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Abstract PHY34 is a synthetic small molecule, inspired by a compound naturally occurring in tropical plants of the Phyllanthus genus. PHY34 was developed to have potent in vitro and in vivo anticancer activity against high grade serous ovarian cancer (HGSOC) cells. Mechanistically, PHY34 induced apoptosis in ovarian cancer cells by late-stage autophagy inhibition. Furthermore, PHY34 significantly reduced tumor burden in a xenograft model of ovarian cancer. In order to identify its molecular target/s, we undertook an unbiased approach utilizing mass spectrometry-based chemoproteomics. Protein targets from the nucleocytoplasmic transport pathway were identified from the pulldown assay with the cellular apoptosis susceptibility (CAS) protein, also known as CSE1L, representing a likely candidate protein. A tumor microarray confirmed data from mRNA expression data in public databases that CAS expression was elevated in HGSOC and correlated with worse clinical outcomes. Overexpression of CAS reduced PHY34 induced apoptosis in ovarian cancer cells based on PARP cleavage and Annexin V staining. Compounds with a diphyllin structure similar to PHY34 have been shown to inhibit the ATP6V0A2 subunit of V(vacuolar)-ATPase. Therefore, ATP6V0A2 wild-type and ATP6V0A2 V823 mutant cell lines were tested with PHY34, and it was able to induce cell death in the wild-type at 246 pM while the mutant cells were resistant up to 55.46 nM. Overall, our data demonstrate that PHY34 is a promising small molecule for cancer therapy that targets the ATP6V0A2 subunit to induce autophagy inhibition while interacting with CAS and altering nuclear localization of proteins.

In Sri Lankan advanced level mathematics curriculum, teachers are required only to provide the intuitive idea of the concept of limit. The purpose of this study is to explore the strategies used by mathematics teachers to achieve this. Twelve in-service secondary mathematics teachers working in government and private schools participated in the study. Data was collected through lesson observations and field notes. Video recorded lessons were transcribed and qualitatively analyzed. Teaching-With-Analogy model was used as a guiding framework to evaluate how teachers integrate real-life examples in classrooms. The analysis revealed few appealing approaches as well as various flaws and misconceptions. In fact, seven teachers took deliberate efforts to link the concept to real-life and among them, four teachers gave an intuition on how x approaches a specific value, through real-life scenarios. However, many were not successful in mapping features of the real-life example to the features of the concept. Few teachers superficially and negligently applied irrelevant metaphors, analogies and colloquial terms. There were gaps in teacher knowledge when incorporating real-life connections to the limit concept. We emphasize the importance of teachers being mindful when using real-life examples in fostering intuition since inappropriate choices of examples could contribute to misconceptions.

Niemann-Pick disease, type C1 (NPC1) is a rare, autosomal recessive, lipid storage disorder caused by mutations in NPC1. As a result, there is accumulation of unesterified cholesterol and sphingolipids in the late endosomal/lysosomal system. Clinically, patients can present with splenomegaly and hepatomegaly. In the current study, we analyzed the differential proteome of the spleen in symptomatic Npc1−/− mice to complement previous studies focused on the differential proteome of the liver, and then evaluated biomolecules that may serve as tissue biomarkers. The proteomic analysis revealed altered pathways in NPC1 representing different functional categories including heme synthesis, cellular regulation and phosphoinositide metabolism in both tissues. Differential proteins included several activators of the ubiquitous and critical protein, Akt, a major kinase involved in multiple cellular processes. Evaluation of Akt revealed decreased expression in both the liver and spleen tissues of symptomatic Npc1−/− mice. Upstream regulation analysis also suggested that miR-155 may modulate the differences of known downstream protein targets observed in our dataset. Upon evaluation of miR-155, we observed an increased expression in the liver and decreased expression in the spleen of symptomatic Npc1−/− mice. Here, we propose that miR-155 may be a novel indicator of spleen and liver pathology in NPC1.

Background Even if promoting antenatal exercises is an evolving concept worldwide, there is a scarcity of qualitative exploratory studies which directly focus on pregnant mothers’ views about exercises. So, this study was designed to (1) explore pregnant women’s perceptions, attitudes and beliefs about antenatal exercises, and (2) provide significant annotations prior to constituting interventions for antenatal exercises.Methods A qualitative survey was carried out with 19 primiparous pregnant women using stratified purposive sampling at the antenatal clinic, in a tertiary care hospital, Sri Lanka. In-depth interviews were conducted through a predesigned, semistructured interview guide from January to April 2021. Data were transcribed, examined and organised, then subjected to thematic analysis using inductive approach.Results Most of the pregnant women described numerous benefits and had optimistic views on exercises. However, the absence of a comprehensive understanding on the impact of exercise on a healthy pregnancy is apparent, primarily caused by a dearth of health education and reliable information sources. Also, they were unlikely to initiate exercises in their pregnancy period due to a lack of guidance through the antenatal clinic and/or health professionals. Concerning beliefs, main stream-believed exercises provide assistance for normal labour process and exercises advantageous in both antenatal and post-partum periods. Besides, few of them restricted their conversations on the drawbacks of exercises by illuminating erroneous beliefs.Conclusions The majority of participants realised the importance of exercises and had positive attitudes while the minority presenting misconceptions. The need for healthcare providers’ support and guidance is highly anticipated by pregnant women to engage in antenatal exercises.

Abstract The rapid expansion of artificial intelligence (AI) across various fields has significantly impacted how individuals construct and present their identities, particularly on social media. This brief communication explains the concept of digital twinning within the public sphere, where AI-generated images create virtual twins. We examine the phenomenon of attachment to AI-generated self-image, proposing that a perceived sense of emptiness predicts attachment to AI-generated self-image. Using the empty self-theory as a theoretical foundation, we argue that individuals experiencing feelings of emptiness are more likely to form deep emotional bonds with their AI-generated self-image. They may find solace by associating their sense of emptiness with AI-generated self-images, similar to idealised images in advertising. This attachment can manifest as either subjective, where users believe the AI-generated image truly represents them, or objective, where the image is seen as a possession. In future research, it would be valuable to investigate the various factors that contribute to an individual's inclination to form an attachment to AI-generated self-images. Deep exploration of the difference between objective and subjective attachment and quantifying this proposed relationship through empirical studies could provide valuable insights into the interplay between technology and human psychology.

Abstract Objective Falls take a high priority among the prevalent medical conditions in old age. Despite this, a history of falls or the risk of future falls is not routinely assessed or properly managed in medical clinics in Sri Lanka. This study was done to evaluate the prevalence and factors associated with falls and recurrent falls among older adults attending medical clinics in four selected tertiary care centres in the country. Methods A cross-sectional study was carried out at four centres (Teaching Hospital Karapitiya, Colombo South Teaching Hospital, Colombo North Teaching Hospital and University Hospital-Kotelawala Defence University) with 704 older adults, aged 65 years and above, attending medical clinics for more than six consecutive months. Information related to falls and possible associated factors (socio-demographic, behavioural, environmental and biological) were collected using an interviewer-administered questionnaire. Results The Mean (SD) age of the participants was 72.5(5.5) years and 58.7% were females. Of the 704 total sample, 220 (31.3%, 95% CI 28–35%) participants experienced at least one fall after the age of 65, and 12.8% (95% CI 10–15%) (n = 90) experienced recurrent falls (two or more falls within the last 12 months). Falls were associated with gender, level of education, marital status, and physical dependence (p

Abstract Background Informal carers face difficulties and challenges when dealing with the behavioural and psychological symptoms of dementia (BPSD) of their family members or friends residing at home. Mobile health (mHealth) applications are promising for educating and supporting carers. However, needs analysis studies have not been conducted in Sri Lanka to develop mHealth applications for informal carers of people with dementia. Aims To explore the needs to design an mHealth application for informal carers of people with dementia concerning the management of BPSD. Method An exploratory cross-sectional survey was conducted among a convenience sample (N = 203) of informal carers as a part of developing an mHealth application. Family members, relatives, or friends who lived with people with dementia and provided care on an unpaid basis for more than three months were included. The questionnaire included sociodemographic data, carer-rated prevalence and severity of BPSD, and informal carers’ knowledge of dementia, carer burden, information-seeking sources, availability of smartphones, mHealth information seeking and perception of mHealth information seeking related to managing BPSD. Descriptive analysis and inferential tests were performed. Results Informal carers of people with dementia were predominantly female (70.4%), and 64% showed low knowledge of dementia. Of the participants, 35% reported a high carer burden, 53.7% reported a low burden, and only 11.3% reported no carer burden. Most of their care recipients (97%) had at least one BPSD. The prevalence and severity of BPSD were significantly and positively correlated with the carer burden. The participants’ main source of information was health professionals. Most of them owned smartphones (63.5%), but none used mHealth applications for dementia-related information seeking. Approximately half of the respondents were ready to spend time (52.7%) and money (46.8%) on mHealth information seeking. Perceived mHealth usefulness was significantly associated with dementia knowledge, smartphone ownership, and readiness to spend time and money on mHealth information seeking. Conclusion Informal carers of people with dementia were affected by BPSD in their care recipients. This study explored carers’ educational needs concerning dementia, BPSD, and carer burden. Informal carers could adapt mHealth for dementia-related information seeking. Their unmet needs in managing BPSD should be explored.

Abstract Introduction Carotid endarterectomy is performed for patients with symptomatic carotid artery occlusions. Surgery can be performed under general and regional anesthesia. Traditionally, surgery is performed under deep cervical plexus block which is technically difficult to perform and can cause serious complications. This case series describes 5 cases in which an intermediate cervical plexus block was used in combination with a superficial cervical plexus block for Carotid endarterectomy surgery. Methods Five patients who were classified as American Society of Anesthesiologists 2–3 were scheduled for Carotid endarterectomy due to symptoms and more than 70% occlusion of the carotid arteries. The procedures were carried out in the University Teaching Hospital- Peradeniya, Sri Lanka. All patients were given superficial cervical plexus block followed by intermediate cervical plexus block using 2% lignocaine and 0.5% plain bupivacaine. Results Adequate anesthesia was achieved in 4 patients, and local infiltration was necessary in 1 patient. Two patients developed hoarseness of the voice, which settled 2 h after surgery. Hemodynamic fluctuations were observed in all 5 patients. No serious complications were observed. All 5 patients had uneventful recoveries. Discussions Regional anesthesia for CEA is preferable in patients who are medically complicated to undergo anesthesia or in patients for whom cerebral monitoring is not available. Intermediate cervical plexus block is described for thyroid surgeries in literature, but not much details on its use for carotid surgeries. Deep cervical plexus blocks has few serious complications which is not there with the use of ICPB making it a good alternative for CEA surgeries . Conclusions Superficial cervical plexus block and intermediate cervical plexus block can be used effectively for providing anesthesia for patients undergoing Carotid endarterectomy. It is safe and easier to conduct than deep cervical plexus block and enables monitoring of cerebral function.

The advent of sixth-generation (6G) networks promises revolutionary advancements in wireless communication, marked by unprecedented speeds, ultra-low latency, and ubiquitous connectivity. This research paper delves into the integration of Artificial Intelligence (AI) in 6G network applications, exploring the challenges and outlining future directions for this transformative synergy. The study investigates the key AI technologies for 6G: the potential of AI to optimize network performance, enhance user experience, and enable novel applications in diverse domains and AI-enabled applications. Analyzing the current landscape, the paper identifies key challenges such as scalability, security, and ethical considerations in deploying AI-enabled 6G networks. Moreover, it explores the dynamic interplay between AI and 6G technologies, shedding light on the intricate relationships that underpin their successful integration. The research contributes valuable insights to the ongoing discourse surrounding the convergence of AI and 6G networks, laying the groundwork for a robust and intelligent future communication infrastructure.

Abstract In river research, forecasting flow velocity accurately in vegetated channels is a significant challenge. The forecasting performance of various independent and hybrid machine learning (ML) models are thus quantified for the first time in this work. Utilizing flow velocity measurements in both natural and laboratory flume experiments, we assess the efficacy of four distinct standalone machine learning techniques—Kstar, M5P, reduced error pruning tree (REPT) and random forest (RF) models. In addition, we also test for eight types of hybrid ML algorithms trained with an Additive Regression (AR) and Bagging (BA) (AR-Kstar, AR-M5P, AR-REPT, AR-RF, BA-Kstar, BA-M5P, BA-REPT and BA-RF). Findings from a comparison of their predictive capabilities, along with a sensitivity analysis of the influencing factors, indicated: (1) Vegetation height emerged as the most sensitive parameter for determining the flow velocity; (2) all ML models displayed outperforming empirical equations; (3) nearly all ML algorithms worked optimal when the model was built using all of the input parameters. Overall, the findings showed that hybrid ML algorithms outperform regular ML algorithms and empirical equations at forecasting flow velocity. AR-M5P (R2 = 0.954, R = 0.977, NSE = 0.954, MAE = 0.042, MSE = 0.003, and PBias = 1.466) turned out to be the optimal model for forecasting of flow velocity in vegetated-rivers.

Measurement inaccuracies and the absence of precise parameters value in conceptual and analytical models pose challenges in simulating the rainfall–runoff modeling (RRM). Accurate prediction of water resources, especially in water scarcity conditions, plays a distinctive and pivotal role in decision-making within water resource management. The significance of machine learning models (MLMs) has become pronounced in addressing these issues. In this context, the forthcoming research endeavors to model the RRM utilizing four MLMs: Support Vector Machine, Gene Expression Programming (GEP), Multilayer Perceptron, and Multivariate Adaptive Regression Splines (MARS). The simulation was conducted within the Malwathu Oya watershed, employing a dataset comprising 4,765 daily observations spanning from July 18, 2005, to September 30, 2018, gathered from rainfall stations, and Kappachichiya hydrometric station. Of all input combinations, the model incorporating the input parameters Qt−1, Qt−2, and R̄t was identified as the optimal configuration among the considered alternatives. The models' performance was assessed through root mean square error (RMSE), mean average error (MAE), coefficient of determination (R2), and developed discrepancy ratio (DDR). The GEP model emerged as the superior choice, with corresponding index values (RMSE, MAE, R2, DDRmax) of (43.028, 9.991, 0.909, 0.736) during the training process and (40.561, 10.565, 0.832, 1.038) during the testing process. HIGHLIGHTS ML models for forecasting streamflow in the Malwathu Oya River basin were evaluated.; Rainfall for several stations was used in model development.; The GEP model showcased the best predictability of streamflow.; Research findings help the proposed Malwathu Oya development scheme.;

A series of three-dimensional numerical simulations have been carried out to examine the onset and characteristics of thermo-solutal Marangoni convection in the floating liquid bridge of SiGe ([Formula: see text] and [Formula: see text]). To this end, a simple half-zone model is considered, and the free surface deformation is taken into account. Simulation results carried out under normal (1-g) and zero gravity show that the computed temperature field in the melt is almost independent of this convective flow, and the concentration field determines the characteristics of the transport structures developing in the melt. The critical conditions for three volume ratios under normal and zero gravity conditions are determined. The thresholds in the liquid bridge depend on the volume ratio, and gravity has a negligible effect on the flow transition in the present calculation regime. The critical azimuthal wave number can shift to higher values at the higher volume ratio or to lower values at the low volume ratio. The random-periodic pattern was observed only at the high-volume ratio for the thermal-solutal Marangoni convection.

The mapping and monitoring of different types of Glacial lakes through the Geospatial techniques is vital to show the impact of climate changes on the Glacier and alleviate hazards that result from the bursting of Glacial Lakes and cause catastrophic consequences to human lives. The main goal of the present work was to map and analyze different types of glacial lakes in Bhutan during the years 1990, 2000, and 2017. Several sets of satellite images, Landsat-TM for 1990, Landsat ETM + for 2000, and Landsat 8-OLI satellite image for 2017, were used to estimate the changes in the glacial lakes and the inventory study. Several glacial lakes, i.e., moraine-dammed lake, supra glacial lake, lateral moraine lake, erosional lake, medial moraine lake, and end moraine lake, were mapped within these periods. It was found that there was a rapid increase in glacial lakes from 1990 to 2017. The number of glacial lakes in 1990 was increased from 213 to 436 in 2017. It was also observed that the spatial dimensions of some of the glacial lakes increased. The study revealed five end moraine lakes, 40 lateral moraine lakes, 50 supra glacial lakes, 239 erosional lakes, and 15 other moraines dammed lakes in 2017.

This research utilized three-dimensional numerical simulations to analyze the effect of volume ratio on fluid dynamics of a range of Prandtl (Pr) number and Schmidt (Sc) number fluids under steady and unsteady Marangoni conditions. Key outcomes highlight that while the volume ratio has a negligible effect on temperature distribution in low Pr number fluids under steady conditions, it becomes important under unsteady Marangoni convection. Conversely, in high Pr number fluids, the volume ratio significantly influences temperature and flow velocity distributions across all conditions, underscoring its critical role in achieving uniform fluid dynamics. Additionally, the volume ratio predominantly affects concentration distribution rather than temperature distribution under steady conditions in fluids of high Sc and low Pr numbers. Concentration and flow velocity distributions are uniform in the flat free surface under steady conditions for high Sc number and all Pr numbers fluids. Low Pr and high Sc number fluids exhibit irregular and quasi-periodic patterns in concentration and flow velocity distributions, and oscillatory flow patterns dominate in high Sc and high Pr number fluids under unsteady conditions.

Abstract Fuel dispensing at fuel stations is performed manually by unprotected male gas station attendants in Sri Lanka, who have long working hours. These workers are exposed to hydrocarbon fuels associated with multiple health effects by modulation of the autonomic nervous system. This study was performed to determine cardiovascular autonomic functions among fuel pump attendants in Sri Lanka. Fuel pump attendants (n = 50) aged between 19 and 65 years were identified for the study from seven fuel stations. They were compared with age‐ and gender‐matched controls (n = 46) without occupational exposure to fuel. A physical examination was performed before the autonomic function and heart rate variability (HRV) assessment. There were no significant differences in weight, height, or BMI between the study and the control populations (p > 0.05). Both the systolic blood pressure (SBP) (Mann Whitney U (MWU) = 743.5, p = 0.003) and diastolic blood pressure (DBP) (MWU = 686.5, p = 0.001) were significantly higher among the gas station attendants compared to controls. Valsalva ratio was significantly higher among the study group (MW U = 874.00, p = 0.043) compared to controls. The HRV analysis showed significantly higher SDNN and SD2 (MWU = 842.00, p = 0.034, and MWU = 843.50, p = 0.035 respectively) among the gas station attendants compared to controls. The changes to the cardiovascular autonomic parameters among those exposed to fuel vapor as a gas station attendant indicate an increase in sympathetic outflow to the vessels. In the occupational setting as fuel pump attendants need periodic monitoring.

Water quality assessment and prediction play crucial roles in ensuring the sustainability and safety of freshwater resources. This study aims to enhance water quality assessment and prediction by integrating advanced machine learning models with XAI techniques. Traditional methods, such as the water quality index, often require extensive data collection and laboratory analysis, making them resource-intensive. The weighted arithmetic water quality index is employed alongside machine learning models, specifically RF, LightGBM, and XGBoost, to predict water quality. The models' performance was evaluated using metrics such as MAE, RMSE, R2, and R. The results demonstrated high predictive accuracy, with XGBoost showing the best performance (R2 = 0.992, R = 0.996, MAE = 0.825, and RMSE = 1.381). Additionally, SHAP were used to interpret the model's predictions, revealing that COD and BOD are the most influential factors in determining water quality, while electrical conductivity, chloride, and nitrate had minimal impact. High dissolved oxygen levels were associated with lower water quality index, indicative of excellent water quality, while pH consistently influenced predictions. The findings suggest that the proposed approach offers a reliable and interpretable method for water quality prediction, which can significantly benefit water specialists and decision-makers.

Abstract Tumor-related trigeminal neuralgia (TN) is a deeply debilitating condition that severely impacts patient quality of life. Two principal treatment methods in use are open surgical resection of the causative tumor or the use of stereotactic radiosurgery (SRS). In this letter, we aim to evaluate the use of both treatment methods and highlight that in patients with commensurate anatomy, open surgical resection continues to provide greater rates of symptomatic relief, lower rates of recurrence, and complication compared to stereotactic radiosurgery.

Abstract Soil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to poor instrumentation and many other unavoidable reasons such as natural disasters like droughts, floods, and cyclones. Therefore, an accurate prediction model would fix these difficulties. Uzbekistan is one of the countries that is concerned about climate change due to its arid climate. Therefore, for the first time, this research presents an integrated model to predict soil temperature levels at the surface and 10 cm depth based on climatic factors in Nukus, Uzbekistan. Eight machine learning models were trained in order to understand the best-performing model based on widely used performance indicators. Long Short-Term Memory (LSTM) model performed in accurate predictions of soil temperature levels at 10 cm depth. More importantly, the models developed here can predict temperature levels at 10 cm depth with the measured climatic data and predicted surface soil temperature levels. The model can predict soil temperature at 10 cm depth without any ground soil temperature measurements. The developed model can be effectively used in planning applications in reaching sustainability in food production in arid areas like Nukus, Uzbekistan.

Abstract Background Engagement and partnership with consumers and communities throughout research processes produces high quality research meeting community needs and promoting translation of research into improved policy and practice. Partnership is critical in research involving Aboriginal and/or Torres Strait Islander people (First Nations Peoples) to ensure cultural safety. We present lessons from the design, implementation and progress of the National Health and Medical Research Council funded INtravenous iron polymaltose for First Nations Australian patients with high FERRitin levels on hemodialysis (INFERR) clinical trial. Main body The trial was designed to understand the benefits and harms of iron therapy in First Nations Australians on haemodialysis with anaemia and hyperferritinaemia. The lack of evidence for treatment was discussed with patients who were potential participants. A key element ensuring safe conduct of the INFERR trial was the establishment of the Indigenous Reference Groups (IRGs) comprising of dialysis patients based in the Top End of Australia and Central Australia. Two IRGs were needed based on advice from First Nations communities and researchers/academics on the project regarding local cultural differences and approaches to trial conduct. The IRGs underpin culturally safe trial conduct by providing input into study materials and translating study findings into effective messages and policies for First Nations dialysis patients. Throughout the trial conduct, the IRGs’ role has developed to provide key mechanisms for advice and guidance regarding research conduct both in this study and more broadly. Support provided to the IRGs by trial First Nations Research Officers and independent First Nations researchers/academics who simplify research concepts is critical. The IRGs have developed feedback documents and processes to participants, stakeholders, and the renal units. They guarantee culturally safe advice for embedding findings from the trial into clinical practice guidelines ensuring evidence-based approaches in managing anaemia in haemodialysis patients with hyperferritinaemia. Conclusion Active consumer and community partnership is critical in research conduct to ensure research impact. Strong partnership with consumers in the INFERR clinical trial has demonstrated that First Nations Consumers will engage in research they understand, that addresses health priorities for them and where they feel respected, listened to, and empowered to achieve change.

Abstract This study reviews recent advancements in food science and technology, analyzing their impact on the development of intelligent food packaging within the complex food supply chain. Modern food technology has brought about intelligent food packaging, which includes sensors, indicators, data carriers, and artificial intelligence. This innovative packaging helps monitor food quality and safety. These innovations collectively aim to establish an unbroken chain of food safety, freshness, and traceability, from production to consumption. This research explores the components and technologies of intelligent food packaging, focusing on key indicators like time–temperature indicators, gas indicators, freshness indicators, and pathogen indicators to ensure optimal product quality. It further incorporates various types of sensors, including gas sensors, chemical sensors, biosensors, printed electronics, and electronic noses. It integrates data carriers such as barcodes and radio-frequency identification to enhance the complexity and functionality of this system. The review emphasizes the growing influence of artificial intelligence. It looks at new advances in artificial intelligence that are driving the development of intelligent packaging, making it better at preserving food freshness and quality. This review explores how modern food technologies, especially artificial intelligence integration, are revolutionizing intelligent packaging for food safety, quality, reduced waste, and enhanced traceability.

Abstract Background This paper reports the first case of basaloid squamous cell carcinoma clinically and radiologically masquerading as a head and neck paraganglioma. Case presentation A 66-year-old Sinhalese male with unilateral hearing impairment and 7th–12th (excluding 11th) cranial nerve palsies was diagnosed radiologically with a head and neck paraganglioma by magnetic resonance imaging of the brain, which revealed a hypointense and hyperintense punctate mass centered at the jugular fossa with intracranial extension. The ascending pharyngeal artery, recognized as the major feeder, was embolized by percutaneous embolization following digital subtraction angiography. Gross total resection of the tumor was followed by an uneventful postoperative recovery. Combined immunohistochemistry and histopathological morphology revealed a basaloid squamous cell carcinoma, following which the patient completed radiotherapy and is at 3-month follow-up currently. Conclusion This case report discusses the diagnostic pitfalls and management challenges of this rare entity on the basis of prior evidence, as well as a literature review and clinical and surgical analysis.

This study evaluates the rainfall erosivity (RE) and erosivity density (ED) over the Kelani River basin, Sri Lanka for a period of 31 years (1990–2020). The river basin is well known for its annual floods during the southwestern monsoon season and severe erosion including landslides can be observed. The catchment was analyzed for its RE using the Wischmeier and Smith algorithm and for its ED using Kinnel's algorithm. The monthly rainfall data spreading over the river basin were used to analyze the monthly, seasonal, and annual RE and ED. Interestingly, the annual RE showed a linear increasing trend line over 31 years, and a maximum value of 2,831.41 MJ mm ha−1 h−1 yr−1 was able to be observed in the year 2016. The RE peaks in May which is in the southwestern monsoon season. This reveals that the risk of soil erosion in the basin is high in the southwestern monsoon season. In addition, land use and land cover changes over the years have adversely impacted the erosion rates. Therefore, it is highly recommended to investigate soil erosion in-depth and then implement relevant regulations to conserve the soil layers upstream of the river basin. HIGHLIGHTS Evaluates the rainfall erosivity and erosivity density over the Kelani River basin, Sri Lanka; The annual rainfall erosivity showed a linear increasing trend line over 31 years; Peaks can be observed during the southwest monsoon time.; Highlights the importance of regulating policy decisions to conserve the soil layers.;