Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT

PURPOSE/OBJECTIVE(S)

The diagnosis of lymph node (LN) metastasis in computed tomography (CT) is an essential yet challenging task in esophageal cancer staging and treatment planning. Although criteria (e.g., RECIST, morphological/texture features) are proposed to predict LN metastasis, the diagnostic accuracy remains low with sensitivity <50% and specificity <75%, as reported in previous studies. Deep learning (DL) has the potential to address this issue by learning from large-scale labeled data. However, due to the practical surgery procedure in lymph node dissection, it is difficult to pair the metastasis of individual LN reported in the pathology report to the LN instance found in the CT image. Hence, in this study, we first use pathology reports to determine the LNS metastasis, then develop a multiple instance deep learning (MIDL) model to predict lymph node station (LNS) metastasis.

MATERIALS/METHODS

We collected 1200 esophageal cancer patients with preoperative contrast-enhanced CT before surgery. A recently developed automatic mediastinal LNS segmentation model was first applied to segment LNS of 1 to 8 based on the IASLC protocol. For each LNS, the local CT region of interest (ROI) was cropped to generate a station-wise CT patch, where the LNS was labeled as metastatic if at least one metastatic LN was indicated in the pathology report. Using the station-wise CT patch and LNS label, we train a 3D MIDL model, MobileNetV3, to predict LNS metastasis. To better provide the LN position priors in MIDL, LN instances (with a short axis >4mm) were also segmented using an automatic LN detection algorithm and were added to the MIDL model as an auxiliary input. Five-fold cross-validation was conducted to evaluate the MIDL performance.

RESULTS

The MIDL model's performance is summarized in Table 1. The MIDL model incorporating an additional LN instance mask demonstrated a superior overall AUC of 0.7539, surpassing the model without the LN mask input by 2.93%. The specificity was evaluated at a threshold resulting in a recall of 0.7, and the best model outperformed the CT input model in terms of specificity by 2.11%. This highlights the value of including the LN position prior to the MIDL model. Notably, when a threshold was set to result in a specificity of 75%, the best MIDL model demonstrated a significantly higher recall compared to the previously reported clinical diagnostic recall (39.7% vs. 63.21%).

CONCLUSION

We developed a MIDL classification model to predict LNS metastasis using CT scans of 1200 patients. Our findings suggest that the MIDL model can substantially improve LNS metastasis prediction and has the potential to play an essential role in cancer staging, treatment planning, and prognostic analysis.

Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy

PURPOSE/OBJECTIVE(S)

In lung cancer radiation therapy, clinicians must outline the gross tumor volume (GTV) precisely on the planning computed tomography (pCT) for accurate radiation dose delivery. However, due to the limited contrast between tumor and normal tissues in lung parenchyma, accurate delineation of tumor boundaries is difficult leading to large inter-observer variation. In this study, we develop an anatomy-guided lung GTV deep segmentation model using a training cohort of multi-center datasets. The quantitative segmentation performance is evaluated on an independent dataset, where the inter-observer delineation variation is also assessed.

MATERIALS/METHODS

We collected and curated four publicly available lung datasets with GTV annotations (Lung-PET-CT-Dx, LIDC-IDRI, NSCLC-Radiogenomics and RIDER-CT) for deep learning model development. A total of 871 CT scans of patients, who were diagnosed with T1-T4 NSCLC, were available for training after data curation. The GTV annotations of primary tumor were examined and edited by two experienced radiation oncologists following the RTOG 1106 protocol. An anatomy-guided deep learning model was proposed, which consisted two deep networks. The first deep network used CT scan as input and segmented 4 anatomic organs (airway, heart, pulmonary artery and pulmonary vein), while the second deep network took both CT scan and these pre-segmented 4 organs as input and segmented the lung GTV. With the help of anatomic priors from 4 pre-segmented organs, the second deep network could more easily locate the GTV. We used nnUNet as the deep segmentation network. For evaluation, we used NSCLC-Radiomics as the testing dataset, which contains 20 CT scans each annotated by 5 radiation oncologists. The auto-segmented GTV were compared against each of the manual GTV reference. Inter-observer variation was also assessed using the 5 manual GTV references.

RESULTS

The proposed anatomic-guided lung GTV segmentation model achieved a mean Dice score of 82.4% and 95% Hausdorff distance (HD95) of 6.9mm when averaged cross 20 patients and 5 GTV references (Table 1), which outperformed the basic deep GTV segmentation model by markedly reducing 19.4% HD95 error. The performance of proposed model was also comparable to the inter-observer variation (Dice score: 82.4% vs. 81.9%, HD95 6.9 vs. 6.4mm), indicating that our model had similar reproducibility as human observers.

CONCLUSION

We developed and tested an anatomy-guided deep learning model for segmenting GTV in NSCLC patients. The model achieves high quantitative segmentation performance, which is comparable to the human observer variation. It can be potentially used in radiotherapy practice to improve GTV delineation consistency and reduce workloads of radiation oncologists.

[Impact of different diagnostic criteria for assessing mild micro-hepatic encephalopathy in liver cirrhosis: an analysis based on a prospective, multicenter, real-world study]

Objective: To compare the differences in the prevalence of mild micro-hepatic encephalopathy (MHE) among patients with cirrhosis by using the psychometric hepatic encephalopathy score (PHES) and the Stroop smartphone application (Encephal App) test. Methods: This prospective, multi-center, real-world study was initiated by the National Clinical Medical Research Center for Infectious Diseases and the Portal Hypertension Alliance and registered with International ClinicalTrials.gov (NCT05140837). 354 cases of cirrhosis were enrolled in 19 hospitals across the country. PHES (including digital connection tests A and B, digital symbol tests, trajectory drawing tests, and serial management tests) and the Stroop test were conducted in all of them. PHES was differentiated using standard diagnostic criteria established by the two studies in China and South Korea. The Stroop test was evaluated based on the criteria of the research and development team. The impact of different diagnostic standards or methods on the incidence of MHE in patients with cirrhosis was analyzed. Data between groups were differentiated using the t-test, Mann-Whitney U test, and χ (2) test. A kappa test was used to compare the consistency between groups. Results: After PHES, the prevalence of MHE among 354 cases of cirrhosis was 78.53% and 15.25%, respectively, based on Chinese research standards and Korean research normal value standards. However, the prevalence of MHE was 56.78% based on the Stroop test, and the differences in pairwise comparisons among the three groups were statistically significant (kappa = -0.064, P < 0.001). Stratified analysis revealed that the MHE prevalence in three groups of patients with Child-Pugh classes A, B, and C was 74.14%, 83.33%, and 88.24%, respectively, according to the normal value standards of Chinese researchers, while the MHE prevalence rates in three groups of patients with Child-Pugh classes A, B, and C were 8.29%, 23.53%, and 38.24%, respectively, according to the normal value standards of Korean researchers. Furthermore, the prevalence rates of MHE in the three groups of patients with Child-Pugh grades A, B, and C were 52.68%, 58.82%, and 73.53%, respectively, according to the Stroop test standard. However, among the results of each diagnostic standard, the prevalence of MHE showed an increasing trend with an increasing Child-Pugh grade. Further comparison demonstrated that the scores obtained by the number connection test A and the number symbol test were consistent according to the normal value standards of the two studies in China and South Korea (Z = -0.982, -1.702; P = 0.326, 0.089), while the other three sub-tests had significant differences (P < 0.001). Conclusion: The prevalence rate of MHE in the cirrhotic population is high, but the prevalence of MHE obtained by using different diagnostic criteria or methods varies greatly. Therefore, in line with the current changes in demographics and disease spectrum, it is necessary to enroll a larger sample size of a healthy population as a control. Moreover, the establishment of more reliable diagnostic scoring criteria will serve as a basis for obtaining accurate MHE incidence and formulating diagnosis and treatment strategies in cirrhotic populations.

An integrated and flexible PDMS/Au film-based electrochemical immunosensor via Fe–Co MOF as a signal amplifier for alpha fetoprotein detection

Ultrasensitive determination of tumor marker (TM) is of great significance in cancer prevention and diagnosis. Traditional TM detection methods involve large instrumentation and professional manipulation, which complicate the assay procedures and increase the cost of investment. To resolve these problems, an integrated electrochemical immunosensor based on the flexible polydimethylsiloxane/gold (PDMS/Au) film with Fe-Co metal-organic framework (Fe-Co MOF) as a signal amplifier was fabricated for ultrasensitive determination of alpha fetoprotein (AFP). First, gold layer was deposited on the hydrophilic PDMS film to form the flexible three-electrode system, and then the thiolated aptamer for AFP was immobilized. Afterward, the aminated Fe-Co MOF possessing high peroxidase-like activity and large specific surface area was prepared by a facile solvothermal method, and subsequently the biofunctionalized MOF could effectively capture biotin antibody (Ab) to form MOF-Ab as a signal probe and amplify the electrochemical signal remarkably, thereby realizing highly sensitive detection of AFP with a wide linear range of 0.01-300 ng/mL and a low detection limit of 0.71 pg/mL. In addition, the PDMS based-immunosensor showed good accuracy for assaying of AFP in clinical serum samples. The integrated and flexible electrochemical immunosensor based on the Fe-Co MOF as a signal amplifier demonstrates great potential for application in the personalized point-of-care (POC) clinical diagnosis.

A wearable sweat electrochemical aptasensor based on the Ni-Co MOF nanosheet-decorated CNTs/PU film for monitoring of stress biomarker

Monitoring cortisol, a hormone released by the adrenal cortex in response to stress, is essential to evaluate the endocrine response to stress stimuli. While the current cortisol sensing methods require large laboratory settings, complex assay, and professional personnel. Herein, a novel flexible and wearable electrochemical aptasensor based on a Ni-Co metal-organic frameworks (MOF) nanosheet-decorated carbon nanotubes (CNTs)/polyurethane (PU) film is developed for rapid and reliable detection of cortisol in sweat. First, the CNTs/PU (CP) film was prepared by a modified wet spinning technology, and the CNTs/polyvinyl alcohol (PVA) solution was thermally deposited on the surface of CP film to form the highly flexible CNTs/PVA/CP (CCP) film with excellent conductivity. Then aminated Ni-Co MOF nanosheet prepared by a facile solvothermal method was conjugated with streptavidin and modified on the CCP film. Biofunctional MOF can effectively capture cortisol aptamer due to its excellent specific surface area. In addition, the MOF with peroxidase activity can catalytic oxidization of hydroquinone (HQ) by hydrogen peroxide (H₂O₂), which could amplify the peak current signal. The catalytic activity of Ni-Co MOF was substantially suppressed in the HQ/H₂O₂ system due to the formation of the aptamer-cortisol complex, which reduced the current signal, thereby realizing highly sensitive and selective detection of cortisol. The sensor has a linear range of 0.1-100 ng/mL and a detection limit of 0.032 ng/mL. Meanwhile, the sensor showed high accuracy for cortisol detection under mechanical deformation conditions. More importantly, the prepared MOF/CCP film based three-electrode was assembled with the polydimethylsiloxane (PDMS) substrate, and the sweat-cloth was used as the sweat collection channel to fabricate a wearable sensor patch for monitoring of cortisol in volunteers' sweat in the morning and evening. This flexible and non-invasive sweat cortisol aptasensor shows great potential for quantitative stress monitoring and management.

Determination of ribavirin by molecularly imprinted electrochemical sensors using pyrro-1-propionyl-alaninoyl-chitooligosaccharide and pyrrole as bifunctional monomers on Prussian blue-gold nanocomposite films

Herein, we developed a highly sensitive imprinted electrochemical sensor for the trace detection of ribavirin (RBV) using pyrrole (PYR) and pyrro-1-propionyl-alaninoyl-chitooligosaccharides (PPACO) as bifunctional monomers on Prussian blue-gold nanocomposite films. PPACO had strong molecular effect on RBV molecule and was selected by quantitative calculations. After the deposition of the Prussian blue-gold nanocomposite on a glassy carbon electrode (GCE) surface, a 4-aminothiophenol layer successfully self-assembled on the surface. Subsequently, the molecularly imprinted membrane (MIM) was subjected to electrochemical polymerization on the electrode surface using RBV as the template and PPACO and PYR as the two monomers. After eluting the RBV molecules from the MIM, the fabricated RBV-MIM/Fn-Au-PB/GCE exhibited the specific adsorption of RBV. Under optimal conditions, differential pulse voltammetry (DPV) was used to measure the performance of the synthesized sensor, which exhibited a linear relationship between the decreasing peak current and RBV concentration from 0.015 to 3.5 μM with a low detection limit of 3 nM (S/N = 3). As a proof of concept, RBV-MIM/Fn-Au-PB/GCE was also applied to monitor the RBV content in RBV granules. It showed a satisfactory recovery (96.5-99.2%) with a relative standard deviation of less than 3.5% (n = 5), and thus, we believe it has potential for practical applications.

Correlation between capsule endoscopy classification and CT lymphangiography of primary intestinal lymphangiectasia

AIM

To investigate the correlation between capsule endoscopy (CE) classification of primary intestinal lymphangiectasia (PIL) and computed tomography (CT) lymphangiography (CTL).

MATERIALS AND METHODS

A total of 52 patients with diagnosed PIL were enrolled. All patients were examined using CTL and small intestinal CE before surgery. CE assessments included the morphology, scope, colour, and size of lesions. CTL assessments included intestinal wall, lymphatic vessel dilatation, lymph fluid reflux, and lymphatic fistula. Patients were divided into three groups according to type diagnosed by CE, and the CTL characteristics were analysed among the groups.

RESULTS

CE showed 15 patients with type I, 27 with II, and 10 with type III. Intestinal wall thickening was observed in 15 type I, 21 type II, and seven type III. Pericardial effusion was observed in only three type I patients; the difference among types was statistically significant (p=0.02). Abnormal contrast agent distribution in the intestinal wall and mesentery was observed in 15 type II patients, and the difference was significantly greater than that of types I and III (p=0.02). Abnormal contrast agent distribution in the abdominal cavity was observed in 12 type II, and the difference was statistically significant (p=0.03).

CONCLUSION

The CE PIL classification reflects the extent and scope of intestinal mucosa lesions; CTL more systematically demonstrates abnormal lymphatic vessels or reflux, and its manifestations of PIL are related to the CE classification. The combination of CTL with CE is useful for accurately evaluating PIL, and provides guidance for preoperative assessment and treatment management of PIL patients.

Correlation between glenoid bone structure and recurrent anterior dislocation of the shoulder joint

BACKGROUND

The aim of the study was to investigate the anatomical characteristics and symmetry of the bilateral glenoid structures of Chinese people and to explore the relationship between the glenoid bone structure and recurrent anterior dislocation.

MATERIALS AND METHODS

The control group included 131 individuals with no history of shoulder dislocation. The dislocation group consisted of 131 patients with a history of unilateral shoulder dislocation. All subjects underwent computed tomography scans. Glenoid shape (pear-shaped, inverted comma-shaped, oval-shaped), width, height, depth, version angle, area, maximum fitting circle area and volume were measured.

RESULTS

There was no significant difference in normal bilateral glenoid of Chinese people (p > 0.05). There were statistically significant differences in depth, height to width ratio, maximum fitting circle area and shape between the dislocation and control groups (p < 0.05). Regression analyses showed that the glenoid depth (odds ratio [OR] 0.48; p < 0.01), the glenoid height to width ratio (OR 28.61; p < 0.01), the glenoid maximum fitting circle area (OR 1.01; p < 0.01) and the glenoid shape (p <0.05; pear-shaped OR 0.432; inverted comma-shaped OR 0.954) were associated with anterior shoulder instability. Pear-shaped and inverted comma-shaped glenoid had lower risk of recurrent anterior shoulder dislocation compared to oval glenoid. Receiver operating characteristic curve analysis showed that individuals with anterior shoulder instability had smaller glenoid depth and larger height to width ratio and the glenoid maximum fitting circle area compared with the control group.

CONCLUSIONS

The normal bilateral glenoids of Chinese people are basically symmetrical. The glenoid shape, depth, height to width ratio and maximum fitting circle area are risk factors for recurrent anterior shoulder dislocation. Evaluation of the glenoid bone structure enables more accurate prediction of the risk of recurrent shoulder dislocation.

Polymer surface ligand and silica coating induced highly stable perovskite nanocrystals with enhanced aqueous fluorescence for efficient Hg2+ and glutathione detection

The poor stability and aqueous-quenching of fluorescence of perovskite nanocrystals (NCs) hinder their application in bio-detection and bio-imaging. Herein, through the synergistic effects of polymer surface ligand and silica encapsulation, highly stable and enhanced aqueous fluorescent CsPbBr₃-mPEG@SiO₂ NCs were synthesized and used as a novel "on-off-on" fluorescent probe for highly sensitive and selective detection of mercury ions (Hg²⁺) and glutathione (GSH) in aqueous solutions. The effects of the methoxypolyethylene glycol amine (mPEG-NH₂) ligand and silica encapsulation on the stability and aqueous fluorescence of the CsPbBr₃ NCs were studied. It indicated that the aqueous fluorescence of perovskite NCs was increased by 2.59 times. The water stability was also greatly improved, with the NCs maintaining 73% of their original fluorescence after storage for 30 days in water. X-ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infrared spectroscopy (FT-IR) analyses further demonstrated that the NCs were successfully passivated by mPEG-NH₂ and silica. The fluorescence of the CsPbBr₃-mPEG@SiO₂ nanocrystals was effectively quenched by Hg²⁺ which is attributed to the electron transfer process between NCs and Hg²⁺. Then, through the interaction between Hg²⁺ and GSH, the restoration of fluorescence for CsPbBr₃-mPEG@SiO₂ was realized. The "on-off-on" fluorescent probe can be used for the detection of Hg²⁺ and GSH with a low detection limit of 0.08 nM and 0.19 μM, respectively. It also shows a fast response time and high accuracy for practical sample detection. The simple and sensitive fluorescent probe of CsPbBr₃-mPEG@SiO₂ shows great potential in environmental and biological sensing.

A Dual-emitting Two-dimensional Nickel-based Metal-organic Framework Nanosheets: Eu3+/Ag+ Functionalization Synthesis and Ratiometric Sensing in Aqueous Solution

Using two-dimensional (2D) nickel-based metal organic framework (Ni-MOF) nanosheets as a matrix, Eu³⁺ and Ag⁺ were incorporated to synthesize Ag/Eu@Ni-MOF with double luminescence centers of Eu³⁺ ion (615 nm) and organic ligand (524 nm). And a ratiometric luminescence sensor is constructed based on Ag/Eu@Ni-MOF for sensitive detection of biothiols in aqueous solutions. The dual-emissive fluorescence properties can be tuned by changing the amounts of Ag⁺ ions doping. The results of temperature and pH effects on the fluorescence of Ag/Eu@Ni-MOF indicates that the Ag/Eu@Ni-MOF is a temperature-sensitive material and the fluorescence of Ag/Eu@Ni-MOF can keep stable over a wide pH range. Due to the binding of -SH in cysteine (Cys) and glutathione (GSH) with Ag⁺, the ligand luminescence was significantly inhibited by weakening the Ag + influence on the energy transfer process in the MOFs. Therefore, ratiometric fluorescent sensing of biomolecular thiols was realized based on the dual-emission Ag/Eu@Ni-MOF. More importantly, the fluorescence color change can be observed with naked eyes to realize visual detection. The ratiometric fluorescent sensor exhibits high performance for Cys and GSH detection with a wide linear range of 5-250 µM and a relatively low detection limit of 0.20 µM and 0.17 µM, respectively. Furthermore, the biothiols content in human serum was determined with satisfactory results. It proves the Ni-MOF nanosheets can be used as a stable matrix for construction luminescent MOFs for the first time, and validate the great potential of Ag/Eu@Ni-MOF as a ratiometric fluorescent probe for point-of-care testing (POCT) in disease diagnosis.

Flexible paper-based Ni-MOF composite/AuNPs/CNTs film electrode for HIV DNA detection

It is very important to develop a rapid, simple, low cost point-of-care (POC) method for the early diagnosis of pathogens. In this work, a flexible paper-based electrode based on nickel metal-organic framework (Ni-MOF) composite/Au nanoparticles/carbon nanotubes/polyvinyl alcohol (Ni-Au composite/CNT/PVA) was constructed to detect target human immunodeficiency virus (HIV) DNA by DNA hybridization using methylene blue (MB) as a redox indicator. The CNT/PVA and Ni-Au composite were deposited on the cellulose membrane by vacuum filtration and drop-coating method in turn to obtain Ni-Au composite/CNT/PVA (CCP) film electrode. Compared to the CNT/PVA film electrode, CCP film electrode makes a higher loading of the probe DNA for its large specific surface area and conjugated π-electron system that can provide hydrogen bond sources to achieve interactions between MOF and single-stranded DNA, which improves the sensitivity for detecting target DNA. The variation of peak current for MB molecules adsorbed onto DNA before and after hybridization with HIV DNA was monitored. Electrochemical results proved that the CCP film maintained stable electrochemical property even after bending 200 times or stretching under different strains from 0% to 20%. The flexible paper electrode showed excellent sensing performance with a linear range of 10 nM-1 μM and a low detection limit of 0.13 nM. The target HIV DNA was successfully detected even in complex serum samples using the flexible CCP film electrode. Therefore, the simple and inexpensive flexible paper-based MOF composite film electrode can also be utilized for other pathogens POC diagnosis.

Curcumin decreases dibutyl phthalate-induced renal dysfunction in Kunming mice via inhibiting oxidative stress and apoptosis

Curcumin (Cur) has been used extensively in dietary supplement with antioxidant and anti-apoptotic properties. Although dibutyl phthalate (DBP) has adverse effects on the kidney, any association between DBP exposure and the role of Cur is unclear. We tested the hypothesis that exposure to DBP has adverse consequences on renal dysfunction in mice and the potential protective role of Cur in decreasing DBP-induced renal dysfunction via inhibiting oxidative stress and apoptosis. Kidney function, oxidative stress biomarkers, and apoptosis factors as well as Bcl-2 and Bax were investigated. The results showed a marked increase of renal dysfunction, oxidative stress and apoptosis level after DBP exposure compared to the control. While administration of Cur to DBP-treated mice may reduce these adverse biochemical changes compared with DBP-alone group. Overall, these results suggest that oxidative stress and apoptosis are involved in DBP-induced renal disorder, whereas Cur plays a protective role in inhibiting these two pathways.

Deep medical image analysis with representation learning and neuromorphic computing

Deep learning is increasingly used in medical imaging, improving many steps of the processing chain, from acquisition to segmentation and anomaly detection to outcome prediction. Yet significant challenges remain: (i) image-based diagnosis depends on the spatial relationships between local patterns, something convolution and pooling often do not capture adequately; (ii) data augmentation, the de facto method for learning three-dimensional pose invariance, requires exponentially many points to achieve robust improvement; (iii) labelled medical images are much less abundant than unlabelled ones, especially for heterogeneous pathological cases; and (iv) scanning technologies such as magnetic resonance imaging can be slow and costly, generally without online learning abilities to focus on regions of clinical interest. To address these challenges, novel algorithmic and hardware approaches are needed for deep learning to reach its full potential in medical imaging.

A near-infrared fluorescent sensor based on the architecture of low-toxic Ag2S quantum dot and MnO2 nanosheet for sensing glutathione in human serum sample

Near-infrared (NIR) emitting Ag₂S quantum dots (QDs) are excellent fluorescent nanoprobes for bioassays with low toxicity. A novel fluorescent sensing platform which employing NIR fluorescent Ag₂S QDs and MnO₂ 2D nanosheets as NIR emitters and quenchers is designed for rapid and selective determination of glutathione (GSH). A facile and efficient approach was demonstrated for the synthesis of NIR fluorescent Ag₂S QDs with the emission of 845 nm. Then the NIR fluorescent nanoprobe of Ag₂S QDs-MnO₂ nanosheets is obtained by adsorbing Ag₂S QDs onto the surface of MnO₂ nanosheets which have atomically thick two-dimensional structure and high specific surface area. And the NIR fluorescence of Ag₂S QDs is quenched by the MnO₂ nanosheets. The presence of GSH could reduce MnO₂ to Mn²⁺ that results in the restoration of NIR fluorescence for Ag₂S QDs. The NIR fluorescent nanoprobe could be used for highly selective detection of GSH. Also a low detection limit of 60 μmol/L was obtained. Because NIR fluorescence of the Ag₂S QDs can efficiently reduce the interferences from background scattering and autofluorescence. The NIR fluorescent nanoprobe was directly applied to monitor the GSH level in human serum sample with high accuracy and precision.

A highly-specific photoelectrochemical platform based on carbon nanodots and polymers functionalized organic-inorganic perovskite for cholesterol sensing

Herein, we reported the introduction of carbon nanodots (CNDs) and polyvinylidene fluoride (PVDF) as additives into perovskite CH₃NH₃PbI₃ through in situ synthesis to prepare PVDF-CH₃NH₃PbI₃@CNDs composite, which demonstrated improved water tolerance and mechanical stability. The application of PVDF-CH₃NH₃PbI₃@CNDs for photoelectrochemical sensing was then explored. A molecularly imprinted polymer (MIP) that could specifically recognize cholesterol (CHO) was anchored to PVDF-CH₃NH₃PbI₃@CNDs via a simple thermal polymerization process, followed by elution with hexane. A label-free and sensitive photoelectrochemical method for CHO detection was achieved by using the MIPs@PVDF-CH₃NH₃PbI₃@CNDs platform. The detection limit for CHO was 2.1 × 10^-14 mol/L, lower than most of the existing CHO detection methods. In our perception, this platform can be extended to numerous other analytes. This research result may provide a new understanding to improve the performance and broaden the application range of organic-inorganic perovskites.

Stretchable Electrochemical Biosensing Platform Based on Ni-MOF Composite/Au Nanoparticle-Coated Carbon Nanotubes for Real-Time Monitoring of Dopamine Released from Living Cells

Existing electrochemical biosensing platforms, using traditional rigid and unstretchable electrodes, cannot monitor the biological signaling molecules released by cells in a mechanically deformed state in real time. Here, a stretchable and flexible electrochemical sensor was developed based on nickel metal-organic framework composite/Au nanoparticle-coated carbon nanotubes (Ni-MOF composite/AuNPs/CNTs) for sensitive detection of dopamine (DA) released by C6 living cells in real time. A Ni-MOF composite was obtained by introducing Ni, NiO, and a carbon frame onto the surface of two-dimensional (2D) Ni-MOF nanosheets using an efficient one-step calcination method. The hybrid of Ni-MOF composite/AuNPs/CNTs that deposited on the poly(dimethylsiloxane) (PDMS) film endowed the sensor with excellent electrochemical performance with a wide linear range of 50 nM to 15 μM and a high sensitivity of 1250 mA/(cm² M) and also provided the sensor with desirable stability against mechanical deformation. Furthermore, the stretchable electrode also displayed good cellular compatibility while C6 living cells can be cultured and proliferated on it with strong adhesion. Then, the DA released by C6 living cells with chemical induction in both natural and stretched states was monitored using our stretchable and flexible electrochemical sensor in real time. This indicates that our new design of flexible Ni-MOF composite/AuNPs/CNTs/PDMS (NACP) film electrodes provides more opportunities for the detection of chemical signals released from cells and soft living organisms even under mechanically deformed states.

A flexible rGO electrode: a new platform for the direct voltammetric detection of salicylic acid

Flexible sensors are of considerable interest for the development of wearable smart miniature devices. This work reported a flexible electrochemical platform based on reduced graphene oxide (rGO) for the detection of salicylic acid (SA). The free-standing and flexible rGO electrode was prepared via a simple extruded process. Dynamic mechanical deformation and bending studies illustrated the resilience and compliance of the flexible electrode against extreme mechanical deformations. Quantitative analysis of SA was performed by using differential pulse voltammetry (DPV) with this flexible rGO electrode. Linearity ranges for SA were obtained from 1.0 × 10^-10 M to 1.0 × 10^-5 M with the detection limit of 2.3 × 10^-11 M (S/N = 3). This strategy provided a new insight into the design and application of flexible electrodes. It will extend the applications of rGO in sensing, bio-electronics and lab-on-chip devices.

[Trends analysis of vitamin D status among pregnant women in Hefei during 2015-2017]

From March 2015 to February 2018, 4 728 women aged 18 to 45 years old with single-pregnancy at the gestational age of 13 to 27 weeks in Hefei were recruited to analyze the trend of vitamin D status. The average levels of serum 25(OH)D in 2015, 2016 and 2017 were (43.22±18.41) nmol/L, (39.3±15.1) nmol/L and (36.6±17.0) nmol/L, and the prevalence of vitamin D deficiency were 69.5%, 77.6% and 81.4%, respectively. Compared with 2015, the levels of serum 25(OH)D in pregnant women in 2016 and 2017 decreased by 5.23 (95%CI: 4.10-6.35) nmol/L and 7.98 (95%CI: 6.77-9.19) nmol/L. The OR (95%CI) values for the risk of vitamin D deficiency were 1.88 (95%CI: 1.57-2.24) and 2.41 (95%CI: 1.98-2.93).

[Phosphatase and tensin homolog deleted on chromosome ten deficiency sensitizes tumor cells to lithium chloride treatment]

Objective: To identify the therapeutic efficacy of lithium chloride (LiCl) on phosphatase and tensin homolog deleted on chromosome ten (PTEN)-deficient tumors. Methods: First, the Catalogue of Somatic Mutations in Cancer for mutation spectrum of human endometrial carcinoma samples was analyzed. Second, the relationship between PTEN abundance and LiCl inhibition of endometrial cancer cell lines using Pten(+/+) and Pten(-/-) mouse embryonic fibroblast (MEF) lines was investigated. Moreover, potential alterations of mammalian target of rapamycin (mTOR) signaling pathway after treatment with LiCl were checked.Last,LiCl's efficacy on PTEN null tumors was studied. Results: PTEN was mutated in 39% of endometrial carcinomas. LiCl preferentially inhibited the proliferation of PTEN-deficient endometrial carcinoma cells and MEFs. Furthermore, LiCl blocked PTEN-deficient tumor development. Mechanistically, LiCl down-regulated mTOR signaling. Conclusions: PTEN is the most frequently mutated gene in endometrial carcinoma.By targeting mTOR signaling pathway,LiCl is a promising regimen for the treatment of tumors with PTEN deficiency.

[Prospective cohort study on association between peri-conceptional air pollution exposure and gestational diabetes mellitus]

Objective: To explore the association between the exposure to major air pollutants in pre-pregnancy and early pregnancy (peri-conceptional period) and gestational diabetes mellitus (GDM). Methods: From March 2015 to April 2018, 4 817 pregnancies were recruited at three prenatal check-ups hospital in Hefei (Hefei First People's Hospital, Hefei. Maternal and Child Care Hospital and the First Affiliated Hospital of Anhui Medical University), China. Questionnaire was used to collect the demographic data, the health status and lifestyle of pregnant women. GDM was diagnosed according to the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes (2017 Edition). Logistic regression was used to investigate the association of exposure to major air pollutants (PM(2.5), PM(10), SO(2), CO and NO(2)) during different periods of pre-pregnancy (12 weeks before pregnancy) and first trimester (12 weeks after last menstruation) and duration of exposure to high levels of pollutants with GDM. Results: The mean±SD of the age of subjects was (29.14±4.19) years old and the prevalence of GDM was 21.4% (n=1 030). The results of multivariate logistic regression analysis showed that after adjusting for confounding factors, the risk of GDM increased gradually with the prolonged exposure time of high-concentration pollutants compared with pregnant women who were not exposed to high pollution during the pre-pregnancy (χ(2)=61.28, P(trend)<0.001) with the OR (95%CI) values for exposure time of 1, 2, and 3 months about 1.42 (1.10-1.84), 1.73 (1.29-2.33), and 2.51 (1.75-3.59), respectively. In the pre-pregnancy period, in every 10 μg/m(3) increase of PM(2.5) and PM(10), the OR (95%CI) values of GDM were 1.14 (1.08-1.20) and 1.13 (1.08-1.19), respectively; for each increase of 1 μg/m(3) and 0.10 mg/m(3) of SO(2) and CO, the OR (95% CI) values of GDM were 1.03 (1.01-1.05) and 1.07 (1.01-1.13), respectively. For every 1 μg/m(3) increase in the average concentration of SO(2) in the first trimester, the OR (95%CI) value of GDM was 1.02 (1.01-1.05). Conclusion: PM(2.5), PM(10), SO(2) and CO exposure during the pre-pregnancy and SO(2) exposure in first trimester were positively correlated with the risk of GDM.

Tumor mutational burden is predictive of response to immune checkpoint inhibitors in MSI-high metastatic colorectal cancer

BACKGROUND

Microsatellite instability (MSI) is a biomarker for response to immune checkpoint inhibitors (ICPIs). PD-1 inhibitors in metastatic colorectal carcinoma (mCRC) with MSI-high (MSI-H) have demonstrated a high disease control rate and favorable progression-free survival (PFS); however, reported response rates to pembrolizumab and nivolumab are variable and often <50%, suggesting that additional predictive biomarkers are needed.

METHODS

Clinicopathologic data were collected from patients with MSI-H mCRC confirmed by hybrid capture-based next-generation sequencing (NGS) treated with PD-1/L1 inhibitors at five institutes. Tumor mutational burden (TMB) was determined on 0.8-1.1 Mb of sequenced DNA and reported as mutations/Mb. Potential biomarkers of response and time to progression were analyzed by univariate and multivariate analyses. Once TMB was confirmed as a predictive biomarker, a larger dataset of 18 140 unique CRC patients was analyzed to define the relevance of the identified TMB cut-point.

RESULTS

A total of 22 patients were treated with PD-1/L1 inhibitors including 19 with pembrolizumab monotherapy. Among tested variables, TMB showed the strongest association with objective response (OR; P < 0.001) and PFS, by univariate (P < 0.001) and multivariate analysis (P < 0.01). Using log-rank statistics, the optimal predictive cut-point for TMB was estimated between 37 and 41 mutations/Mb. All 13 TMBhigh cases responded, while 6/9 TMBlow cases had progressive disease. The median PFS for TMBhigh has not been reached (median follow-up >18 months) while the median PFS for TMBlow was 2 months. A TMB of 37.4 mutations/Mb in a large MSI-H mCRC population (821/18, 140 cases; 4.5%) evaluated by NGS corresponded to the 35th percentile cut-point.

CONCLUSIONS

TMB appears to be an important independent biomarker within MSI-H mCRC to stratify patients for likelihood of response to ICPIs. If validated in prospective studies, TMB may play an important role in guiding the sequencing and/or combinations of ICPIs in MSI-H mCRC.