Publications and Posters

D.melanogaster is one of the model organism used for biological researches. It has 60% homology with human genome and about 75% of human disease genes have been identified in D.melanogaster. In the last decade, the use of D.melanogaster as a model organism to investigate cancer has exponentially increased. Previous studies conducted in the NASA gene has shown alteration of gene expression of D.melanogaster in the outer space. Different signaling pathways involved in cancer such can be analyzed and studied in D.melanogaster for translational research. In this study we aim to explore the expression profiles of genes involved in cell cycle and cell death of D.melanogaster from space flight and control.

Meningiomas are the most common adult brain tumors and are approximately 30% of all intracranial neoplasms. Multiple studies show that skull base meningiomas (SBM) are more likely to have benign biology whereas tumors with more aggressive behavior can constitute close to 30% of convexity/parafalcine tumor. Significant difference in immune-cell gene expression was seen between SBM and convexity meningiomas by Zador Z et al. which explained the biology of the aggressive nature of Non-skull base meningiomas (NSBM). The gene expression profiles between different anatomical subtypes i.e Skull base meningiomas versus non-skull base meningiomas, remain largely unexplored.

The research investigates the newly discovered lunar meteorite, Gadamis-003 discovered in the Ghadamis Basin of Libya in 2021. This certified meteorite listed cataloged in the Meteoritical Bulletin Database is scarcely explored. Therefore, a pilot study was conducted to examine the extraterrestrial sample using equipment and resources available within Pakistan – making a modest contribution to the hottest emerging area of astrobiology. A detailed micrographic report was generated through microscopy and SEM/EDX analysis. Comprehensive petrography and elemental analysis revealed major minerals like anorthite (plagioclase), pyroxene, and olivine, alongside accessory minerals such as magnetite and ilmenites. A comparative study using thin sections of the Apollo mission samples highlighted Gadamis-003 mineralogical similarity and its possible locality with the Apollo 16 mission samples i.e., in proximity with lunar highlands, although its geochemical province is yet to be confirmed. The study also documented detailed sample-handling procedures that included trackable sub-sectioning used for the reconstruction of the fallen parent rock and tracing the geochemistry of the original site of the sample on the Moon. The powdered fragments of the lunar meteorite underwent biosignature investigation using gas chromatography-mass spectrometry, which revealed traces of organic compounds falling in the category of classified as aldehydes and ketones. However, a thorough detailed organic chemistry evaluation is necessary for the characterization of the detected compounds and verification of their isotopic delta values. This work is fundamentally intended to serve as a groundwork for future studies aiming to spur the curiosity of local researchers

The genomic structure and composition of every individual is unique and genetic changes of diseased individuals vary from one another. Genomic literacy can be defined as the ability to achieve, process, understand and apply genomic knowledge for health-related decision-making. Medical practitioners can easily diagnose, analyze, and treat some major life-threatening diseases like cancer, based on genome composition with the introduction of new technologies in genomic sequencing of an individual patient. One of the key challenges is how to translate information of genomic benefits into clinical care. The lack of genomic knowledge, abilities, and confidence among medical practitioners are some of the principal obstacles to the delivery of genomic services into clinical practice.

The growing integration of AI in healthcare presents challenges for medical professionals lacking AI knowledge, limiting their engagement with AI tools in Pakistan (Abernethy et al., 2022; Umer et al., 2024). Without addressing this gap, they risk missing out on AI-driven benefits like improved diagnostics and personalized care (Silcox et al., 2024). Objectives: The AI4Doctors workshop was proposed to: 1) Provide a structured introduction to AI for participants with limited exposure. 2) Build intuition around machine learning models and medical AI datasets. 3) Offer hands-on experience in developing and evaluating simple AI models.

Recent advancements in computer vision (CV) have revolutionized various fields, including medicine, by providing sophisticated tools for tasks such as image classification and segmentation. In particular, digital pathology has emerged as a critical technology for tumor diagnosis and prognosis. However, the application of advanced CV models in underdeveloped regions remains limited due to the prohibitive costs of high-resolution imaging equipment. This study addresses this challenge by exploring the use of Low-Cost Low-Resolution (LCLR) histopathology images for detecting cancer of four different sites: Oral, Gastrointestinal, Colorectal and Breast cancers. We evaluated the performance of four deep learning models, including AlexNet, EfficientNet, Vision Transformer and TransUnet. Among these, TransUnet; a hybrid model combining U-Net’s segmentation capabilities with Transformers’ ability to capture long-range dependencies, demonstrated the best performance across Tabbasum et al OSCC dataset with an accuracy of 96.8% and loss of 3%. The individual accuracy results for Gastrointestinal, Colorectal, Oral and Breast cancers were 95.9%, 96.1%, 98.7% and 97.2%, respectively. The model’s integration of coarse-to-fine attention refinement significantly improved segmentation accuracy, particularly in noisy, low-resolution images, where other models struggled. To assess the models’ effectiveness, we utilized metrics such as accuracy, loss and confusion matrices. TransUnet consistently outperformed the other models, achieving high classification accuracy and low loss values across all cancer datasets. It demonstrated robustness in distinguishing between cancerous and non-cancerous tissues, even in morphologically similar cancer sites, such as Gastrointestinal and Colorectal cancers.

Converting pathological images into mineable datasets based on AI algorithms and linking these extracted and quantified pathological features to clinically related indicators is called Pathomics (1). The project aimed to create a comprehensive dataset of cancer histopathology images, covering various cancer types and subtypes, to train AI models for accurate cancer detection using standard digitization techniques (2). It focused on standardizing slide collection and labeling to ensure high-quality digital images that meet clinical and research standards. Additionally, it sought to establish HistoVault as a reliable repository, advancing AI-driven diagnostics and cancer research (3).

Mobile phones have become an indispensable part of daily life[1], frequently used across various environments, often without proper sanitation. Studies have shown that mobile devices harbour a significant number of bacteria, potentially serving pathogens[2]

“Acrylic” is an umbrella term for any fabric comprising at least 85% polyacrylonitrile (PAN). Although PAN is preferable as an alternative to wool or cashmere and is extensively used in fast fashion, it is rapidly becoming a notorious pollutant among synthetic textiles. For this reason, it is important to find a cost-effective and eco-friendly alternative.

Fenugreek (Trigonella foenum-graecum), also known as “methi,” is commonly used in Pakistani cuisine and traditional medicine for conditions like diabetes and high cholesterol. It is also noted for its potential anticancer properties [1]. In this study, we analyze that fenugreek seed extract (FE) demonstrates cytotoxic effects in vitro against cancer cell lines, suggesting its potential as an anticancer agent.

As health awareness surges, the ability to instantly track nutritional intake through just a snapshot becomes a game changer. Traditional and cultural foods often slip through the cracks of existing dietary apps, but our deep learning model tackles this by effortlessly classifying desi foods from images, putting nutritional insights at your fingertips.

There has been considerable speculation in recent years on the nature of the current carriers in the electrical conductivity of proteins [1]. Evans and Gergely concluded that dry proteins should be electronic semiconductors with an interband gap of about 3.0 eV [2]. A more recent study by Cantiello et al. (2024) suggested strong rectification in purified actin paracrystals with a nonlinear electrical conductance [3].

Food waste is a global issue that is becoming bigger by the day, with 2.1 billion tonnes of municipal waste in 2023 estimated to grow to 3.8 billion tonnes by 2050. Of this waste, 1.3 billion tonnes contributes to food waste, with 36 million tonnes produced by Pakistan [1]. The direct dumping of organic wastes is harmful to the environment because it can result in methane emissions and also cause economic losses to industries [2]. This waste is known to be abundant in natural pigments [3,4], which could be extracted for economic benefit. Mango peels were selected due to their local abundance, vibrant hue, and inedibility.

Numerous members of the human microbiome including P. gingivalis, E. coli, H. pylori and F. nucleatum have been implicated in the onset of cancer. F. nucleatum, a gram-negative opportunistic bacterium, is implicated in establishing disease-favourable environment in colorectal cancer (CRC), breast cancer, esophageal cancer, oral squamous cell carcinoma (OSCC). F. nucleatum is also reported to cause chronic inflammation in head and neck squamous cell carcinoma (HNSCC) one of the most prevalent cancer groups in Pakistan. This study aims to highlight key players common in both CRC and HNSCC that interact with F. nucleatum indicating similar mechanism of that may favor the onset of cancer.

Regenerative medicine allowing the culture of viable tissues and organs relies on 3D bio-printing of a biomimicking hydrogel to support the cultured cells, and the creation of pores and vasculature within the gel construct [1]. However, high costs and the complexity of the technology used have prevented its adoption in Pakistan. Comparatively, plastic 3D printing is more easily available, highlighting it as a potential alternative.

Oral squamous cell carcinoma (OSCC) is a type of malignancy with high mortality, leading to poor prognosis worldwide. However, the molecular mechanisms underlying OSCC carcinogenesis have not been fully understood. LncRNAs, which possess minimal or no coding potential, are defined as capped RNA transcripts exceeding 200 nucleotides in length. New sequencing technologies reveal that many aberrantly expressed LncRNAs are linked to various cancers, highlighting their role in cancer development and progression (1)(2).

Pancreatic ductal adenocarcinoma(PDAC) is one of the commonly associated melignancy with Diabetes Mellitus and is referred to as Pancreatic ductal adenocarcinoma-associated diabetes(PDAC-DM). PDAC-DM has a 5-year average survival rate of less than 6%. Objectives: 1. To understand the progression of PDAC from DM 2. To identify differentially expressed genes that are unique toPDAC-DM 3. To explore pathways that are altered in the condition

Extrachromosomal circular DNA (eccDNA) exists outside the linear chromosomes and, while present in normal cells, takes on a more critical role in cancer [1]. It can harbor oncogenes and regulatory elements that drive tumorigenesis. In the case of colon cancer, which is the third most common cancer worldwide [2], eccDNA may be especially impactful. It is thought to play a key role in driving disease progression and enhancing oncogene expression.

Small Cell Lung Carcinoma (SCLC) is a highly aggressive neuroendocrine malignancy, representing about 15% of lung cancers, and is marked by rapid progression, early metastasis, and high mortality (1). Significant heterogeneity exists in SCLC, characterized by the existence of distinct molecular subtypes that are determined by the varying expression of transcription factors such as ASCL1, NEUROD1, and POU2F3, each linked to unique biological behaviors and therapeutic responses (2). Additionally, recent studies have found a connection between neuronal activity and the development of both primary and metastatic SCLC (3).

Ampullary cancers are rare, accounting for only 0.2% of gastrointestinal cancers and approximately 7% of all periampullary cancers. (1) with an incidence of approximately 4 to 10 cases per million population (2). Adenocarcinoma of the ampulla of Vater is the second most common periampullary malignancy. Early diagnosis is important because lymph node status influences survival (3). Currently, only CEA and CA19-9 , non specific biomarkers are used to diagnose Ampullary Carcinoma.

MB has been classified into subgroups i.e. WNT, SHH, Group 3 and Group 4. The molecularly distinct groups also exhibit unique clinical, pathological, and prognostic features; for instance, WNT has the most favorable prognosis, while Group 3 has the worst outcomes among MBs. Long non-coding RNAs (lncRNAs) are non-coding yet vital in cellular function, development, and disease.

Neuropsychiatric Disorders are multifactorial disease that is not completely understood of the brain. That’s why it is very essential to look and generate knowledge about it , and thus we dove into understanding its genetic element genetic. According to WHO Neuro-behavioral disorders affect 10th of the human population and 15% global disease burden. Objectives: To study and see the common and unique genes of each disorder and see how these genes are involves in biological mechanisms leading up to each disorder.

Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, representing about 90% of all cases. HCC arises from a number of etiological factors and although vaccinations and antiviral treatments have significantly decreased the occurrence of HCC, its incidence continues to rise due to other causes, including alcohol abuse and non-alcoholic steatohepatitis (1). Objectives: To determine the differences in the mechanism of carcinogenesis involved in the different etiologies of HCC to have a better understanding of the pathogenesis of Hepatocellular carcinoma.

Cholangiocarcinoma (CCA) is a rare and fatally aggressive cancer of the biliary tract. Due to its heterogeneous nature, silent presentation, and wavering response to chemotherapy, CCA-associated mortality accounts for ~2% of cancer-afflicted deaths yearly[1]. Cholelithiasis/gallstones (GS) are hardened deposits, usually cholesterol, that form in the gallbladder (GB) and cause severe symptoms mainly inflammation and abdominal pain. They have been termed a possible risk factor for CCA however no definitive link or evidence exists on the molecular level [2,3].

6HAP, an adenine analogue, disrupts DNA synthesis and kills cancer cells. As yet, it’s known to be naturally produced by two Staphylococcus epidermidis strains (M034 and M038). 6HAP has anti-tumour effects on various cancer cell lines (1). 6HAP sensitivity in cancer cells is due to down regulated mitochondrial amidoxime-reducing component enzymes (mARC1 and mARC2), leading to apoptosis. The downregulation of these enzyme genes and the biosynthesis of 6HAP in Staphylococcus epidermidis, however, remain largely unknown.

Various communities of microorganisms such as F. nucleatum P. gingivalis, and E. coli play a significant role in the onset of different cancers. F. nucleatum, is a gram-negative, opportunistic bacteria known to create favorable conditions for colorectal cancer (CRC) and possesses a potential risk in breast cancer, esophageal cancer, and Head and Neck Squamous Cell Carcinoma [1,2]. This study aims to identify factors in OSCC and CRC interacting with F. nucleatum, indicating overlapping mechanisms between them, in the onset of cancer.

Candida albicans: a yeast species commonly found in the oral cavity, has raised intriguing questions about oral cancer. Literature has shown a higher prevalence of yeast and greater diversity in oral cancer patients, with C. albicans playing a pivotal role (1). It has the potential to convert alcohol into the carcinogen acetaldehyde through the CaADH1 mRNA gene (2). We studied the impact of co-cultured C.albicans with oral squamous cell carcinoma cell line in the presence of cisplatin and acetaldehyde.

Rhizosphere is the region of soil where roots of a plant grow. Plant Growth Promoting Rhizobacteria are present in the rhizosphere where they form a symbiotic association with plants – surviving using nutrients produced by the plants, and in-turn performing functions (e.g. Nitrogen-fixation) that help gather raw materials for the plants to use and grow [1]. Mars is the 4th planet in our solar system, out of which its properties are closest to that of planet earth. However, it still has harsh environmental conditions, most notably the soil analogue. Mars ‘regolith’ has acidic pH and is mainly composed of metal oxides, making it hard for seeds to germinate and bacteria to survive [2]. Precision Medicine Lab has composed a Martian Soil Simulant by the name of ‘KP-Mars-1’ that is 65% similar to that of Mars regolith. The aim of this study was to investigate the effect, on germination of chile pepper seeds [3], and survival of PGP Rhizobacteria in KP-Mars-1 (Simulated Mars conditions).

World Health Organisation (WHO) report stated that “Tobacco is the single most preventable cause of death in the world today. By 2030, the death toll will exceed eight million a year” (WHO, 2008). The carcinogens in tobacco can directly alter the genetic code, or their constituent metabolites can affect various pathways and genes (Anand, 2008). Our aim is to identify tobacco-derived metabolites, that are consumed during smoking and by the use of smokeless tobacco, that are playing a major role in the initiation and progression of various cancer types to provide a novel insight into tobacco mediated cancer.

The dominant majority of Afghan patients travel across the border to avail the of healthcare at tertiary care hospitals in Pakistan. According to International Organization for Migration, a total of 75,734 Afghan refugees crossed the Torkham border from January to February 2022. Among them, 16,149 Afghans had valid visas, 596 Afghan patients with medical visas that required medical treatment in Pakistan along with 539 attendants who accompanied the patients. The aim of this study is to map and measure all touchpoints that an Afghan patient goes through in his or her treatment journey in a healthcare facility (before, during, and after treatment). This will help us identify and capture insights into their experience and document the shortcomings of the healthcare system and the challenges they pose to patients in the process of attaining medical care.

Oral Squamous Cell Carcinoma (OSCC) accounts for 90% of cancer cases in the world. Despite advances in preventive and treatment efforts, late detection of OSCC remains one of the leading causes of morbidity and mortality. Recent research has investigated the possibility of using non-invasive approaches, such as “liquid biopsy,” to detect diagnostic and prognostic biomarkers in the bodily fluids of oral cancer patients [1]. Biomarkers are molecular signatures and indicators of normal biological, pathological, and pharmacological responses to therapy, and as such, they may provide useful information for disease detection, diagnosis, and prognosis. Because saliva comes into close contact with oral cancer lesions, it becomes a more specific and possibly sensitive screening method [2]. A number of salivary biomarkers (DNA, RNA, protein, metabolite, or microbiota) have been reported. The aim of this research is to investigate the possibility of salivary biomarkers for the early detection of oral cancer and to assess their diagnostic accuracy and reliability for oral cancer detection. The goal is to develop a non-invasive and dependable diagnostic spit test for early diagnosis of oral cancer, capable of detecting oral cancer at an early stage. This would allow for more rapid intervention and better patient outcomes.

Non-Communicable disease (NCD), also referred to as a chronic disease is a major health concern due to its magnitude and high social cost [1]. The incorporation of personalized data has been challenging, therefore, data from wearable/digital health devices along with other health parameters provide an opportunity to make NCD risk assessment more comprehensive, dynamic, and accurate over a lifetime, which may help in the prevention of NCD [2]. With an increased risk of non-communicable diseases, especially CVDs in developing countries, and a trend of non-adherence to medication that increases in older adults, we set out to monitor our patients’ wellness and enable the early detection of disease onset.

Precision medicine and genomics are transforming traditional healthcare approaches at a rapid pace [1]. In spite of major technological progress being made in genomics, a genomic divide is emerging between the developed and developing countries [2]. This is partly because of the limited genomic literacy amongst healthcare professionals and a scarcity of available genomics workforce that potentially deters from prescription and widespread adoption of genomic testing. We aim to help reduce this genomic divide by proposing a genomic test report design for clinicians that incorporates user-centered design principles.

Initial Mars colonizers priority list will encompass growing plants on the hostile planet. Growth of plants on Mars have a significant importance ranging from being an essential food source to oxygen production and raw material and for manufacturing different products. Rhizosphere dwelling bacteria perform key functions in the growth and development of plants. In this study, the growth and survival of rhizosphere soil bacteria was examined for a period of 7 days in Khyber Pakhtunkhwa Mountain Red Soil (KP-Mars-1) & Mars Global Simulant–1 (MGS-1), both representing Mars soil. KP-Mars-1 is our identified Mars soil simulant, characterized and refined by us. It exhibits similar elemental composition as Mars soil and can potentially be used as a Mars soil simulant. The simulated Mars environment for bacterial growth and survival analysis consisted of diurnal temperatures (positive 20°C to 30°C and negative 80°C), low and high soil moisture content, anaerobic atmosphere (carbon dioxide dominant) and UV-C ionization radiation (200nm – 280nm). These conditions are being tested alone, in combination and all together for effects on bacterial growth and survival. Bacterial cells were inoculated in Mars soil simulants in various volumes (1%, 20%, 40%, 60% & 100%) in 5 grams of Mars soil simulant. The growth and survival of rhizosphere bacteria will be analyzed for 1, 3 & 7 days. Rhizosphere soil bacterial were able to survive -80°C temperature conditions in our preliminary work. Our study may have implications for Martian astronauts in deciding which bacteria should be considered to grow on Mars for effective growth of plants.

Colorectal cancer (CRC) is the third most prevalent and second most fatal cancer worldwide [1]. Despite treatment advancements, the five-year survival rate remains low [2]. FOLFOX, the first-line treatment for advanced CRC, is a common chemotherapy regimen used in clinics [3]. However, treatment often fails due to acquired resistance, observed in 90% of metastatic patients [2]. Therefore, a more efficient and cost-effective drug repurposing approach is needed.

Ovarian cancer is a significant contributor to cancer-related mortality among women worldwide. However, because ovarian cancer is often undiagnosed until late in the disease’s progression, it is also the fifth leading cancer-related cause of death among women in the US¹. Metastasis remains a major challenge, as it often leads to more aggressive disease and poorer prognosis. Understanding the molecular changes that occur during the transition from primary to metastatic tumors is crucial for developing targeted therapies and improving patient outcomes.

Breast cancer comprises four subtypes: Luminal A, Luminal B, HER2-enriched, and Basal, each showing a distinct metastatic precedence to various organs, including the bones, lung, liver, and brain. Interactions between chemokines (cell-derived factors that cause directional migration of cells [1]) and their receptors may contribute to the organ-specific spread of the subtypes.

In 2020, there were 2.3 million women diagnosed with breast cancer and 685,000 deaths globally. This disparity reflects an unmet need, as breast cancer is often difficult to diagnose at early stages. Early diagnosis is essential for minimizing the mortality rate of breast cancer patients, which can be achieved through liquid biopsy. Liquid biopsy can be defined as a non-invasive method to detect tumor cells that have entered the bloodstream or formed metastatic deposits in blood, urine, feces, saliva, and other biological fluids. Liquid biopsy components include circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and circulating microRNAs.

Head and Neck Squamous Cell Carcinoma (HNSCC) originates from squamous cells lining the mucosal surfaces of the head and neck region, affecting areas such as the oral cavity, oropharynx, nasopharynx, nasal cavity, paranasal sinuses, larynx, and hypopharynx [1]. Drug repurposing offers a cost-effective approach to identify new treatments by reutilizing existing drugs with established safety profiles [2]. Exploring protein domain interactions can uncover new insights into disease mechanisms and potential therapeutic targets [3].

With rapid advances in technology, humans are exploring the possibility of staying in Space for longer durations. Space has hazards which are namely Radiation, Microgravity, Distance from Earth, Isolation, Confinement, and Hostile Conditions which all cause alterations in the human body [1]

Lymphoma is a general term for cancer that starts in the lymph system (Mugnaini EN et al., 2016). There are two categories of lymphoma (Radiol Am et al., 2008): Hodgkin’s lymphoma and Non-Hodgkin’s lymphoma. The American Joint Committee on Cancer (AJCC) recognizes two major categories of Hodgkin lymphoma (Matasar et al., 2008): 1) classic Hodgkin lymphoma (95%) and 2) nodular lymphocyte-predominant Hodgkin lymphoma (5%). Although its general prognosis is favorable, 10%–30% of patients with classic Hodgkin lymphoma (cHL) will ultimately develop relapsed or refractory disease (Ansell SM et al., 2015). A stem cell transplant complemented with high-dose chemotherapy is the main treatment used for relapsed cHL (Potre O et al., 2021).

Breast cancer is the most common cancer among women in the world, with incidence rising every year. In 2020, according to GLOBOCAN, Pakistan had 25,928 breast cancer cases, estimated using data from India. In order to obtain comprehensive insights into the epidemiology, risk factors, and disease burden of breast cancer in Pakistan [1, 2], we embarked on this systematic review. We aim to bridge the data gap and provide clinicians and policymakers with a reliable and comprehensive snapshot of breast cancer in Pakistan.

Head and Neck Squamous Cell Carcinoma (HNSCC) is a heterogeneous malignancy of the head and neck region that emerges from the larynx, pharynx, and oral cavity. It is Pakistan’s second most prevalent cancer and has a 5-year survival rate of around 50%. Currently, the incidence of HNSCC in the Pakistani population is rising due to the widespread use of risk factors such as tobacco smoking, naswar, paan, and gutka. To improve patient outcomes in HNSCC, genomic information is required to better understand cancer initiation and progression, ultimately helping to identify better diagnostic, prognostic, and therapeutic markers.

According to World Health Organization, Pakistan has a high burden of tobacco use and it comes amongst the top 15 countries which have the highest number of tobacco related ailment [1]. Because of the huge tobacco consumption secondhand smoke (SHS) is also widespread. Findings from Global Adult Tobacco Survey suggest that nonsmokers at homes (48.3%) and at workplaces (65.3%) are most vulnerable to secondhand smoke exposure [2]. The aim of this study was to have a better understanding of SHS exposure at homes and at workplace.

Microgravity promotes changes at the cellular level as well as the genomic level. These changes contribute to the risks of abnormal physiological and neurological responses faced by astronauts during prolonged missions, for example, at the International Space Station (ISS). This study aims to investigate the potential effects of microgravity on gene expression levels of genes that are key to the central nervous system (CNS) especially the differentiation of stem cells into neurons. We use transcriptomic data from the Gene Expression Omnibus (GEO) as well as the NASA Gene Lab. We have identified 60 key genes that are important across the four stages of neuronal development. Beside these we identified 55 genes that were observed to be influenced when exposed to real microgravity at International Space Station (ISS). Following the detailed analysis of differentially expressed genes (DEGs) across these datasets, we intend to conduct a systems-level study using interaction network as well in order to study the functional interdependencies of the DEGs. We hope to understand how the CNS changes in response to, and adapts with, microgravity conditions.

D. radiodurans is a polyextremophile bacterium that is extremely tolerant to desiccation, harsh temperatures, ionizing radiation and variable fluences of UV-radiation [1]. Furthermore D. radiodurans consists of key features such as oxidative stress resistance, general stress resistance, production of a novel gene product, high transformability etc. which are necessary for a optimal synthetic biology chassis [2]. Genes associated with these features are also well known. [2] described D. radiodurans features, like its high transformability, resistance against stress conditions, ability to form a biofilm and robust cell envelopes and how these characteristics enable D. radiodurans to be an optimal chassis for synthetic biology

Cancer is a leading cause of death worldwide, accounting for 10 million deaths in 2020 [1]. According to GLOBOCAN’s 2020 report for Pakistan, 178,888 new cancer cases have been registered in Pakistan, while the number of prevalent cases is 329,547, for a total of 117,149 deaths due to cancer [2]. Research studies have shown that 20% of cancer patients die during treatment because of the side effects of chemotherapeutic drugs and not because of the cancer itself [3]. This study aims using cell culture assays and in vitro drug screening methodologies to test effective chemotherapeutic drugs in order to improve cancer treatment for the local population of Pakistan. It also aims to address the current lack of low-cost and personalized treatment for cancer patients by testing chemotherapeutic drugs against patient-derived cancer cell lines in a matter of weeks instead of doctors testing them directly on patients, which takes months, along with drug side effects on the patient’s health.

Oral squamous cell carcinoma (OSCC) is a subset of head and neck squamous cell carcinoma (HNSCC), the 7th most common cancer worldwide, and accounts for more than 90% of oral malignancies. Early detection of OSCC is essential for effective treatment and reducing the mortality rate. However, the gold standard method of microscopy-based histopathological investigation is often challenging, time-consuming, and relies on human expertise. Automated analysis of oral biopsy images can aid the histopathologists in performing a rapid and arguably more accurate diagnosis of OSCC. We utilized a transfer learning approach by adapting three pre-trained deep learning (DL) models to OSCC detection.

The status of a surgical margin after resection is an important prognostic factor for relapse in OSCC patients [1]. The relapse may arise from the presence of tumor cells in surgical margins that rely on histopathologist evaluation or from the presence of genetically altered marginal cells [2]. Emerging molecular techniques are being utilized to improve surgical margin assessments in HNSCC, which rely on genetic alterations [3]. In this case, two distant regions of the TP53 gene were analyzed to evaluate the surgical margins of resected OSCC specimens to detect the presence of cancerous cells.

This white paper aims to begin addressing the need for new or modified policies by proposing a genomic data policy framework and corresponding set of ethical tensions for policy-makers, business leaders, researchers, patients and others to consider before taking actions that affect or involve the collection and use of human genomic and genetic data for research and clinical use. Generally, genomics refers to all genes and their interrelationships and genetics focuses on a single or set of genes. The distinction is important and nuanced in several fields; however, for the purposes of this paper, the authors will refer to genomics when our thinking applies to data about all or some genes. This paper is written from a “future of healthcare” perspective, and with a focus on LMICs and emerging economies.

Synthetic biology has significant potential to decarbonize the necessities of human life. It could be applied to what we eat (e.g., alternative and cultured proteins), the clothes we wear (e.g., textile fibres originating from engineered microbes), how we build our homes and workplaces (e.g., mycelium-based construction materials with enhanced carbon capture technologies), and even the way we travel (e.g., mobility powered by sustainable biobased alternatives). Understood in the context of achieving net zero emissions, the successful application of synthetic biology is arguably less a question of science – though challenges still remain – and more a question of navigating a landscape of high initial costs, lengthy development timelines, and a lack of well-established pathways to achieve commercial-scale production and widespread adoption.

Oral Squamous Cell Carcinoma (OSCC) accounts for more than 90% of reported head and neck cancers which is the sixth leading cancer worldwide. Oropharyngeal squamous cell carcinoma (OPSCC) cases, a closely located but a different sub-type of head and neck cancer, are also rising worldwide specifically among young individuals with risk factors including viral infection, smoking and alcohol. HPV infection, specifically the subtype HPV16 is a significant risk factor in the initiation and progression of OPSCC, but has not been reported to play a role in OSCC. This study sets out to decipher mechanistic differences at the molecular level by comparing the viral-human protein-protein interaction (PPI) networks both in oropharyngeal squamous cell carcinoma (OPSCC) and oral squamous cell carcinoma (OSCC). We found that the unbiased HPV16-Human network consisted of 479 nodes, including 7 HPV16 proteins and 472 human proteins. Enrichment analysis revealed significant involvement of the identified human proteins in ubiquitination, protein degradation, and cancer-related pathways. A subset of 37 genes showed differential expression in HPV-positive OPSCC and OSCC, with TP53 over-expressed and ENDOD1 under-expressed in both cancers. Six genes (NUTM1, MYC, SCN9A, COL27A1, ITGB4, and GNB2) exhibited distinct changes in HPV-positive OPSCC compared to the other groups, where NUTM1 was the most over-expressed in OPSCC HPV+. The identified genes and pathways could serve as potential targets for precision medicine and therapeutic interventions in HPV-associated cancers. Further investigations are required to validate their clinical implication in in vitro and in vivo models.

Nature’s most abundant carbohydrate, cellulose, has incredible structural properties that can be leveraged as scaffolds for tissue engineering. With plants being an inexpensive and easily accessible source, it is more feasible to experiment with these techniques and progress in the field of regenerative tissue engineering. In this study, we set out to optimize a low-cost method to obtain cellulose scaffolds that could potentially mimic a blood vessels after recellularization with endothelial cells. We chose a readily available plant specimen, i.e. cauliflower stalk, which offers anatomical similarity to blood vessels, vascular architecture and interconnected porosity. We went on to capture the cellulose scaffold digitally and created a 3-D model using a computer-aided design (CAD) software which was then used for 3-D printing the scaffold in two different sizes. We believe the decellularize-image-print cycle allows for skipping decellularization processes of new scaffolds every time a scaffold is required and therefore cutting cost and time needed, enables instant dissemination between individual researchers and communities and allows scalable printing at any size and level of detail. We hope this will catalyze even faster innovation in the space of tissue engineering and regenerative medicine.

Head and neck cancer is the sixth leading cause of cancer across the globe and is more prevalent in the developing countries of South Asia, including Pakistan DNA methylation is an important contributor to the pathophysiology of the various stages of cancer, making it important to understand the role of specific methylation events in each stage of a particular cancer Previous studies have classified early and late stages of liver carcinoma using two-class machine learning models based on differentially methylated CpG sites No studies have been conducted to classify pathological stages (I-IV) of HNSCC using four-class machine learning models with mutated gene-associated CpG sites in HNSCC, partly due to high computational expense and small sample size.

Oral squamous cell carcinoma (OSCC) is a subset of head and neck squamous cell carcinoma (HNSCC), the 7th most common cancer worldwide, and accounts for more than 90% of oral malignancies. Early detection of OSCC is essential for effective treatment and reducing the mortality rate. However, the gold standard method of microscopy-based histopathological investigation is often challenging, time-consuming and relies on human expertise. Automated analysis of oral biopsy images can aid the histopathologists in performing a rapid and arguably more accurate diagnosis of OSCC. In this study, we present deep learning (DL) based automated classification of 290 normal and 934 cancerous oral histopathological images published by Tabassum et al (Data in Brief, 2020). We utilized transfer learning approach by adapting three pre-trained DL models to OSCC detection. VGG16, InceptionV3, and Resnet50 were fine-tuned individually and then used in concatenation as feature extractors. The concatenated model outperformed the individual models and achieved 96.66% accuracy (95.16% precision, 98.33% recall, and 95.00% specificity) compared to 89.16% (VGG16), 94.16% (InceptionV3) and 90.83% (ResNet50). These results demonstrate that the concatenated model can effectively replace the use of a single DL architecture.

Head and neck cancer is the sixth leading cause of cancer across the globe and is significantly more prevalent in South Asian countries, including Pakistan. Prediction of pathological stages of cancer can play a pivotal role in early diagnosis and personalized medicine. This project ventures into the prediction of different stages of head and neck squamous cell carcinoma (HNSCC) using prioritized DNA methylation patterns. DNA methylation profiles for each HNSCC stage (stage-I-IV) were used to extensively analyze 485,577 methylation CpG sites and prioritize them on the basis of the highest predictive power using a wrapper-based feature selection method, along with different classification models. We identified 68 high-power methylation sites which predicted the pathological stage of HNSCC samples with 90.62 % accuracy using a Random Forest classifier. We set out to construct a protein-protein interaction network for the proteins encoded by the 67 genes associated with these sites to study its network topology and also undertook enrichment analysis of nodes in their immediate neighborhood for GO and KEGG Pathway annotations which revealed their role in cancer-related pathways, cell differentiation, signal transduction, metabolic and biosynthetic processes. With information on the predictive power of each of the 67 genes in each HNSCC stage, we unveil a dynamic stage-course network for HNSCC. We also intend to further study these genes in light of functional datasets from CRISPR, RNAi, drug screens for their putative role in HNSCC initiation and progression.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease which arises due to various genetic, epigenetic and environmental factors. DNA methylation is an epigenetic factor that is found to have a role in the development and progression of HNSCC through genetic and epigenetic silencing. Analysis of the methylation data can facilitate us to explore variations in several gene sites and can narrow down our search for curing HNSCC. The aim of this study was to explore and analyze the DNA Methylation data of HNSCC and make intelligent machine learning (ML) models that can predict the expression levels of a particular gene site based on various features. Difference between the gene expression levels of normal and tumor samples obtained from TCGA was calculated and then the genes were classified into hypo-methylated, hyper-methylated and non-methylated, respectively. Moreover, network analysis and functional enrichment analysis was performed to identify the protein-protein interaction (PPI) and involvement in the biological process followed by training logistic regression, support vector machine (SVM) and k-nearest neighbors (KNN) models for prediction. Logistic regression was found to have the highest accuracy of 65% among all the ML models. Furthermore, MYC, POLR2A, ALB, MTOR, H2AFX, SMARCA4, PAX6, GATA3 and MDM2 were identified as the hub genes in the HNSCC network. Whereas, hyper-methylated, hypo-methylated and non-methylated genes were found to be enriched in neuroactive ligand-receptor interaction, neurogenesis, ion transport channels, cell cycle and plasma membrane. In future, more data and features are required for validation and improving the accuracy of the ML models.

Despite rapid technological progress being made in genomics, a growing disparity is emerging between healthcare in developed and developing countries. This genomic divide can be partly explained by the scarcity of available genomics workforce and in some parts by limited genomic literacy of healthcare professionals that reportedly deters them from proposing genomic testing in a clinical setting. This study aims to study this gap in a local context and learn how we can reduce this genomic divide by developing a user-centred design of genomic test reports in Pakistan. The user being the clinician in this study. We selected two commonly used genomic reports which varied in language, content, and layout. Report A was a one-page genomic report from the Laboratory for Molecular Medicine at Partner’s Healthcare. Report B was a report with multiple pages of information from FoundationOneCDx. We employed a qualitative descriptive study design, including a survey of trainees, non-specialists, and specialists. The parameters recorded were: subjective comprehension, overall visual impression, level of difficulty of the language, and communication efficacy depending on the reports’ graphical representation, along with actionability and degree of reliability. A total of 49 medical professionals across 11 institutes in Pakistan participated in the survey. Based on the answers and suggestions provided by the participants, we extracted 11 recommendations and broadly grouped them into four categories, i.e. language, content, layout and reliability. Our findings highlights key areas that need to be taken into consideration when designing impactful genomic reports for clinicians in Pakistan. This incudes accessible and appropriate language, adequate content and a non-overwhelming and friendly layout as well as an emphasis on establishing reliability and actionability of what the clinician finds in the report. This can be instrumental in helping us improve the adoption of genomic testing in clinics around Pakistan, and potentially in other similar contexts.