Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-supervision.

Human anatomy is the foundation of medical imaging and boasts one striking characteristic: its hierarchy in nature, exhibiting two intrinsic properties: (1) locality: each anatomical structure is morphologically distinct from the others; and (2) compositionality: each anatomical structure is an integrated part of a larger whole. We envision a foundation model for medical imaging that is consciously and purposefully developed upon this foundation to gain the capability of "understanding" human anatomy and to possess the fundamental properties of medical imaging. As our first step in realizing this vision towards foundation models in medical imaging, we devise a novel self-supervised learning (SSL) strategy that exploits the hierarchical nature of human anatomy. Our extensive experiments demonstrate that the SSL pretrained model, derived from our training strategy, not only outperforms state-of-the-art (SOTA) fully/self-supervised baselines but also enhances annotation efficiency, offering potential few-shot segmentation capabilities with performance improvements ranging from 9% to 30% for segmentation tasks compared to SSL baselines. This performance is attributed to the significance of anatomy comprehension via our learning strategy, which encapsulates the intrinsic attributes of anatomical structures-locality and compositionality-within the embedding space, yet overlooked in existing SSL methods. All code and pretrained models are available at GitHub.com/JLiangLab/Eden.

Isolation, characterization and pharmacological potentials of methanol extract of Cassia fistula leaves: Evidenced from mice model along with molecular docking analysis.

The purpose of the current investigation was to conduct a detailed analysis of the chemical components and medicinal properties of the methanolic crude extract derived from the leaves of Cassia fistula. This analysis was carried out using both experimental (in vivo) and computational (in silico) methods. Eleven chemicals were chromatographically isolated using GC-MS/MS, which utilizes a library of NIST and Wiley 2020 versions. FTIR analysis of the extract was performed to identify the functional group of the compounds. The glucose-lowering capacity, analgesic, and anti-diarrheal activities of methanolic crude extract were analyzed utilizing a well-known oral glucose tolerance test, tail immersion method, writhing assay, and castor oil-induced diarrheal mice methods, respectively. After 60 min, 120 min, and 180 min of loading the drugs, a significant reduction of blood glucose levels was examined (p < 0.05) in all the extracts of this plant (200 mg/kg, 400 mg/kg and 600 mg/kg) utilized in this research at a time-dependent manner. Similarly, all the crude extracts showed significant (p < 0.05) effects against pain centrally and peripherally compared to the standard drug morphine (2 mg/kg bw) and diclofenac sodium (50 mg/kg bw). Moreover, the methanol extract (400 mg/kg bw) manifested anti-diarrheal efficacy by inhibiting 72.0 % of the diarrheal episode in mice compared to the standard drug loperamide (inhibition = 80.0%). The results of the computational investigations corroborated existing in-vivo findings. Greater or close to equivalent binding affinity to the active binding sites of kappa opioid receptor, glucose transporter 3 (GLUT 3), and cyclooxygenase 2 was indicative of the potential anti-diarrheal, hypoglycemic, and analgesic characteristics of the isolated compounds (COX-2). Moreover, anticancer and antimicrobial potentiality was also found impressive through evaluation of binding affinity with epidermal growth factor receptor (EGFR) and dihydrofolate reductase (DHFR) receptors. Results from this study indicated that C. fistula might be a beneficial natural resource for treating diarrhea, hyperglycemia, and pain. However, additional research is required to conduct a comprehensive phytochemical screening and establish precise action mechanisms of the crude extract or the plant-derived compounds.

Self-supervised learning for medical image analysis: Discriminative, restorative, or adversarial?

Discriminative, restorative, and adversarial learning have proven beneficial for self-supervised learning schemes in computer vision and medical imaging. Existing efforts, however, fail to capitalize on the potentially synergistic effects these methods may offer in a ternary setup, which, we envision can significantly benefit deep semantic representation learning. Towards this end, we developed DiRA, the first framework that unites discriminative, restorative, and adversarial learning in a unified manner to collaboratively glean complementary visual information from unlabeled medical images for fine-grained semantic representation learning. Our extensive experiments demonstrate that DiRA: (1) encourages collaborative learning among three learning ingredients, resulting in more generalizable representation across organs, diseases, and modalities; (2) outperforms fully supervised ImageNet models and increases robustness in small data regimes, reducing annotation cost across multiple medical imaging applications; (3) learns fine-grained semantic representation, facilitating accurate lesion localization with only image-level annotation; (4) improves reusability of low/mid-level features; and (5) enhances restorative self-supervised approaches, revealing that DiRA is a general framework for united representation learning. Code and pretrained models are available at https://github.com/JLiangLab/DiRA.

Thermoexpandable Memokath stent: Usage and efficacy in ureteral and urethral strictures in Saudi Arabia.

Objectives: Double J (DJ) stent is widely used in cases of ureteric strictures as a temporary solution; however, it has certain limitations, such as the need for frequent exchange. Alternatively, a long-lasting thermoexpandable stent (Memokath™ 051) has been used to relieve ureteral obstructions in comorbid patients with multiple reported advantages, such as longer durability which avoids the need of frequent exchanges. In addition, it can be used in certain cases of urethral strictures. Our study is the first in the region to report the experience and outcome of Memokath stent with ureteral and urethral strictures. Materials and Methods: After local IRB approval, we retrospectively reviewed records of 21 patients who underwent insertion of Memokath 051 stent in the ureter and Memokath 045 in the urethra between 2013 and 2021. Indications of insertion, indwelling duration, and causes of removal were collected and analyzed by SPSS. Results: Twenty-one patients received 21 Memokath stents for 11 ureteral strictures and 10 urethral strictures. Fifty-five percent of ureteral strictures were malignant, and 27.3% of the benign ureteric strictures were transplant ureters. Ureteric memokath stents remained functioning for a mean of 16.1 months. Mean indwelling time for transplant ureteric memokath stents was 24.3 months. Total 4 ureteric stents had migrated, 4 stents blocked, and 2 stents were removed as planned and 1 stent removed due to febrile urinary tract infection (UTI). Ten urethral stents remained in place for mean of 14 months. Three stents were removed as planned with resolution of stricture, two were removed due to blockage, three stents had UTI, one was removed due to pain, and one stent remained functioning until the patient expired. Conclusion: Our outcome is comparable to other published studies, suggesting that ureteric Memokath stent is a better option with adequate indwelling time, especially in transplant ureters, in comparison with DJ stents. In addition, Memokath stents can be used in selected recurrent urethral strictures where surgical reconstruction is not feasible.

Developing an exclusive sensor based on molecularly imprinted polymer/Multi-walled carbon nanotubes/Fe3O4@Au nanocomposite for the selective determination of an anti-cancer drug imatinib.

Determination of pharmaceuticals especially anticancer drugs is one of the important issues in environmental and medical investigation and creating good information about human health. The presence sturdy introducing an electroanalytical sensor based on molecularly imprinted polymer (MIP)/Multi-walled carbon nanotubes (MWCNTs)/Au@Fe3O4 nanoparticles modified carbon paste electrode (PE) to determine imatinib (IMA). The MIP/MWCNTs/Au@Fe3O4/PE showed catalytic activity and also a sensitive strategy to sensing IMA in the concentration range 1-1000 µM with a limit of detection of 0.013 µM. The MIP/MWCNTs/Au@Fe3O4/PE has shown interesting results in the analysis of IMA in real samples, and the interference investigations results show the high selectivity of the MIP/MWCNTs/Au@Fe3O4/PE in the monitoring of IMA in complex fluids such as tablet and blood serum and results approved by F-test and t-test as statistical methods.

Cu-BTC MOF/ionic liquid nanocomposite as novel catalyst to electrochemical monitoring of digoxin in pharmaceutical and environmental samples.

There is no effective environmental treatment strategy that does not include monitoring for pharmaceutical compounds in environmental and biological fluids. The widespread presence of pharmaceutical-based pollutants in water sources is a significant public health concern. The treatment process relies heavily on maintaining a stable digoxin concentration in bodily fluids. Finding the correct dose for this medication appears to be crucial. In this research, an easy and high sensibility electrochemical sensor was developed to determine digoxin based on a paste electrode (CPE) that was modified with Cu-BTC MOF and ion liquid ((IL); 1-Methyl-3-Butyl-imidazolinium bromide in this case) using voltammetric methods in 0.1 M phosphate buffer solution (PBS) at pH 5.0. The sensor's selectivity was significantly increased by using Cu-BTC MOF and IL to detect digoxin. The characteristics of the electrode modifiers were evaluated by SEM, XRD and EDS techniques. The LDR was found to be 0.1-40 µM and the LOD of 0.08 µM, respectively.

Biofeedback Treatment Can Improve Clinical Condition and Quality of Life in Patients with Pelvic Floor Dyssynergy with Irritable Bowel Syndrome: A Prospective Cohort Study.

Background: Chronic constipation is a common health concern. Defecatory disorders are considered one of the mechanisms of chronic idiopathic constipation. This study aimed to evaluate the effect of concurrent irritable bowel syndrome (IBS) on the success rate and response to biofeedback therapy in patients with chronic constipation and pelvic floor dyssynergia (PFD). Methods: This prospective cohort study was performed at the Imam Khomeini Hospital Complex in Tehran from October 2020 to July 2021. Patients aged 18-70 years with chronic constipation and PFD confirmed by clinical examination, anorectal manometry, balloon expulsion test, and/or defecography were included. All patients failed to respond to treatment with lifestyle modifications and laxative use. The diagnosis of IBS was based on the ROME IV criteria. Biofeedback was educated and recommended to all patients. We used three different metrics to assess the patient's response to biofeedback: 1) constipation score (questionnaire), 2) lifestyle score (questionnaire), and 3) manometry findings (gastroenterologist report). Results: Forty patients were included in the final analysis, of which 7 men (17.5%) and 21 (52.2%) had IBS. The mean age of the study population was 37.7 ± 11.4. The average resting pressure decreased in response to treatment; however, this decrease was statistically significant only in non-IBS patients (P = 0.007). Patients with and without IBS showed an increase in the percentage of anal sphincter relaxation in response to treatment, but this difference was not statistically significant. Although the first sensation decreased in both groups, this decrease was not statistically significant. Overall, the clinical response was the same across IBS and non-IBS patients, but constipation and lifestyle scores decreased significantly in both groups of patients with and without IBS (P < 0.001). Conclusion: Biofeedback treatment appears to improve the clinical condition and quality of life of patients with PFD. Considering that a better effect of biofeedback in correcting some manometric parameters has been seen in patients with IBS, it seems that paying attention to the association between these two diseases can be helpful in deciding on treatment.

Evaluation of short-term outcomes of neoadjuvant chemotherapy followed by radical cystectomy in muscle-invasive bladder cancer: a single Egyptian institution experience.

BACKGROUND AND AIM: Neoadjuvant chemotherapy (NAC) before radical cystectomy (RC) became the standard of care for muscle-invasive bladder cancer (MIBC) in the last few years. We aimed to evaluate the radiological, pathological responses to NAC, and the 30-day surgical outcomes after RC in MIBC. PATIENTS AND METHODS: A retrospective cohort study involving adult patients with localized urothelial MIBC who received NAC followed by RC at the National Cancer Institute of Egypt (NCI-E) for 2 years (2017 and 2018). Out of 235 MIBC cases, we recognized 72 patients (30%) who fitted the eligibility criteria. RESULTS: A cohort of 72 patients with a median age of 60.5 years (range 34-87). Hydronephrosis, gross extravesical extension (cT3b), and radiologically negative nodes (cN0) were depicted initially in 45.8, 52.8, and 83.3% of patients, respectively. Gemcitabine and cisplatin (GC) was the rampant NAC employed in 95.8%. Radiological evaluation post NAC using RECIST v1.1 revealed a response rate (RR) of 65.3% in bladder tumor and progressive disease in the former and lymph nodes encountered in 19.4 and 13.9%, respectively. The median time from the end of NAC to surgery was 8.1 weeks (range 4-15). Open RC and ileal conduit were the most common types of surgery and urinary diversion, respectively. Pathological down-staging was encountered in 31.9%, and only 11 cases (15.3%) achieved pathological complete response (pCR). The latter was significantly correlated with the absence of hydronephrosis, low-risk tumors, and associated bilharziasis (p = 0.001, 0.029, and 0.039, respectively). By logistic regression, the high-risk category was the only independent factor associated with a poor likelihood of achieving pCR (OR 4.3; 95% CI 1.1-16.7; p = 0.038). Thirty-day mortality occurred in 5(7%) patients, and 16(22%) experienced morbidity, with intestinal leakage being the most frequent complication. cT4 was the only significant factor associated with post-RC morbidity and mortality compared to cT2 and cT3b (p = 0.01). CONCLUSIONS: Our results are further supporting the radiological and pathological benefits of NAC in MIBC, evidenced by tumor downstaging and pCR. The complication rate after RC is still considerable; hence, more larger studies are necessary to postulate a comprehensive risk assessment tool for patients who would get the maximum benefit from NAC, hoping to accomplish higher complete response rates with ultimately increased adoption of the bladder preservation strategies.

Parotid gland masses: outcomes in the pediatric age group.

BACKGROUND: Childhood parotid neoplasms appear to have different characteristics from adults. This point, in addition to the rarity of these tumors, reflects the challenges faced in diagnosing and treating parotid neoplasms in children. PATIENTS AND METHODS: This retrospective study included all children who presented to the Children's Cancer Hospital Egypt (CCHE, 57357) with parotid masses from January 2008 to December 2020. RESULTS: Twenty-one patients were included. Malignant neoplasms were found in 12 (57.1%) of which mucoepidermoid carcinoma was the most common. Benign neoplasms were found in 6 (28.6%) all of them were pleomorphic adenoma, and non-neoplastic lesions were found in 3 (14.3%). Superficial, deep, or total parotidectomy was performed according to the involved lobes. The facial nerve was sacrificed in three cases because of frank invasion by the tumor. Neck dissection was considered in clinically positive lymph nodes and/or T3/4 masses. Complications occurred in 7 (33.3%) all were of the malignant cases. Adjuvant radiotherapy was restricted to high-risk cases (7 cases). Recurrence occurred in two cases, and one patient died of distant metastasis. Fine needle aspiration cytology (FNAC) showed 88.9% sensitivity and 100% specificity for diagnosing malignant neoplasms. The correlation of radiological and pathological staging was fair (66.74% for overall staging). CONCLUSIONS: Parotidectomy is the backbone treatment for benign and malignant pediatric parotid tumors. Neck nodal dissection should be considered after preoperative FNAC of suspicious nodes. Adjuvant radiotherapy is considered only in high-risk tumors. Preoperative FNAC of parotid masses and clinically suspicious lymph nodes is highly recommended.

CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging.

Recently, self-supervised instance discrimination methods have achieved significant success in learning visual representations from unlabeled photographic images. However, given the marked differences between photographic and medical images, the efficacy of instance-based objectives, focusing on learning the most discriminative global features in the image (i.e., wheels in bicycle), remains unknown in medical imaging. Our preliminary analysis showed that high global similarity of medical images in terms of anatomy hampers instance discrimination methods for capturing a set of distinct features, negatively impacting their performance on medical downstream tasks. To alleviate this limitation, we have developed a simple yet effective self-supervised framework, called Context-Aware instance Discrimination (CAiD). CAiD aims to improve instance discrimination learning by providing finer and more discriminative information encoded from a diverse local context of unlabeled medical images. We conduct a systematic analysis to investigate the utility of the learned features from a three-pronged perspective: (i) generalizability and transferability, (ii) separability in the embedding space, and (iii) reusability. Our extensive experiments demonstrate that CAiD (1) enriches representations learned from existing instance discrimination methods; (2) delivers more discriminative features by adequately capturing finer contextual information from individual medial images; and (3) improves reusability of low/mid-level features compared to standard instance discriminative methods. As open science, all codes and pre-trained models are available on our GitHub page: https://github.com/JLiangLab/CAiD.

POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis.

Vision transformer-based self-supervised learning (SSL) approaches have recently shown substantial success in learning visual representations from unannotated photographic images. However, their acceptance in medical imaging is still lukewarm, due to the significant discrepancy between medical and photographic images. Consequently, we propose POPAR (patch order prediction and appearance recovery), a novel vision transformer-based self-supervised learning framework for chest X-ray images. POPAR leverages the benefits of vision transformers and unique properties of medical imaging, aiming to simultaneously learn patch-wise high-level contextual features by correcting shuffled patch orders and fine-grained features by recovering patch appearance. We transfer POPAR pretrained models to diverse downstream tasks. The experiment results suggest that (1) POPAR outperforms state-of-the-art (SoTA) self-supervised models with vision transformer backbone; (2) POPAR achieves significantly better performance over all three SoTA contrastive learning methods; and (3) POPAR also outperforms fully-supervised pretrained models across architectures. In addition, our ablation study suggests that to achieve better performance on medical imaging tasks, both fine-grained and global contextual features are preferred. All code and models are available at GitHub.com/JLiangLab/POPAR.

Benchmarking and Boosting Transformers for Medical Image Classification.

Visual transformers have recently gained popularity in the computer vision community as they began to outrank convolutional neural networks (CNNs) in one representative visual benchmark after another. However, the competition between visual transformers and CNNs in medical imaging is rarely studied, leaving many important questions unanswered. As the first step, we benchmark how well existing transformer variants that use various (supervised and self-supervised) pre-training methods perform against CNNs on a variety of medical classification tasks. Furthermore, given the data-hungry nature of transformers and the annotation-deficiency challenge of medical imaging, we present a practical approach for bridging the domain gap between photographic and medical images by utilizing unlabeled large-scale in-domain data. Our extensive empirical evaluations reveal the following insights in medical imaging: (1) good initialization is more crucial for transformer-based models than for CNNs, (2) self-supervised learning based on masked image modeling captures more generalizable representations than supervised models, and (3) assembling a larger-scale domain-specific dataset can better bridge the domain gap between photographic and medical images via self-supervised continuous pre-training. We hope this benchmark study can direct future research on applying transformers to medical imaging analysis. All codes and pre-trained models are available on our GitHub page https://github.com/JLiangLab/BenchmarkTransformers.

DiRA: Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysis.

Discriminative learning, restorative learning, and adversarial learning have proven beneficial for self-supervised learning schemes in computer vision and medical imaging. Existing efforts, however, omit their synergistic effects on each other in a ternary setup, which, we envision, can significantly benefit deep semantic representation learning. To realize this vision, we have developed DiRA, the first framework that unites discriminative, restorative, and adversarial learning in a unified manner to collaboratively glean complementary visual information from unlabeled medical images for fine-grained semantic representation learning. Our extensive experiments demonstrate that DiRA (1) encourages collaborative learning among three learning ingredients, resulting in more generalizable representation across organs, diseases, and modalities; (2) outperforms fully supervised ImageNet models and increases robustness in small data regimes, reducing annotation cost across multiple medical imaging applications; (3) learns fine-grained semantic representation, facilitating accurate lesion localization with only image-level annotation; and (4) enhances state-of-the-art restorative approaches, revealing that DiRA is a general mechanism for united representation learning. All code and pretrained models are available at https://github.com/JLiangLab/DiRA.

Survey of antibacterial activity and release kinetics of gold-decorated magnetic nanoparticles of Fe0 conjugated with sulfamethoxazole against Escherichia coli and Staphylococcus aureus.

Drug delivery of antibiotics with magnetic nanoparticles improved by coating metals such as gold and silver has recently been studied. This work describe a simple method to synthesize modified magnetic nanoparticles which have high ability to modify the customary formulation of antibiotics such as sulfamethoxazole (SMX) and pursuant study of adsorption-desorption (release) of this drug. These synthesized nanoparticles were characterized by different methods, including field emission scanning electron microscopy, energy dispersive X-ray spectroscopy and mapping, Fourier-transform infrared spectroscopy, X-ray diffraction, vibrating-sample magnetometry, thermogravimetric analysis and zeta potential test. Present assay showed a well correlation with the introduced carrier for the drug. Also the hypothesis were proved by some adsorption isotherm models and drug kinetics studies of carriers with different drug release kinetics models. This study confirmed the adsorption isotherm models and kinetics of drug sorbate are Temkin and Pseudo-First-Order Lagergren models, respectively; the kinetics of drug release from this carrier is based on Zero-Order model. The values of MIC in antibacterial test for pure SMX and SMX conjugated nanoparticles against Escherichia coli were calculated to be 14 and 2.5 µg/mL, respectively, and these values against Staphylococcus aureus were 24 and 1.25 µg/mL, respectively.

Facile Synthesis of NiO/ZnO nanocomposite as an effective platform for electrochemical determination of carbamazepine.

The pharmaceutical science demand for sustainable and selective electrochemical sensors which exhibit ultrasensitive capabilities for the monitoring of different drugs. In an attempt to build a useful electrochemical sensor, we describe a most efficient method for the fabrication of NiO/ZnO nanocomposite through aqueous chemical growth method. The successfully synthesized NiO/ZnO nanocomposite is successfully employed to modify a glassy carbon electrode in order to build a sensitive and reliable electrochemical sensor for the detection of carbamazepine (CBZ), an anticonvulsant drug. The morphological texture, functionalities and crystalline structure of prepared nanocomposite were determined via FTIR, XRD, EDX, TEM, and SEM analysis. In order to examine the charge transfer kinetics, the cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to exploit the electrochemical properties of the synthesized nanocomposite. The NiO/ZnO nanocomposite exhibited excellent electron transfer kinetics and less resistive behavior than the individual NiO and ZnO nanoparticles. The differential pulse voltammetry and cyclic voltammetry tools were used for the fluent determination of CBZ. Certain parameters were optimized to develop an effective method including optimum scan rate 60 mV/s, potential range from 0.4 to 1.4 V and BRB as supporting electrolyte with pH 3. The developed sensor showed exceptional response for CBZ under the linear dynamic range from 5 to 100 µM. The limit of detection of proposed NiO/ZnO sensor for the CBZ was calculated to be 0.08 µM. The analytical approach of prepared electrochemical sensor was investigated in different pharmaceutical formulation with acceptable percent recoveries ranging from 96.7 to 98.6%.

Simple turn-off fluorescence sensor for determination of raloxifene using gold nanoparticles stabilized by chitosan hydrogel.

It is essential to develop a simple, applicable, and reliable assay to anticancer drug raloxifene (RAF) because of its significant usage and side effect due to entering residue in the environment. Fluorescence sensors developed and widely used because of them high selectivity, fast-response, and highly-sensitivity. The gold nanoparticles using chitosan hydrogel was synthesized and applied as a fluorescence sensor to determine the trace amount of RAF. The characterization methods including DLS, FE-SEM, EDX, XRD, and FT-IR were performed to confirm the synthesized structure. This sensor turned off the fluorescent signals proportional to RAF concentrations at 400 nm. The RAF can be detected in the linear range from 5 × 10-7 to 5 × 10-5 M. Limits of detection and quantification were obtained as 34 × 10-8 and 11 × 10-7 M as well as the relative standard deviation calculated as 1.63% in RAF measuring. The effective parameters on quenching efficiency were studied by central composite design (CCD) with response surface methodology (RSM). The effective parameters in RAF determination, include analyte concentration, temperature, contact time, and pH, were obtained as 35 µM, 30 °C, 8 min, and pH = 8.5. The sensor was applied to determine the RAF concentrations in biological and environmental samples with satisfactory recoveries between 97.5% and 109%.

Advancement in electrochemical strategies for quantification of Brown HT and Carmoisine (Acid Red 14) From Azo Dyestuff class.

Brown HT and carmoisine, which are the most used dyestuffs in pharmaceuticals, textiles, cosmetics and foods, are important components of the Azo family. Although the Azo group is not toxic or carcinogenic under normal conditions, these dyestuffs require great care due to the reduction of the Azo functional group to amines. In particular, fast, reliable, easy, on-site and precise determinations of these substances are extremely necessary and important. In this review, the properties, applications, and electrochemical determinations of brown HT and carmoisine, which are used as synthetic food colorants, are discussed in detail. Up to now, sensor types, detection limits (LOD and LOQ), and analytical applications in the developed electrochemical strategies for both substances were compared. In addition, the validation parameters such as the variety of the sensors, sensitivity, selectivity and electrochemical technique in these studies were clarified one by one. While the electrochemical techniques recommended for brown HT were mostly used for the removal of dyestuff, for carmoisine they included fully quantitative centered studies. The percentiles of voltammetric techniques, which are the most widely used among these electroanalytical methods, were determined. The benefits of a robust electrochemical strategy for the determination of both food colors are summed up in this review. Finally, the brown HT and carmoisine suggestions for future perspectives in electrochemical strategy are given according to all their applications.

Magnetic nanoparticles based on cerium MOF supported on the MWCNT as a fluorescence quenching sensor for determination of 6-mercaptopurine.

In this study, a new magnetic nanocomposite was developed as an efficient and fast-response fluorescence quenching sensor for determination of anticancer drug 6-mercaptopurine (6-MP). For this purpose, the needle-shape fluorescence metal-organic framework of cerium (Ce-MOF) were successfully synthesized on the surface of multiwalled carbon nanotubes using 1,3,5-benzenetricarboxylic acid ligand via a facile solvothermal assisted route and magnetized. The accuracy of the proposed synthesis was confirmed using the FT-IR, FE-SEM, XRD, and VSM methods. The obtained product as presented the fluorescence emission in 331 nm by excitation of 293 nm in excitation/emission slit widths of 10.0 nm. The operation of suggested method is based on quenching the fluorescence signal in accordance with increasing the 6-MP concentration. The proposed assay effectively detected the trace amount of 6-MP in the linear range of 1.0 × 10-6 to 7 × 10-5 M. The limit of detection and limit of quantification were obtained as 8.6 × 10-7 and 2.86 × 10-6 M, respectively. The analyte molecule was determined in real samples with satisfactory recoveries between 98.75 and 105.33.

Ultrasensitive and highly selective "turn-on" fluorescent sensor for the detection and measurement of melatonin in juice samples.

Melatonin (MLT), a hormone related to the regulation of brain functions, is directly related to sleep quality and is considered to be a possible adjuvant therapy for patients needing hospitalization for coronavirus disease 2019 pneumonia, and accurate measurement of MLT is crucial. Herein, a new, highly sensitive, and easy operation fluorescent probe was provided based on Zr metal-organic framework encapsulation into the molecularly imprinted polymer (MOF@MIP). By combining unique properties of MIP and fluorescent MOF, selectivity and operation of the applied method were significantly improved. Different characterization methods, such as XRD, FT-IR, and FE-SEM, were used to confirm the synthesis reliability. MOF@MIP was successfully used for the precise identification and ultrasensitive detection for trace amounts of MLT. The detection mechanism for the analytical system is based on the ''turn-on'' fluorescence (FL) signal in 404 nm. The findings proved that it is possible to detect trace amounts of MLT in real samples including grape, cherry, and sour cherry juice. The linear range and the limit of detection (LOD) for trace amounts of MLT were obtained as 1-100 ng/mL and 0.18 ng/mL, respectively.

The effect of low FODMAP diet with and without gluten on irritable bowel syndrome: A double blind, placebo controlled randomized clinical trial.

BACKGROUND & AIM: Although the effects of low fermentable oligosaccharide, disaccharide, monosaccharide, and polyol (FODMAP) diet on amelioration of irritable bowel syndrome (IBS) symptoms have been reported previously, it has not yet been elucidated whether the gluten of wheat and barley induces the symptoms or only their fructans lead to aggravation of the symptoms. The aim of this study was to assess the effect of low FODMAPs diet with vs. without gluten on clinical symptoms in IBS patients. METHODS: In this double-blind, placebo-controlled randomized trial, forty nine IBS patients were randomly assigned to placebo and/or intervention group. Patients in the intervention group received 5 gr/day of gluten powder with low FODMAP diet, while placebo group received 5 gr of rice flour as placebo, with low FODMAP diet. Quality of life (QoL) and IBS-SSS (symptom severity score) were measured before and after the intervention using a valid QoL questionnaire and a standard visual analog scale, respectively. RESULTS: Significant improvements were observed in total scores of IBS-SSS (-32% vs. - 49%), abdominal pain intensity (-45% vs. -52%), and frequency (-26 vs. -46%), abdominal distension (-29% vs. -63%), Interference with community function (-14% vs. -45%) and quality of life (+23 vs. +32%) in both gluten and placebo groups respectively (P < 0.05). Only 5 patients in the gluten-containing diet reported exacerbation of their symptoms. CONCLUSION: Exacerbation of IBS symptoms after wheat and barley consumption is due to their fructan, and not related to their gluten content in most of the patients. CLINICAL TRIAL REGISTRATION NO: IRCT20100524004010N29.