Which factors help to determine the long-term response to first-line tyrosine kinase inhibitors in patients with metastatic renal cell carcinoma: A Turkish multi-centre study.

Many developing countries lack access to recommended first-line treatments for metastatic renal cell carcinoma (mRCC), such as immune checkpoint inhibitors (ICIs) or ICI-tyrosine kinase inhibitor (TKI) combinations. As a result, predictive markers are necessary to identify patients who may benefit from single-agent TKIs for long-term response. This study aims to identify such parameters. This was a multi-centre, retrospective study of patients with mRCC who were undergoing first-line treatment with sunitinib or pazopanib. Patients who had been diagnosed with mRCC and had not experienced disease progression for 36 months or more were deemed to have achieved a long-term response. Predictive clinical and pathological characteristics of patients who did not experience long-term disease progression were investigated. A total of 320 patients from four hospitals were included in the study. The median age of the patients was 60 years (range 20-89 years). According to the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk classification, 109 patients were classified as having favourable risk and 211 were in the intermediate-poor risk group. The median progression-free survival (PFS) and overall survival (OS) for all patients were 12.5 months and 76.4 months, respectively. In the long-term responder's group, the median PFS was 78.4 months. Among all patients, prior nephrectomy, the Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) <1, and the absence of brain metastasis were predictive factors for long-term response. For patients in the favourable risk group, the lack of brain metastasis was a predictor of long-term response. In the intermediate-poor risk group, prior nephrectomy and ECOG PS <1 were predictive factors for long-term response. Some individuals with mRCC may experience a durable response to TKIs. The likelihood of a long-term response can be determined by factors such as nephrectomy, ECOG PS < 1, and the absence of brain metastases.

The effect of parity, breastfeeding history, and duration on clinical and pathological characteristics of breast cancer patients.

Background/aim: The study is aimed to determine the relationship between the delivery and breastfeeding history of the patients and the clinicopathological properties of breast cancer. Materials and methods: A questionnaire was utilized for the study, which included the age of diagnosis, the number of children at the time of diagnosis, the age of the children, and the breastfeeding period of each child. Results: The study included 828 patients. The median age at diagnosis was 47 years for parous women and 42 years for nonparous women (p < 0.001). The tumor size of the patients diagnosed within the breastfeeding period was significantly larger compared to the other patients. Estrogen and progesterone receptor positivity were lower in patients diagnosed during breastfeeding. Additionally, the mean number of positive lymph nodes, dissected lymph nodes, and positive lymph node/dissected lymph node ratio in parous and breastfed patients with a nonmetastatic disease were statistically significantly higher in multivariable analysis than those patients who were nulliparous and have not breastfed. Conclusion: Breast cancer is seen at a later age in patients who are parous than those who have never given birth. Patients who are parous and have breastfed tend to present with a higher stage of the disease.

Clinicopathologic Features and Efficacy of Induction Chemotherapy in Nasopharyngeal Carcinoma: Real-World Experience.

INTRODUCTION: Nasopharyngeal carcinoma (NPC) accounts for 0.01% of all carcinomas, and 70% of patients have locally advanced disease with a poor prognosis. The mainstay therapy is chemoradiotherapy (CRT), and concurrent administration of platinum-based agents and irradiation provides high local control rates. However, induction (neoadjuvant) chemotherapy (ICT) prior to CRT is recommended for large tumors with a high tumor burden at the category 1 level. For ICT, platinum-based doublet or triplet combination regimens are recommended. Selected patients with a high tumor burden at the time of diagnosis who did not receive ICT before CRT were given adjuvant (consolidation) therapy after CRT. This multicenter study aimed to share our experience in treatment of NPC and evaluate the factors associated with survival. METHODS: The study included patients diagnosed with NPC who were followed and treated between 2008 and 2022. Hundred and forty-two patients from 6 centers were evaluated. The factors associated with disease-free survival (DFS) and overall survival (OS) were evaluated. RESULTS: The median age of our patients was 51 years (IQR: 16-81 years), and the male:female ratio was 2.5:1. A majority of patients (71%) had stage 3-4 disease. They had locally advanced disease, and 48 patients (34%) received ICT. Twenty patients (14%) received adjuvant therapy. The median follow-up was 41 months (range, 2.7-175.1 months). The median DFS in NPC was 92.6 months (range, 71.9-113.3 months), with a 40th month DFS of 70.9%. The median OS was 113 months (range, 91-135 months), with a 40th month OS of 84.7%. Median DFS was 95.3 months (range, 64.2-126.4 months) in patients who received ICT before CRT, which was longer than in the CRT-only group (p = 0.6). DFS at the 40th month was 75.1% in patients treated with ICT compared to 65.1% in the CRT-only group. Median OS was 117 months (range, 92-142 months) in patients receiving ICT, which was longer than in the CRT-only group (p = 0.4). OS at the 40th month was 86.7% in patients receiving ICT but 83.6% in the CRT-only group. CONCLUSIONS: Both the objective response rate and survival were longer in patients who radiologically responded to CRT following ICT. Nonresponse to ICT is a negative predictive indicator. The role of ICT in locally advanced NPC is increasing.

Mathematical modelling of antibiotic interaction on evolution of antibiotic resistance: an analytical approach.

Background: The emergence and spread of antibiotic-resistant pathogens have led to the exploration of antibiotic combinations to enhance clinical effectiveness and counter resistance development. Synergistic and antagonistic interactions between antibiotics can intensify or diminish the combined therapy's impact. Moreover, these interactions can evolve as bacteria transition from wildtype to mutant (resistant) strains. Experimental studies have shown that the antagonistically interacting antibiotics against wildtype bacteria slow down the evolution of resistance. Interestingly, other studies have shown that antibiotics that interact antagonistically against mutants accelerate resistance. However, it is unclear if the beneficial effect of antagonism in the wildtype bacteria is more critical than the detrimental effect of antagonism in the mutants. This study aims to illuminate the importance of antibiotic interactions against wildtype bacteria and mutants on the deacceleration of antimicrobial resistance. Methods: To address this, we developed and analyzed a mathematical model that explores the population dynamics of wildtype and mutant bacteria under the influence of interacting antibiotics. The model investigates the relationship between synergistic and antagonistic antibiotic interactions with respect to the growth rate of mutant bacteria acquiring resistance. Stability analysis was conducted for equilibrium points representing bacteria-free conditions, all-mutant scenarios, and coexistence of both types. Numerical simulations corroborated the analytical findings, illustrating the temporal dynamics of wildtype and mutant bacteria under different combination therapies. Results: Our analysis provides analytical clarification and numerical validation that antibiotic interactions against wildtype bacteria exert a more significant effect on reducing the rate of resistance development than interactions against mutants. Specifically, our findings highlight the crucial role of antagonistic antibiotic interactions against wildtype bacteria in slowing the growth rate of resistant mutants. In contrast, antagonistic interactions against mutants only marginally affect resistance evolution and may even accelerate it. Conclusion: Our results emphasize the importance of considering the nature of antibiotic interactions against wildtype bacteria rather than mutants when aiming to slow down the acquisition of antibiotic resistance.

The Effectiveness of Adjuvant PD-1 Inhibitors in Patients With Surgically Resected Stage III/IV Acral Melanoma.

Our aim was to assess the efficacy of adjuvant programmed cell death protein-1 (PD-1) inhibitors and compare the other adjuvant treatments in patients with surgically resected stage III or IV acral melanoma. This study is a multicenter, retrospective analysis. We included 114 patients with stage III or IV acral malignant melanoma who underwent surgery within the past 10 years. We analyzed the effect of adjuvant programmed cell death protein-1 inhibitors on disease-free survival (DFS). The mean follow-up was 40 months, during which 69 (59.5%) patients experienced recurrence. Among the participants, 64 (56.1%) received systemic adjuvant therapy. Specifically, 48.4% received anti-PD-1 therapy, 29.7% received interferon, 14.1% received tezozolomide, and 7.8% received B-Raf proto-oncogene/mitogen-activated protein kinase inhibitors. Patients who received adjuvant therapy had a median DFS of 24 (10.9-37.2) months, whereas those who did not receive adjuvant therapy had a median DFS of 15 (9.8-20.2) months. Multivariate analysis for DFS revealed that the receipt of adjuvant therapy and lymph node metastasis stage were independent significant parameters ( P = 0.021, P = 0.018, respectively). No statistically significant difference was observed for DFS between programmed cell death protein-1 inhibitor treatment and other adjuvant treatments. Regarding overall survival (OS), patients who received adjuvant treatment had a median OS of 71 (30.4-111.7) months, whereas those who did not receive adjuvant treatment had a median OS of 38 (16.7-59.3; P = 0.023) months. In addition, there were no significant differences in OS observed between various adjuvant treatment agents ( P = 0.122). In our study, we have shown that adjuvant therapy had a positive effect on both DFS and OS in patients with stages III-IV acral melanoma who underwent curative intent surgery. Notably, we found no significant differences between anti-PD-1 therapy and other adjuvant therapies.

The prognostic factors in patients with advanced hepatocellular carcinoma: impact of treatment sequencing.

The prognosis of patients with advanced HCC can vary widely depending on factors such as the stage of the cancer, the patient's overall health, and treatment regimens. This study aimed to investigate survival outcomes and associated factors in patients with hepatocellular carcinoma (HCC). In this retrospective study, data from 23 medical oncology clinics were analyzed. Progression-free survival (PFS) and overall survival (OS) values were estimated using the Kaplan-Meier method. Prognostic factors associated with survival which were identified in univariate analysis were subsequently evaluated in a multivariate Cox-regression survival analysis was conducted using the backward stepwise (Conditional LR) method to determine the independent predictors of PFS and OS. Of 280 patients, 131 received chemotherapy and 142 received sorafenib, 6 received atezolizumab plus bevacizumab and 1 received nivolumab for first-line setting. The median follow-up time was 30.4 (95%CI 27.1-33.6) months. For-first line, median PFS was 3.1 (95%CI2.7-3.5) months, and it was significantly longer in patients who received sorafenib or atezolizumab-bevacizumab or nivolumab (PFS 5.8 (95%CI 4.2-7.5) than in those received chemotherapy (PFS 2.1 (95%CI 1.9-2.3) in the first-line setting (p < 0.001). Multivariate analysis revealed that male gender (HR: 2.75, 95% CI: 1.53-4.94, p = 0.01), poor ECOG performance score (HR: 1.88, 95% CI: 1.10-3.21, p = 0.02), higher baseline AFP level (HR: 2.38, 95% CI: 1.54-3.67, p < 0.001) and upfront sorafenib treatment (HR,0.38; 95% CI: 0.23-0.62, p < 0.001) were significantly associated with shorter PFS. The median OS was 13.2 (95%CI 11.1-15.2) months. It was significantly longer in patients who received sorafenib or atezolizumab-bevacizumab or nivolumab in the first-line setting followed by TKIs (sorafenib or regorafenib, OS 18.6 (95%CI 13.8-23.5)) compared to those who received chemotherapy (OS 10.3 (95%CI 6.6-14.1)) in the first-line setting. The multivariate analysis revealed that upfront chemotherapy treatment approach, male gender (HR: 1.77, 95% CI: 1.07-2.94, p = 0.02), poor ECOG performance score (HR: 1.96, 95% CI: 1.24-3.09, p = 0.004) and Child-Pugh score, presence of extrahepatic disease (HR: 1.54, 95% CI: 1.09-2.18, p = 0.01), and higher baseline AFP value (HR: 1.50, 95% CI: 1.03-2.19, p = 0.03) were significantly associated with poor prognosis. Additionally, regarding of treatment sequence, upfront sorafenib followed by regorafenib showed a significantly lower risk of mortality (HR: 0.40, 95% CI: 0.25-0.66, p < 0.001). Sorafenib followed by regorafenib treatment was associated with a significantly lower risk of mortality rather than upfront sorafenib followed by BSC group or upfront chemotherapy followed by TKIs. These findings underscore the importance of the optimal treatment sequences to improve survival in patients with advanced HCC.

PNI as a Potential Add-On Biomarker to Improve the IMDC Intermediate Prognostic Score.

INTRODUCTION: This study aimed to assess the role of the adjusted PNI-IMDC risk scoring system in stratifying the intermediate group of metastatic RCC patients who received TKIS in the first-line setting. METHODS: A total of 185 patients were included. The adjusted PNI and IMDC model was used to divide the intermediate group into two groups: intermediate PNI-high and intermediate PNI-low groups. The statistical data were analyzed using Kaplan-Meier and Cox regression analysis. RESULTS: The results showed that the adjusted PNI-IMDC risk score, classic IMDC, and PNI had similar prognostic values. Adjusted PNI-IMDC risk score might be used for a more homogeneous differentiation of the classic intermediate group. On the other hand, multivariate analysis revealed that the presence of nephrectomy, adjusted favorable/intermediate (PNI-high) group, ECOG performance score, and presence of bone metastasis were independent predictors of OS. CONCLUSIONS: Pre-treatment PNI, as a valuable and potential add-on biomarker to the adjusted PNI-IMDC classification model, can be helpful for establishing an improved prognostic model for intermediate group mRCC patients treated with first-line TKISs. Further validation studies are needed to clarify these findings.

Syrian Refugee and Turkish Women with Breast Cancer: A Comparison on Clinicopathological Features and Survival.

BACKGROUND: Cancer is a significant health problem for refugees and host countries. Breast cancer is the most common cancer among refugees. The subject of our study is to examine the clinical and pathological features of Syrian refugees with breast cancer and compare them with Turkish patients with breast cancer. METHODS: Data of patients with breast cancer between January 2018 and December 2020 were retrospectively reviewed. The clinical and histological features, treatment modalities and overall survival were collected and analyzed. RESULTS: A total number of 338 women with breast cancer were included in this study. Ninety-nine of the 338 (29.3%) patients were Syrian refugees and 239 patients (70.7%) were Turkish. The median follow-up time was significantly lower in Syrian patients (P<0.001). Median OS was 146 months in Turkish and 116 months in Syrian group (P=0.022). Independent risk factors associated with long survival were receiving adjuvant chemotherapy (HR 0.465; 95% CI 0.234-0.926; P=0.029), adjuvant radiotherapy (HR 0.372 95% CI 0.182-0.758; P=0.007), and adjuvant hormonotherapy (HR 0.367; 95% CI 0.201-0.669; P=0.001). The rates of receiving adjuvant chemotherapy, adjuvant radiotherapy, and adjuvant hormonal therapy were significantly lower in the Syrian group (P=0.023, P=0.005, P=0.002, respectively). CONCLUSION: Syrian refugees with breast cancer are more likely to receive suboptimal treatments. They have inferior survival compared to local patients. Our findings highlight the need for the provision of cancer therapy in such vulnerable populations. We suggest that more attention should be paid to breast cancer, as it is the most common cancer among refugees.

The effect of low HER2 expression on treatment outcomes in metastatic hormone receptor positive breast cancer patients treated with a combination of a CDK4/6 inhibitor and endocrine therapy: A multicentric retrospective study.

BACKGROUND: CDK4/6 inhibitors combined with endocrine therapy have significantly improved treatment outcomes for metastatic hormone receptor-positive (HR+) breast cancer patients. However, the impact of low HER2 expression on treatment response and progression-free survival (PFS) remains unclear. METHODS: This multicenter retrospective study included 204 HR+ breast cancer patients treated with a combination of CDK4/6 inhibitor and endocrine therapy. HER2-zero disease was detected in 138 (68%) and HER2-low disease in 66 (32%) patients. Treatment-related characteristics and clinical outcomes were analyzed, with a median follow-up of 22 months. RESULTS: The objective response rate (ORR) was 72.7% in the HER2 low group and 66.6% in the HER2 zero group (p = 0.54). Median PFS was not significantly different between the HER2-low and HER2 zero groups (19 months vs.18 months, p = 0.89), although there was a trend toward longer PFS in the HER2-low group for first-line treatment (24 months progression-free survival rate 63% vs 49%). In recurrent disease, the median PFS was 25 months in the HER2-low group and 12 months in the HER2-zero group (p = 0.08), while in de novo metastatic disease, the median PFS was 18 months in the HER2-low group and 27 months in the HER2-zero group (p = 0.16). The order of CDK4/6 inhibitor use and the presence of visceral metastasis were identified as independent variables affecting PFS. CONCLUSION: Low HER2 expression did not significantly impact treatment response or PFS in HR+ breast cancer patients treated with a CDK4/6 inhibitor and endocrine therapy. Because of the conflicting results in the literature, further prospective studies are needed to evaluate the clinical significance of HER2 expression in HR+ breast cancer.

Effect of sojourn time distributions on the early dynamics of COVID-19 outbreak.

Compartmental models are commonly used in practice to investigate the dynamical response of infectious diseases such as the COVID-19 outbreak. Such models generally assume exponentially distributed latency and infectiousness periods. However, the exponential distribution assumption fails when the sojourn times are expected to distribute around their means. This study aims to derive a novel S (Susceptible)-E (Exposed)-P (Presymptomatic)-A (Asymptomatic)-D (Symptomatic)-C (Reported) model with arbitrarily distributed latency, presymptomatic infectiousness, asymptomatic infectiousness, and symptomatic infectiousness periods. The SEPADC model is represented by nonlinear Volterra integral equations that generalize ordinary differential equation-based models. Our primary aim is the derivation of a general relation between intrinsic growth rate r and basic reproduction number R0 with the help of the well-known Lotka-Euler equation. The resulting r-R0 equation includes separate roles of various stages of the infection and their sojourn time distributions. We show that R0 estimates are considerably affected by the choice of the sojourn time distributions for relatively higher values of r. The well-known exponential distribution assumption has led to the underestimation of R0 values for most of the countries. Exponential and delta-distributed sojourn times have been shown to yield lower and upper bounds of the R0 values depending on the r values. In quantitative experiments, R0 values of 152 countries around the world were estimated through our novel formulae utilizing the parameter values and sojourn time distributions of the COVID-19 pandemic. The global convergence, R0=4.58, has been estimated through our novel formulation. Additionally, we have shown that increasing the shape parameter of the Erlang distributed sojourn times increases the skewness of the epidemic curves in entire dynamics.

Forecasting contamination in an ecosystem based on a network model.

This paper aims to predict heavy metal pollution based on ecological factors with a new approach, using artificial neural networks (ANNs), by significantly removing typical obstacles like time-consuming laboratory procedures and high implementation costs. Pollution prediction is crucial for the safety of all living things, for sustainable development, and for policymakers to make the right decisions. This study focuses on predicting heavy metal contamination in an ecosystem at a significantly lower cost because pollution assessment still primarily relies on conventional methods, which are recognized to have disadvantages. To accomplish this, the data collected for 800 plant and soil materials have been utilized in the production of an ANN. This research is the first to use an ANN to predict pollution very accurately and has found the network models to be very suitable systemic tools for modelling in pollution data analysis. The findings appear are promising to be very illuminating and pioneering for scientists, conservationists, and governments to swiftly and optimally develop their appropriate work programs to leave a functioning ecosystem for all living things. It has been observed that the relative errors calculated for each of the polluting heavy metals for training, testing, and holdout data are significantly low.

Machine learning aided multiscale modelling of the HIV-1 infection in the presence of NRTI therapy.

Human Immunodeficiency Virus (HIV) is one of the most common chronic infectious diseases in humans. Extending the expected lifetime of patients depends on the use of optimal antiretroviral therapies. Emergence of the drug-resistant strains can reduce the effectiveness of treatments and lead to Acquired Immunodeficiency Syndrome (AIDS), even with antiretroviral therapy. Investigating the genotype-phenotype relationship is a crucial process for optimizing the therapy protocols of the patients. Here, a mathematical modelling framework is proposed to address the impact of existing mutations, timing of initiation, and adherence levels of nucleotide reverse transcriptase inhibitors (NRTIs) on the evolutionary dynamics of the virus strains. For the first time, the existing Stanford HIV drug resistance data have been combined with a multi-strain within-host ordinary differential equation (ODE) model to track the dynamics of the most common NRTI-resistant strains. Overall, the D4T-3TC, D4T-AZT and TDF-D4T drug combinations have been shown to provide higher success rates in preventing treatment failure and further drug resistance. The results are in line with the genotype-phenotype data and pharmacokinetic parameters of the NRTI inhibitors. Moreover, we show that the undetectable mutant strains at the diagnosis have a significant effect on the success/failure rates of the NRTI treatments. Predictions on undetectable strains through our multi-strain within-host model yielded the possible role of viral evolution on the treatment outcomes. It has been recognized that the improvement of multi-scale models can contribute to the understanding of the evolutionary dynamics, and treatment options, and potentially increase the reliability of genotype-phenotype models.

Prediction of HIV-1 protease resistance using genotypic, phenotypic, and molecular information with artificial neural networks.

Drug resistance is a primary barrier to effective treatments of HIV/AIDS. Calculating quantitative relations between genotype and phenotype observations for each inhibitor with cell-based assays requires time and money-consuming experiments. Machine learning models are good options for tackling these problems by generalizing the available data with suitable linear or nonlinear mappings. The main aim of this study is to construct drug isolate fold (DIF) change-based artificial neural network (ANN) models for estimating the resistance potential of molecules inhibiting the HIV-1 protease (PR) enzyme. Throughout the study, seven of eight protease inhibitors (PIs) have been included in the training set and the remaining ones in the test set. We have obtained 11,803 genotype-phenotype data points for eight PIs from Stanford HIV drug resistance database. Using the leave-one-out (LVO) procedure, eight ANN models have been produced to measure the learning capacity of models from the descriptors of the inhibitors. Mean R2 value of eight ANN models for unseen inhibitors is 0.716, and the 95% confidence interval (CI) is [0.592-0.840]. Predicting the fold change resistance for hundreds of isolates allowed a robust comparison of drug pairs. These eight models have predicted the drug resistance tendencies of each inhibitor pair with the mean 2D correlation coefficient of 0.933 and 95% CI [0.930-0.938]. A classification problem has been created to predict the ordered relationship of the PIs, and the mean accuracy, sensitivity, specificity, and Matthews correlation coefficient (MCC) values are calculated as 0.954, 0.791, 0.791, and 0.688, respectively. Furthermore, we have created an external test dataset consisting of 51 unique known HIV-1 PR inhibitors and 87 genotype-phenotype relations. Our developed ANN model has accuracy and area under the curve (AUC) values of 0.749 and 0.818 to predict the ordered relationships of molecules on the same strain for the external dataset. The currently derived ANN models can accurately predict the drug resistance tendencies of PI pairs. This observation could help test new inhibitors with various isolates.

Effects of kangaroo mother care on feeding intolerance in preterm infants.

OBJECTIVE: Feeding intolerance (FI) is a common condition in preterm infants because they have an immature gastrointestinal tract. There are studies on the effects of the position on gastric residual volume (GRV) in preterm infants. Kangaroo mother care (KMC) may be an instrument for reducing FI by providing an upright position to infants. Moreover, numerous studies conducted with this therapeutic position applied by putting an infant on the mother's chest have indicated its positive effects on the infant's weight gain, growth and development, and vital signs. Therefore, this study aimed to reveal the impact of KMC on FI in preterm infants. METHODS: The population of the study, designed as a randomized trial, consisted of 168 preterm infants [KMC: 84, Standart Care (SC): 84] hospitalized in the neonatal intensive care unit of a university hospital between June and November 2020. Infants were randomly selected and divided into two groups. After the vital signs of the infants in both groups became stable, the infants were fed in the same position. KMC was applied to the infants in the intervention group for 1 h by preparing a suitable environment after feeding. Infants in the SC group were placed in the prone position after feeding. The GRVs of the infants in both groups were recorded on the Infant Follow-up Form before the next feeding. RESULTS: No statistically significant difference was detected between the groups upon comparing them in terms of demographic and clinical characteristics. The body temperatures and O2 saturations of the participants in the KMC group were statistically significantly higher, and their respiratory and heart rates were lower than the SC group. The transition time to full enteral feeding was statistically significantly shorter, and FI was experienced significantly less in the KMC group infants than in the SC group (p < 0.05). There was no statistically significant difference between the groups in terms of the infants' weight gain and length of hospital stay (p > 0.05). CONCLUSION: The present study demonstrated that KMC had a positive impact on FI in preterm infants. KMC is not only a safe care model providing the earliest contact between parents and infants but also a practice whose positive effect on the functioning of the digestive system in preterm infants we can use.

An investigation on environmental pollution due to essential heavy metals: a prediction model through multilayer perceptrons.

This research is to predict heavy metal levels in plants, particularly in Robinia pseudoacacia L., and soils using an effective artificial intelligence approach with some ecological parameters, thereby significantly eliminating common defects such as high cost and seriously tedious and time-consuming laboratory procedures. In this respect, the artificial neural network (ANN) is employed to estimate the concentrations of essential heavy metals such as Fe, Mn and Ni, depending on the Cu and Zn concentrations of plant and soil samples collected from five different locations. The derived relative errors for the constructed ANN model have been computed within the ranges 0.041-0.051, 0.017-0.025, and 0.026-0.029 for the training, testing and holdout data regarding Fe, Mn, and Ni, respectively. In addition, it has been realized that the relative errors could be diminished up to 0.007 for Fe, 0.014 for Mn and 0.022 for Ni by considering the Cu, Zn, location and plant parts as independent variables during the analysis. The results produced seem instructive and pioneering for environmentalists and scientists to design optimal study programs to leave a livable ecosystem.

The levels of essential heavy metals, Fe, Mn, Ni, based on Zn and Cu in plant and soil samples have been predicted through an AI-based prediction model, a class of feedforward artificial neural networks (ANNs) with a multilayer perceptron (MLP). Thereby common drawbacks such as high cost and severely time-consuming laboratory procedures have been significantly eradicated. In the evaluation of different pollution levels at locations, it has been shown that the ANN method can overcome several disadvantages of analytical element analyzers to monitor the amounts of heavy metals such as Fe, Mn, and Ni in soil and plants.

Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics.

Background: Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of pandemics such as COVID-19. Methods: To achieve this, we have developed an agent based model based on a time-dynamic graph with stochastic transmission events. The graph is constructed from a real-world social network. The edges of graph have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type COVID-19 and the delta variant have been analyzed. Our purposeful agent based model has carefully executed tens of thousands of individual-based simulations. We propose simple relationships for the trade-offs between effective reproduction number (R e), transmission rate, working hours, vaccination, and stay-at-home restrictions. Results: We have found that the effect of a 13.6% increase in vaccination for wild-type (WT) COVID-19 is equivalent to reducing four hours of work or a one-day stay-at-home restriction. For the delta, 20.2% vaccination has the same effect. Also, since we can keep track of household and non-household infections, we observed that the change in household transmission rate does not significantly alter the R e. Household infections are not limited by transmission rate due to the high frequency of connections. For the specifications of COVID-19, the R e depends on the non-household transmissions rate. Conclusions: Our findings highlight that decreasing working hours is the least effective among the non-pharmaceutical interventions. Our results suggest that policymakers decrease work-related activities as a last resort and should probably not do so when the effects are minimal, as shown. Furthermore, the enforcement of stay-at-home restrictions is moderately effective and can be used in conjunction with other measures if absolutely necessary.

The effectiveness and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early-stage human epidermal growth factor receptor 2-positive breast cancer: Turkish Oncology Group study.

In our study, we aimed to evaluate the pathological response rates and side effect profile of adding pertuzumab to the treatment of HER2+ locally advanced, inflammatory, or early-stage breast cancer. This study was conducted by the Turkish Oncology Group (TOG) with data collected from 32 centers. Our study was multicentric, and a total of 364 patients were included. The median age of the patients was 49 years (18-85 years). Two hundred fifteen (60%) of the cases were hormone receptor/HER2+ positive(ER+ or PR+, or both), and 149 (40%) of them were HER2-rich (ER and PR negative). The number of complete responses was 124 (54%) in the docetaxel+trastuzumab+pertuzumab arm and 102 (45%) in the paclitaxel+trastuzumab+pertuzumab arm, and there was no difference between the groups in terms of complete response. In 226 (62%) patients with complete response, a significant correlation was found with DCIS, tumor focality, removed lymph node, and ER status P < 0.05. Anemia, nausea, vomiting, myalgia, alopecia, and mucosal inflammation were significantly higher in the docetaxel arm, P < 0.05. In our study, no statistical difference was found between the before-after echocardiography values. DCIS positivity in biopsy before neoadjuvant chemotherapy, tumor focality; the number of lymph nodes removed and ER status were found to be associated with pCR. In conclusion, we think that studies evaluating pCR-related clinicopathological variables and radiological imaging features will play a critical role in the development of nonsurgical treatment approaches.

Deficient Mismatch Repair and Lymphocytic Response to Tumor as Prognostic Markers in Stage II Colon Cancer Patients.

OBJECTIVE: To investigate the relationship between colon cancer (CC) subtypes defined by the status of tumor-infiltrating lymphocytes (TIL) and mismatch repair (MMR) combination with clinicopathological features and survival. STUDY DESIGN: Observational study. PLACE AND DURATION OF STUDY: Department of Medical Oncology, Haydarpasa Numune Research and Training Hospital, Istanbul, Turkey, from July 2010 to March 2020. METHODOLOGY: Eighty-three patients with operated stage II colon cancer were included in the study. Pathology, surgery and oncological treatment and follow-up information were obtained from patient files; and statistical analyses were performed on overall survival (OS). Tumor-infiltrating lymphocytes and mismatch repair status was determined with the help of immunohistochemistry. RESULTS: TIL-high and deficient MMR (dMMR) status were detected in 26 patients (31.3%) and 21 patients (25.3%), respectively. Tumors were divided into four subgroups according to TIL and MMR status. TIL-high/dMMR tumors had the most favourable prognosis, while TIL-low/proficient MMR tumors exhibited poor OS. CONCLUSION: The combination of TIL and MMR could enable us to differentiate patients' survival outcomes in more details. Therefore, considering that the TIL and MMR status, evaluated by IHC, may be a cost-effective and effective option for risk classification in patients with stage II colon cancer. Key Word: Lymphocytic response, Mismatch repair, Prognosis, Tumor-infiltrating lymphocytes, Stage II cancer, Colon cancer.

The Effect of FDG-PET/CT on Clinical Prognostic Staging of Breast Cancer Patients being Planned Neoadjuvant Treatment.

OBJECTIVE: To evaluate the effect of FDG-PET/CT in the radiological imaging of breast cancer (BC) patients planned for neoadjuvant treatment (NAT), on the clinical prognostic stage (CPS). STUDY DESIGN: A descriptive study. PLACE AND DURATION OF STUDY: Haydarpasa Numune Training and Research Hospital, Istanbul, Turkey, between June 2014 and September 2020. METHODOLOGY: Consecutive patients with stage I-III breast cancer (BC) who were planned for neoadjuvant treatment (NAT). The distribution of CPS detected by both conventional radiological methods (c-CPS) and FDG-PET/CT (PET-CPS) were compared. RESULTS: Significant upstaging on CPS was detected with the addition of FDG-PET/CT to conventional imaging methods in 25/121 (20.7%) patients (p <0.001). In the c-CPS stage, IB, IIA, IIB, IIIA, IIIB patients, the stage change rate was 22.7%, 28.6%, 37.5%, 50%, and 9.1%, respectively. There was no change in patients with c-CPS stage IA and IIIC. There was a significant change in the cN stages (p <0.001), while no significant change was detected in the cT stages of the patients (p = 0.180). Upstaging was detected in 5/16 (6.3%, p=0.034), 14/71 (19.7%, p <0.01), 15 / 30 (50%, p <0.01) of initially cN 0, 1, 2 patients, respectively (p<0.001). CONCLUSION: The change in CPS was due to nodal upstaging. The effectiveness of including FDG-PET/CT in the initial radiological imaging in patients planned for NAT should be evaluated with prospective studies evaluating treatment choices to be used in NAT. Key Words: PET scan, Breast cancer, Positron emission tomography, Neoadjuvant treatment, Cancer staging, Staging system, TNM.

The Role of FDG PET/CT to Evaluation of Axillary Lymph Nodes after Neoadjuvant Chemotherapy in Breast Cancer.

OBJECTIVE: To determine the diagnostic value of breast and axillary maximum standard uptake (SUVmax) values for predicting ypT0 and ypN0 separately. STUDY DESIGN: A descriptive study. PLACE AND DURATION OF STUDY: Department of Medical Oncology, Haydarpasa Numune Training and Research Hospital, between May 2017 and September 2020.  Methodology: Consecutive patients with operated breast cancer (BC) after neoadjuvant chemotherapy (NAC) were evaluated. SUVmax on FDG-PET/CT after NAC at both primary tumour (postSUVmax-T) and axillary lymph nodes (postSUVmax-N) were assessed to predict the ypT0 and the ypN0, respectively.  Results: Clinically meaningful correlation was detected between postSUVmax-N with ypN0 in patients with human epidermal receptor-positive (Her2+) and triple-negative (TN) BC (in Her2+ BC: r=0.596, p <0.001, in TN BC: r=0.782, p = 0.001). The postSUVmax-N predicted ypN0 with 90.5% positive predictive value (PPV) and 85.7% negative predictive value (NPV) in patients with Her2+ and TN BC. The postSUVmax-T predicted ypT0 with 87.5% PPV and 100% NPV in patients with TN BC (AUC: 0.938, P <0.01) Conclusion: According to this study's findings, the FDG-PET/CT may be an alternative to sentinel lymph node biopsy (SNB) to protect patients from axillary lymph node dissection when the expected FNR of the SNB is high in patients with Her+ and TN BC. Key Words: Breast cancer, FDG PET/CT, Neoadjuvant therapy.