Association of metabolic syndrome and sarcopenia with all-cause and cardiovascular mortality: a prospective cohort study based on the NHANES.

Background: Metabolic syndrome (MetS) and sarcopenia (SP) have emerged as significant public health concerns in contemporary societies, characterized by shared pathophysiological mechanisms and interrelatedness, leading to profound health implications. In this prospective cohort study conducted within a US population, we aimed to examine the influence of MetS and SP on all-cause and cardiovascular mortality. Methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) III for the years 1999-2006 and 2011-2018, and death outcomes were ascertained by linkage to National Death Index (NDI) records through December 31, 2019. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause and cardiovascular mortality. In addition, subgroup and sensitivity analyses were conducted to test the robustness of the results. Results: Over a median follow-up period of 13.3 years (95% CI: 12.8-13.8), 1714 deaths were observed. The groups characterized by MetS-/SP+, MetS+/SP-, and MetS+/SP+ exhibited higher all-cause mortality rates in comparison to the MetS-/SP- group, with the MetS+/SP+ group (HR 1.76, 95% CI: 1.37-2.25) displaying the highest all-cause mortality. Increased cardiovascular mortality was observed in the MetS+/SP- (HR 1.84, 95% CI: 1.24-2.72), and MetS+/SP+ groups (HR 2.39, 95% CI: 1.32-4.35) compared to the MetS-/SP- group, whereas it was not statistically significant in the MetS-/SP+ group. However, among males and individuals aged < 60, the presence of both MetS and SP (MetS+/SP+ group) was found to be significantly associated with a higher risk of all-cause and cardiovascular mortality. Conclusion: The coexistence of MetS and SP increased the risk of all-cause and cardiovascular mortality, particularly in males and in nonelderly populations. Individuals with either MetS or SP may require more careful management to prevent the development of other diseases and thereby reduce mortality.

The effect of intelligent management interventions in intensive care units to reduce false alarms: An integrative review.

Objective: In intensive care units (ICU), frequent false alarms from medical equipment can cause alarm fatigue among nurses, which might lead to delayed or missed responses and increased risk of adverse patient events. This review was conducted to evaluate the effectiveness of intelligent management interventions to reduce false alarms in ICU. Method: Following the framework of Whitmore and Knafl, the reviewers systematically searched six databases: PubMed, EMBASE, CINAHL, OVID, Cochrane Library, and Scopus, and studies included intelligent management of clinical alarms published in the English or Chinese language from the inception of each database to December 2022 were retrieved. The researchers used the PICOS framework to formulate the search strategy, developed keywords, screened literature, and assessed the studies' quality using the Joanna Briggs Institute-Meta-Analysis of Statistics, Assessment, and Review Instrument (JBI-MAStARI). The review was preregistered on PROSPERO (CRD42023411552). Results: Seven studies met the inclusion criteria. The results showed that different interventions for intelligent management of alarms were beneficial in reducing the number of false alarms, the duration of alarms, the response time to important alarms for nurses, and the alarm fatigue levels among nurses. Positive results were found in practice after the application of the novel alarm management approaches. Conclusion: Intelligent management intervention may be an effective way to reduce false alarms. The application of systems or tools for the intelligent management of clinical alarms is urgent in hospitals. To ensure more effective patient monitoring and less distress for nurses, more alarm management approaches combined with artificial intelligence will be needed in the future to enable accurate identification of critical alarms, ensure nurses are responding accurately to alarms, and make a real difference to alarm-ridden healthcare environments.

Topical antimitotic treatments for plantar warts are more beneficial: A Bayesian network meta-analysis of randomized controlled trials.

BACKGROUND: Plantar warts are common infectious cutaneous growths causing severe physiological and psychological discomforts in patients and heaving global financial burdens. However, paucity of clear-cut guidelines for plantar warts, selecting appropriate treatments for plantar warts remains challenging. The objective of the study is to evaluate the efficacy and safety of common treatments for plantar warts. METHODS: PubMed, EMbase, and The Cochrane Library were searched from inception to March 1, 2023 for randomized controlled trials (RCTs) of plantar warts. The primary outcome (complete response) and secondary outcome (recurrence and pain) were extracted and combined using Bayesian network meta-analysis (NMA) with random-effect and fixed-effect models. RESULTS: Totally, 33 RCTs were included in the systematic review and quantitative NMA. In NMA of complete response, topical application of 1% cantharidin, 20% podophylotoxin, 30% salicylic acid (CPS), microneedles plus bleomycin (MNB), and intralesional bleomycin injection (INB) were the only three treatments significantly superior to no treatment (NT) and CPS was of the highest possibility to be the top-ranked treatment (SUCRA = 0.9363). However, traditional warts treatments, salicylic acid (SA) and cryotherapy were not superior to NT. CONCLUSIONS: The NMA has produced evidence for using CPS, MNB, and INB, which are all topical antimitotic treatments, to improve the management of plantar warts. The classic treatment modalities for plantar warts, including SA and cryotherapy, may play a less important role in the clinical practice of plantar warts.

Dual-plasmonic Au@Cu7S4 yolk@shell nanocrystals for photocatalytic hydrogen production across visible to near infrared spectral region.

Near infrared energy remains untapped toward the maneuvering of entire solar spectrum harvesting for fulfilling the nuts and bolts of solar hydrogen production. We report the use of Au@Cu7S4 yolk@shell nanocrystals as dual-plasmonic photocatalysts to achieve remarkable hydrogen production under visible and near infrared illumination. Ultrafast spectroscopic data reveal the prevalence of long-lived charge separation states for Au@Cu7S4 under both visible and near infrared excitation. Combined with the advantageous features of yolk@shell nanostructures, Au@Cu7S4 achieves a peak quantum yield of 9.4% at 500 nm and a record-breaking quantum yield of 7.3% at 2200 nm for hydrogen production in the absence of additional co-catalysts. The design of a sustainable visible- and near infrared-responsive photocatalytic system is expected to inspire further widespread applications in solar fuel generation. In this work, the feasibility of exploiting the localized surface plasmon resonance property of self-doped, nonstoichiometric semiconductor nanocrystals for the realization of wide-spectrum-driven photocatalysis is highlighted.

Developing a theory-driven framework for a web-based intervention to improve transition in childhood cancer survivors: a protocol of realist synthesis.

BACKGROUNDS AND PURPOSE: Childhood cancer survivors (CCSs) who transition through adolescence and enter young adulthood may suffer psychological, cognitive, social, fertility, and sexual issues and concerns. There is an urgent need for comprehensive intervention strategies to improve the transition of CCSs. Web-based technologies are gaining momentum as a new mechanism to provide healthcare and education for adolescents. However, previous frameworks have been limited in their effectiveness in explaining web-based interventions.This realist synthesis aims to synthesise current evidence on transition of CCSs to develop a framework for web-based interventions. The framework can foster understanding of the integrity of web-based intervention implementation chain, examine which mechanistic factors will be triggered by web-based interventions, note and examine the flows, blockages and points of contention in the implementation, to refine web-based interventions. METHOD AND ANALYSIS: A realist synthesis that adheres to the Realist and Meta-narrative Evidence Syntheses-Evolving Standard will be used. Studies will be identified through PubMed, Web of Science, EMBASE, PsycINFO, CINAHL, Ovid and Cochrane Library from the period of January 2005 to May 2023. We will also search the reference lists provided in relevant studies and reviews. Articles will be screened based on two principles: (1) Relevance: does the research address the initial programme theory? (2) Rigour: whether a particular inference drawn by the original researcher has sufficient weight to make a methodologically credible contribution to the test of the initial programme theory. No restrictions regarding the design or language of publication will be considered. ETHICS AND DISSEMINATION: As a review, ethical approval is not required. The results from this study will be presented at international conferences and disseminated through peer-reviewed publications. Patients and the public will be involved in the dissemination plans.

Extraocular muscle volume index at the orbital apex with optic neuritis: a combined parameter for diagnosis of dysthyroid optic neuropathy.

OBJECTIVES: To evaluate the diagnostic performance of the extraocular muscle volume index at the orbital apex (AMI) and the signal intensity ratio (SIR) of the optic nerve in dysthyroid optic neuropathy (DON). METHODS: Clinical data and magnetic resonance imaging were collected retrospectively from 63 Graves' ophthalmopathy patients, including 24 patients with DON and 39 without DON. The volume of these structures was obtained by reconstructing their orbital fat and extraocular muscles. The SIR of the optic nerve and axial length of eyeball were also measured. The posterior 3/5 of the retrobulbar space volume was used as the orbital apex to compare parameters in patients with or without DON. Area under the receiver operating characteristic curve (AUC) analysis was used to select the morphological and inflammatory parameters with the highest diagnostic value. A logistic regression was performed to identify the risk factors of DON. RESULTS: One hundred twenty-six orbits (35 with DON and 91 without DON) were analyzed. Most of the parameters in DON patients were significantly higher than in non-DON patients. However, the SIR 3 mm behind the eyeball of the optic nerve and AMI had the highest diagnostic value in these parameters and are independent risk factors of DON by stepwise multivariate logistic regression analysis. Combining AMI and SIR had a higher diagnostic value than a single index. CONCLUSIONS: Combining AMI with SIR 3 mm behind the eyeball's orbital nerve can be a potential parameter for diagnosing DON. CLINICAL RELEVANCE STATEMENT: The present study provided a quantitative index based on morphological and signal changes to assess the DON, allowing clinicians and radiologists to monitor DON patients timely. KEY POINTS: The extraocular muscle volume index at the orbital apex (AMI) has excellent diagnostic performance for dysthyroid optic neuropathy. A signal intensity ratio (SIR) of 3 mm behind the eyeball has a higher AUC compared to other slices. Combining AMI and SIR has a higher diagnostic value than a single index.

High-speed scanless entire bandwidth mid-infrared chemical imaging.

Mid-infrared spectroscopy probes molecular vibrations to identify chemical species and functional groups. Therefore, mid-infrared hyperspectral imaging is one of the most powerful and promising candidates for chemical imaging using optical methods. Yet high-speed and entire bandwidth mid-infrared hyperspectral imaging has not been realized. Here we report a mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane. This technique offers a lateral resolution of 15 µm, and the field of view is adjustable between 800 µm × 600 µm to 12 mm × 9 mm. The hyperspectral imaging produces a 640 × 480 pixel image in 8 s, which covers a spectral range of 640-3015 cm-1, comprising 1069 wavelength points and offering a wavenumber resolution of 2.6-3.7 cm-1. For discrete frequency mid-infrared imaging, the measurement speed reaches a frame rate of 5 kHz, the repetition rate of the laser. As a demonstration, we effectively identified and mapped different components in a microfluidic device, plant cell, and mouse embryo section. The great capacity and latent force of this technique in chemical imaging promise to be applied to many fields such as chemical analysis, biology, and medicine.

Development and usability of a Mobile Interactive Application (VCPW) for Vascular Crisis Prewarning after Skin Flap Transplantation.

Background: In microsurgical tissue transfer, skin flap transplantation is frequently used to heal the surface of a wound. Effective microcirculation surveillance of the skin flap is crucial. However, with traditional monitoring methods-that is, clinical observation-vascular crisis can still occur, thereby impairing postoperative recovery. A smartphone application is required to assist health care professionals in the standardized collection of flap perfusion parameters for flap management. Methods: The Vascular Crisis Prewarning Application was created using a design science research methodology that prioritizes users and problems. The system usability scale was used to assess the application's usability among medical practitioners. The application was used at the clinic from December 2020 to September 2022. The unplanned return to the operating room, time to diagnose vascular crisis, and flap survival rate were compared with and without the application. Results: The application consisted of 5 modules: patient addition and basic information entry, flap labeling, flap observation, crisis warning, and case archiving. The average rating for the application's usability among medical practitioners was 97.95 score (SD 2.36). With the application, the time to detect vascular crisis reduced from 26.71 to 16.26 h (P < 0.001), the unplanned return to the operation room increased from 8.18% to 10.24% (P = 0.587), and the flap survival rate went from 94.55% to 99.21% (P = 0.083). Conclusions: An easy-to-use flap perfusion monitoring and prewarning application for medical practitioners was produced using a user-centered development method. The application provided a more standardized and accurate platform for data collection in flap management and reduced the time to detect vascular crisis. Larger cohort studies are required in the future to better assess the full potential of the application.

TRPM7 mediates endoplasmic reticulum stress and ferroptosis in sepsis-induced myocardial injury.

Transient receptor potential melastatin 7 (TRPM7), a non-selective cation channel, was significantly upregulated in the blood of patients with sepsis. This study focuses on the preliminary exploration of the probable regulatory mechanism of TRPM7 in sepsis-induced myocardial injury (SIMI). HL-1 cardiac muscle cell line was treated with lipopolysaccharide (LPS) to mimic SIMI in vitro, and TRPM7 level was assessed. The impacts of TRPM7 knockdown on cellular inflammation response, oxidative stress, apoptosis, endoplasmic reticulum (ER) stress, and ferroptosis were identified. In order to explore the mechanism, ER stress agonist tunicamycin (TM) or ferroptosis inducer erastin was applied to treat HL-1 cells. The influences of TM and erastin on the aforementioned aspects were evaluated. TRPM7 was elevated in response to LPS stimulation, and its knockdown reduced the secretion of inflammatory factors and oxidative stress degree. Moreover, TRPM7 knockdown significantly suppressed cell apoptosis, ER stress, and ferroptosis. TM and erastin reversed the functions of TRPM7 knockdown, indicating ER stress and ferroptosis mediated in the regulation of TRPM7. This research proposes the possibility of TRPM7 as a marker or target for SIMI, and provides theoretical support for follow-up research.

Bilingual Bidirectional Stretchable Self-Healing Neuristors with Proprioception.

The coexistence and interaction of excitatory and inhibitory neurotransmitters at biological synapses enable bilingual communication, serving as a physiological foundation for organism adaptation, internal stability, and regulation of behavior and emotions in mammals. Neuromorphic electronics are expected to emulate the bilingual functions of the biological nervous system for artificial neurorobotics and neurorehabilitation. Here, we have proposed a bilingual bidirectional artificial neuristor array, which utilizes ion migration and electrostatic coupling properties between intrinsically stretchable and self-healing poly(urea-urethane) elastomer and carbon nanotube electrodes, realized by van der Waals integration. The neuristor exhibits depression or potentiation behaviors in response to the same stimulus in different operational phases and achieves a four-quadrant information-processing capability. These properties make it possible to simulate complex neuromorphic processes, which involve bilingual bidirectional responses, such as withdrawal or addiction responses, and array-based automated refresh. Furthermore, the neuristor array is a self-healing neuromorphic electronic device that can function effectively even under 50% mechanical strain and can recover operation voluntarily within 2 h after experiencing mechanical injury. Additionally, the bilingual bidirectional stretchable self-healing neuristor can emulate coordinated neural signal transmission from the motor cortex to muscles and integrate proprioception through strain modulation, similar to the biological muscle spindle. The properties, structure, operation mechanisms, and neurologically integrated functions of the proposed neuristor signify an advancement in neuromorphic electronics for next-generation neurorehabilitation and neurorobotics.

Pro- and eukaryotic keystone taxa as potential bio-indicators for the water quality of subtropical Lake Dongqian.

The microbial community plays an important role in the biogeochemical cycles in water aquatic ecosystems, and it is regulated by environmental variables. However, the relationships between microbial keystone taxa and water variables, which play a pivotal role in aquatic ecosystems, has not been clarified in detail. We analyzed the seasonal variation in microbial communities and co-occurrence network in the representative areas taking Lake Dongqian as an example. Both pro- and eukaryotic community compositions were more affected by seasons than by sites, and the prokaryotes were more strongly impacted by seasons than the eukaryotes. Total nitrogen, pH, temperature, chemical oxygen demand, dissolved oxygen and chlorophyll a significantly affected the prokaryotic community, while the eukaryotic community was significantly influenced by total nitrogen, ammonia, pH, temperature and dissolved oxygen. The eukaryotic network was more complex than that of prokaryotes, whereas the number of eukaryotic keystone taxa was less than that of prokaryotes. The prokaryotic keystone taxa belonged mainly to Alphaproteobacteria, Betaproteobacteria, Actinobacteria and Bacteroidetes. It is noteworthy that some of the keystone taxa involved in nitrogen cycling are significantly related to total nitrogen, ammonia, temperature and chlorophyll a, including Polaromonas, Albidiferax, SM1A02 and Leptolyngbya so on. And the eukaryotic keystone taxa were found in Ascomycota, Choanoflagellida and Heterophryidae. The mutualistic pattern between pro- and eukaryotes was more evident than the competitive pattern. Therefore, it suggests that keystone taxa could be as bio-indicators of aquatic ecosystems.

Stepwise rapid electrolytic synthesis of graphene oxide for efficient adsorption of organic pollutants.

Graphene oxide (GO) has been widely used in energy devices, biomedicine, environmental protection, composite materials and other fields. Hummers' method is currently one of the most powerful strategies for the preparation of GO. However, many deficiencies, including severe environmental pollution, operation safety issues and low oxidation efficiency are major obstacles for the large-scale green synthesis of GO. Here, we report a stepwise electrochemical method for the fast preparation of GO using spontaneous persulfate intercalation followed by anodic electrolytic oxidation. Such a step-by-step process not only avoids uneven intercalation and insufficient oxidation in traditional one-pot methods, but also largely shortens the overall duration by two orders of magnitude. In particular, the oxygen content of the obtained GO is as high as 33.7 at%, almost double that from Hummers' method (17.4 at%). The abundant surface functional groups render this GO an excellent adsorption platform for methylene blue with an adsorption capacity of 358 mg g-1, 1.8-fold higher than conventional GO.

Construction and verification of a quantitative index system to evaluate the medical and nursing care for the elderly service needs. / è€å¹´äººåŒ»å »æœåŠ¡éœ€æ±‚é‡åŒ–è¯„ä¼°æŒ‡æ ‡ä½“ç³»çš„æž„å»ºä¸ŽéªŒè¯.

OBJECTIVES: To construct a quantitative index system with the integrated medical and nursing care assessment for the elderly service needs, this system can assess the cost of medical and care services accurately and objectively, so as to provide scientific basis for the allocation of old-age service resources in China. METHODS: Based on the survival needs of the Existence, Relation and Growth theory, an index system is constructed through literature analysis, group discussion, and expert correspondence. Analytic hierarchy process was used to determine the weights of indicators at all levels. The 3-grades service items corresponding to each index were quantified through the measurement of working hours, and the medical and nursing care needs of 624 disabled/demented elderly people over 60 years old in Changsha were investigated to evaluate their reliability and validity. RESULTS: The authoritative coefficients of the 2 rounds of expert correspondence were 88.5% and 88.6%, respectively, and the opinion coordination coefficients were 0.159 and 0.167, respectively. The final quantitative evaluation index system included 4 first-level indicators, 17 second-level indicators, and 105 third-level indicators. The service time of doctor ranged from 6.01 to 22.64 min, the service time of nurses ranged from 0.77 to 24.79 min, and the service time of caregiver ranged from 0.12 to 51.88 min. The Cronbach's αcoefficient was 0.73, the split-half reliability was 0.74, the content validity was 0.93, and the calibration validity was 0.781. CONCLUSIONS: The quantitative evaluation index system of medical and nursing service need for the elderly can be used to accurately evaluate the medical and nursing service need.

Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application.

BACKGROUND: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently. OBJECTIVE: This study aimed to develop an image-artificial intelligence (AI)-based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis. METHODS: A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform. RESULTS: The proposed image-AI-based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users. CONCLUSIONS: An image-AI-based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists' accurate assessment in the real world and chronic disease self-management in patients with psoriasis.

Few-cycle THz wave manipulation with a high degree of freedom via f-t modulation.

THz waves have been intensively applied in many fields, e.g., spectroscopy, imaging, and communications. However, owing to the rarity of available techniques for manipulating circularly polarized few-cycle THz waves on picosecond time scales, most of the current studies are conducted with linearly polarized THz waves. Here we demonstrate circularly polarized (CP) THz (dual) pulses generated by a polarization-twisting pulse/dual pulse (PTP/PTDP). The polarization-twisting optical dual pulses can be generated via a modified Michelson interferometer (MI) system, which provides the ability to control the frequency, helicity, and time interval of the dual pulses arbitrarily and individually. Such a novel, to the best of our knowledge, modulation technique shows huge potential for applications, not only in imaging and spectroscopy but also in next-generation communications.

Evaluation of Lactate Dehydrogenase and Alkaline Phosphatase as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram.

Background: Tumor proliferation is frequently accompanied by aberrant enzyme production. We aim to investigate the potential predictive value of both plasma alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) in patients with HCC and to develop a nomogram to assess the prognosis of HCC. Methods: The trial involved 2327 patients between May 2015 and March 2022. Within 7 days of enrollment, the levels of ALP and LDH were measured, and their association with survival was assessed. And we had developed and validated a new nomogram based on ALD and ALP. Results: Using X-tile software, the optimal cut-off values were determined to be ALP = 172 U/L and LDH = 241 U/L. The high ALP (≥ 172), LDH (≥ 241), and ALP/LDH (≥ 0.91) groups had lower median overall survival (mOS) than low ALP (< 172), LDH (< 241), and ALP/LDH (< 0.91) groups (all p < 0.001). In addition, elevated ALP and LDH levels are independent negative prognostic indicators. Moreover, we established that the area under the curve (AUC) values of the predicted 1-, 2-, and 3-year survival rates of receiver operating characteristic curve (ROC) based on the nomogram were 0.79, 0.77, and 0.74, respectively. In addition, the calibration curves and decision curve analyses (DCA) demonstrated that this model possessed strong predictive capability. Conclusion: ALP, LDH and ALP/LDH can be employed as biomarkers for predicting the prognosis of HCC. Furthermore, the nomograph based on ALH and ALP demonstrates good HCC prediction performance. For HCC patients with high ALH or ALP or ALP/LDH, close surveillance program and adjuvant therapy should be considered.

AFTGAN: prediction of multi-type PPI based on attention free transformer and graph attention network.

MOTIVATION: Protein-protein interaction (PPI) networks and transcriptional regulatory networks are critical in regulating cells and their signaling. A thorough understanding of PPIs can provide more insights into cellular physiology at normal and disease states. Although numerous methods have been proposed to predict PPIs, it is still challenging for interaction prediction between unknown proteins. In this study, a novel neural network named AFTGAN was constructed to predict multi-type PPIs. Regarding feature input, ESM-1b embedding containing much biological information for proteins was added as a protein sequence feature besides amino acid co-occurrence similarity and one-hot coding. An ensemble network was also constructed based on a transformer encoder containing an AFT module (performing the weight operation on vital protein sequence feature information) and graph attention network (extracting the relational features of protein pairs) for the part of the network framework. RESULTS: The experimental results showed that the Micro-F1 of the AFTGAN based on three partitioning schemes (BFS, DFS and the random mode) on the SHS27K and SHS148K datasets was 0.685, 0.711 and 0.867, as well as 0.745, 0.819 and 0.920, respectively, all higher than that of other popular methods. In addition, the experimental comparisons confirmed the performance superiority of the proposed model for predicting PPIs of unknown proteins on the STRING dataset. AVAILABILITY AND IMPLEMENTATION: The source code is publicly available at https://github.com/1075793472/AFTGAN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Drug Repositioning Based on the Enhanced Message Passing and Hypergraph Convolutional Networks.

Drug repositioning, an important method of drug development, is utilized to discover investigational drugs beyond the originally approved indications, expand the application scope of drugs, and reduce the cost of drug development. With the emergence of increasingly drug-disease-related biological networks, the challenge still remains to effectively fuse biological entity data and accurately achieve drug-disease repositioning. This paper proposes a new drug repositioning method named EMPHCN based on enhanced message passing and hypergraph convolutional networks (HGCN). It firstly constructs the homogeneous multi-view information with multiple drug similarity features and then extracts the intra-domain embedding of drugs through the combination of HGCN and channel attention mechanism. Secondly, inter-domain information of known drug-disease associations is extracted by graph convolutional networks combining node and edge embedding (NEEGCN), and a heterogeneous network composed of drugs, proteins and diseases is built as an important auxiliary to enhance the inter-domain message passing of drugs and diseases. Besides, the intra-domain embedding of diseases is also extracted through HGCN. Ultimately, intra-domain and inter-domain embeddings of drugs and diseases are integrated as the final embedding for calculating the drug-disease correlation matrix. Through 10-fold cross-validation on some benchmark datasets, we find that the AUPR of EMPHCN reaches 0.593 (T1) and 0.526 (T2), respectively, and the AUC achieves 0.887 (T1) and 0.961 (T2) respectively, which shows that EMPHCN has an advantage over other state-of-the-art prediction methods. Concerning the new disease association prediction, the AUC of EMPHCN through the five-fold cross-validation reaches 0.806 (T1) and 0.845 (T2), which are 4.3% (T1) and 4.0% (T2) higher than the second best existing methods, respectively. In the case study, EMPHCN also achieves satisfactory results in real drug repositioning for breast carcinoma and Parkinson's disease.

PD-1 inhibitors plus anti-angiogenic therapy with or without intensity-modulated radiotherapy for advanced hepatocellular carcinoma: A propensity score matching study.

Background: Whether intensity-modulated radiotherapy (IMRT) can enhance the efficacy of the programmed death (PD)-1 inhibitors combined with anti-angiogenic therapy for hepatocellular carcinoma (HCC) is unclear. Therefore, we conducted this multicenter retrospective study to investigate the efficacy of the combination of PD-1 inhibitors with anti-angiogenic therapy and IMRT. Methods: From April 2019 to March 2022, a total of 197 patients with HCC [combination of PD-1 inhibitors with anti-angiogenic therapy and IMRT (triple therapy group), 54; PD-1 inhibitors plus anti-angiogenic therapy (control group), 143] were included in our study. Propensity score matching (PSM) was applied to identify two groups with similar baselines. The objective response rate (ORR), overall survival (OS), and progression-free survival (PFS) of the two groups were compared before and after matching. Results: Prior to PSM, the triple therapy group had higher ORR (42.6% vs 24.5%, P = 0.013) and more superior median OS (mOS) (20.1 vs 13.3 months, P = 0.009) and median PFS (mPFS) (8.7 vs 5.4 months, P = 0.001) than the control group. Following PSM, the triple therapy group still exhibited better mPFS (8.7 vs 5.4 months, P = 0.013) and mOS (18.5 vs 12.6 months, P = 0.043) than the control group. However, the ORR of the two groups was similar (40% vs 25%, P = 0.152). No significant difference was observed in the treatment-related adverse events between the two groups (P < 0.05 for all). Conclusions: The combination of PD-1 inhibitors with anti-angiogenic therapy and IMRT for HCC is a promising regimen.