Widespread innervation of motoneurons by spinal V3 neurons globally amplifies locomotor output in mice.

While considerable progress has been made in understanding the neuronal circuits that underlie the patterning of locomotor behaviours such as walking, less is known about the circuits that amplify motoneuron output to enable adaptable increases in muscle force across different locomotor intensities. Here, we demonstrate that an excitatory propriospinal neuron population (V3 neurons, Sim1 + ) forms a large part of the total excitatory interneuron input to motoneurons (∼20%) across all hindlimb muscles. Additionally, V3 neurons make extensive connections among themselves and with other excitatory premotor neurons (such as V2a neurons). These circuits allow local activation of V3 neurons at just one segment (via optogenetics) to rapidly depolarize and amplify locomotor-related motoneuron output at all lumbar segments in both the in vitro spinal cord and the awake adult mouse. Interestingly, despite similar innervation from V3 neurons to flexor and extensor motoneuron pools, functionally, V3 neurons exhibit a pronounced bias towards activating extensor muscles. Furthermore, the V3 neurons appear essential to extensor activity during locomotion because genetically silencing them leads to slower and weaker mice with a poor ability to increase force with locomotor intensity, without much change in the timing of locomotion. Overall, V3 neurons increase the excitability of motoneurons and premotor neurons, thereby serving as global command neurons that amplify the locomotion intensity.

Clinical Assessment of Magnetic Resonance Spectroscopy and Diffusion-Weighted Imaging in Diffuse Glioma: Insights Into Histological Grading and IDH Classification.

PURPOSE: To assess the diagnostic utility of clinical magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) in distinguishing between histological grading and isocitrate dehydrogenase (IDH) classification in adult diffuse gliomas. METHODS: A retrospective analysis was conducted on 247 patients diagnosed with adult diffuse glioma. Experienced radiologists evaluated DWI and MRS images. The Kruskal-Wallis test examined differences in DWI and MRS-related parameters across histological grades, while the Mann-Whitney U test assessed molecular classification. Receiver Operating Characteristic (ROC) curves evaluated parameter effectiveness. Survival curves, stratified by histological grade and IDH classification, were constructed using the Kaplan-Meier test. RESULTS: The cohort comprised 141 males and 106 females, with ages ranging from 19 to 85 years. The Kruskal-Wallis test revealed significant differences in ADC mean, Cho/NAA, and Cho/Cr concerning glioma histological grade (P < .01). Subsequent application of Dunn's test showed significant differences in ADC mean among each histological grade (P < .01). Notably, Cho/NAA exhibited a marked distinction between grade 2 and grade 3/4 gliomas (P < .01). The Mann-Whitney U test indicated that only ADC mean showed statistical significance for IDH molecular classification (P < .01). ROC curves were constructed to demonstrate the effectiveness of the specified parameters. Survival curves were also delineated to portray survival outcomes categorized by histological grade and IDH classification. Conclusions: Clinical MRS demonstrates efficacy in glioma histological grading but faces challenges in IDH classification. Clinical DWI's ADC mean parameter shows significant distinctions in both histological grade and IDH classification.

Cobalt single-atom catalyst tailored ceramic membrane for selective removal of emerging organic contaminants.

Water reuse is an effective way to solve the issues of current wastewater increments and water resource scarcity. Ultrafiltration, a promising method for water reuse, has the characteristics of low energy consumption, easy operation, and high adaptability to coupling with other water treatment processes. However, emerging organic contaminants (EOCs) in municipal wastewater cannot be effectively intercepted by ultrafiltration, which poses significant challenges to the effluent quality and sustainability of ultrafiltration process. Here, we develop a cobalt single-atom catalyst-tailored ceramic membrane (Co1-NCNT-CM) in conjunction with an activated peroxymonosulfate (PMS) system, achieving excellent EOCs degradation and anti-fouling performance. An interfacial reaction mechanism effectively mitigates membrane fouling through a repulsive interaction with natural organic matter. The generation of singlet oxygen at the Co-N3-C active sites through a catalytic pathway (PMS→PMS∗→OH∗→O∗→OO∗→1O2) exhibits selective oxidation of phenols and sulfonamides, achieving >90% removal rates. Our findings elucidate a multi-layered functional architecture within the Co1-NCNT-CM/PMS system, responsible for its superior performance in organic decontamination and membrane maintenance during secondary effluent treatment. It highlights the power of integrating Co1-NCNT-CM/PMS systems in advanced wastewater treatment frameworks, specifically for targeted EOCs removal, heralding a new direction for sustainable water management.

VHL mutation drives human clear cell renal cell carcinoma progression through PI3K/AKT-dependent cholesteryl ester accumulation.

BACKGROUND: Cholesteryl ester (CE) accumulation in intracellular lipid droplets (LDs) is an essential signature of clear cell renal cell carcinoma (ccRCC), but its molecular mechanism and pathological significance remain elusive. METHODS: Enabled by the label-free Raman spectromicroscopy, which integrated stimulated Raman scattering microscopy with confocal Raman spectroscopy on the same platform, we quantitatively analyzed LD distribution and composition at the single cell level in intact ccRCC cell and tissue specimens in situ without any processing or exogenous labeling. Since we found that commonly used ccRCC cell lines actually did not show the CE-rich signature, primary cancer cells were isolated from human tissues to retain the lipid signature of ccRCC with CE level as high as the original tissue, which offers a preferable cell model for the study of cholesterol metabolism in ccRCC. Moreover, we established a patient-derived xenograft (PDX) mouse model that retained the CE-rich phenotype of human ccRCC. FINDINGS: Surprisingly, our results revealed that CE accumulation was induced by tumor suppressor VHL mutation, the most common mutation of ccRCC. Moreover, VHL mutation was found to promote CE accumulation by upregulating HIFα and subsequent PI3K/AKT/mTOR/SREBPs pathway. Inspiringly, inhibition of cholesterol esterification remarkably suppressed ccRCC aggressiveness in vitro and in vivo with negligible toxicity, through the reduced membrane cholesterol-mediated downregulations of integrin and MAPK signaling pathways. INTERPRETATION: Collectively, our study improves current understanding of the role of CE accumulation in ccRCC and opens up new opportunities for treatment. FUNDING: This work was supported by National Natural Science Foundation of China (No. U23B2046 and No. 62027824), National Key R&D Program of China (No. 2023YFC2415500), Fundamental Research Funds for the Central Universities (No. YWF-22-L-547), PKU-Baidu Fund (No. 2020BD033), Peking University First Hospital Scientific and Technological Achievement Transformation Incubation Guidance Fund (No. 2022CX02), and Beijing Municipal Health Commission (No. 2020-2Z-40713).

Role of Hsa_circ_0000880 in the Regulation of High Glucose-Induced Apoptosis of Retinal Microvascular Endothelial Cells.

Purpose: Circular RNAs (circRNAs) have been verified to participate in multiple biological processes and disease progression. Yet, the role of circRNAs in the pathogenesis of diabetic retinopathy (DR) is still poorly understood and deserves further study. This study aimed to investigate the role of circRNAs in the regulation of high glucose (HG)-induced apoptosis of retinal microvascular endothelial cells (RMECs). Methods: Epiretinal membranes from patients with DR and nondiabetic patients with idiopathic macular epiretinal membrane were collected for this study. The circRNA microarrays were performed using high-throughput sequencing. Hierarchical clustering, functional enrichment, and network regulation analyses were used to analyze the data generated by high-throughput sequencing. Next, RMECs were subjected to HG (25 mM) conditions to induce RMECs apoptosis in vitro. A series of experiments, such as Transwell, the Scratch wound, and tube formation, were conducted to explore the regulatory effect of circRNA on RMECs. Fluorescence in situ hybridization (FISH), immunofluorescence staining, and Western blot were used to study the mechanism underlying circRNA-mediated regulation. Results: A total of 53 differentially expressed circRNAs were found in patients with DR. Among these, hsa_circ_0000880 was significantly upregulated in both the diabetic epiretinal membranes and in an in vitro DR model of HG-treated RMECs. Hsa_circ_0000880 knockout facilitated RMECs vitality and decreased the paracellular permeability of RMECs under hyperglycemia. More importantly, silencing of hsa_circ_0000880 significantly inhibited HG-induced ROS production and RMECs apoptosis. Hsa_circ_0000880 acted as an endogenous sponge for eukaryotic initiation factor 4A-III (EIF4A3). Knockout of hsa_circ_0000880 reversed HG-induced decrease in EIF4A3 protein level. Conclusions: Our findings suggest that hsa_circ_0000880 is a novel circRNA can induce RMECs apoptosis in response to HG conditions by sponging EIF4A3, offering an innovative treatment approach against DR. Translational Relevance: The circRNAs participate in the dysregulation of microvascular endothelial function induced by HG conditions, indicating a promising therapeutic target for DR.

Language model based on deep learning network for biomedical named entity recognition.

Biomedical Named Entity Recognition (BioNER) is one of the most basic tasks in biomedical text mining, which aims to automatically identify and classify biomedical entities in text. Recently, deep learning-based methods have been applied to Biomedical Named Entity Recognition and have shown encouraging results. However, many biological entities are polysemous and ambiguous, which is one of the main obstacles to the task of biomedical named entity recognition. Deep learning methods require large amounts of training data, so the lack of data also affect the performance of model recognition. To solve the problem of polysemous words and insufficient data, for the task of biomedical named entity recognition, we propose a multi-task learning framework fused with language model based on the BiLSTM-CRF architecture. Our model uses a language model to design a differential encoding of the context, which could obtain dynamic word vectors to distinguish words in different datasets. Moreover, we use a multi-task learning method to collectively share the dynamic word vector of different types of entities to improve the recognition performance of each type of entity. Experimental results show that our model reduces the false positives caused by polysemous words through differentiated coding, and improves the performance of each subtask by sharing information between different entity data. Compared with other state-of-the art methods, our model achieved superior results in four typical training sets, and achieved the best results in F1 values.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells.

Background: The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD. Method: Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2. Results: Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment. Conclusion: The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

[Analysis and prospect of correlation between relative molecular weight and efficacy of polysaccharides from medicinal plant resources].

Polysaccharides from medicinal plant resources are a kind of polymers extracted from medicinal plants. They are complex long chains formed by different monosaccharides connected via glucosidic bonds. These polysaccharides usually have straight chain and branched chain structures, and their relative molecular weight changes greatly. Modern studies have shown that the biological activi-ty of polysaccharides from medicinal plant resources is closely related to their relative molecular weight. This paper first reviewed the preparation and detection methods of polysaccharides from medicinal plant resources with different relative molecular weights. Then, the paper summarized and analyzed the general experience of the correlation between efficacy and relative molecular weight of polysaccharides from medicinal plant resources with different molecular weights. It was considered that polysaccharides with large relative molecular weights(>100 kDa) play a leading role in immune regulation. Polysaccharides with medium relative molecular weights(10-100 kDa) play a leading role in immune regulation and the protection of the liver. Polysaccharides with small relative molecular weights(<10 kDa) play a leading role in anti-oxidation, regulation of intestinal flora, regulation of blood glucose and lipids, anti-fatigue, and the protection of nerves. Therefore, precise development of polysaccharides from medicinal plant resources based on relative molecular weight is expected to improve their biological activity and application value.

Comparative Proteomics Elucidates the Potential Mechanism of Sperm Capacitation of Chinese Mitten Crabs (Eriocheir sinensis).

Sperm capacitation is broadly defined as a suite of biochemical and biophysical changes resulting from the acquisition of fertilization ability. To gain insights into the regulation mechanism of crustacean sperm capacitation, 4D label-free quantitative proteomics was first applied to analyze the changes of sperm in Eriocheir sinensis under three sequential physiological conditions: seminal vesicles (X2), hatched with the seminal receptacle content (X3), and incubated with egg water (X5). In total, 1536 proteins were identified, among which 880 proteins were quantified, with 82 and 224 proteins significantly altered after incubation with the seminal receptacle contents and egg water. Most differentially expressed proteins were attributed to biological processes by Gene Ontology annotation analysis. As the fundamental bioenergetic metabolism of sperm, the oxidative phosphorylation, glycolysis, and the pentose phosphate pathway presented significant changes under the treatment of seminal receptacle contents, indicating intensive regulation for sperm in the seminal receptacle. Additionally, the seminal receptacle contents also significantly increased the oxidation level of sperm, whereas the enhancement of abundance in superoxide dismutase, peroxiredoxin 1, and glutathione S-transferase after incubation with egg water significantly improved the resistance against oxidation. These results provided a new perspective for reproduction studies in crustaceans.

The Prognostic Value and Potential Immune Mechanisms of lncRNAs Related to Immunogenic Cell Death in Papillary Thyroid Carcinoma.

Background: Long non-coding RNAs (lncRNAs) associated with immunogenic cell death (ICD) play a pivotal role in tumorigenesis and offer prognostic insights for papillary thyroid carcinoma (PTC) patients. This study delves into the impact of ICD-related lncRNAs on the prognosis of PTC. Methods: PTC samples were accessed from The Cancer Genome Atlas-Thyroid carcinoma database (TCGA-THCA) and consensus cluster analysis to elucidate the influence of ICD-related lncRNA expression. To gauge the prognostic significance of these lncRNAs, we developed a prognostic model. Additionally, we conducted GO and KEGG enrichment analyses, assessed immune cell infiltration (ICI) using CIBERSORT and ssGSEA, examined immune checkpoint expression, tumor mutation burden (TMB), tumor microenvironment (TME), T-cell dysfunction and exclusion (TIDE), TCIA, and drug sensitivity across various groups. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of LINC00924 in two PTC cell lines, BCPAP and TPC1, transfected with LINC00924 overexpression plasmids. Results: Two distinct clusters demonstrated varying TME, BRAF, NRAS, and ICI characteristics, suggesting potential immune mechanisms in PTC. Our prognostic model identified seven lncRNAs: SRRM2-AS1, AC008556.1, BHLHE40-AS1, EGOT, AL39066.1, LINC00924, and PICART1. The expression of ICD-related lncRNAs correlated with progression-free interval (PFI) in PTC patients. Overexpression of LINC00924 significantly reduced cell proliferation, migration, and invasion, while augmenting apoptosis in PTC cells. Conclusion: Our findings highlight the potential of ICD-related lncRNAs as prognostic biomarkers for PFI in PTC. In vitro experiments suggest a protective role of LINC00924 in PTC progression.

The multiple roles of viral 3Dpol protein in picornavirus infections.

The Picornaviridae are a large group of positive-sense, single-stranded RNA viruses, and most research has focused on the Enterovirus genus, given they present a severe health risk to humans. Other picornaviruses, such as foot-and-mouth disease virus (FMDV) and senecavirus A (SVA), affect agricultural production with high animal mortality to cause huge economic losses. The 3Dpol protein of picornaviruses is widely known to be used for genome replication; however, a growing number of studies have demonstrated its non-polymerase roles, including modulation of host cell biological processes, viral replication complex assembly and localization, autophagy, and innate immune responses. Currently, there is no effective vaccine to control picornavirus diseases widely, and clinical therapeutic strategies have limited efficiency in combating infections. Many efforts have been made to develop different types of drugs to prohibit virus survival; the most important target for drug development is the virus polymerase, a necessary element for virus replication. For picornaviruses, there are also active efforts in targeted 3Dpol drug development. This paper reviews the interaction of 3Dpol proteins with the host and the progress of drug development targeting 3Dpol.

Tunable Light-Responsive Polyurethane-urea Elastomer Driven by Photochemical and Photothermal Coupling Mechanism.

Light-driven soft actuators based on photoresponsive materials can be used to mimic biological motion, such as hand movements, without involving rigid or bulky electromechanical actuations. However, to our knowledge, no robust photoresponsive material with desireable mechanical and biological properties and relatively simple manufacture exists for robotics and biomedical applications. Herein, we report a new visible-light-responsive thermoplastic elastomer synthesized by introducing photoswitchable moieties (i.e., azobenzene derivatives) into the main chain of poly(ε-caprolactone) based polyurethane urea (PAzo). A PAzo elastomer exhibits controllable light-driven stiffness softening due to its unique nanophase structure in response to light, while possessing excellent hyperelasticity (stretchability of 575.2%, elastic modulus of 17.6 MPa, and strength of 44.0 MPa). A bilayer actuator consisting of PAzo and polyimide films is developed, demonstrating tunable bending modes by varying incident light intensities. Actuation mechanism via photothermal and photochemical coupling effects of a soft-hard nanophase is demonstrated through both experimental and theoretical analyses. We demonstrate an exemplar application of visible-light-controlled soft "fingers" playing a piano on a smartphone. The robustness of the PAzo elastomer and its scalability, in addition to its excellent biocompatibility, opens the door to the development of reproducible light-driven wearable/implantable actuators and lightweight soft robots for clinical applications.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS: In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA). RESULTS: The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models. CONCLUSION: The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Stand in surgeon's shoes: virtual reality cross-training to enhance teamwork in surgery.

PURPOSE: Teamwork in surgery depends on a shared mental model of success, i.e., a common understanding of objectives in the operating room. A shared model leads to increased engagement among team members and is associated with fewer complications and overall better outcomes for patients. However, clinical training typically focuses on role-specific skills, leaving individuals to acquire a shared model indirectly through on-the-job experience. METHODS: We investigate whether virtual reality (VR) cross-training, i.elet@tokeneonedotexposure to other roles, can enhance a shared mental model for non-surgeons more directly. Our study focuses on X-ray guided pelvic trauma surgery, a procedure where successful communication depends on the shared model between the surgeon and a C-arm technologist. We present a VR environment supporting both roles and evaluate a cross-training curriculum in which non-surgeons swap roles with the surgeon. RESULTS: Exposure to the surgical task resulted in higher engagement with the C-arm technologist role in VR, as measured by the mental demand and effort expended by participants ( p < 0.001 ). It also has a significant effect on non-surgeon's mental model of the overall task; novice participants' estimation of the mental demand and effort required for the surgeon's task increases after training, while their perception of overall performance decreases ( p < 0.05 ), indicating a gap in understanding based solely on observation. This phenomenon was also present for a professional C-arm technologist. CONCLUSION: Until now, VR applications for clinical training have focused on virtualizing existing curricula. We demonstrate how novel approaches which are not possible outside of a virtual environment, such as role swapping, may enhance the shared mental model of surgical teams by contextualizing each individual's role within the overall task in a time- and cost-efficient manner. As workflows grow increasingly sophisticated, we see VR curricula as being able to directly foster a shared model for success, ultimately benefiting patient outcomes through more effective teamwork in surgery.

Leaf Traits Explain the Growth Variation and Nitrogen Response of Eucalyptus urophylla × Eucalyptus grandis and Dalbergia odorifera in Mixed Culture.

Mixed cultivation with legumes may alleviate the nitrogen (N) limitation of monoculture Eucalyptus. However, how leaf functional traits respond to N in mixed cultivation with legumes and how they affect tree growth are unclear. Thus, this study investigated the response of leaf functional traits of Eucalyptus urophylla × Eucalyptus grandis (E. urophylla × E. grandis) and Dalbergia odorifera (D. odorifera) to mixed culture and N application, as well as the regulatory pathways of key traits on seedling growth. In this study, a pot-controlled experiment was set up, and seedling growth indicators, leaf physiology, morphological parameters, and N content were collected and analyzed after 180 days of N application treatment. The results indicated that mixed culture improved the N absorption and photosynthetic rate of E. urophylla × E. grandis, further promoting seedling growth but inhibiting the photosynthetic process of D. odorifera, reducing its growth and biomass. Redundancy analysis and path analysis revealed that leaf nitrogen content, pigment content, and photosynthesis-related physiological indicators were the traits most directly related to seedling growth and biomass accumulation, with the net photosynthetic rate explaining 50.9% and 55.8% of the variation in growth indicators for E. urophylla × E. grandis and D. odorifera, respectively. Additionally, leaf morphological traits are related to the trade-off strategy exhibited by E. urophylla × E. grandis and D. odorifera based on N competition. This study demonstrated that physiological traits related to photosynthesis are reliable predictors of N nutrition and tree growth in mixed stands, while leaf morphological traits reflect the resource trade-off strategies of different tree species.

Comparison of progestin-primed ovarian stimulation regimen and antagonist regimen in women aged 35 years or older with diminished ovarian reserve: A propensity score-matched study.

OBJECTIVE: Diminished ovarian reserve (DOR) has been a major challenge in infertility treatment. The present study aimed to compare the efficacy of progestin-primed ovarian stimulation (PPOS) regimen and antagonist regimen in infertile patients aged 35 years or older with DOR. METHODS: A retrospective study of 289 in vitro fertilization (IVF) cycles from April 2016 to June 2022 was performed. Propensity score matching (PSM) was used to balance the baseline characteristics between the two groups at a ratio of 1:1. RESULTS: After matching, there were 87 cycles in the PPOS group and 87 cycles in the antagonist group. The primary outcome measures included the incidence of premature LH surge, the number of retrieved oocytes, and the number of mature oocytes, which were comparable between the two groups (all P values >0.05). There were no significant differences in laboratory indicators and final clinical outcomes between the two groups (all P values >0.05). CONCLUSIONS: For DOR patients aged 35 years or older, the number of retrieved oocytes and the number of mature oocytes were comparable between the PPOS and antagonist groups. Moreover, the two regimens showed no difference in the inhibition of premature LH surge.

Measurement and spatial correlation analysis of high-quality development Level: A case study of the Yangtze River Delta urban agglomeration in China.

Against the backdrop of slowing economic growth and increasing environmental pressure, the Yangtze River Delta city cluster, as one of the largest city clusters in the world, has become more driven in its pursuit of high-quality development. We constructed a system of 24 evaluation indexes and used entropy-weighted TOPSIS to calculate and study the high-quality development index of urban agglomerations in the region. First, the level of high quality development (HQD) of the Yangtze River Delta city cluster generally improved from 2010 to 2021, with 2017 was the best year, while 2010 was the worst year. Second, in the multidimensional evaluation of HQD, Jiangsu excels in innovation and people's livelihood with 0.524 and 0.534, respectively; Shanghai (0.531) excels in coordinated development; Zhejiang excels in green and economic development with 0.557 and 0.484, respectively; and Anhui lags behind in all aspects. Third, the development process of HQD in the Yangtze River Delta region is uneven, and the level of HQD development varies greatly among the city clusters in the province. The measurement results show that Shanghai (0.511) has the highest score, followed by Zhejiang (0.484), Jiangsu (0.440) and Anhui (0.435). Fourth, spatial correlation analysis shows that Shanghai and Jiangsu are mainly distributed in the double-high region, Zhejiang is distributed in the high-low region, while Anhui is concentrated in the low-low region. The results of this study help us understand more deeply the characteristics and challenges of high-quality development in the Yangtze River Delta urban agglomerations and provide a scientific basis for more precise urban development policies.

Nonreciprocal magnon blockade based on nonlinear effects.

We present an alternative scheme to achieve nonreciprocal unconventional magnon blockade (NUMB) in a hybrid system formed by two microwave cavities and one yttrium iron garnet (YIG) sphere, where the pump and signal cavities interact nonlinearly with each other and the signal cavity is coupled to the YIG sphere. It is found that the nonlinear coupling occurs between the pump cavity and magnon modes due to the dispersive interactions among three bosonic modes. Meanwhile, the Kerr nonlinearity is present in the pump cavity. Based on these nonlinear effects, a nonreciprocal magnon blockade could be achieved with the help of the weak parametric driving of the pump cavity. The present work provides an alternative method to prepare single magnon resource, which may be helpful for quantum information processing.

Childhood Mycoplasma pneumoniae: epidemiology and manifestation in Northeast and Inner Mongolia, China.

Mycoplasma pneumoniae (MP) is commonly detected in children. However, the epidemiological trends of MP in Northeast (NE) China are unclear. This retrospective study aimed to investigate the prevalence of MP infections in this understudied region. The clinical manifestations and bronchoscopic findings observed in hospitalized patients with severe Mycoplasma pneumoniae pneumonia (SMPP) were collected from comprehensive data obtained from six tertiary hospitals in NE and Inner Mongolian (IM) China, from 1 January 2017 to 31 December 2023. A total of 5,593,530 children who visited the outpatient and emergency departments, and 412,480 inpatient hospitalized children were included in the study. The positivity rate of MP immunoglobulin M (IgM) in the children who visited the outpatient and emergency departments varied from 7.80% to 10.12%, whereas that of MP infection in hospitalized children ranged from 27.18% to 30.10%. Children hospitalized for MP infection were mainly concentrated in the 1- to 4-year (41.39%) and 4- to 7-year (24.25%) age groups. Before 2020, the season with the highest incidence of MP was winter. After the implementation of non-pharmaceutical interventions (NPIs), the MP epidemic season changed, and the number of children with MP infections decreased; however, the proportion of MP infections in hospitalized children did not change significantly. Starting from August 2023, the MP infection rate in outpatient, emergency, and hospitalized children increased sharply, with SMPP and its complications (e.g., plastic bronchitis and pleural effusion) increasing significantly. MP is prevalent in NE and IM, China. When the NPIs ended, MP infection showed a delayed outbreak trend, and the number of children with severe infection increased significantly. IMPORTANCE: In Northeastern (NE) and Inner Mongolia (IM), the incidence of Mycoplasma pneumoniae (MP) infections, including severe Mycoplasma pneumoniae pneumonia (SMPP), is high, posing health risks and imposing substantial economic burdens on the local population. Therefore, it is imperative to prioritize the study of MP prevalence and address the research gaps in MP epidemiology in these areas of China. We obtained a comprehensive collection of pediatric outpatient, emergency, and inpatient data from six public Grade III hospitals. We believe that our study makes a significant contribution to the literature because understanding regional variations in MP infections can help healthcare professionals tailor prevention and treatment strategies, and studying bronchoscopic manifestations can provide insights into the impact of the disease on the respiratory system, potentially leading to a more effective clinical management.

Vislocas: Vision transformers for identifying protein subcellular mis-localization signatures of different cancer subtypes from immunohistochemistry images.

Proteins must be sorted to specific subcellular compartments to perform their functions. Abnormal protein subcellular localizations are related to many diseases. Although many efforts have been made in predicting protein subcellular localization from various static information, including sequences, structures and interactions, such static information cannot predict protein mis-localization events in diseases. On the contrary, the IHC (immunohistochemistry) images, which have been widely applied in clinical diagnosis, contains information that can be used to find protein mis-localization events in disease states. In this study, we create the Vislocas method, which is capable of finding mis-localized proteins from IHC images as markers of cancer subtypes. By combining CNNs and vision transformer encoders, Vislocas can automatically extract image features at both global and local level. Vislocas can be trained with full-sized IHC images from scratch. It is the first attempt to create an end-to-end IHC image-based protein subcellular location predictor. Vislocas achieved comparable or better performances than state-of-the-art methods. We applied Vislocas to find significant protein mis-localization events in different subtypes of glioma, melanoma and skin cancer. The mis-localized proteins, which were found purely from IHC images by Vislocas, are in consistency with clinical or experimental results in literatures. All codes of Vislocas have been deposited in a Github repository (https://github.com/JingwenWen99/Vislocas). All datasets of Vislocas have been deposited in Zenodo (https://zenodo.org/records/10632698).