Automated, fast, robust brain extraction on contrast-enhanced T1-weighted MRI in presence of brain tumors: an optimized model based on multi-center datasets.

OBJECTIVES: Existing brain extraction models should be further optimized to provide more information for oncological analysis. We aimed to develop an nnU-Net-based deep learning model for automated brain extraction on contrast-enhanced T1-weighted (T1CE) images in presence of brain tumors. METHODS: This is a multi-center, retrospective study involving 920 patients. A total of 720 cases with four types of intracranial tumors from private institutions were collected and set as the training group and the internal test group. Mann-Whitney U test (U test) was used to investigate if the model performance was associated with pathological types and tumor characteristics. Then, the generalization of model was independently tested on public datasets consisting of 100 glioma and 100 vestibular schwannoma cases. RESULTS: In the internal test, the model achieved promising performance with median Dice similarity coefficient (DSC) of 0.989 (interquartile range (IQR), 0.988-0.991), and Hausdorff distance (HD) of 6.403 mm (IQR, 5.099-8.426 mm). U test suggested a slightly descending performance in meningioma and vestibular schwannoma group. The results of U test also suggested that there was a significant difference in peritumoral edema group, with median DSC of 0.990 (IQR, 0.989-0.991, p = 0.002), and median HD of 5.916 mm (IQR, 5.000-8.000 mm, p = 0.049). In the external test, our model also showed to be robust performance, with median DSC of 0.991 (IQR, 0.983-0.998) and HD of 8.972 mm (IQR, 6.164-13.710 mm). CONCLUSIONS: For automated processing of MRI neuroimaging data presence of brain tumors, the proposed model can perform brain extraction including important superficial structures for oncological analysis. CLINICAL RELEVANCE STATEMENT: The proposed model serves as a radiological tool for image preprocessing in tumor cases, focusing on superficial brain structures, which could streamline the workflow and enhance the efficiency of subsequent radiological assessments. KEY POINTS: • The nnU-Net-based model is capable of segmenting significant superficial structures in brain extraction. • The proposed model showed feasible performance, regardless of pathological types or tumor characteristics. • The model showed generalization in the public datasets.

Versatile Neuromorphic Modulation and Biosensing based on N-type Small-molecule Organic Mixed Ionic-Electronic Conductors.

The ion/chemical-based modulation feature of organic mixed ionic-electronic conductors (OMIECs) are critical to advancing next generation bio-integrated neuromorphic hardware. Despite achievements with polymeric OMIECs in organic electrochemical neuronal synapse (OENS). However, small molecule OMIECs based OENS has not yet been realized. Here, for the first time, we demonstrate an effective materials design concept of combining n-type fused all-acceptor small molecule OMIECs with subtle side chain optimization that enables robustly and flexibly modulating versatile synaptic behavior and sensing neurotransmitter in solid or aqueous electrolyte, operating in accumulation modes. By judicious tuning the ending side chains, the linear oligoether and butyl chain derivative gNR-Bu exhibits higher recognition accuracy for a model artificial neural network (ANN) simulation, higher steady conductance states and more outstanding ambient stability, which is superior to the state-of-art n-type OMIECs based OENS. These superior artificial synapse characteristics of gNR-Bu can be attributed to its higher crystallinity with stronger ion bonding capacities. More impressively, we unprecedentedly realized n-type small-molecule OMIECs based OENS as a neuromorphic biosensor enabling to respond synaptic communication signals of dopamine even at sub-µM level in aqueous electrolyte. This work may open a new path of small-molecule ion-electron conductors for next-generation ANN and bioelectronics.

Predicting visual recovery in pituitary adenoma patients post-endoscopic endonasal transsphenoidal surgery: Harnessing delta-radiomics of the optic chiasm from MRI.

OBJECTIVES: To investigate whether morphological changes after surgery and delta-radiomics of the optic chiasm obtained from routine MRI could help predict postoperative visual recovery of pituitary adenoma patients. METHODS: A total of 130 pituitary adenoma patients were retrospectively enrolled and divided into the recovery group (n = 87) and non-recovery group (n = 43) according to visual outcome 1 year after endoscopic endonasal transsphenoidal surgery. Morphological parameters of the optic chiasm were measured preoperatively and postoperatively, including chiasmal thickness, deformed angle, and suprasellar extension. Delta-radiomics of the optic chiasm were calculated based on features extracted from preoperative and postoperative coronal T2-weighted images, followed by machine learning modeling using least absolute shrinkage and selection operator wrapped with support vector machine through fivefold cross-validation in the development set. The delta-radiomic model was independently evaluated in the test set, and compared with the combined model that incorporated delta-radiomics, significant clinical and morphological parameters. RESULTS: Postoperative morphological changes of the optic chiasm could not significantly be used as predictors for the visual outcome. In contrast, the delta-radiomics model represented good performances in predicting visual recovery, with an AUC of 0.821 in the development set and 0.811 in the independent test set. Moreover, the combined model that incorporated age and delta-radiomics features of the optic chiasm achieved the highest AUC of 0.841 and 0.840 in the development set and independent test set, respectively. CONCLUSIONS: Our proposed machine learning models based on delta-radiomics of the optic chiasm can be used to predict postoperative visual recovery of pituitary adenoma patients. CLINICAL RELEVANCE STATEMENT: Our delta-radiomics-based models from MRI enable accurate visual recovery predictions in pituitary adenoma patients who underwent endoscopic endonasal transsphenoidal surgery, facilitating better clinical decision-making and ultimately improving patient outcomes. KEY POINTS: • Prediction of the postoperative visual outcome for pituitary adenoma patients is important but challenging. • Delta-radiomics of the optic chiasm after surgical decompression represented better prognostic performances compared with its morphological changes. • The proposed machine learning models can serve as novel approaches to predict visual recovery for pituitary adenoma patients in clinical practice.

Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.

OBJECTIVES: To develop a U-Net-based deep learning model for automated segmentation of craniopharyngioma. METHODS: A total number of 264 patients diagnosed with craniopharyngiomas were included in this research. Pre-treatment MRIs were collected, annotated, and used as ground truth to learn and evaluate the deep learning model. Thirty-eight patients from another institution were used for independently external testing. The proposed segmentation model was constructed based on a U-Net architecture. Dice similarity coefficients (DSCs), Hausdorff distance of 95% percentile (95HD), Jaccard value, true positive rate (TPR), and false positive rate (FPR) of each case were calculated. One-way ANOVA analysis was used to investigate if the model performance was associated with the radiological characteristics of tumors. RESULTS: The proposed model showed a good performance in segmentation with average DSCs of 0.840, Jaccard of 0.734, TPR of 0.820, FPR of 0.000, and 95HD of 3.669 mm. It performed feasibly in the independent external test set, with average DSCs of 0.816, Jaccard of 0.704, TPR of 0.765, FPR of 0.000, and 95HD of 4.201 mm. Also, one-way ANOVA suggested the performance was not statistically associated with radiological characteristics, including predominantly composition (p = 0.370), lobulated shape (p = 0.353), compressed or enclosed ICA (p = 0.809), and cavernous sinus invasion (p = 0.283). CONCLUSIONS: The proposed deep learning model shows promising results for the automated segmentation of craniopharyngioma. KEY POINTS: • The segmentation model based on U-Net showed good performance in segmentation of craniopharyngioma. • The proposed model showed good performance regardless of the radiological characteristics of craniopharyngioma. • The model achieved feasibility in the independent external dataset obtained from another center.

Isotopic Characterization of Mercury Atmosphere-Foliage and Atmosphere-Soil Exchange in a Swiss Subalpine Coniferous Forest.

To understand the role of vegetation and soil in regulating atmospheric Hg0, exchange fluxes and isotope signatures of Hg were characterized using a dynamic flux bag/chamber at the atmosphere-foliage/soil interfaces at the Davos-Seehornwald forest, Switzerland. The foliage was a net Hg0 sink and took up preferentially the light Hg isotopes, consequently resulting in large shifts (-3.27‰) in δ202Hg values. The soil served mostly as net sources of atmospheric Hg0 with higher Hg0 emission from the moss-covered soils than from bare soils. The negative shift of δ202Hg and Δ199Hg values of the efflux air relative to ambient air and the Δ199Hg/Δ201Hg ratio among ambient air, efflux air, and soil pore gas highlight that Hg0 re-emission was strongly constrained by soil pore gas evasion together with microbial reduction. The isotopic mass balance model indicates 8.4 times higher Hg0 emission caused by pore gas evasion than surface soil photoreduction. Deposition of atmospheric Hg0 to soil was noticeably 3.2 times higher than that to foliage, reflecting the high significance of the soil to influence atmospheric Hg0 isotope signatures. This study improves our understanding of Hg atmosphere-foliage/soil exchange in subalpine coniferous forests, which is indispensable in the model assessment of forest Hg biogeochemical cycling.

Predominant contributions through lichen and fine litter to litterfall mercury deposition in a subalpine forest.

Litterfall, typically referring to needles/leaves, may stand for >50% of the total mercury (Hg) deposition in forest ecosystems. By detailed categorisation, we reveal for the first time that the contributions through lichens and fine litter, together 9.98 µg Hg m-2 yr-1, could be as high as that in needle litter (9.96 µg m-2 yr-1) to the annual total Hg deposition (44.6 µg m-2 yr-1) in a subalpine forest in Switzerland. Noticeably, needle litter had the highest contribution (53%) to total Hg in the autumn litterfall but lichens and fine litter together predominated in other seasons (47-59%). Such a seasonal pattern is caused by the high ability of lichens and fine litter to accumulate Hg and the high needle litterfall in autumn, which is related to a good rainfall in summer followed by a dry period in autumn. The constantly higher Hg levels in lichens and fine litter than in needle litter together with similar seasonal patterns of litterfall during 2009-2019 and rainfall during 1980-2019 suggest that our finding can be generally valid. Here, we highlight not only the considerable role of non-needle litterfall in Hg deposition but also the association with weather for seasonal Hg dynamics in different litterfall components.

Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets.

BACKGROUND: Convolutional neural networks (CNNs) have produced state-of-the-art results in meningioma segmentation on magnetic resonance imaging (MRI). However, images obtained from different institutions, protocols, or scanners may show significant domain shift, leading to performance degradation and challenging model deployment in real clinical scenarios. OBJECTIVE: This research aims to investigate the realistic performance of a well-trained meningioma segmentation model when deployed across different health care centers and verify the methods to enhance its generalization. METHODS: This study was performed in four centers. A total of 606 patients with 606 MRIs were enrolled between January 2015 and December 2021. Manual segmentations, determined through consensus readings by neuroradiologists, were used as the ground truth mask. The model was previously trained using a standard supervised CNN called Deeplab V3+ and was deployed and tested separately in four health care centers. To determine the appropriate approach to mitigating the observed performance degradation, two methods were used: unsupervised domain adaptation and supervised retraining. RESULTS: The trained model showed a state-of-the-art performance in tumor segmentation in two health care institutions, with a Dice ratio of 0.887 (SD 0.108, 95% CI 0.903-0.925) in center A and a Dice ratio of 0.874 (SD 0.800, 95% CI 0.854-0.894) in center B. Whereas in the other health care institutions, the performance declined, with Dice ratios of 0.631 (SD 0.157, 95% CI 0.556-0.707) in center C and 0.649 (SD 0.187, 95% CI 0.566-0.732) in center D, as they obtained the MRI using different scanning protocols. The unsupervised domain adaptation showed a significant improvement in performance scores, with Dice ratios of 0.842 (SD 0.073, 95% CI 0.820-0.864) in center C and 0.855 (SD 0.097, 95% CI 0.826-0.886) in center D. Nonetheless, it did not overperform the supervised retraining, which achieved Dice ratios of 0.899 (SD 0.026, 95% CI 0.889-0.906) in center C and 0.886 (SD 0.046, 95% CI 0.870-0.903) in center D. CONCLUSIONS: Deploying the trained CNN model in different health care institutions may show significant performance degradation due to the domain shift of MRIs. Under this circumstance, the use of unsupervised domain adaptation or supervised retraining should be considered, taking into account the balance between clinical requirements, model performance, and the size of the available data.

Electron-Deficient Polycyclic Molecules via Ring Fusion for n-Type Organic Electrochemical Transistors.

The primary challenge for n-type small-molecule organic electrochemical transistors (OECTs) is to improve their electron mobilities and thus the key figure of merit µC*. Nevertheless, few reports in OECTs have specially proposed to address this issue. Herein, we report a 10-ring-fused polycyclic π-system consisting of the core of naphthalene bis-isatin dimer and the terminal moieties of rhodanine, which features intramolecular noncovalent interactions, high π-delocalization and strong electron-deficient characteristics. We find that this extended π-conjugated system using the ring fusion strategy displays improved electron mobilities up to 0.043 cm2 V-1 s-1 compared to our previously reported small molecule gNR, and thereby leads to a remarkable µC* of 10.3 F cm-1 V-1 s-1 in n-type OECTs, which is the highest value reported to date for small-molecule OECTs. This work highlights the importance of π-conjugation extension in polycyclic-fused molecules for enhancing the performance of n-type small-molecule OECTs.

Clinical Features of Patients Infected With Coronavirus Disease 2019 With Elevated Liver Biochemistries: A Multicenter, Retrospective Study.

BACKGROUND AND AIMS: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19) emerged in Wuhan, China. Although it has been reported that some patients with COVID-19 showed elevated liver biochemistries, there are few studies regarding the clinical features and prognosis of these patients. APPROACH AND RESULTS: In this multicenter, retrospective study, we collected data on laboratory-confirmed patients with COVID-19 from three hospitals in Wuhan, China, who died or were discharged between February 1, 2020, and February 20, 2020. Data on demographics, comorbidities, clinical symptoms, laboratory examinations on admission, complications, treatment, and outcome were collected. A total of 482 patients were enrolled in this study. Of those, 142 (29.5%) patients showed abnormal liver biochemistries on admission, and patients with elevated alanine aminotransferase, aspartate aminotransferase (AST), and total bilirubin (TBIL) accounted for 67.6%, 69.0%, and 16.2%, respectively. Those with abnormal liver biochemistries showed higher percentages of severe cases and comorbidities and were more likely to have dyspnea, chest distress or pain, and increased hemoglobin (Hb) on admission. Higher rates of complications and mortality and worse recovery when discharged were observed in patients with abnormal AST or TBIL. Multivariable regression analysis showed that chest distress or pain (odds ratio [OR], 1.765; P = 0.018), dyspnea (OR, 2.495; P = 0.001), elevated C-reactive protein level (OR, 1.007; P = 0.008), elevated white blood count (OR, 1.139; P = 0.013), and elevated Hb concentration (OR, 1.024; P = 0.001) were independent factors associated with elevated liver biochemistries in patients with COVID-19. CONCLUSIONS: Elevated liver biochemistries were common in patients with COVID-19. Patients with hypoxia or severe inflammation are more likely to experience increased liver biochemistries on admission. Those with abnormal AST or TBIL on admission are more likely to suffer from severe complications and death.

Recent incidence trend of elderly patients with glioblastoma in the United States, 2000-2017.

BACKGROUND: The incidence of glioblastoma increases significantly with age. With the growing and aging population, there is a lack of comprehensive analysis of recent glioblastoma incidence trend in the United States. This study aims to provide in-depth description of the patterns of incidence trends and to examine the age-period-cohort effects to the trends of glioblastoma specific to elderly patients. METHODS: The incidence rates were age-adjusted and reported per 100,000 population. We calculated the annual percent change (APC) in incidence using the Joinpoint Regression Program and conducted an age-period-cohort analysis of elderly glioblastoma reported between 2000 and 2017 to the Surveillance Epidemiology and End Results (SEER) 18 registry database. RESULTS: The overall incidence rate of elderly patients with glioblastoma was 13.16 per 100,000 (95% CI, 12.99-13.32) from 2000 to 2017. Non-Hispanic whites (20,406, 83.6%) made up the majority. The incidence rate of male was about 1.62 times that of female. The trend of incidence remained stable and there was a non-significant increasing tendency for all elderly patients (APC 0.3, 95% CI, - 0.1 to 0.7, p = 0.111). There was a significantly increasing incidence trend for non-Hispanic white (APC 0.6, 95% CI, 0.2 to 1.1, p = 0.013), supratentorial location (APC 0.7, 95% CI, 0.2 to 1.3, p = 0.016), tumor size < 4 cm (APC 2.5, 95% CI, 1.4 to 3.6, p < 0.001), and a significantly decreasing trend for overlapping/NOS location (APC -0.9, 95% CI, - 1.6 to - 0.2, p = 0.012), and unknown tumor size (APC -4.9, 95% CI, - 6.6 to - 3.3, p < 0.001). The age-period-cohort analysis showed the effect of age on incidence trends (p< 0.001, Wald test), while did not indicate the period and cohort effects of the incidence trends of glioblastoma (p = 0.063 and p =0.536, respectively, Wald test). CONCLUSION: The overall incidence of glioblastoma in the elderly population remained stable between 2000 and 2017. Period and cohort effects were not evident in the trend of glioblastoma incidence. Future population-based studies exploring the difference in the trend of glioblastoma incidence by specific molecular subgroups are warranted to further our understanding of the etiology of glioblastoma.

Interleukin-38 is elevated in inflammatory bowel diseases and suppresses intestinal inflammation.

There has been no report investigating the role of IL-38 in inflammatory bowel diseases (IBD). Therefore, we investigated the expression of IL-38 in IBD patients and its role in regulating intestinal inflammation. The levels of IL-38 were significantly elevated in the intestine of IBD patients and DSS-induced colitis mice. Immunofluorescence analysis revealed that B cell, not macrophage or T cell, was the source of IL-38 in the intestine. We found that rIL-38 treatment significantly attenuated DSS-induced colitis, including alleviation of weight loss, disease activity index, macroscopic changes and histological damage of colon, along with lower levels of IL-1ß and TNF-α. In vitro, rIL-38 significantly decreased the expression of proinflammatory cytokines in LPS-stimulated RAW 264.7 cells and BMDM. This is the first study suggesting that IL-38 may have a protective effect in IBD, which inhibits the production of proinflammatory cytokines from macrophages. IL-38 may represent a promising therapeutic strategy in IBD.

Oxidative decarbonylative coupling of aliphatic aldehydes with methacryloyl benzamides to generate isoquinoline-1,3(2H,4H)-diones.

Alkyl-substituted isoquinoline-1,3(2H,4H)-diones were prepared by decarbonylative coupling of N-alkyl-N-methacryloylbenzamides and aliphatic aldehydes under metal-free conditions. The reaction undergoes subsequent decarbonylation, radical addition and cyclization processes with aliphatic aldehydes as the cheap and abundant alkyl radical source. This procedure offers a complementary approach to the convenient generation of alkyl-substituted isoquinoline-1,3(2H,4H)-diones.

Epigenetic modification of m6A methylation: Regulatory factors, functions and mechanism in inflammatory bowel disease.

Although the exact cause of inflammatory bowel disease (IBD) is still unknown, there is a lot of evidence to support the notion that it results from a combination of environmental factors, immune system issues, gut microbial changes, and genetic susceptibility. In recent years, the role of epigenetics in the pathogenesis of IBD has drawn increasing attention. The regulation of IBD-related immunity, the preservation of the intestinal epithelial barrier, and autophagy are all significantly influenced by epigenetic factors. The most extensive epigenetic methylation modification of mammalian mRNA among them is N6-methyladenosine (m6A). It summarizes the general structure and function of the m6A regulating factors, as well as their complex effects on IBD by regulating the intestinal mucous barrier, intestine mucosal immunity, epidermal cell death, and intestinal microorganisms.This paper provides key insights for the future identification of potential new targets for the diagnosis and treatment of IBD.

Has the agricultural cooperatives served each member fairly? A new perspective based on utilization level of member services.

With the rapid increase of the number of agricultural cooperatives in China, the problem of fake cooperatives has become more and more serious. The core problem is that some members do not use cooperative services, and elite capture phenomenon appears in the organization. Since services are one of the most important public goods attributes of cooperatives, it is important to ensure that more members use them. What are the factors that affect members' utilization level of cooperative services? Existing research does not provide a comprehensive answer. Based on the micro-survey data of 74 citrus cooperatives and 524 citrus members in China, the article found out that 50.9% of the members did not use any services provided by cooperatives, and only 20.04% of the members used cooperatives' sales services. So, this study empirically analyzes the factors that influence the use of cooperatives' services by puns model. The results show that quality of service, service convenience and mountain terrain promote the use of cooperative sales services for members. In addition, cooperative knowledge, planting area, surplus distribution, quality of service, and service convenience significantly increased the utilization leve of cooperative sales services by members. Finally, the study puts forward some suggestions, such as propagating cooperative sales service, improving the quality of cooperative sales service, perfecting cooperative distribution system.

Gestational valproic acid exposure enhances facial stimulation-evoked cerebellar mossy fiber-granule cell transmission via GluN2A subunit-containing NMDA receptor in offspring mice.

Valproic acid (VPA) is one of the most effective antiepileptic drugs, and exposing animals to VPA during gestation has been used as a model for autism spectrum disorder (ASD). Numerous studies have shown that impaired synaptic transmission in the cerebellar cortical circuits is one of the reasons for the social deficits and repetitive behavior seen in ASD. In this study, we investigated the effect of VPA exposure during pregnancy on tactile stimulation-evoked cerebellar mossy fiber-granule cell (MF-GC) synaptic transmission in mice anesthetized with urethane. Three-chamber testing showed that mice exposed to VPA mice exhibited a significant reduction in social interaction compared with the control group. In vivo electrophysiological recordings revealed that a pair of air-puff stimulation on ipsilateral whisker pad evoked MF-GC synaptic transmission, N1, and N2. The evoked MF-GC synaptic responses in VPA-exposed mice exhibited a significant increase in the area under the curve (AUC) of N1 and the amplitude and AUC of N2 compared with untreated mice. Cerebellar surface application of the selective N-methyl-D-aspartate (NMDA) receptor blocker D-APV significantly inhibited facial stimulation-evoked MF-GC synaptic transmission. In the presence of D-APV, there were no significant differences between the AUC of N1 and the amplitude and AUC of N2 in the VPA-exposed mice and those of the untreated mice. Notably, blockade of the GluN2A subunit-containing, but not the GluN2B subunit-containing, NMDA receptor, significantly inhibited MF-GC synaptic transmission and decreased the AUC of N1 and the amplitude and AUC of N2 in VPA-exposed mice to levels similar to those seen in untreated mice. In addition, the GluN2A subunit-containing NMDA receptor was expressed at higher levels in the GC layer of VPA-treated mice than in control mice. These results indicate that gestational VPA exposure in mice produces ASD-like behaviors, accompanied by increased cerebellar MF-GC synaptic transmission and an increase in GluN2A subunit-containing NMDA receptor expression in the offspring.

Smad4 regulates TGF-ß1-mediated hedgehog activation to promote epithelial-to-mesenchymal transition in pancreatic cancer cells by suppressing Gli1 activity.

Pancreatic cancer (PC) is an aggressive and metastatic gastrointestinal tumor with a poor prognosis. Persistent activation of the TGF-ß/Smad signaling induces PC cell (PCC) invasion and infiltration via epithelial-to-mesenchymal transition (EMT). Hedgehog signaling is a crucial pathway for the development of PC via the transcription factors Gli1/2/3. This study aimed to investigate the underlying molecular mechanisms of action of hedgehog activation in TGF-ß1-triggered EMT in PCCs (PANC-1 and BxPc-3). In addition, overexpression and shRNA techniques were used to evaluate the role of Smad4 in TGF-ß1-treated PCCs. Our data showed that TGF-ß1 promoted PCC invasion and infiltration via Smad2/3-dependent EMT. Hedgehog-Gli signaling axis in PCCs was activated upon TGF-ß1 stimulation. Inhibition of hedgehog with cyclopamine effectively antagonized TGF-ß1-induced EMT, thereby suggesting that the hedgehog signaling may act as a downstream cascade signaling of TGF-ß1. As a key protein that assists the nuclear translocation of Smad2/3, Smad4 was highly expressed in PANC-1 cells, but not in BxPc-3 cells. Conversely, Gli1 expression was low in PANC-1 cells, but high in BxPc-3 cells. Furthermore, knockdown of Smad4 in PANC-1 cells by shRNA inhibited TGF-ß1-mediated EMT and collagen deposition. Overexpression of Smad4 did not affect TGF-ß1-mediated EMT due to the lack of significant increase in nuclear expression of Smad4. Importantly, Gli1 activity was upregulated by Smad4 knockdown in PANC-1 cells and downregulated by Smad4 overexpression in BxPc-3 cells, indicating that Gli1 may be a negative target protein downstream of Smad4. Thus, Smad4 regulates TGF-ß1-mediated hedgehog activation to promote EMT in PCCs by suppressing Gli1 activity.

Synthesis of imides by palladium-catalyzed C-H functionalization of aldehydes with secondary amides.

An efficient palladium-catalyzed C-H functionalization of aldehydes with various N-substituted N-heteroarene-2-carboxamides has been developed for the synthesis of secondary imides. The reaction tolerates various functionalities, such as methoxy, fluoro, chloro, and bromo groups. A tentative radical mechanism for a Pd(II)/Pd(IV) catalytic cycle is proposed.

NAD+ Metabolism and Immune Regulation: New Approaches to Inflammatory Bowel Disease Therapies.

Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), is a multifactorial systemic inflammatory immune response. Nicotinamide adenine dinucleotide (NAD+) is a co-enzyme involved in cell signaling and energy metabolism. Calcium homeostasis, gene transcription, DNA repair, and cell communication involve NAD+ and its degradation products. There is a growing recognition of the intricate relationship between inflammatory diseases and NAD+ metabolism. In the case of IBD, the maintenance of intestinal homeostasis relies on a delicate balance between NAD+ biosynthesis and consumption. Consequently, therapeutics designed to target the NAD+ pathway are promising for the management of IBD. This review discusses the metabolic and immunoregulatory processes of NAD+ in IBD to examine the molecular biology and pathophysiology of the immune regulation of IBD and to provide evidence and theoretical support for the clinical use of NAD+ in IBD.

New sights of immunometabolism and agent progress in colitis associated colorectal cancer.

Colitis associated colorectal cancer is a disease with a high incidence and complex course that develops from chronic inflammation and deteriorates after various immune responses and inflammation-induced attacks. Colitis associated colorectal cancer has the characteristics of both immune diseases and cancer, and the similarity of treatment models contributes to the similar treatment dilemma. Immunometabolism contributes to the basis of life and is the core of many immune diseases. Manipulating metabolic signal transduction can be an effective way to control the immune process, which is expected to become a new target for colitis associated colorectal cancer therapy. Immune cells participate in the whole process of colitis associated colorectal cancer development by transforming their functional condition via changing their metabolic ways, such as glucose, lipid, and amino acid metabolism. The same immune and metabolic processes may play different roles in inflammation, dysplasia, and carcinoma, so anti-inflammation agents, immunomodulators, and agents targeting special metabolism should be used in combination to prevent and inhibit the development of colitis associated colorectal cancer.