Key pointsO_LIEEG functional connectivity analysis can track progression from infantile epileptic spasms syndrome (IESS) to Lennox-Gastaut Syndrome (LGS). C_LIO_LIHigh connectivity strength at LGS diagnosis decreases with favorable treatment response but remains high with poor response. C_LIO_LIClinical LGS markers correlate with high connectivity, but no single marker predicts connectivity strength. C_LIO_LIEEG functional connectivity analysis may help predict LGS onset, enabling early intervention and improving prognosis. C_LI

neuroscience↗

bioRxiv2023

PyHFO: Lightweight Deep Learning-poweredEnd-to-End High-Frequency Oscillations AnalysisApplication

In the context of epilepsy studies, intracranially-recorded interictal high-frequency oscillations (HFOs) in EEG signals are emerging as promising spatial neurophysiological biomarkers for epileptogenic zones. While significant efforts have been made in identifying and understanding these biomarkers, deep learning is carving novel avenues for biomarker detection and analysis. Yet, transitioning such methodologies to clinical environments is difficult due to the rigorous computational needs of processing EEG data via deep learning. This paper presents our development of an advanced end to end software platform, PyHFO, aimed at bridging this gap. PyHFO provides an integrated and user-friendly platform that includes time-efficient HFO detection algorithms such as short-term energy (STE) and Montreal Neurological Institute and Hospital (MNI) detectors and deep learning models for artifact and HFO with spike classification. This application functions seamlessly on conventional computer hardware. Our platform has been validated to adeptly handle datasets from 10-minute EEG recordings captured via grid/strip electrodes in 19 patients. Through implementation optimization, PyHFO achieves speeds up to 50 times faster than the standard HFO detection method. Users can either employ our pre-trained deep learning model for their analyses or use their EEG data to train their model. As such, PyHFO holds great promise for facilitating the use of advanced EEG data analysis tools in clinical practice and large-scale research collaborations.

neuroscience↗

bioRxiv2023

Analysis of the Distal Urinary Tract in Larval and Adult Zebrafish Reveals Unrecognized Homology to the Human System

Little is known about the distal excretory component of the urinary tract in Danio rerio (zebrafish). This component is affected by many human diseases and disorders of development. Here, we undertook multi-level analyses to determine the structure and composition of the distal urinary tract in the zebrafish. In silico searches identified uroplakin 1a, 2-like and 3-like genes in the zebrafish genome (orthologues to genes that encode proteins that characterise the urothelium in humans). In situ hybridization demonstrated uroplakin-1a expression in the zebrafish pronephros and cloaca from 96 hours post-fertilisation. H&E sectioning of adult zebrafish demonstrated two mesonephric ducts uniting into a urinary bladder which leads to a distinct urethral opening. Immunohistochemistry identified Uroplakin 1a and 2 expression within the urothelial luminal surface and Gata3 expression in cell layers that match human urothelial expression. Fluorescent dye injections demonstrated urinary bladder function, including urine storage, intermittent micturition, and a urethral orifice separate from the larger anal canal and rectum. Our findings reveal homology between the urinary tracts of zebrafish and humans and offer the former as a model system to study disease. Summary StatementThe excretory components of the distal urinary tract in larval and adult zebrafish have been incompletely evaluated. Here, we demonstrate close homology in urinary tract anatomy between zebrafish and human, including the presence of a distinct adult urinary bladder capable of periodic micturition

evolutionary biology↗

bioRxiv2021

Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach

Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, visual verification of HFOs is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish HFOs generated from the epileptogenic zone (epileptogenic HFOs: eHFOs) from those generated from other areas (non-epileptogenic HFOs: non-eHFOs). To address these issues, we constructed a deep learning (DL)-based algorithm using HFO events from chronic intracranial electroencephalogram (iEEG) data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: 1) replicate human expert annotation of artifacts and HFOs with or without spikes, and 2) discover eHFOs by designing a novel weakly supervised model (HFOs from the resected brain regions are initially labeled as eHFOs, and those from the preserved brain regions as non-eHFOs). The "purification power" of DL is then used to automatically relabel the HFOs to distill eHFOs. Using 12,958 annotated HFO events from 19 patients, the model achieved 96.3% accuracy on artifact detection (F1 score = 96.8%) and 86.5% accuracy on classifying HFOs with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the DL-based algorithm trained from 84,602 HFO events from nine patients who achieved seizure-freedom after resection, the majority of such DL-discovered eHFOs were found to be HFOs with spikes (78.6%, p < 0.001). While the resection ratio of detected HFOs (number of resected HFOs/number of detected HFOs) did not correlate significantly with post-operative seizure freedom (the area under the curve [AUC]=0.76, p=0.06), the resection ratio of eHFOs positively correlated with post-operative seizure freedom (AUC=0.87, p=0.01). We discovered that the eHFOs had a higher signal intensity associated with ripple (80-250 Hz) and fast ripple (250-500 Hz) bands at the HFO onset and with a lower frequency band throughout the event time window (the inverted T-shaped), compared to non-eHFOs. We then designed perturbations on the input of the trained model for non-eHFOs to determine the models decision-making logic. The model probability significantly increased towards eHFOs by the artificial introduction of signals in the inverted T-shaped frequency bands (mean probability increase: 0.285, p < 0.001), and by the artificial insertion of spike-like signals into the time domain (mean probability increase: 0.452, p < 0.001). With this DL-based framework, we reliably replicated HFO classification tasks by human experts. Using a reverse engineering technique, we distinguished eHFOs from others and identified salient features of eHFOs that aligned with current knowledge. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/458385v1_ufig1.gif" ALT="Figure 1"> View larger version (81K): org.highwire.dtl.DTLVardef@39977dorg.highwire.dtl.DTLVardef@108b182org.highwire.dtl.DTLVardef@1bdf864org.highwire.dtl.DTLVardef@fe9e57_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Waterbird abundance and diversity along a stretch of Ganga River, India modified by construction of a barrage

Damming and diverting river water alters the channel characteristics and natural flow regime. The change in biotic and abiotic factors results in dissimilar habitat conditions upstream and downstream of the barrage. Given the habitat dissimilarity and therefore resource availability, we hypothesized the dissimilarity in waterbird abundance and species diversity in the river habitat upstream and downstream of the barrage. The study was conducted on a 24 km stretch of Ganga River at Narora, Uttar Pradesh, India. This stretch overlaps with a Ramsar site as well as an Important Bird and Biodiversity Area (IBA). Bird sampling was done using transect count method for summer and winter season in 2017. The abundance was studied in relation to three habitat variables viz. channel depth, channel width and anthropogenic disturbances using Generalized Linear Model. A total of 140 species of birds were recorded. There was statistically significant difference in the abundance of waterbirds between upstream and downstream stretch in winter season (Mann-Whitney U, p < 0.05). During winters, migratory waterbirds especially ducks and geese occupied the deep water upstream of barrage, while the downstream was mostly occupied by terns and cormorants. Waterbird species diversity was higher in downstream during winters (Effective Number of Species=28; Shannons Index= 3.35) and higher in upstream during summer (Effective Number of Species=25, Shannons Index=2.87). Channel width, channel depth and anthropogenic disturbance influenced waterbird abundance in both the seasons (Generalized Linear Model; p < 0.05). The influence of channel depth varied with season for the upstream stretch.

ecology↗

bioRxiv2020

Molecular evidence indicates the existence of multiple lineages of Sperata species in Indian Rivers

Sperata seenghala (Giant river-catfish) and Sperata aor (Long-whiskered catfish) are commercially important freshwater catfishes of India, belongs to family Bagridae. Due to high nutritional significance and the low number of intramuscular bones, both fishes have considerable demand in South Asian countries. Both of the Sperata species are morphologically close and well adapted to the same habitat. In this study, we have assessed the level of genetic diversity and differentiation of S. seenghala and S. aor in the Ganga River based on the mitochondrial DNA (mtDNA) control region and compared with the other major Indian rivers. We found high haplotypes diversity for both the species in the Ganga. However, it was comparatively low for S. seenghala in Mahanadi and Brahmaputra populations. The phylogenetic and median-joining network strongly indicated the presence of two distinct maternal lineages of S. seenghala from the Ganga river. Interestingly, the genetic differentiation between S. seenghala of Ganga-Brahmaputra was much higher (~25.3%) than the S. seenghala and S. aor (~17%), whereas it was comparatively low between Ganges-Mahanadi (~8.0%). Our finding provided evidence that all the three rivers: Ganga, Mahanadi, and the Brahmaputra sustain a highly diverse and genetically distinct stock of giant river catfish; therefore, all populations should be considered as a different management unit for the protection of stocks. Our findings indicated that Brahmaputra lineages qualify the species level variations. This study can be further used as a reference database for proper lineage identification of S. seenghala and S. aor that could formulate the appropriate conservation and management plans.

genetics↗

bioRxiv2020

Comprehensive studies of Head Maralla, Punjab, Pakistan vegetation for ethnopharmacological and ethnobotanical uses and their elaboration through quantitative indices

Head Maralla is a non-recognized wetland with diversified flora that becomes focus of current studies. Whole plant or their parts are being used for treating various maladies and they are the integral part of livelihood in the area. Unique species including Osmunda regalis is used for blood and renal diseases purifier. Wild plant resources are key to traditional ethnobotanical knowledge based practices and industrial applications. Current study reports Head Marala inhabitants interaction with these resources and identify priorities at species and habitat level for conservation. Four sites viz., River Tavi, Upstream Chenab, River Manawarwala Tavi and Bhalolpur were designated to record traditional knowledge through questionnaire and interviews during field trips. One hundred nineteen (119) plant species were identified belonging to 54 families, of which 87 species were of dicot, 12monocots, 05ferns, and 4 species of bryophytes. Fifty percent of the plant species were utilized as a whole for therapeutic purposes, followed by leaves which had more than 20% usage of total consumption. Ailments viz., urination (14%) followed by cough (8%), cold (7%), stomach (6%), asthma (6%), constipation (5%), laxative (5%), diarrhea (4%) etc., were associated with vegetation. Bronchial disorders, pneumonia, dyspepsia, anthelmintic and kidney stones, etc., were also among other diseases commonly cured by traditional knowledge. Fifteen percent of vegetation contributes as fodder species consumed by local community for livestock while almost 17% of local plants were utilized for industrial purposes like timber, fuel, furniture, wooden pots and sports goods. In conclusion the ecosystem of Head Maralla is a complex of aquatic, terrestrial and agricultural land that is located on climatic and geographical divides, which further add to botanical interest as included many wetland habitats with unique diversity of plants. It is suggested to devise comprehensive conservation strategies to safe indigenous knowledge in systematic way for comprehending ecological services.

plant biology↗

bioRxiv2020

Computational characteristics of interictal EEG as objective markers of epileptic spasms

ObjectiveFavorable neurodevelopmental outcomes in epileptic spasms (ES) are tied to early diagnosis and prompt treatment, but uncertainty in the identification of the disease can delay this process. Therefore, we investigated five computational electroencephalographic (EEG) measures as markers of ES. MethodsWe measured 1) amplitude, 2) power spectra, 3) entropy, 4) long-range temporal correlations, via detrended fluctuation analysis (DFA) and 5) functional connectivity of EEG data from ES patients (n=40 patients) and healthy controls (n=20 subjects), with multiple blinded measurements during wakefulness and sleep for each patient. ResultsIn ES patients, EEG amplitude was significantly higher in all electrodes. Shannon and permutation entropy were lower in ES patients than control subjects, while DFA intercept values in ES patients were significantly higher than control subjects. DFA exponent values were not significantly different between the groups. EEG functional connectivity networks in ES patients were significantly stronger than controls. Using logistic regression, a multi-attribute classifier was derived that accurately distinguished cases from controls (area under curve of 0.96). ConclusionsComputational EEG features successfully distinguish ES patients from controls in a large, blinded study. SignificanceThese objective EEG markers, in combination with other clinical factors, may speed the diagnosis and treatment of the disease, thereby improving long-term outcomes. HighlightsO_LIObjective computational EEG features may aid diagnosis of epileptic spasms (ES) C_LIO_LIES EEG has increased delta and theta power and decreased entropy relative to controls C_LIO_LIStronger functional connectivity networks differentiate ES patients from controls C_LI

neuroscience↗

bioRxiv2020

Wavefront-sensorless adaptive optics with a laser-free spinning disk confocal microscope

Adaptive optics is being applied widely to a range of microscopies in order to improve imaging quality in the presence of specimen-induced aberrations. We present here the first implementation of wavefront-sensorless adaptive optics for a laser-free, aperture correlation, spinning disk microscope. This widefield method provides confocal-like optical sectioning through use of a patterned disk in the illumination and detection paths. Like other high-resolution microscopes, its operation is compromised by aberrations due to refractive index mismatch and variations within the specimen. Correction of such aberrations shows improved signal level, contrast and resolution.

cell biology↗

bioRxiv2020

Scalp EEG interictal high frequency oscillations as an objective EEG biomarker of infantile spasms

ObjectiveTo investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms. MethodsWe retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs). ResultsTwenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p < 0.001 by HFO rate; p < 0.01 by MIs at 3-4 Hz; p = 0.02 by MIs at 0.5-1 Hz). The presence of active spasms was predicted by the logistic regression models incorporating HFO-related metrics (AUC: 0.80-0.98) better than that incorporating hypsarrhythmia (AUC: 0.61). The predictive performance of the best model remained favorable (87.5% accuracy) after a cross-validation procedure. ConclusionsIncreased rate of HFOs and coupling between HFOs and SWA are associated with active epileptic spasms. SignificanceScalp-recorded HFOs may serve as an objective EEG biomarker for active epileptic spasms. HighlightsO_LIObjective analyses of scalp high frequency oscillations and its coupling with slow-wave activity in infantile spasms were feasible. C_LIO_LIIncreased rate of high frequency oscillations and its coupling with slow-wave activity correlated with active epileptic spasms. C_LIO_LIThe scalp high frequency oscillations were also detected in neurologically normal children (although at the low rate). C_LI

neuroscience↗

bioRxiv2019

Demographic and genetic structure of a severely fragmented population of the endangered hog deer (Axis porcinus) in the Indo- Burma biodiversity hotspot

The population of the globally endangered hog deer (Axis porcinus) has declined severely across its geographic range. Intensive monitoring of its demographic and genetic status is necessary. Northeast India is a stronghold of the species; however, in recent years the population has been getting fragmented, and it is vulnerable to extinction. We examined the demographic and genetic structure of a small hog deer population in the floating meadows of Keibul Lamjao National Park (KLNP), located on the western fringe of the Indo-Burma biodiversity hotspot for conservation planning. We used a double-observer distance sampling method to derive the hog deer abundance and population structure. We also derived the genetic diversity of the population through microsatellite screening and bottleneck detection. Our study revealed that the abundance of the deer in the park was 1.82-4.32 individuals/km2. The adult male to female ratio and fawn to doe ratio were 36.2 {+/-} 1.9 males/100 females and 16.5 {+/-} 0.4 fawns/100 females, respectively. The mean number of alleles at 23 loci was 2.70 {+/-} 0.18, the observed heterozygosity (HO) ranged from 0.26 to 0.63 (mean 0.42 {+/-} 0.02), the expected heterozygosity (HE) ranged from 0.23 to 0.73 ({chi} = 0.51 {+/-} 0.03), and the polymorphic information content (PIC) ranged from 0.2 to 0.67 ({chi} = 0.43 {+/-} 0.03). The observed allelic distribution reveals that the population has not encountered any genetic bottleneck in the recent past. Although the population is declining, it still retains some rare alleles, and the genetic diversity is 50%. This diversity will probably not affect the short-term population growth but may affect the evolutionary potential by limiting the selection flexibility. Conservation measures coupled with a scientifically sound management regime may help the persistence of the population in the region at a time when the population still retains rare alleles and maintains reproductive fitness.

genetics↗