DPP7 as a Potential Therapeutic Marker for Colorectal Cancer.

Background: Dipeptidyl peptidase 7 (DPP7) is overexpressed in various tumors, but its role in colorectal cancer (CRC) remains unclear. Study the Impact of DPP7 on malignant progression and tumor immunity in CRC. Methods: We utilized Tumor Immune Estimation Resource 2.0 (TIMER2.0) and The Cancer Genome Atlas (TCGA) analyses to assess the expression of DPP7 in tumors and validated it through immunohistochemistry and immunoblotting. Additionally, we investigated the relationship between DPP7 and immune cell infiltration using single-sample Gene Set Enrichment Analysis (ssGSEA) analysis. Finally, the impact of DPP7 on cell proliferation, invasion, migration, and immune cell function in the tumor microenvironment was confirmed through cell experiments and animal studies. Results: DPP7 is highly expressed in CRC, and high expression of DPP7 is associated with poor prognosis. Cell experiments demonstrate that overexpression of DPP7 enhances the proliferation, migration, and invasion capabilities of colorectal cancer cells both in vitro and in vivo. Immune infiltration analysis and co-culture results indicate that overexpression of DPP7 suppresses the immune cell's cytotoxic function against tumors in the tumor microenvironment. Conclusions: DPP7 promotes the malignant potential of colorectal cancer cells and inhibits tumor immune function, thereby promoting the progression of colorectal cancer.

A novel approach for large-scale characterization of residential cooking-generated PM with computer vision and low-cost sensors.

Cooking is one of the major sources of indoor particulate matter (PM), which poses significant health risks and is a severe health hazard. Current studies lack an economical and effective analytical framework for quantifying inhalable particles (PM10) and fine particulate matter (PM2.5) from residential cooking activities on a large scale under real-world scenarios. This study bridges this gap by employing computer vision (CV) technology and readily available sensors. We collected data over a month in real-world settings, including cooking videos and air quality data (indoor PM10, PM2.5, CO2, temperature, relative humidity, and outdoor PM10 and PM2.5 concentrations). To classify high-emission (pan-frying, stir-frying, deep-frying) and low-emission (stewing, steaming, boiling, non-cooking) activities, we developed and validated a robust CV model named "Cooking-I3D." This model leverages a pre-trained Two-Stream Inflated 3D ConvNet (I3D) architecture. We then assessed the efficacy of the CV-predicted cooking method in PM characterization using a first-order multivariate autoregressive model, controlling for environmental factors. The Cooking-I3D model achieved exceptional performance, boasting an accuracy of 95 % and an Area Under the Curve (AUC) of 0.98. Our results indicate that a single 6-minute high-emission cooking event triggers a 21-25 % increase in indoor PM concentrations and a 23-24 % increase in the indoor/outdoor ratio, with relative errors in these estimates ranging from 10 to 21 %. This innovative method offers a powerful tool for long-term assessment of cooking-related indoor air pollution and facilitates precision exposure assessment in human health studies.

HS-GC-IMS Analysis of Volatile Organic Compounds in Six Spicy Spices and Their Effects on Ulcerative Colitis.

The volatile organic compounds of six spices, including black pepper, dried ginger, cinnamon, fennel, clove, and zanthoxylum, were analyzed by gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with principal component analysis (PCA) and Euclidean distance. In further analyses, the effects of volatile oils in six spices on ulcerative colitis were assayed in a zebrafish model induced by 3-nitrobenzenesulfonic acid. A total of 120 kinds of volatile organic compounds were detected and 80 among them were identified, which included 10 common components and 3 to 24 characteristic components belonging to different spices. The major VOCs in six spices were estimated to be terpenes with the contents of 45.02%, 56.87%, 36.68%, 58.19%, 68.68%, and 30.62%, respectively. Meanwhile, the volatile components of fennel, dried ginger, black pepper, and cinnamon are quite similar, but differ from clove and zanthoxylum. The volatile oils in six spices presented efficient activity to improve ulcerative colitis which can decrease the number of neutrophils, restore the structure of intestinal epithelial and the morphology of the epithelial cells. Our study achieved rapid analysis of the volatile organic compounds and flavors in six spices and further revealed the potential health benefits of their volatile oils on ulcerative colitis, especially for clove and zanthoxylum. This study is expected to provide certain data support for the quality evaluation and the potential use in functional foods of six spices.

Exploring blood transcriptomic signatures in patients with herpes zoster and postherpetic neuralgia.

Postherpetic neuralgia (PHN) is a common, severe, and hard-to-treat chronic pain condition in clinics. Although PHN is developed from herpes zoster (HZ), the developing mechanism is unknown. A previous study investigated blood metabolomic and proteomic profiling in patients with PHN and HZ. The current study aims to explore the blood transcriptomic signature of PHN compared to HZ patients. Whole blood from eight PHN and 15 HZ patients was used for RNA-Seq analysis. There were 82 and 1,788 genes detected specifically in the PHN and HZ groups, respectively. PHN-specific genes are involved in viral infection, lipid and carbohydrate metabolism, and immune response. For genes coexpressed in PHN and HZ patients, there were 407 differential expression genes (DEGs), including 205 upregulated (UP DEGs) and 202 downregulated (DOWN DEGs) in PHN compared to HZ groups. DEGs are involved in viral infection, type I interferon (IFN), and hemoglobin and oxygen carrier activity. UP DEGs are associated with regulatory T cells (Tregs), activated NK cells, and neutrophils, while DOWN DEGs are associated with Tregs, resting NK cells, and monocytes. The results suggest that the metabolism of lipid, glycan, and nucleotides, type I IFN signaling, and altered neutrophil activation are associated with and might contribute to the development of PHN in HZ. It is also suggested that persistent or altered activation of nonspecific immunity may contribute to the development of PHN from HZ.

Lung vessel connectivity map as anatomical prior knowledge for deep learning-based lung lobe segmentation.

Purpose: Our study investigates the potential benefits of incorporating prior anatomical knowledge into a deep learning (DL) method designed for the automated segmentation of lung lobes in chest CT scans. Approach: We introduce an automated DL-based approach that leverages anatomical information from the lung's vascular system to guide and enhance the segmentation process. This involves utilizing a lung vessel connectivity (LVC) map, which encodes relevant lung vessel anatomical data. Our study explores the performance of three different neural network architectures within the nnU-Net framework: a standalone U-Net, a multitasking U-Net, and a cascade U-Net. Results: Experimental findings suggest that the inclusion of LVC information in the DL model can lead to improved segmentation accuracy, particularly, in the challenging boundary regions of expiration chest CT volumes. Furthermore, our study demonstrates the potential for LVC to enhance the model's generalization capabilities. Finally, the method's robustness is evaluated through the segmentation of lung lobes in 10 cases of COVID-19, demonstrating its applicability in the presence of pulmonary diseases. Conclusions: Incorporating prior anatomical information, such as LVC, into the DL model shows promise for enhancing segmentation performance, particularly in the boundary regions. However, the extent of this improvement has limitations, prompting further exploration of its practical applicability.

Acupuncture for the treatment of painful diabetic peripheral neuropathy: A systematic review and meta-analysis.

BACKGROUND AND PURPOSE: A growing number of studies have investigated the efficacy of acupuncture in the treatment of painful diabetic peripheral neuropathy (PDPN), but the findings of these studies have generated conflicting results. This study therefore aimed to assess the efficacy of acupuncture for treating PDPN so as to offer more conclusive results. METHODS: Seven databases were systematically searched for studies published up until December 1, 2023. All randomized controlled trials (RCTs) of acupuncture for PDPN with visual analog scale (VAS) for pain score were included. Study selection, data extraction, and evaluation were conducted independently by researchers. The Risk of Bias 2 (RoB2) tool was employed to assess the risk of bias. From this sample, the mean difference (MD), 95 % confidence intervals (CI), publication bias, and heterogeneity were then computed. RESULTS: The manual acupuncture group exhibited a significant decrease in the VAS for pain score compared with the routine care group (p < 0.0001; MD = -1.45 [95 % CI, -1.97 to -0.93], I2 = 84 %). The real acupuncture group demonstrated a greater reduction in VAS scores than the sham acupuncture group (p = 0.004; MD = -0.97 [95 % CI, -1.63 to -0.31], I2 = 65 %). Additionally, the acupuncture group showed improvements in sensory nerve conduction velocity (SNCV, p < 0.0001; MD = 2.29 [95 % CI, 1.79 to 2.78], I2 = 14 %) as well as motor nerve conduction velocity (MNCV, p < 0.0001; MD = 2.87 [95 % CI, 2.46 to 3.27], I2 = 0). Different durations of acupuncture treatment, including 6-10 weeks and 3-4 weeks, demonstrated a significant reduction in VAS scores compared with the routine care group. CONCLUSION: This meta-analysis provides preliminary evidence for the claim that acupuncture has the potential to alleviate PDPN symptoms and improve SNCV and MNCV. However, high-quality RCTs are needed to offer further evidence and thus better substantiate such a contention.

The protective effects of methylene blue on astrocytic swelling after cerebral ischemia-reperfusion injuries are mediated by Aquaporin-4 and metabotropic glutamate receptor 5 activation.

Methylene blue (MB) was found to exert neuroprotective effect on different brain diseases, such as ischemic stroke. This study assessed the MB effects on ischemia induced brain edema and its role in the inhibition of aquaporin 4 (AQP4) and metabotropic glutamate receptor 5 (mGluR5) expression. Rats were exposed 1 h transient middle cerebral artery occlusion (tMCAO), and MB was injected intravenously following reperfusion (3 mg/kg). Magnetic resonance imaging (MRI) and 2,3,5-triphenyltetrazolium chloride (TTC) staining was performed 48 h after the onset of tMCAO to evaluate the brain infarction and edema. Brain tissues injuries as well as the glial fibrillary acidic protein (GFAP), AQP4 and mGluR5 expressions were detected. Oxygen and glucose deprivation/reoxygenation (OGD/R) was performed on primary astrocytes (ASTs) to induce cell swelling. MB was administered at the beginning of reoxygenation, and the perimeter of ASTs was measured by GFAP immunofluorescent staining. 3,5-dihydroxyphenylglycine (DHPG) and fenobam were given at 24 h before OGD to examine their effects on MB functions on AST swelling and AQP4 expression. MB remarkably decreased the volumes of T2WI and ADC lesions, as well as the cerebral swelling. Consistently, MB treatment significantly decreased GFAP, mGluR5 and AQP4 expression at 48 h after stroke. In the cultivated primary ASTs, OGD/R and DHPG significantly increased ASTs volume as well as AQP4 expression, which was reversed by MB and fenobam treatment. The obtained results highlight that MB decreases the post-ischemic brain swelling by regulating the activation of AQP4 and mGluR5, suggesting potential applications of MB on clinical ischemic stroke treatment.

Associations of maternal and personal smoking with all-cause and cause-specific mortality risk and life expectancy: a prospective cohort study.

OBJECTIVES: The aim of this study was to evaluate the individual and combined effects of maternal smoking during pregnancy (MSDP) and personal smoking on mortality and life expectancy. STUDY DESIGN: A prospective cohort study based on the UK Biobank, with a median follow-up of 12.47 years. METHODS: This study employed multivariate Cox regression to determine the relative risks of mortality from all causes and specific diseases according to maternal and/or personal smoking status and pack-years of smoking (0, 1-20, 21-30, >30). Additionally, this study estimated the additive interaction between the two exposures. Life table analyses were performed using the estimated age-specific mortality rates to forecast life expectancy. RESULTS: Results indicated that MSDP elevated the risk of all-cause mortality (HR = 1.12, 95% CI: 1.09-1.15) and mortality due to neoplasms (HR = 1.10, 95% CI: 1.06-1.12), circulatory (HR = 1.13, 95% CI: 1.06-1.19), respiratory (HR = 1.27, 95% CI: 1.16-1.40) and digestive system diseases (HR = 1.22, 95% CI: 1.08-1.38). Notably, both multiplicative and additive interactions were observed between maternal and personal smoking, with Relative Excess Risk due to Interaction (RERI) values for mortality from all causes, neoplasms, circulatory, and respiratory diseases being 0.21, 0.22, 0.16, and 0.76, respectively. This study also found a trend towards shorter gained life expectancy when maternal smoking and increasing pack-years of personal smoking were combined. CONCLUSIONS: In this cohort study of UK Biobank, MSDP was associated with an increased risk of all-cause mortality and reduced life expectancy, suggesting that quitting smoking during pregnancy might have health and longevity benefits for both generations.

Quantifying the contributions of road and air traffic to ambient ultrafine particles in two urban communities.

Traffic-related activities are widely acknowledged as a primary source of urban ambient ultrafine particles (UFPs). However, a notable gap exists in quantifying the contributions of road and air traffic to size-resolved and total UFPs in urban areas. This study aims to delineate and quantify the traffic's contributions to size-resolved and total UFPs in two urban communities. To achieve this, stationary sampling was conducted at near-road and near-airport communities in Seattle, Washington State, to monitor UFP number concentrations during 2018-2020. Comprehensive correlation analyses among all variables were performed. Furthermore, a fully adjusted generalized additive model, incorporating meteorological factors, was developed to quantify the contributions of road and air traffic to size-resolved and total UFPs. The study found that vehicle emissions accounted for 29% of total UFPs at the near-road site and 13% at the near-airport site. Aircraft emissions contributed 14% of total UFPs at the near-airport site. Notably, aircraft predominantly emitted UFP sizes below 20 nm, while vehicles mainly emitted UFP sizes below 50 nm. These findings reveal the variability in road and air traffic contributions to UFPs in distinct areas. Our study emphasizes the pivotal role of traffic layout in shaping urban UFP exposure.

KRT80 Promotes Lung Adenocarcinoma Progression and Serves as a Substrate for VCP.

Background: Keratin 80(KRT80) encodes a type II intermediate filament protein, known for maintaining cell integrity of cells and its involvement in the tumorigenesis and progression of various cancers. However, comprehensive research on its relevance to lung adenocarcinoma remains limited. Methods: In this study, we utilized multiple databases to investigate the transcriptional expression of KRT80 and its correlation with clinicopathological features. A range of assays, including the Cell Counting Kit 8 assay, colony formation assay, cell migration assay, and flow cytometry, were employed to elucidate the impact of KRT80 on the malignant behavior of lung adenocarcinoma. Immunoprecipitation and mass spectrometry were also used to identify putative genes interacting with KRT80. Results: The expression of KRT80 was elevated in lung adenocarcinoma and patients with high levels of KRT80 expression had poor clinical outcomes. Silencing KRT80 suppressed cell viability, and migration, while overexpression had the opposite effect. In addition, Immunoprecipitation and mass spectrometry revealed an interaction between KRT80 and valosin-containing protein (VCP), with VCP knockdown reducing the stability of KRT80 protein. Overexpression of KRT80 mitigated the inhibitory effect of VCP knockdown to some extent. Conclusion: Our findings collectively suggest that KRT80 is a promising diagnostic and prognostic indicator for lung adenocarcinoma. Additionally, the interaction between KRT80 and VCP plays a crucial role in the progression of lung adenocarcinoma, which implies that KRT80 is a promising therapeutic target.

Prognostic biomarker HIF1α and its correlation with immune infiltration in gliomas.

Certain glioma subtypes, such as glioblastoma multiforme or low-grade glioma, are common malignant intracranial tumors with high rates of relapse and malignant progression even after standard therapy. The overall survival (OS) is poor in patients with gliomas; hence, effective prognostic prediction is crucial. Herein, the present study aimed to explore the potential role of hypoxia-inducible factor 1 subunit alpha (HIF1α) in gliomas and investigate the association between HIF1α and infiltrating immune cells in gliomas. Data from The Cancer Genome Atlas were evaluated via RNA sequencing, clinicopathological, immunological checkpoint, immune infiltration and functional enrichment analyses. Validation of protein abundance was performed using paraffin-embedded samples from patients with glioma. A nomogram model was created to forecast the OS rates at 1, 3 and 5 years after cancer diagnosis. The association between OS and HIF1α expression was estimated using Kaplan-Meier survival analysis and the log-rank test. Finally, HIF1α expression was validated using western blotting, reverse transcription-quantitative PCR, Cell Counting Kit-8 and Transwell assays. The results demonstrated that HIF1α expression was significantly upregulated in gliomas compared with normal human brain glial cells. Immunohistochemistry staining demonstrated differential expression of the HIF1α protein. Moreover, glioma cell viability and migration were inhibited via HIF1α downregulation. HIF1α impacted DNA replication, cell cycling, DNA repair and the immune microenvironment in glioma. HIF1α expression was also positively associated with several types of immune cells and immunological checkpoints and with neutrophils, plasmacytoid dendritic cells and CD56bright cells. The Kaplan-Meier survival analyses further demonstrated a strong association between high HIF1α expression and poor prognosis in patients with glioma. Analysis of the receiver operating characteristic curves demonstrated that HIF1α expression accurately differentiated paired normal brain cells from tumor tissues. Collectively, these findings suggested the potential for HIF1α to be used as a novel prognostic indicator for patients with glioma and that OS prediction models may help in the future to develop effective follow-up and treatment strategies for these patients.

4D Multimaterial Printing of Soft Actuators with Spatial and Temporal Control.

Soft actuators (SAs) are devices which can interact with delicate objects in a manner not achievable with traditional robotics. While it is possible to design a SA whose actuation is triggered via an external stimulus, the use of a single stimulus creates challenges in the spatial and temporal control of the actuation. Herein, a 4D printed multimaterial soft actuator design (MMSA) whose actuation is only initiated by a combination of triggers (i.e., pH and temperature) is presented. Using 3D printing, a multilayered soft actuator with a hydrophilic pH-sensitive layer, and a hydrophobic magnetic and temperature-responsive shape-memory polymer layer, is designed. The hydrogel responds to environmental pH conditions by swelling or shrinking, while the shape-memory polymer can resist the shape deformation of the hydrogel until triggered by temperature or light. The combination of these stimuli-responsive layers allows for a high level of spatiotemporal control of the actuation. The utility of the 4D MMSA is demonstrated via a series of cargo capture and release experiments, validating its ability to demonstrate active spatiotemporal control. The MMSA concept provides a promising research direction to develop multifunctional soft devices with potential applications in biomedical engineering and environmental engineering.

Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction.

OBJECTIVES: Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method. MATERIALS AND METHODS: Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis. RESULTS: SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r = - 0.69 vs. r = - 0.49/r = - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r = - 0.77 vs. r = - 0.69/r = - 0.65, p = 0.03/p = 0.002), and in the random sample (r = - 0.39 vs. r = - 0.26/r = - 0.25, p = 0.001/p = 0.007). CONCLUSION: The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores. CLINICAL RELEVANCE STATEMENT: The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores. KEY POINTS: • A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.

Early venous filling after mechanical thrombectomy in acute ischemic stroke due to large vessel occlusion in anterior circulation.

BACKGROUND: The significance of early venous filling (EVF) after mechanical thrombectomy (MT) in acute ischemic stroke (AIS) is not fully understood. In this study, we aimed to investigate the impact of EVF after MT. METHODS: From January 2019 to May 2022, AIS patients with successful recanalization (modified Thrombolysis in Cerebral Infarction score (mTICI) ≥2b) after MT were retrospectively reviewed. EVF was evaluated on final digital subtraction angiography runs after successful recanalization and was categorized into phase subgroups (arterial phase and capillary phase) and pathway subgroups (cortical veins subgroup and thalamostriate veins subgroup), respectively. The impact of EVF subgroups on functional outcomes after successful recanalization were both investigated. RESULTS: A total of 349 patients achieving successful recanalization after MT were included, including 45 patients in the EVF group and 304 patients in the non-EVF group. Multivariable logistic regression analysis showed the EVF group had a higher rate of intracranial hemorrhage (ICH; 66.7% vs 22%, adjusted odds ratio (aOR) 6.805, 95% CI 3.389 to 13.662, P<0.001), symptomatic ICH (sICH; 28.9% vs 4.9%, aOR 6.011, 95% CI 2.493 to 14.494, P<0.001) and malignant cerebral edema (MCE; 20% vs 6.9%, aOR 2.682, 95% CI 1.086 to 6.624, P=0.032) than the non-EVF group. Furthermore, the cortical veins subgroup of EVF had a higher rate of mortality than the thalamostriate veins subgroup (37.5% vs 10.3%, P=0.029). CONCLUSIONS: EVF is independently associated with ICH, sICH and MCE after successful recanalization of MT, but not with favorable outcome and mortality.

Automatic estimation of the cross-sectional area of the waist of the nerve fibre layer at the optic nerve head.

PURPOSE: Glaucoma leads to pathological loss of axons in the retinal nerve fibre layer at the optic nerve head (ONH). This study aimed to develop a strategy for the estimation of the cross-sectional area of the axons in the ONH. Furthermore, improving the estimation of the thickness of the nerve fibre layer, as compared to a method previously published by us. METHODS: In the 3D-OCT image of the ONH, the central limit of the pigment epithelium and the inner limit of the retina, respectively, were identified with deep learning algorithms. The minimal distance was estimated at equidistant angles around the circumference of the ONH. The cross-sectional area was estimated by the computational algorithm. The computational algorithm was applied on 16 non-glaucomatous subjects. RESULTS: The mean cross-sectional area of the waist of the nerve fibre layer in the ONH was 1.97 ± 0.19 mm2 . The mean difference in minimal thickness of the waist of the nerve fibre layer between our previous and the current strategies was estimated as CIµ (0.95) 0 ± 1 µm (d.f. = 15). CONCLUSIONS: The developed algorithm demonstrated an undulating cross-sectional area of the nerve fibre layer at the ONH. Compared to studies using radial scans, our algorithm resulted in slightly higher values for cross-sectional area, taking the undulations of the nerve fibre layer at the ONH into account. The new algorithm for estimation of the thickness of the waist of the nerve fibre layer in the ONH yielded estimates of the same order as our previous algorithm.

Impact of Maternal Smoking, Offspring Smoking, and Genetic Susceptibility on Crohn's Disease and Ulcerative Colitis.

BACKGROUND AND AIMS: The long-term impact of maternal smoking during pregnancy (MSDP) on adult offspring's risk of Crohn's disease (CD) and ulcerative colitis (UC) remains uncertain. Our study aims to investigate the individual and combined effects of early life exposure (MSDP), offspring personal behavior (smoking), and genetic risk on the development of CD and UC in adult offspring. METHODS: We conducted a prospective cohort study using UK Biobank data, including 334,083 participants recruited between 2006-2010, with follow-up until December 31, 2021. Multivariable Cox regression models were used to evaluate the associations of genetic factors, maternal and personal smoking, and their combination with CD and UC. RESULTS: Participants exposed to MSDP had an 18% increased risk of CD compared to those without MSDP (hazard ratio (HR) = 1.18, 95% confidence interval (CI) = 1.01-1.39). However, no significant association was found between MSDP and the UC risk (HR = 1.03, 95%CI = 0.92-1.16). Personal smoking increased the risk of CD and UC, and had a numerically amplified effect with MSDP. Participants with high genetic risk and MSDP had a 2.01-fold (95%CI = 1.53-2.65) and a 2.45-fold (95%CI = 2.00-2.99) increased risk of CD and UC, respectively, compared to participants without MSDP and with low genetic risk. CONCLUSIONS: Our prospective cohort study provides evidence that MSDP increases the risk of CD in adult offspring, whereas no evidence supports their causal association. Additionally, smoking and genetic susceptibility had a numerically amplified effect with MSDP on CD and UC, but the interaction lacked statistical significance.

Thickness of simple calcaneal tuberosity avulsion fractures influences the optimal fixation method employed.

Aims: This study aimed to establish the optimal fixation methods for calcaneal tuberosity avulsion fractures with different fragment thicknesses in a porcine model. Methods: A total of 36 porcine calcanea were sawed to create simple avulsion fractures with three different fragment thicknesses (5, 10, and 15 mm). They were randomly fixed with either two suture anchors or one headless screw. Load-to-failure and cyclic loading tension tests were performed for the biomechanical analysis. Results: This biomechanical study predicts that headless screw fixation is a better option if fragment thickness is over 15 mm in terms of the comparable peak failure load to suture anchor fixation (headless screw: 432.55 N (SD 62.25); suture anchor: 446.58 N (SD 84.97)), and less fracture fragment displacement after cyclic loading (headless screw: 3.94 N (SD 1.76); suture anchor: 8.68 N (SD 1.84)). Given that the fragment thickness is less than 10 mm, suture anchor fixation is a safer option. Conclusion: Fracture fragment thickness helps in making the decision of either using headless screw or suture anchor fixation in treating calcaneal tuberosity avulsion fracture, based on the regression models of our study.

Label-efficient deep semantic segmentation of intracranial hemorrhages in CT-scans.

Intracranial hemorrhage (ICH) is a common finding in traumatic brain injury (TBI) and computed tomography (CT) is considered the gold standard for diagnosis. Automated detection of ICH provides clinical value in diagnostics and in the ability to feed robust quantification measures into future prediction models. Several studies have explored ICH detection and segmentation but the research process is somewhat hindered due to a lack of open large and labeled datasets, making validation and comparison almost impossible. The complexity of the task is further challenged by the heterogeneity of ICH patterns, requiring a large number of labeled data to train robust and reliable models. Consequently, due to the labeling cost, there is a need for label-efficient algorithms that can exploit easily available unlabeled or weakly-labeled data. Our aims for this study were to evaluate whether transfer learning can improve ICH segmentation performance and to compare a variety of transfer learning approaches that harness unlabeled and weakly-labeled data. Three self-supervised and three weakly-supervised transfer learning approaches were explored. To be used in our comparisons, we also manually labeled a dataset of 51 CT scans. We demonstrate that transfer learning improves ICH segmentation performance on both datasets. Unlike most studies on ICH segmentation our work relies exclusively on publicly available datasets, allowing for easy comparison of performances in future studies. To further promote comparison between studies, we also present a new public dataset of ICH-labeled CT scans, Seq-CQ500.

Identification of DNA-binding protein based multiple kernel model.

DNA-binding proteins (DBPs) play a critical role in the development of drugs for treating genetic diseases and in DNA biology research. It is essential for predicting DNA-binding proteins more accurately and efficiently. In this paper, a Laplacian Local Kernel Alignment-based Restricted Kernel Machine (LapLKA-RKM) is proposed to predict DBPs. In detail, we first extract features from the protein sequence using six methods. Second, the Radial Basis Function (RBF) kernel function is utilized to construct pre-defined kernel metrics. Then, these metrics are combined linearly by weights calculated by LapLKA. Finally, the fused kernel is input to RKM for training and prediction. Independent tests and leave-one-out cross-validation were used to validate the performance of our method on a small dataset and two large datasets. Importantly, we built an online platform to represent our model, which is now freely accessible via http://8.130.69.121:8082/.

Tumor regression grade in locally advanced rectal cancer after neoadjuvant chemoradiotherapy: influencing factors and prognostic significance.

OBJECTIVE: The extent of tumor regression varies widely among patients who receive neoadjuvant chemoradiotherapy (NACRT) followed by total mesorectal excision (TME) surgery. We evaluated the tumor regression grade (TRG) classification of patients and analyzed factors related to TRG and its value in predicting prognosis in locally advanced rectal cancer (LARC). METHODS: This study retrospectively analyzed the clinicopathologic data of 269 consecutive patients with LARC treated from February 2002 to October 2014. The grade of TRG was based on the extent of primary tumor replaced by fibrosis. Clinical characteristics and relative survival were retrospectively analyzed. RESULTS: There were 269 patients, among whom 67 patients (24.9%) achieved TRG0, whereas 46 patients (17.1%) showed TRG3. TRG1 and TRG2 were both found in 78 patients (29.0%). Clinicopathologic factors that were related to TRG included post-NACRT carcinoembryonic antigen (CEA) level (P=0.002), clinical T stage (P=0.022), pathologic T stage (P<0.001) and pathologic lymph node status (P=0.003). The 5-year overall survival (OS) was 74.6%, 55.1%, 47.4%, 28.3% for TRG0, TRG1, TRG2, TRG3, respectively (P<0.001). The 5-year disease-free survival (DFS) was 64.2%, 47.4%, 37.2%, 23.9% for TRG0, TRG1, TRG2, TRG3, respectively (P<0.001). Based on multivariate analysis, TRG was a significant predictor for both OS (P=0.039) and DFS (P=0.043). CONCLUSION: Clinicopathologic factors such as post-NACRT CEA level, clinical T stage, pathological T stage and pathological lymph node status are significantly associated with TRG. TRG is an independent predictor of survival. Therefore, it is reasonable to include the TRG for clinicopathologic assessment.