Value of spectral parameters in the differential diagnosis of benign and malignant breast nodules in non-enhanced chest CT.

Background: Dual-layer spectral computed tomography (DSCT) is capable of acquiring both conventional and spectral images during one routine scan, and is widely used for the quantitative and qualitative analyses of substances, differential diagnosis, and disease staging. However, limited research has been conducted on its performance in the differential diagnosis of benign and malignant breast nodules using non-enhanced scans. This study aimed to assess the diagnostic performance of multiple quantitative parameters derived from non-enhanced DSCT in differentiating benign from malignant breast nodules. Methods: This retrospective cross-sectional study examined a total of 121 breast nodules from 114 patients (malignant group: n=68; benign group: n=53) identified during chest physical examination or routine admission for the treatment of breast diseases at The First Affiliated Hospital of Soochow University from March 2023 to December 2023. All the patients underwent DSCT scanning and pathological diagnosis. The DSCT quantitative parameters, including the effective atomic number (Zeff), computed tomography (CT) attenuation values at 40-70 keV, and the slope of the spectral Hounsfield unit curve (λHU), in non-enhanced images were measured. The λHU was calculated as follows: λHU = CT70 keV - CT40 keV/30 HU. Additionally, typical radiological features were analyzed. A DSCT parameter diagnostic model and a conventional CT diagnostic model were assessed using receiver operating characteristic (ROC) curves. The Delong test was used to assess and compare the diagnostic performance of each model. Results: The DSCT parameters, including the Zeff (P<0.001), λHU (P<0.001), and CT attenuation values at 40 keV (P<0.001) and 50 keV (P=0.001), as well as the presence of the lobular sign (P<0.001) and spicule sign (P<0.001), exhibited statistically significant differences between the benign and malignant groups. The logistic regression analysis revealed that the Zeff [odds ratio (OR): 9.22; 95% confidence interval (CI): 2.11-40.35; P=0.003], λHU (OR: 0.64; 95% CI: 0.52-0.79; P<0.001), 40 keV CT attenuation value (OR: 8.69; 95% CI: 3.28-23.06; P<0.001), 50 keV CT attenuation value (OR: 0.01; 95% CI: 0.001-0.07; P<0.001), and lobular sign (OR: 3.95; 95% CI: 1.52-10.31; P=0.005) were independent predictors of malignancy. Compared to the benign group, the malignant group had a higher likelihood of presenting with the lobular sign and higher Zeff values but lower λHU values. The ROC curve indicated that the Zeff had the highest diagnostic efficacy [area under the curve (AUC) of the ROC =0.792, 95% CI: 0.71-0.87]. Further, the DSCT parameter diagnostic model had improved diagnostic efficacy with an AUC of 0.899 (95% CI: 0.84-0.96), which was higher than the AUC of the conventional CT diagnostic model (AUC =0.796, 95% CI: 0.72-0.87). The Delong test revealed a statistically significant difference between these two models (P=0.04). Conclusions: DSCT parameters derived from non-enhanced DSCT images, such as the Zeff value and λHU, can be used to differentiate benign and malignant breast nodules, and the differential diagnosis efficacy of the DSCT parameters is higher than that of conventional CT parameters.

Versatile and efficient mammalian genome editing with Type I-C CRISPR System of Desulfovibrio vulgaris.

CRISPR-Cas tools for mammalian genome editing typically rely on single Cas9 or Cas12a proteins. While type I CRISPR systems in Class I may offer greater specificity and versatility, they are not well-developed for genome editing. Here, we present an alternative type I-C CRISPR system from Desulfovibrio vulgaris (Dvu) for efficient and precise genome editing in mammalian cells and animals. We optimized the Dvu type I-C editing complex to generate precise deletions at multiple loci in various cell lines and pig primary fibroblast cells using a paired PAM-in crRNA strategy. These edited pig cells can serve as donors for generating transgenic cloned piglets. The Dvu type I-C editor also enabled precise large fragment replacements with homology-directed repair. Additionally, we adapted the Dvu-Cascade effector for cytosine and adenine base editing, developing Dvu-CBE and Dvu-ABE systems. These systems efficiently induced C-to-T and A-to-G substitutions in human genes without double-strand breaks. Off-target analysis confirmed the high specificity of the Dvu type I-C editor. Our findings demonstrate the Dvu type I-C editor's potential for diverse mammalian genome editing applications, including deletions, fragment replacement, and base editing, with high efficiency and specificity for biomedicine and agriculture.

One-stage anammox and thiocyanate-driven autotrophic denitrification for simultaneous removal of thiocyanate and nitrogen: Pathway and mechanism.

The coupled process of anammox and reduced-sulfur driven autotrophic denitrification can simultaneously remove nitrogen and sulfur from wastewater, while minimizing energy consumption and sludge production. However, the research on the coupled process for removing naturally toxic thiocyanate (SCN-) is limited. This work successfully established and operated a one-stage coupled system by co-cultivating mature anammox and SCN--driven autotrophic denitrification sludge in a single reactor. In this one-stage coupled system, the average total nitrogen removal efficiency was 89.68±3.33 %, surpassing that of solo anammox (81.80±2.10 %) and SCN--driven autotrophic denitrification (85.20±1.54 %). Moreover, the average removal efficiency of SCN- reached 99.50±3.64 %, exceeding that of solo SCN--driven autotrophic denitrification (98.80±0.65 %). The results of the 15N stable isotope tracer labeling experiment revealed the respective reaction rates of anammox and denitrification as 106.38±10.37 µmol/L/h and 69.07±8.07 µmol/L/h. By analyzing metagenomic sequencing data, Thiobacillus_denitrificans was identified as the primary contributor to SCN- degradation in this coupled system. Furthermore, based on the comprehensive analysis of nitrogen and sulfur metabolic pathways, as well as the genes associated with SCN- degradation, it can be inferred that the cyanate (CNO) pathway was responsible for SCN- degradation. This work provided a deeper insight into coupling anammox with SCN--driven autotrophic denitrification in a one-stage coupled system, thereby contributing to the development of an effective approach for wastewater treatment involving both SCN- and nitrogen.

Optimistic growth of marginal region plantations under climate warming: Assessing divergent drought resilience.

Given the context of significant global warming and the intensification of extreme climate events in the last century, large-scale reforestation and afforestation have been recognized as effective strategies to mitigate the climate crisis. Since the 1970s, China has launched several afforestation programs aimed at regional ecological protection, playing an important role in reaching carbon neutrality by 2060. This study provided a detailed analysis of the growth suitability of the main planted conifers (Pinus sylvestris var. mongolica and Pinus tabulaeformis) and broadleaves (Populus spp., Robinia pseudoacacia) in the semi-arid northern China. We compared the radial growth trends of plantations and their responses to extreme droughts from 1980 to 2018. Growth of most plantations has significantly increased over time, but broadleaves showed recent growth reductions in the past decade, which may be related to tree age and reduced soil moisture. Nevertheless, under warmer climate scenarios, the growth of plantations is forecasted to continue increasing. Broadleaves showed a better post-drought recovery, probably linked to their anisohydric behavior, than conifers, which presented a better resistance to drought. Growth of conifers depended more on warmer temperature and better precipitation conditions during the growing season, whereas broadleaves mainly reacted to warm temperature. Additionally, pre-drought growth levels weakened resilience components, while post-drought precipitation compensated for drought-induced growth deficit. Growth and resilience were negatively related to tree age, while higher stand density reduced growth. This assessment and projections of growth and drought resilience indicate the sustainability of most plantations in semi-arid regions, but future warmer and drier conditions may lead to an uncertain future regarding forest health and reduce their carbon sink potential.

Orbital-dependent electron correlation in double-layer nickelate La3Ni2O7.

The latest discovery of high temperature superconductivity near 80 K in La3Ni2O7 under high pressure has attracted much attention. Many proposals are put forth to understand the origin of superconductivity. The determination of electronic structures is a prerequisite to establish theories to understand superconductivity in nickelates but is still lacking. Here we report our direct measurement of the electronic structures of La3Ni2O7 by high-resolution angle-resolved photoemission spectroscopy. The Fermi surface and band structures of La3Ni2O7 are observed and compared with the band structure calculations. Strong electron correlations are revealed which are orbital- and momentum-dependent. A flat band is formed from the Ni-3d z 2 orbitals around the zone corner which is ~ 50 meV below the Fermi level and exhibits the strongest electron correlation. In many theoretical proposals, this band is expected to play the dominant role in generating superconductivity in La3Ni2O7. Our observations provide key experimental information to understand the electronic structure and origin of high temperature superconductivity in La3Ni2O7.

Uppermost global tree elevations are primarily limited by low temperature or insufficient moisture.

The impact of anthropogenic global warming has induced significant upward dispersal of trees to higher elevations at alpine treelines. Assessing vertical deviation from current uppermost tree distributions to potential treeline positions is crucial for understanding ecosystem responses to evolving global climate. However, due to data resolution constraints and research scale limitation, comprehending the global pattern of alpine treeline elevations and driving factors remains challenging. This study constructed a comprehensive quasi-observational dataset of uppermost tree distribution across global mountains using Google Earth imagery. Validating the isotherm of mean growing-season air temperature at 6.6 ± 0.3°C as the global indicator of thermal treeline, we found that around two-thirds of uppermost tree distribution records significantly deviated from it. Drought conditions constitute the primary driver in 51% of cases, followed by mountain elevation effect which indicates surface heat (27%). Our analyses underscore the multifaceted determinants of global patterns of alpine treeline, explaining divergent treeline responses to climate warming. Moisture, along with temperature and disturbance, plays the most fundamental roles in understanding global variation of alpine treeline elevation and forecasting alpine treeline response to ongoing global warming.

Long-term response of the microbial community to the degradation of DOC released from Undaria pinnatifida.

With the aim to study the mechanism underlying the macroalgal carbon sequestration driven by microbes, we investigated the microbial community using metagenomics methods and its long-term degradation of dissolved organic carbon (DOC) derived from Undaria pinnatifida. It was observed that after removing U. pinnatifida, the concentration of the DOC decreased significantly (p < 0.05) within 4 days. Over a period of 120 days of degradation, the concentration of remaining DOC (26%) remained stable. The succession of microbial community corresponded to the three stages of DOC concentration variation. Moreover, the structure of microbes community and its metabolic function exhibited evident patterns of succession. The concentration of DOC was correlated negatively with the abundances of Planctomycetaceae (p < 0.01), and was correlated positively with the abundances of Roseobacteraceae and Rhodobacteraceae (p < 0.01). In addition, the metabolic pathways related to "Glycolysis/Gluconeogenesis", "Alanine, aspartate, and glutamate metabolism", "Citrate cycle (TCA cycle)" and "Tryptophan metabolism" was significantly correlated with the variations in DOC concentration (p < 0.05). These findings indicate that the variation in the DOC concentration was closely linked to the succession of Planctomycetaceae, Roseobacteraceae, Rhodobacteraceae, and the degradation of DOC derived from U. pinnatifida appeared to be influenced by metabolic functions.

Modulating functionally-distinct vagus nerve fibers using microelectrodes and kilohertz frequency electrical stimulation.

Modulation of functionally distinct nerve fibers with bioelectronic devices provides a therapeutic opportunity for various diseases. In this study, we began by developing a computational model including four major subtypes of myelinated fibers and one unmyelinated fiber. Second, we used an intrafascicular electrode to perform kHz-frequency electric stimulation to preferentially modulate a population of fibers. Our model suggests that fiber physical properties and electrode-to-fascicle distance severely impacts stimulus-response relationships. Large diameter fibers (Aα- and Aß-) were only minimally influenced by the fascicle size and electrode location, while smaller diameter fibers (Aδ-, B- and C-) indicated a stronger dependency.Clinical Relevance- Our findings support the possibility of selectively modulating functionally-distinct nerve fibers using electrical stimulation in a small, localized region. Our model provides an effective tool to design next-generation implantable devices and therapeutic stimulation strategies toward minimizing off-target effects.

Deep reinforcement learning-aided autonomous navigation with landmark generators.

Mobile robots are playing an increasingly significant role in social life and industrial production, such as searching and rescuing robots, autonomous exploration of sweeping robots, and so on. Improving the accuracy of autonomous navigation of mobile robots is a hot issue to be solved. However, traditional navigation methods are unable to realize crash-free navigation in an environment with dynamic obstacles, more and more scholars are gradually using autonomous navigation based on deep reinforcement learning (DRL) to replace overly conservative traditional methods. But on the other hand, DRL's training time is too long, and the lack of long-term memory easily leads the robot to a dead end, which makes its application in the actual scene more difficult. To shorten training time and prevent mobile robots from getting stuck and spinning around, we design a new robot autonomous navigation framework which combines the traditional global planning and the local planning based on DRL. Therefore, the entire navigation process can be transformed into first using traditional navigation algorithms to find the global path, then searching for several high-value landmarks on the global path, and then using the DRL algorithm to move the mobile robot toward the designated landmarks to complete the final navigation, which makes the robot training difficulty greatly reduced. Furthermore, in order to improve the lack of long-term memory in deep reinforcement learning, we design a feature extraction network containing memory modules to preserve the long-term dependence of input features. Through comparing our methods with traditional navigation methods and reinforcement learning based on end-to-end depth navigation methods, it shows that while the number of dynamic obstacles is large and obstacles are rapidly moving, our proposed method is, on average, 20% better than the second ranked method in navigation efficiency (navigation time and navigation paths' length), 34% better than the second ranked method in safety (collision times), 26.6% higher than the second ranked method in success rate, and shows strong robustness.

Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes.

Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.

Multiparametric MRI radiomics for the differentiation of brain glial cell hyperplasia from low-grade glioma.

BACKGROUND: Differentiating between low-grade glioma and brain glial cell hyperplasia is crucial for the customized clinical treatment of patients. OBJECTIVE: Based on multiparametric MRI imaging and clinical risk factors, a radiomics-clinical model and nomogram were constructed for the distinction of brain glial cell hyperplasia from low-grade glioma. METHODS: Patients with brain glial cell hyperplasia and low-grade glioma who underwent surgery at the First Affiliated Hospital of Soochow University from March 2016 to March 2022 were retrospectively included. In this study, A total of 41 patients of brain glial cell hyperplasia and 87 patients of low-grade glioma were divided into training group and validation group randomly at a ratio of 7:3. Radiomics features were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1-enhanced). Then, LASSO, SVM, and RF models were created in order to choose a model with a greater level of efficiency for calculating each patient's Rad-score (radiomics score). The independent risk factors were identified via univariate and multivariate logistic regression analysis to filter the Rad-score and clinical risk variables in turn. A radiomics-clinical model was next built of which effectiveness was assessed. RESULTS: Brain glial cell hyperplasia and low-grade gliomas from the 128 cases were randomly divided into 10 groups, of which 7 served as training group and 3 as validation group. The mass effect and Rad-score were two independent risk variables used in the construction of the radiomics-clinical model, and their respective AUCs for the training group and validation group were 0.847 and 0.858. The diagnostic accuracy, sensitivity, and specificity of the validation group were 0.821, 0.750, and 0.852 respectively. CONCLUSION: Combining with radiomics constructed by multiparametric MRI images and clinical features, the radiomics-clinical model and nomogram that were developed to distinguish between brain glial cell hyperplasia and low-grade glioma had a good performance.

Observation of flat band, Dirac nodal lines and topological surface states in Kagome superconductor CsTi3Bi5.

Kagome lattices of various transition metals are versatile platforms for achieving anomalous Hall effects, unconventional charge-density wave orders and quantum spin liquid phenomena due to the strong correlations, spin-orbit coupling and/or magnetic interactions involved in such a lattice. Here, we use laser-based angle-resolved photoemission spectroscopy in combination with density functional theory calculations to investigate the electronic structure of the newly discovered kagome superconductor CsTi3Bi5, which is isostructural to the AV3Sb5 (A = K, Rb or Cs) kagome superconductor family and possesses a two-dimensional kagome network of titanium. We directly observe a striking flat band derived from the local destructive interference of Bloch wave functions within the kagome lattice. In agreement with calculations, we identify type-II and type-III Dirac nodal lines and their momentum distribution in CsTi3Bi5 from the measured electronic structures. In addition, around the Brillouin zone centre, [Formula: see text] nontrivial topological surface states are also observed due to band inversion mediated by strong spin-orbit coupling.

Asymmetric Intramolecular Hydroalkylation of Internal Olefin with Cycloalkanone to Directly Access Polycyclic Systems.

An asymmetric intramolecular hydroalkylation of unactivated internal olefins with tethered cyclic ketones was realized by the cooperative catalysis of a newly designed chiral amine (SPD-NH2 ) and PdII complex, providing straightforward access to either bridged or fused bicyclic systems containing three stereogenic centers with excellent enantioselectivity (up to 99 % ee) and diastereoselectivity (up to >20 : 1 dr). Notably, the bicyclic products could be conveniently transformed into a diverse range of key structures frequently found in bioactive terpenes, such as Δ6 -protoilludene, cracroson D, and vulgarisins. The steric hindrance between the Ar group of the SPD-NH2 catalyst and the branched chain of the substrate, hydrogen-bonding interactions between the N-H of the enamine motif and the C=O of the directing group MQ, and the counterion of the PdII complex were identified as key factors for excellent stereoinduction in this dual catalytic process by density functional theory calculations.

Efficient Autonomous Exploration and Mapping in Unknown Environments.

Autonomous exploration and mapping in unknown environments is a critical capability for robots. Existing exploration techniques (e.g., heuristic-based and learning-based methods) do not consider the regional legacy issues, i.e., the great impact of smaller unexplored regions on the whole exploration process, which results in a dramatic reduction in their later exploration efficiency. To this end, this paper proposes a Local-and-Global Strategy (LAGS) algorithm that combines a local exploration strategy with a global perception strategy, which considers and solves the regional legacy issues in the autonomous exploration process to improve exploration efficiency. Additionally, we further integrate Gaussian process regression (GPR), Bayesian optimization (BO) sampling, and deep reinforcement learning (DRL) models to efficiently explore unknown environments while ensuring the robot's safety. Extensive experiments show that the proposed method could explore unknown environments with shorter paths, higher efficiencies, and stronger adaptability on different unknown maps with different layouts and sizes.

Determinants of growth and carbon accumulation of common plantation tree species in the three northern regions, China: Responses to climate and management strategies.

The Three-North (Northwest, North and Northeast) Shelter Forests Program (TNSFP) in China has effectively promoted vegetation growth and carbon sink in the temperate semi-humid and semi-arid regions. To compare the afforestation benefits of commonly used tree species in the area and explore the effect of environment on growth and carbon accumulation in plantations, backpack LiDAR was used to acquire 3 dimensional lidar point clouds of forests from a total of 480 pure plantation patches consisting of Pinus sylvestris (P.s.), Pinus tabuliformis (P.t.), Populus spp. (Pop.), and Robinia pseudoacacia (R.p.). Then, diameter at breast height (DBH), forest height, canopy coverage, and aboveground carbon accumulation were calculated for each plantation patches, which ranged from 7.0 to 37.3 cm, 1.5-14.5 m, 10-99 % and 4.2-205.9 Mg/ha, respectively. Generalized linear mixed-effect models and ANOVA were applied to account for the environmental constraints on the variations of forest parameters. Results showed that precipitation had a stronger effect on all the above parameters of plantations than temperature, and P.t. was more sensitive to climate than other three species. With regard to forest management in Pop. plantations, thinning could improve afforestation efficiency because carbon accumulation would reduce after the age exceeds 30 years. In contrast, P.s. populations maintained a continuous increase in carbon accumulation at least before 40 years old, while the radial growth of canopy became saturated after 12 years of age. The optimal planting density for P.s. and Pop. are about 1000 trees/ha, beyond which the increase in carbon accumulation will slow down or change rate of canopy coverage will be insignificant. Within the TNSFP area, P.t. and R.p. plantations would be more suitable in southern regions, while P.s. and Pop. plantations grow better in the northeastern regions. Meanwhile, mountains along the "Hu Line" showed high potential for growth and carbon accumulation for all tree species examined.

Climate drivers of seed rain phenology of subtropical forest communities along an elevational gradient.

Seed rain phenology (the start and end date of seed rain) is an essential component of plant phenology, critical for understanding population regeneration and community dynamics. However, intra- and inter-annual changes of seed rain phenology along environmental gradients have rarely been studied and the responses of seed rain phenology to climate variations are unclear. We monitored seed rain phenology of four forest communities in four years at different elevations (900 m, 1450 m, 1650 m, 1900 m a.s.l.) of a subtropical mountain in Central China. We analyzed the spatiotemporal patterns of seed rain phenology of 29 common woody plant species (total observed species in the seed rain), and related the phenological variations to seed number and climatic variables using mixed-effect models with the correlation matrix of phylogeny. We found that changes in the period length were mainly driven by the end rather than the start date. The end date and the period length of seed rain were significantly different between the mast and non-mast seeding years, while no significant elevation-related trend was detected in seed rain phenology variation. Seed number, mean temperature in spring (Tspr), and winter (Twin), summer precipitation (Psum) had significant effects on seed rain phenology. When Tspr increased, the start date of seed rain advanced, while the end date was delayed and the seed rain period length was mainly prolonged by a higher seed number, Twin and Psum. Forest canopy might have a buffering effect on understory climatic conditions, especially in precipitation that lead to difference in seed rain phenology between canopy and shrub species. Our novel evidence of seed rain phenology can improve prediction of community regeneration dynamics in responding to climate changes.

Multi-omics profiling of cholangiocytes reveals sex-specific chromatin state dynamics during hepatic cystogenesis in polycystic liver disease.

BACKGROUND & AIMS: Cholangiocytes transit from quiescence to hyperproliferation during cystogenesis in polycystic liver disease (PLD), the severity of which displays prominent sex differences. Epigenetic regulation plays important roles in cell state transition. We aimed to investigate the sex-specific epigenetic basis of hepatic cystogenesis and to develop therapeutic strategies targeting epigenetic modifications for PLD treatment. METHODS: Normal and cystic primary cholangiocytes were isolated from wild-type and PLD mice of both sexes. Chromatin states were characterized by analyzing chromatin accessibility (ATAC sequencing) and multiple histone modifications (chromatin immunoprecipitation sequencing). Differential gene expression was determined by transcriptomic analysis (RNA sequencing). Pharmacologic inhibition of epigenetic modifying enzymes was undertaken in PLD model mice. RESULTS: Through genome-wide profiling of chromatin dynamics, we revealed a profound increase of global chromatin accessibility during cystogenesis in both male and female PLD cholangiocytes. We identified a switch from H3K9me3 to H3K9ac on cis-regulatory DNA elements of cyst-associated genes and showed that inhibition of H3K9ac acetyltransferase or H3K9me3 demethylase slowed cyst growth in male, but not female, PLD mice. In contrast, we found that H3K27ac was specifically increased in female PLD mice and that genes associated with H3K27ac-gained regions were enriched for cyst-related pathways. In an integrated epigenomic and transcriptomic analysis, we identified an estrogen receptor alpha-centered transcription factor network associated with the H3K27ac-regulated cystogenic gene expression program in female PLD mice. CONCLUSIONS: Our findings highlight the multi-layered sex-specific epigenetic dynamics underlying cholangiocyte state transition and reveal a potential epigenetic therapeutic strategy for male PLD patients. IMPACT AND IMPLICATIONS: In the present study, we elucidate a sex-specific epigenetic mechanism underlying the cholangiocyte state transition during hepatic cystogenesis and identify epigenetic drugs that effectively slow cyst growth in male PLD mice. These findings underscore the importance of sex difference in the pathogenesis of PLD and may guide researchers and physicians to develop sex-specific personalized approaches for PLD treatment.

Benzodiazepine Derivatives as Potent Vasopressin V2 Receptor Antagonists for the Treatment of Autosomal Dominant Kidney Disease.

Cyst formation and enlargement in autosomal dominant kidney disease (ADPKD) is mainly driven by aberrantly increased cytosolic cAMP in renal tubule epithelial cells. Because the vasopressin V2 receptor (V2R) regulates intracellular cAMP levels in kidneys, a series of benzodiazepine derivatives were developed targeting the V2R. Among these derivatives, compound 25 exhibited potent binding affinity to the V2R (Ki = 9.0 ± 1.5 nM) and efficacious cAMP inhibition (IC50 = 9.2 ± 3.0 nM). This led to the suppression of cyst formation and growth in both an MDCK cell model and an embryonic kidney cyst model. Further advancing compound 25 in a murine model of ADPKD demonstrated a significantly improved in vivo efficacy compared with the reference compound tolvaptan. Overall, compound 25 holds therapeutic potential for the treatment of ADPKD.

Insight into impact of sewage discharge on microbial dynamics and pathogenicity in river ecosystem.

Direct sewage discharge could cause copious numbers of serious and irreversible harm to the environment. This study investigated the impacts of treated and raw sewage on the river ecosystem. Through our analysis, sewage carried various nutrients into the river, leading to changes in the microbial community in the river and reducing the diversity and richness of bacteria. The relative abundances of Hydrogenophaga, Thauera, Planctomyces, Zoogloea, and Pseudomonas boosted from 0.25, 0.01, 0.00, 0.05, and 0.08% to 3.33, 3.43, 0.02, 6.28, and 2.69%, before and after raw sewage discharge, respectively. The gene abundance of pathogenic bacteria significantly increased after raw sewage discharge. For instance, the gene abundance of Vibrio, Helicobacter, Tuberculosis, and Staphylococcus augmented from 4055, 3797, 13,545, 33 reads at Site-1 to 23,556, 13,163, 19,887, 734 reads at Site-2, respectively. In addition, according to the redundancy analysis (RDA), the infectious pathogens were positively related to the environmental parameters, in which COD showed the highest positive correlation with Mycobacterium tuberculosis. Additionally, river self-purification may contribute to improving water quality and reducing pathogenicity. The outcomes of this study showed that direct discharge brought pathogens and changed microbial community structure of the river.

Oxyallyl cation promoted dearomative semipinacol rearrangement: a facile stereodivergent synthesis of spiro-indolines with contiguous quaternary centers.

A novel oxyallyl cation promoted semipinacol rearrangement of indole-type allylic alcohols was disclosed for the stereodivergent synthesis of spiro-indolines. A variety of spiro-indolines were obtained with moderate to good yields. Three contiguous stereocenters, two of which are vicinal quaternary centers, were effectively formed with good diastereoselectivity. It is worth noting that two diastereoisomers of rearranged products can be readily achieved by easily regulating the reaction conditions. This method may provide an applicable approach for the synthesis of natural indole alkaloids.