Related Databases Research Articles

QUALITY CONTROL OF EVA SHOE PRODUCTION

The material hanging on moulds after EVA shoe removal, is to be removed before next batch to be prepared otherwise the left hanging material will disrupt the fineness and smoothness of the prepared shoe of the incoming new batch. The human error is evident in inspection & detection. So, automation in shoeindustry for defect inspection and analysis is must, resulting inquality in production and also time saving methodology in massproduction. The purpose of this work is to design the system which monitors whether the moulds are cleaned properly after to obtained good quality shoes as end result. In this work the identification of clean and unclean moulds is focused on the methods using MATLAB. First, we extract certain features from the input mould image, later using different method like thresholding, segmentation, k-means clustering and thus obtain related databases. From the proposed method able to identify the cleaned and uncleaned moulds with accuracy successfully using image processing. Keywords: EVA; Matlab; thresholding; segmentation; k-means clustering

Exploring the components and mechanisms of Shen-qi-wang-mo granule in the treatment of retinal vein occlusion by UPLC-Triple TOF MS/MS and network pharmacology

This study aimed to explore the substance basis and mechanisms of Shen-qi-wang-mo Granule (SQWMG), a traditional Chinese medicine prescription that had been clinically utilized to treat retinal vein occlusion (RVO) for 38 years. Components in SQWMG were analyzed by UPLC-Triple-TOF/MS and a total of 63 components were identified with ganoderic acids (GA) being the largest proportion. Potential targets of active components were retrieved from SwissTargetPrediction. RVO-related targets were acquired from related disease databases. Core targets of SQWMG against RVO were acquired by overlapping the above targets. The 66 components (including 5 isomers) and 169 targets were obtained and concluded into a component-target network. Together with biological enrichment analysis of targets, it revealed the crucial role of the “PI3K-Akt signaling pathway”, “MAPK signaling pathway” and their downstream factor iNOS and TNF-α. The 20 key targets of SQWMG in treating RVO were acquired from the network and pathway analysis. The effects of SQWMG on targets and pathways were validated by molecular docking based on AutoDock Vina and qPCR experiment. The molecular docking showed great affinity for these components and targets, especially on ganoderic acids (GA) and alisols (AS), which were both triterpenoids and qPCR exhibited remarkably reduced inflammatory factor gene expression through regulation of these two pathways. Finally, the key components were also identified from rat serum after treatment of SQWMG.

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening-based approaches.

Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large number of patients, efficient treatments for viral cancers are needed. De novo drug discovery is time consuming and expensive process with high failure rate in clinical stages. To address this problem and provide treatments to patients suffering from viral cancers faster, drug repurposing emerges as an effective alternative which aims to find the other indications of the Food and Drug Administration approved drugs. Applied to viral cancers, drug repurposing studies following the niche have tried to find if already existing drugs could be used to treat viral cancers. Multiple drug repurposing approaches till date have been introduced with successful results in viral cancers and many drugs have been successfully repurposed various viral cancers. Here in this study, a critical review of viral cancer related databases, tools, and different machine learning, deep learning and virtual screening-based drug repurposing studies focusing on viral cancers is provided. Additionally, the mechanism of viral cancers is presented along with drug repurposing case study specific to each viral cancer. Finally, the limitations and challenges of various approaches along with possible solutions are provided.

Chinese herbal compound Huangqin Qingrechubi capsule reduces lipid metabolism disorder and inflammatory response in gouty arthritis via the LncRNA H19/APN/PI3K/AKT cascade

Context Gouty arthritis (GA) is a characteristically inflammatory disease often associated with lipid metabolism disorder. Huangqin Qingrechubi capsule (HQC) has been used for the treatment of GA. Objective To explore the mechanism of HQC in the treatment of GA. Materials and methods A total of 30 GA patients (GA group) and 30 healthy subjects [normal control (NC) group] were recruited. The GA group was treated with HQC (3.6 g/d) for 10 days. Lipid metabolism and inflammation indexes were detected. Five herbal names of HQC, or ‘gouty arthritis’, ‘hyperlipidemia’ and ‘inflammation’ were used as key words to search related databases for network pharmacological analysis. Subsequently, GA-fibroblast-like synoviocytes (FLSs) were stimulated with GA-peripheral blood mononuclear cells (PBMCs) (3:1) and treated with HQC drug-containing serum (20%). RT-qPCR, Western blot, and ELISA were conducted to further explore the mechanism of HQC in improving GA. Results In clinical observation, HQC decreased the expression of lncRNA H19 and IL-1β, and increased the expression of adiponectin (APN) and IL-4 in the GA group (about half). Through network pharmacology, the PI3K/AKT signaling pathway was identified. Cell experiments showed that HQC treatment reduced the viability of GA-FLSs (49.61%), up-regulated the expression of IL-4 (155.18%), IL-10 (165.13%), and APN (31.24%), and down-regulated the expression of lncRNA H19 (33.70%), IL-1β (64.70%), TNF-α (78.32%), p-PI3K (48.80%), and p-AKT (53.48%). Discussion and conclusions HQC improved lipid metabolism disorder and inflammatory response of GA by regulating the lncRNA H19/APN/PI3K/AKT. Maintaining the stability of lipid metabolism may be an effective way to alleviate GA.

Contrastive learning-based general Deepfake detection with multi-scale RGB frequency clues

Deepfake is a type of image and video face manipulation methods which could cause security and society threats. Although some related databases and detection models have been proposed for detecting face forgery media, achieving a generalizable detector for both known and unknown manipulations remains challenging. In this study, a novel deepfake detection model with high generalizability is proposed to tackle this issue. We employ supervised contrastive learning to enhance the generalizability to unknown manipulations and datasets. In addition, we design a cross-modality data augmentation method by combining SRM and RGB features to extract detection clues comprehensively. Furthermore, we propose a multi-scale feature enhancement module to enhance textural and semantic information. Extensive experiments have demonstrated that our method improves model generalization in both intra- and cross- dataset scenarios.

CAFrgDB: a database for cancer-associated fibroblasts related genes and their functions in cancer

As one of the most essential components of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) interact extensively with cancer cells and other stromal cells to remodel TME and participate in the pathogenesis of cancer, which earmarked themselves as new promising targets for cancer therapy. Numerous studies have highlighted the heterogeneity and versatility of CAFs in most cancer types. Thus, the identification and appropriate use of CAF-related genes (CAFGenes) in the context of specific cancer types will provide critical insights into disease mechanisms and CAF-related therapeutic targets. In this study, we collected and curated 5421 CAFGenes identified from small- or large-scale experiments, encompassing 4982 responsors that directly or indirectly participate in cancer malignant behaviors managed by CAFs, 1069 secretions that are secreted by CAFs and 281 regulators that contribute in modulating CAFs in human and mouse, which covered 24 cancer types. For these human CAFGenes, we performed gene expression and prognostic marker-based analyses across 24 cancer types using TCGA data. Furthermore, we provided annotations for CAF-associated proteins by integrating the knowledge of protein-protein interaction(s), drug-target relations and basic annotations, from 9 public databases. CAFrgDB (CAF related Gene DataBase) is free for academic research at http://caf.zbiolab.cn and we anticipate CAFrgDB can be a useful resource for further study of CAFs.

Quantification and Diversity Analyses of Major Glucosinolates in Conserved Chinese Cabbage (Brassica rapa L. ssp. pekinensis) Germplasms

The genebank at the National Agrobiodiversity Center (RDA-Genebank, Jeonju, Republic of Korea), conserves approximately 8000 germplasms of Brassica spp., of which Chinese cabbage (Brassica rapa L. ssp. pekinensis) is one of the major crops actively used as food in Northeast Asia, including Korea, as the main ingredient for kimchi. Glucosinolates are a major class of compounds in Chinese cabbage that are responsible for their distinctive flavor, and RDA-Genebank is constantly building a related database (DB) to select suitable germplasms required by consumers and provide resources for breeding programs. In this study, ten glucosinolates were analyzed in sixty Chinese cabbage germplasms. Six aliphatic glucosinolates were the major components, accounting for 85.00% to 91.98% of total glucosinolates in each germplasm. Among them, gluconapin (333.26 to 23,501.58 μmol∙kg-1 DW) was highly represented, followed by glucobrassicanapin (545.60 to 10,344.70 μmol∙kg-1 DW) and progoitrin (155.28 to 8536.51 μmol∙kg-1 DW). In addition, we selected germplasms with a high content of each studied glucosinolate. To analyze the diversity and distribution of glucosinolates among the studied germplasms, Pearson's correlation was performed, and the related results were interpreted through their biosynthetic pathways. The k-means clustering indicated four optimal clusters, which were confirmed through principal component analysis. Orthogonal projection to latent structure discriminant analysis (OPLS-DA) was also performed on the status (landrace and cultivar) and origin (Korea, China, Taiwan, and Japan) passport data of the germplasms, followed by the calculation of variable importance in the projection (VIP) values. These results are part of a continuous series of studies to analyze the glucosinolates of Brassica germplasms that are being conserved at RDA-Genebank. We aim to provide related results through a public platform accessible to everyone and thereby improve the distribution of Brassica germplasms.

Systematic Review: Benefits of Juices for Delayed Onset Muscle Soreness after Exercise

<p>目的：探討蔬果飲食的使用是否能改善運動後所造成的延遲性肌肉痠痛(delayed onset muscle soreness, DOMS)。</p> <p>方法：首先我們檢索了2021年12月以前文獻資料庫。並於2022年1月時第二次搜尋相關新發表文獻。檢索關鍵字如下：延遲性肌肉痠痛及蔬菜(vegetable)或果汁(juice)。最後所選用的文獻均發表於2017年至2019年。納入的文獻為(1)隨機對照研究；(2)天然蔬果汁的介入；(3)包括延遲性肌肉疼痛的結果。資料收集是根據：作者、國家、臨床試驗設計、實驗組和對照組的數量、年齡、性別、蔬果汁的介入方式與種類及介入時間長度、還有兩組在蔬果汁介入前後的結果比較。探討方式為身體的(1)功能性；(2)生物標記；(3)量表。</p> <p>結果：我們從收錄的72篇文獻中篩選出5篇符合條件的研究。介入的果汁有9種，其中酸櫻桃及石榴能改善最大等長肌力(maximal isometric voluntary contraction)，但無法有效減少肘關節活動範圍(range of motion, ROM)的下降，有一半的研究顯示對於DOMS的改善有益處，但另外一半則是發現沒有治療效果。而視覺模擬量表(visual analogue scale)的結果如同DOMS。酸櫻桃有降低肌酸激酶(creatine kinase, CK)及C反應蛋白(C-reactive protein, CRP)的趨勢，但在統計上無明顯差異。對於離心運動後的發炎指標「腫瘤壞死因子α(TNF-α, tumor necrosis factor-α)」、「干擾素-γ(INF-γ, interferon-gamma)」、「白細胞介素(IL, interleukin)」亦無統計上顯著差異。石榴則無顯著降低肌酸激酶CK水平。越橘在半馬拉松比賽前後使用的研究顯示在CK及CRP無顯著差異，但有研究卻指出越橘汁降低CK的程度低於對照組，CRP則是有中等程度的升高，DOMS亦有些微高。使用富含花青素的果汁進行下坡跑步96小時後的CK值比對照組顯著降低。</p> <p>結論：回顧分析發現，蔬果汁確實對於運動引起的肌肉損傷有一定的幫助，在功能性、生物標記、量表等指標上呈現肌肉損傷的下降趨勢。</p> <p> </p><p>Objective: This review aimed at investigating the benefits of fruit and vegetable juices for alleviating the symptoms of delayed onset muscle soreness (DOMS) after exercise. </p> <p>Methods: An initial search was performed to identify from related databases previous studies in the literature published before December 2021, and a second search was conducted for locating subsequent studies published before January 2022. The keywords of search we used included “delayed onset muscle soreness” and (“vegetable” or “juice”). Those studies we finally selected for review were published between 2017 and 2019; most of them were randomized controlled studies examining dietary interventions based on natural fruits and vegetables and presenting DOMS-related results. The reviewed studies could be grouped by author, country, clinical trial design, number of experimental and control groups, age and gender of participants, kinds of vegetable juices used as interventions, period of interventions, and outcomes in both experimental and control groups before and after intervention. The review focused on body functionality, biomarkers, and scale.</p> <p>Results: Five eligible studies from 72 previous works in the literature were selected. There were 9 kinds of juices for intervention. Tart cherries and pomegranates appeared to be able to mitigate MIVC (maximal isometric voluntary contraction) but failed to prevent reduced elbow ROM (range of motion). Half of the studies reported benefits on DOMS, while the other half found no obvious intervention effect. The result of VAS (visual analogue scale) was similar to that of DOMS. A tendency of reducing concentrations of creatine kinase (CK) and C-reactive protein (CRP) was observed in tart cherries, but there was no statistical significance. Nor was statistical significancy detected in TNF-α (tumor necrosis factor-α), INF-γ (interferon-gamma), and IL (interleukin) following the eccentric exercise. Pomegranate did not significantly reduce CK levels. Studies on the use of bilberry juice before and after a half-marathon indicated no significant difference in CK and CRP, while some studies found the degree of reducing CK by bilberry juice lower in the experimental group. There was a moderate increase in CRP and a slight elevation in DOMS. Compared to the performance of the control group, CK values were significantly lower after 96 hours of downhill running with anthocyanin-rich fruit juice in the experimental group.</p> <p>Conclusion: Results of the retrospective analysis suggest that fruit juice is indeed helpful in alleviating exercise-induced muscle damage, and the functionality, biomarker, scale and other indicators show a downward trend in the degree of muscle damage.</p> <p> </p>

Crude extract of Ficus deltoidea Jack (FD) as a natural biological therapy.

This study shows how important it is to coordinate research on Ficus deltoidea Jack (FD) so that results from different sources can be compared directly and a scientific conclusion can be made. The author looked for research papers on Ficus (F.) deltoidea on Google Scholar, Science Direct, Google.com, Wiley, PubMed, Hindawi, Springer, and other related databases. This analysis excludes data that cannot be trusted, thesis papers, and review articles about F. deltoidea. In traditional medicine, the plant's leaves and syconia are used to cure a wide variety of ailments, including itchiness, diarrhoea, cancer, sexual dysfunction, age-related issues, malaria, cancer, anxiety, pain, constipation, fever, diabetes, tooth pain, and tooth decay. In vitro and in vivo studies showed the effectiveness of the leaves against cancer cell lines. Based on the existing research on the health benefits of FD, it is critical to focus on its more active constituents and their identification, determination, further development, and, most importantly, standardization of the leaves for the management and treatment of cancer and its related cases. More research is needed before it can be considered a promising herbal source of novel medication candidates for treating various disorders.

Floristic Inventory of Ethnobotanically Important Halophytes of North-Western Mediterranean Coastal Brackish Areas, Tuscany, Italy

Plants have always been used by people for multiple purposes, but over the centuries knowledge of useful plants has largely been lost. Through ethnobotanical studies it is possible to retrieve information on the uses of plants and renew the ancient attention to plants which could be useful to apply in modern applications. In this context, the ethnobotanical use of halophytes has not been explored in depth. The present study focused on the flora of two brackish areas of the north-western Mediterranean sited in Tuscany, Italy. This research aimed to identify the halophyte species of ethnobotanical interest and create a relative map database of the study areas. The floristic list of the two areas, including 78 halophyte and non-halophyte species, was created following periodic field sampling, localization of the species by GPS, and taxonomic identification. The ethnobotanical information was acquired through a bibliographic survey. Botanical, geographic, and ethnobotanical information was filed and included in floristic maps produced using the free Open Source QGIS software. Of the total wild species surveyed, 50% were halophytes with ethnobotanical properties, with a predominance for medicinal ones. Some of them are the subject of numerous studies today such as those on antioxidants. Both investigated areas showed a high floristic and ethnobotanical value. This makes them interesting as potential germplasm banks to be used in various application contexts of ethnobotany.

Using an optimized relative response factor database to simplify a pyrolyzer/thermal desorption-gas chromatography-mass spectrometry method of screening for phthalate esters, polybrominated diphenyl ethers, and polybrominated biphenyls in polymers

The international analytical standard IEC 62321–3–3 describes a method for the screening analysis of phthalate esters, polybrominated diphenyl ethers (PBDEs), and polybrominated biphenyls (PBBs) in polymers by pyrolyzer/thermal desorption-gas chromatography-mass spectrometry (Py/TD-GC/MS). The IEC 62321–3–3 method uses a database of relative response factors (RRFs) (calculated by dividing the response factor (RF) for a target compound by the RF value for a substitute compound (SC) selected from among all target compounds) to quantitate each targeted analyte. A drawback of this method is that a separate RRF database must be created from expensive standard solutions that contain each targeted compound for each instrument, which is a labor-intensive task. In this study, we have developed a “ready-to-use” RRF database that can be used on multiple different instruments. This method eliminates the need to create an RRF database for each instrument and greatly simplifies the screening workflow described in the IEC 62321–3–3 standard. Because it only requires a mixed n-alkane solution and polymer reference materials, which are generally easy to procure and easy to use, the method is highly convenient and suitable for general-purpose use. Assigning tetra-BDE, penta-BDE, deca-BDE, or deca-BB as the SC for each PBDE and PBB analyte allowed the variance in RRFs between instruments to be reduced to a degree suitable for screening analysis. When this method was applied, recovery rates of individual PBDEs and PBBs remained within the range of 74–130 % over an extended period of 54 months. Simultaneous analysis of phthalate esters, PBDEs, and PBBs in various polymer reference materials was also performed with the optimized method on four different instruments and recovery rates of each targeted compound were evaluated. The recovery rates for each phthalate ester, total PBDEs, and total PBBs were within the range of around 100 ± 30 % for all tested samples.

Research on the Intelligent Distribution System of College Dormitory Based on the Decision Tree Classification Algorithm

The trend toward designing an intelligent distribution system based on students’ individual differences and individual needs has taken precedence in view of the traditional dormitory distribution system, which neglects the students’ personality traits, causes dormitory disputes, and affects the students’ quality of life and academic quality. This paper collects freshmen's data according to college students’ personal preferences, conducts a classification comparison, uses the decision tree classification algorithm based on the information gain principle as the core algorithm of dormitory allocation, determines the description rules of students’ personal preferences and decision tree classification preferences, completes the conceptual design of the database of entity relations and data dictionaries, meets students’ personality classification requirements for the dormitory, and lays the foundation for the intelligent dormitory allocation system.

Genetic Analysis of a Case of Sotos Syndrome with Suspected Germinal Mosaicism in Mother.

This study is to identify the pathogenic mutation of a child with Sots syndrome and provide prenatal diagnosis for his pregnant mother. Chromosome microarray technology was used to detect whether there were minor deletions/duplication in patients' chromosomes. The gene mutation of patients was screened by next-generation sequencing technology, and it was verified by Sanger sequencing. Prenatal diagnosis of the fetus was conducted according to the selected pathogenic sites, and genetic counseling was conducted for her parents. Chromosome microarray results showed that there was no minor deletion in a chromosome 5q35 region, and the second-generation sequencing results showed that there was a c.4138delG heterozygous mutation in the patient's NSD1 gene, and the pathogenic of this mutation was not reported in related databases. Sanger sequencing found that there was a c.4138delG heterozygous mutation in the NSD1 gene of the patient and her parents' genotype at this locus was wild type. The prenatal gene test results indicated that there was heterozygous mutation of NSD1 gene c.4138delG in the fetus, so it was suggested to terminate the pregnancy. Gentling results indicated that the fetus and the patient inherited the same maternal chromosome 5. The heterozygous mutation of NSD1 gene c.4138delG is the pathogenic mutation of this Sots syndrome patient, and the mother may be germinal mosaicism.

New panel of biomarkers to discriminate between amelanotic and melanotic metastatic melanoma.

Melanoma is a form of skin cancer that can rapidly invade distant organs. A distinctive feature of melanomas is their pigmentation status, as melanin is present in most skin melanomas, whilst many metastatic tumors could become amelanotic. Besides the obvious malfunction of the key genes of the melanin pathway, the amelanotic tumors could bear a characteristic molecular signature accounting for their aggressivity. Using mass spectrometry-based proteomics we report here a distinctive panel of biomarkers for amelanotic aggressive melanoma that differ from the less invasive pigmented cells. The developed method allows the label-free quantification of proteins identified by LC-MS/MS analysis. We found a set of proteins comprising AHNAK, MYOF, ANXA1, CAPN2, ASPH, EPHA2, THBS1, TGM2, ACTN4 along with proteins involved in cell adhesion/migration (integrins, PLEC, FSCN1, FN1) that are highly expressed in amelanotic melanoma. Accompanying the down regulation of pigmentation specific proteins such as tyrosinase and TYRP1, these biomarkers are highly specific for a type of highly invasive melanoma. Interestingly, the LC-MS/MS proteomics analysis in hypoxia revealed that the abundance of this specific set of proteins found in normoxia was rather unaltered in these conditions. These biomarkers could therefore predict a metastatic behaviour for the amelanotic cells in the early stages of the tumor development and thus serve in melanoma prognostic. Applying this algorithm to related databases including melanoma samples published by independent laboratories/public databases we confirm the specificity of the newly found signatures. Overall, we begin to unravel the molecular alterations in the amelanotic melanoma and how basic proteomics offers insights into how to assess the clinical, pathological and misdiagnosis differences between the main subtypes of melanoma.

Curcumol suppresses endothelial-to-mesenchymal transition via inhibiting the AKT/GSK3β signaling pathway and alleviates pulmonary arterial hypertension in rats

Endothelial dysfunction is essential in pulmonary arterial hypertension (PAH) pathogenesis and is considered to be a therapeutic target of PAH. Curcumol is a bioactive sesquiterpenoid with pharmacological properties including restoring endothelial cells damage. This study aimed to evaluate the effect of curcumol on PAH rats and investigate its possible mechanisms. PAH was induced by subcutaneous injection of 60 mg/kg monocrotaline (MCT) in male Sprague Dawley rats. Curcumol (12.5, 25, and 50 mg/kg/day) were administered by intragastric administration for 3 weeks. The results demonstrated that curcumol dose-dependently alleviated MCT-induced right ventricular hypertrophy and pulmonary arterial wall thickness. In addition, endothelial-to-mesenchymal transition (EndMT) in the pulmonary arteries of MCT-challenged rats was inhibited after curcumol treatment, as evidenced by the restored expressions of endothelial and myofibroblast markers. The possible pharmacological mechanisms of curcumol were analyzed using network pharmacology. After screening the common therapeutic targets of PAH and curcumol by searching related databases and comparison, pathway enrichment was performed and AKT/GSK3β was screened out as a possible signaling pathway which was relevant to the therapeutic mechanism of curcumol on PAH. Western blot analysis verified this in lung tissues. Moreover, combination of TNF-α, TGF-β1 and IL-1β-induced EndMT in primary rat pulmonary arterial endothelial cells were blocked by curcumol, and this effect was resembled by PI3K/AKT inhibitor LY294002. Above all, our study suggested that curcumol inhibited EndMT via inhibiting the AKT/GSK3β signaling pathway, which may contribute to its alleviated effect on PAH. Curcumol may be developed as a therapeutic for PAH in the future.

Linear Solvation–Energy Relationships (LSER) and Equation-of-State Thermodynamics: On the Extraction of Thermodynamic Information from the LSER Database

There is a remarkable wealth of thermodynamic information in freely accessible databases, the LSER database being a classical example. The LSER, or Abraham solvation parameter model, is a very successful predictive tool in a variety of applications in the (bio)chemical and environmental sector. The model and the associated database are very rich in thermodynamic information and information on intermolecular interactions, which, if extracted properly, would be particularly useful in various thermodynamic developments for further applications. Partial Solvation Parameters (PSP), based on equation-of-state thermodynamics, are designed as a versatile tool that would facilitate this extraction of information. The present work explores the possibilities of such an LSER–PSP interconnection and the challenging issues this effort is faced with. The thermodynamic basis of the very linearity of the LSER model is examined, especially, with respect to the contribution of strong specific interactions in the solute/solvent system. This is done by combining the equation-of-state solvation thermodynamics with the statistical thermodynamics of hydrogen bonding. It is verified that there is, indeed, a thermodynamic basis of the LFER linearity. Besides the provenance of the sought linearity, an insight is gained on the thermodynamic character and content of coefficients and terms of the LSER linearity equations. The perspectives from this insight for the further development of LSER and related databases are discussed. The thermodynamic LSER–PSP interconnection is examined as a model for the exchange in information between QSPR-type databases and equation-of-state developments and the associated challenges are examined with representative calculations.

Genetic analysis of a family with BCL11A-related intellectual disability

To explore the genetic basis for two patients from a family with BCL11A-related intellectual disability (BCL11A-ID). Clinical data of the proband and her family members was analyzed. Chromosomal karyotyping analysis, trio-whole exome sequencing (trio-WES) and copy number variation sequencing (CNV-seq) were carried out. For the suspected genetic variants, Sanger sequencing was used to verify, and pathogenicity assessment was conducted. The proband and her mother both had intellectual and language impairment, and their fetal hemoglobin (HbF) was significantly elevated. A heterozygous c.1327_c.1328delTC (p.Ser443Hisfs*128) variant was found in exon 4 of the BCL11A gene by WES, which has resulted in truncated expression of the encoded protein, and Sanger sequencing has verified that the variant was inherited from the mother. The variant was not found in related databases. The variant was predicted as pathogenic according to the guidelines from the American College of Medical Genetics and Genomics (ACMG) (PVS1+PM2+PP1). No karyotypic abnormality was found in the proband, her parents and brother, and no pathogenic CNVs was found in the proband and her parents. The c.1327_c.1328delTC (p.Ser443Hisfs*128) variant may underlay the BCL11A-ID in the proband and her mother. This de novo variant has expanded the mutational spectrum of the BCL11A gene.

The age-related required number of zygotes estimated from prior clinical studies of preimplantation genetic testing for aneuploidy (PGT-A)

Women who are undergoing preimplantation genetic testing for aneuploidy (PGT-A) often wish to know how many eggs will be required to optimize the chances of a live birth. However, no precise data on this can yet be provided during genetic counseling for this procedure. On the basis of PGT-A data from related studies and current databases, we have estimated that the number of zygotes required for a 50% chance of a live birth is 8 at age 40 but increases markedly to 21 at age 43. PGT-A markedly reduces the miscarriage rate per embryo transfer but does not alleviate the extremely high number of zygotes required for a live birth in women of an advanced maternal age. Detailed genetic counseling will therefore be desirable prior to undergoing this procedure.

MICROMINE CALCULATIONS OF ORE RESERVES IN THE BOROV DOL PORPHYRY COPPER DEPOSIT, REPUBLIC OF NORTH MACEDONIA

The calculations of ore reserves in the Borov Dol deposit were mainly carried out with the support of the AutoCAD software package, and those results received official confirmation in the Republic of North Macedonia. The latest calculation using MICROMINE provides a wider range of use of source data from detailed geological surveys and rapid correlation between metals and associated elements in the deposit. The MICROMINE procedure for the calculation of ore reserves in the Borov Dol deposit consists of several stages starting from: creation of new project and related data base (Excel and Micromine), Micromine database validation process, building and creating wireframe, creation of the particular block model as well as calculation of ore reserves by MICROMINE software package. The obtained results are highly correlative and compatible with the same obtained through the method of vertical parallel profiles calculated using the AutoCAD software package (difference 1.21%).

Network-based drug repurposing for HPV-associated cervical cancer

In women, cervical cancer (CC) is the fourth most common cancer around the world with average cases of 604,000 and 342,000 deaths per year. Approximately 50% of high-grade CC are attributed to human papillomavirus (HPV) types 16 and 18. Chances of CC in HPV-positive patients are 6 times more than HPV-negative patients which demands timely and effective treatment. Repurposing of drugs is considered a viable approach to drug discovery which makes use of existing drugs, thus potentially reducing the time and costs associated with de-novo drug discovery. In this study, we present an integrative drug repurposing framework based on a systems biology-enabled network medicine platform. First, we built an HPV-induced CC protein interaction network named HPV2C following the CC signatures defined by the omics dataset, obtained from GEO database. Second, the drug target interaction (DTI) data obtained from DrugBank, and related databases was used to model the DTI network followed by drug target network proximity analysis of HPV-host associated key targets and DTIs in the human protein interactome. This analysis identified 142 potential anti-HPV repurposable drugs to target HPV induced CC pathways. Third, as per the literature survey 51 of the predicted drugs are already used for CC and 33 of the remaining drugs have anti-viral activity. Gene set enrichment analysis of potential drugs in drug-gene signatures and in HPV-induced CC-specific transcriptomic data in human cell lines additionally validated the predictions. Finally, 13 drug combinations were found using a network based on overlapping exposure. To summarize, the study provides effective network-based technique to quickly identify suitable repurposable drugs and drug combinations that target HPV-associated CC.