Topological Isomerism in Three-Dimensional Covalent Organic Frameworks.

Although isomerism is a typical and significant phenomenon in organic chemistry, it is rarely found in covalent organic framework (COF) materials. Herein, for the first time, we report a controllable synthesis of topological isomers in three-dimensional COFs via a distinctive tetrahedral building unit under different solvents. Based on this strategy, both isomers with a dia or qtz net (termed JUC-620 and JUC-621) have been obtained, and their structures are determined by combining powder X-ray diffraction and transmission electron microscopy. Remarkably, these architectures show a distinct difference in their porous features; for example, JUC-621 with a qtz net exhibits permanent mesopores (up to ∼23 Å) and high surface area (∼2060 m2 g-1), which far surpasses those of JUC-620 with a dia net (pore size of ∼12 Å and surface area of 980 m2 g-1). Furthermore, mesoporous JUC-621 can remove dye molecules efficiently and achieves excellent iodine adsorption (up to 6.7 g g-1), which is 2.3 times that of microporous JUC-620 (∼2.9 g g-1). This work thus provides a new way for constructing COF isomers and promotes structural diversity and promising applications of COF materials.

Transcriptome Screening of Long Noncoding RNAs and Their Target Protein-Coding Genes Unmasks a Dynamic Portrait of Seed Coat Coloration Associated with Anthocyanins in Tibetan Hulless Barley.

Many plants have the capability to accumulate anthocyanins for coloration, and anthocyanins are advantageous to human health. In the case of hulless barley (Hordeum vulgare L. var. nudum), investigation into the mechanism of anthocyanin formation is limited to the level of protein-coding genes (PCGs). Here, we conducted a comprehensive bioinformatics analysis to identify a total of 9414 long noncoding RNAs (lncRNAs) in the seed coats of purple and white hulless barley along a developmental gradient. Transcriptome-wide profiles of lncRNAs documented several properties, including GC content fluctuation, uneven length, a diverse range of exon numbers, and a wide variety of transcript classifications. We found that certain lncRNAs in hulless barley possess detectable sequence conservation with Hordeum vulgare and other monocots. Furthermore, both differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) were concentrated in the later seed development stages. On the one hand, DElncRNAs could potentially cis-regulate DEPCGs associated with multiple metabolic pathways, including flavonoid and anthocyanin biosynthesis in the late milk and soft dough stages. On the other hand, there was an opportunity for trans-regulated lncRNAs in the color-forming module to affect seed coat color by upregulating PCGs in the anthocyanin pathway. In addition, the interweaving of hulless barley lncRNAs and diverse TFs may function in seed coat coloration. Notably, we depicted a dynamic portrait of the anthocyanin synthesis pathway containing hulless barley lncRNAs. Therefore, this work provides valuable gene resources and more insights into the molecular mechanisms underlying anthocyanin accumulation in hulless barley from the perspective of lncRNAs, which facilitate the development of molecular design breeding in crops.

Groundwater potential assessment using GIS-based ensemble learning models in Guanzhong Basin, China.

Groundwater plays a crucial role in sustaining industrial and agricultural production and meeting the water demands of the growing population in the semi-arid Guanzhong Basin of China. The objective of this study was to evaluate the groundwater potential of the region through the use of GIS-based ensemble learning models. Fourteen factors, including landform, slope, slope aspect, curvature, precipitation, evapotranspiration, distance to fault, distance to river, road density, topographic wetness index, soil type, lithology, land cover, and normalized difference vegetation index, were considered. Three ensemble learning models, namely random forest (RF), extreme gradient boosting (XGB), and local cascade ensemble (LCE), were trained and cross-validated using 205 sets of samples. The models were then applied to predict groundwater potential in the region. The XGB model was found to be the best, with an area under the curve (AUC) value of 0.874, followed by the RF model with an AUC of 0.859, and the LCE model with an AUC of 0.810. The XGB and LCE models were more effective than the RF model in discriminating between areas of high and low groundwater potential. This is because most of the RF model's prediction outcomes were concentrated in moderate groundwater potential areas, indicating that RF is less decisive when it comes to binary classification. In areas predicted to have very high and high groundwater potential, the proportions of samples with abundant groundwater were 33.6%, 69.31%, and 52.45% for RF, XGB, and LCE, respectively. In contrast, in areas predicted to have very low and low groundwater potential, the proportions of samples without groundwater were 57.14%, 66.67%, and 74.29% for RF, XGB, and LCE, respectively. The XGB model required the least amount of computational resources and achieved the highest accuracy, making it the most practical option for predicting groundwater potential. The results can be useful for policymakers and water resource managers in promoting the sustainable use of groundwater in the Guanzhong Basin and other similar regions.

Transcriptomic and alternative splicing analyses provide insights into the roles of exogenous salicylic acid ameliorating waxy maize seedling growth under heat stress.

BACKGROUND: Salicylic acid (SA) is a phytohormone which works to regulate the abiotic stress response of plants. However, the molecular mechanism by which SA mediates heat tolerance in waxy maize (Zea mays L. sinsensis Kulesh) remains unknown. RESULTS: Two varieties of waxy maize seedlings, heat-tolerant 'Yunuo7' (Y7) and heat-sensitive 'Suyunuo5' (S5), were pretreated with SA prior to heat stress (HTS). After treatment, physiological and transcriptomic changes were analyzed. Compared with HTS, the exogenous application of SA enhanced the shoot dry weight, the activities of antioxidant enzymes (e.g., SOD, POD, CAT and APX), and the concentration of endogenous phytohormones (e.g., SA, ABA, IAA, GA3), while decreased the MDA content. Transcriptome analysis showed that the number of differentially expressed genes (DEGs) identified in the control (CK) vs HTS and HTS vs HTS + SA comparisons were more in S5 than in Y7. HTS induced the downregulation of genes involved in photosynthesis and the upregulation of genes encoding heat shock transcription factors (HSFs) and heat shock proteins (HSPs). Compared with HTS, SA pretreatment reversed the expression of 5 photosynthesis-related genes, 26 phytohormone-related genes, and all genes encoding HSFs and HSPs in S5. Furthermore, the number of alternative splicing (AS) events increased under HTS treatment for both varieties, while decreased under SA pretreatment of S5. Differentially spliced genes (DSGs) showed little overlap with DEGs, and DEGs and DSGs differed significantly in functional enrichment. CONCLUSIONS: Physiological and transcriptional together indicated that HTS and SA pretreatment had a greater effect on S5 than Y7. Additionally, it appears that transcriptional regulation and AS work synergistically to enhance thermotolerance in heat-sensitive waxy maize. Our study revealed the regulatory effects and underlying molecular mechanisms of SA on waxy maize seedling under HTS.

E3 ubiquitin ligases STUB1/CHIP contributes to the Th17/Treg imbalance via the ubiquitination of aryl hydrocarbon receptor in rheumatoid arthritis.

STIP1-homologous U-Box containing protein 1 (STUB1) is involved in the development of immune pathologies and the regulation of T cell. However, the potential role of STUB1 in the pathogenesis of rheumatoid arthritis (RA), especially in the regulation of T cells, remains elusive. Here we show that STUB1 promotes the imbalance of Th17/Treg cells through non-degradative ubiquitination of aryl hydrocarbon receptor (AHR). Using Western blot and flow cytometry analysis, we observe that the level of STUB1 was increased in RA patients compared with healthy controls. In particular, the expression of STUB1 protein was different in Th17 cells and Treg cells of RA patients. We also demonstrated that STUB1 facilitates Th17/Treg imbalance by up- or downregulating the expression of STUB1. In a subsequent series of in vitro experiments, we revealed that STUB1 promoted the imbalance of Th17 and Treg cells through non-degradative ubiquitination of AHR. Both knockdown of the AHR expression by siRNA and assays of CYP1A1 enzymatic activity by ethoxyresorufin-O-deethylase (EROD) supported this conclusion. Furthermore, we explored the ubiquitination sites of AHR responsible for STUB1-mediated ubiquitination and revealed that STUB1 promotes ubiquitination of AHR via K63 chains. Together, STUB1 may induce the imbalance of Th17/Treg cells via ubiquitination of AHR and serve as a potential therapeutic target for RA.

Systematic Identification of Methyl Jasmonate-Responsive Long Noncoding RNAs and Their Nearby Coding Genes Unveils Their Potential Defence Roles in Tobacco BY-2 Cells.

Long noncoding RNAs (lncRNAs) are distributed in various species and play critical roles in plant growth, development, and defence against stimuli. However, the lncRNA response to methyl jasmonate (MeJA) treatment has not been well characterized in Nicotiana tabacum Bright Yellow-2 (BY-2) cells, and their roles in plant defence remain elusive. Here, 7848 reliably expressed lncRNAs were identified in BY-2 cells, of which 629 differentially expressed (DE) lncRNAs were characterized as MeJA-responsive lncRNAs. The lncRNAs in BY-2 cells had a strong genus specificity in Nicotiana. The combined analysis of the cis-regulated lncRNAs and their target genes revealed the potential up- and downregulated target genes that are responsible for different biological functions and metabolic patterns. In addition, some lncRNAs for response-associated target genes might be involved in plant defence and stress resistance via their MeJA- and defence-related cis-regulatory elements. Moreover, some MeJA-responsive lncRNA target genes were related to quinolinate phosphoribosyltransferase, lipoxygenases, and endopeptidase inhibitors, which may contribute to nicotine synthesis and disease and insect resistance, indicating that MeJA-responsive lncRNAs regulate nicotine biosynthesis and disease resistance by regulating their potential target genes in BY-2 cells. Therefore, our results provide more targets for genetically engineering the nicotine content and plant defence in tobacco plants.

Deep Neural Networks Offer Morphologic Classification and Diagnosis of Bacterial Vaginosis.

Bacterial vaginosis (BV) is caused by the excessive and imbalanced growth of bacteria in vagina, affecting 30 to 50% of women. Gram staining followed by Nugent scoring based on bacterial morphotypes under the microscope is considered the gold standard for BV diagnosis; this method is often labor-intensive and time-consuming, and results vary from person to person. We developed and optimized a convolutional neural network (CNN) model and evaluated its ability to automatically identify and classify three categories of Nugent scores from microscope images. The CNN model was first established with a panel of microscopic images with Nugent scores determined by experts. The model was trained by minimizing the cross-entropy loss function and optimized by using a momentum optimizer. The separate test sets of images collected from three hospitals were evaluated by the CNN model. The CNN model consisted of 25 convolutional layers, 2 pooling layers, and a fully connected layer. The model obtained 82.4% sensitivity and 96.6% specificity with the 5,815 validation images when altered vaginal flora and BV were considered the positive samples, which was better than the rates achieved by top-level technologists and obstetricians in China. The capability of our model for generalization was so strong that it exhibited 75.1% accuracy in three categories of Nugent scores on the independent test set of 1,082 images, which was 6.6% higher than the average of three technologists, who are hold bachelor's degrees in medicine and are qualified to make diagnostic decisions. When three technologists ran one specimen in triplicate, the precision of three categories of Nugent scores was 54.0%. One hundred three samples diagnosed by two technologists on different days showed a repeatability of 90.3%. The CNN model outperformed human health care practitioners in terms of accuracy and stability for three categories of Nugent score diagnosis. The deep learning model may offer translational applications in automating diagnosis of bacterial vaginosis with proper supporting hardware.

Management of Eisenmenger syndrome by cardiac defect closure combined bilateral lung transplantation with intraoperative venoarterial ECMO support.

BACKGROUND: Optimal surgical treatment for Eisenmenger syndrome in adult congenital heart disease remains in debate. CASE REPORT: We report a case of a 22-year-old female with Eisenmenger syndrome secondary to ventricular septum defect (VSD), who underwent cardiac defect closure combined with bilateral lung transplantation in our center. The patient had an uncorrected peri-membranous VSD and subsequently developed severe pulmonary hypertension. We patched the defect under cardiopulmonary bypass. Then a sequential bilateral lung transplantation was performed with venoarterial extracorporeal membrane oxygenation support. The patient had a good postoperative recovery and remained well at follow-up at 1 year. To conclude, cardiac defect repair combined bilateral lung transplantation may be a feasible option for selected patients with Eisenmenger Syndrome.

The first lutetacyclopentadienes: synthesis, structure, and diversified insertion/C-H activation reactivity.

The first well-defined lutetacyclopentadienes are synthesised from pentamethylcyclopentadienyl lithium (Cp*Li), 1,4-dilithio-1,3-butadienes, and LuCl3. The lutetacyclopentadiene shows excellent reactivity towards some small molecules, such as pivalaldehyde, Se, carbon dioxide, and isonitrile to efficiently construct 3-, 5-, 7-, 8-, and 9-membered rare-earth metallacycles. Both monoinsertion and double-insertion of two Lu-Csp2 bonds are observed. Specially, the reaction between lutetacyclopentadiene and isonitrile afforded [3,5,5]-fused metallacycles. The distinguished reactivity can be attributed to the highly ionic character and the cooperative reactivity of two Lu-Csp2 bonds.

Half-Sandwich Complexes of Dy(III): A Janus-Motif with Facile Tunability of Magnetism.

Three half-sandwich organometallics [(Cp(R))Dy(DBM)2(THF)]·solvent [Cp(R) = Cp* (1Dy, Cp* = C5Me5), Cp(4PrPh) (2Dy, Cp(4PrPh) = C5Pr4Ph), Cp' (3Dy, Cp' = C5Me4TMS, solvent = THF), DBM(-) = dibenzoylmethanoate anion, THF = tetrahydrofuran, TMS = trimethylsilyl] with a Janus structural motif, where the ligands of DBM(-) and [Cp(R)](-) are widely used in Dy(III)/ß-diketonate and Ln(III)/cyclopentadienyl systems, were synthesized, structurally and magnetically characterized, and theoretically investigated. Single-crystal structural analysis reveals that the three complexes crystallize in the same space group P21/c. All the molecules display slow magnetic relaxation in the absence of an applied magnetic field, and the magnetic hysteresis loops of 2Dy and 3Dy can be observed under a magnetic field sweep rate of 10 Oe/s, indicating all three complexes are single-ion magnets (SIMs). The modifications of the Cp-ring lead to the distinct increment of the energy barrier from 46 K (1Dy) to 76 K (2Dy) to 320 K (3Dy). Ab initio calculations show that the ground Kramers doublet is strongly axial with gz approaching the value of 20 expected for the pure MJ = ±15/2 state, and the magnetic anisotropy axes for three complexes share a similar orientation which is perpendicular to the molecular pseudosymmetric axis. Electrostatic analyses confirm the magnetic anisotropy orientations and reveal that proper charge distribution of the coordination sphere (including the first and second) around Dy(III) ion enhances the magnetic anisotropy. Further investigation of the relaxation mechanisms suggests the energy barrier should be carefully used to evaluate single-ion magnets if Raman process is dominant in the low temperature range.

Spatial predictions of groundwater potential using automated machine learning (AutoML): a comparative study of feature selection and training sample size in Qinghai Province, China.

Predicting groundwater potential is crucial for identifying the spatial distribution of groundwater in a region. It serves as an essential guide for the development, utilization, and protection of groundwater resources. Previous studies have primarily emphasized finding the most accurate prediction model for groundwater potential while giving less attention to the selection of training features and sample sizes. This study aims to predict groundwater potential within Qinghai Province using automated machine learning technology and assess the influence of sample sizes and feature selection on prediction accuracy. Sixteen groundwater conditioning factors were categorized into categorical and numerical variables. Four feature selection modes were utilized as input in training the model. The results indicated that, except for correlations between evaporation and landforms (- 0.8) and precipitation and normalized difference vegetation index (0.8), the Pearson correlation coefficients among the remaining sixteen factors were ≤ 0.5 or ≥ - 0.5. The models XGB-ALL, RF-Entropy, ET-CRITIC, and XGB-PCA yielded accuracy scores of 0.783, 0.685, 0.745, and 0.703, and area under curve (AUC) of 0.819, 0.724, 0.779, and 0.747, respectively. If enough samples are available with the tree model, an increased number of features can improve prediction accuracy. The principal component analysis method showed difficulty in reducing the dimensionality of the input space, while the Entropy method proved efficient. The accuracy and AUC value of the prediction model improved with an increasing number of samples. Training with 8 features and 200 data points achieved an accuracy of 0.745, sufficient to evaluate regional groundwater potential. As for training with 600 samples, the model's performance accuracy rose to 0.9, enabling precise groundwater potential prediction. The outputs of this research can provide decision-makers in groundwater resource management in Qinghai Province with crucial theoretical and practical support. The lessons learned can have future applications in similar situations.

Endovascular Interventional Procedure is a Significant Risk Factor of Postsurgical Gout: A Retrospective Cohort Study.

INTRODUCTION: Surgery is a risk factor for flares in people with gout. However, gout flares after endovascular interventional procedures are not well understood. The aim of this study was to evaluate the clinical features and risk factors for gout flare that develop during the postsurgical period including endovascular procedures. METHODS: We enrolled 222 patients with gout who developed postsurgical gout and 196 controls who had histories of gout but did not develop gout flares after surgery within 20 days. Clinical characteristics of patients who developed a postsurgical gout flare were compared with the controls. RESULTS: The rate of endovascular interventional procedures was higher (38.74% vs. 13.48%, P < 0.001) in the flare group than in the no-flare group and lower in orthopedic surgery (13.96% vs. 41.84%, P < 0.001). The Cox model showed that endovascular interventional procedures (HR, hazard ratio 1.752; 95% CI, confidence interval 1.126-2.724, P = 0.013) and presurgical uric acid levels of ≥ 7 mg/dl (HR 1.489; 95% CI 1.081-2.051, P = 0.015) were significantly associated with increased risks of postsurgical gout flare, and taking colchicine before surgery were significantly associated with decreased risk of postsurgical gout flare (HR 0.264; 95% CI 0.090-0.774, P = 0.015). There was no significant difference in the types of endovascular interventional procedures between the flare group and the no-flare group. CONCLUSIONS: Patients with a history of gout should be more alert to recurrence gout flares after endovascular interventional procedures. Adequate presurgical control of serum uric acid levels and/or prophylactic treatment with colchicine will help prevent gout flares during the postsurgical period.

Effects of exogenous salicylic acid on starch physicochemical properties and in vitro digestion under heat stress during the grain-filling stage in waxy maize.

Waxy maize starch serves as a pivotal component in global food processing and industrial applications, while high temperature (HT) during the grain-filling stage seriously affects its quality. Salicylic acid (SA) has been recognized for its role in enhancing plant heat resistance. Nonetheless, its regulatory effect on the quality of waxy maize starch under HT conditions remains unclear. In this study, two waxy maize varieties, JKN2000 (heat-tolerant) and SYN5 (heat-sensitive) were treated with SA after pollination and then subjected to HT during the grain-filling stage to explore the effect of SA on grain yield and starch quality. The results indicate that exogenous SA under HT treatment led to an increase in kernel weight and starch content in both varieties. Moreover, SA reduced the HT-induced holes on the surfaces of starch granules, enlarged the starch granule size, elevated the amylopectin branching degree, and reduced amylopectin average chain length. Consequently, improvements of pasting viscosity and the decrease of retrogradation percentage of starch were observed with SA under HT. Exogenous SA reduced HT-induced rapidly digestible starch content in SYN5, but had no significant effect on that in JKN2000. In summary, SA pretreatment effectively alleviated the detrimental effects of HT on starch pasting and thermal properties of waxy maize.

Three-dimensional covalent organic frameworks with nia nets for efficient separation of benzene/cyclohexane mixtures.

The synthesis of three-dimensional covalent organic frameworks with highly connected building blocks presents a significant challenge. In this study, we report two 3D COFs with the nia topology, named JUC-641 and JUC-642, by introducing planar hexagonal and triangular prism nodes. Notably, our adsorption studies and breakthrough experiments reveal that both COFs exhibit exceptional separation capabilities, surpassing previously reported 3D COFs and most porous organic polymers, with a separation factor of up to 2.02 for benzene and cyclohexane. Additionally, dispersion-corrected density functional theory analysis suggests that the good performance of these 3D COFs can be attributed to the incorporation of highly aromatic building blocks and the presence of extensive pore structures. Consequently, this research not only expands the diversity of COFs but also highlights the potential of functional COF materials as promising candidates for environmentally-friendly separation applications.

Transcriptomic Profiles of Long Noncoding RNAs and Their Target Protein-Coding Genes Reveals Speciation Adaptation on the Qinghai-Xizang (Tibet) Plateau in Orinus.

Long noncoding RNAs (lncRNAs) are RNA molecules longer than 200 nt, which lack the ability to encode proteins and are involved in multifarious growth, development, and regulatory processes in plants and mammals. However, the environmental-regulated expression profiles of lncRNAs in Orinus that may associated with their adaptation on the Qinghai-Xizang (Tibet) Plateau (QTP) have never been characterized. Here, we utilized transcriptomic sequencing data of two Orinus species (O. thoroldii and O. kokonoricus) to identify 1624 lncRNAs, including 1119 intergenic lncRNAs, 200 antisense lncRNAs, five intronic lncRNAs, and 300 sense lncRNAs. In addition, the evolutionary relationships of Orinus lncRNAs showed limited sequence conservation among 39 species, which implied that Orinus-specific lncRNAs contribute to speciation adaptation evolution. Furthermore, considering the cis-regulation mechanism, from 286 differentially expressed lncRNAs (DElncRNAs) and their nearby protein coding genes (PCGs) between O. thoroldii and O. kokonoricus, 128 lncRNA-PCG pairs were obtained in O. thoroldii, whereas 92 lncRNA-PCG pairs were obtained in O. kokonoricus. In addition, a total of 19 lncRNA-PCG pairs in O. thoroldii and 14 lncRNA-PCG pairs in O. kokonoricus were found to participate in different biological processes, indicating that the different expression profiles of DElncRNAs between O. thoroldii and O. kokonoricus were associated with their adaptation at different elevations on the QTP. We also found several pairs of DElncRNA nearby transcription factors (TFs), indicating that these DElncRNAs regulate the expression of TFs to aid O. thoroldii in adapting to the environment. Therefore, this work systematically identified a series of lncRNAs in Orinus, laying the groundwork for further exploration into the biological function of Orinus in environmental adaptation.

Tumor immunity: A brief overview of tumor­infiltrating immune cells and research advances into tumor­infiltrating lymphocytes in gynecological malignancies (Review).

Tumor immunity is a promising topic in the area of cancer therapy. The 'soil' function of the tumor microenvironment (TME) for tumor growth has attracted wide attention from scientists. Tumor-infiltrating immune cells in the TME, especially the tumor-infiltrating lymphocytes (TILs), serve a key role in cancer. Firstly, relevant literature was searched in the PubMed and Web of Science databases with the following key words: 'Tumor microenvironment'; 'TME'; 'tumor-infiltrating immunity cells'; 'gynecologic malignancies'; 'the adoptive cell therapy (ACT) of TILs'; and 'TIL-ACT' (https://pubmed.ncbi.nlm.nih.gov/). According to the title and abstract of the articles, relevant items were screened out in the preliminary screening. The most relevant selected items were of two types: All kinds of tumor-infiltrating immune cells; and advanced research on TILs in gynecological malignancies. The results showed that the subsets of TILs were various and complex, while each subpopulation influenced each other and their effects on tumor prognosis were diverse. Moreover, the related research and clinical trials on TILs were mostly concentrated in melanoma and breast cancer, but relatively few focused on gynecological tumors. In conclusion, the present review summarized the biological classification of TILs and the mechanisms of their involvement in the regulation of the immune microenvironment, and subsequently analyzed the development of tumor immunotherapy for TILs. Collectively, the present review provides ideas for the current treatment dilemma of gynecological tumor immune checkpoints, such as adverse reactions, safety, personal specificity and efficacy.

Mechanistic study on the cleavage and reorganization of C(sp3)-H and C=N bonds in carbodiimides: synthesis of 1,2-dihydrothiopyrimidines and 2,3-dihydropyrimidinthiones through four-component coupling.

This study sheds light on the cleavage and reorganization of C(sp(3))-H and C=N bonds of carbodiimides in a three-component reaction of terminal alkynes, sulfur, and carbodiimides by a combination of methods including 1) isolation and X-ray analysis of six-membered-ring lithium species 2-S, 2) trapping of the oxygen-analogues (B-O and D-O) of both four-membered-ring intermediate B-S and ring-opening intermediate D-S, 3) deuterium labeling studies, and 4) theoretical studies. These results show that 1) the reaction rate-determining step is [2+2] cycloaddition, 2) the C=N bond cleavage takes place before C(sp(3))-H bond cleavage, 3) the hydrogen attached to C6 in 2-S originates from the carbodiimide, and 4) three types of new aza-heterocycles, such as 1,2-dihydrothiopyrimidines, N-acyl 2,3-dihydropyrimidinthiones, and 1,2-dihydropyrimidinamino acids are constructed efficiently based on 2-S. All results strongly support the idea that the reaction proceeds through [2+2] cycloaddition/4π electrocyclic ring-opening/1,5-H shift/6π electrocyclic ring-closing as key steps. The research strategy on the synthesis, isolation, and reactivity investigation of important intermediates in metal-mediated reactions not only helps achieve an in-depth understanding of reaction mechanisms but also leads to the discovery of new synthetically useful reactions based on the important intermediates.

Recognition of the Subtypes Classification and Diagnostic Signature Based on RNA N6-Methyladenosine Regulators in Recurrent Spontaneous Abortion.

Recurrent spontaneous abortion (RSA) is a common reproductive disease in female patients that seriously affects the quality of life of patients. N6-methyladenosine (m6A), as the most common modification, plays an important role in various biological behaviors; however, the relationship between m6A and RSA is still unknown. In the present study, we utilized RNA sequencing data and clinical information of RSA patients and normal women in the GEO database to identify the expression profiles of m6A regulators in RSA. Based on the m6A regulators' expression profiles, we constructed a random forest model consisting of 4 genes to predict the prevalence of RSA patients, including FMR1, METTL14, LRPPRC, and RBMX. The predictive performance of the nomogram was constructed and validated. Not only that, consensus clustering was performed to divide RSA patients into 3 clusters based on the expression of m6A regulators and calculated the m6A scores and immune infiltration of patients in different clusters. It was found that the TH1-type immune response was dominant in the A cluster, the B-type immune activity was poor, and the C cluster was the strongest. In addition, on the basis of m6A typing, we further used the differentially expressed genes between clusters to perform consensus clustering verification, and the results were consistent with the previous findings. In conclusion, the m6A regulators played an indispensable role in the occurrence of RSA, and the m6A-based typing could effectively identify the immune characteristics of different RSA patients to a certain extent, providing a new direction and strategy for the diagnosis and treatment of RSA patients.

The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin.

Groundwater is a vital resource in arid areas that sustains local industrial development and environmental preservation. Mapping groundwater potential zones and determining high-potential regions are essential for the responsible use of the local groundwater resource. When utilizing machine learning or deep learning algorithms to forecast groundwater potential in arid areas, difficulties such as inaccurate and overfitting predictions might occur due to a shortage of borehole samples. In this study, a database of groundwater conditioning factors with a size of 275,157 × 9 was created in the Qaidam Basin, and 85 known borehole samples were collected. The groundwater potential was evaluated using a combination of rank sum ratio (RSR), projection pursuit regression (PPR) and random forest (RF) algorithms, resulting in four models: PPR, RSR-PPR, RSR-RF, and RF. Results indicated that the groundwater potential was higher in mountainous regions surrounding the Qaidam Basin and decreased progressively towards the central and northwestern regions where most industries and facilities are located. The two primary factors, according to the PPR and RF models, were evapotranspiration (0.246, 0.225) and landform (0.176, 0.294). In terms of their ability to accurately forecast the borehole samples, the four models ranked as follows: RF > RSR-RF > RSR-PPR > PPR. The accuracy of the four models in the low-potential area was 0.73 (PPR), 0.60 (RSR-PPR), 0.87 (RSR-RF), and 0.80 (RF), respectively. However, the RF model showed overfitting due to a lack of samples, especially in high-potential regions, which limits its applicability. The RSR-RF method was applied directly to evaluate the entire factor database, avoiding the risk of overfitting caused by a limited number of training samples. The results demonstrate that the RSR-RF model is effective for classifying groundwater potential types in samples and mapping groundwater potential of the study area. This research presents a novel approach for groundwater potential predictions in areas with insufficient sample sizes, providing a reference for policymakers and researchers.