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ABSTRACTThe 20-year war in Afghanistan has had a catastrophic impact on agricultural planting and food security, but the assessment was difficult due to a lack of existing statistics. We used 30m Landsat data to extract the annual planting area and built the time series to measure the condition of agriculture, and used constant nighttime light data to quantify the impact of the war. Combined with climate, Digital Elevation Model (DEM) data, etc., we quantitatively analysis the impact of the war using regression model. From a time perspective, the total planting area reached peek during some period of relative pacification, but maintained a low level of planting most time. From a spatial perspective, the main planting areas shifted from east to west. Both poppy and wheat planting have a high correlation with non-natural factor, while wheat affected more by natural conditions compared with poppy. In addition, the cultivation of wheat is limited by poppy. As a verification, we collect relative history records to explain the rationality of the result of analysis. According to the result, we reveal the adverse effects of war on agricultural planting and food security in Afghanistan and provide a reference for relevant researches on war and agriculture.

Forest defoliating pests are significant global forest disturbance agents, posing substantial threats to forest ecosystems. However, previous studies have lacked systematic analyses of the continuous spatiotemporal distribution characteristics over a complete 3–5 year disaster cycle based on remote sensing data. This study focuses on the Dendrolimus superans outbreak in the Changbai Mountain region of northeastern China. Utilizing leaf area index (LAI) data derived from Sentinel-2A satellite images, we analyze the extent and dynamic changes of forest defoliation. We comprehensively examine the spatiotemporal patterns of forest defoliating pest disasters and their development trends across different forest types. Using the geographical detector method, we quantify the main influencing factors and their interactions, revealing the differential impacts of various factors during different growth stages of the pests. The results show that in the early stage of the Dendrolimus superans outbreak, the affected area is extensive but with mild severity, with newly affected areas being 23 times larger than during non-outbreak periods. In the pre-hibernation stage, the affected areas are smaller but more severe, with a cumulative area reaching up to 8213 hectares. The spatial diffusion characteristics of the outbreak follow a sequential pattern across forest types: Larix olgensis, Pinus sylvestris var. mongolica, Picea koraiensis, and Pinus koraiensis. The most significant influencing factor during the pest development phase was the relative humidity of the year preceding the outbreak, with a q-value of 0.27. During the mitigation phase, summer precipitation was the most influential factor, with a q-value of 0.12. The combined effect of humidity and the low temperatures of 2020 had the most significant impact on both the development and mitigation stages of the outbreak. This study’s methodology achieves a high-precision quantitative inversion of long-term disaster spatial characteristics, providing new perspectives and tools for real-time monitoring and differentiated control of forest pest infestations.

Soil microarthropods are sensitive to environmental changes and can respond quickly to external fluctuations in the environment. To investigate the response of soil microarthropod communities to long-term nitrogen addition in a Stipa baicalensis meadow steppe, six nitrogen addition treatments (0 (Control group), 30, 50, 100, 150 and 200 kg ha−1 yr−1) were designed in 2010 in Ewenke Banner, Hulunbeier City, Inner Mongolia. The soil microarthropod community structure and diversity in response to long-term nitrogen additions in the litter and soil layers and the relationship with environmental factors were then analysed. The results showed the following: (1) The number of individuals and taxa of soil microarthropods significantly increased under long-term nitrogen addition; particularly, in the N200 treatment. The vertically distribution pattern showed that the litter layer (532 specimens, 47 families) > 0–10 cm soil layer (383 specimens, 35 families) > 10–20 cm soil layer (98 specimens, 19 families). The common dominant taxa in the litter layer (Poduromorpha) and 0–10 cm soil layer (Poduromorpha and Psocoptera) was Poduromorpha, and that in the 0–10 cm and 10–20 cm soil layers (Psocoptera and Prostigmata) was Psocoptera, both of which showed universal adaptability to microhabitat changes under nitrogen addition. (2) The addition of nitrogen resulted in the division of community structure of soil microarthropods in the litter layer and the 0–10 cm soil layer into 3 groups. The N0-N100 treatments formed one group, while the N150 and N200 treatments formed another two group, and the community distribution of soil microarthropods among the 3 groups was significantly different. (3) The Shannon–Wiener and Jaccard indices of soil microarthropods exhibited significantly greater values in the N150 and N200 treatment, the composition of the soil microarthropod community is evolving towards the co-development of multiple taxa. (4) With long-term nitrogen addition conditions, the community composition and diversity characteristics of soil microarthropods were regulated by litter nitrogen and phosphorus and aboveground biomass in the litter layer, soil pH, nitrate nitrogen and belowground biomass in the 0–10 cm soil layer, and soil nitrate nitrogen and soil moisture content in the 10–20 cm soil layer. In conclusion, soil microarthropod community structure was significantly different among different microhabitats under long-term nitrogen addition, and the change in environmental factors in microhabitats was the main factor driving the development of the soil microarthropod community.

Individuals with PhDs and postdoctoral experience in the life sciences can pursue a variety of career paths. Many PhD students and postdocs aspire to a permanent research position at a university or research institute, but competition for such positions has increased. Here, we report a time-resolved analysis of the career paths of 2284 researchers who completed a PhD or a postdoc at the European Molecular Biology Laboratory (EMBL) between 1997 and 2020. The most prevalent career outcome was Academia: Principal Investigator (636/2284=27.8% of alumni), followed by Academia: Other (16.8%), Science-related Non-research (15.3%), Industry Research (14.5%), Academia: Postdoc (10.7%) and Non-science-related (4%); we were unable to determine the career path of the remaining 10.9% of alumni. While positions in Academia (Principal Investigator, Postdoc and Other) remained the most common destination for more recent alumni, entry into Science-related Non-research, Industry Research and Non-science-related positions has increased over time, and entry into Academia: Principal Investigator positions has decreased. Our analysis also reveals information on a number of factors – including publication records – that correlate with the career paths followed by researchers.

The t(14;19)(q32;q13) often juxtaposes BCL3 with immunoglobulin heavy chain (IGH) resulting in overexpression of the gene. In contrast to other oncogenic translocations, BCL3 rearrangement (BCL3-R) has been associated with a broad spectrum of lymphoid neoplasms. Here we report an integrative whole-genome sequence, transcriptomic, and DNA methylation analysis of 13 lymphoid neoplasms with BCL3-R. The resolution of the breakpoints at single base-pair revealed that they occur in two clusters at 5’ (n=9) and 3’ (n=4) regions of BCL3 associated with two different biological and clinical entities. Both breakpoints were mediated by aberrant class switch recombination of the IGH locus. However, the 5’ breakpoints (upstream) juxtaposed BCL3 next to an IGH enhancer leading to overexpression of the gene whereas the 3’ breakpoints (downstream) positioned BCL3 outside the influence of the IGH and were not associated with its expression. Upstream BCL3-R tumors had unmutated IGHV, trisomy 12, and mutated genes frequently seen in chronic lymphocytic leukemia (CLL) but had an atypical CLL morphology, immunophenotype, DNA methylome, and expression profile that differ from conventional CLL. In contrast, downstream BCL3-R neoplasms were atypical splenic or nodal marginal zone lymphomas (MZL) with mutated IGHV, complex karyotypes and mutated genes typical of MZL. Two of the latter four tumors transformed to a large B-cell lymphoma. We designed a novel fluorescence in situ hybridization assay that recognizes the two different breakpoints and validated these findings in 17 independent tumors. Overall, upstream or downstream breakpoints of BCL3-R are mainly associated with two subtypes of lymphoid neoplasms with different (epi)genomic, expression, and clinicopathological features resembling atypical CLL and MZL, respectively.

NOTCH mutations are frequent in B cell malignancies. Here the authors use retroviral transduction of primary malignant B cells from Chronic Lymphocytic Leukemia (CLL) and Mantle Cell Lymphoma (MCL) patients to show that NOTCH1/2-mutations facilitate mechanism of immune escape.

Proteomics can be used to refine cancer classification. Here, the authors characterise chronic lymphocytic leukaemia patients by proteogenomics, and identified a subtype of patients with poor prognosis associated with aberrant B cell receptor signalling.

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease’s diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

In order to explore the influence of foaming agent, water-binder ratio, tailings specific surface area and fiber on pyrite tailings foamed concrete the compressive strength tests of concrete were carried out and the optimal types and proportions of the above ingredients were obtained for the subsequent exploration of the influence of the amount of pyrite tailings on the strength of foam concrete. The test results show that with the increase in the amount of pyrite tailings the compressive strength of the foam concrete gradually decrease, and when the amount is 20%-30% the compressive strength of foam concrete decreases most. In the DSC-TG tests it is found that the increase in the amount of pyrite tailings will lead to the reduction of hydration products, thereby reducing the compressive strength of the foamed concrete. Through IR tests found that an increase in the amount of doping will lead to a decrease in OH-, Si-O bonds and Al-O bonds. This represents the reduction of hydration products C-S-H gel and wollastonite Thereby its compressive strength was reduced; the heat of hydration tests not only found that the increase in the amount of doping will decline its mechanical properties. It is also found that the strength provided by pyrite tailings to foamed concrete is mainly after the protection age of 50 h. Therefore, adding appropriate amount of pyrite tailings to foamed concrete can improve its compressive strength.

Abstract Screening of mRNAs and lncRNAs associated with prognosis and immunity of lung adenocarcinoma (LUAD) and used to construct a prognostic risk scoring model (PRS-model) for LUAD. To analyze the differences in tumor immune microenvironment between distinct risk groups of LUAD based on the model classification. The CMap database was also used to screen potential therapeutic compounds for LUAD based on the differential genes between distinct risk groups. he data from the Cancer Genome Atlas (TCGA) database. We divided the transcriptome data into a mRNA subset and a lncRNA subset, and use multiple methods to extract mRNAs and lncRNAs associated with immunity and prognosis. We further integrated the mRNA and lncRNA subsets and the corresponding clinical information, randomly divided them into training and test set according to the ratio of 5:5. Then, we performed the Cox risk proportional analysis and cross-validation on the training set to construct a LUAD risk scoring model. Based on the risk scoring model, patients were divided into distinct risk group. Moreover, we evaluate the prognostic performance of the model from the aspects of Area Under Curve (AUC) analysis, survival difference analysis, and independent prognostic analysis. We analyzed the differences in the expression of immune cells between the distinct risk groups, and also discuss the connection between immune cells and patient survival. Finally, we screened the potential therapeutic compounds of LUAD in the Connectivity Map (CMap) database based on differential gene expression profiles, and verified the compound activity by cytostatic assays. We extracted 26 mRNAs and 74 lncRNAs related to prognosis and immunity by using different screening methods. Two mRNAs (i.e., KLRC3 and RAET1E) and two lncRNAs (i.e., AL590226.1 and LINC00941) and their risk coefficients were finally used to construct the PRS-model. The risk score positions of the training and test set were 1.01056590 and 1.00925190, respectively. The expression of mRNAs involved in model construction differed significantly between the distinct risk population. The one-year ROC areas on the training and test sets were 0.735 and 0.681. There was a significant difference in the survival rate of the two groups of patients. The PRS-model had independent predictive capabilities in both training and test sets. Among them, in the group with low expression of M1 macrophages and resting NK cells, LUAD patients survived longer. In contrast, the monocyte expression up-regulated group survived longer. In the CMap drug screening, three LUAD therapeutic compounds, such as resveratrol, methotrexate, and phenoxybenzamine, scored the highest. In addition, these compounds had significant inhibitory effects on the LUAD A549 cell lines. The LUAD risk score model constructed using the expression of KLRC3, RAET1E, AL590226.1, LINC00941 and their risk coefficients had a good independent prognostic power. The optimal LUAD therapeutic compounds screened in the CMap database: resveratrol, methotrexate and phenoxybenzamine, all showed significant inhibitory effects on LUAD A549 cell lines.

Abstract Background To develop a reliable model to predict rapid kidney function decline (RKFD) among population at risk of cardiovascular disease. Methods In this retrospective study, key monitoring residents including the elderly, and patients with hypertension or diabetes of China National Basic Public Health Service who underwent community annual physical examinations from January 2015 to December 2020 were included. Healthy records were extracted from regional chronic disease management platform. RKFD was defined as the reduction of estimated glomerular filtration rate (eGFR) ≥ 40% during follow-up period. The entire cohort were randomly assigned to a development cohort and a validation cohort in a 2:1 ratio. Cox regression analysis was used to identify the independent predictors. A nomogram was established based on the development cohort. The concordance index (C-index) and calibration plots were calculated. Decision curve analysis was applied to evaluate the clinical utility. Results A total of 8455 subjects were included. During the median follow-up period of 3.72 years, the incidence of RKFD was 11.96% (n = 1011), 11.98% (n = 676) and 11.92% (n = 335) in the entire cohort, development cohort and validation cohort, respectively. Age, eGFR, hemoglobin, systolic blood pressure, and diabetes were identified as predictors for RKFD. Good discriminating performance was observed in both the development (C-index, 0.73) and the validation (C-index, 0.71) cohorts, and the AUCs for predicting 5-years RKFD was 0.763 and 0.740 in the development and the validation cohort, respectively. Decision curve analysis further confirmed the clinical utility of the nomogram. Conclusions Our nomogram based on five readily accessible variables (age, eGFR, hemoglobin, systolic blood pressure, and diabetes) is a useful tool to identify high risk patients for RKFD among population at risk of cardiovascular disease in primary care. Whereas, further external validations are needed before clinical generalization.

BackgroundTriglyceride-glucose (TyG) index is a simple marker of insulin resistance. However, insufficient data is available on whether the TyG index is associated with worsening renal function (WRF) in the elderly. Therefore, this study was designed to explore the association between the TyG index and WRF based on a community elderly cohort.MethodsIn this study, 7,822 elderly (aged ≥ 65 years) adults from southern China were enrolled and divided into four groups according to the TyG index quartiles. The primary endpoint was incident chronic kidney disease (CKD), defined as incident estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2. Additional endpoints included a decline in eGFR of 30% and 40% during the follow-up period.ResultsDuring the median 2.04 year follow-up period, 1,541 (19.7%) participants developed CKD. After adjusting for confounding factors, multivariable Cox regression models revealed significant associations between TyG index and incident CKD (HR per SD increase, 1.21; 95% CI: 1.14–1.29), a decline in eGFR of 30% (HR per SD increase, 1.38; 95% CI: 1.26–1.50), and decline in eGFR of 40% (HR per SD increase, 1.42; 95% CI: 1.24–1.63). Furthermore, compared with those in Q1, participants in Q4 demonstrated a higher risk of developing CKD (HR, 1.59; 95% CI: 1.35–1.88). These positive associations remained consistent across different subgroup populations.ConclusionOur study suggests a positive and independent association between the TyG index and WRF in the elderly.

Abstract The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL‐infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell‐extrinsic mechanisms of drug resistance and disease progression.

The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Chemical perturbations can be readily applied to primary cancer samples at large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a chemical compound has affinities to multiple proteins. To computationally infer specific molecular dependencies of individual cancers from their ex vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Through integrating a drug-kinase profiling dataset and several drug response datasets, our method, DepInfeR, correctly identified known protein kinase dependencies, including the EGFR dependence of HER2+ breast cancer cell lines, the FLT3 dependence of acute myeloid leukemia (AML) with FLT3-ITD mutations and the differential dependencies on the B-cell receptor pathway in the two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a detailed map of the kinase dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.

BackgroundGeneral health checks can help in controlling cardiovascular risk factors. However, few studies have investigated whether regular participation in annual health checks could further improve the control of cardiovascular risk factors compared with intermittent participation. Therefore, our study aimed to explore the association between the frequency of annual health check participation and the control of cardiovascular risk factors.MethodsResidents aged ≥ 65 years or having chronic diseases (hypertension or diabetes) from 37 communities of Guangzhou, Guangdong, who participated in the Basic Public Health Service project between January 2015 and December 2019, were enrolled and divided into 3 groups (“Sometimes,” “Usually,” and “Always”) according to their frequencies of annual health check participation. Multivariable linear regression models were performed to assess the association between the frequency of annual health check participation and the control of cardiovascular risk factors. A subgroup analysis stratified by gender was also conducted.ResultsIn total, 9,102 participants were finally included. Significant differences were identified between groups in systolic blood pressure (SBP), diastolic blood pressure (DBP), weight, fasting glucose, total cholesterol, high-density lipoprotein cholesterol, and serum creatinine. After fully adjusting for confounding factors, residents who always participated in the annual health check tended to have lower SBP (β = −4.36, 95% CI: −5.46; −3.26, p < 0.001), fasting glucose (β = −0.27, 95% CI: −0.38; −0.15, p < 0.001), and total cholesterol (β = −0.19, 95% CI: −0.26; −0.13, p < 0.001), compared with those who attended sometimes. Furthermore, gender did not alter these associations.ConclusionA higher frequency of annual health check participation was associated with lower SBP, fasting glucose, and total cholesterol.

Objective To study the molecular characterization of Cronobacter sakazakii(C. sakazakii) from infant foods. Methods The C. sakazakii isolates were characterized using antibiotic susceptibility tests and whole genome sequencing(WGS). BioNumerics software was used to analyze and assemble WGS data. Then, the multilocus sequence typing(MLST), core-genome multi-locus sequence typing(cgMLST), virulence genes profiles were performed using assembled genome sequences. The resistance genes profiles and antimicrobial susceptibility were investigated. Furthermore, STs of C. sakazakii in this study were compared with those from PubMLST database. Results In this study, nine C. sakazakii isolates were detected and subtyped into five STs. ST1 and ST64 were the predominant STs, which were also the predominant STs of C. sakazakii in PubMLST database. Three C. sakazakii isolates were found to carry the mcr-9 gene. However, all C. sakazakii isolates were sensitive to 12 antibiotics including polymyxin B and E. ST1, ST64 and ST458 carried gtrB in addition to the common virulence genes. The nine C. sakazakii isolates showed highly genomic diversity according to cgMLST results. Conclusion ST1 and ST64 were predominant STs in this study, which were also predominant STs in clinical isolates in PubMLST database. These results suggested the potential pathogenicity of C. sakazakii. Our data underscored the importance of continuous surveillance of C. sakazakii in infant foods for prevention of foodborne disease caused by C. sakazakii.

AimsTo explore the relationship between the severity of coronary artery disease (CAD) and the occurrence of ventricular tachycardia/ventricular fibrillation (VT/VF) in patients with acute myocardial infarction (AMI).MethodsWe retrospectively enrolled 705 patients with AMI, who were hospitalized and underwent percutaneous coronary intervention (PCI), in Nanfang Hospital from July 2017 to July 2020. Logistic regression analysis and backward stepwise approach were taken to select the correlation factors. The left and the receiver operating characteristic curves (ROC) analysis were plotted to observe the discriminative power of the SYNTAX score (SS)/caFFR-guided functional SS (FSScaFFR) on the incident VT/VF.ResultsAbout 58 (8.2%) patients experienced life-threatening VT/VF. The FSScaFFR (OR: 1.155; 95% CI: 1.047 to 1.273; p = 0.004) was an independent predictor of VT/VF after AMI. The ROC analysis showed that the discriminative power of FSScaFFR on the incident VT/VF was significantly better than SS (0.759 vs.0.695, p < 0.0001). Patients with VT/VF were categorized into 2 groups according to the interval between the onset of AMI and the VT/VF. The logistic regression analysis revealed that FSScaFFR was a significant independent correlation of early- and late-VT/VF.ConclusionThe incident VT/VF in patients with AMI is closely associated with the severity of CAD evaluated by SS and FSScaFFR. Compared to SS, FSScaFFR has a higher correlation with VT/VF, and FSScaFFR was demonstrated to be an independent correlation factor of incident VT/VF after AMI.

BackgroundVisceral adiposity index (VAI) is an indicator of visceral fat accumulation and dysfunction. However, little is known about whether VAI is associated with worsening renal function (WRF) in the elderly. Therefore, our study aimed to explore the association between VAI and WRF among the elderly population.MethodsIn total, 5,583 elderly participants (aged ≥ 65 years) who participated in the annual health checkups at least twice between January 2017 and July 2021 were enrolled and divided into four groups according to the VAI quartiles. The primary endpoint was incident chronic kidney disease (CKD), defined as incident estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2. The secondary endpoint was rapid kidney function decline (RKFD), defined as decline in eGFR of 40%. To evaluate the association between VAI and WRF, three Cox regression models were conducted, where VAI was treated as a continuous variable and a categorical variable (Q1 as reference), respectively. Subgroup analysis in participants with different baseline characteristics was also performed.ResultsDuring a median of 2.46 year follow-up, 931 (16.68%) participants developed CKD. After fully adjusting for confounding factors, VAI was significantly associated with incident CKD (HR, 1.052; 95% CI: 1.029–1.076, p < 0.001), and RKFD (HR, 1.077; 95% CI: 1.041–1.114, p < 0.001). Moreover, compared to those with the lowest VAI quartiles, subjects with the highest quartiles had a higher risk of incident CKD (HR, 1.286; 95% CI: 1.033–1.601, p = 0.024), and RKFD (HR, 1.895; 95% CI: 1.086–3.307, p = 0.025). The risk of incident CKD also tended to increase with elevated VAI quartiles (all p-values for trend

Objective To compare the species identification method of Cronobacter spp. in food, in order to establish rapid, high throughout identification method. Methods A total of 19 Cronobacter spp. in foods were identified with three method including biochemical method using VITEK 2.0 Compact, matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and whole-genome sequencing (WGS). The advantages and disadvantages of the three identification method were analyzed. Results The result indicated that the accuracy of VITEK identification for C. sakazakii and C. malonaticus was 67% and 66% respectively. However, WGS and MALDI-TOF MS obtained the same result for 19 Cronobacter spp.. Three subspecies could not be identified by MALDI-TOF MS due to the limited database. Conclusion Biochemical method could not be used for species identification of Cronobacter spp. MALDI-TOF MS was rapid, high throughout and accurate, but still need to expand the fingerprint database for more Cronobacter spp. isolates.

Immunoglobulin (Ig) rearrangement and translocation information are usually obtained by targeted sequencing of the respective loci. Here, the authors present the IgCaller algorithm, which extracts Ig heavy and light chain genetic properties from short-read whole-genome sequencing results to provide a feasible alternative to direct sequencing.

As object detection is widely adopted in aerial images, scene texts and other fields, rotating object detection plays an important role and draws attention since it can provide highly accurate orientation and scale information. In this article, we propose a novel and simple baseline to effectively conduct rotating object detection. First, we design a brand-new representation for rotating objects by using a circle cut horizontal rectangle (CCH). The CCH ensures that the regression parameters will not exceed the defined domain and avoids vertex sorting, thus solving some problems in current common representations, including the boundary problem and order problem, and improving the robustness. Second, we design a lightweight head based on the CCH to add the rotating regression to classic benchmark in an almost cost-free manner and propose a single-stage anchor-free rotating (SAR) object detection convolutional neural network. Finally, we demonstrate the details of our method by applying it to data sets with different scenarios. The experiments confirm that our method achieves competitive accuracy and state-of-the-art speed in aerial image and scene text detection.

Aims To develop a nomogram for incident chronic kidney disease (CKD) risk evaluation among community residents with high cardiovascular disease (CVD) risk.Methods In this retrospective cohort study, 5730 non-CKD residents with high CVD risk participating the National Basic Public Health Service between January 2015 and December 2020 in Guangzhou were included. Endpoint was incident CKD defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 during the follow-up period. The entire cohorts were randomly (2:1) assigned to a development cohort and a validation cohort. Predictors of incident CKD were selected by multivariable Cox regression and stepwise approach. A nomogram based on these predictors was developed and evaluated with concordance index (C-index) and area under curve (AUC).Results During the median follow-up period of 4.22 years, the incidence of CKD was 19.09% (n=1094) in the entire cohort, 19.03% (727 patients) in the development cohort and 19.21% (367 patients) in the validation cohort. Age, body mass index, eGFR 60–89 mL/min/1.73 m2, diabetes and hypertension were selected as predictors. The nomogram demonstrated a good discriminative power with C-index of 0.778 and 0.785 in the development and validation cohort. The 3-year, 4-year and 5-year AUCs were 0.817, 0.814 and 0.834 in the development cohort, and 0.830, 0.847 and 0.839 in the validation cohort.Conclusion Our nomogram based on five readily available predictors is a reliable tool to identify high-CVD risk patients at risk of incident CKD. This prediction model may help improving the healthcare strategies in primary care.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Emerging data suggest that CLL-cells efficiently evade immunosurveillance. T-cell deficiencies in CLL include immuno(metabolic) exhaustion that is achieved by inhibitory molecules, with programmed cell death 1/programmed cell death ligand 1 (PD-L1) signaling emerging as a major underlying mechanism. Moreover, CLL-cells are characterized by a close and recurrent interaction with their stromal niches in the bone marrow and lymph nodes. Here, they receive nurturing signals within a well-protected environment. We could previously show that the interaction of CLL-cells with stroma leads to c-Myc activation that is followed by metabolic adaptations. Recent data indicate that c-Myc also controls expression of the immune checkpoint molecule PD-L1. Therefore, we sought out to determine the role of stromal contact for the CLL-cells’ PD-L1 expression and thus their immuno-evasive phenotype.To do so, we analyzed PD-L1 expression on CLL cell (subsets) in untreated patients and on healthy donor-derived B-cells. Impact of stromal contact on PD-L1 expression on CLL-cells and the underlying signaling pathways were assessed in well-established in vitro niche models. Ex vivo and in vitro findings were validated in the Eµ-TCL1 transgenic CLL mouse model.We found increased PD-L1 expression on CLL-cells as compared with B-cells that was further enhanced in a cell-to-cell contact-dependent manner by stromal cells. In fact, circulating recent stromal-niche emigrants displayed higher PD-L1 levels than long-time circulating CLL-cells. Using our in vitro niche model, we show that a novel Notch-c-Myc-enhancer of zeste homolog 2 (EZH2) signaling axis controls PD-L1 upregulation. Ultimately, elevated PD-L1 levels conferred increased resistance towards activated autologous T-cells.In summary, our findings support the notion that the CLL microenvironment contributes to immune escape variants. In addition, several targetable molecules (eg, Notch or EZH2) could be exploited in view of improving immune responses in patients with CLL, which warrants further in-depth investigation.

The quantity and quality of cropland are the key to ensuring the sustainable development of national agriculture. Remote sensing technology can accurately and timely detect the surface information, and objectively reflect the state and changes of the ground objects. Using high-resolution remote sensing images to accurately extract cropland is the basic task of precision agriculture. The traditional model of cropland semantic segmentation based on the deep learning network is to down-sample high-resolution feature maps to low resolution, and then restore from low-resolution feature maps to high-resolution ideas; that is, obtain low-resolution feature maps through a network, and then recover to high resolution by up-sampling or deconvolution. This will bring about the loss of features, and the segmented image will be more fragmented, without very clear and smooth boundaries. A new methodology for the effective and accurate semantic segmentation cropland of high spatial resolution remote sensing images is presented in this paper. First, a multi-temporal sub-meter cropland sample dataset is automatically constructed based on the prior result data. Then, a fully convolutional neural network combined with contextual feature representation (HRNet-CFR) is improved to complete the extraction of cropland. Finally, the initial semantic segmentation results are optimized by the morphological post-processing approach, and the broken spots are ablated to obtain the internal homogeneous cropland. The proposed method has been validated on the Jilin-1 data and Gaofen Image Dataset (GID) public datasets, and the experimental results demonstrate that it outperforms the state-of-the-art method in cropland extraction accuracy. We selected the comparison of Deeplabv3+ and UPerNet methods in GID. The overall accuracy of our approach is 92.03%, which is 3.4% higher than Deeplabv3+ and 5.12% higher than UperNet.

Chronic lymphocytic leukemia cells have an altered energy metabolism compared to normal B cells. While there is a growing understanding of the molecular heterogeneity of the disease, the extent of metabolic heterogeneity and its relation to molecular heterogeneity has not been systematically studied. Here, we assessed 11 bioenergetic features, primarily reflecting cell oxidative phosphorylation and glycolytic activity, in leukemic cells from 140 chronic lymphocytic leukemia patients using metabolic flux analysis. We examined these bioenergetic features for relationships with molecular profiles (including genetic aberrations, transcriptome and methylome profiles) of the tumors, their ex vivo responses to a panel of 63 compounds, and with clinical data. We observed that leukemic cells with mutated immunoglobulin variable heavy-chain show significantly lower glycolytic activity than cells with unmutated immunoglobulin variable heavy-chain. Accordingly, several key glycolytic genes (PFKP, PGAM1 and PGK1) were found to be down-regulated in samples harboring mutated immunoglobulin variable heavy-chain. In addition, 8q24 copy number gains, 8p12 deletions, 13q14 deletions and ATM mutations were identified as determinants of cellular respiration. The metabolic state of leukemic cells was associated with drug sensitivity; in particular, higher glycolytic activity was linked to increased resistance towards several drugs including rotenone, navitoclax, and orlistat. In addition, we found glycolytic capacity and glycolytic reserve to be predictors of overall survival (P

Feature-based remote sensing image registration methods have achieved great accomplishments. However, they have faced some limitations of applicability, automation, accuracy, efficiency, and robustness for large high-resolution remote sensing image registration. To address the above issues, we propose a novel instance segmentation based registration framework specifically for large-sized high-resolution remote sensing images. First, we design an instance segmentation model based on a convolutional neural network (CNN), which can efficiently extract fine-grained instances as the deep features for local area matching. Then, a feature-based method combined with the instance segmentation results is adopted to acquire more accurate local feature matching. Finally, multi-constraints based on the instance segmentation results are introduced to work on the outlier removal. In the experiments of high-resolution remote sensing image registration, the proposal effectively copes with the circumstance of the sensed image with poor positioning accuracy. In addition, the method achieves superior accuracy and competitive robustness compared with state-of-the-art feature-based methods, while being rather efficient.

The M2 subtype Acute Myeloid Leukemia (AML-M2) with t(8;21) represents an unmet challenge because of poor clinical outcomes in a sizable portion of patients. In this study,we report that FTY720 (Fingolimod), a sphingosine analogue and an FDA approved drug for treating of multiple sclerosis, shows antitumorigenic activity against the Kasumi-1 cell line, xenograft mouse models and leukemic blasts isolated from AML-M2 patients with t(8;21) translocation. Primary investigation indicated that FTY720 caused cell apoptosis through caspases and protein phosphatase 2A (PP2A) activation. Transcriptomic profiling further revealed that FTY720 treatment could upregulate AML1 target genes and interfere with genes involved in ceramide synthesis. Treatment with FTY720 led to the elimination of AML1-ETO oncoprotein and caused cell cycle arrest. More importantly, FTY720 treatment resulted in rapid and significant increase of pro-apoptotic ceramide levels, determined by high-performance liquid chromatography-electrospray ionization tandem mass spectrometry based lipidomic approaches. Structural simulation model had also indicated that the direct binding of ceramide to inhibitor 2 of PP2A (I2PP2A) could reactivate PP2A and cause cell death. This study demonstrates, for the first time, that accumulation of ceramide plays a central role in FTY720 induced cell death of AML-M2 with t(8;21). Targeting sphingolipid metabolism by using FTY720 may provide novel insight for the drug development of treatment for AML-M2 leukemia.

Protein arginine methyltransferase 1 (PRMT1), the major arginine asymmetric dimethylation enzyme in mammals, is emerging as a potential drug target for cancer and cardiovascular disease. Understanding the catalytic mechanism of PRMT1 will facilitate inhibitor design. However, detailed mechanisms of the methyl transfer process and substrate deprotonation of PRMT1 remain unclear. In this study, we present a theoretical study on PRMT1 catalyzed arginine dimethylation by employing molecular dynamics (MD) simulation and quantum mechanics/molecular mechanics (QM/MM) calculation. Ternary complex models, composed of PRMT1, peptide substrate, and S-adenosyl-methionine (AdoMet) as cofactor, were constructed and verified by 30-ns MD simulation. The snapshots selected from the MD trajectory were applied for the QM/MM calculation. The typical SN2-favored transition states of the first and second methyl transfers were identified from the potential energy profile. Deprotonation of substrate arginine occurs immediately after methyl transfer, and the carboxylate group of E144 acts as proton acceptor. Furthermore, natural bond orbital analysis and electrostatic potential calculation showed that E144 facilitates the charge redistribution during the reaction and reduces the energy barrier. In this study, we propose the detailed mechanism of PRMT1-catalyzed asymmetric dimethylation, which increases insight on the small-molecule effectors design, and enables further investigations into the physiological function of this family.

The histone acetylation of post-translational modification can be highly dynamic and play a crucial role in regulating cellular proliferation, survival, differentiation and motility. Of the enzymes that mediate post-translation modifications, the GCN5 of the histone acetyltransferase (HAT) proteins family that add acetyl groups to target lysine residues within histones, has been most extensively studied. According to the mechanism studies of GCN5 related proteins, two key processes, deprotonation and acetylation, must be involved. However, as a fundamental issue, the structure of hGCN5/AcCoA/pH3 remains elusive. Although biological experiments have proved that GCN5 mediates the acetylation process through the sequential mechanism pathway, a dynamic view of the catalytic process and the molecular basis for hGCN5/AcCoA/pH3 are still not available and none of theoretical studies has been reported to other related enzymes in HAT family. To explore the molecular basis for the catalytic mechanism, computational approaches including molecular modeling, molecular dynamic (MD) simulation and quantum mechanics/molecular mechanics (QM/MM) simulation were carried out. The initial hGCN5/AcCoA/pH3 complex structure was modeled and a reasonable snapshot was extracted from the trajectory of a 20 ns MD simulation, with considering post-MD analysis and reported experimental results. Those residues playing crucial roles in binding affinity and acetylation reaction were comprehensively investigated. It demonstrated Glu80 acted as the general base for deprotonation of Lys171 from H3. Furthermore, the two-dimensional QM/MM potential energy surface was employed to study the sequential pathway acetylation mechanism. Energy barriers of addition-elimination reaction in acetylation obtained from QM/MM calculation indicated the point of the intermediate ternary complex. Our study may provide insights into the detailed mechanism for acetylation reaction of GCN5, and has important implications for the discovery of regulators against GCN5 enzymes and related HAT family enzymes.

Lysine-specific demethylase 1 (LSD1), the first identified histone demethylase, is a flavin-dependent amine oxidase which specifically demethylates mono- or dimethylated H3K4 and H3K9 via a redox process. It participates in a broad spectrum of biological processes and is of high importance in cell proliferation, adipogenesis, spermatogenesis, chromosome segregation and embryonic development. To date, as a potential drug target for discovering anti-tumor drugs, the medical significance of LSD1 has been greatly appreciated. However, the catalytic mechanism for the rate-limiting reductive half-reaction in demethylation remains controversial. By employing a combined computational approach including molecular modeling, molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations, the catalytic mechanism of dimethylated H3K4 demethylation by LSD1 was characterized in details. The three-dimensional (3D) model of the complex was composed of LSD1, CoREST, and histone substrate. A 30-ns MD simulation of the model highlights the pivotal role of the conserved Tyr761 and lysine-water-flavin motif in properly orienting flavin adenine dinucleotide (FAD) with respect to substrate. The synergy of the two factors effectively stabilizes the catalytic environment and facilitated the demethylation reaction. On the basis of the reasonable consistence between simulation results and available mutagenesis data, QM/MM strategy was further employed to probe the catalytic mechanism of the reductive half-reaction in demethylation. The characteristics of the demethylation pathway determined by the potential energy surface and charge distribution analysis indicates that this reaction belongs to the direct hydride transfer mechanism. Our study provides insights into the LSD1 mechanism of reductive half-reaction in demethylation and has important implications for the discovery of regulators against LSD1 enzymes.