Peutz Jeghers Syndrome presented as intermittent gastric outlet obstruction and ileoileal intussusceptions

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Peutz Jeghers Syndrome Presented as intermittent gastric outlet obstruction

Peutz Jeghers Syndrome (PJS), which was first described in 1921 by Peutz, followed by Jeghers etal in 1949, is an uncommon but not a rare disorder characterized by mucocutaneous melanin pigmentation, gastrointestinal hamartomatous polyps and increased risk of gastrointestinal and otherorgans cancer. The polyps vary in size from few millimeters to several centimeters, with lobulated surface, and could be pedunculated as in large polyps, or sessile as in the small ones. The clinical symptoms of the disease are recurrent abdominal pain, intestinal intussusception and obstruction, gastrointestinal bleeding with symptoms of iron deficiency anaemia. The symptoms usually take place in the second and third decade of life. The complications of PJS which brings the patient to the doctor is severe anemia due to blood loss from GIT, acute abdomen, intestinal obstruction due to tumor-mass obstruction or intussusception, or rarely due to gastric outlet obstruction as in this presented case. The treatment of polyposis is by endoscopic polypectomy, laprotomy and resection which may lead to complications as short bowel syndrome. The other difficulty which the doctor comes across while managing these cases is to follow-up the occurrence of malignant disease in these patients, malignant changes of hamartomatus polyps and other organs cancers have been reported in patients with PJS.Keywords: hamartomatus polyps, polypectomy, mucocutaneous

3D morphometric evaluation of palatal rugae among Malaysian Malay population

Palatal rugae pattern may have a promising and interesting future for human identification purpose. Previous studies showed that palatal rugae pattern has a lot of morphological and dimensional characteristics that are different from a person to another even among the identical twins. In fact, palatal rugae are anatomically located in a well protected place, behind boons, teeth, cheeks and lips, which provides a good alternative option for human identification in mass disasters and accidents. This study aimed to evaluate the variability and uniqueness of palatal rugae among Malaysian Malays using 3D dental models. A 3D Next Engine Laser scanner (USA) was used to digitize plaster dental casts of 130 Malaysian Malay patients (65 males and 65 females) obtained from the archive of Orthodontic Clinic, Hospital Universiti Sains Malaysia. The resulting 3D models were highlighted using Paint 3D software (USA) for the purpose of rugae shape assessment. Rugae size category and direction were assessed using 3Matic research software (Belgium). The classification method of Thomas and Kotze (1983) as described by Kapali et al. (1997) was adopted. Palatal rugae uniqueness was performed by superimposing 42 pairs of digital models (21 models were duplicated from the same patients and 21 models were randomly selected from the group). The 42 superimposition sets were examined for palatal rugae surface fitting by a single blinded evaluator. Prevalence of palatal rugae was presented in percentages while mean and standard deviation were presented for number of rugae. Chi-square analyses were used to evaluate the association between sex and prevalence of palatal rugae variables. Independent t-test was used to compare sex difference in number of palatal rugae. Correct/wrong decision of superimposition was presented in percentages. P-value <0.05 was considered statistically significant. Total number of rugae was 1359 (673 in males and 686 in females). Wavy shape was the predominant rugae among the sample, followed by curve shape and straight shape respectively. The predominant rugae size category was the primary size. Forwardly directed rugae were the most prevalent rugae among the sample. There was no significant difference regarding rugae features between males and females except for the rugae direction in the left side of the palate, as the backward rugae direction was more prevalent among the females (p=0.001). Palatal rugae pattern was unique. No two individuals have the same pattern. Wavy shape, Primary size and forward direction were the most prevalent among Malaysian Malays. Palatal rugae is unique thus could be used for human identification in the case where pre-mortem and post-mortem records are available

3D morphometric evaluation of palatal rugae among Malaysian Malay population

Palatal rugae pattern may have a promising and interesting future for human identification purpose. Previous studies showed that palatal rugae pattern has a lot of morphological and dimensional characteristics that are different from a person to another even among the identical twins. In fact, palatal rugae are anatomically located in a well protected place, behind boons, teeth, cheeks and lips, which provides a good alternative option for human identification in mass disasters and accidents. This study aimed to evaluate the variability and uniqueness of palatal rugae among Malaysian Malays using 3D dental models. A 3D Next Engine Laser scanner (USA) was used to digitize plaster dental casts of 130 Malaysian Malay patients (65 males and 65 females) obtained from the archive of Orthodontic Clinic, Hospital Universiti Sains Malaysia. The resulting 3D models were highlighted using Paint 3D software (USA) for the purpose of rugae shape assessment. Rugae size category and direction were assessed using 3Matic research software (Belgium). The classification method of Thomas and Kotze (1983) as described by Kapali et al. (1997) was adopted. Palatal rugae uniqueness was performed by superimposing 42 pairs of digital models (21 models were duplicated from the same patients and 2

Dissecting Energy Consumption of NB-IoT Devices Empirically

3GPP has recently introduced NB-IoT, a new mobile communication standard offering a robust and energy efficient connectivity option to the rapidly expanding market of Internet of Things (IoT) devices. To unleash its full potential, end-devices are expected to work in a plug and play fashion, with zero or minimal parameters configuration, still exhibiting excellent energy efficiency. We perform the most comprehensive set of empirical measurements with commercial IoT devices and different operators to date, quantifying the impact of several parameters to energy consumption. Our campaign proves that parameters setting does impact energy consumption, so proper configuration is necessary. We shed light on this aspect by first illustrating how the nominal standard operational modes map into real current consumption patterns of NB-IoT devices. Further, we investigate which device reported metadata metrics better reflect performance and implement an algorithm to automatically identify device state in current time series logs. Then, we provide a measurement-driven analysis of the energy consumption and network performance of two popular NB-IoT boards under different parameter configurations and with two major western European operators. We observed that energy consumption is mostly affected by the paging interval in Connected state, set by the base station. However, not all operators correctly implement such settings. Furthermore, under the default configuration, energy consumption in not strongly affected by packet size nor by signal quality, unless it is extremely bad. Our observations indicate that simple modifications to the default parameters settings can yield great energy savings.Comment: 18 pages, 25 figures, IEEE journal format, all Figures recreated for better readability, new section with results summar

IGFBP7 is upregulated in islets from T2D donors and reduces insulin secretion

\ua9 2024 The Author(s)Intra-islet crosstalk has become a focus area to fully understand the regulation of insulin secretion and impaired β-cell function in type 2 diabetes (T2D). Here, we put forward evidence for insulin-like growth factor binding protein 7 (IGFBP7) as a potential protein involved in autocrine and paracrine β-cell regulation. We showed presence of IGFBP7 in granules of both human α- and β-cells and measured elevated gene expression as well as IGFBP7 protein in T2D. Insulin secretion was reduced in human islets, and the human β-cell line EndoC-βH1, after 72-h incubation with IGFBP7. Mechanistically reduced insulin secretion by IGFBP7 is attributed to reduced p21-activated kinase 1 (PAK1) protein, and decreased oxygen consumption and ATP-production. Knockdown of IGFBP7 in EndoC-βH1 cells verified reduced IGFBP7 levels in the medium, as well as improved insulin secretion. Finally, IGFBP7 knockdown in islets from T2D donors improved insulin secretion, making IGFBP7 a potential drug target in diabetes

Attention Based Spatial-Temporal GCN with Kalman filter for Traffic Flow Prediction

Intelligent Transportation Systems (ITS) are becoming increasingly important as traditional traffic management systems struggle to handle the rapid growth of vehicles on the road. Accurate traffic prediction is a critical component of ITS, as it can help improve traffic management, avoid congested roads, and allocate resources more efficiently for connected vehicles. However, modeling traffic in a large and interconnected road network is challenging because of its complex spatio-temporal data. While classical statistics and machine learning methods have been used for traffic prediction, they have limited ability to handle complex traffic data, leading to unsatisfactory accuracy. In recent years, deep learning methods, such as Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), have shown superior capabilities for traffic prediction. However, most CNN-based models are built for Euclidean grid-structured data, while traffic road network data are irregular and better formatted as graph-structured data. Graph Convolutional Neural Networks (GCNs) have emerged to extend convolution operations to more general graph-structured data. This paper reviews recent developments in traffic prediction using deep learning, focusing on GCNs as a promising technique for handling irregular, graph-structured traffic data. We also propose a novel GCN-based method that leverages attention mechanisms to capture both local and long-range dependencies in traffic data with Kalman Filter, and we demonstrate its effectiveness through experiments on real-world datasets where the model achieved around 5% higher accuracy compared to the original model

Quantitative analysis of human adult pancreatic histology reveals separate fatty and fibrotic phenotypes in type 2 diabetes

\ua9 The Author(s) 2025. Aims/hypothesis: The role of intra-pancreatic lipid and collagen in type 2 diabetes pathogenesis remains unclear. We sought to examine this in pancreases from organ donors with and without diabetes. Methods: Tissue biopsies from 36 adult donor pancreases with/without type 2 diabetes were collected from 16 anatomically defined regions, with H&amp;E, Sirius Red Fast Green and chromogranin A immunohistochemical staining and quantification performed. Intracellular lipid droplet area was quantified using transmission electron microscopy in acinar, islet endocrine, beta and alpha cells identified through ultrastructural morphology. Results: Increasing adipocyte proportional area was associated with increasing pancreas donor BMI (r=0.385, p=0.021), decreased acinar area (r=−0.762, p&lt;0.001) and increased endocrine mass (r=0.749, p&lt;0.001). Fibrosis was not associated with BMI, acinar area or endocrine mass. Type 2 diabetes was associated with decreased islet circularity and reduced beta:alpha cell ratio but endocrine mass was not affected. Adipocyte and fibrosis proportional areas were highest in donors with diabetes but not associated with each other. Pancreases with high fat and those with high fibrosis (&gt;40% proportional area) appeared to form two separate subgroups. All donors with insulin-treated diabetes had a high collagen proportional area. Fibrosis but not adipocytosis was associated with decreased beta:alpha cell ratio. There was an inverse relationship between pancreatic adipocytosis and intra-acinar cell lipid content (r=−0.490, p=0.003), with the lowest levels seen in type 2 diabetes. Beta cell lipid content was associated with BMI but not type 2 diabetes. Conclusions/interpretation: Systematic human pancreatic analysis revealed two separate type 2 diabetes phenotypes: fatty, associated with central obesity; and fibrotic, associated with reduced beta cell mass without central obesity. This suggests distinct underlying pathogenic mechanisms and has potential for developing personalised disease-modifying therapeutics

Generation of a pseudo-timeline describing progressive human exocrine and endocrine pancreatic pathology in cystic fibrosis through novel semi-quantitative scoring and AI-driven quantitative image analysis

\ua9 The Author(s) 2025. Aims/hypothesis: Cystic fibrosis (CF) is associated with pancreatic exocrine insufficiency (PEI) early in life and diabetes in at least 50% of adults. Underlying CF-related changes within the pancreas remain incompletely understood due to scarcity of available human tissue, protracted disease course and absence of robust and reproducible analytical approaches. This study aimed to develop and apply a systematic analysis cross-sectionally to CF pancreatic tissue samples to construct a timeline of exocrine and endocrine changes with progressive disease. Methods: Through a pathologist-led iterative approach, a light-microscopy semi-quantitative scoring system and artificial-intelligence-driven quantitative image analysis for individual pancreatic variables were developed. These were applied to human pancreatic tissue from 29 CF and 58 control donors without pancreatic disease. Results: Rapid loss of acinar tissue with virtually complete absence and replacement by adipocytes by the age of 7 years was confirmed. Ductal blockage by thickened secretions was associated with increasing ductal dilatation accompanied by periductal fibrosis, followed by ductal loss with involution of associated fibrosis in parallel with increasing adipocyte proportional area. Remaining ducts were relatively small, surrounded by residual fibrosis. Islets became increasingly clustered, initially surrounded by pancreatic stellate cells and fibrosis, then disorganised by interposing fibrotic tissue between endocrine cell regions and surrounded by residual collagen stranding in a ‘lipotic’ pancreas. Overall islet mass was not reduced but proportional beta cell area was reduced from birth without further loss over the course of progressive disease. Conclusions/interpretation: The natural history of pancreatic CF progresses rapidly from duct blockage and dilatation associated with periductal fibrosis to global fat replacement in keeping with early onset of PEI in the majority of affected individuals. Beta cell proportional area is reduced at birth before clinical evidence of pancreatic endocrine dysfunction without significant further loss of islet/beta cell mass with age. Increasing islet disorganisation and intra-islet collagen deposition in older donors temporo-spatially implicates fibrosis in and around the islet as being aetiologically important in the development of CF-related diabetes