B-lymphoblastic leukaemia presenting as intrahepatic cholestasis

Acute cholangitis is a critical medical condition requiring prompt intervention. This case report explores the complexities and uncertainties encountered in clinical decision-making when faced with a patient presenting with symptoms suggestive of acute cholangitis. We emphasise the importance of considering individual circumstances and factors in the diagnostic process. A 38-year-old woman with a history of Crohn’s colitis presented with abdominal pain, jaundice and leukocytosis. Initial evaluation raised suspicions of acute cholangitis, but unexpected findings of blast cells in the peripheral smear led to a diagnosis of B-lymphoblastic leukaemia with BCR-ABL1 fusion. Treatment with steroids and chemotherapy resulted in the resolution of liver abnormalities. This case underscores the necessity of comprehensive assessments for obstructive jaundice and highlights the potential diagnostic challenges posed by underlying haematologic malignancies. It also raises awareness about drug-induced liver injury, and emphasises the importance of complete blood counts and differentials in the initial workup. Healthcare providers should be vigilant in considering alternative diagnoses when faced with obstructive jaundice, as misdiagnosis can lead to invasive procedures with potential adverse events

Identifying COVID-19 survivors living with post-traumatic stress disorder through machine learning on Twitter

The COVID-19 pandemic has disrupted people’s lives and caused significant economic damage around the world, but its impact on people’s mental health has not been paid due attention by the research community. According to anecdotal data, the pandemic has raised serious concerns related to mental health among the masses. However, no systematic investigations have been conducted previously on mental health monitoring and, in particular, detection of post-traumatic stress disorder (PTSD). The goal of this study is to use classical machine learning approaches to classify tweets into COVID-PTSD positive or negative categories. To this end, we employed various Machine Learning (ML) classifiers, to segregate the psychotic difficulties with the user’s PTSD in the context of COVID-19, including Random Forest Support Vector Machine, Naïve Bayes, and K-Nearest Neighbor. ML models are trained and tested using various combinations of feature selection strategies to get the best possible combination. Based on our experimentation on real-world dataset, we demonstrate our model’s effectiveness to perform classification with an accuracy of 83.29% using Support Vector Machine as classifier and unigram as a feature pattern

Pattern of utilization of ante-natal and delivery services in a semi-urban community of North-Central Nigeria.

Background: Nigeria accounts for only 2% of the world\u2019s population, but contributes up to 10 % of the global estimates of maternal deaths. The study assesses the utilization of antenatal and delivery services by women of reproductive age in Afon community. Methodology: It was a descriptive cross-sectional study that collected both quantitative and qualitative data using semi-structured interviewer administered questionnaire and focus group discussions (FGD). Interviews were house-hold based. FGD had two homogenous groups. Data was analysed using Epi-info version 3.5.1 software package. Level of statistical significance was set at p <0.05. Results: There was a high level of utilization of antenatal/delivery services in the community. Barriers to utilization of ANC/ delivery services include lack of money, distance from health facility, long waiting time, poor attitude of health workers and no permission from husbands. Level of education and employment status were significantly associated with utilization of ANC/ delivery services. Conclusion: Girl- child education and women empowerment are required to improve utilization of services. Ante-natal care providers need to be trained to improve quality of care in the discharge of their duties

Synergistic overview and perspectives of two-dimensional heterostructures for cathodes and separators in flexible Li–S batteries

Because of their high energy densities and specific capacities, lithium–sulfur (Li–S) batteries have recently received an extensive amount of research. The best way to boost battery performance is by altering the electrode materials. The adoption of 2D material-based heterostructures has attracted significant attention for increasing electrochemical performance and preventing the shuttle effect. Therefore, a summary of the link between the specific properties of 2D material heterostructures and electrochemical performance is required for the development of next-generation Li–S batteries. The present research focuses on the latest developments that boost the performance of Li–S batteries by using the unique features of 2D material heterostructures. This evaluation also categorizes several meticulously selected 2D materials with specific properties. Some solutions have been developed to overcome the difficulties of insulating intermediates, polysulfide shuttle, and sluggish kinetics. Superior conductivity, tunable functional groups, and exceptional flexibility are some of the most crucial elements in boosting electrochemical performance

Sustainable metal-organic framework co-engineered glass fiber separators for safer and longer cycle life of Li-S batteries

Most of the issues with making Li–S batteries are caused by the growth of Li dendrites and the movement of polysulfide. To solve both of these problems at the same time, this study describes the placement of Cu or Fe atoms on an ultrathin metal organic framework (MOF) nanosheet-based glass fiber separator for making Li–S batteries that are safe and last a long time. Cu or Fe atoms coordinated with oxygen atoms on the surface of ultrathin MOF nanosheets can greatly facilitate the movement of Li ions while acting as "traps" to stop polysulfide from moving around by introducing the Lewis acid-base interaction. Because of this, the Li–S cells with the Cu/MOF or Fe/MOF coatings on the glass fiber separator show long-term cycling stabilities with low-capacity decay of 0.080% and 0.057% per cycle over 400 cycles, respectively. Furthermore, Li–S cells assembled with the Cu/MOF and Fe/MOF separators show capacity retention of 985 and 1237 mAh g-1, respectively, after 400 cycles, indicating the potential of the Cu/MOF and Fe/MOF separators for practical applications

Use of Reservoir Sediments to Improve Engineering Properties of Dune Sand in Oman

Managing sediments dredged from reservoirs of recharge dams is an environmental issue, however, these sediments can be an abundant and economical source of fine-grained fill soil. This experimental investigation quantifies the geotechnical properties of a reservoir sediment used to improve engineering properties of a poorly graded dune sand in Oman. The binary mixes were prepared with different percentages (5, 10, 20, 50, 75, 90, 95%) of sediment with sand. Laboratory tests such as gradation, consistency limits, compaction, and unconfined compression tests were performed to measure the engineering characteristics of the binary mixtures. The results showed that the maximum dry density increases up to a sediment content of 50% and then decreases with further increase in the sediment content. The optimum water content increases with the increase in sediment content from 17% for pure sand to 22.5% for pure sediment. The optimum moisture content shows a good correlation with the plastic limit of the binary mixture of sand and sediment. The unconfined compressive strength substantially increases with sediment content up to 75% and then decreases with further increase in the sediment content. The binary mixture of sand sediment is sensitive to moisture, however, the order of strength stability against moisture is dune sand mixed with 75, 50, and 20% sediments. The addition of sediment to dune sand improved the uniformity coefficient to some extent with an increase in the maximum and minimum void ratios as well. The elemental analysis of the sediment confirms that the material is non-contaminated and can be employed in geotechnical engineering applications as a sustainable and environmentally friendly solution

Ab-initio Study of Paramagnetic Defects in Mn and Cr Doped Transparent Polycrystalline Al2O3 Ceramics

Birefringence is a major source of difficulty in sintering of transparent polycrystalline alumina ceramics, especially as the grain size exceeds a few hundred nanometers, which ultimately leads to complete opacity, mainly due to scattering of light. Recent studies have made it clear that by application of a strong magnetic field, alumina grains can be aligned along a particular crystallographic orientation, which minimizes scattering due to birefringence, and enhances transparency. Defects that cause spin delocalization are known to induce a paramagnetic behavior in alumina ceramics. Therefore, such defects have become a focal point of research for magnetic field assisted sintering of transparent polycrystalline alumina, in order to reduce the necessary magnetic field strength during production process. In light of recent studies on paramagnetic potentials of transition metal doped alumina, we have applied Spin Polarized Density Functional Theory (SP-DFT) calculations on manganese and chromium doped and co-doped alumina to calculate the magnetic moments, density of states and defect formation energies, which should be expected from this system of dopants, along with their interactions with oxygen vacancies. The results clearly indicate that formation of a point defect comprised of chromium and manganese positioned substitutionally at adjacent aluminum sites, in vicinity of an oxygen vacancy can induce a magnetic moment equivalent to 5 Bohr magnetons (μβ), outperforming previously reported defects. Based on this study we find it likely that chromium and manganese co-doping in alumina can further reduce the required magnetic field strength for production of transparent polycrystalline alumina