Unraveling the causality between gastroesophageal reflux disease and increased cancer risk: evidence from the UK Biobank and GWAS consortia.

BACKGROUND: Gastroesophageal reflux disease (GERD) is a common condition characterized by the reflux of stomach contents into the esophagus. Despite its widespread prevalence worldwide, the causal link between GERD and various cancer risks has not been fully established, and past medical research has often underestimated or overlooked this relationship. METHODS: This study performed Mendelian randomization (MR) to investigate the causal relationship between GERD and 19 different cancers. We leveraged data from 129,080 GERD patients and 473,524 controls, along with cancer-related data, obtained from the UK Biobank and various Genome-Wide Association Studies (GWAS) consortia. Single nucleotide polymorphisms (SNPs) associated with GERD were used as instrumental variables, utilizing methods such as inverse variance weighting, weighted median, and MR-Egger to address potential pleiotropy and confounding factors. RESULTS: GERD was significantly associated with higher risks of nine types of cancer. Even after adjusting for all known risk factors-including smoking, alcohol consumption, major depression, and body mass index (BMI)-these associations remained significant, with higher risks for most cancers. For example, the adjusted risk for overall lung cancer was (OR, 1.23; 95% CI: 1.14-1.33), for lung adenocarcinoma was (OR, 1.18; 95% CI: 1.03-1.36), for lung squamous cell carcinoma was (OR, 1.35; 95% CI: 1.19-1.53), and for oral cavity and pharyngeal cancer was (OR, 1.73; 95% CI: 1.22-2.44). Especially noteworthy, the risk for esophageal cancer increased to (OR, 2.57; 95% CI: 1.23-5.37). Mediation analyses further highlighted GERD as a significant mediator in the relationships between BMI, smoking, major depression, and cancer risks. CONCLUSIONS: This study identifies a significant causal relationship between GERD and increased cancer risk, highlighting its role in cancer development and underscoring the necessity of incorporating GERD management into cancer prevention strategies.

Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways.

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor, highlighting a significant need for reliable predictive models to assess clinical prognosis, disease progression, and drug sensitivity. Recent studies have highlighted the critical role of various programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, NETotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, in tumor development. Therefore, by investigating these pathways, we aimed to develop a predictive model for HCC prognosis and drug sensitivity. We analyzed transcriptome, single-cell transcriptome, genomic, and clinical information using data from the TCGA-LIHC, GSE14520, GSE45436, and GSE166635 datasets. Machine learning algorithms were used to establish a cell death index (CDI) with seven gene signatures, which was validated across three independent datasets, showing that high CDI correlates with poorer prognosis. Unsupervised clustering revealed three molecular subtypes of HCC with distinct biological processes. Furthermore, a nomogram integrating CDI and clinical information demonstrated good predictive performance. CDI was associated with immune checkpoint genes and tumor microenvironment components using single-cell transcriptome analysis. Drug sensitivity analysis indicated that patients with high CDI may be resistant to oxaliplatin and cisplatin but sensitive to axitinib and sorafenib. In summary, our model offers a precise prediction of clinical outcomes and drug sensitivity for patients with HCC, providing valuable insights for personalized treatment strategies.

Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer's disease signature regions and predicted future tau deposition.

BACKGROUND: Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer's disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. METHODS: The present study recruited 517 participants comprising Aß negative cognitively normal (CN-) participants (n = 135), Aß positive cognitively normal (CN +) participants (n = 64), individuals with amnestic mild cognitive impairment (aMCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these imaging biomarkers. RESULTS: The results showed that baseline NfL levels and the rate of change were associated with Aß deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions (P<0.05). In both Aß positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus (ß = 0.336, P = 0.032; ß = 0.313, P = 0.047). Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. CONCLUSIONS: The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.

High-precision calculation and experiments on the thermal blooming of high-energy lasers.

Thermal blooming (TB) is one of the important factors affecting the quality of high-energy laser beams. Reasonable simulation of thermal blooming is important to the application of a high-energy laser. However, reported investigations on TB simulation are mainly based on one method, such as the perturbation method or the phase screen method, which often leads to obvious errors in some conditions. In the paper, the reasonable ranges of optical generalized distortion parameters for both methods are determined based on the reported experimental data, which solves the problem of accurate TB simulations for the first time. In addition, the dynamic effect of thermal blooming is also calculated. Finally, the formula method is presented to extract the phase of thermal blooming distortion. We then use LC-SLM (Liquid crystal spatial light modulator) to emulate thermal blooming effect in the lab. The experimental results are more consistent with the numerical simulation results than conventional phase extraction methods. Our work provides a quantitatively and programmable way to accurately simulate TB with LC-SLM in the lab.

Shorter TR combined with finer atlas positively modulate topological organization of brain network: A resting state fMRI study.

BACKGROUND: The use of shorter TR and finer atlases in rs-fMRI can provide greater detail on brain function and anatomy. However, there is limited understanding of the effect of this combination on brain network properties. METHODS: A study was conducted with 20 healthy young volunteers who underwent rs-fMRI scans with both shorter (0.5s) and long (2s) TR. Two atlases with different degrees of granularity (90 vs 200 regions) were used to extract rs-fMRI signals. Several network metrics, including small-worldness, Cp, Lp, Eloc, and Eg, were calculated. Two-factor ANOVA and two-sample t-tests were conducted for both the single spectrum and five sub-frequency bands. RESULTS: The network constructed using the combination of shorter TR and finer atlas showed significant enhancements in Cp, Eloc, and Eg, as well as reductions in Lp and γ in both the single spectrum and subspectrum (p < 0.05, Bonferroni correction). Network properties in the 0.082-0.1 Hz frequency range were weaker than those in the 0.01-0.082 Hz range. CONCLUSION: Our findings suggest that the use of shorter TR and finer atlas can positively affect the topological characteristics of brain networks. These insights can inform the development of brain network construction methods.

A critical review of adsorption isotherm models for aqueous contaminants: Curve characteristics, site energy distribution and common controversies.

The quantitative description of the equilibrium data by the isotherm models is an indispensable link in adsorption studies. The previous review papers focus on the underlying assumptions, fitting methods, error functions and practical applications of the isotherm models, usually ignoring their curve characteristics, selection criteria and common controversies. The main contents of this review include: (i) effect of the model parameters on the isotherm curves; (ii) determination of the site energy distribution; (iii) selection criteria of the isotherm models; and (iv) elimination of some common controversies. It is of great significance to reveal the curve characteristics for selecting a proper isotherm model. The site energy distribution is conducive to understanding the physicochemical properties of the adsorbent surface. The complete isotherm is recommended to be correlated with the experimental data. The model parameter qmax should be cautiously adopted for comparison of the adsorbent performance. The residual plot can be used to diagnose the fitting quality of the isotherm models further. This review also addresses some common mistakes and controversies and thereby avoids their propagation in future publications.

Brain network hierarchy reorganization in Alzheimer's disease: A resting-state functional magnetic resonance imaging study.

Hierarchy is a fundamental organizational principle of the human brain network. Whether and how the network hierarchy changes in Alzheimer's disease (AD) remains unclear. To explore brain network hierarchy alterations in AD and their clinical relevance. Forty-nine healthy controls (HCs), 49 patients with mild cognitive impairment (MCI), and 49 patients with AD were included. The brain network hierarchy of each group was depicted by connectome gradient analyses. We assessed the network hierarchy changes by comparing the gradient values in each network across the AD, MCI, and HC groups. Whole-brain voxel-level gradient values were compared across the AD, MCI, and HC groups to identify abnormal brain regions. Finally, we examined the relationships between altered gradient values and clinical features. In the secondary gradient, the posterior default mode network (DMN) gradient values decreased significantly in patients with AD compared with HCs. Regionally, compared with HCs, both MCI and AD groups showed that most of the brain regions with increased gradient values were located in anterior DMN, while most of the brain regions with decreased gradient values were located in posterior DMN. The decrease of gradients in the left middle occipital gyrus was associated with better logical memory performance. The increase of gradients in the right middle frontal gyrus was associated with lower rates of dementia. The network hierarchy changed characteristically in patients with AD and was closely related to memory function and disease severity. These results provide a novel view for further understanding the underlying neuro-mechanisms of AD.

Tunable Berreman mode in highly conductive organic thin films.

The unique performances of Epsilon-near-zero (ENZ) materials allow them to play a crucial role in many optoelectronic devices and have spawned a wide range of inventive uses. In this paper, we found that the modified PEDOT:PSS film formed with a kind of so-called "Metastable liquid-liquid Contact (MLLC)" solution treatment method can achieve a wide tuning of ENZ wavelength from 1270 nm to 1550 nm in the near-infrared region. We further analyzed the variation trend of imaginary permittivity for these samples with different ENZ wavelengths. The Berreman mode was successfully excited by a simple structural design to realize a tunable polarization absorber.

Kinetic studies of nitrate removal from aqueous solution using granular chitosan-Fe(III) complex.

In the present study, a granular chitosan-Fe(III) complex was prepared as a feasible adsorbent for the removal of nitrate from an aqueous solution. There was no significant change in terms of nitrate removal efficiency over a wide pH range of 3-11. Nitrate adsorption on the chitosan-Fe(III) complex followed the Langmuir-Freundlich isotherm model. In order to more accurately reflect adsorption and desorption behaviors at the solid/solution interface, kinetic model I and kinetic model II were proposed to simulate the interfacial process in a batch system. Nitrate adsorption on the chitosan-Fe(III) complex followed the pseudo-first-order kinetic model and kinetic model I. The proposed half-time could provide useful information for optimizing process design. Adsorption and desorption rate constants obtained from kinetic model I and kinetic model II were beneficial to understanding the interfacial process and the extent of adsorption reaction. Kinetic model I and kinetic model II implied that nitrate uptake exponentially approaches a limiting value.

A study of the mechanism of fluoride adsorption from aqueous solutions onto Fe-impregnated chitosan.

UNLABELLED: The adsorption of fluoride from aqueous solutions onto an Fe-impregnated chitosan (Fe-CTS) granular adsorbent was studied, and the adsorption capacity was determined to be 1.9736 mg g(-1) at an initial fluoride concentration of 10 mg L(-1). The effects of the initial fluoride concentration, dosage, and temperature were investigated using factorial design and analysis. The results indicated that high initial fluoride concentrations, low dosages, and low temperatures could enhance the fluoride adsorption capacity. In addition, Fe-CTS exhibited high selectivity for fluoride removal in the presence of high levels of several coexisting anions (nitrate, chloride, bicarbonate, and phosphate), except carbonate and sulfate. The adsorption process followed the Langmuir model at low fluoride concentrations and the Freundlich model at high initial fluoride concentrations. The data also fit the pseudo-second-order model. Scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and extended X-ray absorption fine-structure (EXAFS) spectroscopy were used to elucidate the adsorption mechanism. The FTIR and EXAFS analyses revealed that Fe was chelated with -NH2 and -OH groups on the CTS, and fluoride adsorption on the Fe-CTS occurred due to ion exchange between chloride and fluoride. HIGHLIGHTS: a granular Fe-impregnated chitosan (Fe-CTS) adsorbent was synthesized via chelation of Fe ions to -OH and -NH2 groups of CTS. The Fe-CTS granular adsorbent exhibited high performance for the adsorption of fluoride. The mechanism of fluoride adsorption on Fe-CTS was elucidated using EXAFS and FTIR analyses. Fluoride adsorption on Fe-CTS occurred via ion exchange between chloride and fluoride.

Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer's Disease signature regions and predicted future tau deposition.

Background: Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer's disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. Methods: The present study recruited 517 participants comprising Aß negative cognitively normal (CN-) participants (n = 135), CN + participants (n = 64), individuals with mild cognitive impairment (MCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these MRI markers. Results: The results showed that baseline NfL levels and the rate of change were associated with Aß deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions. In both Aß positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus. Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. Conclusions: The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.

Enhanced removal of phosphate from aqueous solutions by oxygen vacancy-rich MgO microspheres: Performance and mechanism.

The efficient removal of phosphate from water environments was extremely significant to control eutrophication of water bodies and prevent further deterioration of water quality. In this study, oxygen vacancy-rich magnesium oxide (OV-MgO) microspheres were synthesized by a simple solvothermal method coupling high-temperature calcination. The effects of adsorbent dosage, contact time, initial pH and coexisting components on phosphate adsorption performance were examined. The physicochemical properties of OV-MgO microspheres and the phosphate removal mechanisms were analyzed by various characterization techniques. The maximum adsorption capacity predicted by the Sips isotherm model was 379.7 mg P/g for OV-MgO microspheres. The phosphate adsorption in this study had a fast adsorption kinetics and a high selectivity. OV-MgO microspheres had a good acid resistance for phosphate adsorption, but their adsorption capacity decreased under alkaline conditions. The electrostatic attraction, ligand exchange, surface precipitation, inner-sphere surface complexation and oxygen vacancy capture were mainly responsible for efficient removal of phosphate from aqueous solutions. This study probably promoted the development of oxygen vacancy-rich metal (hydr)oxides with potential application prospects.

Electrically empowered microcomb laser.

Optical microcomb underpins a wide range of applications from communication, metrology, to sensing. Although extensively explored in recent years, challenges remain in key aspects of microcomb such as complex soliton initialization, low power efficiency, and limited comb reconfigurability. Here we present an on-chip microcomb laser to address these key challenges. Realized with integration between III and V gain chip and a thin-film lithium niobate (TFLN) photonic integrated circuit (PIC), the laser directly emits mode-locked microcomb on demand with robust turnkey operation inherently built in, with individual comb linewidth down to 600 Hz, whole-comb frequency tuning rate exceeding 2.4 × 1017 Hz/s, and 100% utilization of optical power fully contributing to comb generation. The demonstrated approach unifies architecture and operation simplicity, electro-optic reconfigurability, high-speed tunability, and multifunctional capability enabled by TFLN PIC, opening up a great avenue towards on-demand generation of mode-locked microcomb that is of great potential for broad applications.

Smooth muscle cells, interstitial cells and neurons in the gallbladder (GB): Functional syncytium of electrical rhythmicity and GB motility (Review).

The motility of the gallbladder (GB) involves the storage, concentration and delivery of bile. GB motor functions are controlled by multiple complex factors, such as extrinsic and intrinsic innervation, humoral factors and neuropeptides. GB emptying results from coordinated contractions of the muscular layers of the GB wall. Depolarization of GB smooth muscle (GBSM) depends on the activation of the regular depolarization­repolarization potential, referred to as slow waves (SWs). These rhythmic SWs of GBSM contraction are mediated by several cell types, including smooth muscle cells (SMCs), GB neurons, telocytes (TC) and specialized pacemaker cells called interstitial cells of Cajal (ICC). The present article introduced a new GB motor unit, the SMC­TC­ICC­neuron (STIN) syncytium. In GB, STIN cells provide pacemaker activity, propagation pathways for SWs, transduction of inputs from motor and sensory neurons and mechanosensitivity. The present review provided an overview of STIN cells, mechanisms generating GBSM contractile behavior and GB motility, and discussed alterations of STIN cell function under different disease conditions.

Successful Surgical Removal of a Huge Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Hepatectomy and transcatheter arterial chemoembolisation (TACE) are generally accepted methods for the treatment of huge HCCs, but the most appropriate treatment is still controversial. We report a 43-year woman with giant HCC, who successfully underwent surgery. The patient was admitted with persistent right upper abdominal pain and fever. Before operation, we assessed the residual liver function and reserve capacity of the patient, and excluded the relevant surgical contra-indications. The results showed that the patient could tolerate surgical treatment, so we performed HCC resection, and the patient was successfully treated. Individualised treatment should be carried out according to tumor factors, baseline liver function and patient's functional status, so as to maximise the benefit to patients. Key Words: Huge hepatocellular carcinoma, Hepatectomy, TACE.

Pelvic effusion in patients with ovarian thecoma-fibroma associated with the tumor size and plaste CA-125 level: A retrospective magnetic resonance imaging study.

PURPOSE: To survey the occurrence rate of ascites in patients with thecoma-fibroma and its potential correlation with tumor MR imaging characteristics. METHODS: A total of 40 patients with surgically proven thecoma-fibroma were enrolled in this retrospective study. We determined the tumor size, the components (solid or cystic) and their signal intensity features. Second, we identified ascites according to the fat-suppressed sagittal T2-weighted imaging sequence and divided all cases into two groups (with or without ascites). Furthermore, we explored the correlations of ascites with tumor size, tumor solidity, pathological types, patient's postmenopausal status and serum CA-125 levels by using the χ2 test. RESULTS: (1) Among the 40 cases, 15 tumors were fibromas, 15 thecomas, and 10 fibrothecomas. Nine patients (26.47%) had elevated CA-125 levels (>35.0 U/ml). (2) Thirty-one patients had ascites (77.50%), 29 of which had a small amount of ascites. Nine cases had no ascites (22.50%). (3) MRI showed a solid mass in 22 cases (55.0%), cystic mass in five cases (12.5%) and mixed solid-cystic mass in 13 cases (32.5%). The χ2 test revealed that the incidence of ascites was significantly correlated with tumor size, tumor solidity and serum CA-125 levels (P < 0.05), but not with menopause and pathological type (P > 0.05). CONCLUSION: Our data revealed that the incidence of ascites was 77.50% and was mainly correlated with tumor size and elevated CA-125 levels. These findings have potential value for improving the diagnosis and differential diagnosis of thecoma-fibroma.

Deeper Insights into the Bohart-Adams Model in a Fixed-Bed Column.

The Bohart-Adams model was one of the most widely used breakthrough models in column experiments. However, it usually provided a poor fit for the modeling of an asymmetric breakthrough curve. This work proposed the n-order Bohart-Adams and fractal-like Bohart-Adams models. The former indicated a nonlinear decay process of the concentration of the adsorbate or residual capacity of the adsorbent, while the latter reflected a diffusion-limited process on the heterogeneous surfaces. The Bohart-Adams and modified Bohart-Adams models were mathematically equivalent. The applicability of the n-order Bohart-Adams and fractal-like Bohart-Adams models was validated by norfloxacin and Cu(II) adsorption in a fixed-bed column. Compared with the Bohart-Adams model, the two new models had better fitting performance with higher R2 and lower χ2 values, and all of the residuals were randomly distributed. The fractal-like Bohart-Adams and modified dose-response models provided the best fitting quality for the adsorption of Cu(II) (R2 = 0.9956 and χ2 = 7.56 × 10-4) and norfloxacin (R2 = 0.9991 and χ2 = 1.37 × 10-4), respectively. This work may provide a practical method for the modeling of the asymmetric breakthrough curves.

Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level.

Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer's disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer's Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer's Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer's disease.

Comment on ″Low-cost chitosan-calcite adsorbent development for potential phosphate removal and recovery from wastewater effluent″.

In the adsorption studies, the accurate estimation of the model parameters contributes to getting insights into adsorption behaviors and optimizing adsorber design. After reading the research work of Pap et al. (2020) carefully, it was found that the fitting results were questionable. Thus, this comment tried to address the following aspects: (i) Correction of the fitting results for the kinetic and isotherm models; (ii) Correct form of the Bohart-Adams model; (iii) Usage of the Clark model; and (iv) Effects of the partial or complete experimental data on the model parameters. This work is expected to help readers better understand the adsorption models and estimate the model parameters.

Comment on ″Exponential and logistic functions: The two faces of the Bohart-Adams model″.

The Bohart-Adams model has been one of the most widely used breakthrough models for the modeling of dynamic adsorption behaviors of water pollutants in a fixed-bed column. However, the fitting quality was often questioned by many researchers when the Bohart-Adams model was correlated with the experimental data. Recently, Chu (2020) discussed the two simplified forms of the Bohart-Adams model and tested their applicability. In fact, in our previous study (Hu et al., 2019), it has been proved that the two forms represented the logistic and exponential functions in mathematical nature, respectively. The fitting quality depended on whether the experimental data approached the shape of the model curve. Besides, the curve characteristics and fitting ability of the original Bohart-Adams model were not revealed, and how to analyze asymmetrical breakthrough curve remained to be solved. This comment tried to expound the Bohart-Adams model completely. The authors hope that this work will be helpful for readers who are interested in the adsorption studies.