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We demonstrate a high-power InnoSlab amplifier based on a multi-segmented composite ytterbium-doped yttrium aluminum garnet (Yb:YAG) crystal. A systematic comparison was performed of the laser amplification output performance of multi-segmented and conventional Yb:YAG crystals to demonstrate the feasibility of using gain media with multiple doping concentrations in InnoSlab laser amplifiers. We achieved an amplified output of 245 W based on the multi-segmented composite Yb:YAG crystal InnoSlab amplifier, with a beam quality of M2 = 1.21 × 1.25 and an optical-to-optical efficiency of 38.9%. Thanks to the unique doping structure of the composite crystal, compared to homogeneous dopant crystals, the average output power, optical-to-optical efficiency and beam quality were significantly improved. Exceptional output power stability with a root mean square fluctuation of 0.11% and pointing stability of approximately 7.5 μrad were achieved.
Nerve growth factor (NGF), which acts on receptors tropomyosin receptor kinase A and p75 neurotrophic receptor, is a member of neurotrophin family and a kind of secretory polypeptides.
Methods
A comprehensive literature search was conducted in the following databases: PubMed and Web of Science. The following search terms were used in various combinations: “NGF,” “nerve growth factor,” “ovarian steroidogenesis,” “follicular development,” “oocyte maturation,” and “ovulation.” Boolean operators (AND, OR) were applied to combine search terms (e.g., “NGF AND PCOS,” “NGF AND follicular development”).
Results
NGF plays important roles in multiple reproductive physiological activities. Its ovarian effects are crucial for oocyte maturation, follicular assembly, early follicle development, ovulation and steroidogenesis. While the ovary is a major target, NGF’s role extends to the broader regulation of the female reproductive system. In particular, the role of NGF in inducing ovulation by acting on the hypothalamus has garnered considerable scholarly attention. Although relatively few studies have examined the direct impact of NGF on hypothalamic gonadotrophin-releasing hormone neurons—the central regulators of the hypothalamic–pituitary–ovary (HPO) axis, extensive evidence demonstrates that NGF can cause an influence on the synthesis and release of follicle-stimulating hormone, luteinizing hormone and steroid hormones, which act downstream in the HPO axis.
Conclusions
Our review outlines the critical role of NGF in female reproductive physiology, with a particular focus on its modulatory influence on induced ovulation. Furthermore, in this review, we aim to provide a more comprehensive perspective on NGF’s role in reproductive disorders, such as polycystic ovary syndrome, diminished ovarian reserve and endometriosis.
While the relationships between somatic movement, mental well-being, and brain health have been well established, the causal nature and underlying mechanisms of such associations remain incompletely understood.
Methods
By applying multi-stage Mendelian randomization to multi-source summary data derived from genome-wide association studies, we examined the causal effects of 4 somatic movement measures on 2 mental well-being indices and 13 types of brain structures, followed by testing the mediating roles of brain structures in accounting for the causal associations between somatic movement and mental well-being.
Results
Two-sample Mendelian randomization revealed that more physical activity was causally associated with greater mental well-being (life satisfaction and positive affect), while more sedentary behavior (longer leisure screen time and more sedentary behavior at work) with lower mental well-being. With respect to brain structures, sedentary behavior was causally linked to decreased volume, surface area, and local gyrification index in distributed cortical regions. Remarkably, decreased surface area of the piriform cortex was found to mediate the causal associations between sedentary behavior and lower mental well-being.
Conclusions
Our findings not only complement and extend earlier reports on the associations of somatic movement with mental well-being and brain health by further resolving the causality but also help elucidate the neural mechanisms by which sedentary behavior adversely affects mental well-being.
Crush syndrome, also known as traumatic rhabdomyolysis, often occurs in disasters like earthquakes, traffic accidents, and building collapses. It results in muscle cell necrosis, leading to symptoms such as hypovolemic shock, hyperkalemia, and acute kidney injury (AKI). The mortality rate of rhabdomyolysis is about 10%. An intelligent auxiliary diagnostic system for rhabdomyolysis based on machine learning is crucial.
Methods:
This study aimed to develop an intelligent auxiliary diagnostic system, utilizing the MIMIC-III database and electronic medical records from several Chinese hospitals. The system was trained and validated with 70% and 30% of patient data, respectively. A variety of machine learning methods were used to establish injury grading and prognosis assessment models, and statistical methods and feature importance assessment methods were used to analyze and explain the features selected by the model.
Results:
The 22 clinical indicators originally included in the modeling were reduced to 11 through feature analysis and feature screening. In internal tests, the auxiliary diagnostic system based on 11 parameters achieved an average accuracy of 0.89. External validation with 360 cases showed an average accuracy of 0.84, with an AKI prediction accuracy of 0.83 and an AUC value of 0.82. Death risk prediction accuracy reached 0.89.
Conclusion:
This intelligent auxiliary diagnostic system provides valuable recommendations for the diagnosis and treatment of rhabdomyolysis, improving treatment success rates and optimizing medical resource allocation in disaster situations. By leveraging machine learning, we have established a robust and reliable tool to assist healthcare providers in managing this complex condition.
With extraordinary preservation, the bivalved Cassicaris clarksoni gen. et sp. nov. from the early Cambrian (Stage 3) Xiaoshiba Lagerstätte in Kunming, China, is characterised by having an anterior cardinal spine and a heavily segmented body, including an abdomen with a heavily sclerotised shell. Anatomically, the antennulae are small and the antennae are robust with seta-bearing podomeres, possibly of predatory function, followed by the other five pairs of biramous cephalic limbs. There are about 11 pairs of thorax segments, each corresponding to a pair of biramous limbs, including a multi-segmented endopod with feather-like podomeres and terminal spines, and a small paddle-shaped exopod fringed with setae. The bulbous, stalked eyes, which exhibit fineness of vision, infer adaptation to a vagile epibenthic lifestyle. Functionally, such assorted appendages may indicate an efficient suspension-feeding strategy for capturing tiny zooplankton. The median eye is presumably not a typical ocellar system but another compound eye, which may offer further insights into the evolution of compound eyes. Cladistic analysis implies that Cassicaris is a sister taxon to Pectocaris and Jugatacaris; these intriguing euarthropods are critical for discerning their body plan and living habits. Our findings offer fresh insights into the early evolution of Cambrian euarthropods, characterised by notable morphological disparity and ecological diversity. These fossils, including not only many intact individuals but also a few with well-preserved soft parts, form well-characterised groupings, making the broad pattern of Cambrian arthropod systematics increasingly consensual.
Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.
The Resistance War of 1937-1945 is the centerpiece of contemporary Chinese nationalism and contention over war memory has long exacerbated China-Japan frictions. The present blogged article by the dissident Christian writer Yu Jie, building on an earlier statement by literary critic Ge Hongbing, is both a rare challenge to the Chinese Communist Party's nationalist orthodoxy on the war by a China-based author, and a plea for Chinese reconciliation with Japan. Who are the victims, and who the assailants in the Resistance War? Specifically, were Chinese alone victims? And what is the relationship between representations of the Resistance War and questions of Chinese nationalism and free speech? Yu Jie and Ge Hongbing offer controversial answers to these and other questions. Looking beyond the Japanese government's failure to repent for its war crimes, Yu insists that reconciliation need not require repentance and underlines instead both the shared nationalism of the two parties to the war and the importance of reconciliation for both nations. This is part of a continuing Japan Focus series on reconciliation and community in Northeast Asia of which the most recent contribution is Mel Gurtov's Reconciling Japan and China MS
The dissolution kinetics occurring on clay minerals are influenced by various factors, including pH, temperature and mineral lattice structure. However, the influence of the surfactant is rarely studied. In the present work, cationic surfactants were investigated in terms of the dissolution of clay minerals in acidic environments. Kaolinite was selected as the representative clay mineral. The cationic surfactant inhibited the dissolution of clay minerals because it limited the attack of H+ on the kaolinite surface and then inhibited the dissolution of kaolinite by modifying the hydrophilicity of the kaolinite surface towards hydrophobicity. The inhibition ability of the surfactant might be related to its molecular structure and the type of acid used in dissolution experiments.
Schistosomiasis is a parasitic disease that imposes a significant burden on society. The eggs are the primary pathogenic factor in schistosomiasis, and their accumulation in liver could lead to the formation of granulomas and liver fibrosis. However, the metabolic changes in liver resulting from schistosomiasis remain poorly understood. We established a mouse model of schistosomiasis japonica, where the eggs accumulate in the liver and form egg granulomas. We used mass spectrometry imaging to analyze the differences in metabolites among various liver regions, including the liver tissue from normal mice, the liver area outside the granulomas in schistosomiasis mice, and the granuloma region in schistosomiasis mice. There were significant differences in metabolites between different liver regions, which enriched in metabolic pathways such as the biosynthesis of unsaturated fatty acids, taurine and hypotaurine metabolism, glycerophospholipid metabolism, glycolysis/gluconeogenesis, purine metabolism, arachidonic acid metabolism, and bile secretion. In normal liver tissue, higher concentrations of oleic acid (FA (18:1)), eicosapentaenoic acid (FA (20:5)), and L-glutamine were observed. In liver regions outside the granulomas, D-glucose and pyruvic acid were elevated compared to those in normal mice. Taurine increased in the liver of schistosomiasis. Meanwhile, there were elevated uric acid and spermidine in the egg granulomas. We employed mass spectrometry imaging technology to investigate metabolic reprogramming in liver of Schistosoma japonicum-infected mice. We explored the spatial distribution of differential metabolites in liver of schistosomiasis including unsaturated fatty acids, taurine, glutamine, spermidine, and uric acid. Our research provides valuable insights for further elucidating metabolic reprogramming in schistosomiasis.
This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.
MicroRNAs (miRNAs) are endogenous, non-coding RNAs, which are functional in a variety of biological processes through post-transcriptional regulation of gene expression. However, the role of miRNAs in the interaction between Bacillus thuringiensis and insects remains unclear. In this study, small RNA libraries were constructed for B. thuringiensis-infected (Bt) and uninfected (CK) Spodoptera exigua larvae (treated with double-distilled water) using Illumina sequencing. Utilising the miRDeep2 and Randfold, a total of 233 known and 726 novel miRNAs were identified, among which 16 up-regulated and 34 down-regulated differentially expressed (DE) miRNAs were identified compared to the CK. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that potential target genes of DE miRNAs were associated with ABC transporters, fatty acid metabolism and MAPK signalling pathway which are related to the development, reproduction and immunity. Moreover, two miRNA core genes, SeDicer1 and SeAgo1 were identified. The phylogenetic tree showed that lepidopteran Dicer1 clustered into one branch, with SeDicer1 in the position closest to Spodoptera litura Dicer1. A similar phylogenetic relationship was observed in the Ago1 protein. Expression of SeDicer1 increased at 72 h post infection (hpi) with B. thuringiensis; however, expression of SeDicer1 and SeAgo1 decreased at 96 hpi. The RNAi results showed that the knockdown of SeDicer1 directly caused the down-regulation of miRNAs and promoted the mortality of S. exigua infected by B. thuringiensis GS57. In conclusion, our study is crucial to understand the relationship between miRNAs and various biological processes caused by B. thuringiensis infection, and develop an integrated pest management strategy for S. exigua via miRNAs.
We demonstrate efficient and economical all-solid-state post-compression based on dual-stage periodically placed thin fused silica plates driven by a more than 100 W ytterbium-doped yttrium aluminum garnet Innoslab amplifier seeded by a fiber frontend. Not only is a more than eight-fold pulse compression with 94% transmission achieved, but also the pulse quality and spatial mode are improved, which can be attributed to the compensation for the residual high-order dispersion and the spatial mode self-cleaning effect during the nonlinear process. It enables a high-power ultrafast laser source with 64 fs pulse duration, 96 W average power at 175 kHz repetition rates and good spatiotemporal quality. These results highlight that this all-solid-state post-compression can overcome the bandwidth limitation of Yb-based lasers with exceptional efficiency and mitigate the spatiotemporal degradation originating from the Innoslab amplifier and fiber frontend, which provides an efficient and economical complement for the Innoslab laser system and facilitates this robust and compact combination as a promising scheme for high-quality higher-power few-cycle laser generation.
The Righi–Leduc heat flux generated by the self-generated magnetic field in the ablative Rayleigh–Taylor instability driven by a laser irradiating thin targets is studied through two-dimensional extended-magnetohydrodynamic simulations. The perturbation structure gets into a low magnetization state though the peak strength of the self-generated magnetic field could reach hundreds of teslas. The Righi–Leduc effect plays an essential impact both in the linear and nonlinear stages, and it deflects the total heat flux towards the spike base. Compared to the case without the self-generated magnetic field included, less heat flux is concentrated at the spike tip, finally mitigating the ablative stabilization and leading to an increase in the velocity of the spike tip. It is shown that the linear growth rate is increased by about 10% and the amplitude during the nonlinear stage is increased by even more than 10% due to the feedback of the magnetic field, respectively. Our results reveal the importance of Righi–Leduc heat flux to the growth of the instability and promote deep understanding of the instability evolution together with the self-generated magnetic field, especially during the acceleration stage in inertial confinement fusion.
The construction of organic-inorganic hybrid ferroelectric materials with larger, high-polarity guest molecules intercalated in kaolinite (K) faces difficulties in terms of synthesis and uncertainty of structure-property relationships. The purpose of the present study was to optimize the synthesis method and to determine the mechanism of ferroelectric behavior of kaolinite intercalated with p-aminobenzamide (PABA), with an eye to improving the design of intercalation methods and better utilization of clay-based ferroelectric materials. The K-PABA intercalation compound (chemical formula Al2Si2O5(OH)4∙(PABA)0.7) was synthesized in an autoclave and then characterized using X-ray diffraction (XRD), infrared spectroscopy (IR), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). The experimental results showed that PABA expanded the kaolinite interlayer from 7.2 Å to 14.5 Å, and the orientation of the PABA molecule was ~70° from the plane of the kaolinite layers. The amino group of the PABA molecule was close to the Si sheet. The presence of intermolecular hydrogen bonds between kaolinite and PABA and among PABA molecules caused macro polarization of K-PABA and dipole inversion under the external electric field, resulting in K-PABA ferroelectricity. Simulation calculations using the Cambridge Sequential Total Energy Package (CASTEP) and the ferroelectricity test revealed the optimized intercalation model and possible ferroelectric mechanism.
Fast neutron absorption spectroscopy is widely used in the study of nuclear structure and element analysis. However, due to the traditional neutron source pulse duration being of the order of nanoseconds, it is difficult to obtain a high-resolution absorption spectrum. Thus, we present a method of ultrahigh energy-resolution absorption spectroscopy via a high repetition rate, picosecond duration pulsed neutron source driven by a terawatt laser. The technology of single neutron count is used, which results in easily distinguishing the width of approximately 20 keV at 2 MeV and an asymmetric shape of the neutron absorption peak. The absorption spectroscopy based on a laser neutron source has one order of magnitude higher energy-resolution power than the state-of-the-art traditional neutron sources, which could be of benefit for precisely measuring nuclear structure data.
To evaluate the mental health of paediatric cochlear implant users and analyse the relationship between six dimensions (movements, cognitive ability, emotion and will, sociality, living habits and language) and hearing and speech rehabilitation.
Methods
Eighty-two cochlear implant users were assessed using the Mental Health Survey Questionnaire. Age at implantation, time of implant use and listening modes were investigated. Categories of Auditory Performance and the Speech Intelligibility Rating Scale were used to score hearing and speech abilities.
Results
More recipients scored lower in cognitive ability and language. Age at implantation was statistically significant (p < 0.05) for movements, cognitive ability, emotion and will, and language. The time of implant usage and listening mode indicated statistical significance (p < 0.05) in cognitive ability, sociality and language.
Conclusion
Timely attention should be paid to the mental health of paediatric cochlear implant users, and corresponding psychological interventions should be implemented to make personalised rehabilitation plans.
Insect response to cold stress is often associated with adaptive strategies and chemical variation. However, low-temperature domestication to promote the cold tolerance potential of Bactrocera dorsalis and transformation of main internal substances are not clear. Here, we use a series of low-temperature exposure experiments, supercooling point (SCP) measurement, physiological substances and cryoprotectants detection to reveal that pre-cooling with milder low temperatures (5 and 10°C) for several hours (rapid cold hardening) and days (cold acclimation) can dramatically improve the survival rate of adults and pupae under an extremely low temperature (−6.5°C). Besides, the effect of rapid cold hardening for adults could be maintained even 4 h later with 25°C exposures, and SCP was significantly declined after cold acclimation. Furthermore, content of water, fat, protein, glycogen, sorbitol, glycerol and trehalose in bodies were measured. Results showed that water content was reduced and increased content of proteins, glycogen, glycerol and trehalose after two cold domestications. Our findings suggest that rapid cold hardening and cold acclimation could enhance cold tolerance of B. dorsalis by increasing proteins, glycerol, trehalose and decreasing water content. Conclusively, identifying a physiological variation will be useful for predicting the occurrence and migration trend of B. dorsalis populations.
Sleep apnea is one of the most common sleep disorders. The consequences of undiagnosed sleep apnea can be very serious, increasing the risk of high blood pressure, heart disease, stroke, and Alzheimer’s disease over a long period of time. However, many people are often unaware of their condition. The gold standard for diagnosing sleep apnea is nighttime polysomnography monitoring in a specialized sleep laboratory. However, these diagnoses are expensive and the number of beds is limited, and there is insufficient monitoring in terms of time dimension. Existing methods for automated detection use no more than three physiological signals, but all other signals are also associated with the patient’s sleep. In addition, the limited amount of medical real annotation data, especially abnormal samples, lead to weak model generalization capability. The gap between model generalization capability and medical field needs still exists. In this paper, we propose a method for integrating medical interpretation rules into a long short-term memory neural network based on self-attention with multichannel respiratory signals as input. We obtain attention weights through a token-level attention mechanism and then extract key rules of medical interpretation to assist the weights, improving model generalization and reducing the dependence on data volume. Compared with the best prediction performance of existing methods, the average improvements of our method in accuracy, precision, and f1-score are 3.26%, 7.03%, and 1.78%, respectively. The algorithm tested the performance of our model on the Sleep Heart Health Study data set and found that the model outperformed existing methods and could help physicians make decisions in their practices.