Maternal serum CA-125 repeated measurement during pregnancy and how to use as a prognostic factor of first trimester pregnancy outcome

Background: The aim of this study was to estimate the prognostic efficacy of repeated measurement of maternal serum CA125 in first trimester threatened miscarriage.Methods: Prospective case control study was conducted in the outpatient clinic. 100 pregnant women were divided into 50 women with normal course of pregnancy, and the other 50 were subdivided into 25 pregnant women with lower abdominal pain without vaginal bleeding and 25 presented with minimal vaginal bleeding. Repeated measuring of serum CA125 was done for each case on the 5th, 10th weeks of gestation.Results: Findings of this study suggested the possibility of using serum CA-125 for determining the prognosis of first trimester threatened miscarriage with cut-off value of CA125 38.25 U/ml on the 5th week of gestation and 53 U/ml on the 10th week of gestation in patients presented with pain only but in patients presented with minimal vaginal bleeding the cut-off value of CA125 on the 5th week of gestation become 45.6 U/ml and 68 U/ml on the 10th week of gestation.Conclusions: CA125, on its own, can discriminate between continued and non-continued pregnancy.

Novel Exopolysaccharide from Marine Bacillus subtilis with Broad Potential Biological Activities: Insights into Antioxidant, Anti-Inflammatory, Cytotoxicity, and Anti-Alzheimer Activity

In the presented study, Bacillus subtilis strain AG4 isolated from marine was identified based on morphological, physiological, phylogenetic characteristics and an examination of 16S rRNA sequences. Novel exopolysaccharide (EPSR4) was extracted and isolated from the Bacillus subtilis strain as a major fraction of exopolysaccharide (EPS). The analysis of structural characterization indicated that EPSR4 is a β-glycosidic sulphated heteropolysaccharide (48.2%) with a molecular weight (Mw) of 1.48 × 104 g/mole and has no uronic acid. Analysis of monosaccharide content revealed that EPSR4 consists of glucose, rhamnose and arabinose monosaccharide in a molar ratio of 5:1:3, respectively. Morphological analysis revealed that EPSR4 possess a high crystallinity degree with a significant degree of porosity, and its aggregation and conformation in the lipid phase might have a significant impact on the bioactivity of EPSR4. The biological activity of EPSR4 was screened and evaluated by investigating its antioxidant, cytotoxicity, anti-inflammatory, and anti-Alzheimer activities. The antioxidant activity results showed that EPSR4 has 97.6% scavenging activity toward DPPH free radicals at 1500 µg/mL, with an IC50 value of 300 µg/mL, and 64.8% at 1500 µg/mL toward hydrogen peroxide free radicals (IC50 = 1500 µg/mL, 30 min). Furthermore, EPSR4 exhibited considerable inhibitory activity towards the proliferation of T-24 (bladder carcinoma), A-549 (lung cancer) and HepG-2 (hepatocellular carcinoma) cancer cell lines with IC50 of 244 µg/mL, 148 µg/mL and 123 µg/mL, respectively. An evaluation of anti-inflammatory activity revealed that EPSR4 has potent lipoxygenase (LOX) inhibitory activity (IC50 of 54.3 µg/mL) and a considerable effect on membrane stabilization (IC50 = 112.2 ± 1.2 µg/mL), while it showed cyclooxygenase (COX2) inhibitory activity up to 125 µg/mL. Finally, EPSR4 showed considerable inhibitory activity towards acetylcholine esterase activity. Taken together, this study reveals that Bacillus subtilis strain AG4 could be considered as a potential natural source of novel EPS with potent biological activities that would be useful for the healthcare system.Faculty of Science, Suez Canal UniversityPrincess Nourah bint Abdulrahman UniversityTaif UniversityPeer Reviewe

Herd Immunity against Severe Acute Respiratory Syndrome Coronavirus 2 Infection in 10 Communities, Qatar.

We investigated what proportion of the population acquired severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whether the herd immunity threshold has been reached in 10 communities in Qatar. The study included 4,970 participants during June 21-September 9, 2020. Antibodies against SARS-CoV-2 were detected by using an electrochemiluminescence immunoassay. Seropositivity ranged from 54.9% (95% CI 50.2%-59.4%) to 83.8% (95% CI 79.1%-87.7%) across communities and showed a pooled mean of 66.1% (95% CI 61.5%-70.6%). A range of other epidemiologic measures indicated that active infection is rare, with limited if any sustainable infection transmission for clusters to occur. Only 5 infections were ever severe and 1 was critical in these young communities; infection severity rate of 0.2% (95% CI 0.1%-0.4%). Specific communities in Qatar have or nearly reached herd immunity for SARS-CoV-2 infection: 65%-70% of the population has been infected

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

“So what if ChatGPT wrote it?”:Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

Clinical Decision Support Framework for Segmentation and Classification of Brain Tumor MRIs Using a U-Net and DCNN Cascaded Learning Algorithm

Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development of computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic resonance imaging (MRI) has been the subject of many research papers so far. However, research in this sector is still in its early stage. The ultimate goal of this research is to develop a lightweight effective implementation of the U-Net deep network for use in performing exact real-time segmentation. Moreover, a simplified deep convolutional neural network (DCNN) architecture for the BT classification is presented for automatic feature extraction and classification of the segmented regions of interest (ROIs). Five convolutional layers, rectified linear unit, normalization, and max-pooling layers make up the DCNN’s proposed simplified architecture. The introduced method was verified on multimodal brain tumor segmentation (BRATS 2015) datasets. Our experimental results on BRATS 2015 acquired Dice similarity coefficient (DSC) scores, sensitivity, and classification accuracy of 88.8%, 89.4%, and 88.6% for high-grade gliomas. When it comes to segmenting BRATS 2015 BT images, the performance of our proposed CAD framework is on par with existing state-of-the-art methods. However, the accuracy achieved in this study for the classification of BT images has improved upon the accuracy reported in prior studies. Image classification accuracy for BRATS 2015 BT has been improved from 88% to 88.6%