Incidence and Survivability of Acute Lymphocytic Leukemia Patients in the United States: Analysis of SEER Data Set from 2000-2019

The main goal of this research is to assess the impact of race, age at diagnosis, sex, and phenotype on the incidence and survivability of acute lymphocytic leukemia (ALL) among patients in the United States. By taking these factors into account, the study aims to explore how existing cancer registry data can aid in the early detection and effective treatment of ALL in patients. Our hypothesis was that statistically significant correlations exist between race, age at which patients were diagnosed, sex, and phenotype of the ALL patients, and their rate of incidence and survivability data were evaluated using SEER*Stat statistical software from National Cancer Institute. Analysis of the incidence data revealed that a higher prevalence of ALL was among the Caucasian population. The majority of ALL cases (59%) occurred in patients aged between 0 to 19 years at the time of diagnosis, and 56% of the affected individuals were male. The B-cell phenotype was predominantly associated with ALL cases (73%). When analyzing survivability data, it was observed that the 5-year survival rates slightly exceeded the 10-year survival rates for the respective demographics. Survivability rates of African Americans patients were the lowest compared to Caucasian, Asian, Pacific Islanders, Alaskan Native, Native Americans and others. Survivability rates progressively decreased for older patients. Moreover, this study investigated the typical treatment methods applied to ALL patients, mainly comprising chemotherapy, with occasional supplementation of radiation therapy as required. The study demonstrated the considerable efficacy of chemotherapy in enhancing patients’ chances of survival, while those who remained untreated faced a less favorable prognosis from the disease. Although a significant amount of data and information exists, this study can help doctors in the future by diagnosing patients with certain characteristics. It will further assist the health care professionals in screening potential patients and early detection of cases. This could also save the lives of elderly patients who have a higher mortality rate from this disease.

Exploring emerald global geochemical provenance through fingerprinting and machine learning methods

Emeralds-the green colored variety of beryl-occur as gem-quality specimens in over fifty deposits globally.While digital traceability methods for emerald have limitations,sample-based approaches offer robust alterna-tives,particularly for determining the geographic origin of emerald.Three factors make emerald suitable for provenance studies and hence for developing models for origin determination.First,the diverse elemental chemistry of emerald at minor(<1 wt%)and trace levels(<1 to 100’s ppmw)exhibits unique inter-element fractionations between global deposits.Second,minimally destructive techniques,including laser ablation inductively coupled plasma mass spectrometry(LA-ICP-MS),enable measurement of these diagnostic elemental signatures.Third,when applied to extensive datasets,machine learning(ML)techniques enable the creation of predictive models and statistical discrimination with adequate characterization of the deposits.This study em-ploys a carefully selected dataset comprising more than 1000 LA-ICP-MS analyses of gem-quality emeralds,enriched with new analyses.This dataset represents the largest available for global emerald deposits.We con-ducted unsupervised exploratory analysis using Principal Component Analysis(PCA).For machine learning-based classification,we employed Support Vector Machine Classification(SVM-C),achieving an initial accu-racy rate of 79%.This was enhanced to 96.8%through the use of hierarchical SVM-C with PCA filters as our modeling approach.The ML models were trained using the concentrations of eight statistically significant ele-ments(Li,V,Cr,Fe,Sc,Ga,Rb,Cs).By leveraging high-quality LA-ICP-MS data and ML techniques,accurate identification of the geographical origin of emerald becomes possible.These models are important for accurate provenance of emerald,and from a geochemical perspective,for understanding the formation environments of beryl-bearing pegmatites and shales.

Malaria over-diagnosis in Cameroon:diagnostic accuracy of Fluorescence and Staining Technologies(FAST)Malaria Stain and LED microscopy versus Giemsa and bright field microscopy validated by polymerase chain reaction

Background:Malaria is a major world health issue and its continued burden is due,in part,to difficulties in the diagnosis of the illness.The World Health Organization recommends confirmatory testing using microscopy-based techniques or rapid diagnostic tests(RDT)for all cases of suspected malaria.In regions where Plasmodium species are indigenous,there are multiple etiologies of fever leading to misdiagnoses,especially in populations where HIV is prevalent and children.To determine the frequency of malaria infection in febrile patients over an 8-month period at the Regional Hospital in Bamenda,Cameroon,we evaluated the clinical efficacy of the Flourescence and Staining Technology(FAST)Malaria stain and ParaLens AdvanceTM microscopy system(FM)and compared it with conventional bright field microscopy and Giemsa stain(GS).Methods:Peripheral blood samples from 522 patients with a clinical diagnosis of“suspected malaria”were evaluated using GS and FM methods.A nested PCR assay was the gold standard to compare the two methods.PCR positivity,sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV)were determined.Results:Four hundred ninety nine samples were included in the final analysis.Of these,30 were positive via PCR(6.01%)with a mean PPV of 19.62%and 27.99%for GS and FM,respectively.The mean NPV was 95.01%and 95.28%for GS and FM,respectively.Sensitivity was 26.67%in both groups and specificity was 92.78%and 96.21%for GS and FM,respectively.An increased level of diagnostic discrepancy was observed between technicians based upon skill level using GS,which was not seen with FM.Conclusions:The frequency of malarial infections confirmed via PCR among patients presenting with fever and other symptoms of malaria was dramatically lower than that anticipated based upon physicians’clinical suspicions.A correlation between technician skill and accuracy of malaria diagnosis using GS was observed that was less pronounced using FM.Additionally,FM increased the specificity and improved the PPV,suggesting this relatively low cost approach could be useful in resource-limited environments.Anecdotally,physicians were reluctant to not treat all patients symptomatically before results were known and in spite of a negative microscopic diagnosis,highlighting the need for further physician education to avoid this practice of overtreatment.A larger study in an area with a known high prevalence is being planned to compare the two microscopy methods against available RDTs.