Unravelling reference bias in ancient DNA datasets.

MOTIVATION: The alignment of sequencing reads is a critical step in the characterization of ancient genomes. However, reference bias and spurious mappings pose a significant challenge, particularly as cutting-edge wet lab methods generate datasets that push the boundaries of alignment tools. Reference bias occurs when reference alleles are favoured over alternative alleles during mapping, whereas spurious mappings stem from either contamination or when endogenous reads fail to align to their correct position. Previous work has shown that these phenomena are correlated with read length but a more thorough investigation of reference bias and spurious mappings for ancient DNA has been lacking. Here, we use a range of empirical and simulated palaeogenomic datasets to investigate the impacts of mapping tools, quality thresholds, and reference genome, on mismatch rates across read lengths. RESULTS: For these analyses, we introduce AMBER, a new bioinformatics tool for assessing the quality of ancient DNA mapping directly from BAM-files and informing on reference bias, read-length cut-offs and reference selection. AMBER rapidly and simultaneously computes the sequence read mapping bias in the form of the mismatch rates per read length, cytosine deamination profiles at both CpG and non-CpG sites, fragment length distributions, and genomic breadth and depth of coverage. Using AMBER, we find that mapping algorithms and quality threshold choices dictate reference bias and rates of spurious alignment at different read lengths in a predictable manner, suggesting that optimised mapping parameters for each read length will be a key step in alleviating reference bias and spurious mappings. AVAILABILITY: AMBER is available for non-commercial use on GitHub (https://github.com/tvandervalk/AMBER.git). Scripts used to generate and analyze simulated data sets are available on Github (https://github.com/sdolenz/refbias_scripts). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Power spectral density-based resting-state EEG classification of first-episode psychosis.

Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and cognitive tasks have been studied many times. However, any significant dissimilarity in the resting-state low-frequency bands is yet to be established. Spectral analysis of the alpha and delta band waves shows the effectiveness of stimulus-independent EEG in identifying the abnormal activity patterns of pathological brains. A generalized model incorporating multiple frequency bands should be more efficient in associating potential EEG biomarkers with first-episode psychosis (FEP), leading to an accurate diagnosis. We explore multiple machine-learning methods, including random-forest, support vector machine, and Gaussian process classifier (GPC), to demonstrate the practicality of resting-state power spectral density (PSD) to distinguish patients of FEP from healthy controls. A comprehensive discussion of our preprocessing methods for PSD analysis and a detailed comparison of different models are included in this paper. The GPC model outperforms the other models with a specificity of 95.78% to show that PSD can be used as an effective feature extraction technique for analyzing and classifying resting-state EEG signals of psychiatric disorders.

Bridging distances and saving costs: insights from a pilot project of telerheumatology in a rural area of Pakistan.

Enhancing access to healthcare remains a formidable challenge in rural regions of low- and lower-middle-income countries. Amid evolving healthcare challenges, telerheumatology provides opportunities to bridge gaps and expand access to rheumatology care, particularly in remote areas. We describe a pilot telerheumatology program and its cost-, time-, and travel-saving potential in a remote rural setting in northern Pakistan. The telerheumatology program commenced at the Pakistan Institute of Medical Sciences Islamabad, providing services through video consultations to a basic health unit in the Gilgit-Baltistan region. Patients visiting from the Gilgit-Baltistan region willing to participate were recruited in the program. Demographics and logistical metrics were recorded in a dedicated registry. A total of 533 consultations were carried out from April 2022 to April 2023. The majority of the patients were female (318/533, 59.7%). The median age of patients was 50 ± 15.7 years. The average wait time for consultation was 20 ± 13 min. The average travel time to reach telecentre was 59 ± 53 min. The average travel cost to reach telecentre was 379 ± 780 PKR (1.85 ± 3.81 USD). The average duration of consultation was 15 ± 5 min. The most common diagnosis for consultation was knee osteoarthritis (237, 44.5%), chronic low back pain (118, 22.1%), and rheumatoid arthritis (42, 7.9%). On average, patients saved 787 ± 29 km of distance, 15 ± 1 h of traveling, and 6702 ± 535 PKR (33 ± 3 USD) that would have been required to travel to our tertiary care hospital. Telerheumatology substantially reduced travel time, distance, and cost for patients. It has the potential to deliver outpatient rheumatology consultation in an economically efficient manner, effectively breaking geographical barriers and expanding access to essential services for patients in remote areas.

Exploring the effects of noise pollution on physiology and ptilochronology of birds.

Short and long-term sound-induced stress on daily basis can affect the physiology of avian individuals because they are more susceptible to sound stress in an open environment. OBJECTIVES: An ex-situ study was carried out to determine the impact of noise on physiology and ptilochronology of non-breeding male domesticated quail birds. METHODOLOGY: During 60-days long trial, male quail birds, aged 5-weeks, weighing (c.100gm) were used. Out of 72 experimental birds, 18 birds were assigned to the Control Group (G1) while remaining 54 birds were divided equally into 3 treatment groups: Road Traffic noise (G2), Military activity noise (G3) and Human Activities noise (G4). Birds were housed in standard-sized separate cages (20 ×45 × 20 cm), every bird was kept apart in separate cage in open laboratory under maintained environmental conditions. Millet seeds and water were provided to all the experimental birds ad libitum. Noise originated from several sources of recorded high-intensity music (1125 Hz/ 90 dB), was administered for 5-6 hours per day. Observations were recorded in the morning and afternoon. The experiment was conducted during the non-breeding season from August to October in triplicate. Blood sampling was done after 60 days. RESULTS: According to the current study, noise stress significantly (p<0.05) increased the concentrations of creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin, uric acid, cholesterol, triglycerides, total protein, and glucose while a decline in the levels of albumin was seen in treatment birds of G3. While in terms of hematology, total white blood cells count (TWBC), total red blood cells count (TRBC), mean cell volume (MCV) & packed cell volume (PCV) concentrations were raised in blood of treatment birds of G3. In terms of hormones, noise stress significantly (p<0.05) increased the serum concentrations of Corticosterone in G3 while a significant (p<0.05) decline was observed in the concentrations of luteinizing hormone (LH), thyroid stimulating hormone (TSH), and follicle stimulating hormone (FSH) in the same group. Moreover, fault bar formation in G3 was more prominent than others. CONCLUSION: Noise stress can significantly affect serology, hematology, hormonal physiology and ptilochronology in quail birds.

Consumption of proton pump inhibitors in outpatients of Gastroenterology Clinics in Khyber Pakhtunkhwa: evidence of inexpedient use.

Introduction: Proton pump inhibitors (PPIs) are effective drugs used for multiple gastrointestinal complications. They are commonly used in both hospitalised and outpatients. However, little is known about its utilisation pattern in ambulatory patients. Aim: To evaluate the inexpedient continuous use of PPIs in patients with respect to treatment duration. Material and methods: A cross-sectional observational study was conducted from January 2018 to November 2019 in Khyber Pakhtunkhwa, Pakistan. Regular proton pump inhibitor users were identified through patient histories. Results: During the study period, 171 patients were included using a non-probability consecutive sampling technique, who were using regular proton pump inhibitors for a longer duration, i.e. from 3 months to 15 years. The highest proportion (42.8%) were using PPI regularly from 3 months to 1 year followed by 22.9% for 1-2 years, 12.0% for 2-3 years, 7.8% for 3-4 years, 4.2% for 4-5 years, and 10.24% for > 5 years. Omeprazole and esomeprazole were the most commonly used drugs, with 71.1% and 23.5% prevalence, respectively. A total of 33.73% of patients had continued PPI use on their own after initially being prescribed by the physician. Conclusions: It can be deduced that PPIs are used in outpatients beyond standard treatment guidelines. The inexpedient continuous use of proton pump inhibitors is of concern due to the risk of developing adverse effects. Therefore, patient counselling and periodic monitoring must be carried out to prevent the irrational use of PPIs.

Multifaceted role of TRIM21 in inflammation.

Tripartite motif (TRIM) family members participate in a variety of cellular activities, such as intracellular signaling, development, cellular death, protein quality control, immunological defense, waste degradation, and the emergence of cancer. These proteins usually act as E3 ubiquitin ligase. The final line of resistance against infectious viruses is a cytosolic ubiquitin ligase and antibody receptor called TRIM containing 21. TRIM21, a protein with a tripartite structure, has been linked to autoimmune erythematosus, Sjogren's disorder, and innate immunity. TRIM21 may either promote the formation of specific cancer-activating proteins, resulting in their proteasomal degradation, or it may do neither, depending on the kind of cancer and cancer-causing trigger. The current research has shown that the antiviral action of TRIM mostly depends on their role as E3-ubiquitin ligases and a significant portion of the TRIM family mediates the transmission of innate immune cell signals and the subsequent production of cytokines. We highlighted the function of TRIM family members in various inflammatory diseases.

Localization and grading of NPDR lesions using ResNet-18-YOLOv8 model and informative features selection for DR classification based on transfer learning.

Complications in diabetes lead to diabetic retinopathy (DR) hence affecting the vision. Computerized methods performed a significant role in DR detection at the initial phase to cure vision loss. Therefore, a method is proposed in this study that consists of three models for localization, segmentation, and classification. A novel technique is designed with the combination of pre-trained ResNet-18 and YOLOv8 models based on the selection of optimum layers for the localization of DR lesions. The localized images are passed to the designed semantic segmentation model on selected layers and trained on optimized learning hyperparameters. The segmentation model performance is evaluated on the Grand-challenge IDRID segmentation dataset. The achieved results are computed in terms of mean IoU 0.95,0.94, 0.96, 0.94, and 0.95 on OD, SoftExs, HardExs, HAE, and MAs respectively. Another classification model is developed in which deep features are derived from the pre-trained Efficientnet-b0 model and optimized using a Genetic algorithm (GA) based on the selected parameters for grading of NPDR lesions. The proposed model achieved greater than 98 % accuracy which is superior to previous methods.

An idiopathic severe macroglossia in a young adult patient: a rare case.

Macroglossia, an uncommon anatomical anomaly, can manifest as either congenital or acquired. The size of the tongue undergoes variations with age, peaking at 8 years and reaching full maturity at 18 years. Congenital macroglossia stems from diverse conditions, such as muscular hypertrophy, hemangioma, lymphangioma, Down syndrome, and others. Acquired macroglossia can result from malignancies, endocrine and metabolic disorders, chronic infectious diseases, and head and neck infections, among other factors. Additionally, extended-prone surgery can lead to its development. The incidence of macroglossia is likely underreported. This presentation is rare with only six reported cases in the literature.

Review and Assessment of Material, Method, and Predictive Modeling for Fiber-Reinforced Polymer (FRP) Partially Confined Concrete Columns.

The repairing and strengthening of concrete structures using external and internal partial confinements are inevitable in the construction industry due to the new standards and rapid developments. The conventional materials and methods of confinement are unable to meet modern safety and functional standards. The fiber-reinforced polymer (FRP) enhances the strength and ductility of deteriorating and new concrete columns by reducing lateral confinement pressure and resistance against seismic shocks. The precise methods of partial confinement are inevitable for effective FRP-concrete bonding, durability, and cost-effectiveness under different loading conditions and to cope with external environmental factors. Predictive modeling and simulation techniques are pivotal for the optimization of confinement materials and methods by investigating the FRP-concrete novel confinement configurations, stress-strain responses, and failure modes. The novel materials and methods for concrete columns' partial confinement lack high compressive strength, ductility, chemical attack resistivity, and different fiber orientation impacts. This review provides an overview of recent confinement materials, novel methods, and advanced modeling and simulation techniques with a critical analysis of the research gaps for partial FRP confinement of concrete columns. The current challenges and future prospects are also presented.

Shining insights: Deciphering the biogenic synthesis of Ajuga bracteosa-mediated gold nanoparticles with advanced microscopy techniques.

In this study, gold nanoparticles (AuNPs) were bioreduced from Ajuga bracteosa, a medicinal herb known for its therapeutic properties against various diseases. Different fractions of the plant extract were used, including the methanolic fraction (ABMF), the n-hexane fraction (ABHF), the chloroform fraction (ABCF), and the aqueous extract for AuNPs synthesis. The characterization of AuNPs was performed using UV-Vis spectrophotometry, FT-IR, XRD, EDX, and TEM. UV-Vis spectroscopy confirmed the formation of AuNPs, with peaks observed at 555 nm. FT-IR analysis indicated strong capping of phytochemicals on the surface of AuNPs, which was supported by higher total phenolic contents (TPC) and total flavonoid contents (TFC) in AuNPs. XRD results showed high crystallinity and a smaller size distribution of AuNPs. TEM analysis revealed the spherical shape of AuNPs, with an average size of 29 ± 10 nm. The biologically synthesized AuNPs exhibited superior antibacterial, antioxidant, and cytotoxic activities compared to the plant extract fractions. The presence of active biomolecules in A. bracteosa, such as neoclerodan flavonol glycosides, diterpenoids, phytoecdysone, and iridoid glycosides, contributed to the enhanced biological activities of AuNPs. Overall, this research highlights the potential of A. bracteosa-derived AuNPs for various biomedical applications due to their remarkable therapeutic properties and effective capping by phytochemicals. RESEARCH HIGHLIGHTS: This research underscores the growing significance of herbal medicine in contemporary healthcare by exploring the therapeutic potential of Ajuga bracteosa and gold nanoparticles (AuNPs). The study highlights the notable efficacy of A. bracteosa leaf extracts and AuNPs in treating bacterial infections, demonstrating their bactericidal effects on a range of strains. The anti-inflammatory properties of plant extracts and nanoparticles are evidenced through paw edema method suggesting their applicability in managing inflammatory conditions. These findings position A. bracteosa and AuNPs as potential candidates for alternative and effective approaches to modern medication.

Novel frameless LINAC radiosurgery solution for uveal melanoma.

Introduction: Radiation treatment has replaced enucleation as an organ-preservation treatment for patients with uveal melanoma (UM). We developed a novel non-invasive, frameless LINAC based solution for fractionated stereotactic radiosurgery (fSRS) treatment. Methods: We designed and constructed the a stereotactic ocular localization box that can be attached and indexed to a stereotactic LINAC tabletop. It contains adjustable LED lights as a gaze focus point and CCD camera for monitoring of the patient's eye position. The device also has 6 infrared spheres compatible with the ExacTRAC IGRT system. Treatment plans were developed using iPLAN Dose version 4.5, with conformal dynamic arcs and 6MV photon beam in flattening filter free mode, dosed to 50Gy in 5 fractions. During treatment, patients were instructed to stare at the light when a radiation beam is prepared and ready for delivery. Eye movement was tracked throughout treatment. Residual setup errors were recorded for evaluation. Results: The stereotactic ocular localization box was 3D-printed with polylactic acid material and attached to the stereotactic LINAC tabletop. 10 patients were treated to evaluate the feasibility, tolerability and setup accuracy. Median treatment time for each arc is 17.3 ± 2.4 seconds (range: 13.8-23.4). After ExacTRAC setup, the residual setup errors are -0.1 ± 0.3 mm laterally, -0.1 ± 0.3 mm longitudinally, and 0 ± 0.2 mm vertically. The residue rotational errors are -0.1 ± 0.3 degree pitch, 0.1 ± 0.2 degree roll, and 0 ± 0.2 degree couch rotation. All patients received treatment successfully. Conclusion: We successfully developed a novel non-invasive frameless mask-based LINAC solution for SRS for uveal melanoma, or other ocular tumors. It is well tolerated with high set up accuracy. Future directions for this localization box would include a multi-center trial to assess the efficacy and reproducibility in the fabrication and execution of such a solution for UM therapy.

Hypertrophic Pachymeningitis: An Unusual Cause of Headache.

Hypertrophic pachymeningitis (HP) is a rare condition characterized by inflammation and thickening of the dura mater. It can be idiopathic or secondary to various causes, including infections, tumors, or systemic inflammatory diseases. Diagnosis is challenging due to its rarity and the overlap of symptoms with other conditions. We present the case of a 42-year-old Hispanic woman with diabetes mellitus type 2 and end-stage kidney disease who presented with chest pain, dry cough, mild dyspnea, and chronic occipital headaches. Physical examination revealed cranial VI nerve palsy. Imaging showed pulmonary cavitary lesions and mediastinal lymphadenopathy. Elevated inflammatory markers and positive autoimmune tests, including rheumatoid factor and antineutrophil cytoplasmic antibody (ANCA), led to further investigation. Brain imaging revealed dural thickening, confirming HP. The patient's medical history revealed double ANCA positivity and a lung biopsy confirmed granulomatous pneumonitis. A diagnosis of ANCA-associated vasculitis (granulomatosis with polyangiitis (GPA)) was established, and treatment with rituximab and high-dose corticosteroids led to symptom improvement. GPA rarely involves meningeal inflammation, but severe and persistent headaches are common early symptoms. Inflammatory markers are often elevated, and around two-thirds of HP cases related to GPA have positive serum ANCA. MRI is the primary diagnostic tool, with characteristic findings of dural thickening and contrast enhancement. This case highlights HP as a rare cause of chronic headaches and the importance of a comprehensive medical history in diagnosis. Early recognition and treatment are crucial for improving outcomes in GPA-related HP.

Up-scaling of fly ash-based geopolymer concrete to investigate the binary effect of locally available metakaolin with fly ash.

Owing to the increasing threat to environment due to the emission of greenhouse gases from cement industry globally, various promising solutions has been introduced in the past decades. The development of geoplymer concrete (GPC) is one of the contribution by the researches towards ecofriendly and sustainable construction. In this research, geopolymer concrete (GPC) is optimized by adding fixed amount of fly Ash (FA) and alkali activator to fine aggregate ratio as 0.5 with varying Molarity from 12 M to 16 M and Na2SiO3/NaOH ratio from 1.5 to 2.5. Physical and mechanical properties along with effect of heat and ambient curing conditions were investigated at various ages. The optimized mixture of fly ash based geopolymer concrete was then up scaled by blending with locally available Metakaolin (MK) with different dosages (i.e., 10%, 20%, 30%, 40%). The aim of the study is to identify the binary effect of FA and MK on overall performance of geopolymer concrete. Results showed that 30% FA-MK based GPC depicted 21%, 19% and 26% more compressive strength, split tensile strength and flexural strength respectively than Fly Ash based GPC alone at heat cured condition. This can be explained mainly due to two facts namely binary action of metakaolin that enhances compaction of GPC and pozzolanic activity of MK that expedite geopolymeric strength causing phases. The results were further verified by Modified Chapelle test and FTIR. Morphology of the developed GPC is also examined from SEM images. The work is an effort to utilize the fly ash produced by coal power plants to effectively address UN sustainable development goal related to sustainable cities and communities.

Clinically acquired new challenging dataset for brain SOL segmentation: AJBDS-2023.

Space-occupying lesions (SOL) brain detected on brain MRI are benign and malignant tumors. Several brain tumor segmentation algorithms have been developed but there is a need for a clinically acquired dataset that is used for real-time images. This research is done to facilitate reporting of MRI done for brain tumor detection by incorporating computer-aided detection. Another objective was to make reporting unbiased by decreasing inter-observer errors and expediting daily reporting sessions to decrease radiologists' workload. This is an experimental study. The proposed dataset contains clinically acquired multiplanar, multi-sequential MRI slices (MPMSI) which are used as input to the segmentation model without any preprocessing. The proposed AJBDS-2023 consists of 10667 images of real patients imaging data with a size of 320*320*3. Acquired images have T1W, TW2, Flair, T1W contrast, ADC, and DWI sequences. Pixel-based ground-truth annotated images of the tumor core and edema of 6334 slices are made manually under the supervision of a radiologist. Quantitative assessment of AJBDS-2023 images is done by a novel U-network on 4333 MRI slices. The diagnostic accuracy of our algorithm U-Net trained on AJBDS-2023 was 77.4 precision, 82.3 DSC, 87.4 specificity, 93.8 sensitivity, and 90.4 confidence interval. An experimental analysis of AJBDS-2023 done by the U-Net segmentation model proves that the proposed AJBDS-2023 dataset has images without preprocessing, which is more challenging and provides a more realistic platform for evaluation and analysis of newly developed algorithms in this domain and helps radiologists in MRI brain reporting more realistically.

Correction: Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

[This corrects the article DOI: 10.1371/journal.pone.0292601.].

Computer vision-based plants phenotyping: A comprehensive survey.

The increasing demand for food production due to the growing population is raising the need for more food-productive environments for plants. The genetic behavior of plant traits remains different in different growing environments. However, it is tedious and impossible to look after the individual plant component traits manually. Plant breeders need computer vision-based plant monitoring systems to analyze different plants' productivity and environmental suitability. It leads to performing feasible quantitative analysis, geometric analysis, and yield rate analysis of the plants. Many of the data collection methods have been used by plant breeders according to their needs. In the presented review, most of them are discussed with their corresponding challenges and limitations. Furthermore, the traditional approaches of segmentation and classification of plant phenotyping are also discussed. The data limitation problems and their currently adapted solutions in the computer vision aspect are highlighted, which somehow solve the problem but are not genuine. The available datasets and current issues are enlightened. The presented study covers the plants phenotyping problems, suggested solutions, and current challenges from data collection to classification steps.

A Holistic Strategy of Mother and Child Health Care to Improve the Coverage of Routine and Polio Immunization in Pakistan: Results from a Demonstration Project.

BACKGROUND: The eradication of poliovirus and improving routine immunization (RI) coverage rates present significant challenges in Pakistan. There is a need for interventions that focus on strengthening community engagement to improve routine immunization coverage. Our primary objective is to assess the impact of an integrated strategy designed to enhance community engagement and maternal and child health immunization campaigns on immunization coverage in Pakistan's high-risk union councils of polio-endemic districts. METHOD: We implemented an integrated approach for routine immunization and maternal and child health in the polio-endemic district of Pakistan. This approach involved setting up health camps and actively engaging and mobilizing the local community. An independent team conducted surveys at three key points: baseline, midline, and endline, to evaluate immunization coverage among children under the age of five. The primary outcome measures for the study were coverage of OPV, IPV, and changes in the proportion of unvaccinated and fully vaccinated children. To select clusters and eligible households in each cluster, we utilized a 30 × 15 cluster sampling technique. Multivariable associations between socio-demographic factors and changes in the proportion of fully vaccinated children at the UC level were assessed using hierarchical linear regression models. RESULTS: A total of 256,946 children under the age of five (122,950 at baseline and 133,996 at endline) were enrolled in the study. By the endline, full immunization coverage had increased to 60% or more in all three study areas compared to the baseline. Additionally, there was a significant increase in the coverage of both OPV and IPV across all three provinces at the endline. The full immunization rates were assessed on three levels of the framework: the distal, intermediate (access and environment), and proximal level (camp attendance and effectiveness). At the distal level, on multivariate analysis, family size was found to be a significant predictor of change in immunity within the families (ß = 0.68; p ≤ 0.0001). At the intermediate level, the likelihood of full immunization decreased with the decrease in knowledge about vaccination (ß = -0.38; p = 0.002), knowledge about polio vaccine (ß = -0.25; p = 0.011), and knowledge about IPV (ß = -0.06; p = 0.546). Perceived obstacles to vaccination were fear of adverse events (ß = -0.4; p ≤ 0.0001) and lack of education (ß = 0.23; p = 0.031), which were found to be significant in bivariate and multivariate analyses. At the proximal level, community mobilization (ß = 0.26; p = 0.008) and attendance at health camp (ß = 0.21; p ≤ 0.0001) were found to enhance full immunization coverage. On the other hand, the most prominent reason for not attending health camp included no need to attend the health camp as the child was not ill (ß = -0.13; p = 0.008). CONCLUSIONS: This study found that community mobilization and attendance at health camps significantly enhanced full immunization coverage. The findings highlight the importance of community engagement and targeted interventions in improving immunization coverage and addressing barriers to healthcare seeking.

Microscopic parasite malaria classification using best feature selection based on generalized normal distribution optimization.

Malaria disease can indeed be fatal if not identified and treated promptly. Due to advancements in the malaria diagnostic process, microscopy techniques are employed for blood cell analysis. Unfortunately, the diagnostic process of malaria via microscopy depends on microscopic skills. To overcome such issues, machine/deep learning algorithms can be proposed for more accurate and efficient detection of malaria. Therefore, a method is proposed for classifying malaria parasites that consist of three phases. The bilateral filter is applied to enhance image quality. After that shape-based and deep features are extracted. In shape-based pyramid histograms of oriented gradients (PHOG) features are derived with the dimension of N × 300. Deep features are derived from the residual network (ResNet)-50, and ResNet-18 at fully connected layers having the dimension of N × 1,000 respectively. The features obtained are fused serially, resulting in a dimensionality of N × 2,300. From this set, N × 498 features are chosen using the generalized normal distribution optimization (GNDO) method. The proposed method is accessed on a microscopic malarial parasite imaging dataset providing 99% classification accuracy which is better than as compared to recently published work.

Effects of long-term proton pump inhibitor use on sexual hormones and sexual and reproductive health in female patients.

PURPOSE: Proton pump inhibitors (PPIs) are widely used to treat a range of gastrointestinal diseases around the world. Long-term use of PPIs has been associated to a variety of undesirable effects. Although short-term therapy has been shown to have little or no effect on endocrine hormone in women, however, its long-term safety has received little attention. We aimed at evaluating long-term use of PPIs and its effects on female reproductive hormones as well as related clinical consequences. METHODS: A cross-sectional study was conducted in two outpatient gastroenterology clinics in the province of Khyber Pakhtunkhwa. This study included female patients who had been using PPIs on a regular basis for 3 months or more. RESULTS: In total of 101 participants, patients with sexual complaints have significantly altered levels of prolactin (p = 0.05), estrogen (p < 0.001) and progesterone (p = 0.001) than patient without sexual complaints. The frequency of amenorrhea (p < 0.001), cyclic disturbances (p < 0.001), breast augmentation (p = 0.001) and painful breast (p = 0.004) were statistically significant in patients with raised serum prolactin values. Serum values of Sex hormone binding globulin SHBG (p < 0.001), estradiol (p = 0.002) and total testosterone (p < 0.001) were significantly altered between normal prolactin and hyperprolactinemic patients. CONCLUSION: These findings suggest that long-term PPI use may cause endocrine hormone disturbances leading to sexual difficulties in women.