The Effect of Obesity on Severity of Asthma: An Observational Prospective Study from Pakistan.

Objective: The current research study aimed to access the relationship between obesity and asthma exacerbations and severity among adult patients at the outpatient section of a federal hospital (PIMS) in Islamabad, Pakistan. Methods: A cross-sectional research study was carried out on 207 asthma adult patients belonging to different areas and ethnic groups from the country. The study setting was the PIMS hospital, which attracts patients from all over the country due to its facilities and cost-effective treatments. The body mass index (BMI) of asthma patients was calculated using the heights and weights of the study subjects. However, the pulmonary functions were calculated using a computerized spirometer i-e Spirolab III S/N 303681 in line with Winspiro PRO 7.1.version software. It presents the patient's forced vital capacity that expires in the first second of expiration to full (FEV1) in comparison to forced vital capacity (FVC) ratio, that is, Tiffeneau-Pinelli index was also recorded to determine the asthma severity. Results: According to recent surveys, the overall prevalence of patients with overweight and obesity was 29.0% and 23.7%, respectively. A Chi-square test was used, and a statistically significant relationship was observed between BMI and asthma severity (P < 0.001). The adult obese female patients presented poor pulmonary functions. The average FEV1/FVC ratio presented significant variance among four different categories of BMI with P < 0.05. This difference was due to the normal BMI category as the Tiffeneau-Pinelli index, that is, FEV1/FVC in the normal BMI group was significantly lower as compared to that in underweight and obese patients. Conclusion: The study subjects presented raised asthma severity in accordance with the raised BMI. Obese patients presented comparatively raised asthma exacerbations. Moreover, a statistically significant association of gender difference was observed between obesity and asthma severity. It was concluded that adult asthmatic women with obesity presented raised asthma severity as compared to adult asthmatic males.

3D-Printed Conformal Meta-Lens with Multiple Beam-Shaping Functionalities for Mm-Wave Sensing Applications.

In this paper, a 3D conformal meta-lens designed for manipulating electromagnetic beams via height-to-phase control is proposed. The structure consists of a 40 × 20 array of tunable unit cells fabricated using 3D printing, enabling full 360° phase compensation. A novel automatic synthesizing method (ASM) with an integrated optimization process based on genetic algorithm (GA) is adopted here to create the meta-lens. Simulation using CST Microwave Studio and MATLAB reveals the antenna's beam deflection capability by adjusting phase compensations for each unit cell. Various beam scanning techniques are demonstrated, including single-beam, dual-beam generation, and orbital angular momentum (OAM) beam deflection at different angles of 0°, 10°, 15°, 25°, 30°, and 45°. A 3D-printed prototype of the dual-beam feature has been fabricated and measured for validation purposes, with good agreement between both simulation and measurement results, with small discrepancies due to 3D printing's low resolution and fabrication errors. This meta-lens shows promise for low-cost, high-gain beam deflection in mm-wave wireless communication systems, especially for sensing applications, with potential for wider 2D beam scanning and independent beam deflection enhancements.

Refining the correction factor for a better monitoring of antidepressant use by wastewater-based epidemiology: A case study of amitriptyline.

Wastewater-based epidemiology (WBE) is proposed as a cost-effective approach to objectively monitor the antidepressant use but it requires more accurate correction factors (CF) than what had been used in previous studies. Amitriptyline is a popular prescription medicine for treating depression and nerve pain, which could be prone to misuse and need monitoring. The CF of amitriptyline employed in previous WBE studies varied from 10 to 100, leading to substantial disparities between WBE estimates and expected mass of antidepressants in wastewater. Hence, this study aimed to take amitriptyline as a case study and refine the CF by correlating mass loads measured in wastewater from 12.2 million inhabitants collected during the 2016 Census with corresponding annual sales data. The triangulation of WBE data and sales data resulted in a newly-derived CF of 7, which is significantly different from the CF values used in previous studies. The newly derived CF was applied to a secondary, multi-year (2017 to 2020) WBE dataset for validation against sales data in the same period, demonstrating the estimated amitriptyline use (380 ± 320 mg/day/1000 inhabitants) is consistent with sales data (450 ± 190 mg/day/1000 inhabitants). When we applied the new CF to previous studies, the wastewater consumption loads matched better to prescription data than previous WBE estimations. The refined CF of amitriptyline can be used in future WBE studies to improve the accuracy of the consumption estimates.

An algorithm for standardization of tumor Infiltrating lymphocyte evaluation in head and neck cancers.

PURPOSE: The prognostic and predictive significance of pathologist-read tumor infiltrating lymphocytes (TILs) in head and neck cancers have been demonstrated through multiple studies over the years. TILs have not been broadly adopted clinically, perhaps due to substantial inter-observer variability. In this study, we developed a machine-based algorithm for TIL evaluation in head and neck cancers and validated its prognostic value in independent cohorts. EXPERIMENTAL DESIGN: A network classifier called NN3-17 was trained to identify and calculate tumor cells, lymphocytes, fibroblasts and "other" cells on hematoxylin-eosin stained sections using the QuPath software. These measurements were used to construct three predefined TIL variables. A retrospective collection of 154 head and neck squamous cell cancer cases was used as the discovery set to identify optimal association of TIL variables and survival. Two independent cohorts of 234 cases were used for validation. RESULTS: We found that electronic TIL variables were associated with favorable prognosis in both the HPV-positive and -negative cases. After adjusting for clinicopathologic factors, Cox regression analysis demonstrated that electronic total TILs% (p = 0.025) in the HPV-positive and electronic stromal TILs% (p < 0.001) in the HPV-negative population were independent markers of disease specific outcomes (disease free survival). CONCLUSIONS: Neural network TIL variables demonstrated independent prognostic value in validation cohorts of HPV-positive and HPV-negative head and neck cancers. These objective variables can be calculated by an open-source software and could be considered for testing in a prospective setting to assess potential clinical implications.

Identification of kidney stones in KUB X-ray images using VGG16 empowered with explainable artificial intelligence.

A kidney stone is a solid formation that can lead to kidney failure, severe pain, and reduced quality of life from urinary system blockages. While medical experts can interpret kidney-ureter-bladder (KUB) X-ray images, specific images pose challenges for human detection, requiring significant analysis time. Consequently, developing a detection system becomes crucial for accurately classifying KUB X-ray images. This article applies a transfer learning (TL) model with a pre-trained VGG16 empowered with explainable artificial intelligence (XAI) to establish a system that takes KUB X-ray images and accurately categorizes them as kidney stones or normal cases. The findings demonstrate that the model achieves a testing accuracy of 97.41% in identifying kidney stones or normal KUB X-rays in the dataset used. VGG16 model delivers highly accurate predictions but lacks fairness and explainability in their decision-making process. This study incorporates the Layer-Wise Relevance Propagation (LRP) technique, an explainable artificial intelligence (XAI) technique, to enhance the transparency and effectiveness of the model to address this concern. The XAI technique, specifically LRP, increases the model's fairness and transparency, facilitating human comprehension of the predictions. Consequently, XAI can play an important role in assisting doctors with the accurate identification of kidney stones, thereby facilitating the execution of effective treatment strategies.

The groundbreaking impact of digitalization and artificial intelligence in sheep farming.

The integration of digitalization and Artificial Intelligence (AI) has marked the onset of a new era of efficient sheep farming in multiple aspects ranging from the general well-being of sheep to advanced web-based management applications. The resultant improvement in sheep health and consequently better farming yield has already started to benefit both farmers and veterinarians. The predictive analytical models embedded with machine learning (giving sense to machines) has helped better decision-making and has enabled farmers to derive most out of their farms. This is evident in the ability of farmers to remotely monitor livestock health by wearable devices that keep track of animal vital signs and behaviour. Additionally, veterinarians now employ advanced AI-based diagnostics for efficient parasite detection and control. Overall, digitalization and AI have completely transformed traditional farming practices in livestock animals. However, there is a pressing need to optimize digital sheep farming, allowing sheep farmers to appreciate and adopt these innovative systems. To fill this gap, this review aims to provide available digital and AI-based systems designed to aid precision farming of sheep, offering an up-to-date understanding on the subject. Various contemporary techniques, such as sky shepherding, virtual fencing, advanced parasite detection, automated counting and behaviour tracking, anomaly detection, precision nutrition, breeding support, and several mobile-based management applications are currently being utilized in sheep farms and appear to be promising. Although artificial intelligence and machine learning may represent key features in the sustainable development of sheep farming, they present numerous challenges in application.

Corporate capital structure effects on corporate performance pursuing a strategy of innovation in manufacturing companies.

Within the sphere of finance, the concept of capital structure has long been a subject of intense debate, serving as a quantitative depiction of the balance between debt, preference shares, and common stock within a company. This structure serves a crucial role in optimizing the utilization of a company's existing resources while simultaneously elevating the revenue streams for stakeholders. This particular study delves into the intricate relationship between corporate performance and capital structure, focusing on 78 publicly listed firms within the Dhaka Stock Exchange (DSE). Bangladesh holds the 29th position globally in terms of purchasing power, lending significant weight to this investigation. To comprehensively analyze this correlation, panel data encompassing the span from 2017 to 2021 was collected for these 78 sample companies operating within the DSE. Several key determinants of capital structure were considered in this analysis, namely the debt-to-equity ratio, short-term leverage ratio, long-term leverage ratio, and total debt ratio. Meanwhile, the performance of these firms was gauged using key metrics such as Return on Assets (ROA), Return on Equity (ROE), and Earnings Per Share (EPS). To ensure a robust analysis, factors such as inflation, liquidity, growth rate, tax rate, and firm size were meticulously controlled for. The findings unveiled a compelling narrative: all forms of debt ratios-be it short-term, long-term, or the total debt ratio-exhibited a substantial negative impact on ROA at a significant level of 1 %. Conversely, specific debt ratios, like the short-term total debt and the total debt-to-total asset ratio, displayed a notable positive correlation with ROE at a 1 % significance level. Intriguingly, the long-term total debt ratio yielded a negative and insignificant effect on ROE. Moreover, within the spectrum of predictors influencing a firm's performance, the liquidity ratio emerged as a non-significant factor-a notable discovery that highlights the nuanced nature of the interplay between capital structure and performance within these companies.

Seroepidemiological and biomolecular survey on Toxoplasma gondii in Sardinian wild boar (Sus scrofa).

Toxoplasma gondii is a zoonotic parasite able of infecting all warm-blooded animals. Toxoplasmosis is one of the major foodborne diseases globally. The consumption of wild boar (Sus scrofa) meat from recreational hunting has been linked to outbreaks of human toxoplasmosis. The island of Sardinia (Italy) contains a large wild boar population, thus providing an opportunity to assess the distribution of Toxoplasma in this species and the associated risks of transmission to humans. A total of 562 wild boars were screened: heart and meat juice samples were tested for T. gondii DNA via nested-PCR and IgG anti-Toxoplasma by commercial ELISA. Anti-Toxoplasma IgG were detected in 24.6% (138/562) of animals, while 37.2% (209/562) of the heart samples were PCR positive. The prevalence of T. gondii antibodies and DNA highlights the potential role of wild boar as an important reservoir for this parasite. The study suggests that wild boar could play a significant role in spreading the parasite to humans. As wild boar numbers are increasing throughout their range, their potential role in transmitting toxoplasmosis should be communicated to stakeholders, and the impact of different population control methods on disease transmission should be thoroughly assessed to mitigate potential threats effectively.

Dyschromatosis symmetrica hereditaria: A clue to early diagnosis of Aicardi-Goutières syndrome.

A 6-year-old female with a history of Aicardi-Goutières syndrome (AGS) presented to dermatology clinic with hypopigmented and hyperpigmented macules and patches consistent with dyschromatosis symmetrica hereditaria (DSH). Previous genetic workup demonstrated a de novo, heterozygous mutation in the adenosine deaminase acting on RNA 1 (ADAR) gene. While the co-occurrence of AGS and DSH has previously been described in mutations of the ADAR gene, our case highlights the potential association between these disorders that may aid in earlier future diagnosis of AGS.

A conformal beam splitter with polarization transformation operation.

A multifunctional beam splitting frequency selective surface (FSS) is modeled, analyzed, and tested in transmission and reflection modes. The proposed FSS comprises a C-shaped split-ring resonator designed and fabricated on an ultrathin, flexible polyimide material. When a linearly polarized incident wave interacts with the unit cell of the proposed FSS, half of the wave is reflected, and the other half is transmitted at two frequency bands from 5.8-6.2 GHz and 18.5-22 GHz. Moreover, the proposed FSS is angularly stable upto 40° and also performs simultaneous beam splitting and quarter-wave operation within one of its two bands of operation i.e., from 16.5-18.2 GHz. Such flexible beam splitting FSSs with polarization transformation operation and having angular stability, size miniaturization and multi-band operation is a specialized component having potential to be used for electromagnetic wave manipulation in antenna systems, radar technology, stealth technology, wireless communication, satellite communication, medical imaging, security and surveillance, aerospace and defense, and automotive radar.

Awareness of undergraduate dental students, interns, and freshly graduated dentists about oral manifestation associated with COVID-19.

OBJECTIVE: There is growing evidence supporting the presence of oral manifestations associated with COVID-19. The study investigates the knowledge of dental undergraduates and recently graduated dentists concerning oral presentations related to COVID-19. METHODS: A cross-sectional descriptive study in Saudi Arabia comprised 305 individuals, including undergraduate dental students, interns, and freshly graduated dentists. Data were collected using a questionnaire disseminated to approximately 500 subjects via WhatsApp groups and other applications. The questionnaire was tested in a pilot study for validity, edited, and validated by 2 supervisors at the College of Dentistry, Qassim University, Buraydah, Saudi Arabia. The questionnaire consisted of questions regarding sociodemographic attributes, the level of expertise of dental practitioners, and their knowledge and perspectives regarding COVID-19 and the implementation of oral lesions interrelated to it. The data was subjected to analysis through the utilization of descriptive statistics and chi-square tests, employing the statistical software SPSS (version 24). RESULTS: About 43.9% of subjects stated that COVID-19 causes oral symptoms. Respondents most frequently reported COVID-19-related dry mouth. Oral ulcers, Candida infection, Hyperpigmentation, tongue coating, atrophy, Petechiae, Herpes, white lesions, Gingivitis, and Periodontitis are further symptoms. COVID-19's oral manifestation was unknown to 41.0% of subjects, and 37.7% of respondents lacked knowledge regarding the most impacted locations of oral manifestations. Oral signs and COVID-19 symptoms are debated and significantly associated with higher educational levels. CONCLUSION: The dental students and freshly graduated dentists in this study have proper knowledge of COVID-19 and its symptoms. Also, most dental students and newly graduated dentists recognize the potential correlation between COVID-19 and oral manifestations with an average to excellent knowledge of the types and sites commonly affected. The level of awareness was associated with higher educational levels.

Lithium Monotherapy in Graves Thyrotoxicosis.

Lithium is not commonly used to treat thyrotoxicosis, and there are few reports in the literature of its use as initial therapy in thyrotoxicosis. We describe the case of a patient with Graves thyrotoxicosis and ophthalmopathy, on a background of autoimmune neutropenia, treated successfully with relatively long-term lithium monotherapy. Lithium was used at a lower dose and longer duration than previously reported on, to good effect. We demonstrate that lithium is an important and useful option for those who are unable to tolerate thionamide therapy.

Reconfigurable absorptive and polarization conversion metasurface consistent for wide angles of incidence.

In this paper, a single-layer reconfigurable reflective metasurface is presented. The proposed metasurface operates at 5.4 GHz and can achieve either absorption or cross-polarization conversion corresponding at two different diode biasing states. The reflective metasurface acts as an absorber for an incident wave when the diodes are forward-biased. Similarly, it changes the polarization state of the reflected wave for a linearly polarized incident wave when the diodes are reverse-biased. The proposed structure maintains the aforementioned performance characteristics for oblique incidence, up to 60° compared to the perpendicular incidence. The proposed metasurface can achieve linear to linear polarization conversion with polarization conversion ratio (PCR) > 95% and absorption, with absorption ratio (AR) > 80% in the same frequency band just by reconfiguring the state of the PIN diodes.

Impact of UV Modifying Factors on the Incidence of Keratinocyte Carcinomas in Solid Organ Transplant Recipients: A Systematic Review.

INTRODUCTION: Solid organ transplant recipients (SOTR) are at an increased risk for developing keratinocyte carcinomas (KC). Four ultraviolet (UV) modifying factors have been identified that impact the incidence of KC: Fitzpatrick Skin Type (FST), race, sun exposure, and sun-protective factors. OBJECTIVES: We conducted a systematic review to summarize the association between UV modifying factors and the incidence of KC in SOTR. METHODS: We systematically searched PubMed, Scopus, and Web of Science databases, and after screening for inclusion and exclusion criteria, we included 13 studies with 6,910 solid organ transplant recipients in our analysis. RESULTS: Our review found that lower FST (I-II), white and Latinx populations, lack of regulated sunscreen application, and occupational and residential sun exposure are individual risk factors among solid organ transplant recipients for KC incidence. Although previous studies showed an in-creased SCC:BCC ratio, some studies found a contradictory increased BCC:SCC ratio. Limitations include few research studies that analyze these UV modifying factors and a lack of incorporating both varying immunosuppressant factors and transplantation follow-up times. CONCLUSIONS: These findings support the need for dermatological advice in increased risk patient demographic populations, lower FST and white and Latinx populations, and subsequently moderating sun exposure and protective factors.

Integrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality.

BACKGROUND: Colorectal cancers are the fourth most diagnosed cancer and the second leading cancer in number of deaths. Many clinical variables, pathological features, and genomic signatures are associated with patient risk, but reliable patient stratification in the clinic remains a challenging task. Here we assess how image, clinical, and genomic features can be combined to predict risk. METHODS: We developed and evaluated integrative deep learning models combining formalin-fixed, paraffin-embedded (FFPE) whole slide images (WSIs), clinical variables, and mutation signatures to stratify colon adenocarcinoma (COAD) patients based on their risk of mortality. Our models were trained using a dataset of 108 patients from The Cancer Genome Atlas (TCGA), and were externally validated on newly generated dataset from Wayne State University (WSU) of 123 COAD patients and rectal adenocarcinoma (READ) patients in TCGA (N = 52). FINDINGS: We first observe that deep learning models trained on FFPE WSIs of TCGA-COAD separate high-risk (OS < 3 years, N = 38) and low-risk (OS > 5 years, N = 25) patients (AUC = 0.81 ± 0.08, 5 year survival p < 0.0001, 5 year relative risk = 1.83 ± 0.04) though such models are less effective at predicting overall survival (OS) for moderate-risk (3 years < OS < 5 years, N = 45) patients (5 year survival p-value = 0.5, 5 year relative risk = 1.05 ± 0.09). We find that our integrative models combining WSIs, clinical variables, and mutation signatures can improve patient stratification for moderate-risk patients (5 year survival p < 0.0001, 5 year relative risk = 1.87 ± 0.07). Our integrative model combining image and clinical variables is also effective on an independent pathology dataset (WSU-COAD, N = 123) generated by our team (5 year survival p < 0.0001, 5 year relative risk = 1.52 ± 0.08), and the TCGA-READ data (5 year survival p < 0.0001, 5 year relative risk = 1.18 ± 0.17). Our multicenter integrative image and clinical model trained on combined TCGA-COAD and WSU-COAD is effective in predicting risk on TCGA-READ (5 year survival p < 0.0001, 5 year relative risk = 1.82 ± 0.13) data. Pathologist review of image-based heatmaps suggests that nuclear size pleomorphism, intense cellularity, and abnormal structures are associated with high-risk, while low-risk regions have more regular and small cells. Quantitative analysis shows high cellularity, high ratios of tumor cells, large tumor nuclei, and low immune infiltration are indicators of high-risk tiles. INTERPRETATION: The improved stratification of colorectal cancer patients from our computational methods can be beneficial for treatment plans and enrollment of patients in clinical trials. FUNDING: This study was supported by the National Cancer Institutes (Grant No. R01CA230031 and P30CA034196). The funders had no roles in study design, data collection and analysis or preparation of the manuscript.

Coronavirus pandemic in the South Asia region: Health policy and economy trade-off.

Background: The South Asian Association for Regional Cooperation (SAARC) covers Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. We conducted a comparative analysis of the trade-off between the health policies for the prevention of COVID-19 spread and the impact of these policies on the economies and livelihoods of the South Asia populations. Methods: We analyzed COVID-19 data on epidemiology, public health and health policy, health system capacity, and macroeconomic indicators from January 2020 to March 2021 to determine temporal trends by conducting joinpoint regression analysis using average weekly percent change (AWPC). Results: Bangladesh had the highest statistically significant AWPC for new COVID-19 cases (17.0; 95% CI = 7.7-27.1, P < 0.001), followed by the Maldives (12.9; 95% CI = 5.3-21.0, P < 0.001) and India (10.0; 95% CI = 8.4-11.5, P < 0.001). The AWPC for COVID-19 deaths was significant for India (6.5; 95% CI = 4.3-8.9, P < 0.001) and Bangladesh (6.1; 95% CI = 3.7-8.5, P < 0.001). Nepal (55.79%), and India (34.91%) had the second- and third-highest increase in unemployment, while Afghanistan (6.83%) and Pakistan (16.83%) had the lowest. The rate of change of real GDP had the highest decrease for Maldives (557.51%), and India (297.03%); Pakistan (46.46%) and Bangladesh (70.80%), however, had the lowest decrease. The government response stringency index for Pakistan had a see-saw pattern with a sharp decline followed by an increase in the government health policy restrictions that approximated the test-positivity trend. Conclusions: Unlike developed economies, the South Asian developing countries experienced a trade-off between health policy and their economies during the COVID-19 pandemic. South Asian countries (Nepal and India), with extended periods of lockdowns and a mismatch between temporal trends of government response stringency index and the test-positivity or disease incidence, had higher adverse economic effects, unemployment, and burden of COVID-19. Pakistan demonstrated targeted lockdowns with a rapid see-saw pattern of government health policy response that approximated the test-positivity trend and resulted in lesser adverse economic effects, unemployment, and burden of COVID-19.

Communication and information sharing with pediatric patients including refugees with advanced cancer, their caregivers, and health care professionals in Jordan: a qualitative study.

Introduction: Effective communication in pediatric palliative cancer care is an important aspect of practice to enhance patient- and family-centered care, and to optimize decision-making. However, little is known about communication preferences practices from the perspectives of children, caregivers and their health care professionals (HCPs) in the Middle Eastern region. Furthermore, involving children in research is crucial but limited. This study aimed to describe the communication and information-sharing preferences and practices of children with advanced cancer, their caregivers, and health care professionals in Jordan. Methods: A qualitative cross-sectional study was conducted using semi-structured face to face interviews with three groups of stakeholders (children, caregivers and HCPs). Purposive sampling recruited a diverse sample from inpatient and outpatient settings at a tertiary cancer center in Jordan. Procedures were in line with the Consolidated criteria for reporting qualitative research (COREQ) reporting guidelines. Verbatim transcripts were thematically analyzed. Findings: Fifty-two stakeholders participated: 43 Jordanian and 9 refugees (25 children, 15 caregivers and 12 HCPs). Four major themes emerged: 1) Hiding information between the three stakeholders which includes parents who hide the information from their sick children and ask the HCPs to do so to protect the child from distressful emotions and children who hide their suffering from their parents to protect them from being sad; 2) Communication and sharing of clinical versus non-clinical information; 3) Preferred communication styles such as use of a companionate approach by acknowledging patients and caregivers' suffering, building a trustful relationship, proactive information sharing, considering child age and medical status, parents as facilitators in communication, and patients' and caregivers' health literacy; 4) Communication and information sharing with refugees where they had dialect issues, which hindered effective communication. Some refugees had unrealistically high expectations regarding their child's care and prognosis, which posed challenges to communication with staff. Discussion: The novel findings of this study should inform better child-centered practices and better engage them in their care decisions. This study has demonstrated children's ability to engage in primary research and to express preferences, and parents' ability to share views on this sensitive topic.