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Colorectal cancer (CRC) is considered as the third most frequent cancer in the world and the incidence increases with increasing age. CRC accounts for nearly 9 % of all cancer incidence, with an estimated 1.4 million cases happening in 2012. The aim of this paper is to provide a review of incidence, risk factors, screening strategies, and treatment of colorectal cancer. We searched the studies in five English databases, including Web of Science, PubMed, Scopus, EMBASE, and Google Scholar with no limitation in publication time to find all papers regarding colorectal cancers. Papers with any language were included in the first step of search if they had an English abstract. We used the following words and terms including colorectal cancer, treatment, risk factor, diagnosis, chemotherapy, radiotherapy, surgery. Geographical variations and different time courses in the CRC incidence indicate that environmental factors and lifestyle are major factors in the development of this disease. The main preventable risk factors for CRC are nutrition, a high-fat diet, a low-fiber diet, obesity and physical inactivity, smoking and alcohol consumption, aspirin and nonsteroidal anti-inflammatory drugs, and some non-preventable risk factors such as age, gender, race, and diabetes mellitus. Colonoscopy remains the study of choice to diagnose colorectal cancer. Prior to any treatment, CT imaging of chest, abdomen and pelvis with contrast is needed for staging the patient’s CRC. The preferred option for localized colorectal cancer is surgery (etc, laparoscopic surgery, colostomy for rectal cancer); whereas the adjuvant chemotherapy is generally recommended for patients with lymph node metastases. Targeted treatment of colorectal cancer by monoclonal antibodies are important bioengineered proteins that can help the body's natural immune response to detect, attack, and kill cancer cells. Monoclonal antibodies may be used alone or in combination with other treatments such as chemotherapy. CRC accounts an important health problem worldwide that is estimated to increase because of the growth and aging of the population, and because of the adoption of at-risk manners and lifestyles, particularly in economically less developed countries. Screening has been confirmed to significantly decrease mortality and can prevent the onset of the disease. More international efforts are required to situate into practice targeted prevention approaches that might reduce the burden of CRC worldwide.

Guillain-Barré syndrome (GBS) is an acute immunemediated polyradiculoneuropathy with a highly variable clinical course and outcome. Intravenous immunoglobulin (IVIG) and plasma exchange (PE) are proven effective treatments, but about half of the patients may not respond to these therapies; moreover, these are not established yet to treat patients of every stage of GBS or its variants. Results from the International Guillain-Barré Syndrome Outcome Study suggest that geographical variations exist in Guillain-Barré syndrome, including insufficient access to immunotherapy in low-income countries. There is a need to provide improved access to treatment for all patients with Guillain-Barré syndrome, and to develop effective disease-modifying therapies that can limit the extent of nerve injury. In this review, the current literature about immunotherapeutic options is highlighted in the context of stages of the disease and its variants and additionally, upcoming modalities are discussed briefly. J Bangladesh Coll Phys Surg 2022; 40: 57-64

Abstract Background People with liver disease are at increased risk of developing cardiovascular disease (CVD), however, there has yet been an investigation of incidence burden, risk, and premature mortality across a wide range of liver conditions and cardiovascular outcomes. Methods We employed population-wide electronic health records (EHRs; from 1998 to 2020) consisting of almost 4 million adults to assess regional variations in disease burden of five liver conditions, alcoholic liver disease (ALD), autoimmune liver disease, chronic hepatitis B infection (HBV), chronic hepatitis C infection (HCV) and NAFLD, in England. We analysed regional differences in incidence rates for 17 manifestations of CVD in people with or without liver disease. The associations between biomarkers and comorbidities and risk of CVD in patients with liver disease were estimated using Cox models. For each liver condition, we estimated excess years of life lost (YLL) attributable to CVD (i.e., difference in YLL between people with or without CVD). Results The age-standardised incidence rate for any liver disease was 114.5 per 100,000 person years. The highest incidence was observed in NAFLD (85.5), followed by ALD (24.7), HCV (6.0), HBV (4.1) and autoimmune liver disease (3.7). Regionally, the North West and North East regions consistently exhibited high incidence burden. Age-specific incidence rate analyses revealed that the peak incidence for liver disease of non-viral aetiology is reached in individuals aged 50–59 years. Patients with liver disease had a two-fold higher incidence burden of CVD (2634.6 per 100,000 persons) compared to individuals without liver disease (1339.7 per 100,000 persons). When comparing across liver diseases, atrial fibrillation was the most common initial CVD presentation while hypertrophic cardiomyopathy was the least common. We noted strong positive associations between body mass index and current smoking and risk of CVD. Patients who also had diabetes, hypertension, proteinuric kidney disease, chronic kidney disease, diverticular disease and gastro-oesophageal reflex disorders had a higher risk of CVD, as do patients with low albumin, raised C-reactive protein and raised International Normalized Ratio levels. All types of CVD were associated with shorter life expectancies. When evaluating excess YLLs by age of CVD onset and by liver disease type, differences in YLLs, when comparing across CVD types, were more pronounced at younger ages. Conclusions We developed a public online app (https://lailab.shinyapps.io/cvd_in_liver_disease/) to showcase results interactively. We provide a blueprint that revealed previously underappreciated clinical factors related to the risk of CVD, which differed in the magnitude of effects across liver diseases. We found significant geographical variations in the burden of liver disease and CVD, highlighting the need to devise local solutions. Targeted policies and regional initiatives addressing underserved communities might help improve equity of access to CVD screening and treatment.

Purpose This study aims to critically review the research on the phenomenon of discrimination in hospitality and tourism services to identify the key thematic areas, scenarios, antecedents and consequences; to provide theoretical propositions for future research; and to propose practical strategies to reduce discrimination and to improve equality in the field. Design/methodology/approach This paper adopts the preferred reporting items for systematic reviews and meta-analyses guidelines to collect relevant academic work on discrimination in hospitality and tourism services from 1985 to 2020 and critically reviews and analyses the studies through bibliometric analysis, content analysis and critical analysis. Findings The findings show that the main sources of discrimination in hospitality and tourism services include sexism, racism, ethnocentrism, lookism and ego-altruism. Discrimination-related research has temporal and geographical variations. A research map is proposed to present existing knowledge of discrimination in hospitality and tourism services, which indicates that while the impacts (at the individual, organizational and institutional levels) of discrimination in hospitality and tourism services have been thoroughly researched, the nature and characteristics of the phenomenon remain context-based and poorly conceptualized. Practical implications An anti-discrimination guideline for hospitality and tourism practitioners is designed to cope with and eliminate discriminatory situations. This evidence-based guideline provides useful coping strategies based on the prevent–monitor–manage principle. Originality/value This paper is comprehensive in its scope, methodology and wide coverage of discrimination-related research in hospitality and tourism services. It is the first attempt to review this phenomenon in the existing literature and identifies the research gaps and future research agendas.

Cerebrovascular accidents (CVA) or stroke has been a global phenomenon that causes disability and deaths of people worldwide, particularly in the middle- and low-income countries. It has been reported that more than 100,000 cases are recorded every year in Nigeria. Moreover, several deaths were reported globally by the World Health Organization (WHO). Diagnostic tools, preventive measures, and medical experts are insufficient and contribute to the escalation of the disease worldwide. Several predictive models have been proposed by scholars but have been inadequate due to variability in the risk factors, race, and geographical variations. This paper compared six machine learning-based models with three feature selection algorithms on a Nigerian dataset containing 103 instances with 22 features. We trained and evaluated the NB, SVM, LR, MLP, J-48, and RF with CBFS, CAE FS, and Relief FS algorithms. The results of our experiments showed that the J-48 model with the CBFS algorithm was computationally faster and achieved an excellent prediction accuracy of 100.00% in 0.00 seconds. The type of data used has a substantial impact on the performance of machine learning classifiers. Therefore, based on the experiments performed, J-48 with CBFS algorithm was proposed for deployment as the clinical decision support system that could assist medical professionals in predicting cerebrovascular diseases.

Elemental profiles are frequently applied to identify the geographical origin and authenticity of food products, to guarantee quality. The concentrations of fifteen major, minor, and trace elements (Na, Mg, K, Ca, Al, Fe, Mn, Cu, Zn, Rb, Sr, Li, Cd, Cs, and Ba) were determined in soils, “Meili” grapes, and wines from six regions in China by inductively coupled plasma mass spectrometry (ICP-MS). The elemental concentrations in these samples, according to the geographical origins, were analyzed by one-way analysis of variance (ANOVA) with Duncan’s multiple comparisons. The bioconcentration factor (BCF) from soil to grape and the transfer factor (TF) from grape to wine were calculated. Mg, K, Ca, Cu, Zn, Rb, Sr, and Ba presented higher BCF values than the other seven elements. The TF values of six elements (Na, Mg, K, Zn, Li, and Cs) were found to be greater than one. Moreover, the correlation of element content between the pairs of soil–grape, grape–wine, and bioconcentration factor (BCF)–environmental factor were analyzed. Significant correspondences among soil, grape, and wine were observed for K and Li. Two elements (Sr and Li) showed significant correlations between BCF and environmental factor (relative humidity, temperature, and latitude). A linear discriminant analysis (LDA) with three variables (K, Sr, Li) revealed a high accuracy (>90%) to determine the geographical origin for different Chinese regions.

Abstract India is a hotspot of the COVID-19 crisis. During the first wave several lockdowns (L) and gradual unlock (UL) phases were implemented by the Government of India (GOI) to curb the virus spread. Twitter, a social media platform, was extensively used by citizens to react to various events and topics related to resource management and virus spread that varied geographically. This paper attempts to capture those variations by analyzing the sentiments of geotagged tweets during L and UL phases, which remains a research gap. The sentiments were predicted through a proposed hybrid Deep Learning (DL) model which leverages the strengths of BiLSTM and CNN model classes. The model was trained on a freely available Sentiment140 dataset and was tested over manually annotated COVID-19 related tweets from India. The model classified the tweets with high accuracy of around 90%, and analysis of geotagged tweets during L and UL phases reveal significant geographical variations. The findings can aid decision-makers in analyzing citizen reactions toward the resources and events during an ongoing pandemic, which can result in better resource planning.

AbstractBreast cancer is a public health challenge globally as well as in India. Improving outcome and cure requires appropriate biomarker testing to assign risk and plan treatment. Because it is documented that significant ethnic and geographical variations in biological and genetic features exist worldwide, such biomarkers need to be validated and approved by authorities in the region where these are intended to be used. The use of western guidelines, appropriate for the Caucasian population, can lead to inappropriate overtreatment or undertreatment in Asia and India. A virtual meeting of domain experts discussed the published literature, real-world practical experience, and results of opinion poll involving 185 oncologists treating breast cancer across 58 cities of India. They arrived at a practical consensus recommendation statement to guide community oncologists in the management of hormone positive (HR-positive) Her2-negative early breast cancer (EBC). India has a majority (about 50%) of breast cancer patients who are diagnosed in the premenopausal stage (less than 50 years of age). The only currently available predictive test for HR-positive Her2-negative EBC that has been validated in Indian patients is CanAssist Breast. If this test gives a score indicative of low risk (< 15.5), adjuvant chemotherapy will not increase the chance of metastasis-free survival and should not be given. This is applicable even during the ongoing COVID-19 pandemic.