DNA-MP: a generalized DNA modifications predictor for multiple species based on powerful sequence encoding method.

Accurate prediction of deoxyribonucleic acid (DNA) modifications is essential to explore and discern the process of cell differentiation, gene expression and epigenetic regulation. Several computational approaches have been proposed for particular type-specific DNA modification prediction. Two recent generalized computational predictors are capable of detecting three different types of DNA modifications; however, type-specific and generalized modifications predictors produce limited performance across multiple species mainly due to the use of ineffective sequence encoding methods. The paper in hand presents a generalized computational approach "DNA-MP" that is competent to more precisely predict three different DNA modifications across multiple species. Proposed DNA-MP approach makes use of a powerful encoding method "position specific nucleotides occurrence based 117 on modification and non-modification class densities normalized difference" (POCD-ND) to generate the statistical representations of DNA sequences and a deep forest classifier for modifications prediction. POCD-ND encoder generates statistical representations by extracting position specific distributional information of nucleotides in the DNA sequences. We perform a comprehensive intrinsic and extrinsic evaluation of the proposed encoder and compare its performance with 32 most widely used encoding methods on $17$ benchmark DNA modifications prediction datasets of $12$ different species using $10$ different machine learning classifiers. Overall, with all classifiers, the proposed POCD-ND encoder outperforms existing $32$ different encoders. Furthermore, combinedly over 5-fold cross validation benchmark datasets and independent test sets, proposed DNA-MP predictor outperforms state-of-the-art type-specific and generalized modifications predictors by an average accuracy of 7% across 4mc datasets, 1.35% across 5hmc datasets and 10% for 6ma datasets. To facilitate the scientific community, the DNA-MP web application is available at https://sds_genetic_analysis.opendfki.de/DNA_Modifications/.

De novo manifestations during adalimumab treatment in Behçet's syndrome.

OBJECTIVES: Treatment response may be variable across organ manifestations of Behçet syndrome (BS). We aimed to determine the frequency of de novo manifestations during adalimumab treatment. METHODS: We conducted a chart review of all BS patients who received adalimumab in our center between 2008 and 2023. Demographic data, reasons for initiating adalimumab, concurrent medications, previous treatments, and outcomes were recorded. We defined de novo manifestations as new BS manifestations that occurred for the first time during treatment with adalimumab. For patients with vascular involvement, a new vascular event at another vessel was also considered as a de novo manifestation. RESULTS: Among the 335 patients, a de novo manifestation developed in 14 (4%) patients. De novo manifestations were vascular involvement in 5 patients, arthritis in 3, anterior uveitis in 2, nervous system involvement in 2, gastrointestinal involvement in 1, and epididymitis in 1 patient. The primary reasons for adalimumab treatment were vascular involvement in 5 patients, uveitis in 4, arthritis in 3, mucocutaneous involvement in 1, and epididymitis in 1 patient. Upon the development of de novo manifestation, adalimumab was switched to another biologic in 4 patients, dose was intensified in 3, colchicine, conventional immunosuppressives, and/or glucocorticoids were added in 5, and topical eye drops were added in 2 patients, leading to remission of de novo manifestations in all patients. CONCLUSION: De novo manifestations were infrequent (4%) among BS patients treated with adalimumab. Of these, 57% were major organ involvement, mainly vascular involvement. None of the patients developed posterior uveitis.

Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort.

BACKGROUND: The early identification of patients at high-risk for end-stage renal disease (ESRD) is essential for providing optimal care and implementing targeted prevention strategies. While the Kidney Failure Risk Equation (KFRE) offers a more accurate prediction of ESRD risk compared to static eGFR-based thresholds, it does not provide insights into the patient-specific biological mechanisms that drive ESRD. This study focused on evaluating the effectiveness of KFRE in a UK-based advanced chronic kidney disease (CKD) cohort and investigating whether the integration of a proteomic signature could enhance 5-year ESRD prediction. METHODS: Using the Salford Kidney Study biobank, a UK-based prospective cohort of over 3000 non-dialysis CKD patients, 433 patients met our inclusion criteria: a minimum of four eGFR measurements over a two-year period and a linear eGFR trajectory. Plasma samples were obtained and analysed for novel proteomic signals using SWATH-Mass-Spectrometry. The 4-variable UK-calibrated KFRE was calculated for each patient based on their baseline clinical characteristics. Boruta machine learning algorithm was used for the selection of proteins most contributing to differentiation between patient groups. Logistic regression was employed for estimation of ESRD prediction by (1) proteomic features; (2) KFRE; and (3) proteomic features alongside KFRE. RESULTS: SWATH maps with 943 quantified proteins were generated and investigated in tandem with available clinical data to identify potential progression biomarkers. We identified a set of proteins (SPTA1, MYL6 and C6) that, when used alongside the 4-variable UK-KFRE, improved the prediction of 5-year risk of ESRD (AUC = 0.75 vs AUC = 0.70). Functional enrichment analysis revealed Rho GTPases and regulation of the actin cytoskeleton pathways to be statistically significant, inferring their role in kidney function and the pathogenesis of renal disease. CONCLUSIONS: Proteins SPTA1, MYL6 and C6, when used alongside the 4-variable UK-KFRE achieve an improved performance when predicting a 5-year risk of ESRD. Specific pathways implicated in the pathogenesis of podocyte dysfunction were also identified, which could serve as potential therapeutic targets. The findings of our study carry implications for comprehending the involvement of the Rho family GTPases in the pathophysiology of kidney disease, advancing our understanding of the proteomic factors influencing susceptibility to renal damage.

Terbium Phenanthroline Complex as a Luminescent Probe for the Detection of Anthrax Biomarker: Dipicolinic acid.

Dipicolinic acid (DPA) is a prominent biomarker for Anthrax disease. Bacillus anthracis bacterial endospores is composed of DPA as the significant component, which on over inhalation can cause severe health issues. Such contagious and life-threatening pathogens can be employed as bioweapons or biothreat agents for spreading bioterrorism which is a major risk for national security and public health concerns. Hence, effective detection or a surveillance system is essential for preventing the growth of bioterrorism events. Herein, we have developed a Terbium - 1,10 Phenanthroline (Tb-Phen) based lanthanide luminescence complex with bright green fluorescence. On addition of DPA, the green fluorescence is turn-off at a linear range from 0.6 to 4.762 mM. In this effect, 5D4- 7F5 transition caused by 1,10-phenanthroline to Tb3+ at 544 nm is restricted due to energy transfer quenching and Inner Filter Effect (IFE). The developed probe shows good sensitivity towards the detection of DPA with other coexisting biomolecules and ions with a low Limit of Detection (LOD) of 5.029 µM. The practical feasibility was evaluated in paper strip assay and extended in real samples such as human serum and tap water with satisfactory recovery percentage. Thereby, probe finds promising application in sensing of anthrax spore biomarker (DPA) and biothreat agents.

L-Methionine and D-Methionine Capped Fluorescent Silicon Quantum Dots Based Probes for Turn on Sensing of Glutathione - A Comparative Study.

Oral Squamous Cell Carcinoma (OSCC), a prevalent type of oral cancer originates in squamous cells that develop due to tobacco use, excess alcohol consumption, human papillomavirus infection, chronic irritation and weakened immune system. When detected early, survival rates of OSCC can be increased to more than 85%. Hence its early detection is crucial for appropriate management. Oxidative stress has a vital role in pathogenesis of various cancers including OSCC. Early detection of OSCC can be done by exploring serum Glutathione (GSH); an oxidative stress biomarker. Herein, we have developed two Silicon quantum dots (SiQDs); (L-methionine capped Silicon quantum dots (LSiQDs) and D-methionine capped Silicon quantum dots (DSiQDs)) and their fluorescence was quenched with Cu2+. The obtained Cu@LSiQDs and Cu@DSiQDs were then explored and compared for sensing GSH. Both the SiQDs were checked for selectivity and interference studies using coexisting biomolecules extended for sensing GSH from real samples. Moreover, a paper strip assay was also developed and compared.

Radiological characteristics of invasive micropapillary carcinoma of the breast.

AIM: To analyse the various imaging features of invasive micropapillary carcinoma (IMPC), a distinct variant of breast cancer, by mammography, ultrasound, and contrast-enhanced mammography. MATERIALS AND METHODS: This study included 68 female patients with histopathologically proven invasive micropapillary carcinoma who underwent mammography, ultrasound, and contrast-enhanced mammography examinations. The findings encountered by each imaging tool were analysed using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. RESULTS: In this retrospective study, 64.7% of cases were of the pure form of IMPC. Most of the cases showed an aggressive clinical course, with lymphovascular invasion noted in 76.5% of cases, while 60.3% of cases showed associated pathological lymphadenopathy. The N3 stage was reported in 25% of cases. On analysing the mammographic and ultrasound imaging findings, a significant association between irregular shape and a non-circumscribed margin with IMPC was found. Associated calcification was noted in 47% of cases. Pathological enhancement of moderate or marked conspicuity was noted in cases that underwent contrast-enhanced mammography, with the most commonly encountered finding being enhancing irregular and non-circumscribed masses. CONCLUSION: The mammographic and ultrasound imaging features of IMPC are indistinguishable from other aggressive types of breast cancer. At contrast-enhanced mammography examination, pathological enhancement of moderate to marked conspicuity was shown in all cases. The observed strong association of IMPC with lymphovascular invasion and lymph node metastasis with higher nodal stage in this study mandate meticulous sonographic examination of the axilla, as well as the infra, and supraclavicular regions if pathological axillary lymphadenopathy was noted.

Pattern of sleep disorders among children with autism spectrum disorder.

BACKGROUND: Sleep disorders (SDs) are among many co-morbid medical conditions that affect children with autism spectrum disorder (ASD). Raising awareness and improving the standard of care for children diagnosed with ASD may result from identifying SDs among them. This study aims to evaluate patterns of SDs among Sudanese children diagnosed with ASD. METHOD: Using the Childhood Sleep Habit Questionnaire (CSHQ) to gather data on sleep disorders and SPSS version 26.0 for data analysis, a descriptive cross-sectional study was carried out in the five main autistic centres in Khartoum state covering all registered patients with ASD between April and June 2022. Ninety-two children diagnosed with ASD were enrolled in this study after the purpose of the research was explained and consent was obtained from their guardians. A p-value < 0.05 was considered to indicate statistical significance. RESULTS: The mean age was 6.90 (± 2.6) years with a boys-to-girls ratio of 2.17:1. The prevalence of SDs (at least one sleep condition almost daily) was 95.65%. Sleep onset 71 (77.2%), limit setting 32 (32.6%), resistant onset to sleep 48 (52.2%), and combined 52 (56.5%) insomnia affected the majority of children. Additionally, there were significant associations between sex and Limit-setting insomnia, advanced sleep phase disorder, and narcolepsy type 2 (P values = 0.033, 0.009, and 0.037, respectively). Additionally, there was a significant association between age and sleep-related breathing disorders-snoring (p value = 0.031). CONCLUSION: The frequency of SDs is significant among children diagnosed with ASD from Sudan, and certain SDs are associated with age and sex. Subsequent studies are required to develop national guidelines for the prevalence, presentation, screening, and treatment of SDs in children diagnosed with ASD.

Highly sensitive lanthanide complex as a probe for l-kynurenine: A cancer biomarker.

A lanthanide complex based on europium (Eu) and chelidamic acid was synthesized (Eu-CHE) and characterized. The complex Eu-CHE exhibited intense luminescence at 615 nm under excitation at 300 nm and was further investigated for highly sensitive turn-off detection of l-kynurenine (l-kyn), a cancer biomarker. The probe detected l-kyn linearly from 6 nM to 0.2 µM with a limit of detection and limit of quantification of 1.37 and 4.57 nM, respectively. The probe was investigated for selectivity towards l-kyn among co-existing amino acids and further extended for detecting l-kyn from human serum and urine samples. A low-cost paper strip-based sensing platform was also developed for the visual detection of l-kyn.

Antibody-functionalized gold nanoclusters/gold nanoparticle platform for the fluorescence turn-on detection of cardiac troponin I.

A selective fluorescence turn-on immunosensor for the specific detection of cardiac troponin I (cTnI), the potent biomarker for myocardial infarction diagnosis, was developed with a nano couple comprised of protein-stabilized gold nanocluster and gold nanoparticle. The red fluorescence of cTnI-specific antibody tagged bovine serum albumin stabilized gold nanoclusters was quenched with gold nanoparticles (AuNP) via the intensive interaction between amine and hydroxyl functionalities of BSA and AuNP. Through this, the adsorption of gold nanoclusters at the surface of AuNP, resulting in a core-satellite assembly, was assumed to quench the fluorescence emission. While in the presence of cTnI antigen, this gets disturbed due to the formation of immunocomplex between cTnI antigen and antibody, which restricts the close interaction between gold clusters and nanoparticles, thereby restoring quenched fluorescence. The enhancement in fluorescence signal is directly related to the concentration of cTnI, and this facilitates the selective detection of cTnI in the linear concentration range 0.7 to 10 ng/mL without any interference from other potentially interfering co-existing biomolecules. An appreciable limit of detection of 0.51 ng/mL and a limit of quantification of 0.917 ng/mL for cTnI is comparable to that of the previous report.

Impregnation of two-dimensional manganese dioxide nanosheets with 5-carboxyfluorescein as an immunoassay platform for sensitive detection of cardiac troponin T.

A novel immunoassay platform is presented utilizing a cardiac troponin T antibody (Ab-cTnT) labelled with 5-carboxyfluorescein (5-FAM) integrated into a two-dimensional (2D) manganese dioxide nanosheet (MnO2 NS) matrix. This strategy enables a turn-on response towards cTnT antigen within a mere 10-min incubation period, boasting an impressive lower detection limit of 0.038 ng/mL. Crucially, our probe demonstrates exceptional selectivity amidst the presence of coexisting biomolecules and ions, ensuring precise detection of cTnT. Moreover, the developed platform showcases promising utility in sensing cTnT from spiked human serum samples, yielding satisfactory recovery percentages ranging from 82 to 105%. Additionally, we introduce and easy-to-use and cost-effective test strip for point-of-care detection of cTnT, further enhancing accessibility to critical cardiovascular diagnostics.

Medical students' perceptions towards implementing case-based learning in the clinical teaching and clerkship training.

BACKGROUND: Depending on the subject area and the 'case' used, many methods can be used to describe case-based learning (CBL). The majority of health professional education is patient-centered. As a result, clinical presentations and diseases are combined with social and clinical sciences, and student learning is linked to real-world applications. The purpose of this study was to evaluate how medical students at the Faculty of Medicine, National Ribat University, felt about the implementation of CBL. METHODS: This descriptive cross-sectional study was conducted on 171 final-year medical students (100 females and 71 males). Students were voluntarily invited to complete a self-administered questionnaire consisting of 15 closed-ended questions with 5-point Likert scale responses, covering data on perception, awareness, and barriers to CBL. RESULTS: The CBL satisfaction rate among medical students was 92.4%. The mean value of the medical student's perception was 3.7 out of 5. Regarding perceptions of CBL, 65.5% of students agreed with the positive impact of CBL on their academic performance. "8.2%" (14/171) of students strongly concur that CBL improved teamwork, while "31.6%" (54/171) strongly disagree. "36.3%" of students strongly believe that CBL improved their ability to use clinical reasoning. Regarding CBL barriers, 53% of medical students considered a group of twenty participants per session to be a barrier. (69%) of students refused to consider physical presence as a barrier. "76.6%" of the students agreed that the moderator's approach and style can have a big influence on the CBL session's outcome. CONCLUSION: Overall, students had positive perceptions of CBL. Academic performance, clinical reasoning, teamwork, and information retention and retrieval were all improved by incorporating CBL into training modules. Students agreed that the group size of 20 students per session was a barrier, despite their moderate to excellent knowledge of CBL. Preparation for CBL is both time-consuming and tiring. Despite this, students agree that CBL has a positive impact on the learning process.

Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey.

BACKGROUND: Artificial intelligence (AI) is transforming health profession education (HPE) through personalized learning technologies. HPE students must also learn about AI to understand its impact on healthcare delivery. We examined HPE students' AI-related knowledge and attitudes, and perceived challenges in integrating AI in HPE. METHODS: This cross-sectional included medical, nursing, physiotherapy, and clinical nutrition students from four public universities in Jordan, the Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), and Egypt. Data were collected between February and October 2023 via an online survey that covered five main domains: benefits of AI in healthcare, negative impact on patient trust, negative impact on the future of healthcare professionals, inclusion of AI in HPE curricula, and challenges hindering integration of AI in HPE. RESULTS: Of 642 participants, 66.4% reported low AI knowledge levels. The UAE had the largest proportion of students with low knowledge (72.7%). The majority (54.4%) of participants had learned about AI outside their curriculum, mainly through social media (66%). Overall, 51.2% expressed positive attitudes toward AI, with Egypt showing the largest proportion of positive attitudes (59.1%). Although most participants viewed AI in healthcare positively (91%), significant variations were observed in other domains. The majority (77.6%) supported integrating AI in HPE, especially in Egypt (82.3%). A perceived negative impact of AI on patient trust was expressed by 43.5% of participants, particularly in Egypt (54.7%). Only 18.1% of participants were concerned about the impact of AI on future healthcare professionals, with the largest proportion from Egypt (33.0%). Some participants (34.4%) perceived AI integration as challenging, notably in the UAE (47.6%). Common barriers included lack of expert training (53%), awareness (50%), and interest in AI (41%). CONCLUSION: This study clarified key considerations when integrating AI in HPE. Enhancing students' awareness and fostering innovation in an AI-driven medical landscape are crucial for effectively incorporating AI in HPE curricula.

Novel ibuprofen prodrug: A possible promising agent for the management of complications of Alzheimer's disease.

Background: Alzheimer's disease (AD) is a severe, varied, and complex brain condition that gradually impairs memory and cognitive function. Epidemiological studies have shown that patients who have a history of long-term NSAID use have a decreased risk of developing AD. The objective of this study is to conduct the structural analysis of a novel ibuprofen prodrug and test its anti-Alzheimer's properties. Methods: Computational and docking studies were conducted using AMBER 18 package. The in-vivo studies were performed using aluminum chloride-induced experimental AD in rats. Adult Wistar rats of either sex were used and treated with aluminum chloride (32.5 mg/kg, p.o) and ibuprofen prodrug (50 mg/kg, p.o) daily for 30 days. The hole-board test and elevated plus maze were conducted on 10th, 20th and 30th day. Further, on 31st day, animals were euthanized and the brain tissue was used for histopathology. The results obtained were subjected to statistical analysis by one-way ANOVA and Dunnet's test, p < 0.05 was considered to indicate the significance. Results: The structural configuration of the novel compound indicated the presence of several structures such as aliphatic, aromatic, and asymmetry in the compound. The geometrical analysis indicated that the ibuprofen conjugate has dreiding energy of 51.22 kcal/mol with a van der waals radius of 62.56 A. The Huckel analysis confirmed the presence of aromatic rings in the compound. The molecular docking studies suggested affinity towards beta-secretase and acetylcholinesterase, besides indicating that the compound has ideal characteristics for the oral route (Log P = 2.33), cellular absorption (TPSA = 95.50), and oral bioavailability (number of rotatable bonds = 10). The toxicity profile indicated devoid of major systemic toxicity with mild possibility of cytotoxicity. The in-vivo analysis showed that the Ibu-prodrug significantly (P < 0.001) reversed the changes induced by aluminum chloride and restored histomorphological features in brain tissue. Conclusion: The findings suggested that the ibuprofen conjugate might possess the potential to manage the complications of AD. The action appears to be mediated through inhibition of beta-secretase and acetylcholinesterase activities. More studies might aid in identifying a specific therapeutic intervention that is still lacking in the treatment of AD.

Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

BACKGROUND: Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking. METHODS: Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses. RESULTS: The resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched. CONCLUSIONS: The in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

A microbiological identification and recovery actions of critical symptoms of anammox image bacteria.

Currently, the risks posed by bacteria are becoming increasingly important. It now appears that the cell wall of Anammox image bacteria is very different from what has been generally considered for many years. Not every textbook contains the peptidoglycan on the cell wall of Anammox image bacteria - the sugar-protein chain that strengthens the cells of most bacteria. Most researchers in this Anammox image bacteria diseased identification wanted to find out what gave the Anammox image cell its stability. It used powerful cryo-electron microscopes to examine the bacterial cell wall and find the exact structure of the peptidoglycan. A new algorithm is proposed to discover that Anammox image bacteria contain peptidoglycan, which completes a theory in microbiology. The identification of different diseases is listed, and the proposed model compares the exact results while comparing the parameters like accuracy, precision, recall, and F1-Score. Keywords: Anammox image bacteria, cell wall, cell stability, cryo-electron, microscope images, accuracy, precision, recall, F1-score.

NaYF4:Yb/Ho upconversion nanoprobe incorporated gold nanoparticle (AuNP) based FRET immunosensor for the "turn-on" detection of cardiac troponin I.

Cardiac troponin I (cTnI) is a significant biomarker for acute heart attack. Hence, fast, economical, easy and real time monitoring of cardiac troponin I (cTnI) is of great importance in diagnosis and prognosis of heart failure in the healthcare domain. In this work, an immunoassay based on NaYF4:Yb/Ho based photon-upconversion nanoparticle (UCNP) with narrow emission peaks at 540 nm and 655 nm respectively, is synthesized. Then, it is encapsulated with amino functionalized silica using 3-aminopropyltriethoxysilane (APTES) to form APTES@SiO2-NaYF4:Yb/Ho UCNPs. When AuNPs is added to this system, the fluorescence is quenched by the electrostatic interaction with APTES@SiO2-NaYF4:Yb/Ho UCNPs, thereby exhibiting a FRET-based biosensor. When the cTnI antigen is introduced into the developed probe, an antibody-antigen complex is formed on the surface of the UCNPs resulting in fluorescence recovery. The developed sensor shows a linear response towards cTnI in the range from 0.1693 ng mL-1 to 1.9 ng mL-1 with a low limit of detection (LOD) of 5.5 × 10-2 ng mL-1. The probe exhibits adequate selectivity and sensitivity when compared with coexisting cardiac biomarkers, biomolecules and in real human serum samples.

Role of neutrophil / lymphocyte ratio, uric acid / albumin ratio and uric acid / creatinine ratio as predictors to severity of preeclampsia.

BACKGROUND: Pre-eclampsia (PE) is an intractable obstetric disorder with high mortality and morbidity, affecting 6-8% of pregnancies worldwide. As its etiology and pathogenesis remain unclear, there are no specific prevention or treatment options. This study aimed to determine the association between neutrophil to lymphocyte ratio (NLR), uric acid to albumin ratio (UAR) and uric acid to creatinine ratio (UA/Cr) and severity of pre-eclampsia. METHODS: A cross-sectional hospital-based study was conducted among pre-eclamptic women in Kosti Maternity Hospital from September to December 2022. Forty-five pre-eclamptic women were enrolled in this study and were classified according to the WHO classification of PE into mild PE (23 PE patients) and severe PE (22 PE patients). Data were collected using a semi-structured questionnaire covering medical history and clinical assessment. A blood sample was taken from each participant for measurements of the complete blood count (CBC), liver functions test (LFT) with enzymes, renal functions test (RFT) with electrolytes, and uric acid by standard techniques. RESULTS: NLR was found to be statistically significantly higher in mothers with severe PE (6.3-9.9) than in those with mild PE (2.2-1.5) (p-value 0.048). Alanine aminotransferase (ALT) was significantly higher in women with severe PE than in those with mild PE (p-value = 0.02). The total means of platelet-lymphocyte ratio (PLR), UA/Cr, and UAR were insignificantly higher in women with severe PE compared with those with mild PE (p-values 0.666, 0.427, and 0.525, respectively). The means of uric acid and serum creatinine showed insignificant statistical elevation in women with severe PE compared with mild PE (p-values of 0.27 and 0.44, respectively). Serum albumin was found to be insignificantly lower in mothers with severe PE (3.3 ± 0.6 g/dl) than in those with mild PE (3.6 ± 0.6 g/dl); p-value = 0.21. CONCLUSIONS: PE showed a significant statistical increase in WBC, neutrophils, alanine transaminase (ALT), and NLR in severe PE compared to mild PE and a significant statistical decrease in lymphocyte count in severe PE compared to mild PE. The measurement of NLR may be a useful laboratory marker for predicting the severity of PE.

Comparative study of pulmonary functions test among different substances abusers.

BACKGROUND: Substance use is a problem that affects people all over the world and is prevalent in different age groups. The lungs in particular, with their unique exposure to the environment and the bloodstream, are vulnerable to damage from substance use and can affect lung function. Efforts have generally focused on cigarettes, while there is little research on different substances of use. The study aimed to detect changes in pulmonary function tests in different substance users. METHODS: An analytical cross-sectional study was carried out among different substance users at the Abdalaal Elidridi Psychiatric Hospital. A total of 60 adults were included: 16 cannabis users, 16 heroin users, 16 methamphetamine users, and 12 alcohol users. Participants used only one substance. Height and weight were measured, and BMI was calculated. For each participant, pulmonary function tests (PFTs) including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC ratio and peak expiratory flow rate (PEFR) were measured using an electronic spirometer, and the results were compared with normal reference values for Sudanese subjects matched for age, sex, and height. RESULTS: A high prevalence of lung function abnormalities (100.0%) is seen in all abusers. Obstructive lung disease is found in 80.0% of patients, and restrictive lung disease is found in 20.0% of cases. The measured FEV1/FVC ratio in different substance groups was lower than the expected normal values of (88.2 ± 2.9%). The mean FEV1/FVC ratio of alcohol was (83.6 ± 7.6%), for heroin, it was (77.3 ± 15.8%), for methamphetamine, it was (77.7 ± 17.8%) and for cannabis, it was (71.03 ± 11.3%), the latter was significantly lower than the other two groups (P < 0.001). Duration of substance use was inversely correlated with the FEV1/FVC ratio (r = -0.378, P 0.001), indicating that a longer duration of substance use correlates with lower FEV1/FVC ratios. CONCLUSIONS: Obstructive lung abnormalities are frequent in substance abusers. All types of substances have a major deleterious effect on PFTs and harm the respiratory system. More action should be taken to address the effects of substances on the lungs. Awareness, early detection, and intervention are essential.

Comparative assessment of homemade ELISA and lateral flow assay (LFA)in the rapid, specific and sensitive detection of SARS-CoV-2 anti-nucleocapsid protein in sera of Egyptian patients.

Several diagnostic measures have been employed to precisely detect the SARS-CoV-2 viral infection using viral antigens, nucleic acids, and other serological approaches. The sensitivity and specificity of the serological tests remain a challenging need. Here, we describe the detection of human anti-SARS-CoV-2 IgG and IgM antibodies qualitatively through two optimized in-house ELISA and lateral flow immunoassay. Both approaches are based on the prokaryotic expression of 50 kDa SARS-CoV-2 recombinant nucleocapsid protein. This SARS-CoV-2rN-6×His was used either to coat ELISA plates or to be conjugated to gold nanoparticles followed by colorimetric detection of bound human IgG or IgM. In the LFA, we show the optimization of nanoparticle size, protein-binding capacity, membrane treatment, and finally testing the potential capacity of using either the optimized ELISA or LFA in detecting antibodies raised against viral infection. Assessment of both methods was carried out using human sera-positive and negative SARS-CoV-2 antibodies. The ELISA and LFA tests showed 86%, 96.5% sensitivity, 92%, 93.75% specificity, 97%, 98.2% PPV, and 64%, 88.2% NPV, respectively. In conclusion, both approaches were able to successfully detect human antibodies against SARS-CoV-2 nucleocapsid protein. The importance of both protocols cannot be overstated in the detection and diagnosis of viral infections, especially in developing countries.

Machine Learning-Based Ultrasound Texture Analysis in Differentiation of Benign Phyllodes Tumors from Borderline-Malignant Phyllodes Tumors.

PURPOSE: Phyllodes tumors (PTs) are uncommon fibroepithelial breast lesions that are classified as three different forms as benign phyllodes tumor (BPT), borderline phyllodes tumor (BoPT), and malignant phyllodes tumor (MPT). Conventional radiologic methods make only a limited contribution to exact diagnosis, and texture analysis data increase the diagnostic performance. In this study, we aimed to evaluate the contribution of texture analysis of US images (TAUI) of PTs in order to discriminate between BPTs and BoPTs-MPTs. METHODS: The number of patients was 63 (41 BPTs, 12 BoPTs, and 10 MPTs). Patients were divided into two groups (Group 1-BPT, Group 2-BoPT/MPT). TAUI with LIFEx software was performed retrospectively. An independent machine learning approach, MATLAB R2020a (Math- Works, Natick, Massachusetts) was used with the dataset with p < 0.004. Two machine learning approaches were used to build prediction models for differentiating between Group 1 and Group 2. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance of statistically significant texture data between phyllodes subgroups. RESULTS: In TAUI, 10 statistically significant second order texture values were identified as significant factors capable of differentiating among the two groups (p < 0.05). Both of the models of our dataset make a diagnostic contribution to the discrimination between BopTs-MPTs and BPTs. CONCLUSION: In PTs, US is the main diagnostic method. Adding machine learning-based TAUI to conventional US findings can provide optimal diagnosis, thereby helping to choose the correct surgical method. Consequently, decreased local recurrence rates can be achieved.