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Innovation roadmaps are important, because they encourage the actors in an innovation ecosystem to creatively imagine multiple possible science future(s), while anticipating the prospects and challenges on the innovation trajectory. In this overarching context, this expert review highlights the present unmet need for therapeutic innovations for pituitary neuroendocrine tumors (PitNETs), also known as pituitary adenomas. Although there are many drugs used in practice to treat PitNETs, many of these drugs can have negative side effects and show highly variable outcomes in terms of overall recovery. Building innovation roadmaps for PitNETs' treatments can allow incorporation of systems biology approaches to bring about insights at multiple levels of cell biology, from genes to proteins to metabolites. Using the systems biology techniques, it will then be possible to offer potential therapeutic strategies for the convergence of preventive approaches and patient-centered disease treatment. Here, we first provide a comprehensive overview of the molecular subtypes of PitNETs and therapeutics for these tumors from the past to the present. We then discuss examples of clinical trials and drug repositioning studies and how multi-omics studies can help in discovery and rational development of new therapeutics for PitNETs. Finally, this expert review offers new public health and personalized medicine approaches on cases that are refractory to conventional treatment or recur despite currently used surgical and/or drug therapy.

The term \"alopecia\" is used for abnormal hair loss and it is a chronic dermatological condition observed in both genders and all races. Androgenetic alopecia (AGA) or male pattern baldness is the most common type of alopecia; however, it may be observed in females. Alopecia areata (AA) is the second most common non-scarring alopecia or hair loss around the world. Beyond the fact that alopecia is a disease itself, sometimes it might be one of the major side effects of many drugs including chemotherapeutics. Since healthy hair has been a symbol of well-being, youth, and vitality for centuries, the treatment of alopecia has essential importance to increasing life quality of the individuals that have faced hair loss. Regarding the progressively generated high-throughput data at various omics levels, systems biology has gained importance to better understand biologic processes by utilizing high-throughput data from multiple sources to develop models of biologic processes In this review, we overviewed AGA and AA via systems biology with the aid of omics technologies point of view to highlight not only the molecular mechanisms of the hair loss phenomenon but also potential preventive and therapeutic avenues. We discussed the findings in light of the multi-omics data integration that converges the future of uncovering personalized therapeutic options targeting hair loss.

Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neurons that mainly affects the motor cortex, brainstem, and spinal cord. Under disease conditions, microglia could possess two distinct profiles, M1 (toxic) and M2 (protective), with the M2 profile observed at disease onset. SOD1 (superoxide dismutase 1) gene mutations account for up to 20% of familial ALS cases. Comparative gene expression differences in M2-protective (early) stage SOD1(G93A) microglia and age-matched SOD1(G93A) motor neurons are poorly understood. We evaluated the differential gene expression profiles in SOD1(G93A) microglia and SOD1(G93A) motor neurons utilizing publicly available transcriptomics data and bioinformatics analyses, constructed biomolecular networks around them, and identified gene clusters as potential drug targets. Following a drug repositioning strategy, 5 small compounds (belinostat, auranofin, BRD-K78930611, AZD-8055, and COT-10b) were repositioned as potential ALS therapeutic candidates that mimic the protective state of microglia and reverse the toxic state of motor neurons. We anticipate that this study will provide new insights into the ALS pathophysiology linking the M2 state of microglia and drug repositioning.

Kaufman oculocerebrofacial syndrome is a rare autosomal recessive disorder which represents a phenotype mainly involving craniofacial and neurodevelopmental manifestations due to UBE3B gene mutations. The vast majority of the affected individuals exhibit microcephaly, eye abnormalities, and typical facial gestalt including blepharophimosis, ptosis, telecanthus, upslanting palpebral fissures, dysplastic ears, and micrognathia. We encountered 2 siblings in whom severe psychomotor delay, distinctive facial features, hearing loss, and respiratory distress were observed. Some clinical manifestations of the patients, including epibulbar dermoid, microtia, and multiple preauricular tags, were reminiscent of the oculoauriculovertebral spectrum. However, 2 affected siblings exhibited a similar clinical picture consisting of microcephaly, severe developmental and cognitive disabilities, failure to thrive, and dysmorphic features, which were not fully consistent with oculoauriculovertebral spectrum. Also, hypoplastic nails, considered as a core manifestation of Coffin-Siris syndrome, were present in our patients. Therefore, whole-exome sequencing was carried out in order to identify the underlying genetic alterations, contributing to the complex phenotype shared by the 2 siblings. A homozygous pathogenic mutation was found in both affected siblings in the UBE3B gene which caused Kaufman oculocerebrofacial syndrome. Kaufman oculocerebrofacial syndrome should be considered among the autosomal recessive causes of blepharophimosis-mental retardation syndromes, particularly in populations with a high rate of consanguineous marriages, even if there are dysmorphic facial features that are not typically associated with the phenotype.

Algebraic study of graphs is a relatively recent subject which arose in two main streams: One is named as the spectral graph theory and the second one deals with graphs over several algebraic structures. Topological graph indices are widely-used tools in especially molecular graph theory and mathematical chemistry due to their time and money saving applications. The Wiener index is one of these indices which is equal to the sum of distances between all pairs of vertices in a connected graph. The graph over the nite dot product of monogenic semigroups has recently been dened and in this paper, some results on the Wiener index of the dot product graph over monogenic semigroups are given.

Advances in omics technologies have made it possible to unravel biomarkers from different biological levels. Intensive studies have been carried out to uncover the dysregulations in psoriasis and to identify molecular signatures associated with the pathogenesis of psoriasis. In this review, we presented an overview of the current status of the omics-driven biomarker research and emphasized the transcriptomic, epigenomic, proteomic, metabolomic, and glycomic signatures proposed as psoriasis biomarkers. Furthermore, insights on the limitations and future directions of the current biomarker discovery strategies were discussed, which will continue to comprehend broader visions of psoriasis research, diagnosis, and therapy especially in the context of personalized medicine.

Pituitary neuroendocrine tumors (PitNETs) are the second most common type of intracranial neoplasia. Since their manifestation usually causes hormone hypersecretion, effective management of PitNETs is indisputably necessary. Most of the non-functioning PitNETs pose a real challenge in diagnosis as they grow without giving any signs. Despite the good response of prolactinomas to dopamine agonist therapy, some of these tumors persist or recur; also, about 20% are resistant and 10% behave aggressively. The silent corticotropinomas may not cause symptoms until the tumor mass causes a complication. In somatotropinomas, the possibility of recurrence after transsphenoidal resection is more common in pediatric patients than in adult patients. Therefore, detection of tumors at early stages or identification of recurrence and remission after transsphenoidal surgery would allow wiser management of the disease. Extensive studies have been performed to uncover potential signatures that can be used for preventive diagnosis and/or prognosis of PitNETs as well as for targeted therapy. These molecular signatures at multiple biological levels hold promise for the convergence of preventive approaches and patient-centered disease management and offer potential therapeutic strategies. In this review, we provide an overview of the omics-based biomarker research and highlight the multi-omics signatures that have been proposed as pitNET biomarkers. In addition, understanding the multi-omics data integration of current biomarker discovery strategies was discussed in terms of preventive, predictive, and personalized medicine. The topics discussed in this review will help to develop broader visions for pitNET research, diagnosis, and therapy, particularly in the context of personalized medicine. WOS:000666821500001 Q1

Introduction: BRAF(V600E) activating mutation is the most frequent genetic abnormality in the pathogenesis of papillary thyroid carcinoma. We aimed to evaluate the association between BRAF(V600E )mutation and well-established prognostic clinicopathological characteristics as well as iodine exposure. Material and methods: From 2000 to 2012, the data of PTC patients admitted to Dr. Lutfi Kirdar Kartal Education and Research Hospital in Turkey were reviewed retrospectively. Clinicopathological parameters were collected. BRAF(V600E) mutation was analysed by DNA sequencing method in tumour specimens. We hypothesised that BRAF(V600E) mutation prevalence is positively correlated with prolonged iodine exposure and expected to be higher in the second half of the recruitment period due to the increment in time spent from the iodisation process of the table salt in our country. Thus, iodine exposure was categorised as short-term (2000-2006) and long-term (2006-2012). Results: A total of 197 patients were accrued. The study population predominantly consisted of conventional variant. A statistically significant relationship was observed between BRAF(V600E) mutation presence and age (p = 0.03), conventional variant PTC (p = 0.00002), T4 stage (p= 0.002), vascular invasion (p= 0.036), thyroid capsule invasion (p < 0.00001), extrathyroidal tissue invasion (p < 0.00001), and lymph node metastasis (p < 0.00001). When categorised as long-term and short-term, iodine exposure was not statistically significantly related with BRAF(V600E) mutation; however, there were far more PTC cases in the long-term group (86.3% vs. 13.7%). Conclusion: We revealed that BRAF(V600E) mutation is associated with adverse clinicopathological parameters. There appeared to be no relation between long-term iodine exposure and BRAF(V600E). Research Fund of the Tekirdag Namik Kemal University [NKUBAP.01, YL.16.021] This work was supported by a grant of the Research Fund of the Tekirdag Namik Kemal University (Project number: NKUBAP.01.YL.16.021).

Non-functioning pituitary adenomas (NFPAs) are tumors with clinically challenging features since they have insidious progression. A complex network of gene interactions is thought to have roles in tumor formation and progression. Therefore, revealing the genetic network behind NFPA tumorigenesis is not only essential to attain further knowledge of tumor biology, but also plays a fundamental role in the development of efficacious treatment strategies. Differential co-expression network analysis is an outstanding approach for elucidation of groups of genes which show distinct co-expression patterns among phenotypes. In this study, we carried out a differential co-expression network analysis of NFPA-associated transcriptome dataset (n=40) considering invasive (n=22) and non-invasive (n=18) phenotypes. Furthermore, we identified differentially co-expressed and co-regulated mRNA modules, which might be considered as potential systems biomarkers for NFPA prognosis and invasiveness. As a result, we have identified a novel 13-gene module, including CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1, MYO18A, PDCD2, SGIP1, SWSAP1 and four unknown genes (A_24_P127621, A_24_P255786, A_24_P683553, and A_24_P916979), which was able to categorize the patients into two groups as invasive and non-invasive NFPA with distinct prognosis. The prognostic core module genes were associated with progression and prognosis of brain and glandular based cancers as well. Furthermore, these module genes were also expressed in blood, salivary gland, and spinal cord tissues. These results may provide the evidence on featured gene module which might play a prominent role in NFPA prognosis and sub-typing as effective biomarkers and therapeutic targets in the future.

Background: Despite prolonged survival, the mortality rate of acromegalic patients is still higher. Cardiovascular disorders continue to be the most common cause of death. The exact pathophysiologic mechanisms of acromegalic cardiomyopathy (AC) remain to be established. In this study, we investigated the role of FSTL1 levels and FSTL1 gene polymorphisms on AC and assessed the functional and structural properties of cardiac muscle by cardiac MRI. Finally, we examined the relationship between FSTL1 levels, FSTL1 gene polymorphism and cardiac MRI findings. Materials and Methods: Forty-six acromegalic patients (28F/18M, age: 50.3±12.1 yrs) with a median disease duration of eight years and 81 age-sex matched healthy controls (48F/33M, age: 48.4±7.2 yrs) were included in the study. The rs1259293 region of the FSTL1 gene was subjected to polymorphism analysis. SNPs were identified (TT, TC and CC). A 1.5 Tesla scanner was used to obtain cardiac images. Results: The median serum IGF- 1 level and IGF-1 index were 232.5 ng/mL (50-1278) and 0.69 (0.17-3.1), respectively. Acromegalic patients had significantly lower levels of FSTL1 (median, IQR; A: 0.88, 0.44-2.13 ng/mL, C: 1.54, 0.85-3.16 ng/mL, p=0.04). FSTL1 levels were not different among polymorphism groups (TT, TC and CC). Left ventricular (LV) mass was increased in 18 patients (41%). In 20 acromegalic patients (45.4%), regional late gadolinium enhancement (LGE) was determined. Serum IGF-1 index was positively correlated with LV end-diastolic volume index, end-systolic volume index, stroke volume index, cardiac index and cardiac mass index; r: 0.36, 0.34, 0.32, 0.31 and 0.42, p: 0.02, 0.03, 0.03, 0.04 and 0.004 respectively. The IGF-1 index was defined as an independent risk factor for LV hypertrophy (95 % CI OR: 0.89-18.84); on the other hand, the CC polymorphism was shown to be an independent protective factor (95 % CI OR: 0.06-0.87). Discussion: Our study is the first study that assesses the role of serum FSTL1 levels and FSTL1 polymorphisms in AC. We found low FSTL1 levels in patients with acromegaly. FSTL-1 prevents hypertrophy in cardiomyocytes. In a previous report, homozygous deletion of FSTL1 in mice was shown to result in enlargement of heart. The relatively low abundance of FSTL1 in acromegalic patients could be an underlying mechanism for AC. Almost half of the acromegalic patients had increased LV mass and LGE. Contrary to the previous report, we show that LV hypertrophy and regional fibrosis are common findings in acromegaly. The IGF-1 index was found to be associated with hyperdynamic cardiac functions. Furthermore, we demonstrate that high IGF-1 index is an independent risk factor for increased LV mass. Finally, we revealed that the CC polymorphism is a protective factor against the LV mass increase. Conclusions: FSTL1 can have roles in the pathogenesis of AC. Specific polymorphism at the FSTL1 gene may prevent the growth of the LV.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, more commonly COVID-19 has emerged as a world health pandemic. There are couples of treatment methods for COVID-19, however, well-established drugs and vaccines are urgently needed to treat the COVID-19. The new drug discovery is a tremendous challenge; repurposing of existing drugs could shorten the time and expense compared with de novo drug development. In this study, we aimed to decode molecular signatures and pathways of the host cells in response to SARS-CoV-2 and the rapid identification of repurposable drugs using bioinformatics and network biology strategies. We have analyzed available transcriptomic RNA-seq COVID-19 data to identify differentially expressed genes (DEGs). We detected 177 DEGs specific for COVID-19 where 122 were upregulated and 55 were downregulated compared to control (FDR, Highlights • Molecular transcriptomes alterations of the lung epithelial cells in response to SARS-CoV-2 were detected. • Significant molecular pathways altered in COVID-19 revealed. • Hub proteins were detected as novel drug targets for COVID-19. • Molecular regulatory signatures were identified. • Repurposable drugs were identified for COVID-19.

Metabolic systems engineering is being used to redirect microbial metabolism for the overproduction of chemicals of interest with the aim of transforming microbial hosts into cellular factories. In this study, a genome-based metabolic systems engineering approach was designed and performed to improve biopolymer biosynthesis capability of a moderately halophilic bacterium Halomonas smyrnensis AAD6T producing levan, which is a fructose homopolymer with many potential uses in various industries and medicine. For this purpose, the genome-scale metabolic model for AAD6T was used to characterize the metabolic resource allocation, specifically to design metabolic engineering strategies for engineered bacteria with enhanced levan production capability. Simulations were performed in silico to determine optimal gene knockout strategies to develop new strains with enhanced levan production capability. The majority of the gene knockout strategies emphasized the vital role of the fructose uptake mechanism, and pointed out the fructose-specific phosphotransferase system (PTSfru) as the most promising target for further metabolic engineering studies. Therefore, the PTSfru of AAD6T was restructured with insertional mutagenesis and triparental mating techniques to construct a novel, engineered H. smyrnensis strain, BMA14. Fermentation experiments were carried out to demonstrate the high efficiency of the mutant strain BMA14 in terms of final levan concentration, sucrose consumption rate, and sucrose conversion efficiency, when compared to the AAD6T. The genome-based metabolic systems engineering approach presented in this study might be considered an efficient framework to redirect microbial metabolism for the overproduction of chemicals of interest, and the novel strain BMA14 might be considered a potential microbial cell factory for further studies aimed to design levan production processes with lower production costs.

Ecballium elaterium, common name squirting cucumber juice is used for the symptomatic treatment of rhinosinusitis in folk medicine. There are reports of allergic reactions of this plant in the literature. It has strong anti-inflammatory effect and people in the eastern Mediterranean region widely use this fruit juice for rhinitis and sinusitis. We presented a case of uvular edema caused by this plant.

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health.