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Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate rare cell types and achieve accurate identification. We benchmark scCAD on 25 real-world scRNA-seq datasets, demonstrating its superior performance compared to 10 state-of-the-art methods. In-depth case studies across diverse datasets, including mouse airway, brain, intestine, human pancreas, immunology data, and clear cell renal cell carcinoma, showcase scCAD’s efficiency in identifying rare cell types in complex biological scenarios. Furthermore, scCAD can correct the annotation of rare cell types and identify immune cell subtypes associated with disease, thereby offering valuable insights into disease progression. Identifying rare cells is essential for advancing our understanding of complex biological systems and disease mechanisms. Here, authors propose scCAD, a method that combines cluster decomposition and anomaly detection to effectively identify rare cell types across diverse biological scenarios.

Triangle packing problem has been paid lots of attention to in the literature. In this paper, we study the kernelization of the triangle packing problem in tournaments. For the parameterized arc-disjoint triangle packing problem in tournaments, we find a maximal arc-disjoint triangle packing with the number of vertices bounded by 2.5 k . Based on the relation between the maximal arc-disjoint triangle packing and the vertices outside of the packing, a kernel of size 3.5 k for the problem is obtained, improving the previous best one 6 k . For the parameterized vertex-disjoint triangle packing problem in sparse tournaments, several new properties between the triangles in maximal vertex-disjoint triangle packing and the arcs in the feedback arc set are presented, which result in a kernel of size 7 k for the problem, improving the previous best one of 15 k . We also give a 7 k vertex kernel for the parameterized feedback vertex set problem in sparse tournaments. The kernelization process presented in this paper for the parameterized arc-disjoint triangle packing can be applied to solve the parameterized arc-disjoint triangle packing problem on other restricted directed graph classes.

The reverse water-gas shift reaction (RWGSR) is essential for converting CO 2 into fuels using renewable hydrogen, but it remains challenged by the difficulty of simultaneously maximizing catalyst activity, selectivity, and stability. These limitations stem from thermodynamic constraints – specifically, the Gibbs-Curie-Wulff theorem - which restricts the synthetic accessibility of high-energy micro-faceted nanocrystals via conventional methods. To address this, we introduce a near-surface “quasi-hyperbaric” ammonia strategy that integrates atmospheric-pressure processing with in-situ ammonia decomposition. This approach enables the controlled synthesis of molybdenum nitride nanocrystals with preferentially exposed high-energy (112) microfacets. These facets promote CO 2 activation through a hydrogen-assisted redox mechanism, driven by geometrically confined and stabilized Mo-N/M-O hybrid active sites. The resulting catalyst outperforms the benchmark Pt/CeO₂, which typically suffers from CO selectivity below 92%. Our catalyst achieves near-equilibrium conversion (56%) at a space velocity (24000 ml/g cat /h), with 100% CO selectivity and outstanding stability (≤ 1% deactivation over 250 hours). The reverse water–gas shift reaction is crucial for CO₂ conversion using renewable hydrogen, but simultaneously achieving high activity, selectivity, and stability in catalysts remains a challenge. Here, the authors introduce a near-surface “quasi-hyperbaric” ammonia strategy that integrates atmospheric-pressure processing with in situ ammonia decomposition to synthesize a high-energy Mo₂N-based catalyst capable of overcoming these trade-offs.

In order to increase the potential kidney transplants between patients and their incompatible donors, kidney exchange programs have been created in many countries. In the programs, designing algorithms for the kidney exchange problem plays a critical role. The graph theory model of the kidney exchange problem is to find a maximum weight packing of vertex-disjoint cycles and chains for a given weighted digraph. In general, the length of cycles is not more than a given constant L (typically 2 ≤ L ≤ 5), and the objective function corresponds to maximizing the number of possible kidney transplants. In this paper, we study the parameterized complexity and randomized algorithms for the kidney exchange problem without chains from theory. We construct two different parameterized models of the kidney exchange problem for two cases L = 3 and L ≥ 3, and propose two randomized parameterized algorithms based on the random partitioning technique and the randomized algebraic technique, respectively.

Background Most previous studies on women of childbearing age have focused on reproductive health and fertility intentions, and evidence regarding the comprehensive health status of women of childbearing age is limited. This study aimed to comprehensively examine the health status of women of childbearing age through a multi-method and multi-indicator evaluation, analyze the factors that influence their overall health, and provide sound recommendations for the improvement and promotion of healthy behaviors. Methods Data on women of childbearing age living in Shanxi Province were collected between September 2021 and January 2022 through online and offline surveys. The k-means algorithm was used to assess health-related patterns in women, and multivariate nonconditional logistic regression was used to assess the influencing factors of women’s overall health. Results In total, 1,258 of 2,925 (43%) participants were classified as having a good health status in all five domains of the three health dimensions: quality of life, mental health, and illness. Multivariate logistic regression showed that education level, gynecological examination status, health status of family members, access to medical treatment, age, cooking preferences, diet, social support, hand washing habits, attitude toward breast cancer prevention, and awareness of reproductive health were significantly associated with different health patterns. Conclusions The comprehensive health status of women of childbearing age in Shanxi Province is generally good; however, a large proportion of women with deficiencies in some dimensions remains. Since lifestyle greatly impacts women’s health, health education on lifestyle and health-related issues should be strengthened.

Elevated H2O2 is implicated in many cardiovascular diseases. We previously demonstrated that H2O2‐induced endothelial nitric oxide synthase (eNOS) activation and excessive NO production contribute to vascular cell injury and increases in microvessel permeability. However, the mechanisms of excessive NO‐mediated vascular injury and hyperpermeability remain unknown. This study aims to examine the functional role of NO‐derived peroxynitrite (ONOO−) in H2O2‐induced vascular barrier dysfunction by elucidating the interrelationships between H2O2‐induced NO, superoxide, ONOO−, and changes in endothelial [Ca2+]i and microvessel permeability. Experiments were conducted on intact rat mesenteric venules. Microvessel permeability was determined by measuring hydraulic conductivity (Lp). Endothelial [Ca2+]i, NO, and O2− were assessed with fluorescence imaging. Perfusion of vessels with H2O2 (10 µmol/L) induced marked productions of NO and O2−, resulting in extensive protein tyrosine nitration, a biomarker of ONOO−. The formation of ONOO− was abolished by inhibition of NOS with NG‐Methyl‐L‐arginine. Blocking NO production or scavenging ONOO− by uric acid prevented H2O2‐induced increases in endothelial [Ca2+]i and Lp. Additionally, the application of exogenous ONOO− to microvessels induced delayed and progressive increases in endothelial [Ca2+]i and microvessel Lp, a pattern similar to that observed in H2O2‐perfused vessels. Importantly, ONOO− caused further activation of eNOS with amplified NO production. We conclude that the augmentation of NO‐derived ONOO− is essential for H2O2‐induced endothelial Ca2+ overload and progressively increased microvessel permeability, which is achieved by self‐promoted amplifications of NO‐dependent signaling cascades. This novel mechanism provides new insight into the reactive oxygen and/or reactive nitrogen species‐mediated vascular dysfunction in cardiovascular diseases. This study, conducted in intact microvessels, revealed new mechanistic insight into reactive oxygen and nitrogen species‐mediated vascular barrier dysfunction. Results demonstrated that elevated H2O2 not only increases nitric oxide (NO), but also NO‐derived peroxynitrite, which further activates eNOS and amplifies NO production. This self‐promoted augmentation of NO‐derived peroxynitrite contributes to H2O2‐induced Ca2+ overload and progressively increased microvessel permeability.

To identify health hazard behaviors and provide a basis for targeted management and intervention for patients with hypertension, we classified their health-related behaviors. A multi-stage random sampling method was used to conduct an on-site questionnaire survey among residents aged ≥15 years in a certain urban area of Taiyuan City, Shanxi Province, China. A latent class analysis was used to classify the lifestyle behaviors of patients with hypertension. The lifestyle behavior characteristics of different types of patients with hypertension and their awareness of hypertension were assessed. The prevalence of hypertension in Taiyuan City was 19.5%. Patients with hypertension were classified into three clusters according to their lifestyle patterns: smoking and drinking (13.35%), excessive edible oil and salt intake (68.27%), and healthy behavior (18.38%). Comparing the three latent classes of lifestyle, the distribution of age, sex, marital status, and education level was different ( < 0.05). The awareness of hypertension and the rate of control among the three classes were also different ( < 0.05). The lifestyle behaviors of patients with hypertension have evident classification characteristics. Approximately two-thirds of the patients with hypertension have an excessive intake of oil and salt. Therefore, targeted and precise intervention measures should be taken to control the intake of oil and salt in this cohort.

The Maximum Agreement Forest （MAF） problem on two given phylogenetic trees is an important NP-hard problem in the field of computational biology. In this paper, we study the parameterized version of the MAF problem： given two unrooted （multifurcating） phylogenetic trees T1 and T2 with the same leaf-label set L, and a parameter k, either construct an agreement forest of at most k trees for T1 and T2, or report that no such a forest exists. Whether there is a fixed-parameter tractable algorithm for this problem was posed as an open problem several times in the literature. In this paper, we resolve this open problem by presenting a parameterized algorithm of running time O（4kn5） for the problem.

We recently reported that zacopride is a selective inward rectifier potassium current （IK1 ） channel agonist, suppressing ventricular arrhythmias without affecting atrial arrhythmias. The present study aimed to investigate the unique pharmacological properties of zacopride. The whole-cell patch-clamp technique was used to study IK1 currents in rat atrial myocytes and Kir2.x currents in human embryonic kidney （HEK）-293 cells transfected with inward rectifier potassium channel （Kir）2.1, Kir2.2, Kir2.3, or mutated Kir2.1 （at phosphorylation site S425L）. Western immunoblots were performed to estimate the relative protein expression levels of Kir2.x in rat atria and ventricles. Results showed that zacopride did not affect the IK1 and transmembrane potential of atrial myocytes. In HEK293 cells, zacopride increased Kir2.1 homomeric channels by 40.7%±9.7% at 50 mV, but did not affect Kir2.2 and Kir2.3 homomeric channels, and Kir2.1-Kir2.2, Kir2.1-Kir2.3 and Kir2.2-Kir2.3 heteromeric channels. Western immunoblots showed that similar levels of Kir2.3 protein were expressed in rat atria and ventricles, but atrial Kir2.1 protein level was only 25% of that measured in the ventricle. In addition, 5-hydroxytryptamine （5-HT） 3 receptor was undetectable, whereas 5-HT 4 receptor was weakly expressed in HEK293 cells. The Kir2.1-activating effect of zacopride in these cells was abolished by inhibition of protein kinase A （PKA）, but not PKC or PKG. Furthermore, zacopride did not activate the mutant Kir2.1 channel in HEK293 cells but selectively activated the Kir2.1 homomeric channel via a PKA-dependent pathway, independent to that of the 5-HT receptor.

Balanced clustering is a frequently encountered problem in applications requiring balanced class distributions, which generalizes the standard clustering problem in that the number of clients connected to each facility is constrained by the given lower and upper bounds. It was known that both the problems of balanced k -means and k -median are W[2]-hard if parameterized by k , implying that the existences of FPT( k )-time exact algorithms for these problems are unlikely. In this paper, we give FPT( k )-time ( 9 + ϵ ) -approximation and ( 3 + ϵ ) -approximation algorithms for balanced k -means and k -median respectively, improving upon the previous best approximation ratios of 86.9 + ϵ and 7.2 + ϵ obtained in the same time. Our main technical contribution and the crucial step in getting the improved ratios is a different random sampling method for selecting opened facilities.