Treatment of Wilms’ nephroblastoma cancer cells via EGFR targeting of dactinomycin loaded DNA-nanowires

Baig Mirza Muhammad Faran Ashraf,Zhang Chengfei,Akhtar Muhammad Furqan,Saleem Ammara,Nisar Naveed 한국약제학회 2021 Journal of Pharmaceutical Investigation Vol.51 No.2

Purpose Dactinomycin (DCTM) is a highly cytotoxic hydrophobic drug requiring robust nanomaterials for uniformed water dispersion and safe delivery to tumor site avoiding exposure to healthy cells. Methods DNA triangulation produces sturdier two-dimensional nanostructures through the polymerization of DNA-triangles by sticky ends cohesion in the form of DNA-nanosheets. The curvature of the B-form (right twisted) DNA causes the coiling of the DNA-nanosheets into DNA-nanowires (D-NWs) structures. DNA-triangles scaffolded by the short circular templates (84-NT) are stiffer in topology giving rise to compact D-NWs for DCTM loading, and cellular delivery. The PAGE gel analysis was performed to assess the polymerization of the DNA-triangles to observe restricted electrophoretic mobility, and attainment of a single sharp band. The morphology and compactness of the D-NWs were confirmed by the AFM analysis and confocal imaging. Epidermal growth factor (EGF) functionalization of the D-NWs was performed through amide chemistry using amino-modified DNA strands reacting with the carboxylic group of EGF for EGFR targeting. EGFR is highly expressed on NB-OK-1 Wilms’ tumor nephroblastoma cancer cells. DCTM loading onto D-NWs was carried out through intercalation between the base pairs of GC rich DNA duplex by physical mixing/incubation, and was confirmed through the UV peak shift analysis and confocal imaging. Cell internalizations and the cytotoxic effects were monitored via confocal imaging, MTT assay, and flow cytometry. Results AFM images of the synthesized D-NWs showed that polymerization of DNA-triangles was successful with the length ranging from 4 to 6 μm, and width ranging from 80 to 120 nm. EGF functionalization was confirmed through the confocal microscopy after labeling EGF with the FITC hook conjugating dye. The slight UV shift (> 15 nm) confirmed DCTM loading onto D-NWs. Blank D-NWs showed biocompatibility to the cells at different (low to high) concentrations (10 μM to 640 μM). MTT assay revealed that DCTM loaded D-NWs showed a dose-dependent (0.25–128 nM) decrease in cell viability. Conclusion EGF functionalized D-NWs effectively targeted the EGFR rich NB-OK-1 cancer cells compared to the control HEK293/D75 cells lacking EGFR (receptors). By these results, we can expect similar site-specific targeted treatment if administered systemically.

Use of Platelet-Rich Plasma in Treating Low Back Pain: A Review of the Current Literature

Baig Mirza Zain,Abdullah Umm E Hani,Muhammad Aun,Aziz Abeer,Syed Maryam Jamil,Darbar Aneela 대한척추외과학회 2021 Asian Spine Journal Vol.15 No.1

Low back pain (LBP) is a common problem encountered by physicians. It is a considerable cause of morbidity and socioeconomic loss and is one of the most expensive musculoskeletal disorders. Conventional treatments include bed rest, analgesics, therapeutic exercises, lumbar or caudal epidural corticosteroids, and surgery. Several new biological therapies are being investigated for use in LBP and one of these is platelet-rich plasma (PRP). In this article, we summarize the current literature published on PRP concerning its composition, classification, and application in LBP. We believe our review will prove useful to clinicians and academics alike, interested in new developing therapies for LBP.

Experimental and Numerical Analysis of Slurry Flow in Chemical Mechanical Polishing

윤영빈,이도형,Mirza Baig 한국물리학회 2008 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.53 No.4

A slurry flow field in chemical mechanical polishing (CMP) was analyzed by using particle image velocimetry (PIV) and numerical simulations. PIV experiment for analyzing the CMP hydrodynamic regime is a novel approach and the first to combine both experimental measurements and numerical simulations. The quality of CMP in semiconductor production is characterized by its output properties, such as its removal rate (RR) and nonuniformity (NU). The nonuniformity of the wafer surface is due to the irregularity of the material removal rate across the wafer's surface and both NU and RR problems result from an uneven slurry flow distribution on the wafer surface. The slurry ow field was studied on the wafer scale under various pad and carrier rpm conditions. Direct measurement of the slurry flow field was first applied to the CMP process by adequately modifying a conventional PIV system. A numerical simulation was carried out for the validation of the current analysis and for future use under various CMP conditions. The analysis showed that the flow speed was strongly in fluenced by the pad velocity and that the overall flow field was characterized mainly by the ratio between the pad rpm and the carrier rpm. A slurry flow field in chemical mechanical polishing (CMP) was analyzed by using particle image velocimetry (PIV) and numerical simulations. PIV experiment for analyzing the CMP hydrodynamic regime is a novel approach and the first to combine both experimental measurements and numerical simulations. The quality of CMP in semiconductor production is characterized by its output properties, such as its removal rate (RR) and nonuniformity (NU). The nonuniformity of the wafer surface is due to the irregularity of the material removal rate across the wafer's surface and both NU and RR problems result from an uneven slurry flow distribution on the wafer surface. The slurry ow field was studied on the wafer scale under various pad and carrier rpm conditions. Direct measurement of the slurry flow field was first applied to the CMP process by adequately modifying a conventional PIV system. A numerical simulation was carried out for the validation of the current analysis and for future use under various CMP conditions. The analysis showed that the flow speed was strongly in fluenced by the pad velocity and that the overall flow field was characterized mainly by the ratio between the pad rpm and the carrier rpm.

Study of heavy fuel oil fly ash for use in concrete blocks and asphalt concrete mixes

Al-Osta, Mohammed A.,Baig, Mirza G.,Al-Malack, Muhammad H.,Al-Amoudi, Omar S. Baghabra Techno-Press 2016 Advances in concrete construction Vol.4 No.2

Use of heavy fuel fly ash (HFFA) (diesel and cracked fuel) for power generation in Saudi Arabia has generated and accumulated large quantities of HFFA as a byproduct. In this research, HFFA is studied with the emphasis on the utilization of this waste material in concrete blocks and asphalt concrete mixes. Two types of mixes, one with low and other with high cement content, were studied for concrete blocks. Different mixes having varying percentages of HFFA (0% to 25%), as cement/sand replacement or as an additive, were studied. The performance of concrete blocks is evaluated in terms of compressive strength, water absorption, durability and environmental concerns. The results showed that blocks cannot be cast if more than 15% HFFA is used; also there is a marginal reduction in the strength of all the mixes before and after being exposed to the sulfate solution for a period of ten months. HFFA is studied in asphalt concrete mixes in two ways, as an asphalt modifier (3&5%) and as a filler (50%) replacement, the results showed an improvement in stiffness and fatigue life of mixes. However, the stability and indirect tensile strength loss were found to be high as compared to the control mix due to moisture damage, indicating a need of using antistripping agents. On environmental concerns, it was found that most of the concerned elements are within acceptable limits also it is observed that lower concentration of barium is leached out with the higher HFFA concentrations, which indicates that HFFA may work as an adsorbent for this leaching element.

Preparation and evaluation of carbamazepine loaded fibrous electrospun mats of starch

Tarique Ali Meer,Mirza Shehzad Baig,Purnima D. Amin 한국약제학회 2015 Journal of Pharmaceutical Investigation Vol.45 No.3

The preset work deals with preparation of fibrous electrospun mats of starch (FEMOS) carrier, from naı¨ve starch, through a process of electrospinning. The developed FEMOS was explored for the solubility enhancement of poorly water soluble drug carbamazepine. Solid state characterization was performed with respect to Fourier transform infra-red spectroscopy, X-ray diffraction, scanning electron microscopy, contact angle determination, dissolution kinetics, and differential scanning calorimetry. Rapid release profiles were observed when the carbamazepine was loaded on FEMOS. This effect may be due to high surface area, improved wettability and reduced crystallinity of the loaded drug on FEMOS. The developed formulation was found to have a similar in vivo performance as compared to marketed formulation TegretolⓇ.

An Application of Machine Learning in Retail for Demand Forecasting

Muhammad Umer Farooq,Mustafa Latif,Waseemullah,Mirza Adnan Baig,Muhammad Ali Akhtar,Nuzhat Sana International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.9

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

An Application of Machine Learning in Retail for Demand Forecasting

Muhammad Umer Farooq,Mustafa Latif,Waseem,Mirza Adnan Baig,Muhammad Ali Akhtar,Nuzhat Sana International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.8

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

Use of Prucalopride for Chronic Constipation: A Systematic Review and Meta-analysis of Published Randomized, Controlled Trials

( Muhammad S Sajid ),( Madhu Hebbar ),( Mirza K Baig ),( Andy Li ),( Zinu Philipose ) 대한소화기기능성질환·운동학회(구 대한소화관운동학회) 2016 Journal of Neurogastroenterology and Motility (JNM Vol.22 No.3

This article highlights the role of prucalopride in the management of chronic constipation based upon the principles of meta-analysis using data reported in the published randomized, controlled trials. Sixteen randomized, controlled trials on 3943 patients reported the effectiveness of prucalopride in patients with chronic constipation. Prucalopride successfully increased the frequency of spontaneous bowel movements per week in all variable doses of 1 mg (standardized mean difference [SMD], 0.42 [95% CI, 0.18-0.66; P = 0.006]), 2 mg (SMD, 0.34 [95% CI, 0.11-0.56; P = 0.003]), and 4 mg (SMD, 0.33 [95% CI, 0.22-0.44; P = 0.00001]). The risks of adverse events or side effects such as headache, abdominal cramps, excessive flatulence, dizziness, diarrhea, and rash were higher (odds ratio, 1.70 [95% CI, 1.27 to -2.27; P = 0.0004]) in prucalopride group. Prucalopride is clinically a beneficial pharmacotherapy for chronic constipation and its routine use may be considered in patients with chronic simple laxative-resistant constipation. (J Neurogastroenterol Motil 2016;22:412-422)

Lane Detection and Detection-Error Correction by using Hough Transform

Jaegwon Seo(서재권),Sungchul Jung(정성철),Mirza Waqar Baig(미르자 와카르 백),Hyunchul Shin(신현철) 대한전기학회 2010 정보 및 제어 심포지엄 논문집 Vol.2010 No.4

Intelligent vehicles with robust lane detection and warning systems (LDWS) have been gaining popularity for enhanced safety. Robust lane following is important to warn the driver efficiently from lane departure. Accurate lane detection under diverse road and weather conditions is a critical issue for LDWS. In this paper, we have developed a cost effective vision based approach which is capable of detecting the lanes with robustness and capable of overcoming the errors caused due to the illumination changes or clutters. A cost effective technique using a single camera has been used to capture the road. The edges are detected by Sobel edge detector. A filtering process is used to remove noises e.g., shadows and clutters in the edge map. The Hough transform is used to find the lanes in the filtered edge map. The online tracking of lanes is done by using data comparison through Hough transform.

Statistical Analysis of Constraints Acquiring Higher Secondary Education

Najeed A. Khan,Syed Shah Sultan Mohiuddin,Mirza Mehmood Baig,Twaha Ahmed Minai 보안공학연구지원센터 2014 International Journal of Database Theory and Appli Vol.7 No.2