CapeOX as neoadjuvant chemotherapy for locally advanced rectal cancer: might less be more?

BACKGROUND: Locally advanced rectal cancer (LARC) poses unique challenges in treatment, with current neoadjuvant chemoradiotherapy (NA-CRT) showing limitations. The CapeOX regimen emerges as a potential less aggressive neoadjuvant chemotherapy (NAC) for LARC. METHODS: We conducted a retrospective study involving treatment-naïve patients with LARC from March 2014 to March 2021 who received 2-4 cycles of CapeOX NAC followed by radical surgery. Treatment response was evaluated using tumor regression grade (TRG), MRI-based TRG (MRI-TRG), and Neoadjuvant Rectal (NAR) score. RESULTS: 94.7% of patients experienced symptom improvement and 96.4% achieved sphincter-preserving surgery. Post-NAC showed significant tumor regression and MRI confirmed a tumor length reduction (P < 0.001). Clinical and pathological staging discrepancies post-NAC suggest broader therapeutic advantages. 5-year overall and disease-free survival rates were 78.4% and 73.4%. NAR scores provided better prognostic accuracy than MRI-TRG. CONCLUSION: CapeOX NAC presents notable benefits for LARC patients and its clinical significance may be underestimated. The NAR score demonstrates superior prognostic value over MRI-TRG.

Analysis of Hybrid NAR-RBFs Networks for complex non-linear Covid-19 model with fractional operators.

The Hybrid NAR-RBFs Networks for COVID-19 fractional order model is examined in this scientific study. Hybrid NAR-RBFs Networks for COVID-19, that is more infectious which is appearing in numerous areas as people strive to stop the COVID-19 pandemic. It is crucial to figure out how to create strategies that would stop the spread of COVID-19 with a different age groups. We used the epidemic scenario in the Hybrid NAR-RBFs Networks as a case study in order to replicate the propagation of the modified COVID-19. In this research work, existence and stability are verified for COVID-19 as well as proved unique solutions by applying some results of fixed point theory. The developed approach to investigate the impact of Hybrid NAR-RBFs Networks due to COVID-19 at different age groups is relatively advanced. Also obtain solutions for a proposed model by utilizing Atanga Toufik technique and fractal fractional which are the advanced techniques for such type of infectious problems for continuous monitoring of spread of COVID-19 in different age groups. Comparisons has been made to check the efficiency of techniques as well as for finding the reliable solutions to understand the dynamical behavior of Hybrid NAR-RBFs Networks for non-linear COVID-19. Finally, the parameters are evaluated to see the impact of illness and present numerical simulations using Matlab to see actual behavior of this infectious disease for Hybrid NAR-RBFs Networks of COVID-19 for different age groups.

Naringin attenuates Actinobacillus pleuropneumoniae-induced acute lung injury via MAPK/NF-κB and Keap1/Nrf2/HO-1 pathway.

Actinobacillus pleuropneumoniae (APP) causes porcine pleuropneumonia (PCP), which is clinically characterized by acute hemorrhagic, necrotizing pneumonia, and chronic fibrinous pneumonia. Although many measures have been taken to prevent the disease, prevention and control of the disease are becoming increasingly difficult due to the abundance of APP sera, weak vaccine cross-protection, and increasing antibiotic resistance in APP. Therefore, there is an urgent need to develop novel drugs against APP infection to prevent the spread of APP. Naringin (NAR) has been reported to have an excellent therapeutic effect on pulmonary diseases, but its therapeutic effect on lung injury caused by APP is not apparent. Our research has shown that NAR was able to alleviate APP-induced weight loss and quantity of food taken and reduce the number of WBCs and NEs in peripheral blood in mice; pathological tissue sections showed that NAR was able to prevent and control APP-induced pathological lung injury effectively; based on the establishment of an in vivo/in vitro model of APP inflammation, it was found that NAR was able to play an anti-inflammatory role through inhibiting the MAPK/NF-κB signaling pathway and exerting anti-inflammatory effects; additionally, NAR activating the Nrf2 signalling pathway, increasing the secretion of antioxidant enzymes Nqo1, CAT, and SOD1, inhibiting the secretion of oxidative damage factors NOS2 and COX2, and enhancing the antioxidant stress ability, thus playing an antioxidant role. In summary, NAR can relieve severe lung injury caused by APP by reducing excessive inflammatory response and improving antioxidant capacity.

Development and validation of a novel nomogram model predicting the unfavorable outcome based on NAR and collaterals status for patients with AIS.

INTRODUCTION: Stroke is a leading cause of disability and mortality globally. This study aimed to develop a prognostic nomogram based on neutrophil-to-albumin ratio (NAR) and collateral status in acute ischemic stroke (AIS) patients with anterior large vessel occlusion (LVO). MATERIAL & METHOD: 590 AIS patients with LVO assessed for regional leptomeningeal collateral (rLMC) were retrospectively enrolled, and randomly divided into a training set (n = 414) and a testing set (n = 176). Unfavorable functional outcome was defined as a modified Rankin scale (mRS) score of 3 to 6 at 3 months. We assessed the accuracy and clinical utility of the nomogram using calibration plots, area under the curve (AUC), decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI). RESULTS: Both NAR and rLMC were independently associated with unfavorable outcome at 3 months (OR=8.96, p=0.0341; OR=0.89, p=0.0002, respectively). The developed nomogram (akaike information criterion (AIC)=398.77), which included NAR, rLMC and other factors, showed good performance (the AUC for the development and validation cohorts was 0.848 and 0.840 respectively) and improved the predictive value compared to a model without NAR and rLMC, according to an overall NRI of 3.27% (p=0.2401), overall IDI of 3.27% (p=0.2414), and a higher AUC (0.848 vs 0.831). CONCLUSIONS: NAR can serve as an independent predictor in AIS patients with anterior LVO, and the nomogram incorporating NAR and rLMC is reliable in predicting unfavorable outcome. Further studies with larger sample sizes are needed to validate and extend these findings.

A New Real-Time Simple Method to Measure the Endogenous Nitrate Reductase Activity (Nar) in Paracoccus denitrificans and Other Denitrifying Bacteria.

The transmembrane nitrate reductase (Nar) is the first enzyme in the dissimilatory alternate anaerobic nitrate respiratory chain in denitrifying bacteria. To date, there has been no real-time method to determine its specific activity embedded in its native membrane; here, we describe such a new method, which is useful with the inside-out membranes of Paracoccus denitrificans and other denitrifying bacteria. This new method takes advantage of the native coupling of the endogenous NADH dehydrogenase or Complex I with the reduction of nitrate by Nar through the quinone pool of the inner membranes of P. denitrificans. This is achieved under previously reached anaerobic conditions. Inner controls confirming the specific Nar activity determined by this new method were made by the total inhibition of the Nar enzyme by sodium azide and cyanide, well-known Nar inhibitors. The estimation of the Michaelis-Menten affinity of Nar for NO3- using this so-called Nar-JJ assay gave a Km of 70.4 µM, similar to previously determined values. This new Nar-JJ assay is a suitable, low-cost, and reproducible method to determine in real-time the endogenous Nar activity not only in P. denitrificans, but in other denitrifying bacteria such as Brucella canis, and potentially in other entero-pathogenic bacteria.

Naringin's Alleviation of the Inflammatory Response Caused by Actinobacillus pleuropneumoniae by Downregulating the NF-κB/NLRP3 Signalling Pathway.

Actinobacillus pleuropneumoniae (APP) is responsible for causing Porcine pleuropneumonia (PCP) in pigs. However, using vaccines and antibiotics to prevent and control this disease has become more difficult due to increased bacterial resistance and weak cross-immunity between different APP types. Naringin (NAR), a dihydroflavonoid found in citrus fruit peels, has been recognized as having significant therapeutic effects on inflammatory diseases of the respiratory system. In this study, we investigated the effects of NAR on the inflammatory response caused by APP through both in vivo and in vitro models. The results showed that NAR reduced the number of neutrophils (NEs) in the bronchoalveolar lavage fluid (BALF), and decreased lung injury and the expression of proteins related to the NLRP3 inflammasome after exposure to APP. In addition, NAR inhibited the nuclear translocation of nuclear factor kappa-B (NF-κB) P65 in porcine alveolar macrophage (PAMs), reduced protein expression of NLRP3 and Caspase-1, and reduced the secretion of pro-inflammatory cytokines induced by APP. Furthermore, NAR prevented the assembly of the NLRP3 inflammasome complex by reducing protein interaction between NLRP3, Caspase-1, and ASC. NAR also inhibited the potassium (K+) efflux induced by APP. Overall, these findings suggest that NAR can effectively reduce the lung inflammation caused by APP by inhibiting the over-activated NF-κB/NLRP3 signalling pathway, providing a basis for further exploration of NAR as a potential natural product for preventing and treating APP.

Characterization and genomics identification of key genes involved in denitrification-DNRA-nitrification pathway of plant growth-promoting rhizobacteria (Serratia marcescens OK482790).

BACKGROUND: A wide variety of microorganisms, including bacteria, live in the rhizosphere zone of plants and have an impact on plant development both favorably and adversely. The beneficial outcome is due to the presence of rhizobacteria that promote plant growth (PGPR). RESULTS: In this study, a bacterial strain was isolated from lupin rhizosphere and identified genetically as Serratia marcescens (OK482790). Several biochemically and genetically characteristics were confirmed in vitro and in vivo to determine the OK482790 strain ability to be PGPR. The in vitro results revealed production of different lytic enzymes (protease, lipase, cellulase, and catalase), antimicrobial compounds (hydrogen cyanide, and siderophores), ammonia, nitrite, and nitrate and its ability to reduce nitrate to nitrite. In silico and in vitro screening proposed possible denitrification-DNRA-nitrification pathway for OK482790 strain. The genome screening indicated the presence of nitrite and nitrate genes encoding Nar membrane bound sensor proteins (NarK, NarQ and NarX). Nitrate and nitrite reductase encoding genes (NarI, NarJ, NarH, NarG and NapC/NirT) and (NirB, NirC, and NirD) are also found in addition to nitroreductases (NTR) and several oxidoreductases. In vivo results on wheat seedlings confirmed that seedlings growth was significantly improved by soil inoculation of OK482790 strain. CONCLUSIONS: This study provides evidence for participation of S. marcescens OK482790 in nitrogen cycling via the denitrification-DNRA-nitrification pathway and for its ability to produce several enzymes and compounds that support the beneficial role of plant-microbe interactions to sustain plant growth and development for a safer environment.

Identity and functional characterisation of the transporter supporting the Na+ -dependent high-affinity NO3 - uptake in Zostera marina L.

Zostera marina is a seagrass, a group of angiosperms that evolved from land to live submerged in seawater, an environment of high salinity, alkaline pH and usually very low NO3 - . In 2000, we reported the first physiological evidence for the Na+ -dependent high-affinity NO3 - uptake in this plant. Now, to determine the molecular identity of this process, we searched for NO3 - transporters common to other vascular plants encoded in Z. marina's genome. We cloned two candidates, ZosmaNPF6.3 and ZosmaNRT2 with its partner protein ZosmaNAR2. ZosmaNAR2 expression levels increase up to 4.5-fold in Z. marina leaves under NO3 - -deficiency, while ZosmaNRT2 and ZosmaNPF6.3 expressions were low and unaffected by NO3 - . NO3 - transport capacity, kinetic properties and H+ or Na+ -dependence were examined by heterologous expression in the Hansenula polymorpha high-affinity NO3 - transporter gene disrupted strain (∆ynt1). ZosmaNPF6.3 functions as a H+ -dependent NO3 - transporter, without functionality at alkaline pH and apparent dual kinetics (KM = 11.1 µM at NO3 - concentrations below 50 µM). ZosmaNRT2 transports NO3 - in a H+ -independent but Na+ -dependent manner (KM = 1 mM Na+ ), with low NO3 - affinity (KM = 30 µM). When ZosmaNRT2 and ZosmaNAR2 are co-expressed, a Na+ -dependent high-affinity NO3 - transport occurs (KM = 5.7 µM NO3 - ), mimicking the in vivo value. These results are discussed in the physiological context, providing evidence that ZosmaNRT2 is a Na+ -dependent high-affinity NO3 - transporter, the first of its kind to be functionally characterised in a vascular plant, that requires ZosmaNAR2 to achieve the necessary high-affinity for nitrate uptake from seawater.

Relative growth rate (RGR) and other confounded variables: mathematical problems and biological solutions.

BACKGROUND: Relative growth rate (RGR) has a long history of use in biology. In its logged form, RGR = ln[(M + ΔM)/M], where M is size of the organism at the commencement of the study, and ΔM is new growth over time interval Δt. It illustrates the general problem of comparing non-independent (confounded) variables, e.g. (X + Y) vs. X. Thus, RGR depends on what starting M(X) is used even within the same growth phase. Equally, RGR lacks independence from its derived components, net assimilation rate (NAR) and leaf mass ratio (LMR), as RGR = NAR × LMR, so that they cannot legitimately be compared by standard regression or correlation analysis. FINDINGS: The mathematical properties of RGR exemplify the general problem of 'spurious' correlations that compare expressions derived from various combinations of the same component terms X and Y. This is particularly acute when X >> Y, the variance of X or Y is large, or there is little range overlap of X and Y values among datasets being compared. Relationships (direction, curvilinearity) between such confounded variables are essentially predetermined and so should not be reported as if they are a finding of the study. Standardizing by M rather than time does not solve the problem. We propose the inherent growth rate (IGR), lnΔM/lnM, as a simple, robust alternative to RGR that is independent of M within the same growth phase. CONCLUSIONS: Although the preferred alternative is to avoid the practice altogether, we discuss cases where comparing expressions with components in common may still have utility. These may provide insights if (1) the regression slope between pairs yields a new variable of biological interest, (2) the statistical significance of the relationship remains supported using suitable methods, such as our specially devised randomization test, or (3) multiple datasets are compared and found to be statistically different. Distinguishing true biological relationships from spurious ones, which arise from comparing non-independent expressions, is essential when dealing with derived variables associated with plant growth analyses.

The neoadjuvant rectal score and a novel magnetic resonance imaging based neoadjuvant rectal score are stage independent predictors of long-term outcome in locally advanced rectal cancer.

AIM: Neoadjuvant rectal (NAR) score is an early surrogate for longer-term outcomes in rectal cancer undergoing radiotherapy and resection. In an era of increasing organ preservation, resection specimens are not always available to calculate the NAR score. Post-treatment magnetic resonance imaging (MRI) re-staging of regression is subjective, limiting reproducibility. We explored the potential for a novel MRI-based NAR score (mrNAR) adapted from the NAR formula. METHODS: Locally advanced rectal cancer patients undergoing neoadjuvant therapy (nCRT) and surgery were retrospectively identified between 2008 and 2020 in a single cancer network. mrNAR was calculated by adapting the NAR formula, replacing pathological (p) stages with post-nCRT MR stages (ymr). Cox regression assessed relationships between clinicopathological characteristics, NAR and mrNAR with overall survival (OS) and recurrence-free survival (RFS). RESULTS: In total, 381 NAR and 177 mrNAR scores were calculated. On univariate analysis NAR related to OS (hazard ratio [HR] 2.05, 95% confidence interval [CI] 1.33-3.14, p = 0.001) and RFS (HR 2.52, 95% CI 1.77-3.59, p = 0.001). NAR 3-year OS <8 was 95.3%, 8-16 was 88.6% and >16 was 80%. mrNAR related to OS (HR 2.96, 95% CI 1.38-6.34, p = 0.005) and RFS (HR 2.99, 95% CI 1.49-6.00, p = 0.002). 3-year OS for mrNAR <8 was 96.2%, 8-16 was 92.4% and >16 was 78%. On multivariate analysis, mrNAR was a stage-independent predictor of OS and RFS. mrNAR corresponded to NAR score category in only 15% (positive predictive value 0.23) and 47.5% (positive predictive value 0.48) of cases for categories <8 and >16, respectively. CONCLUSIONS: Neoadjuvant rectal score is validated as a surrogate end-point for long-term outcomes. mrNAR categories do not correlate with NAR but have stage-independent prognostic value. mrNAR may represent a novel surrogate end-point for future neoadjuvant treatments that focus on organ preservation.

Development and validation of neoadjuvant rectal score-based signature nomograms to predict overall survival and disease-free survival in locally advanced rectal cancer: a retrospective, double center, cohort study.

AIM: To evaluate the prognostic significance of the NAR score and develop nomograms for locally advanced rectal cancer (LARC) treated after neoadjuvant chemo-radiotherapy (nCRT) combined with total meso-rectal excision (TME) surgery to predict prognostic. METHODS: Retrospective collection among LARC patients treated at Fujian Medical University Union Hospital (training cohort) and Fujian Medical University Affiliated Zhangzhou Hospital (external validation cohort) between Jan 10, 2011 and Dec 28, 2021. The NAR score was calculated by formula: [5pN-3(cT-pT) + 12]^2/9.61. NAR score low (< 8), intermediate (8-16), and high (> 16). RESULTS: 1665 patients in the training cohort and 256 patients in the external validation cohorts were enrolled. Lower NAR score was significantly associated with better cumulative incidence of OS, DFS, local recurrence (LR), and distant metastasis (DM) (all P < 0.001). Multivariate Cox regression analysis indicates that NAR score, distance to the anal verge, no.253 LN metastasis, post-CRT carbohydrate antigen 19-9, tumor regression grade, and surgery method are independent predictors of OS and DFS (all P < 0.001). Among these independent factors, the NAR score had the highest area under the curve (AUC) and the nomograms to predict OS and DFS were generated. The AUCs for the accuracy of the prediction OS were 1 year = 0.742, 3 years = 0.749, 5 years = 0.713; prediction DFS were 1 year = 0.727, 3 years = 0.739, 5 years = 0.718, the models have good accuracy. CONCLUSIONS: The NAR score can effectively classify patients with LARC into groups with varying outcomes of OS, DFS, LR, and DM. Moreover, the novel nomograms comprising the NAR score were developed and validated to help predict OS and DFS.

Therapeutic Effect and Safety Evaluation of Naringin on Klebsiella pneumoniae in Mice.

Critically ill patients with Corona Virus Disease 2019 (COVID-19) often develop secondary bacterial infections that pose a significant threat to patient life safety, making the development of drugs to prevent bacterial infections in the lungs critical to clinical care. Naringin (NAR) is one of the significant natural flavonoids rich in Pummelo Peel (Hua Ju Hong), with anti-inflammatory, antimicrobial, and antioxidant activities, and is commonly used in treating respiratory tract infectious diseases. In this study, the in vitro and in vivo findings revealed that, after Klebsiella pneumoniae (Kpn) infection, NAR inhibited overactivation of the nuclear factor kappa-B(NF-κB) signaling pathway in alveolar macrophages of mice, reduced neutrophil (NEs) recruitment, and lowered the induced production of proinflammatory markers, such as Interleukin-6(IL-6) and tumor necrosis factor α(TNF-α). Thus, it suppressed excessive immune responses in the lungs, as well as attenuated the induced pulmonary fibrosis and inflammatory infiltrates. These results suggest that NAR has a preventive effect against Kpn in mice. In addition, the study evaluated NAR's potential toxicity, demonstrating that NAR is safe at effective doses. These results suggested that NAR effectively reduces excessive inflammatory damage in the lungs induced by Kpn and enhances the body's ability to clear bacteria. Therefore, NAR may be an effective and safe healthcare drug for preventing and caring for bacterial pneumonia.

Neoadjuvant rectal score is prognostic for survival: A population-based propensity-matched analysis.

INTRODUCTION: Neoadjuvant rectal (NAR) score may serve as a surrogate short-term endpoint for overall survival (OS) in clinical trials. This study aims to test the NAR score using a large, national cancer registry. METHODS: National Cancer Database patients with clinical stage II/III rectal adenocarcinoma (RAC) treated with neoadjuvant chemoradiation (CRT) followed by surgery were selected and divided into low-, intermediate-, and high-NAR subgroups. OS outcomes were analyzed using Kaplan-Meier and logistic regression models. RESULTS: A total of 12 452 patients were selected, of which 5071 (40.7%) were in clinical stage II and 7381 (59.3%) were in clinical stage III; 15.2% had pathologic complete response. The mean NAR score was 10.01 ± 10.61. Six thousand nine hundred and forty-one (55.7%) did not receive adjuvant chemotherapy (AC) and were propensity-matched across NAR subgroups (966 in each group). A significant difference in 5-year OS between low-, intermediate-, and high-NAR groups was observed (85% vs. 76% vs. 68%; p < 0.001). Five thousand five hundred and eleven (44.3%) received AC and 1045 triplets were propensity-matched per NAR groups. A significant difference was again observed for 5-year OS (93% vs. 88% vs. 75%; p < 0.001). Logistic regression confirmed NAR strata as a significant predictor of 5-year OS. CONCLUSION: NAR score, as a neoadjuvant response measure, is a strong predictor of 5-year OS, regardless of AC receipt in a heterogenous population of locally advanced RAC patients.

Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment.

The environmental microclimatic characteristics are often subject to fluctuations of considerable importance, which can cause irreparable damage to art works. We explored the applicability of Artificial Intelligence (AI) techniques to the Cultural Heritage area, with the aim of predicting short-term microclimatic values based on data collected at Rosenborg Castle (Copenhagen), housing the Royal Danish Collection. Specifically, this study applied the NAR (Nonlinear Autoregressive) and NARX (Nonlinear Autoregressive with Exogenous) models to the Rosenborg microclimate time series. Even if the two models were applied to small datasets, they have shown a good adaptive capacity predicting short-time future values. This work explores the use of AI in very short forecasting of microclimate variables in museums as a potential tool for decision-support systems to limit the climate-induced damages of artworks within the scope of their preventive conservation. The proposed model could be a useful support tool for the management of the museums.

Immunological Functions and Evolutionary Emergence of Heavy-Chain Antibodies.

Homodimeric antibodies devoid of light chains have evolved multiple times through convergent evolution, yet their specific immunological functions remain poorly understood. We survey the molecular and structural features of these antibodies, their immunological functions in host defense, and reflect on the long-standing question of the evolutionary forces driving their emergence.

Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India.

BACKGROUND: Time-series forecasting has a critical role during pandemics as it provides essential information that can lead to abstaining from the spread of the disease. The novel coronavirus disease, COVID-19, is spreading rapidly all over the world. The countries with dense populations, in particular, such as India, await imminent risk in tackling the epidemic. Different forecasting models are being used to predict future cases of COVID-19. The predicament for most of them is that they are not able to capture both the linear and nonlinear features of the data solely. METHODS: We propose an ensemble model integrating an autoregressive integrated moving average model (ARIMA) and a nonlinear autoregressive neural network (NAR). ARIMA models are used to extract the linear correlations and the NAR neural network for modeling the residuals of ARIMA containing nonlinear components of the data. Comparison: Single ARIMA model, ARIMA-NAR model and few other existing models which have been applied on the COVID-19 data in different countries are compared based on performance evaluation parameters. RESULT: The hybrid combination displayed significant reduction in RMSE (16.23%), MAE (37.89%) and MAPE (39.53%) values when compared with single ARIMA model for daily observed cases. Similar results with reduced error percentages were found for daily reported deaths and cases of recovery as well. RMSE value of our hybrid model was lesser in comparison to other models used for forecasting COVID-19 in different countries. CONCLUSION: Results suggested the effectiveness of the new hybrid model over a single ARIMA model in capturing the linear as well as nonlinear patterns of the COVID-19 data.

Impact of the COVID-19 pandemic on management and outcomes in acute appendicitis: Should these new practices be the norm?

BACKGROUND: In early 2020, the COVID-19 pandemic significantly altered management of surgical patients globally. International guidelines recommended that non-operative management be implemented wherever possible (e.g. in proven uncomplicated appendicitis) to reduce pressure on healthcare services and reduce risk of peri-operative viral transmission. We sought to compare our management and outcomes of appendicitis during lockdown vs a non-pandemic period. METHODS: All presentations to our department with a clinical diagnosis of acute appendicitis between 12/03/2020 and 30/06/2020 were compared to the same 110-day period in 2019. Quantity and severity of presentations, use of radiological investigations, rate of operative intervention and histopathological findings were variables collected for comparison. RESULTS: There was a reduction in appendicitis presentations (from 74 to 56 cases), and an increase in radiological imaging (from 70.27% to 89.29%) (P = 0.007) from 2019 to 2020. In 2019, 93.24% of patients had appendicectomy, compared to 71.42% in 2020(P < 0.001). This decrease was most pronounced in uncomplicated cases, whose operative rates dropped from 90.32% to 62.5% (P = 0.009). Post-operative histology confirmed appendicitis in 73.9% in 2019, compared to 97.5% in 2020 (P = 0.001). Normal appendiceal pathology was reported for 17 cases (24.64%) in 2019, compared to none in 2020 (P < 0.001) - a 0% negative appendicectomy rate (NAR). DISCUSSION: The 0% NAR in 2020 is due to a combination of increased CT imaging, a higher threshold to operate, and is impacted by increased disease severity due to delayed patient presentation. This study adds to growing literature promoting routine use of radiological imaging to confirm appendicitis diagnosis. As we enter a second lockdown, patients should be encouraged to avoid late presentations, and surgical departments should continue using radiological imaging more liberally in guiding appendicitis management.

Network Autoregressive Model for the Prediction of COVID-19 Considering the Disease Interaction in Neighboring Countries.

Predicting the way diseases spread in different societies has been thus far documented as one of the most important tools for control strategies and policy-making during a pandemic. This study is to propose a network autoregressive (NAR) model to forecast the number of total currently infected cases with coronavirus disease 2019 (COVID-19) in Iran until the end of December 2021 in view of the disease interactions within the neighboring countries in the region. For this purpose, the COVID-19 data were initially collected for seven regional nations, including Iran, Turkey, Iraq, Azerbaijan, Armenia, Afghanistan, and Pakistan. Thenceforth, a network was established over these countries, and the correlation of the disease data was calculated. Upon introducing the main structure of the NAR model, a mathematical platform was subsequently provided to further incorporate the correlation matrix into the prediction process. In addition, the maximum likelihood estimation (MLE) was utilized to determine the model parameters and optimize the forecasting accuracy. Thereafter, the number of infected cases up to December 2021 in Iran was predicted by importing the correlation matrix into the NAR model formed to observe the impact of the disease interactions in the neighboring countries. In addition, the autoregressive integrated moving average (ARIMA) was used as a benchmark to compare and validate the NAR model outcomes. The results reveal that COVID-19 data in Iran have passed the fifth peak and continue on a downward trend to bring the number of total currently infected cases below 480,000 by the end of 2021. Additionally, 20%, 50%, 80% and 95% quantiles are provided along with the point estimation to model the uncertainty in the forecast.

Identification of potential therapeutic target of naringenin in breast cancer stem cells inhibition by bioinformatics and in vitro studies.

Cancer therapy is a strategic measure in inhibiting breast cancer stem cell (BCSC) pathways. Naringenin, a citrus flavonoid, was found to increase breast cancer cells' sensitivity to chemotherapeutic agents. Bioinformatics study and 3D tumorsphere in vitro modeling in breast cancer (mammosphere) were used in this study, which aims to explore the potential therapeutic targets of naringenin (PTTNs) in inhibiting BCSCs. Bioinformatic analyses identified direct target proteins (DTPs), indirect target proteins (ITPs), naringenin-mediated proteins (NMPs), BCSC regulatory genes, and PTTNs. The PTTNs were further analyzed for gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction (PPI) networks, and hub protein selection. Mammospheres were cultured in serum-free media. The effects of naringenin were measured by MTT-based cytotoxicity, mammosphere forming potential (MFP), colony formation, scratch wound-healing assay, and flow cytometry-based cell cycle analyses and apoptosis assays. Gene expression analysis was performed using real-time quantitative polymerase chain reaction (q-RT PCR). Bioinformatics analysis revealed p53 and estrogen receptor alpha (ERα) as PTTNs, and KEGG pathway enrichment analysis revealed that TGF-ß and Wnt/ß-catenin pathways are regulated by PTTNs. Naringenin demonstrated cytotoxicity and inhibited mammosphere and colony formation, migration, and epithelial to mesenchymal transition in the mammosphere. The mRNA of tumor suppressors P53 and ERα were downregulated in the mammosphere, but were significantly upregulated upon naringenin treatment. By modulating the P53 and ERα mRNA, naringenin has the potential of inhibiting BCSCs. Further studies on the molecular mechanism and formulation of naringenin in BCSCs would be beneficial for its development as a BCSC-targeting drug.

Importance of the neoadjuvant rectal (NAR) score to the outcome of neoadjuvant chemotherapy alone for locally advanced rectal cancer.

PURPOSE: The neoadjuvant rectal (NAR) score is a promising indicator of survival after preoperative chemoradiotherapy for rectal cancer. However, its effectiveness after neoadjuvant chemotherapy (NAC) alone has not been fully investigated. METHODS: We analyzed data retrospectively on 61 patients with rectal cancer, who received NAC followed by surgical resection between 2010 and 2015, and evaluated the impact of the NAR score on survival. RESULTS: The median NAR score was 14.9. Of the 61 patients, 13, 35, and 13 were classified as having NAR-low (< 8), NAR-intermediate (8-16), and NAR-high (> 16) scores, respectively. The median observation period was 49.0 months. According to the NAR score, the 3-year DFS in the NAR-low group was 100%, which was significantly better than that in the NAR-intermediate (64.8%, p = 0.041), and NAR-high (61.5%, p = 0.018) groups. When the NAR-intermediate and NAR-high groups were investigated as a single high-risk group, the 3-year DFS of the patients who received adjuvant chemotherapy was 88.7%, which was significantly better than that of the patients who did not receive adjuvant chemotherapy (53.3%, p = 0.042). CONCLUSIONS: The NAR score may predict the DFS and could serve as a favorable indicator of adjuvant chemotherapy after NAC alone.