Exposure to endocrine disrupting chemicals from beverage packaging materials and risk assessment for consumers.

This study investigated the influence of beverage packaging materials on the presence of endocrine disrupting chemicals (EDCs) in plastic, glass, carton, aluminium, and tin canned non-alcoholic beverages. Results showed that 63 EDCs including perfluoroalkyl and polyfluoroalkyl substances (PFAS), bisphenols, parabens, benzophenone-type UV-filters, biocides, nitrophenols, and alkylphenols, were detected in 144/162 screened products. Detected ∑63EDC concentrations ranged from 1.3 to 19,600 ng/L. EDC concentrations were higher in beverages packaged in metal cans while lower or no levels were detected in glass, plastic, and carton packaged drinks. Bisphenol levels were higher on average in canned beverages compared to glass (p < 0.01) and plastic products (p < 0.05) produced by the same brand and manufacturer. Two structural isomers of bisphenol A (BPA) were identified in 19 beverages, constituting the first detection in foodstuffs. The calculated daily intake of detected EDCs showed that exposure to BPA from per capita beverage consumption of 364 mL/day are up to 2000-fold higher than the newly revised safety guideline for BPA recommended by the EFSA (European Food Safety Authority). Overall, these findings suggest that BPA exposure poses a potential health hazard for individuals who regularly consume non-alcoholic beverages packaged in aluminium or tin cans, particularly young children.

Label-Free Metal-Oxide Transistor Biosensors for Metabolite Detection in Human Saliva.

Metabolites are essential molecules involved in various metabolic processes, and their deficiencies and excessive concentrations can trigger significant physiological consequences. The detection of multiple metabolites within a non-invasively collected biofluid could facilitate early prognosis and diagnosis of severe diseases. Here, a metal oxide heterojunction transistor (HJ-TFT) sensor is developed for the label-free, rapid detection of uric acid (UA) and 25(OH)Vitamin-D3 (Vit-D3) in human saliva. The HJ-TFTs utilize a solution-processed In2O3/ZnO channel functionalized with uricase enzyme and Vit-D3 antibody for the selective detection of UA and Vit-D3, respectively. The ultra-thin tri-channel architecture facilitates strong coupling between the electrons transported along the buried In2O3/ZnO heterointerface and the electrostatic perturbations caused by the interactions between the surface-immobilized bioreceptors and target analytes. The biosensors can detect a wide range of concentrations of UA (from 500 nm to 1000 µM) and Vit-D3 (from 100 pM to 120 nm) in human saliva within 60 s. Moreover, the biosensors exhibit good linearity with the physiological concentration of metabolites and limit of detections of ≈152 nm for UA and ≈7 pM for Vit-D3 in real saliva. The specificity is demonstrated against various interfering species, including other metabolites and proteins found in saliva, further showcasing its capabilities.

Mucinous Differentiation in Colorectal Cancer: A 10-Year Experience Audit at King Faisal Specialist Hospital and Research Centre, Jeddah.

Given that colorectal cancer is one of the leading causes of mortality, mucinous adenocarcinoma is one of the subtypes and is characterized by the presence of mucin-producing tumor cells with mucin components and is more challenging to manage. In Saudi Arabia, it represents approximately 10-15% of all colorectal carcinoma. The main etiological cause of mucinous adenocarcinoma is yet not well understood. The main goal of our study is to discuss the histopathology and the molecular background of mucinous colorectal adenocarcinoma and also to provide an update on its prognosis and therapeutics from recent published literature. It is a retrospective cohort study that was conducted at King Faisal Specialist Hospital, Jeddah, Saudi Arabia. The study included 68 adult patients diagnosed with mucinous colon cancer, who did surgical resection alone or with or without adjuvant chemotherapy following from January 2011 to December 2020. The mucinous subtypes are found more commonly in the proximal colon. In our study, 26 patients (38.2% of the cases) were right-sided and 35 patients (51.5%) were from the left side, but these included the rectum as well and this reflects the higher incidence of diagnosis of rectal cancer in the region. Most tumors were classified as Grade II in 56 patients (82.4%), consistent with the intermediate differentiation status often associated with the mucinous subtypes. The most common symptom at presentation was abdominal pain in 38 patients (55.9%) followed by per rectal bleeding and abdominal mass. The management in our study was in line with the standard established practice and surgical resection as expected was the primary potentially curative approach. Notably of patients presenting with locally advanced rectal cancer, six patients underwent concomitant chemoradiotherapy followed by surgery and four patients had upfront surgery. The duration of the median follow-up was 32 months. At the time of analysis, 30 patients (44.1%) were alive and remained on regular follow-up, 17 patients (25%) had succumbed to the disease, and 21 patients (30.9%) were lost to follow-up. The median overall survival was not reached, and notably, 49 patients (71.6%) remained alive at the four-year mark. Whilst our study contributes to the current understanding of mucinous adenocarcinomas of the colon, further research in molecular profiling and genomic testing and larger clinical trials with tailored treatments is necessary to refine treatment strategies and improve outcomes.

Knowledge, Awareness, and Attitude Regarding Obstructive Sleep Apnea Among Primary Healthcare Physicians in the Al-Baha Region of Saudi Arabia.

INTRODUCTION: Obstructive sleep apnea (OSA) is a clinically significant disorder that requires attention from healthcare professionals. This study aimed to assess the knowledge, awareness, and attitude of primary healthcare physicians regarding OSA in Saudi Arabia. METHODOLOGY: A cross-sectional observational study design was employed from January 18, 2023, to August 18, 2023, focusing on primary healthcare physicians practicing in the Al-Baha region of Saudi Arabia. The survey included questions related to knowledge, awareness, and attitudes toward OSA, using the Obstructive Sleep Apnea Knowledge and Attitude (OSAKA) questionnaire for OSA, and demographic information. Descriptive statistics and chi-square tests were used to analyze the data. RESULTS: A total sample size of 174 primary health care physicians was collected, where the majority of participants were male (101, 58.0%), and the mean age of the participants was 32.73 years (SD = 9.14). The item with the most correct answers was "The majority of patients with obstructive sleep apnea snore" (150, 86.2%). On the other hand, the item with the lowest number of correct answers was "Laser-assisted uvulopalatoplasty is an appropriate treatment for severe obstructive sleep apnea" (17, 9.8%). The majority of participants agreed that it is essential for physicians to know about OSA as a clinical disorder (161, 92.5%). However, when it came to screening all patients for possible OSA, there was a higher proportion of participants who disagreed or strongly disagreed (111, 63.8%). In general, the majority of participants had a low level of knowledge (109, 62.6%). Gender was significantly associated with both knowledge (p = 0.021) and awareness (p = 0.039), as well as nationality (knowledge (p = 0.012) and awareness (p = 0.039)), and specialty training, which was significantly associated with both knowledge (p = 0.000) and awareness (p = 0.002). CONCLUSION: Although all participants acknowledged that OSA is a clinical disease, their perspectives on screening and levels of confidence in utilizing screening techniques varied. While the participants exhibited commendable understanding in the majority of domains, there were some facets of OSA in which they lacked expertise.

Bilateral Congenital Stromal Corneal Cysts: Report of a Unique Case.

The purpose of this report is to provide a comprehensive account of an exceptional case involving the presentation of congenital rubella syndrome (CRS) in a newborn. Furthermore, it aims to document the successful regression of CRS through medical treatment alone. We present the case of a five-day-old infant who was referred to our facility as a CRS case. The patient presented with bilateral white corneal opacity, which was observed shortly after birth. The mother was diagnosed as rubella-positive during pregnancy. Upon the initial examination under anesthesia, both eyes exhibited central white corneal opacity accompanied by large intrastromal cysts. Although a few breaks in Descemet's membrane were observed in both eyes, there were no signs of vascularization or the presence of iridocorneal or lenticular-corneal adhesions. After undergoing medical treatment consisting of topical sodium chloride and steroids, the cysts in both eyes completely regressed. Subsequently, the patient underwent penetrating keratoplasty to further address the dense scar. This case enhances our comprehension of ophthalmological complications associated with CRS and provides valuable insights into alternative therapeutic approaches for corneal stromal cysts.

The prevalence and risk factors for hiatal hernia among patients undergoing endoscopy: A retrospective analysis.

OBJECTIVES: To determine the prevalence of hiatal hernia (HH) and its association with age, gender, and body mass index (BMI). METHODS: We retrospectively included patients who underwent esophagogastroduodenoscopy (EGD) at an academic tertiary care hospital. Data were collected on the presence of HH as well as patient demographics including age, gender, and BMI. Univariate and multivariate analysis were done to determine risk factors for HH. RESULTS: A total of 2805 patients were included in this study. The mean age was 48.6 (±18.6) years and males constituted 28.8% of the study population. The mean BMI was 29.7 (±8.6) kg/m². The prevalence of HH was 29.8% among all patients and 48.6% among those who underwent EGD for gastroesophageal reflux disease-related indications. There was no significant association between HH and female gender (OR 1.04, 95%CI: 0.88 -1.26, p=0.53), older age (OR 0.77, 95%CI: 0.72 - 1.06, p=0.19) or BMI (OR 1.07, 95%CI: 0.9 - 1.2, p=0.39). CONCLUSION: The prevalence of HH was 28.9% based on this large endoscopy-based population. We found no association between HH and gender, age, or BMI.

Non-invasive, ultrasensitive detection of glucose in saliva using metal oxide transistors.

Transistor-based biosensors represent an emerging technology for inexpensive point-of-care testing (POCT) applications. However, the limited sensitivity of the current transistor technologies hinders their practical deployment. In this study, we developed tri-channel In2O3/ZnO heterojunction thin-film transistors (TFTs) featuring the surface-immobilized enzyme glucose oxidase to detect glucose in various biofluids. This unusual channel design facilitates strong coupling between the electrons transported along the buried In2O3/ZnO heterointerface and the electrostatic perturbations caused by the interactions between glucose and surface-immobilized glucose oxidase. The enzyme selectively binds to glucose, causing a change in charge density on the channel surface. By exploring this effect, the solid-state biosensing TFT (BioTFT) can selectively detect glucose in artificial and real saliva over a wide range of concentrations from 500 nM to 20 mM with limits of detection of ∼365 pM (artificial saliva) and ∼416 nM (real saliva) in less than 60 s. The specificity of the sensor towards glucose has been demonstrated against various interfering species in artificial saliva, further highlighting its unique capabilities. Moreover, the BioTFTs exhibited good operating stability upon storage for up to two weeks, with relative standard deviation (RSD) values ranging from 2.36% to 6.39% for 500 nM glucose concentration. Our BioTFTs are easy to manufacture with reliable operation, making them ideal for non-invasive POCT applications.

Appendix diverticulosis in a patient diagnosed on pathology after laparoscopic appendectomy for appendicular mucinous mass-case report and literature review.

Diverticulum of the appendix is uncommon cause of right iliac fossa pain and inflammation with delayed diagnosis and high risk of complications, as it mimics acute appendicitis. Here we present a case of an elderly male patient who had lung cancer post-treatment. During the follow-up, appendicle lesion was discovered and suspected to be mucinous appendix. The pathology reported after appendectomy as appendicular diverticulosis without evidence of malignancy. As appendicular diverticulum is best confirmed by pathology, still its clinical presentation is difficult to be distinguished from other appendicular diseases. It is frequently linked to increased risk of cancer, particularly carcinoid tumors and mucinous adenomas.

Influence of Acidic Environment on the Hardness, Surface Roughness and Wear Ability of CAD/CAM Resin-Matrix Ceramics.

This study aimed to measure the effect of storage environment on the hardness, surface roughness and wear ability of CAD/CAM resin-matrix ceramics. A total of 200 rectangular-shaped specimens were obtained by sectioning 5 CAD/CAM blocks; Crystal Ultra (CU), Vita Enamic (VE), Lava Ultimate (LU), Cerasmart (CS) and Vita blocks Mark II (MII). Microhardness and surface roughness were measured at baseline and after 7 days of immersion either in saliva or cola (n = 10). The wear ability of the CAD/CAM materials against steatite-ceramics antagonist was determined using a chewing simulator. The data were statistically analyzed using factorial ANOVA followed by post hoc Bonferroni multiple comparison tests (p < 0.05). The independent factors significantly influenced the microhardness and surface roughness (p < 0.05). The highest VHN was observed in MII at baseline (586.97 ± 13.95), while CU showed the lowest VHN after 7 days of immersion in cola (68.3 ± 1.89). On the contrary, the highest Ra was observed after 120,000 chewing cycles for the VE specimens (1.09 ± 0.43 µm) immersed in cola, while LU showed the lowest Ra at baseline (0.07 ± 0.01 µm). The highest % mass loss of the antagonist was observed with MII immersed in cola (1.801%), while CS demonstrated the lowest % mass loss of 0.004% and 0.007% in AS and cola, respectively. This study confirms that the surface properties of tested CAD/CAM materials are susceptible to degradation in an acidic environment except for hardness and wear of CS material.

A Tri-Channel Oxide Transistor Concept for the Rapid Detection of Biomolecules Including the SARS-CoV-2 Spike Protein.

Solid-state transistor sensors that can detect biomolecules in real time are highly attractive for emerging bioanalytical applications. However, combining upscalable manufacturing with the required performance remains challenging. Here, an alternative biosensor transistor concept is developed, which relies on a solution-processed In2 O3 /ZnO semiconducting heterojunction featuring a geometrically engineered tri-channel architecture for the rapid, real-time detection of important biomolecules. The sensor combines a high electron mobility channel, attributed to the electronic properties of the In2 O3 /ZnO heterointerface, in close proximity to a sensing surface featuring tethered analyte receptors. The unusual tri-channel design enables strong coupling between the buried electron channel and electrostatic perturbations occurring during receptor-analyte interactions allowing for robust, real-time detection of biomolecules down to attomolar (am) concentrations. The experimental findings are corroborated by extensive device simulations, highlighting the unique advantages of the heterojunction tri-channel design. By functionalizing the surface of the geometrically engineered channel with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody receptors, real-time detection of the SARS-CoV-2 spike S1 protein down to am concentrations is demonstrated in under 2 min in physiological relevant conditions.

Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities.

Coughing is a common symptom of several respiratory diseases. The sound and type of cough are useful features to consider when diagnosing a disease. Respiratory infections pose a significant risk to human lives worldwide as well as a significant economic downturn, particularly in countries with limited therapeutic resources. In this study we reviewed the latest proposed technologies that were used to control the impact of respiratory diseases. Artificial Intelligence (AI) is a promising technology that aids in data analysis and prediction of results, thereby ensuring people's well-being. We conveyed that the cough symptom can be reliably used by AI algorithms to detect and diagnose different types of known diseases including pneumonia, pulmonary edema, asthma, tuberculosis (TB), COVID19, pertussis, and other respiratory diseases. We also identified different techniques that produced the best results for diagnosing respiratory disease using cough samples. This study presents the most recent challenges, solutions, and opportunities in respiratory disease detection and diagnosis, allowing practitioners and researchers to develop better techniques.

The association of stress with sleep quality among medical students at King Abdulaziz University.

OBJECTIVE: This study aims to determine the prevalence and the association of stress with sleep quality among medical students at King Abdulaziz University (KAU), Jeddah, Saudi Arabia. METHODS: A cross-sectional study was done among 326 medical students of KAU using a stratified random sampling technique. An electronic self-administered questionnaire was used. Kessler Psychological Distress Scale (K10) and Pittsburgh Sleep Quality Index (PSQI) were used to assess the stress and sleep quality, respectively. RESULTS: The overall students who experienced stress were 65%. The prevalence of poor sleep quality (total PSQI score ≥5) was 76.4%. There was a strong association between stress and poor sleep quality (value of Cramer's V = 0.371, P < 0.001), and it showed that the increase in stress level is a significant predictor of poor sleep quality. CONCLUSION: A high prevalence of stress and poor sleep quality was found among the students and the study confirms a strong association between them. We recommend establishing courses focusing on educating the students about proper sleep hygiene and how to deal with the stressful environment.

Survival of Patients with Small Cell Lung Cancer in King Abdulaziz University Hospital, Jeddah, Saudi Arabia.

Background Lung cancer is estimated to be 12% of all new cases of cancer. It is one of the most common cancers in men and women, and it is the main cause of cancer-related death in the United States of America. More than 90% of small cell lung cancer (SCLC) patients are elderly, with a current or past history of smoking. In Saudi Arabia, lung cancer incidence is low as compared to the global incidence. In 2013, the age-standardized ratio (ASR) was 1.8 per 100,000 for females and 5.5 per 100,000 for males. In our study, we aimed to assess the outcomes of SCLC at King Abdulaziz University Hospital (KAUH), Jeddah, Saudi Arabia. Methods This retrospective cohort study included all patients aged 14 years and older with a diagnosis of SCLC from 2007 to 2017 using electronic medical records at KAUH. Data analysis was performed using Stata SE, version 15.0 (StataCorp LLC, TX). The primary outcome of this study was the survival of patients diagnosed with SCLC. Survival was defined as the time the patient lived in months from the date of pathological diagnosis to the date of the last follow-up or death. We included all variables in a univariate and multivariate analysis to determine the hazard ratio for each variable. Results In our study, we initially collected 193 lung cancer cases diagnosed during the period of 2007 to 2017 at KAUH, which was then narrowed to 22 after the selection of only SCLC cases. Data obtained showed 20 males (90.91%) and two females (9.09%), the median age of diagnosis was 64 years, and 45% of patients are active smokers, 9% are ex-smokers, and the smoking status of 41% of patients is unknown. Our data showed an overall median survival of 6.4 months (interval=11). Conclusion We observed that more than half of our patients who received chemotherapy showed improvement and a higher survival rate than those who didn't. In addition, 19% who received radiation therapy showed improvement and a higher survival rate than those who didn't. Future efforts to address the major issues that surround SCLC survivors, and to formulate a comprehensive survivorship care plan are required to develop better outcomes in survival and to improve the overall quality of life to pretreatment levels.

A Deep Learning-Based Approach for the Detection of Early Signs of Gingivitis in Orthodontic Patients Using Faster Region-Based Convolutional Neural Networks.

Computer-based technologies play a central role in the dentistry field, as they present many methods for diagnosing and detecting various diseases, such as periodontitis. The current study aimed to develop and evaluate the state-of-the-art object detection and recognition techniques and deep learning algorithms for the automatic detection of periodontal disease in orthodontic patients using intraoral images. In this study, a total of 134 intraoral images were divided into a training dataset (n = 107 [80%]) and a test dataset (n = 27 [20%]). Two Faster Region-based Convolutional Neural Network (R-CNN) models using ResNet-50 Convolutional Neural Network (CNN) were developed. The first model detects the teeth to locate the region of interest (ROI), while the second model detects gingival inflammation. The detection accuracy, precision, recall, and mean average precision (mAP) were calculated to verify the significance of the proposed model. The teeth detection model achieved an accuracy, precision, recall, and mAP of 100 %, 100%, 51.85%, and 100%, respectively. The inflammation detection model achieved an accuracy, precision, recall, and mAP of 77.12%, 88.02%, 41.75%, and 68.19%, respectively. This study proved the viability of deep learning models for the detection and diagnosis of gingivitis in intraoral images. Hence, this highlights its potential usability in the field of dentistry and aiding in reducing the severity of periodontal disease globally through preemptive non-invasive diagnosis.