A Review for Artificial Intelligence Based Protein Subcellular Localization.

Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to a broad range of diseases, such as cancer and Alzheimer's disease. Knowing where a target protein resides within a cell will give insights into tailored drug design for a disease. As the gold validation standard, the conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, and fluorescent biomarker tags for protein subcellular location identification. However, the booming era of proteomics and high-throughput sequencing generates tons of newly discovered proteins, making protein subcellular localization by wet-lab experiments a mission impossible. To tackle this concern, in the past decades, artificial intelligence (AI) and machine learning (ML), especially deep learning methods, have made significant progress in this research area. In this article, we review the latest advances in AI-based method development in three typical types of approaches, including sequence-based, knowledge-based, and image-based methods. We also elaborately discuss existing challenges and future directions in AI-based method development in this research field.

A novel radiomics nomogram based on T2-sampling perfection with application-optimized contrasts using different flip-angle evolutions (SPACE) images for predicting cochlear and vestibular endolymphatic hydrops in Meniere's disease patients.

OBJECTIVES: To construct and validate a radiomics nomogram based on T2-sampling perfection with application-optimized contrasts using different flip-angle evolutions (SPACE) images for predicting cochlear and vestibular endolymphatic hydrops (EH) in Meniere's disease patients. METHODS: A total of 156 patients (312 affected ears) with bilateral definite Meniere's disease who underwent delayed enhancement MRI scans were enrolled in this study. All ears of the patients were divided into a training set (n = 218) and an internal validation set (n = 94). A radiomics nomogram was constructed from radiomics features extracted from the T2-SPACE images, and a radiomics score was calculated. Performance of the radiomics nomogram was assessed using receiver operating characteristics analysis. RESULTS: Five features were selected for the construction of the cochlear radiomics nomogram, and seven features for the vestibular radiomics nomogram. The radiomics nomograms exhibited robust performance in differentiating between EH-positive and EH-negative statuses in both training and validation cohorts, with the area under the receiver operating characteristics curve values for cochlear and vestibular radiomic nomograms being 0.703 and 0.728 in the training set, and 0.718 and 0.701 in the validation set, respectively. CONCLUSION: The novel radiomics nomograms based on T2-SPACE images were successfully constructed to predict cochlear and vestibular EH in Meniere's disease. The models showed a solid and superior performance and may play an important role in the EH prediction. CLINICAL RELEVANCE STATEMENT: We constructed a novel radiomics nomogram, which can be a very useful tool for predicting cochlear and vestibular endolymphatic hydrops in Meniere's disease patients. KEY POINTS: • This is the first T2-SPACE-based nomogram to predict cochlear and vestibular endolymphatic hydrops. • The nomogram is of great value to patients who are unable to undergo delayed enhancement MRI scans.

Single-cell and bulk RNA sequencing highlights the role of M1-like infiltrating macrophages in antibody-mediated rejection after kidney transplantation.

Background: Antibody-mediated rejection (ABMR) significantly affects transplanted kidney survival, yet the macrophage phenotype, ontogeny, and mechanisms in ABMR remain unclear. Method: We analyzed post-transplant sequencing and clinical data from GEO and ArrayExpress. Using dimensionality reduction and clustering on scRNA-seq data, we identified macrophage subpopulations and compared their infiltration in ABMR and non-rejection cases. Cibersort quantified these subpopulations in bulk samples. Cellchat, SCENIC, monocle2, and monocle3 helped explore intercellular interactions, predict transcription factors, and simulate differentiation of cell subsets. The Scissor method linked macrophage subgroups with transplant prognosis. Furthermore, hdWGCNA, nichnet, and lasso regression identified key genes associated with core transcription factors in selected macrophages, validated by external datasets. Results: Six macrophage subgroups were identified in five post-transplant kidney biopsies. M1-like infiltrating macrophages, prevalent in ABMR, correlated with pathological injury severity. MIF acted as a primary intercellular signal in these macrophages. STAT1 regulated monocyte-to-M1-like phenotype transformation, impacting transplant prognosis via the IFNγ pathway. The prognostic models built on the upstream and downstream genes of STAT1 effectively predicted transplant survival. The TLR4-STAT1-PARP9 axis may regulate the pro-inflammatory phenotype of M1-like infiltrating macrophages, identifying PARP9 as a potential target for mitigating ABMR inflammation. Conclusion: Our study delineates the macrophage landscape in ABMR post-kidney transplantation, underscoring the detrimental impact of M1-like infiltrating macrophages on ABMR pathology and prognosis.

A 3-hour time interval may not be sufficient for delayed enhancement magnetic resonance imaging with intravenous gadoteridol injection based on 3d-real IR sequence of the inner ear in Meniere's disease patient.

BACKGROUND: Magnetic resonance imaging (MRI) can be applied to visualize endolymphatic hydrops (EH). AIMS/OBJECTIVES: To explore whether a 3-h time interval was feasible for clinical practice. MATERIALS AND METHODS: We prospectively enrolled 15 patients with unilateral Meniere's disease, each of whom underwent delayed enhancement MRI scan of the inner ear after intravenous gadoteridol injection at a 3-h interval. The ears of these patients were divided into two groups (group A: the affected ears; group B: the unaffected ears). Among the two groups, the signal intensity in perilymphatic area of the basal turn of cochlea, the results of visual evaluations in the vestibule, cochlea and semicircular canal and the detection results of EH were compared. RESULTS: Regarding the signal intensity, a difference was found between group A and group B (p = .016). Besides, no difference was found between the visual evaluations in the vestibule, cochlea and semicircular canal of the two groups. Regarding the detection results of EH, group A (6 vestibules were undiagnosable; 8 cochleae were undiagnosable); group B (9 vestibules were undiagnosable; 10 cochleae were undiagnosable). CONCLUSIONS AND SIGNIFICANCE: In the clinical application of gadoteridol for the inner ear, 3-h delayed MR imaging may not be sufficient.

Differentiation of Sinonasal NKT From Diffuse Large B-Cell Lymphoma Using Machine Learning and MRI-Based Radiomics.

PURPOSE: The aim of this study was to construct and validate a noninvasive radiomics method based on magnetic resonance imaging to differentiate sinonasal extranodal natural killer/T-cell lymphoma from diffuse large B-cell lymphoma. METHODS: We collected magnetic resonance imaging scans, including contrast-enhanced T1-weighted imaging and T2-weighted imaging, from 133 patients with non-Hodgkin lymphoma (103 sinonasal extranodal natural killer/T-cell lymphoma and 30 diffuse large B-cell lymphoma) and randomly split them into training and testing cohorts at a ratio of 7:3. Clinical characteristics and image performance were analyzed to build a logistic regression clinical-image model. The radiomics features were extracted on contrast-enhanced T1-weighted imaging and T2-weighted imaging images. Maximum relevance minimum redundancy, selectKbest, and the least absolute shrinkage and selection operator algorithms (LASSO) were applied for feature selection after balancing the training set. Five machine learning classifiers were used to construct the single and combined sequences radiomics models. Sensitivity, specificity, accuracy, precision, F1score, the area under receiver operating characteristic curve, and the area under precision-recall curve were compared between the 15 models and the clinical-image model. The diagnostic results of the best model were compared with those of 2 radiologists. RESULTS: The combined sequence model using support vector machine proves to be the best, incorporating 7 features and providing the highest values of specificity (0.903), accuracy (0.900), precision (0.727), F1score (0.800), and area under precision-recall curve (0.919) with relatively high sensitivity (0.889) in the testing set, along with a minimum Brier score. The diagnostic results differed significantly ( P < 0.05) from those of radiology residents, but not significantly ( P > 0.05) from those of experienced radiologists. CONCLUSIONS: Magnetic resonance imaging based on machine learning and radiomics to identify the type of sinonasal non-Hodgkin lymphoma is effective and has the potential to help radiology residents for diagnosis and be a supplement for biopsy.

Tumor-suppressive effect of Reg3A in COAD is mediated by T cell activation in nude mice.

Regenerating family protein 3 A (Reg3A) is highly expressed in a variety of organs and inflammatory tissues, and is closely related to tumorigenesis and cancer progression. However, clinical statistics show that high expression of Reg3A is associated with better prognosis in colorectal cancer (CRC) patients, suggesting a tumor-suppressive effect. The precise action and underlying mechanism of Reg3A in CRC remain controversial. The present study sought to investigate the relationship among Reg3A expression, CRC development, and immune cell alteration in patients using the TCGA, GEPIA, PrognoScan, TIMER and TISIDB databases. Reg3A-overexpressing LoVo cell line (LoVo-Reg3A), a representative of colon adenocarcinoma (COAD), was constructed and the action of Reg3A was assessed in a xenograft nude mouse model. Our bioinformatical analyses revealed that Reg3A upregulation is highly associated with CRC, along with increased frequency of immune cell infiltration. In the xenograft nude mice, Reg3A overexpression offered a tumor-suppressive effect by inhibiting cell proliferation and promoting apoptosis. The result of RNA-seq suggested a positive regulation of leukocytes and an upregulation of T cells in LoVo-Reg3A tumor tissue. CD4+ and CD8+ T cells in tumors, splenic Reg3A-reactive IFN-γ+/CD4+ T cells, and serum TNF-α, IFN-γ and IL-17 were significantly increased by Reg3A overexpression. In the ex vivo co-culture experiment, elevated cytotoxic effect, increased proportion of CD3ε+ T cells, and upregulated expressions of TNF-α, IFN-γ and IL-17 were detected in the PBMCs isolated from LoVo-Reg3A cell-xenografted nude mice. In conclusion, high expression of Reg3A could activate and recruit T cells in COAD leading to the cytotoxic tumor-suppressive effect.

N6-methyladenosine regulators-related immune genes enable predict graft loss and discriminate T-cell mediate rejection in kidney transplantation biopsies for cause.

Objective: The role of m6A modification in kidney transplant-associated immunity, especially in alloimmunity, still remains unknown. This study aims to explore the potential value of m6A-related immune genes in predicting graft loss and diagnosing T cell mediated rejection (TCMR), as well as the possible role they play in renal graft dysfunction. Methods: Renal transplant-related cohorts and transcript expression data were obtained from the GEO database. First, we conducted correlation analysis in the discovery cohort to identify the m6A-related immune genes. Then, lasso regression and random forest were used respectively to build prediction models in the prognosis and diagnosis cohort, to predict graft loss and discriminate TCMR in dysfunctional renal grafts. Connectivity map (CMap) analysis was applied to identify potential therapeutic compounds for TCMR. Results: The prognostic prediction model effectively predicts the prognosis and survival of renal grafts with clinical indications (P< 0.001) and applies to both rejection and non-rejection situations. The diagnostic prediction model discriminates TCMR in dysfunctional renal grafts with high accuracy (area under curve = 0.891). Meanwhile, the classifier score of the diagnostic model, as a continuity index, is positively correlated with the severity of main pathological injuries of TCMR. Furthermore, it is found that METTL3, FTO, WATP, and RBM15 are likely to play a pivotal part in the regulation of immune response in TCMR. By CMap analysis, several small molecular compounds are found to be able to reverse TCMR including fenoldopam, dextromethorphan, and so on. Conclusions: Together, our findings explore the value of m6A-related immune genes in predicting the prognosis of renal grafts and diagnosis of TCMR.

The Prediction of Necroptosis-Related lncRNAs in Prognosis and Anticancer Therapy of Colorectal Cancer.

Background: Colorectal cancer is one of the most common gastrointestinal malignancies globally. Necroptosis has been proved to play a role in the occurrence and development of the tumor, which makes it a new target for molecular therapy. However, the role of necroptosis in colorectal cancer remains unknown yet. Our study aims to build a prognostic signature of necroptosis-related lncRNAs (nrlncRNAs) to predict the outcomes of patients with colorectal cancer and facilitate in anticancer therapy. Method: We obtained RNA-seq and clinical data of colorectal adenocarcinoma from the TCGA database and got prognosis-related nrlncRNAs by univariate regression analysis. Then, we carried out the LASSO regression and multivariate regression analysis to build the prognostic signature, whose predictive ability was tested by the Kaplan-Meier as well as ROC curves and verified by the internal cohort. Moreover, we divided the cohort into 2 groups based on median of risk scores: high- and low-risk groups. By analyzing the difference in the tumor microenvironment, microsatellite instability, and tumor mutation burden between the two groups, we explored the potential chemotherapy and immunotherapy drugs. Results: We screened out 9 nrlncRNAs and built a prognostic signature based on them. With its good prognostic ability, the risk scores can act as an independent prognostic factor for patients with colorectal cancer. The overall survival rate of patients in high-risk group was significantly higher than the low-risk one. Furthermore, risk scores can also give us hints about the tumor microenvironment and facilitate in predicting the response to the CTLA-4 blocker treatment and other chemotherapeutic agents with potential efficacy such as cisplatin and staurosporine. Conclusions: In conclusion, our prognostic signature of necroptosis-related lncRNAs can facilitate in predicting the prognosis and response to the anticancer therapy of colorectal cancer patients.

Recombinant Reg3α Prevents Islet ß-Cell Apoptosis and Promotes ß-Cell Regeneration.

Progressive loss and dysfunction of islet ß-cells has not yet been solved in the treatment of diabetes. Regenerating protein (Reg) has been identified as a trophic factor which is demonstrated to be associated with pancreatic tissue regeneration. We previously produced recombinant Reg3α protein (rReg3α) and proved that it protects against acute pancreatitis in mice. Whether rReg3α protects islet ß-cells in diabetes has been elusive. In the present study, rReg3α stimulated MIN6 cell proliferation and resisted STZ-caused cell death. The protective effect of rReg3α was also found in mouse primary islets. In BALB/c mice, rReg3α administration largely alleviated STZ-induced diabetes by the preservation of ß-cell mass. The protective mechanism could be attributed to Akt/Bcl-2/-xL activation and GRP78 upregulation. Scattered insulin-expressing cells and clusters with small size, low insulin density, and exocrine distribution were observed and considered to be neogenic. In isolated acinar cells with wheat germ agglutinin (WGA) labeling, rReg3α treatment generated insulin-producing cells through Stat3/Ngn3 signaling, but these cells were not fully functional in response to glucose stimulation. Our results demonstrated that rReg3α resists STZ-induced ß-cell death and promotes ß-cell regeneration. rReg3α could serve as a potential drug for ß-cell maintenance in anti-diabetic treatment.

Government information disclosure and citizen coproduction during COVID-19 in China.

While information campaigns have been widely recognized as a pillar of public health crisis management and heightened by the current COVID-19 pandemic, an insufficient number of studies have investigated the impact of information disclosure on influencing citizen cooperation crucial for emergency management. Focusing on generic information disclosure practices during the recovery period from January 19, 2020, to February 29, 2020, in China and by employing a difference-in-difference method, this study finds that information disclosure significantly enhanced citizen coproduction as measured by aggregated search queries of COVID-19-related information, and earlier disclosure yielded greater effect more quickly. Moreover, government capacity and citizens' trust in government at the local level significantly moderate the positive impact of information disclosure. This study uncovers the novel relationship between information disclosure and citizen coproduction during emergencies in the Chinese context.

Diagnostic Accuracy of Donor-derived Cell-free DNA in Renal-allograft Rejection: A Meta-analysis.

BACKGROUND: Donor-derived cell-free DNA (dd-cfDNA) is a potential noninvasive molecular marker of graft rejection after kidney transplant, whose diagnostic accuracy remains controversial. METHODS: We performed a systematic review and metaanalysis to evaluate the diagnostic accuracy of dd-cfDNA. Relevant literature was searched from online databases, and the data on the diagnostic accuracy of discriminating main rejection episodes (MRE) and antibody-mediated rejection (AMR) were merged, respectively. RESULTS: Nine studies were included in the metaanalysis, of which 6 were focused on the diagnostic accuracy of dd-cfDNA for MRE, whose pooled sensitivity, specificity, area under the receiver operating characteristics curve, diagnostic odds ratio, overall positive likelihood ratio, and negative likelihood ratio with 95% confidence intervals were 0.70 (0.57-0.81), 0.78 (0.70-0.84), 0.81 (0.77-0.84), 8.18 (5.11-13.09), 3.15 (2.47-4.02), and 0.39 (0.27-0.55), respectively. Five tests were focused on discriminating AMR, whose pooled indicators were 0.84 (0.75-0.90), 0.80 (0.74-0.84), 0.89 (0.86-0.91), 20.48 (10.76-38.99), 4.13(3.21-5.33), and 0.20(0.12-0.33), respectively. CONCLUSIONS: Donor-derived cell-free DNA can be a helpful marker for the diagnosis of AMR among those recipients suspected of renal dysfunction. Its diagnostic accuracy on the MRE remains uncertain, which requires further prospective, large-scale, multicenter, and common population research.

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During atmospheric precipitation, the evaporation of raindrops falling from the bottom of cloud layer to the ground and passing through unsaturated air, a process was called sub-cloud secondary evaporation, which will change the isotopic composition of precipitation. Using the hydrogen and oxygen stable isotope method to understand the temporal and spatial variation of secondary evaporation effect under clouds and its causes is important to understand regional water cycle process. Based on hourly meteorological data of 187 meteorological stations in Shaanxi-Gansu-Ningxia region from March 2018 to February 2019, the spatial and temporal variations of evaporation surplus ratio (f) and precipitation excess deuterium variation (Δd) were analyzed using the improved Ste-wart model, and the relationships between f and meteorological elements and Δd were examined. The results showed that, at the hourly scale, the minimum values of f and Δd in all provinces of the region appeared in the daytime, and the maximum values appeared in the night, indicating that the secondary evaporation effect under the cloud was more obvious in the daytime. At the monthly scale, the monthly variation trend of f and Δd in each province was relatively consistent, with the minimum value appearing in the summer half year, and the maximum value appearing in the winter half year, indicating that the second evaporation effect under cloud was more significant in the summer half year. From the spatial perspective, the spatial variation of f and Δd values in the region was consistent with that at the seasonal scale. In spring, the eastern and western regions were larger while the central part was smaller. In summer, the northwest region was smaller, and other regions were larger. In autumn, it decreased from south to north. In winter, the central and southern regions were smaller, and the western and northeast regions were larger. The spatial differences of secondary evaporation effects under clouds in different seasons was significant. The slopes of the linear relationship between f and Δd in Shaanxi, Gansu and Ningxia provinces were all less than 1‰·%-1, which may be caused by the arid and semi-arid climate in this area. When air temperature was higher and the relative humidity, vapor pressure, precipitation and raindrop diameter were smaller, the value of Δd was smaller, and the secondary evaporation effect under the cloud was more obvious.

Identification of Kidney Transplant Recipients with Coronavirus Disease 2019.

Coronavirus disease 2019 (COVID-19) is a novel and lethal infectious disease, posing a threat to global health security. The number of cases has increased rapidly, but no data concerning kidney transplant (KTx) recipients infected with COVID-19 are available. To present the epidemiological, clinical, and therapeutic characteristics of KTx recipients infected with COVID-19, we report on a case series of five patients who were confirmed as having COVID-19 through nucleic acid testing (NAT) from January 1, 2020 to February 28, 2020. The most common symptoms on admission to hospital were fever (five patients, 100%), cough (five patients, 100%), myalgia or fatigue (three patients, 60%), and sputum production (three patients, 60%); serum creatinine or urea nitrogen levels were slightly higher than those before symptom onset. Four patients received a reduced dose of maintenance immunosuppressive therapy during hospitalization. As of March 4, 2020 NAT was negative for COVID-19 in three patients twice in succession, and their computed tomography scans showed improved images. Although greater patient numbers and long-term follow-up data are needed, our series demonstrates that mild COVID-19 infection in KTx recipients can be managed using symptomatic support therapy combined with adjusted maintenance immunosuppressive therapy.

Bacterial community composition shaped by water chemistry and geographic distance in an anthropogenically disturbed river.

'Core bacterial communities', bacterial species that are found consistently throughout a river continuum, have previously been identified. However, variations in core and non-core bacterial community structure, as well as the relationships between these communities and water chemistry or geographic distance have not been well studied. Here, we sampled in the entire course of the Le'an River, China, and explored the bacterial community composition at each site using Illumina high-throughput sequencing. The proportion of sequence reads assigned to the core community was ~95% in the upper and middle reaches, gradually decreasing below 90% in the lower reaches. Both the Chao1 richness index and the Shannon diversity index of the bacterial communities were significantly higher in the wet season than in the dry season, and both indices increased slightly from upstream to downstream. The variation in the non-core community was more aggregated from upstream to downstream in the wet season than in the dry season, while the aggregation of the core community was similar between the dry season and the wet season. The proportion of typical freshwater bacterial was significantly higher in the core community than in the non-core community. NO3--N was the subset of water chemistry parameters that best explained bacterial community dissimilarities, while 'river length' was the subset of geographic distance parameters that best explained bacterial community dissimilarities. Water chemistry parameters explained more of the variations in the bacterial communities than did geographic distance, especially in the dry season. However, the correlation between water chemistry and bacteria was primarily due to collective allochthonous input (mass effects), not because of any nutritious or toxic effects on bacterial growth competition (species sorting). The greater influence of the mass effects, as compared to species sorting, on bacterial community structure was due to the allochthonous input of bacteria from anthropogenic sources.