Golgi signalling proteins GOLPH3, MYO18A, PITPNC1 and RAB1B: implications in prognosis and survival outcomes of AML patients.

BACKGROUND: The role of different Golgi signalling proteins remains unexplored in the progression and spread of acute myeloid leukaemia (AML), whom all interact together in a way that facilitates proliferation and differentiation of myeloid lineage cells. OBJECTIVE: Since Golgi apparatus acts as master brain in membrane trafficking and signalling events that affect cell polarity necessary for migration, division, or differentiation; this study aims to explore the association between signalling proteins and the diagnosis, prognosis, and survival of AML patients. MATERIAL AND METHODS: This study comprised 70 newly diagnosed AML patients and 20 healthy controls to investigate the serum levels of signalling proteins; Golgi Phosphoprotein 3 (GOLPH3), Myosin 18A (MYO18A), Cytoplasmic Phosphatidylinositol Transfer Protein 1 (PITPNC1) and Ras-Associated Binding Protein 1B (RAB1B). RESULTS: AML patients showed higher serum levels of GOLPH3, MYO18A, PITPNC1 and RAB1B when compared to control (p < 0.001). A significant negative correlation was found between the patients' overall survival and GOLPH3 (p = 0.001), MYO18A (p = 0.011), PITPNC1 (p = 0.001) and RAB1B (p = 0.042). Results were confirmed by Kaplen-Meier survival analysis showing lower survival estimates in patients with higher GOLPH3 (p = 0.014), MYO18A (p = 0.047), PITPNC1 (p = 0.008) and RAB1B (p = 0.033) serum levels. CONCLUSION: GOLPH3, MYO18A, PITPNC1 and RAB1B maybe promising diagnostic and prognostic biomarkers in AML patients.

Successful Management of Severe Hyperhaemolysis with Combined Tocilizumab and Rituximab in Non-Transfusion-Dependent Thalassaemia: A Case Report.

Introduction: This is the fourth case reporting the administration of tocilizumab to control hyperhaemolysis. It was administered with rituximab to stop hyperhaemolysis refractory to frontline therapy. Hyperhaemolysis is a rare life-threatening subtype of delayed haemolytic transfusion reaction. Refractory cases pose a clinical challenge with no standard of care to date. Case Presentation: A 29-year-old lady with non-transfusion-dependent thalassaemia presented with refractory hyperhaemolysis necessitating the administration of rituximab. This was complicated with anaemic heart failure and altered sensorium exacerbated with further transfusions. A nadir haemoglobin of 2.1 g/dL was reached after the initiation of rituximab, and her condition was too critical to wait for the slow expected improvement. Hence, tocilizumab was given as a bridging therapy to block haemolysis till the delayed onset of radical treatment. Conclusion: Tocilizumab can be effectively combined with rituximab to stop hyperhaemolytic episode refractory to first-line treatment when a prompt response is needed.

Modelling the impact of climate change on dengue outbreaks and future spatiotemporal shift in Pakistan.

Climate change has a significant impact on the intensity and spread of dengue outbreaks. The objective of this study is to assess the number of dengue transmission suitable days (DTSD) in Pakistan for the baseline (1976-2005) and future (2006-2035, 2041-2070, and 2071-2099) periods under Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Moreover, potential spatiotemporal shift and future hotspots of DTSD due to climate change were also identified. The analysis is based on fourteen CMIP5 models that have been downscaled and bias-corrected with quantile delta mapping technique, which addresses data stationarity constraints while preserving future climate signal. The results show a higher DTSD during the monsoon season in the baseline in the study area except for Sindh (SN) and South Punjab (SP). In future periods, there is a temporal shift (extension) towards pre- and post-monsoon. During the baseline period, the top ten hotspot cities with a higher frequency of DTSD are Karachi, Hyderabad, Sialkot, Jhelum, Lahore, Islamabad, Balakot, Peshawar, Kohat, and Faisalabad. However, as a result of climate change, there is an elevation-dependent shift in DTSD to high-altitude cities, e.g. in the 2020s, Kotli, Muzaffarabad, and Drosh; in the 2050s, Garhi Dopatta, Quetta, and Zhob; and in the 2080s, Chitral and Bunji. Karachi, Islamabad, and Balakot will remain highly vulnerable to dengue outbreaks for all the future periods of the twenty-first century. Our findings also indicate that DTSD would spread across Pakistan, particularly in areas where we have never seen dengue infections previously. The good news is that the DTSD in current hotspot cities is projected to decrease in the future due to climate change. There is also a temporal shift in the region during the post- and pre-monsoon season, which provides suitable breeding conditions for dengue mosquitos due to freshwater; therefore, local authorities need to take adaption and mitigation actions.

Serum levels of FAK and some of its effectors in adult AML: correlation with prognostic factors and survival.

Focal adhesion kinase (FAK), human myofibrillogenesis regulator-1 (MR-1), ephrin receptor type A4 (EphA4), proto-oncogene tyrosine kinase Src (Src), and protein kinase C (PKC) are important markers in proliferation, survival, and migration in some cancers. However, the significance of each is still unclear in different malignancies, including acute myeloid leukemia (AML). Therefore, this study was conducted to investigate their serum levels in Egyptian adult de novo AML patients (n = 70) against healthy volunteers (n = 20). We managed to study the correlation between each pair and to investigate their association with diagnosis, prognosis, and survival. Serum levels were analyzed using enzyme-linked immunosorbent assay (ELISA). We found that FAK, MR-1, Src, and PKC serum levels were significantly higher in AML patients compared to control (p < 0.0001), and this was associated with significantly lower EphA4 level (p < 0.0001). Interestingly, we also observed a significant negative correlation of FAK (p = 0.027), MR-1 (p = 0.003), Src (p = 0.038), and PKC (p = 0.03) with patients' overall survival (OS) while there was a positive significant correlation between EphA4 and OS (p = 0.007). In conclusion, this study suggests that FAK, MR-1, EphA4, Src, and PKC may be used as early diagnostic and prognostic markers with high sensitivity and specificity in AML patients and thus may be incorporated into the patients' early diagnostic and prognostic panels.

Modelling and forecasting of new cases, deaths and recover cases of COVID-19 by using Vector Autoregressive model in Pakistan.

COVID-19 emerged in Wuhan, China in December 2019 has now spread around the world causes damage to human life and economy. Pakistan is also severely effected by COVID-19 with 202,955 confirmed cases and total deaths of 4,118. Vector Autoregressive time series models was used to forecast new daily confirmed cases, deaths and recover cases for ten days. Our forecasted model results show maximum of 5,363/day new cases with 95% confidence interval of 3,013-8,385 on 3rd of July, 167/day deaths with 95% confidence interval of 112-233 and maximum recoveries 4,016/day with 95% confidence interval of 2,182-6,405 in the next 10 days. The findings of this research may help government and other agencies to reshape their strategies according to the forecasted situation. As the data generating process is identified in terms of time series models, then it can be updated with the arrival of new data and provide forecasted scenario in future.

Minimal Residual Disease in Adult Acute Lymphoblastic Leukemia: Egyptian Experience.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is a clonal disease that affects early lymphoid progenitors in the bone marrow. Minimal residual disease (MRD) is assessed by different methods to monitor disease kinetics after treatment. AIM: to Assess MRD post-induction, at 6 and 12 months after intensive chemotherapy in adult patients with ALL. PATIENTS AND METHODS:  Seventy adult newly diagnosed acute lymphoblastic leukaemia patients were enrolled between July 2018 and July 2019 at the Clinical Hematology Unit, Ain Shams University hospitals, Egypt. MRD was assessed on the bone marrow samples using multi-parameter four color flow cytometry with 0.01% cut-off; below which cases are deemed MRD negative. RESULTS: After the end of induction period, 13 out of 46 patients (28%) had positive MRD. However, MRD positivity is demonstrable in 14/32(43.8%), and 10/28(35.7%) patients at 6 and 12 months; respectively. MRD positivity was significantly associated with older age group (more than 39 years) and high NCCN risk stratum with p-values <0.05. Moreover, most of MRD positive patients at 12 months of therapy were of T-ALL immunophenotype (P value 0.002).  Patients with complete remission and negative MRD exhibited significantly higher overall survival when compared to patients having MRD positivity (P value 0.027). CONCLUSION: MRD is a powerful predictor of outcome in ALL and its positivity at different time points is associated with poor prognostic factors as well as survival outcomes.

Forecasting daily new infections, deaths and recovery cases due to COVID-19 in Pakistan by using Bayesian Dynamic Linear Models.

The COVID-19 has caused the deadliest pandemic around the globe, emerged from the city of Wuhan, China by the end of 2019 and affected all continents of the world, with severe health implications and as well as financial-damage. Pakistan is also amongst the top badly effected countries in terms of casualties and financial loss due to COVID-19. By 20th March, 2021, Pakistan reported 623,135 total confirmed cases and 13,799 deaths. A state space model called 'Bayesian Dynamic Linear Model' (BDLM) was used for the forecast of daily new infections, deaths and recover cases regarding COVID-19. For the estimation of states of the models and forecasting new observations, the recursive Kalman filter was used. Twenty days ahead forecast show that the maximum number of new infections are 4,031 per day with 95% prediction interval (3,319-4,743). Death forecast shows that the maximum number of the deaths with 95% prediction interval are 81 and (67-93), respectively. Maximum daily recoveries are 3,464 with 95% prediction interval (2,887-5,423) in the next 20 days. The average number of new infections, deaths and recover cases are 3,282, 52 and 1,840, respectively, in the upcoming 20 days. As the data generation processes based on the latest data has been identified, therefore it can be updated with the availability of new data to provide latest forecast.