First Cycle Neutrophil Count and Subsequent Chemotherapy Dose Delivery in Breast Cancer Patients Receiving Adjuvant Chemotherapy

Background: Chemotherapy-induced neutropenia is a major dose-limiting toxicity of systemic cancer chemotherapy, and it is associated with substantial morbidity, mortality, and costs. The ability to predict the group of patients who are at high risk for neutropenic complications might help to reduce the morbidity due to febrile neutropenia and increase the likelihood of delivering full chemotherapy dose on time. In addition, hematopoietic growth factors could be administered to patients who need them and allow more efficient use of medical resources. Methods: The study included 120 female patients with breast cancer, treated in adjuvant setting with FAC chemotherapy regimen. Chemotherapy was delayed if the ANC was less than 1500 cells/μL on the planned first day of the cycle. Dose delays would be for 1 week. The chemotherapy dose was reduced if the patient experienced an episode of febrile neutropenia. Dose reductions usually consist of a 20% reduction in dosage of all chemotherapy drugs. Results: Out of the 120 patients in the study, 58 patients experienced neutropenic complications (febrile neutropenia or dose delayed) accounting for 48.3% of total sample size. In univariate analysis, there was statistically significant association between first cycle ANC nadir and neutropenic complication (p = 0.0001). There was also statistically significant association between pretreatment first cycle ANC (p = 0.001), pretreatment platelets count (p = 0.054), first cycle platelets count nadir (p = 0.041), number of involved lymph nodes (p = 0.031) and the occurrence of varies neutropenic complications. However, in multivariate analysis, ANC nadir was only the independent risk factor for occurrence of neutropenic. Conclusions: The first cycle absolute neutrophil counts nadir provides useful information on the risk of future neutropenia, febrile neutropenia and dose delay or reduction with estimated sensitivity and specificity, which were 64.5% and 77.6%, respectively. Other factors such as pretreatment absolute neutrophil count, number of involved LN, pretreatment platelet count and first cycle platelet nadir can be used to predict occurrence of neutropenic complications in breast cancer patients undergoing chemotherapy. Further studies are needed among different populations with different tumor types and different treatment regimens to confirm the results and explore other factors which may contribute to occurrence of neutropenic complications.

Production of Citric Acid from Corncobs with Its Biological Evaluation

Corncobs could serve as a substrate for citric acid production using solid state fermentation technique. The culture optimization concerning substrate concentration, culture duration, pH, temperature and substrate hydrolysis was carried out for maximum productivity of citric acid. Under the optimized conditions, 48.4 g of citric acid was produced from 1 kg dry corncobs. Biological evaluation was carried out for citric acid such as melanin synthesis inhibitory, anti-allergy, anti-bacterial, and hyaluronic acid production activities. The results showed that citric acid has potent melanin inhibitory activity, good inhibition for β-hexosaminidase release and potent stimulatory effect for the production of hyaluronic acid. These activities (melanin synthesis inhibitory, anti-allergy and hyaluronic acid productive activities) of citric acid have been reported for the first time.

Intelligent Deep Convolutional Neural Network Based Object DetectionModel for Visually Challenged People

Artificial Intelligence(AI)and Computer Vision(CV)advancements have led to many useful methodologies in recent years,particularly to help visually-challenged people.Object detection includes a variety of challenges,for example,handlingmultiple class images,images that get augmented when captured by a camera and so on.The test images include all these variants as well.These detection models alert them about their surroundings when they want to walk independently.This study compares four CNN-based pre-trainedmodels:ResidualNetwork(ResNet-50),Inception v3,DenseConvolutional Network(DenseNet-121),and SqueezeNet,predominantly used in image recognition applications.Based on the analysis performed on these test images,the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and speed.To further improve the performance of the Inception v3 model,the thermal exchange optimization(TEO)algorithm is applied to tune the hyperparameters(number of epochs,batch size,and learning rate)showing the novelty of the work.Better accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer,hyperparameter optimizer,and factorization approach.Additionally,Inception V3 can handle images of different sizes.This makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things(IoT)-based devices.

Melanin Biosynthesis Inhibitory Activity of Compounds Isolated from Unused Parts of <i>Ammi visinaga</i>

Ten compounds have been isolated from the unused parts of Ammi visinaga. The isolated compounds were identified as tetracosanoic acid (1), β-sitosterol (2), visnadine (3), khellin (4), β-sitosterol glucoside (5), norkhellol (6), khellol (7), rhamnazin (8), cimifugin (9), and cis-khellactone-3’-β-glucopyranoside (10). The chemical structures of these compounds were elucidated based on spectroscopic data (NMR, UV, MS and IR spectra). This is the first report on the identification of tetracosanoic acid (1), norkhellol (6) and cimifugin (9) in the Ammi genus. The melanin biosynthesis inhibitory activities of khellin (4), khellol (7), visnadine (3), cimifugin (9), β-sitosterol (2) and β-sitosterol glucoside (5) were evaluated. Khellin (4) exhibited a potent melanin inhibitory effect compared to arbutin with less toxicity.