Pashto script and graphics detection in camera captured Pashto document images using deep learning model.

Layout analysis is the main component of a typical Document Image Analysis (DIA) system and plays an important role in pre-processing. However, regarding the Pashto language, the document images have not been explored so far. This research, for the first time, examines Pashto text along with graphics and proposes a deep learning-based classifier that can detect Pashto text and graphics per document. Another notable contribution of this research is the creation of a real dataset, which contains more than 1,000 images of the Pashto documents captured by a camera. For this dataset, we applied the convolution neural network (CNN) following a deep learning technique. Our intended method is based on the development of the advanced and classical variant of Faster R-CNN called Single-Shot Detector (SSD). The evaluation was performed by examining the 300 images from the test set. Through this way, we achieved a mean average precision (mAP) of 84.90%.

Kojic acid reverses LPS-induced neuroinflammation and cognitive impairment by regulating the TLR4/NF-κB signaling pathway.

Intense neuroinflammation contributes to neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease. Lipopolysaccharides (LPSs) are an integral part of the cell wall of Gram-negative bacteria that act as pathogen-associated molecular patterns (PAMPs) and potentially activate the central nervous system's (CNS) immune system. Microglial cells are the local macrophages of the CNS and have the potential to induce and control neuroinflammation. This study aims to evaluate the anti-inflammatory and antioxidant effect of kojic acid against the toxic effects of LPSs, such as neuroinflammation-induced neurodegeneration and cognitive decline. The C57BL/6N mice were subjected to LPS injection for 2 weeks on alternate days (each mouse received 0.25 mg/kg/i.p. for a total of seven doses), and kojic acid was administered orally for 3 weeks consecutively (50 mg/kg/mouse, p. o). Bacterial endotoxins, or LPSs, are directly attached to TLR4 surface receptors of microglia and astrocytes and alter the cellular metabolism of immune cells. Intraperitoneal injection of LPS triggers the toll-like receptor 4 (TLR4), phospho-nuclear factor kappa B (p-NFκB), and phospho-c-Jun n-terminal kinase (p-JNK) protein expressions in the LPS-treated group, but these expression levels were significantly downregulated in the LPS + KA-treated mice brains. Prolong neuroinflammation leads to the generation of reactive oxygen species (ROS) followed by a decrease in nuclear factor erythroid-2-related factor 2 (Nrf2) and the enzyme hemeoxygenase 1 (HO-1) expression in LPS-subjected mouse brains. Interestingly, the levels of both Nrf-2 and HO-1 increased in the LPS + KA-treated mice group. In addition, kojic acid inhibited LPS-induced TNF-α and IL-1ß production in mouse brains. These results indicated that kojic acid may suppress LPS-induced neuroinflammation and oxidative stress in male wild-type mice brains (in both the cortex and the hippocampus) by regulating the TLR4/NF-κB signaling pathway.

Does the digital economy improve female employment? A cross-country panel data analysis.

The digital economy has had an impact on the female employment rate over time. Currently, the researchers are more interested in investigating the impacts of the digital economy by focusing on its various aspects of female employment. The current study is motivated by this renewed interest to investigate the impact of the digital economy on female employment rates in Asian Developing Countries from 1990 to 2021. The digital economy is measured by several indicators such as fixed telephone subscriptions, fixed broadband subscriptions, mobile phone subscriptions, secure internet servers, and internet users. The Panel Autoregressive Distributed Lag (PARDL) model is used for analysis that reveals a positive relationship between female employment rates and the digital economy in both the short and long run. The control variables/factors, Education and GDP, also showed positive relationships with female employment. We suggest that governments prioritize funding for digital infrastructure and encourage fair access to technology, especially for women, based on our study. Furthermore, the positive effects of the digital economy on female employment can be strengthened through focused policy interventions, such as offering financial incentives to companies that hire and train women in digital skills. By utilizing these tactics, policymakers can guarantee that women are prepared to take advantage of the chances brought about by the quickly changing digital landscape, promoting gender equality and inclusive economic growth throughout Asian developing nations.

Vanadium toxicity was alleviated by supplementation of silicon in tomato seedlings: Upregulating antioxidative enzymes and glyoxalase system.

The primary goal of this research is to investigate the mitigating effect of silicon (Si; 2 mM) on the growth of tomato seedlings under vanadium (V; 40 mg) stress. V stress caused higher V uptake in leaf, and enhanced concentration of leaf anthocyanin, H2O2, O2•-, and MDA, but a decreased in plant biomass, root architecture system, leaf pigments content, mineral elements, and Fv/Fm (PSII maximum efficiency). Si application increased the concentrations of crucial antioxidant molecules such as AsA and GSH, as well as the action of key antioxidant enzymes comprising APX, GR, DHAR, and MDHAR. Importantly, oxidative damage was remarkably alleviated by upregulation of these antioxidant enzymes genes. Moreover, Si application enhanced the accumulation of secondary metabolites as well as the expression their related-genes, and these secondary metabolites may restricted the excessive accumulation of H2O2. In addition, Si rescued tomato plants against the damaging effects of MG by boosting the Gly enzymes activity. The results confirmed that spraying Si to plants might diminish the V accessibility to plants, along with promotion of V stress resistance.

Demographic characteristics and short-term outcomes of laparoscopic colon cancer surgeries at a newly developed cancer center in Peshawar, Pakistan.

Objective: In Pakistan, colon cancer ranks fourth in incidence, exhibiting survival rates of 90% to 14%, contingent on TNM staging and early detection. This research focuses on the demographic involvement and short-term outcomes of elective colon cancer resections at a newly established tertiary care cancer center utilizing laparoscopic procedures. Method: A retrospective analysis of elective laparoscopic colorectal resections at Shaukat Khanum Memorial Cancer Institute and Research Centre, Peshawar, from April 2021 to February 2022 was conducted. Out of 157 cases, 79 had colon cancer. Criteria included patients >18 years old with positive biopsies; consent non-providers were excluded. Statistical analysis employed descriptive statistics and cross-tabulations using SPSS-22. Results: The study encompassed biopsy-confirmed colon cancers in patients >18 years. 157 colorectal cases were performed, including 79 colon cancers. The sample comprised 61 males (77.2%) and 18 females (22.7%), mean age 42 years. Most patients (33%) were in the 36-45 age group. Majority were from KPK (69.6%), followed by Afghanistan (24%). Tumors were predominantly in the ascending colon (30.3%). Most were moderately differentiated (70.8%). Mean lymph node yield was 19.0, with 1.2% requiring open laparotomy. Post-discharge, one readmission occurred within 30 days. Mortality within 90 days was 2%, attributed to aspiration pneumonia and chemotherapy-related effects. Conclusions: Elective laparoscopic colonic surgery exhibits safety and efficacy in treating colon cancer. The study provides evidence of minimal morbidity and mortality, low readmission rates, and absence of anastomotic leaks. Hence, elective laparoscopic colonic surgery should be favored due to fewer post-operative complications and superior short-term outcomes. Larger studies on colon cancer are imperative for enhanced healthcare delivery.

Novel techniques to analyze dynamical properties of quantum chaos with peculiar evidence of hybrid systems confinement.

Recent results demonstrate the dynamical peculiarities of the quantum chaos within the hybrid systems by chaotic parameters and probe the pattern formation under the influence of condensation. The complex dynamic behavior of the considered systems was determined with numerical simulation and presented an efficient technique that studied fractional systems comprising chaos-coherence fractions. The findings divulge the peculiar association between the coherence structure and the correlations at finite relative momenta. Thus the present study helps to explore the partially chaos hybrid systems in order to stimulate the experimental applications of nonlinear phenomena. The coherent-chaotic parameters can be measured by examining the chaos peculiarities that possess explicit relations with the condensations to demonstrate the environs of the physical systems. We investigate the influence of the multiplicities, chaos, momentum and temperature of the nonlinear system on the coherent-chaotic normalized correlations. The chaotic parameters are suppressed considerably with the coherence fraction and it appears numerically zero at maximum condensation and one at ideal chaos emissions. We procure that the meaningful parameters decrease significantly with the multiplicity of the nonlinear systems and increase with the momentum in the specified regimes. The identical multiplicity leads to contemplating the coherence and thus the normalized chaotic parameters within its spectacular influences exhibit significance worth contemplating in earnest. The findings underscore the significance of cogitating correlations in deciphering the nonlinear system characteristics and bestowing extraordinary perceptiveness into the convoluted essence of complex systems. The contemplated methodology can be applied to evaluating and analyzing the nonlinear systems and such an innovative approach computes the problems of celestial mechanics, heartbeats and chemical reactions in engineering and medical fields.

ALL classification using neural ensemble and memetic deep feature optimization.

Acute lymphoblastic leukemia (ALL) is a fatal blood disorder characterized by the excessive proliferation of immature white blood cells, originating in the bone marrow. An effective prognosis and treatment of ALL calls for its accurate and timely detection. Deep convolutional neural networks (CNNs) have shown promising results in digital pathology. However, they face challenges in classifying different subtypes of leukemia due to their subtle morphological differences. This study proposes an improved pipeline for binary detection and sub-type classification of ALL from blood smear images. At first, a customized, 88 layers deep CNN is proposed and trained using transfer learning along with GoogleNet CNN to create an ensemble of features. Furthermore, this study models the feature selection problem as a combinatorial optimization problem and proposes a memetic version of binary whale optimization algorithm, incorporating Differential Evolution-based local search method to enhance the exploration and exploitation of feature search space. The proposed approach is validated using publicly available standard datasets containing peripheral blood smear images of various classes of ALL. An overall best average accuracy of 99.15% is achieved for binary classification of ALL with an 85% decrease in the feature vector, together with 99% precision and 98.8% sensitivity. For B-ALL sub-type classification, the best accuracy of 98.69% is attained with 98.7% precision and 99.57% specificity. The proposed methodology shows better performance metrics as compared with several existing studies.

Deep learning-based recognition system for pashto handwritten text: benchmark on PHTI.

This article introduces a recognition system for handwritten text in the Pashto language, representing the first attempt to establish a baseline system using the Pashto Handwritten Text Imagebase (PHTI) dataset. Initially, the PHTI dataset underwent pre-processed to eliminate unwanted characters, subsequently, the dataset was divided into training 70%, validation 15%, and test sets 15%. The proposed recognition system is based on multi-dimensional long short-term memory (MD-LSTM) networks. A comprehensive empirical analysis was conducted to determine the optimal parameters for the proposed MD-LSTM architecture; Counter experiments were used to evaluate the performance of the proposed system comparing with the state-of-the-art models on the PHTI dataset. The novelty of our proposed model, compared to other state of the art models, lies in its hidden layer size (i.e., 10, 20, 80) and its Tanh layer size (i.e., 20, 40). The system achieves a Character Error Rate (CER) of 20.77% as a baseline on the test set. The top 20 confusions are reported to check the performance and limitations of the proposed model. The results highlight complications and future perspective of the Pashto language towards the digital transition.

Health risk assessment of heavy metals in saffron (Crocus sativus L.) cultivated in domestic wastewater and lake water irrigated soils.

Irrigation of crops with domestic wastewater (DW) is a common practice in developing countries like India. However, domestic wastewater irrigation poses a risk of migration of toxic heavy metals to edible parts of crops, which requires serious measures to prevent their uptake. In this study, the effect of DW irrigation in comparison with Sarbal Lake water (SLW) and borewell water (BW) on soil characteristics and cultivated saffron (Crocus sativus L.) was investigated. For this purpose, samples of water, soil, and saffron (corm, petal, and stigma) were collected from the suburban area of Pampore, Srinagar district, Jammu and Kashmir, India. The results showed that DW irrigation had the maximum significant (p < 0.05) influence on the physico-chemical and nutrient characteristics of the soil, followed by SLW and BW irrigation, respectively. The growth and yield parameters of saffron were also significantly (p < 0.05) increased in the case of DW irrigation as compared to SLW and BW. The quality ranking of the cultivated saffron was found to be in accordance with the ISO standard (III: BW and II: DW and SLW). On the other hand, DW irrigation showed a significant increase in heavy metal contents (mg/kg) of saffron plant parts such as As (0.21-0.40), Cd (0.04-0.09), Cr (0.16-0.41), Cu (7.31-14. 75), Fe (142.38-303.15), Pb (0.18-0.31), Mn (15.26-22.81), Hg (0.18-0.25), Ni (0.74-1.18), Se (0.13-0.22), and Zn (3.44-4.59), followed by SLW and BW. However, the levels of heavy metals did not exceed the FAO/WHO safe limits. Bioaccumulation factor (BAF), dietary intake modeling (DIM<0.006496), health risk assessment (HRI<0.028571), and target hazard quotient (THQ<1) analyses showed no potential health hazard associated with the consumption of saffron irrigated with DW and SLW. Therefore, the results of this study provide valuable insights into the optimization of irrigation sources for saffron cultivation.

Short-Term Outcomes of First 100 Laparoscopic Colorectal Surgeries at a Newly Developed Surgical Setup at Peshawar.

BACKGROUND: The incidence of colorectal cancer (CRC) has risen steadily, necessitating innovative strategies for diagnosis and treatment. Minimally invasive surgery, exemplified by laparoscopic techniques, has emerged as a transformative approach in colorectal surgical practices. Laparoscopy offers advantages such as improved aesthetic outcomes, reduced post-operative pain, early patient mobilization, and shorter hospital stays. OBJECTIVE: This study aims to present the short-term surgical outcomes of the first 100 elective laparoscopic CRC resections performed at a newly established tertiary care cancer center in Peshawar, Pakistan. MATERIALS AND METHODS: Data were prospectively collected for CRC resections performed between April 2021 and February 2022. The study included patients above 18 years of age with biopsy-proven CRC. Surgical procedures were performed by two dedicated colorectal surgeons trained in minimally invasive surgery. Patient demographics, pre-operative factors, intraoperative parameters, and post-operative outcomes were systematically recorded and analyzed. RESULTS: Among the 100 cases included in the study, laparoscopic colorectal surgeries were successfully performed without any conversions to open surgery. The mean age of the study population was 52.5 years, with a male-to-female ratio of 2:1. The majority of cases were colon (48%) and anorectal cancers (52%). The mean lymph node yield was 18.29 (range 6-49). Only one patient required a re-look laparoscopy for a pelvic hematoma, and overall mortality was reported at 1%. CONCLUSION: Laparoscopic colorectal surgery is a safe and effective treatment option for elective colorectal operations with minimal post-operative complications and favorable short-term outcomes.

Mass spectrometric study of low energy Cs+ ion-induced sputtered fragmentation of PADC polymer.

In this study, low-energy cesium (Cs+ ) ion-induced sputtered fragmentation of poly allyl diglycol carbonate (PADC) was investigated using mass spectrometry. The collision-induced dissociation mechanism revealed emission of various fragments, including monoatomic (H- , C1 - , O1 - ), diatomic (C2 - ), and multiatomic (C3 - , CO2 - , C2 O2 - , C3 O2 - ) species within the Cs+ ion energy range of 1-5 keV. The anion current of these fragments exhibited a linear increase with rising incident Cs+ ion energy, indicating a corresponding rise in fragment abundance. Analysis of normalized yield indicated that at 1 keV incident energy, the dominant fragment was monoatomic hydrogen (H- ), followed by diatomic carbon (C2 - ), monoatomic carbon (C1 - ), and monoatomic oxygen (O1 - ). Although C2 - remained dominant up to 5 keV, other fragments exhibited varying normalized yields at different ion energy steps. The sputter yield estimation revealed that monoatomic hydrogen (H- ) and diatomic carbon (C2 - ) exhibited the highest yields, increasing exponentially beyond 3 keV, while multiatomic fragments like C3 - , CO2 - , C2 O2 - , and C3 O2 - displayed the lowest yields. The sputter dissociation mechanism pointed to dehydrogenation, chain scission, and bond breakage as the primary processes during low-energy Cs+ ion impact. Postsputtering Scanning Electron Mircoscope (SEM) micrographs show craters, pits, and micropores on the PADC surface, indicating significant surface degradation. X-ray Diffraction (XRD) spectra exhibited reduced diffraction intensity, while Fourier Transform Infrared Spectroscopy (FTIR) analysis indicated the absence of molecular bands in the IR spectrum, confirming extensive surface damage due to Cs+ ion-induced sputtering.

Immunization Effects of a Novel α-Synuclein-Based Peptide Epitope Vaccine in Parkinson's Disease-Associated Pathology.

Parkinson's disease (PD) is a chronic neurodegenerative disease that affects the central nervous system, specifically the motor system. It is mainly caused by the loss of dopamine due to the accumulation of α-synuclein (α-syn) protein in the striatum and substantia nigra pars compacta (SNpc). Previous studies have reported that immunization may be a potential preventive strategy for neurodegenerative diseases such as Alzheimer's disease (AD) and amyotrophic lateral sclerosis (ALS). Therefore, the aim of the study was to design an α-syn specific epitope vaccine and investigate its effect in PD-related pathophysiology using an α-syn-induced mouse model. We used an in silico model to identify and design a non-toxic α-syn-based peptide epitope vaccine and, to overcome poor immunogenicity, the vaccine was coupled with immunogenic carrier proteins, i.e., ovalbumin (OVA) and keyhole limpet haemocyanin (KLH). Our results showed that vaccinated PD mouse models, especially with vaccines with carrier proteins, improved in motor functions compared with the non-vaccinated PD model. Additionally, the vaccinated groups showed increased immunoglobulin G (IgG) levels in the spleen and plasma as well as decreased interleukin-10 (IL-10) levels in the plasma. Furthermore, vaccinated groups, especially OVA and KLH groups, showed decrease in α-syn levels and increased dopamine-related markers, i.e., tyrosine hydroxylase (TH), vesicle monoamine transporter 2 (VMAT2), and dopamine transporter (DAT), and autophagy activities in the striatum and SNpc. Lastly, our data showed decreased neuroinflammation by reducing the activation of microglia and astrocytes and pro-inflammatory cytokines in the immunized groups, especially with OVA and KLH carrier proteins. Overall, these results suggest that vaccination, especially with immunogenic carrier proteins, is effective in reducing the accumulation of α-syn aggregates in the brain and ameliorate PD-related pathophysiology. Hence, further development of this approach might have a potential role in preventing the development of PD.

Insights on the Nutritional Profiling of Cantaloupe (Cucumis melo L.) via 1-Naphthalene Acetic Acid.

The nutritional components of cantaloupe, including vitamins, minerals, antioxidants, and dietary fiber, contribute to overall health, improved immunity, hydration, and protection against chronic diseases. This study was conducted to investigate the influence of different concentrations (0 (control), 100, 150, and 200 ppm) of 1-naphthalene acetic acid (1-NAA) on the nutritional components of the cantaloupe (Cucumis melo L. Var. Super White Honey). All the studied treatments were applied twice at the 2nd and 4th leaf stages. The applied concentrations of 1-NAA significantly improved the sex expression and fruit yield attributes. Different nutritional components like proximate contents, minerals, vitamins, selected fatty acids, and amino acids were analyzed. The results showed that the maximum moisture content, proteins, carbohydrates, ash, and energy were recorded with 100 ppm. The higher lipids were recorded during the supplementation of 150 ppm. Significantly greater fibers were recorded using 200 ppm. Regarding minerals, 100 ppm was found to be the best as it increased calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), phosphorous (P), manganese (Mn), copper (Cu), iron (Fe), and zinc (Zn). Vitamins were also found to be the maximum with 100 ppm, including vitamin A, vitamin B, vitamin C, vitamin D, vitamin E, and vitamin K. Total selected fatty acids and amino acids were also found significantly greater in the fruits administered 100 ppm.

A Triterpenoid Lupeol as an Antioxidant and Anti-Neuroinflammatory Agent: Impacts on Oxidative Stress in Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease illustrated by neuronal dysfunctions, leading to memory weaknesses and personality changes mostly in the aged population worldwide. The exact cause of AD is unclear, but numerous studies have addressed the involvement of oxidative stress (OS), induced by reactive oxygen species (ROS), to be one of the leading causes in developing AD. OS dysregulates the cellular homeostasis, causing abnormal protein and lipid metabolism. Nutrition plays a pivotal role in modulating the antioxidant system and decreases the neuronal ROS level, thus playing an important therapeutic role in neurodegenerative diseases, especially in AD. Hence, medicinal herbs and their extracts have received global attention as a commercial source of antioxidants Lupeol. Lupeol is a pentacyclic triterpenoid and has many biological functions. It is available in fruits, vegetables, and medicinal plants. It has shown effective antioxidant and anti-inflammatory properties, and higher blood-brain barrier permeability. Also, the binding and inhibitory potentials of Lupeol have been investigated and proved to be effective against certain receptor proteins and enzymes in AD studies by computational molecular docking approaches. Therefore, AD-related research has gained interest in investigating the therapeutic effects of Lupeol. However, despite its beneficial effects in AD, there is still a lack of research in Lupeol. Hence, we compiled in this analysis all preclinical research that looked at Lupeol as an antioxidant and anti-inflammatory agent for AD.

A Novel, Precise and High-Throughput Technology for Viroid Detection in Cannabis (MFDetectTM).

Hop latent viroid (HLVd) is a severe disease of cannabis, causing substantial economic losses in plant yield and crop value for growers worldwide. The best way to control the disease is early detection to limit the spread of the viroid in grow facilities. This study describes MFDetectTM as a rapid, highly sensitive, and high-throughput tool for detecting HLVd in the early stages of plant development. Furthermore, in the largest research study conducted so far for HLVd detection in cannabis, we compared MFDetectTM with quantitative RT-PCR in a time course experiment using different plant tissues, leaves, petioles, and roots at different plant developmental stages to demonstrate both technologies are comparable. Our study found leaf tissue is a suitable plant material for HLVd detection, with the viroid titer increasing in the infected leaf tissue with the age of plants. The study showed that other tissue types, including petiole and roots, were equally sensitive to detection via MFDetectTM. The assay developed in this research allows the screening of thousands of plants in a week. The assay can be scaled easily to provide growers with a quick turnaround and a cost-effective diagnostic tool for screening many plants and tissue types at different stages of development.

Epigenetics regulation during virus-host interaction and their effects on the virus and host cell.

Epigenetics, a field of study focused on cellular gene regulation independent of DNA sequence alterations, encompasses DNA methylation, histone modification and microRNA modification. Epigenetics processes play a pivotal role in governing the life cycles of viruses, enabling their transmission, persistence, and maintenance with in host organisms. This review examines the epigenetics regulation of diverse virus including orthomoxyviruses, coronavirus, retroviridae, mononegavirales, and poxviruses among others. The investigation encompasses ten representative viruses from these families. Detailed exploration of the epigenetic mechanisms underlying each virus type, involving miRNA modification, histone modification and DNA methylation, sheds light on the intricate and multifaceted epigenetic interplay between viruses and their hosts. Furthermore, this review investigates the influence of these epigenetic processes on infection cycles, emphasizing the utilization of epigenetics by viruses such as Epstein-Barr virus and Human immunodeficiency virus (HIV) to regulate gene expression during chronic or latent infections, control latency, and transition to lytic infection. Finally, the paper explores the novel treatments possibilities stemming from this epigenetic understanding.

Vitamin E Analog Trolox Attenuates MPTP-Induced Parkinson's Disease in Mice, Mitigating Oxidative Stress, Neuroinflammation, and Motor Impairment.

Trolox is a potent antioxidant and a water-soluble analog of vitamin E. It has been used in scientific studies to examine oxidative stress and its impact on biological systems. Trolox has been shown to have a neuroprotective effect against ischemia and IL-1ß-mediated neurodegeneration. In this study, we investigated the potential protective mechanisms of Trolox against a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinson's disease mouse model. Western blotting, immunofluorescence staining, and ROS/LPO assays were performed to investigate the role of trolox against neuroinflammation, the oxidative stress mediated by MPTP in the Parkinson's disease (PD) mouse model (wild-type mice (C57BL/6N), eight weeks old, average body weight 25-30 g). Our study showed that MPTP increased the expression of α-synuclein, decreased tyrosine hydroxylase (TH) and dopamine transporter (DAT) levels in the striatum and substantia nigra pars compacta (SNpc), and impaired motor function. However, Trolox treatment significantly reversed these PD-like pathologies. Furthermore, Trolox treatment reduced oxidative stress by increasing the expression of nuclear factor erythroid-2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). Lastly, Trolox treatment inhibited the activated astrocytes (GFAP) and microglia (Iba-1), also reducing phosphorylated nuclear factor-κB, (p-NF-κB) and tumor necrosis factor-alpha (TNF-α) in the PD mouse brain. Overall, our study demonstrated that Trolox may exert neuroprotection on dopaminergic neurons against MPTP-induced oxidative stress, neuroinflammation, motor dysfunction, and neurodegeneration.

Early Failure of Primary Total Knee Arthroplasty Due to Massive Osteolysis Caused by Bio-Absorbable Interference Screws.

We report an unusual case in which an unabsorbed bio-absorbable screw in the tibial tunnel of anterior cruciate ligament reconstruction (ACLR) performed 11 years ago caused massive osteolysis and subsequent failure of total knee arthroplasty (TKA). ACLR was performed using suspensory fixation on the femoral side and a bio-absorbable interference screw on the tibial side. Fragmentation of the bio-absorbable screw at the time of tibial component implantation is thought to have evoked an accelerated inflammatory response, causing osteolysis, which finally resulted in early failure of the TKA.

Leukocytes Classification for Leukemia Detection Using Quantum Inspired Deep Feature Selection.

Leukocytes, also referred to as white blood cells (WBCs), are a crucial component of the human immune system. Abnormal proliferation of leukocytes in the bone marrow leads to leukemia, a fatal blood cancer. Classification of various subtypes of WBCs is an important step in the diagnosis of leukemia. The method of automated classification of WBCs using deep convolutional neural networks is promising to achieve a significant level of accuracy, but suffers from high computational costs due to very large feature sets. Dimensionality reduction through intelligent feature selection is essential to improve the model performance with reduced computational complexity. This work proposed an improved pipeline for subtype classification of WBCs that relies on transfer learning for feature extraction using deep neural networks, followed by a wrapper feature selection approach based on a customized quantum-inspired evolutionary algorithm (QIEA). This algorithm, inspired by the principles of quantum physics, outperforms classical evolutionary algorithms in the exploration of search space. The reduced feature vector obtained from QIEA was then classified with multiple baseline classifiers. In order to validate the proposed methodology, a public dataset of 5000 images of five subtypes of WBCs was used. The proposed system achieves a classification accuracy of about 99% with a reduction of 90% in the size of the feature vector. The proposed feature selection method also shows a better convergence performance as compared to the classical genetic algorithm and a comparable performance to several existing works.