Heterojunction polarization enhancement and shielding for AlGaN-based solar-blind ultraviolet avalanche detectors.

AlGaN-based solar-blind ultraviolet avalanche detectors have huge potentials in the fields of corona discharge monitoring, biological imaging, etc. Here, we study the impact of the heterojunction polarization-related effects on the AlGaN-based solar-blind ultraviolet avalanche detectors. Our work confirms that the polarization heterojunction is beneficial to reducing avalanche bias and lifting avalanche gain by improving the electric field in the depletion region, while the polarization-induced fixed charges will lead to a redistribution of the electrons, in turn shielding the charges and weakening the electric field enhancement effect. This shielding effect will need external bias to eliminate, and that is why the polarization heterojunction cannot work at relatively low bias but has an enhancement effect at high bias. Controlling the doping level between the hetero-interface can affect the shielding effect. An unintentionally doped polarization heterojunction can effectively reduce the shielding effect, thus reducing the avalanche bias. The conclusions also hold true for the negative polarization regime. We believe our findings can provide some useful insights for the design of the AlGaN-based solar-blind ultraviolet detectors.

Synthetic Mn3Ce2O5-Cluster Mimicking the Oxygen-Evolving Center in Photosynthesis.

The photosynthetic oxygen-evolving center (OEC) is a unique Mn4CaO5-cluster that catalyzes water splitting into electrons, protons, and dioxygen. Precisely structural and functional mimicking of the OEC is a long-standing challenge and pressingly needed for understanding the structure-function relationship and catalytic mechanism of O-O bond formation. Herein we report two simple and robust artificial Mn3Ce2O5-complexes that display a remarkable structural similarity to the OEC in regarding of the ten-atom core (five metal ions and five oxygen bridges) and the alkyl carboxylate peripheral ligands. This Mn3Ce2O5-cluster can catalyze the water-splitting reaction on the surface of ITO electrode. These results clearly show that cerium can structurally and functionally replace both calcium and manganese in the cluster. Mass spectroscopic measurements demonstrate that the oxide bridges in the cluster are exchangeable and can be rapidly replaced by the isotopic oxygen of H218O in acetonitrile solution, which supports that the oxide bridge(s) may serve as the active site for the formation of O-O bond during the water-splitting reaction. These results would contribute to our understanding of the structure-reactivity relationship of both natural and artificial clusters and shed new light on the development of efficient water-splitting catalysts in artificial photosynthesis.

Effect of Face Masks on Voice Quality Associated with Young and Older Chinese Adult Speakers.

OBJECTIVES: Face masks have become important after the pandemic, but the change in voice when wearing a face mask is still unclear. The study investigated the effect of face masks on the acoustic and perceptual characteristics of voice quality associated with young and older Chinese adults. METHODS: Voice samples of the sustained vowel /a/ and continuous speech produced by 44 older and 61 young adults with and without an ASTM level-3 surgical face mask were recorded and analyzed. Perceptual and acoustic parameters including mean fundamental frequency (F0) and intensity, perturbation measures (jitter and shimmer), harmonic-to-noise ratio (HNR), smoothed cepstral peak prominence (CPPs), and long-term average spectrum (LTAS) measures were obtained and compared. RESULTS: When comparing masked to unmasked voices, for both male and female speakers, F0 and intensity showed no significant changes, except for F0 of continuous speech, which increased significantly. Meanwhile, perturbation measures such as jitter and shimmer were reduced, while HNR and CPPs increased. In addition, LTAS measures included low-frequency mean spectral energy (MSE), high-frequency MSE, and spectral tilt (ST), which were different. For perceptual measures, the overall grade of dysphonia, and roughness were reduced, except for the breathiness among older male speakers, while the other vocal qualities were not changed. Between young and older speakers, significant differences in shimmer, CPPs, and perceived breathiness among male speakers, and low-frequency MSE among female speakers were found. CONCLUSION: Wearing a surgical mask appeared to change the perceived voice quality. This is supported by the change in perturbation and LTAS measures, and HNR and CPPs values. In addition, some differences between young and older adults were observed. Oral Communication effectiveness may be affected when wearing surgical masks due to changes in voice quality. Additionally, clinicians need to exercise hightened caution in evaluating the voice quality of clients when wearing face masks.

Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning.

BACKGROUND: Prior studies have suggested a potential relationship between osteoporosis and sarcopenia, both of which can present symptoms of compromised mobility. Additionally, fractures among the elderly are often considered a common outcome of both conditions. There is a strong correlation between fractures in the elderly population, decreased muscle mass, weakened muscle strength, heightened risk of falls, and diminished bone density. This study aimed to pinpoint crucial diagnostic candidate genes for osteoporosis patients with concomitant sarcopenia. METHODS: Two osteoporosis datasets and one sarcopenia dataset were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes were identified using Limma and Weighted Gene Co-expression Network Analysis (WGCNA), followed by functional enrichment analysis, construction of protein-protein interaction (PPI) networks, and application of a machine learning algorithm (least absolute shrinkage and selection operator (LASSO) regression) to determine candidate hub genes for diagnosing osteoporosis combined with sarcopenia. Receiver operating characteristic (ROC) curves and column line plots were generated. RESULTS: The merged osteoporosis dataset comprised 2067 DEGs, with 424 module genes filtered in sarcopenia. The intersection of DEGs between osteoporosis and sarcopenia module genes consisted of 60 genes, primarily enriched in viral infection. Through construction of the PPI network, 30 node genes were filtered, and after machine learning, 7 candidate hub genes were selected for column line plot construction and diagnostic value assessment. Both the column line plots and all 7 candidate hub genes exhibited high diagnostic value (area under the curve ranging from 1.00 to 0.93). CONCLUSION: We identified 7 candidate hub genes (PDP1, ALS2CL, VLDLR, PLEKHA6, PPP1CB, MOSPD2, METTL9) and constructed column line plots for osteoporosis combined with sarcopenia. This study provides reference for potential peripheral blood diagnostic candidate genes for sarcopenia in osteoporosis patients.

Structure-Assisted Boronic Acid Implanted Mesoporous Metal-Organic Frameworks for Specific Extraction of cis-Diol Molecules.

cis-Diol-containing molecules, an essential type of compounds in living organisms, have attracted intensive research interest from various fields. The analysis of cis-diol-containing molecules is still suffering from some drawbacks, including low abundance and abundant interference. Metal-organic frameworks (MOFs) have proven to be an ideal sorbent for sample preparation. However, most of the reported MOFs are mainly restricted to a microporous regime (pore size <2 nm), which greatly limits the application. Herein, a facile strategy is established to construction of boronate affinity MOFs via the postsynthetic ligand-exchange process. Owing to the fact that the ligand-exchange process was assisted by the structural integrity of the primitive metal-organic framework and the great compatibility of click chemistry, the obtained EPBA-PCN-333(Fe) is able to realize the maximum maintaining the porosity and crystallinity of the parent material. Several intriguing features of EPBA-PCN-333(Fe) (e.g., excellent selectivity, efficient diffusion, good accessibility, and size exclusion effect) are experimentally demonstrated via a series of cis-diol-containing molecules with different molecular sizes (small molecules, glycopeptides, and glycoproteins). The binding performance of EPBA-PCN-333(Fe) is evaluated by employing catechol as the test molecule (binding capacity: 0.25 mmol/g, LOD: 200 ng/mL). Finally, the real-world applications of EPBA-PCN-333(Fe) were demonstrated by the detection of nucleosides of human urine samples.

Improved cure rate of periprosthetic joint infection through targeted antibiotic therapy based on integrated pathogen diagnosis strategy.

Objectives: This study aimed to determine whether combined of pathogen detection strategies, including specimen acquisition, culture conditions, and molecular diagnostics, can improve treatment outcomes in patients with periprosthetic joint infections (PJI). Methods: This retrospective study included suspected PJI cases from three sequential stages at our institution: Stage A (July 2012 to June 2015), Stage B (July 2015 to June 2018), and Stage C (July 2018 to June 2021). Cases were categorized into PJI and aseptic failure (AF) groups based on European Bone and Joint Infection Society (EBJIS) criteria. Utilization of pathogen diagnostic strategies, pathogen detection rates, targeted antibiotic prescription rates, and treatment outcomes were analyzed and compared across the three stages. Results: A total of 165 PJI cases and 38 AF cases were included in this study. With the progressive implementation of the three optimization approaches across stages A, B and C, pathogen detection rates exhibited a gradual increase (χ2 = 8.282, P=0.016). Similarly, utilization of targeted antibiotic therapy increased stepwise from 57.1% in Stage A, to 82.3% in Stage B, and to 84% in Stage C (χ2 = 9.515, P=0.009). The 2-year infection control rate exceeded 90% in both stages B and C, surpassing stage A (71.4%) (χ2 = 8.317, P=0.011). Combined application of all three optimized protocols yielded the highest sensitivity of 91.21% for pathogen detection, while retaining higher specificity of 92.11%. Conclusion: The utilization of combined pathogen diagnostic strategies in PJI can increase pathogen detection rates, improve targeted antibiotic prescription, reduce the occurrence of antibiotic complications, and achieve better treatment outcomes.

The effects of dietary macronutrient composition on resting energy expenditure following active weight loss: A systematic review and meta-analysis.

A systematic review and meta-analysis was conducted to evaluate the relative effectiveness of different dietary macronutrient patterns on changes in resting energy expenditure (REE) in relation to weight loss, categorized as minimal (<5%) and moderate to high (>5%). Changes in REE were assessed using a DerSimonian and Laird random-effects meta-analysis. A diet lower in carbohydrates (CHO) or higher in fat and protein was associated with smaller reductions in REE, with these trends being more pronounced among participants who experienced moderate to high weight loss. Adjusted meta-regression analysis indicated that, within the participants who experienced moderate to high weight loss, each 1% increase in CHO intake was associated with a reduction of 2.30 kcal/day in REE (95% CI: -4.11 to -0.47, p = 0.013). In contrast, a 1% increase in protein and fat intake was correlated with an increase in REE by 3.00 (95% confidence interval [CI] [1.02, 5.07], p = 0.003) and 0.5 (95% CI [-2.43, 3.41], p = 0.740) kcal/day, respectively. No significant associations were found among participants who experienced minimal weight loss. These findings indicate that, under a caloric deficit, the impact of dietary macronutrient composition on REE may vary depending on the degree of weight loss and individual metabolic responses.

Multiomics-based molecular subtyping based on the commensal microbiome predicts molecular characteristics and the therapeutic response in breast cancer.

The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.

An Expert-Knowledge-Based Graph Convolutional Network for Skeleton- Based Physical Rehabilitation Exercises Assessment.

Physical therapists play a crucial role in guiding patients through effective and safe rehabilitation processes according to medical guidelines. However, due to the therapist-patient imbalance, it is neither economical nor feasible for therapists to provide guidance to every patient during recovery sessions. Automated assessment of physical rehabilitation can help with this problem, but accurately quantifying patients' training movements and providing meaningful feedback poses a challenge. In this paper, an Expert-knowledge-based Graph Convolutional approach is proposed to automate the assessment of the quality of physical rehabilitation exercises. This approach utilizes experts' knowledge to improve the spatial feature extraction ability of the Graph Convolutional module and a Gated pooling module for feature aggregation. Additionally, a Transformer module is employed to capture long-range temporal dependencies in the movements. The attention scores and weight matrix obtained through this approach can serve as interpretability tools to help therapists understand the assessment model and assist patients in improving their exercises. The effectiveness of the proposed method is verified on the KIMORE dataset, achieving state-of-the-art performance compared to existing models. Experimental results also illustrate the interpretability of the method in both spatial and temporal dimensions.

Chronic increasing nitrogen and endogenous phosphorus release from sediment threaten to the water quality in a semi-humid region reservoir.

The water quality in the drinking water reservoir directly affects people's quality of life and health. When external pollution input is effectively controlled, endogenous release is considered the main cause of water quality deterioration. As the major nitrogen (N) and phosphorus (P) sources in reservoirs, sediment plays a vital role in affecting the water quality. To understand the spatial and temporal variation of N and P in the sediment, this study analyzed the current characteristics and cumulative effects of a semi-humid reservoir, Yuqiao Reservoir, in North China. The N and P concentrations in the reservoir sediment were decreased along the flow direction, while the minimum values were recorded at the central sediment profile. External input and algal deposition were the main factors leading to higher sediment concentrations in the east (Re-E) and west (Re-W) areas of reservoir sediment profiles. According to the long-term datasets, the peaks of both sediment total nitrogen content and deposition rate were observed in the 2010s, which has increased about three times and six times than in the1990s, respectively. Therefore, the increase in phosphorus concentration may be the main reason for eutrophication in water in recent years. The mineralization of organic matter has a significant promoting effect on releasing N and P from sediments, which will intensify eutrophication in water dominated by P and bring huge challenges to water environment management. This study highlights that the current imbalance in N and P inputs into reservoirs and the endogenous P release from sediment will have a significant impact on water quality.

Corrigendum: Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.

[This corrects the article DOI: 10.3389/fimmu.2023.1340446.].

The effect of rehabilitation time on functional recovery after arthroscopic rotator cuff repair: a systematic review and meta-analysis.

Objective: We compared the effects of early and delayed rehabilitation on the function of patients after rotator cuff repair by meta-analysis to find effective interventions to promote the recovery of shoulder function. Methods: This meta-analysis was registered in PROSPERO (CRD42023466122). We manually searched the randomized controlled trials (RCTs) in the Cochrane Library, Pubmed, Cochrane Library, EMBASE, the China National Knowledge Infrastructure (CNKI), the China VIP Database (VIP), and the Wanfang Database to evaluate the effect of early and delayed rehabilitation after arthroscopic shoulder cuff surgery on the recovery of shoulder joint function. Review Manager 5.3 software was used to analyze the extracted data. Then, the PEDro scale was employed to appraise the methodological quality of the included research. Results: This research comprised nine RCTs and 830 patients with rotator cuff injuries. According to the findings of the meta-analysis, there was no discernible difference between the early rehabilitation group and the delayed rehabilitation group at six and twelve months after the surgery in terms of the VAS score, SST score, follow-up rotator cuff healing rate, and the rotator cuff retear rate at the final follow-up. There was no difference in the ASES score between the early and delayed rehabilitation groups six months after the operation. However, although the ASES score in the early rehabilitation group differed significantly from that in the delayed rehabilitation group twelve months after the operation, according to the analysis of the minimal clinically important difference (MCID), the results have no clinical significance. Conclusions: The improvement in shoulder function following arthroscopic rotator cuff surgery does not differ clinically between early and delayed rehabilitation. When implementing rehabilitation following rotator cuff repair, it is essential to consider the paradoxes surrounding shoulder range of motion and tendon anatomic healing. A program that allows for flexible progression based on the patient's ability to meet predetermined clinical goals or criteria may be a better option.

Lithium tantalate photonic integrated circuits for volume manufacturing.

Electro-optical photonic integrated circuits (PICs) based on lithium niobate (LiNbO3) have demonstrated the vast capabilities of materials with a high Pockels coefficient1,2. They enable linear and high-speed modulators operating at complementary metal-oxide-semiconductor voltage levels3 to be used in applications including data-centre communications4, high-performance computing and photonic accelerators for AI5. However, industrial use of this technology is hindered by the high cost per wafer and the limited wafer size. The high cost results from the lack of existing high-volume applications in other domains of the sort that accelerated the adoption of silicon-on-insulator (SOI) photonics, which was driven by vast investment in microelectronics. Here we report low-loss PICs made of lithium tantalate (LiTaO3), a material that has already been adopted commercially for 5G radiofrequency filters6 and therefore enables scalable manufacturing at low cost, and it has equal, and in some cases superior, properties to LiNbO3. We show that LiTaO3 can be etched to create low-loss (5.6 dB m-1) PICs using a deep ultraviolet (DUV) stepper-based manufacturing process7. We demonstrate a LiTaO3 Mach-Zehnder modulator (MZM) with a half-wave voltage-length product of 1.9 V cm and an electro-optic bandwidth of up to 40 GHz. In comparison with LiNbO3, LiTaO3 exhibits a much lower birefringence, enabling high-density circuits and broadband operation over all telecommunication bands. Moreover, the platform supports the generation of soliton microcombs. Our work paves the way for the scalable manufacture of low-cost and large-volume next-generation electro-optical PICs.

A novel controllable capacitor commutation based superconducting hybrid direct current breaker.

Featuring low power loss and high reliability, voltage source converter medium voltage direct current (VSC-MVDC) systems have been widely employed for grid-tied renewable energy applications. To maintain high operational safety, circuit breakers are needed to isolate faulted powerlines by comprehensively considering response speed and installation cost. Research efforts have been put to realizing DC fault isolation by coordinating resistive type superconducting fault current limiter (R-SFCL) and integrated-gate-commutated-thyristor (IGCT) based hybrid DC circuit breaker. In this paper, a controllable current commutation based superconducting DC circuit breaker (CCCB-SDCCB) is proposed. By integrating R-SFCL with IGCT based hybrid DC circuit breakers, the current interrupting capacity can be greatly enlarged with the advantage of low cost and fast speed, and hence the overall cost for suppress large fault currents can be greatly reduced for MVDC systems. In addition, a new current injection circuit branch using H-bridge structure is designed to recycle the residual capacitor voltage from the previous fault stage to trigger the IGCTs without the capacitor pre-charging process. Simulation results show that the fault current can be successfully suppressed from 24.2 to 2.1 kA and fully interrupted within 4.11 ms by the proposed CCCB-SDCCB.

Precision Colorectal Cancer Fecal Immunological Test Screening With Fecal-Hemoglobin-Concentration-Guided Interscreening Intervals.

Importance: Given a gradient relationship between fecal hemoglobin (f-Hb) concentration and colorectal neoplasia demonstrated previously, using f-Hb-guided interscreening interval has increasingly gained attention in population-based fecal immunological test (FIT), but it is very rare to address how to implement such a precision strategy and whether it can economize the use of FIT and colonoscopy. Objective: To demonstrate the applicability of personalized colorectal cancer (CRC) screening with f-Hb-guided screening intervals to reduce the number of FITs and colonoscopy with as equivalent efficacy as universal biennial screening equivalent efficacy as universal biennial screening. Design, Setting, and Participants: A retrospective cohort study for developing f-Hb-guided precision interscreening interval was conducted using data on a Taiwanese biennial nationwide FIT screening program that enrolled more than 3 million participants aged 50 to 74 years between 2004 and 2014. The cohort was followed up over time until 2019 to ascertain colorectal neoplasia and causes of death. A comparative study was further designed to compare the use of FIT and colonoscopy between the personalized f-Hb-guided group and the universal biennial screening group given the equivalent efficacy of reducing CRC-related outcomes. Main Outcomes and Measurements: A spectrum of f-Hb-guided intervals was determined by using the Poisson regression model given the equivalent efficacy of a universal biennial screening. The use of FIT and colonoscopy for the pragmatic f-Hb-guided interval group was measured compared with the universal biennial screening group. Data analysis was performed from September 2022 to October 2023. Results: Using data from the 3 500 250 participants (mean [SD] age, 57.8 [6.0] years) enrolled in the Taiwanese biennial nationwide FIT screening program, an incremental increase in baseline f-Hb associated with colorectal neoplasia and CRC mortality consistently was observed. Participants with different f-Hb levels were classified into distinct risk categories. Various screening intervals by different f-Hb levels were recommended. Using the proposed f-Hb-guided screening intervals, it was found that the personalized method was imputed to reduce the number of FIT tests and colonoscopies by 49% and 28%, respectively, compared with the universal biennial screening. Conclusion and Relevance: The gradient relationship between f-Hb and colorectal neoplasia and CRC mortality was used to develop personalized FIT screening with f-Hb-guided screening intervals. Such a precision interscreening interval led to the reduced use of FIT test and colonoscopy without compromising the effectiveness of universal biennial screening.

Investigating quantitative approach for microalgal biomass using deep convolutional neural networks and image recognition.

The effective monitoring of microalgae cultivation is crucial for optimizing their energy utilization efficiency. In this paper, a quantitative analysis method, using microalgae images based on two convolutional neural networks, EfficientNet (EFF) and residual network (RES), is proposed. Suspension samples prepared from two types of dried microalgae powders, Rhodophyta (RH) and Spirulina (SP), were used to mimic real microalgae cultivation settings. The method's prediction accuracy of the algae concentration ranges from 0.94 to 0.99. RH, with a distinctively pronounced red-green-blue value shift, achieves a higher prediction accuracy than SP. The prediction results of the two algorithms were significantly superior to those of a linear regression. Additionally, RES outperforms EFF in terms of its generalization ability and robustness, which is attributable to its distinct residual block architecture. The RES provides a viable approach for the image-based quantitative analysis.

Adenosine kinase inhibits ß-cell proliferation by upregulating DNA methyltransferase 3A expression.

AIM: To investigate the effects of adenosine kinase (ADK), a key enzyme in determining intracellular adenosine levels, on ß cells, and their underlying mechanism. METHODS: Genetic animal models and transgenic immortalized cells were applied to study the effect of ADK on islet beta-cell proliferation and function. The beta-cell mass and response to glucose were measured in vivo using mice with beta-cell-specific ADK overexpression, and in vitro using ADK-overexpressed immortalized beta-cell. RESULTS: The expression of ADK in human islets at high abundance, especially in ß cells, was decreased during the process of ß-cell proliferation. Additionally, a transgenic mouse model (ADKtg/tg /Mip-Cre) was generated wherein the mouse Insulin1 gene promoter specifically overexpressed ADK in pancreatic ß cells. The ADKtg/tg /Mip-Cre model exhibited impaired glucose tolerance, decreased fasting plasma insulin, loss of ß-cell mass, and inhibited ß-cell proliferation. Proteomic analysis revealed that ADK overexpression inhibited the expression of several proteins that promote cell proliferation and insulin secretion. Upregulating ADK in the ß-cell line inhibited the expression of ß-cell related regulatory molecules, including FoxO1, Appl1, Pxn, Pdx-1, Creb and Slc16a3. Subsequent in vitro experiments indicated that the inhibition of ß-cell proliferation and the decreased expression of Pdx-1, Creb and Slc16a3 were rescued by DNA methyltransferase 3A (DNMT3A) knockdown in ß cells. CONCLUSION: In this study, we found that the overexpression of ADK decreased the expression of several genes that regulate ß cells, resulting in the inhibition of ß-cell proliferation and dysfunction by upregulating the expression of DNMT3A.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Background: Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods: Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results: A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

Bioinspired Robust Gas-Permeable On-Skin Electronics: Armor-Designed Nanoporous Flash Graphene Assembly Enhancing Mechanical Resilience.

Soft on-skin electrodes play an important role in wearable technologies, requiring attributes such as wearing comfort, high conductivity, and gas permeability. However, conventional fabrication methods often compromise simplicity, cost-effectiveness, or mechanical resilience. In this study, a mechanically robust and gas-permeable on-skin electrode is presented that incorporates Flash Graphene (FG) integrated with a bioinspired armor design. FG, synthesized through Flash Joule Heating process, offers a small-sized and turbostratic arrangement that is ideal for the assembly of a conductive network with nanopore structures. Screen-printing is used to embed the FG assembly into the framework of polypropylene melt-blown nonwoven fabrics (PPMF), forming a soft on-skin electrode with low sheet resistance (125.2 ± 4.7 Ω/□) and high gas permeability (≈10.08 mg cm⁻2 h⁻¹). The "armor" framework ensures enduring mechanical stability through adhesion, washability, and 10,000 cycles of mechanical contact friction tests. Demonstrating capabilities in electrocardiogram (ECG) and electromyogram (EMG) monitoring, along with serving as a self-powered triboelectric sensor, the FG/PPMF electrode holds promise for scalable, high-performance flexible sensing applications, thereby enriching the landscape of integrated wearable technologies.

Depression in Polycystic Ovary Syndrome: Focusing on Pathogenesis and Treatment.

Polycystic ovary syndrome (PCOS) is one of the most prevalent gynecological endocrine conditions affecting reproductive women. It can feature a variety of symptoms, such as obesity, insulin resistance, skin conditions, and infertility. Women with PCOS are susceptible to illnesses including mood disorders, diabetes, hypertension, and dyslipidemia. Among them, depression is the most common in PCOS and has a detrimental effect on quality of life. Depression may occasionally develop due to the pathological traits of PCOS, but its exact pathogenesis in PCOS have eluded researchers to date. Therefore, there is an urgent need to explore the pathogenesis and treatments of depression in PCOS. The present review discusses the epidemiology of depression in PCOS, potential pathogenic mechanisms underlying PCOS and depression, as well as some potential factors causing depression in PCOS, including obesity, insulin resistance, hyperandrogenism, inflammation, and infertility. Meanwhile, some common treatment strategies for depression in PCOS, such as lifestyle intervention, acupuncture, oral contraceptive pills, psychological intervention, and insulin-sensitizer, are also reviewed. To fully understand the pathogenesis and treatment of depression in PCOS, a need remains for future large-scale multi-center randomized controlled trials and in-depth mechanism studies. Appeared originally in Front Psychiatry 2022; 13:1001484.