Fate of Cryptosporidium and Giardia through conventional and compact drinking water treatment plants.

Over the past three decades, a notable rise in the occurrence of enteric protozoan pathogens, especially Giardia and Cryptosporidium spp., in drinking water sources has been observed. This rise could be attributed not only to an actual increase in water contamination but also to improvements in detection methods. These waterborne pathogens have played a pivotal role in disease outbreaks and the overall escalation of disease rates in both developed and developing nations worldwide. Consequently, the control of waterborne diseases has become a vital component of public health policies and a primary objective of drinking water treatment plants (DWTPs). Limited studies applied real-time PCR (qPCR) and/or immunofluorescence assay (IFA) for monitoring Giardia and Cryptosporidium spp., particularly in developing countries like Egypt. Water samples from two conventional drinking water treatment plants and two compact units (CUs) were analyzed using both IFA and qPCR methods to detect Giardia and Cryptosporidium. Using qPCR and IFA, the conventional DWTPs showed complete removal of Giardia and Cryptosporidium, whereas Mansheyat Alqanater and Niklah CUs achieved only partial removal. Specifically, Cryptosporidium gene copies removal rates were 33.33% and 60% for Mansheyat Alqanater and Niklah CUs, respectively. Niklah CU also removed 50% of Giardia gene copies, but no Giardia gene copies were removed by Mansheyat Alqanater CU. Using IFA, both Mansheyat Alqanater and Niklah CUs showed a similar removal rate of 50% for Giardia cysts. Additionally, Niklah CU achieved a 50% removal of Cryptosporidium oocysts, whereas Mansheyat Alqanater CU did not show any removal of Cryptosporidium oocysts. Conventional DWTPs were more effective than CUs in removing enteric protozoa. The contamination of drinking water by enteric pathogenic protozoa remains a significant issue globally, leading to increased disease rates. Infectious disease surveillance in drinking water is an important epidemiological tool to monitor the health of a population.

On the significance of fuzzification of the N and m in cancer staging.

The tumor, node, metastasis (TNM) staging system has been regarded as one of the most widely used staging systems for solid cancer. The "T" is assigned a value according to the primary tumor size, whereas the "N" and "M" are dependent on the number of regional lymph nodes and the presence of distant metastasis, respectively. The current TNM model classifies stages into five crisp classes. This is unrealistic since the drastic modification in treatment that is based on a change in one class may be based on a slight shift around the class boundary. Moreover, the system considers any tumor that has distant metastasis as stage 4, disregarding the metastatic lesion concentration and size. We had handled the problem of T staging in previous studies using fuzzy logic. In this study, we focus on the fuzzification of N and M staging for more accurate and realistic modeling which may, in turn, lead to better treatment and medical decisions.