Network medicine in ovarian cancer: topological properties to drug discovery.

Network medicine provides network theoretical tools, methods and properties to study underlying laws governing human interactome to identify disease states and disease complexity leading to drug discovery. Within this framework, we investigated the topological properties of ovarian cancer network (OCN) and the roles of hubs to understand OCN organization to address disease states and complexity. The OCN constructed from the experimentally verified genes exhibits fractal nature in the topological properties with deeply rooted functional communities indicating self-organizing behavior. The network properties at all levels of organization obey one parameter scaling law which lacks centrality lethality rule. We showed that $\langle k\rangle $ can be taken as a scaling parameter, where, power law exponent can be estimated from the ratio of network diameters. The betweenness centrality $C_B$ shows two distinct behaviors one shown by high degree hubs and the other by segregated low degree nodes. The $C_B$ power law exponent is found to connect the exponents of distributions of high and low degree nodes. OCN showed the absence of rich-club formation which leads to the missing of a number of attractors in the network causing formation of weakly tied diverse functional modules to keep optimal network efficiency. In OCN, provincial and connector hubs, which includes identified key regulators, take major responsibility to keep the OCN integrity and organization. Further, most of the key regulators are found to be over expressed and positively correlated with immune infiltrates. Finally, few potential drugs are identified related to the key regulators.

Automated bidirectional coupling of multiscale models of aerosol dosimetry: validation with subject-specific deposition data.

Assessing the toxicity of airborne particulate matter or the efficacy of inhaled drug depends upon accurate estimates of deposited fraction of inhaled materials. In silico approaches can provide important insights into site- or airway-specific deposition of inhaled aerosols in the respiratory system. In this study, we improved on our recently developed 3D/1D model that simulate aerosol transport and deposition in the whole lung over multiple breath cycles (J. Aerosol Sci 151:105647). A subject-specific multiscale lung model of a healthy male subject using computational fluid-particle dynamics (CFPD) in a 3D model of the oral cavity through the large bronchial airways entering each lobe was bidirectionally coupled with a recently improved Multiple Path Particle Dosimetry (MPPD) model to predict aerosol deposition over the entire respiratory tract over multiple breaths for four conditions matching experimental aerosol exposures in the same subject from which the model was developed. These include two particle sizes (1 and 2.9 µm) and two subject-specific breathing rates of ~300 ml/s (slow breathing) and ~750 ml/s (fast breathing) at a target tidal volume of 1 L. In silico predictions of retained fraction were 0.31 and 0.29 for 1 µm and 0.66 and 0.62 for 2.9 µm during slow and fast breathing, respectively, and compared well with experimental data (1 µm: 0.31±0.01 (slow) and 0.27±0.01 (fast), 2.9 µm: 0.63±0.03 (slow) and 0.68±0.02 (fast)). These results provide a great deal of confidence in the validity and reliability of our approach.

Genome-wide detection of copy number variations in Tharparkar cattle.

Copy number variations (CNVs) are major forms of genetic variation with an increasing importance in animal genomics. This study used the Illumina BovineSNP 50 K BeadChip to detect the genome-wide CNVs in the Tharparkar cattle. With the aid of PennCNV software, we noticed a total of 447 copy number variation regions (CNVRs) across the autosomal genome, occupying nearly 2.17% of the bovine genome. The average size of detected CNVRs was found to be 122.2 kb, the smallest CNVR being 50.02 kb in size, to the largest being 1,232.87 Kb. Enrichment analyses of the genes in these CNVRs gave significant associations with molecular adaptation-related Gene Ontology (GO) terms. Most CNVR genes were significantly enriched for specific biological functions; signaling pathways, sensory responses to stimuli, and various cellular processes. In addition, QTL analysis of CNVRs described them to be linked with economically essential traits in cattle. The findings here provide crucial information for constructing a more comprehensive CNVR map for the indigenous cattle genome.

Is mucormycosis the end? A comprehensive management of orbit in COVID associated rhino-orbital-cerebral mucormycosis: preserving the salvageable.

BACKGROUND: Rhino-orbital-cerebral mucor mycosis (ROCM) is a relatively rare opportunistic infection caused by the Mucorales species. While ROCM suggests involvement of the paranasal sinuses, orbit and brain ROM (rhino-orbital-Mucormycosis) stands for the fungal invasion in sinuses and orbit sans cerebral involvement. In India with the outbreak of the second COVID wave and the delta variant of the virus, there has been a steep increase in this opportunistic fulminant fungal infection, named COVID-associated Mucor mycosis (CAM). The most critical question in orbital management is when to go ahead with an exenteration. Our study aims to design a pertinent minimal invasive surgical protocol for surgeons to manage such cases based on our surgical experience and mitigate the need for exenteration and save the eyes wherever possible. METHODS: The study is a retrospective analysis of patients of ROM with and without brain involvement, who underwent minimal surgical management between March 2021 to March 2022 along with their follow-up. RESULTS: There were 184 eyes of 148 patients diagnosed with CAM. The mean age was 51.7 years with a male predominance of 103 (70%). All patients developed ROM following the COVID-19 infection and the duration between diagnosis of COVID-19 and ROM was 36 ± 23 days. 18 cases (12%) were bilateral. 76 eyes (41%) had no vision at the presentation. Imaging revealed paranasal sinus involvement (100%), orbital apex involvement (61%), cavernous sinus involvement (53%), and central nervous system (CNS) involvement (47%). All the patients (100%) were treated with systemic Liposomal amphotericin-B and sinus debridement. Endoscopic debridement of the orbital disease was performed in 45 (30.4%) cases, 15(8.1%) eyes underwent exenteration and were later rehabilitated with a customized ocular prosthesis, 103 (56%) eyes underwent transcutaneous retrobulbar amphotericin-B. At a mean follow-up of 13.1 months; the complete resolution was seen in 25 (17%) cases, the residual stable lesion was seen in 77(52%) of the cases and new lesions were developed in 13(9%) of the cases. Mortality was seen in 33 (22%) patients and all of them had CNS involvement. CONCLUSIONS: Systemic and protocol-based management can save the life and salvage the eyes.

Knowledge and Information Resources about Child Abuse among Government and Private Dental Practitioner in Uttar Pradesh, India.

Background and Aim: To evaluate knowledge, attitude, and information sources about child abuse and neglect (CAN) among dentists in Varanasi district of Uttar Pradesh state, India. Subjects and Methods: A cross-sectional online survey was carried out of dentist working in government and private hospitals in the Varanasi district, Uttar Pradesh State, India (n = 674). The structured questionnaire was sent through electronic mail that contained the consent form, instructions for filling, and returning the questionnaire. The data obtained were systematically compiled and the Chi-square test was applied to test the association. The significance level of P ≤ 0.05 was applied. Results: A maximum number of dental practitioners from the government (81.97%) and private sector (85.98%) were aware of the child protection law. A significant number of government and private dental practitioners were satisfied with their knowledge (p = 0.0092); however, 83.79% suggested that the continuing education programs/courses were important tool to update their knowledge. The girl child was maximum sufferer (p = 0.0056) of CAN. Only 14.08% of practitioners acted on the suspected cases, and a statistical significant relation was observed between the government and private dental practitioners for not taking any action on child abuse and neglect (p = 0.0010). Conclusions: Data from this study may provide a useful contribution to the current limited knowledge about the familiarity of dental practitioners with child maltreatment and their skills to recognize and manage CAN cases in their practice. The majority of dental practitioners knew about the child protection law in India, but they were reluctant to report such cases due to the fear of anger from the parents and family of the child. Continuing education programs/courses were the most preferred method for increasing the knowledge regarding CAN. They should report the CAN cases to local legislators and health authorities so to prevent child abuse and neglect from ever occurring.

Influence of alveolar mixing and multiple breaths of aerosol intake on particle deposition in the human lungs.

Predictive dosimetry models play an important role in assessing health effect of inhaled particulate matter and in optimizing delivery of inhaled pharmaceutical aerosols. In this study, the commonly used 1D Multiple-Path Particle Dosimetry model (MPPD) was improved by including a mechanistically based model component for alveolar mixing of particles and by extending the model capabilities to account for multiple breaths of aerosol intake. These modifications increased the retained fraction of particles and consequently particle deposition predictions in the deep lung during tidal breathing. Comparison with an existing dataset (J. Aerosol Sci., 99:27-39, 2016) obtained under two breathing conditions referred to as slow and fast breathing showed significant differences in 1 µm particle deposition between predictions based on subject-specific breathing patterns and lung volume (slow: 30 ± 1%, fast: 21 ± 1%, (average ± standard deviation), N = 7) and measurements (slow: 43 ± 9%, fast: 30 ± 5%) when the prior version of MPPD (single breath and no mixing, J. Aerosol Sci., 151:105647, 2021) was used. Adding a mixing model and multiple breaths moved the predictions (slow: 34 ± 2%, fast:25 ± 2%) closer to the range of deposition measurements. For 2.9 µm particles, predictions from both the original (slow: 70 ± 2%, fast: 57 ± 2%) and the revised MPPD model (slow: 71 ± 2%, fast: 59 ± 3%) compared well with experiments (slow: 67 ± 8%, fast: 58 ± 10%). This was expected as suspended fraction of 2.9 µm particles was small and thus the addition of alveolar mixing and multi breath capability only slightly increased the retained fraction for particles of this size and greater. The revised 1D model improves dose predictions in the deep lung and support human risk assessment from exposure to airborne particles.

Genome-wide assessment of genetic diversity, linkage disequilibrium and haplotype block structure in Tharparkar cattle breed of India.

Knowledge about genetic diversity is very essential for the management and sustainable utilization of livestock genetic resources. In this study, we presented a comprehensive genome-wide analysis of genetic diversity, ROH, inbreeding, linkage disequilibrium, effective population size and haplotype block structure in Tharparkar cattle of India. A total of 24 Tharparkar animals used in this study were genotyped with Illumina BovineSNP50 array. After quality control, 22,825 biallelic SNPs were retained, which were in HWE, MAF > 0.05 and genotyping rate >90%. The overall mean observed (HO) and expected heterozygosity (HE) were 0.339 ± 0.156 and 0.325 ± 0.129, respectively. The average minor allele frequency was 0.234 with a standard deviation of ± 0.131. We identified a total of 1832 ROH segments and the highest autosomal coverage of 13.87% was observed on chromosome 23. The genomic inbreeding coefficients estimates by FROH, FHOM, FGRM and FUNI were 0.0589, 0.0215, 0.0532 and 0.0160 respectively. The overall mean linkage disequilibrium (LD) for a total of 133,532 pairwise SNPs measured by D' and r2 was 0.6452 and 0.1339, respectively. In addition, we observed a gradual decline in effective population size over the past generations.

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds.

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and FST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and FST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.

Genome wide association study of MAGIC population reveals a novel QTL for salinity and sodicity tolerance in rice.

The present study was conducted to identify the novel QTLs controlling salinity and sodicity tolerance using indica MAGIC rice population. Phenotyping was carried out in salinity (EC ~ 10 dS/m) and sodicity (pH ~ 9.8) at the seedling stage. Among 391 lines, 43 and 98 lines were found tolerant and moderately tolerant to salinity. For sodicity condition, 2 and 45 lines were showed tolerance and moderately tolerance at seedling stage. MAGIC population was genotyped with the help of genotyping by sequencing (GBS) and filtered 27041SNPs were used for genome wide marker trait association studies. With respect to salinity tolerance, 25 SNPs were distributed on chromosomes 1, 5, 11 and 12, whereas 18 SNPs were mapped on chromosomes 6, 4 and 11 with LOD value of > 3.25 to sodicity tolerance in rice. The candidate gene analysis detected twelve causal genes including SKC1 gene at Saltol region for salinity and six associated genes for sodic stress tolerance. The significant haplotypes responsible for core histone protein coding gene (LOC_Os12g25120) and three uncharacterized protein coding genes (LOC_Os01g20710, LOC_Os01g20870 and LOC_Os12g22020) were identified under saline stress. Likewise, five significant haplotypes coding for ribose 5-phosphate isomerise (LOC_Os04g24140), aspartyl protease (LOC_Os06g15760), aluminum-activated malate transporter (LOC_Os06g15779), OsFBX421-Fbox domain containing protein (LOC_Os11g32940) and one uncharacterized protein (LOC_Os11g32930) were detected for sodic stress tolerance. The identified novel SNPs could be the potential candidates for functional characterization. These candidate genes aid to further understanding of genetic mechanism on salinity and sodicity stress tolerance in rice. The tolerant line could be used in future breeding programme to enhance the salinity and sodicity tolerance in rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-022-01174-8.

Diversity of SARS-CoV-2 isolates driven by pressure and health index.

One of the main concerns about the fast spreading coronavirus disease 2019 (Covid-19) pandemic is how to intervene. We analysed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) isolates data using the multifractal approach and found a rich in viral genome diversity, which could be one of the root causes of the fast Covid-19 pandemic and is strongly affected by pressure and health index of the hosts inhabited regions. The calculated mutation rate (mr) is observed to be maximum at a particular pressure, beyond which mr maintains diversity. Hurst exponent and fractal dimension are found to be optimal at a critical pressure (Pm), whereas, for P > Pm and P < Pm, we found rich genome diversity relating to complicated genome organisation and virulence of the virus. The values of these complexity measurement parameters are found to be increased linearly with health index values.

Efficient bi-directional coupling of 3D Computational Fluid-Particle Dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry.

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. As a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFPD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. These methods can be used as the foundation for multi-scale modeling of the full respiratory system.

Comparative analysis of five different methods to design a breed-specific SNP panel for cattle.

Single nucleotide polymorphisms (SNPs) have now replaced microsatellite markers in several species for various genetic investigations like parentage assignment, genetic breed composition, assessment for individuality and, most popularly, as a useful tool in genomic selection. However, such a resource, which can offer to assist breed identification in a cost-effective manner is still not explored in cattle breeding programs. In our study, we have tried to describe methods for reducing the number of SNPs to develop a breed-specific panel. We have used SNP data from Dryad open public access repository. Starting from a global dataset of 178 animals belonging to 10 different breeds, we selected five panels each comprising of similar number of SNPs using different methods i.e., Delta, Pairwise Wright's FST, informativeness for assignment, frequent item feature selection (FIFS) and minor allele frequency-linkage disequilibrium (MAF-LD) based method. MAF-LD based method has been recently developed by us for construction of breed-specific SNP panels. The STRUCTURE software analysis of MAF-LD based method showed appropriate clustering in comparison to other panels. Later, the panel of 591 breed-specific SNPs was called to their respective breeds using Venny 2.1.0 and UGent web tools software. Breed-specific SNPs were later annotated by using various Bioinformatics softwares.

Kinless hubs are potential target genes in prostate cancer network.

Complex disease networks can be studied successfully using network theoretical approach which helps in finding key disease genes and associated disease modules. We studied prostate cancer (PCa) protein-protein interaction (PPI) network constructed from patients' gene expression datasets and found that the network exhibits hierarchical scale free topology which lacks centrality lethality rule. Knockout experiments of the sets of leading hubs from the network leads to transition from hierarchical (HN) to scale free (SF) topology affecting network integration and organization. This transition, HN â†’ SF, due to removal of significant number of the highest degree hubs, leads to relatively decrease in information processing efficiency, cost effectiveness of signal propagation, compactness, clustering of nodes and energy distributions. A systematic transition from a diassortative PCa PPI network to assortative networks after the removal of top 50 hubs then again reverting to disassortativity nature on further removal of the hubs was also observed indicating the dominance of the largest hubs in PCa network intergration. Further, functional classification of the hubs done by using within module degrees and participation coefficients for PCa network, and leading hubs knockout experiments indicated that kinless hubs serve as the basis of establishing links among constituting modules and heterogeneous nodes to maintain network stabilization. We, then, checked the essentiality of the hubs in the knockout experiment by performing Fisher's exact test on the hubs, and showed that removal of kinless hubs corresponded to maximum lethality in the network. However, excess removal of these hubs essentially may cause network breakdown.

Revelation of genomic breed composition in a crossbred cattle of India with the help of Bovine50K BeadChip.

The aim of the present study was to assess the population structure and admixture levels in the Vrindavani composite population in India by using Bovine50KSNP BeadChip data. Genotypic data were generated for randomly selected animals (n = 72) of Vrindavani population and the data for parental breeds i.e., Hariana (n = 10), Holstein-Friesian (n = 63), Jersey (n = 28) and Brown Swiss (n = 22) were retrieved from a public repository. The indices of population structure were calculated using PLINK software and R-program. The merged dataset was analysed for assessing admixture levels and population stratification using three different approaches i.e., principal component analysis (PCA), multi-dimensional scaling (MDS) approach and the model-based approach in STRUCTURE software. The average minor allele frequency (MAF) value for Vrindavani population was estimated to be 0.235. Vrindavani population was found to possess an average ancestry of 39.5, 22.9, 26.9, and 10.7% inheritance levels from Holstein Friesian, Jersey, Hariana and Brown Swiss cattle breeds, respectively.

Ancestry informative markers derived from discriminant analysis of principal components provide important insights into the composition of crossbred cattle.

The cost of SNP genotyping to screen different breeds and to estimate the exact proportion of ancestry level is quite high, which can be compensated through deriving a small panel of ancestry informative markers (AIMs). Hence, we carried out the present study to provide an insight into ancestry level inferred from a panel of informative markers in the crossbred Vrindavani population developed at ICAR-IVRI, India. We have performed a new method i.e., discriminant analysis of principal components (DAPC) for the first time on the dataset of Vrindavani cattle. To confirm our method, we had performed DAPC on two other well-known crossbred cattle, i.e., Frieswal and Beefmaster. Three sets of panels (500, 1000 and 2000 markers) were tested for clustering of individuals. Among all the panels, we found the panel (1000 markers) with DAPC based contribution method was of the smallest size and comparatively of the highest accuracy.

Fugitive dust emission control study for a developed smart dry fog system.

Air pollution due to dust emission is continuously increasing day by day in mining and allied industrial areas. Mining operations contribute a substantial amount of dust emission at the crushing, screening, and bulk material handling in loading areas. The ambient suspended dust particles create a severe nuisance to workers and local dwellers. For effective controlling of positive dust emission, an innovative automated dry fog dust suppression system (DFDSS) has been developed using hybrid nozzles, sensors, actuators, controllers, screw compressors, air receivers, pumps, motors, and water arrangement with filtration facility. The DFDSS was installed in a crushing and screening plant of an iron ore mine in India. Performance study indicted fugitive dust emission concentration values ranged from 354 to 7040 µg m-3, which was reduced to 91-300 µg m-3 after installation of DFDSS. The reduced values were within the permissible limit of 1200 µg m-3 at a distance of 25 ± 2 m in the predominant downwind direction. The installed DFDSS added a meager addition of moisture content of 0.032% in the handling iron ore material, which was below the acceptable limit of 0.1%. The DFDSS precisely regulated fugitive dust emission from various mining activities without affecting the minerals processing performance. Thus, the DFDSS can be implemented effectively in different mining and allied industries where there is a dust emission problem.

Breast cancer patient advocacy: A qualitative study of the challenges and opportunities for civil society organizations in low-income and middle-income countries.

BACKGROUND: Breast cancer advocacy movements, driven by advocate-led civil society organizations (CSOs), have proven to be a powerful force for the advancement of cancer control in high-income countries (HICs). However, although patient advocacy movements are growing in low-income and middle-income countries (LMICs) in response to an increasing cancer burden, the experiences and needs of advocate-led breast cancer CSOs in LMICs is understudied. METHODS: The authors conducted a qualitative study using in-depth interviews and focus group discussions with 98 participants representing 23 LMICs in Eastern Europe, Central Asia, East and Southern Africa, and Latin America. RESULTS: Despite geographic, cultural, and socioeconomic differences, the common themes that emerged from the data across the 3 regions are strikingly similar: trust, knowledge gaps, stigma, sharing experiences, and sustainability. The authors identified common facilitators (training/education, relationship building/networking, third-party facilitators, and communication) and barriers (mistrust, stigma, organizational fragility, difficulty translating HIC strategies) to establishing trust, collaboration, and advancing cancer advocacy efforts. To the authors' knowledge, the current study is the first to describe the role that coalitions and regional networks play in advancing breast cancer advocacy in LMICs across multiple regions. CONCLUSIONS: The findings of the current study corroborate the importance of investing in 3-way partnerships between CSOs, political leaders, and health experts. When provided with information that is evidence-based and resource appropriate, as well as opportunities to network, advocates are better equipped to achieve their goals. The authors propose that support for CSOs focuses on building trust through increasing opportunities for engagement, disseminating best practices and evidence-based information, and fostering the creation of platforms for partnerships and networks.

Molecular crosstalk: Notch can manipulate Hes1 and miR-9 behavior.

We propose a Hes1-Notch-miR-9 regulatory network and studied the regulating mechanism of miR-9 and Hes1 dynamics driven by Notch. Change in Notch concentration, which serves as a stress signal, can trigger the dynamics of Hes1 and miR-9 at five different states, namely, sTable (2), sustain (1) and mixed (2) states those may correspond to different cellular states. Further, this Notch stress signal introduce time reversal oscillation, which behaves as backward wave, after a certain threshold value of the stress signal and defends the system from moving to apoptosis. We also observe heterogeneous patterns of Hes1, miR-9 and other molecular species in various two dimensional parameter spaces and found that the variability in the patterns is triggered by Hill coefficient and Hes1 stress signal. The phase or bifurcation diagram in time period of oscillation (TN) driven by Notch signal provides all five states, predicts minimum threshold value TNc beyond which tendency to build up backward wave starts and TNc serves as bifurcation point of the system.

Stochastic approach to study control strategies of Covid-19 pandemic in India.

India is one of the severely affected countries by the Covid-19 pandemic at present. Within the stochastic framework of the SEQIR model, we studied publicly available data of the Covid-19 patients in India and analysed possible impacts of quarantine and social distancing as controlling strategies for the pandemic. Our stochastic simulation results clearly show that proper quarantine and social distancing should be maintained right from the start of the pandemic and continued until its end for effective control. This calls for a more disciplined social lifestyle in the future. However, only social distancing and quarantine of the exposed population are found not sufficient enough to end the pandemic in India. Therefore, implementation of other stringent policies like complete lockdown as well as increased testing of susceptible populations is necessary. The demographic stochasticity, which is quite visible in the system dynamics, has a critical role in regulating and controlling the pandemic.

Non-Gaussian subdiffusion of single-molecule tracers in a hydrated polymer network.

Single molecule tracking experiments inside a hydrated polymer network have shown that the tracer motion is subdiffusive due to the viscoelastic environment inside the gel-like network. This property can be related to the negative autocorrelation of the instantaneous displacements at short times. Although the displacements of the individual tracers exhibit Gaussian statistics, the displacement distribution of all the trajectories combined from different spatial locations of the polymer network exhibits a non-Gaussian distribution. Here, we analyze many individual tracer trajectories to show that the central portion of the non-Gaussian distribution can be well approximated by an exponential distribution that spreads sublinearly with time. We explain all these features seen in the experiment by a generalized Langevin model for an overdamped particle with algebraically decaying correlations. We show that the degree of non-Gaussianity can change with the extent of heterogeneity, which is controlled in our model by the experimentally observed distributions of the motion parameters.