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Rui Duan,1,* Si-Yu Wang,1,* Bin Wei,1 Yang Deng,2 Xin-Xin Fu,2 Peng-Yu Gong,1 Yan E,1 Xiao-Jin Sun,2 Hai-Ming Cao,1 Jian-Quan Shi,1 Teng Jiang,1 Ying-Dong Zhang1,2 1Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, People’s Republic of China; 2School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, People’s Republic of China*These authors contributed equally to this workCorrespondence: Teng Jiang; Ying-Dong ZhangDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, No. 68, Changle Road, Nanjing, Jiangsu, 210006, People’s Republic of ChinaEmail jiang_teng@njmu.edu.cn; zhangyingdong@njmu.edu.cnObjective: Emerging evidence suggests that brain angiotensin-(1– 7) (Ang-(1– 7)) deficiency contributes to the pathogenesis of Alzheimer’s disease (AD). Meanwhile, our previous studies revealed that restoration of brain Ang-(1– 7) levels provided neuroprotection by inhibition of inflammatory responses during AD progress. However, the potential molecular mechanisms by which Ang-(1– 7) modulates neuroinflammation remain unclear.Materials and Methods: APP/PS1 mice were injected intraperitoneally with AVE0991 (a nonpeptide analogue of Ang-(1– 7)) once a day for 30 consecutive days. Cognitive functions, neuronal and synaptic integrity, and inflammation-related markers were assessed. Since astrocytes played a crucial role in AD-related neuroinflammation whilst long noncoding RNAs (lncRNAs) were reported to participate in modulating inflammatory responses, astrocytes of APP/PS1 mice were isolated for high-throughput lncRNA sequencing to identify the most differentially expressed lncRNA following AVE0991 treatment. Afterward, the downstream pathways of this lncRNA in the anti-inflammatory action of AVE0991 were investigated using primary astrocytes.Results: AVE0991 rescued spatial cognitive impairments and alleviated neuronal and synaptic damage in APP/PS1 mice. The levels of Aβ1-42 in the brain of APP/PS1 mice were not affected by AVE0991. By employing high-throughput lncRNA sequencing, our in vitro study demonstrated for the first time that AVE0991 suppressed astrocytic NLRP3 inflammasome-mediated neuroinflammation via a lncRNA SNHG14-dependent manner. SNHG14 acted as a sponge of miR-223-3p while NLRP3 represented a direct target of miR-223-3p in astrocytes. In addition, miR-223-3p participated in the AVE0991-induced suppression of astrocytic NLRP3 inflammasome.Conclusion: Our results suggest that Ang-(1– 7) analogue AVE0991 inhibits astrocyte-mediated neuroinflammation via SNHG14/miR-223-3p/NLRP3 pathway and offers neuroprotection in APP/PS1 mice. These findings reveal the underlying mechanisms by which Ang-(1– 7) inhibits neuroinflammation under AD condition and uncover the potential of its nonpeptide analogue AVE0991 in AD treatment.Keywords: Alzheimer’s disease, AVE0991, lncRNAs, SNHG14, miR-223-3p, astrocyte, neuroinflammation

Bian-Rong Wang,1 Hui-Fen Zheng,1 Chang Xu,1 Yi Sun,1 Ying-Dong Zhang,2 Jian-Quan Shi2 1Department of Neurology, Geriatric Hospital of Nanjing Medical University, Nanjing, Jiangsu Province 210024, People’s Republic of China; 2Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu Province 210006, People’s Republic of ChinaCorrespondence: Ying-Dong Zhang; Jian-Quan ShiDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, No. 68, Changle Road, Nanjing, Jiangsu Province 210006, People’s Republic of ChinaTel +86 0 258 772 6218; +86 0 258 772 6224Email zhangyingdong@aliyun.com; myxiyi_0717@163.comObjective: The aim of this study was to validate the reliability of the Chinese version of Addenbrooke’s Cognitive Examination III (ACE-III) for detecting mild cognitive impairment. Furthermore, the present study compares the diagnostic accuracy of ACE-III with that of Montreal Cognitive Assessment (MoCA).Methods: One hundred and twenty patients with MCI and 136 healthy controls were included in the study. All patients were evaluated by the Chinese version of ACE-III, MoCA and MMSE.Results: Subjects in the control group showed better performance in ACE-III total score and its subdomain scores than those in the MCI group. There was a significantly positive correlation between ACE-III total score and MoCA score. Meanwhile, there was also a significantly positive correlation between ACE-III total score and MMSE score. For ACE-III total score, a cut-off point of 85 yielded a sensitivity of 97.3% and a specificity of 90.7%. The AUC for ACE-III total score was 0.978. For MoCA, a cut-off point of 23 yielded a sensitivity of 86.5% and a specificity of 97.7%. The AUC for MoCA was 0.961. There were no significant differences in diagnostic accuracy between ACE-III and MoCA.Conclusion: The present findings support that both ACE-III and MoCA are useful for detecting MCI in early stages.Keywords: Addenbrooke’s Cognitive Examination III, Montreal Cognitive Assessment, mild cognitive impairment, cognitive screening, Chinese

Objective: Over the last two decades one of the main surgical treatment for stress urinary incontinence (SUI) and pelvic organ prolapse (POP) surgery was the insertion of non-absorbable mesh to restore continence and prolapse respectively. Over time complications arose including mesh-associated pain syndrome (MAPS), mesh exposure, mesh, erosion, chronic bladder/vaginal infections, and dyspareunia. Consequently, women chose surgical mesh removal to counter these problems. However, little is known about the demographics, medical co-morbidities, mesh types involved and the timing from mesh insertion to mesh removal. This retrospective study will look at which of these factors may be closely associated with mesh removal surgery., Design: Retrospective evaluation., Setting: Female Pelvic Medicine and Reconstructive Surgery (FPMRS) Clinic at University College London Hospitals NHS Foundation Trust., Population: All patients presenting to the FPMRS Clinic between June 2011 to December 2019, requesting mesh removal surgery with a history of MAPS and other mesh complications were included in this study., Methods: Patient demographics including age, ethnicity, obstetric history, and medical co-morbidities; type of mesh/anatomical route used; onset of symptoms; and time from insertion to removal were recorded., Main Outcome Measures: Determination of correlation coefficients between patient demographics, patient reported symptoms and mesh removal surgery., Results: Three hundred and forty-five women with a history of MAPS were included in the study. Women in the 40-60 year old cohort accounted for 54.4% of mesh removal surgery; 54.8% had a BMI under 30 and almost 90% were Caucasian. 96.5% had had children, with over 77% having had a vaginal delivery. 91.9% of patients reported other health conditions including 18.8% with a concomitant history of mental health problems and 15.4% with a history of heart disease. Over 80% of women undergoing mesh removal surgery had a continence mesh (49% retropubic and 32% obturator continence mesh) removed, whereas 20% had an abdominal prolapse and/or vaginal prolapse mesh removed. The average time from mesh insertion to mesh removal was seven years, with the prevalence of mesh removal surgery averaging 85% (range 50-100%) depending on the comorbidity determined., Conclusions: All women presented to the clinic with a history of MAPS and other comorbidities which may have influenced their decision to pursue mesh removal surgery. There were no specific predictors, other than chronic pain associated with mesh, determining which women underwent surgery, though those with continence mesh were more likely to do so., (© 2024. The Author(s).)

Background: Neuromyelitis Optica Spectrum Disorder (NMOSD) is an autoimmune demyelinating disease characterized by recurrent myelitis and optic neuritis. It is associated with high rates of relapse and disability. The main treatment strategies for acute attacks include intravenous methylprednisolone pulse (IVMP) treatment and rescue treatment with plasma exchange (PLEX). Recently, the blockade of neonatal Fc receptor (FcRn)-IgG interaction has gained momentum as a therapeutic strategy. Efgartigimod, the first approved FcRn inhibitor for treating generalized myasthenia gravis, has shown impressive safety, efficacy, and tolerability, and is being regarded as "PLEX in a bottle"., Case Description: We report a 65-year-old female patient who was diagnosed with anti-AQP4 antibody positive NMOSD. Add-on treatment with efgartigimod to IVMP and intravenous immunoglobulin (IVIG) at the second acute relapse showed favorable results., Conclusion: This case suggests that efgartigimod is a potentially effective add-on therapy in acute attacks of AQP4-IgG-positive NMOSD., (© 2024. Fondazione Società Italiana di Neurologia.)

Background: Restrictive practices (RPs) are defined by measures linked to physical and chemical restraints to reduce the movement or control behaviours during any emergency. Seclusion is an equal part of RPs intended to isolate and reduce the sensory stimulation to safeguard the patient and those within the vicinity. Using interventions by way of virtual reality (VR) could assist with reducing the need for RPs as it could help reduce anxiety or agitation by way of placing users into realistic and immersive environments. This could also aid staff to and change current RPs., Aim: To assess the feasibility and effectiveness of using a VR platform to provide reduction in RP training., Methods: A randomised controlled feasibility study, accompanied by evaluations at 1 month and 6 months, was conducted within inpatient psychiatric wards at Southern Health National Health Service Foundation Trust, United Kingdom. Virti VR scenarios were used on VR headsets to provide training on reducing RPs in 3 inpatient psychiatric wards. Outcome measures included general self-efficacy scale, generalised anxiety disorder assessment 7 (GAD-7), Burnout Assessment Tool 12, the Everyday Discrimination Scale, and the Compassionate Engagement and Action Scale., Results: Findings revealed statistically significant differences between the VR and treatment as usual groups, in the Everyday Discrimination Scale items Q8 and Q9: P = 0.023 and P = 0.040 respectively, indicating higher levels of perceived discrimination in the VR group. There were no significant differences between groups in terms of general self-efficacy, generalised anxiety disorder assessment 9, and Burnout Assessment Tool 12 scores. A significant difference was observed within the VR group for compassionate engagement from others ( P = 0.005) over time. Most respondents recorded System Usability Scale scores above 70, with an average score of 71.79. There was a significant reduction in rates of RPs in the VR group vs treatment as usual group with a fluctuating variability observed in the VR group likely due to external factors not captured in the study., Conclusion: Ongoing advancement of VR technology enables the possibility of creating scenarios and simulations tailored to healthcare environments that empower staff by providing more comprehensive and effective training for handling situations., Competing Interests: Conflict-of-interest statement: Phiri P has received research grant from Novo Nordisk, and other, educational from Queen Mary University of London, other from John Wiley & Sons, other from Otsuka, other from Janssen, outside the submitted work. All other authors report no conflict of interest. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Department of Health and Social Care or the Academic institutions., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Efgartigimod was the first-in-class neonatal Fc receptor antagonist approved for the treatment of acetylcholine receptor antibody positive (AChR+), Myasthenia Gravis Foundation of America (MGFA) Class II-IV generalized myasthenia gravis (gMG) patients. As a novel therapy, the clinical experiences are still lacking, especially for the use of efgartigimod in manifest and impending myasthenic crisis (IMC). We reported three AChR+, gMG patients, two with myasthenic crisis (MC) and one with IMC, treated with efgartigimod. MGFA class, MG-Activity of Daily Living score (MG-ADL), Quantitative MG score (QMG), and Muscle Research Council sum score (MRC), concentration of anti-AChR antibody, IgG, globulin, and albumin, subsets of T and B lymphocyte were evaluated or measured before, during and after efgartigimod treatment. All patients showed fast and robust response to efgartigimod with marked improvement in MGFA, MG-ADL, QMG, and MRC scores. Patient 1 did not respond effectively to IVIg but was successfully rescued by add-on efgartigimod. She extubated at 7 days after the first infusion and got rid of NIV after 14-days treatment. Patient 2 and patient 3 directly used efgartigimod when symptoms were not ameliorated by adjusting of oral drugs. Patient 2 wean from BiPAP at seven days after the first infusion. Patient 3 in IMC status, overcame the severe dysphagia at three days after the first infusion. Clinical symptoms continued to improve 1-2 weeks after discharge. Concentration of anti-AChR antibody, IgG and globulin were remarkably reduced by efgartigimod treatment. Our study supported that efgartigimod could act as a fast-acting rescue therapy for patients with MC or IMC. Larger studies from multicenter are required to provide further evidence., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier B.V.)

Background: Endometriosis surgery outcomes have been widely studied, yet heterogeneity in terminology and techniques persist., Objectives: This study focuses on the perioperative outcomes of a single surgeon using the same structured approach (SOSURE: Survey & Sigmoid mobilisation, Ovarian mobilisation, Suspension of uterus and ovaries, Ureterolysis, Rectovaginal and pararectal space development, Excision of all visible disease) and adheres to the recent standardised terminology proposed by international gynaecological and endometriosis societies., Materials and Methods: A quality improvement study was conducted retrospectively from January 2015 to January 2023. Data collection involved two databases: the National British Society for Gynaecological Endoscopy (BSGE) database and a more comprehensive locally kept database. The methodology also integrated four endometriosis staging systems., Main Outcome Measures: Intra-operative and post-operative complication rates., Results: Between 2015 and 2023, 1047 women underwent 1116 endometriosis procedures in various UK hospitals with S.K. as primary surgeon. Exclusions totalled 20 due to missing records and specific surgical criteria. The rate of major post-operative complications (Clavien-Dindo grade 3a and 3b) was 1.5% and minor post-operative complications (Clavien-Dindo grade 1 and 2) were seen in 13.8%. No Clavien-Dindo grade 4 or 5 complications were noted., Conclusion: Our study has shown a low complication rate in endometriosis surgery, despite increasing complexity of surgical cases. This is likely attributed to the surgeon's learning curve, high surgical volume and adherence to a structured approach., What's New?: Our study demonstrates the learning curve of a surgeon over the course of 8 years. This series involved more than 1000 patients and to our knowledge, is the first to report the complexity of the casemix using four different endometriosis staging systems.

Amyotrophic lateral sclerosis (ALS) is a debilitating and rapidly fatal neurodegenerative disease, which is characterized by the selective loss of the upper and lower motor neurons. The pathogenesis of ALS remains to be elucidated and has been connected to genetic, environmental and immune conditions. Evidence from clinical and experimental studies has suggested that the immune system played an important role in ALS pathophysiology. Autoantibodies are essential components of the immune system. Several autoantibodies directed at antigens associated with ALS pathogenesis have been identified in the serum and/or cerebrospinal fluid of ALS patients. The aim of this review is to summarize the presence and clinical significance of autoantibodies in ALS., (© 2024. Fondazione Società Italiana di Neurologia.)

Modern deep neural networks, particularly recent large language models, come with massive model sizes that require significant computational and storage resources. To enable the deployment of modern models on resource-constrained environments and to accelerate inference time, researchers have increasingly explored pruning techniques as a popular research direction in neural network compression. More than three thousand pruning papers have been published from 2020 to 2024. However, there is a dearth of up-to-date comprehensive review papers on pruning. To address this issue, in this survey, we provide a comprehensive review of existing research works on deep neural network pruning in a taxonomy of 1) universal/specific speedup, 2) when to prune, 3) how to prune, and 4) fusion of pruning and other compression techniques. We then provide a thorough comparative analysis of eight pairs of contrast settings for pruning (e.g., unstructured/structured, one-shot/iterative, data-free/data-driven, initialized/pre-trained weights, etc.) and explore several emerging topics, including pruning for large language models, vision transformers, diffusion models, and large multimodal models, post-training pruning, and different levels of supervision for pruning to shed light on the commonalities and differences of existing methods and lay the foundation for further method development. Finally, we provide some valuable recommendations on selecting pruning methods and prospect several promising research directions for neural network pruning. To facilitate future research on deep neural network pruning, we summarize broad pruning applications (e.g., adversarial robustness, natural language understanding, etc.) and build a curated collection of datasets, networks, and evaluations on different applications. We maintain a repository on https://github.com/hrcheng1066/awesome-pruning that serves as a comprehensive resource for neural network pruning papers and corresponding open-source codes. We will keep updating this repository to include the latest advancements in the field.

A challenge of channel pruning is designing efficient and effective criteria to select channels to prune. A widely used criterion is minimal performance degeneration, e.g., loss changes before and after pruning being the smallest. To accurately evaluate the truth performance degeneration requires retraining the survived weights to convergence, which is prohibitively slow. Hence existing pruning methods settle to use previous weights (without retraining) to evaluate the performance degeneration. However, we observe that the loss changes differ significantly with and without retraining. It motivates us to develop a technique to evaluate true loss changes without retraining, using which to select channels to prune with more reliability and confidence. We first derive a closed-form estimator of the true loss change per mask change, using influence functions without retraining. Influence function is a classic technique from robust statistics that reveals the impacts of a training sample on the model's prediction and is repurposed by us to assess impacts on true loss changes. We then show how to assess the importance of all channels simultaneously and develop a novel global channel pruning algorithm accordingly. We conduct extensive experiments to verify the effectiveness of the proposed algorithm, which significantly outperforms the competing channel pruning methods on both image classification and object detection tasks. To the best of our knowledge, we are the first that shows evaluating true loss changes or pruning without retraining is possible. This finding will open up opportunities for a series of new paradigms to emerge that differ from existing pruning methods.

Carbon-carbon (C-C) coupling is essential in the electrocatalytic reduction of CO 2 for the production of green chemicals. However, due to the complexity of the reaction network, there remains controversy regarding the underlying reaction mechanisms and the optimal direction for catalyst material design. Here, we present a global perspective to establish a comprehensive data set encompassing all C-C coupling precursors and catalytic active site compositions to explore the reaction mechanisms and screen catalysts via big data set analysis. The 2D-3D ensemble machine learning strategy, developed to target a variety of adsorption configurations, can quickly and accurately expand quantum chemical calculation data, enabling the rapid acquisition of this extensive big data set. Analyses of the big data set establish that (1) asymmetric coupling mechanisms exhibit greater potential efficiency compared to symmetric coupling, with the optimal path involving the coupling CHO with CH or CH 2 , and (2) C-C coupling selectivity of Cu-based catalysts can be enhanced through bimetallic doping including CuAgNb sites. Importantly, we experimentally substantiate the CuAgNb catalyst to demonstrate actual boosted performance in C-C coupling. Our finding evidence the practicality of our big data set generated from machine learning-accelerated quantum chemical computations. We conclude that combining big data with complex catalytic reaction mechanisms and catalyst compositions will set a new paradigm for accelerating optimal catalyst design.

Anther dehiscence is a crucial event in plant reproduction, tightly regulated and dependent on the lignification of the anther endothecium. In this study, we investigated the rapid lignification process that ensures timely anther dehiscence in Arabidopsis. Our findings reveal that endothecium lignification can be divided into two distinct phases. During Phase I, lignin precursors are synthesized without polymerization, while Phase II involves simultaneous synthesis of lignin precursors and polymerization. The transcription factors MYB26, NST1/2, and ARF17 specifically regulate the pathway responsible for the synthesis and polymerization of lignin monomers in Phase II. MYB26-NST1/2 is the key regulatory pathway responsible for endothecium lignification, while ARF17 facilitates this process by interacting with MYB26. Interestingly, our results demonstrate that the lignification of the endothecium, which occurs within approximately 26 h, is much faster than that of the vascular tissue. These findings provide valuable insights into the regulation mechanism of rapid lignification in the endothecium, which enables timely anther dehiscence and successful pollen release during plant reproduction., (© 2024 Institute of Botany, Chinese Academy of Sciences.)

Single photon emission tomography/computed tomography (SPECT/CT) is a mature imaging technology with a dynamic role in the diagnosis and monitoring of a wide array of diseases. This paper reviews the technological advances, clinical impact, and future directions of SPECT and SPECT/CT imaging. The focus of this review is on signal amplifier devices, detector materials, camera head and collimator designs, image reconstruction techniques, and quantitative methods. Bulky photomultiplier tubes (PMTs) are being replaced by position-sensitive PMTs (PSPMTs), avalanche photodiodes (APDs), and silicon PMs to achieve higher detection efficiency and improved energy resolution and spatial resolution. Most recently, new SPECT cameras have been designed for cardiac imaging. The new design involves using specialised collimators in conjunction with conventional sodium iodide detectors (NaI(Tl)) or an L-shaped camera head, which utilises semiconductor detector materials such as CdZnTe (CZT: cadmium-zinc-telluride). The clinical benefits of the new design include shorter scanning times, improved image quality, enhanced patient comfort, reduced claustrophobic effects, and decreased overall size, particularly in specialised clinical centres. These noticeable improvements are also attributed to the implementation of resolution-recovery iterative reconstructions. Immense efforts have been made to establish SPECT and SPECT/CT imaging as quantitative tools by incorporating camera-specific modelling. Moreover, this review includes clinical examples in oncology, neurology, cardiology, musculoskeletal, and infection, demonstrating the impact of these advancements on clinical practice in radiology and molecular imaging departments.

Oocyte maturation and early embryonic development are key steps in the reproductive physiology of female mammals, and any error in this process can adversely affect reproductive development. Recent studies have shown that epigenetic modifications of histones play important roles in the regulation of oocyte meiosis and quality assurance of early embryonic development. Histone deacetylase 11 (HDAC11) is the smallest known member of the histone deacetylases (HDACs) family, and inhibition of HDAC11 activity significantly suppresses the rate of oocyte maturation, as well as the development of 8-cell and blastocyst embryos at the embryonic stage. This paper focuses on recent progress on the important role of HDAC11 in the regulation of mammalian oocyte maturation and early embryonic development, hoping to gain insights into the key roles played by epitope-modifying proteins represented by HDAC11 in the regulation of mammalian reproduction and their molecular mechanisms.

Whilst . pharmacological therapies remain the cornerstone of pain management in chronic pain, factors including the current opioid epidemic have led to non-pharmacological techniques becoming a more attractive proposition. We explored the prevalence of medical device use and their treatment efficacy in non-cancer pain management. A systematic methodology was developed, peer reviewed and published in PROSPERO (CRD42021235384). Key words of medical device, pain management devices, chronic pain, lower back pain, back pain, leg pain and chronic pelvic pain using Science direct, PubMed, Web of Science, PROSPERO, MEDLINE, EMBASE, PorQuest and ClinicalTrials.gov. All clinical trials, epidemiology and mixed methods studies that reported the use of medical devices for non-cancer chronic pain management published between the 1st of January 1990 and the 30th of April 2022 were included. 13 studies were included in systematic review, of these 6 were used in the meta-analysis. Our meta-analysis for pain reduction showed that transcutaneous electrical nerve stimulation combined with instrument-assisted soft tissue mobilization treatment and pulsed electromagnetic therapy produced significant treatment on chronic lower back pain patients. Pooled evidence revealed the use of medical device related interventions resulted in 0.7 degree of pain reduction under a 0-10 scale. Significant improvement in disability scores, with a 7.44 degree reduction in disability level compared to a placebo using a 50 score range was also seen. Our analysis has shown that the optimal use of medical devices in a sustainable manner requires further research, needing larger cohort studies, greater gender parity, in a more diverse range of geographical locations., (© 2024. The Author(s).)

Background : Total hysterectomy with bilateral salpingo-oophorectomy via minimally invasive surgery (MIS) has emerged as the standard of care for early-stage endometrial cancer (EC). Prior systematic reviews and meta-analyses have focused on outcomes reported solely from randomised controlled trials (RCTs), overlooking valuable data from non-randomised studies. This inaugural systematic review and network meta-analysis comprehensively compares clinical and oncological outcomes between MIS and open surgery for early-stage EC, incorporating evidence from randomised and non-randomised studies. Methods : This study was prospectively registered on PROSPERO (CRD42020186959). All original research of any experimental design reporting clinical and oncological outcomes of surgical treatment for endometrial cancer was included. Study selection was restricted to English-language peer-reviewed journal articles published 1 January 1995-31 December 2021. A Bayesian network meta-analysis was conducted. Results : A total of 99 studies were included in the network meta-analysis, comprising 181,716 women and 14 outcomes. Compared with open surgery, laparoscopic and robotic-assisted surgery demonstrated reduced blood loss and length of hospital stay but increased operating time . Compared with laparoscopic surgery, robotic-assisted surgery was associated with a significant reduction in ileus (OR = 0.40, 95% CrI: 0.17-0.87) and total intra-operative complications (OR = 0.38, 95% CrI: 0.17-0.75) as well as a higher disease-free survival (OR = 2.45, 95% CrI: 1.04-6.34). Conclusions : For treating early endometrial cancer, minimal-access surgery via robotic-assisted or laparoscopic techniques appears safer and more efficacious than open surgery. Robotic-assisted surgery is associated with fewer complications and favourable oncological outcomes.

It is estimated 1.5 billion of the global population suffer from chronic pain with prevalence increasing with demographics including age. It is suggested long-term exposure to chronic could cause further health challenges reducing people's quality of life. Therefore, it is imperative to use effective treatment options. We explored the current pharmaceutical treatments available for chronic pain management to better understand drug efficacy and pain reduction. A systematic methodology was developed and published in PROSPERO (CRD42021235384). Keywords of opioids, acute pain, pain management, chronic pain, opiods, NSAIDs, and analgesics were used across PubMed, Science direct, ProQuest, Web of science, Ovid Psych INFO, PROSPERO, EBSCOhost, MEDLINE, ClinicalTrials.gov and EMBASE. All randomised controlled clinical trials (RCTs), epidemiology and mixed-methods studies published in English between the 1st of January 1990 and 30th of April 2022 were included. A total of 119 studies were included. The data was synthesised using a tri-partied statistical methodology of a meta-analysis (24), pairwise meta-analysis (24) and network meta-analysis (34). Mean, median, standard deviation and confidence intervals for various pain assessments were used as the main outcomes for pre-treatment pain scores at baseline, post-treatment pain scores and pain score changes of each group. Our meta-analysis revealed the significant reduction in chronic pain scores of patients taking NSAID versus non-steroidal opioid drugs was comparative to patients given placebo under a random effects model. Pooled evidence also indicated significant drug efficiency with Botulinum Toxin Type-A (BTX-A) and Ketamine. Chronic pain is a public health problem that requires far more effective pharmaceutical interventions with minimal better side-effect profiles which will aid to develop better clinical guidelines. The importance of understanding ubiquity of pain by clinicians, policy makers, researchers and academic scholars is vital to prevent social determinant which aggravates issue., (© 2024. The Author(s).)

The secondary metabolites of marine fungi with rich chemical diversity and biological activity are an important and exciting target for natural product research. This study aimed to investigate the fungal community in Quanzhou Bay, Fujian, and identified 28 strains of marine fungi. A total of 28 strains of marine fungi were screened for small-scale fermentation by the OSMAC (One Strain-Many Compounds) strategy, and 77 EtOAc crude extracts were obtained and assayed for cancer cell inhibition rate. A total of six strains of marine fungi (P-WZ-2, P-WZ-3-2, P-WZ-4, P-WZ-5, P56, and P341) with significant changes in cancer cell inhibition induced by the OSMAC strategy were analysed by UPLC-QTOF-MS. The ACD/MS Structure ID Suite software was used to predict the possible structures with inhibitory effects on cancer cells. A total of 23 compounds were identified, of which 10 compounds have been reported to have potential anticancer activity or cytotoxicity. In this study, the OSMAC strategy was combined with an untargeted metabolomics approach based on UPLC-QTOF-MS to efficiently analyse the effect of changes in culture conditions on anticancer potentials and to rapidly find active substances that inhibit cancer cell growth.

Single-atom catalysts (SACs) offer significant potential across various applications, yet our understanding of their formation mechanism remains limited. Notably, the pyrolysis of zeolitic imidazolate frameworks (ZIFs) stands as a pivotal avenue for SAC synthesis, of which the mechanism can be assessed through infrared (IR) spectroscopy. However, the prevailing analysis techniques still rely on manual interpretation. Here, we report a machine learning (ML)-driven analysis of the IR spectroscopy to unravel the pyrolysis process of Pt-doped ZIF-67 to synthesize Pt-Co 3 O 4 SAC. Demonstrating a total Pearson correlation exceeding 0.7 with experimental data, the algorithm provides correlation coefficients for the selected structures, thereby confirming crucial structural changes with time and temperature, including the decomposition of ZIF and formation of Pt-O bonds. These findings reveal and confirm the formation mechanism of SACs. As demonstrated, the integration of ML algorithms, theoretical simulations, and experimental spectral analysis introduces an approach to deciphering experimental characterization data, implying its potential for broader adoption.

Despite today's commercial-scale graphene production using chemical vapor deposition (CVD), the growth of high-quality single-layer graphene with controlled morphology and crystallinity remains challenging. Considerable effort is still spent on designing improved CVD catalysts for producing high-quality graphene. Conventionally, however, catalyst design has been pursued using empirical intuition or trial-and-error approaches. Here, we combine high-throughput density functional theory and machine learning to identify new prospective transition metal alloy catalysts that exhibit performance comparable to that of established graphene catalysts, such as Ni(111) and Cu(111). The alloys identified through this process generally consist of combinations of early- and late-transition metals, and a majority are alloys of Ni or Cu. Nevertheless, in many cases, these conventional catalyst metals are combined with unconventional partners, such as Zr, Hf, and Nb. The approach presented here therefore highlights an important new approach for identifying novel catalyst materials for the CVD growth of low-dimensional nanomaterials.

Objectives: The aim of this perspective is to report the use of synthetic data as a viable method in women's health given the current challenges linked to obtaining life-course data within a short period of time and accessing electronic healthcare data., Methods: We used a 3-point perspective method to report an overview of data science, common applications, and ethical implications., Results: There are several ethical challenges linked to using real-world data, consequently, generating synthetic data provides an alternative method to conduct comprehensive research when used effectively. The use of clinical characteristics to develop synthetic data is a useful method to consider. Aligning this data as closely as possible to the clinical phenotype would enable researchers to provide data that is very similar to that of the real-world., Discussion: Population diversity and disease characterisation is important to optimally use data science. There are several artificial intelligence techniques that can be used to develop synthetic data., Conclusion: Synthetic data demonstrates promise and versatility when used efficiently aligned to clinical problems. Therefore, exploring this option as a viable method in women's health, in particular for epidemiology may be useful., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: PP has received research grant from Novo Nordisk and Janssen Cilag, and other, educational, other from John Wiley & Sons, outside the submitted work. DB’s work is funded by an EPSRC PhD Studentship with reference number 2612869. AZ is supported by the EPSRC grant EP/V049038/1 and the Alan Turing Institute under the EPSRC grant EP/N510129/1. All other authors report no conflict of interest. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Department of Health and Social Care or the Academic institutions., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU). Apart from the latter task is much more challenging, the main causation is that recent approaches learn human interactive relations via shallow graphical representations, which are inadequate to model complicated human interactive-relations. This paper proposes a deep consistency-aware framework aiming at tackling the grouping and labelling inconsistencies in HIU. This framework consists of three components, including a backbone CNN to extract image features, a factor graph network to implicitly learn higher-order consistencies among labelling and grouping variables, and a consistency-aware reasoning module to explicitly enforcing consistencies. The last module is inspired by our key observation that the consistency-aware reasoning bias can be embedded into an energy function or a particular loss function, minimizing which delivers consistent predictions. An efficient mean-field inference algorithm is proposed, such that all modules of our network could be trained in an end-to-end fashion. Experimental results demonstrate that the two proposed consistency-learning modules complement each other, and both make considerable contributions in achieving leading performance on three benchmarks of HIU. The effectiveness of the proposed approach is further validated by experiments on detecting human-object interactions.

Introduction: In people with Parkinson's (PwP) impaired mobility is associated with an increased falls risk. To improve mobility, dopaminergic medication is typically prescribed, but complex medication regimens result in suboptimal adherence. Exploring medication adherence and its impact on mobility in PwP will provide essential insights to optimise medication regimens and improve mobility. However, this is typically assessed in controlled environments, during one-off clinical assessments. Digital health technology (DHT) presents a means to overcome this, by continuously and remotely monitoring mobility and medication adherence. This study aims to use a novel DHT system (DHTS) (comprising of a smartphone, smartwatch and inertial measurement unit (IMU)) to assess self-reported medication adherence, and its impact on digital mobility outcomes (DMOs) in PwP., Methods and Analysis: This single-centre, UK-based study, will recruit 55 participants with Parkinson's. Participants will complete a range of clinical, and physical assessments. Participants will interact with a DHTS over 7 days, to assess self-reported medication adherence, and monitor mobility and contextual factors in the real world. Participants will complete a motor complications diary (ON-OFF-Dyskinesia) throughout the monitoring period and, at the end, a questionnaire and series of open-text questions to evaluate DHTS usability. Feasibility of the DHTS and the motor complications diary will be assessed. Validated algorithms will quantify DMOs from IMU walking activity. Time series modelling and deep learning techniques will model and predict DMO response to medication and effects of contextual factors. This study will provide essential insights into medication adherence and its effect on real-world mobility in PwP, providing insights to optimise medication regimens., Ethics and Dissemination: Ethical approval was granted by London-142 Westminster Research Ethics Committee (REC: 21/PR/0469), protocol V.2.4. Results will be published in peer-reviewed journals. All participants will provide written, informed consent., Trial Registration Number: ISRCTN13156149., Competing Interests: Competing interests: FC was CEO and shareholder of Aeqora. JE and MN are employees of McRoberts. SDD reports consultancy activity with Hoffmann-La Roche outside of this study., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Genomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among the genomic prediction modelling approaches, linear based models have proven to provide accurate predictions even when the number of genetic markers exceeds the number of data samples. However, breeding programmes are now compiling data from large numbers of lines and test environments for analyses, rendering these approaches computationally prohibitive. Machine learning (ML) now offers a solution to this problem through the construction of fully connected deep learning architectures and high parallelisation of the predictive task. However, the fully connected nature of these architectures immediately generates an over-parameterisation of the network that needs addressing for efficient and accurate predictions., Results: In this research we explore the use of an ML architecture governed by variational Bayesian sparsity in its initial layers that we have called VBS-ML. The use of VBS-ML provides a mechanism for feature selection of important markers linked to the trait, immediately reducing the network over-parameterisation. Selected markers then propagate to the remaining fully connected feed-forward components of the ML network to form the final genomic prediction. We illustrated the approach with four large Australian wheat breeding data sets that range from 2665 lines to 10375 lines genotyped across a large set of markers. For all data sets, the use of the VBS-ML architecture improved genomic prediction accuracy over legacy linear based modelling approaches., Conclusions: An ML architecture governed under a variational Bayesian paradigm was shown to improve genomic prediction accuracy over legacy modelling approaches. This VBS-ML approach can be used to dramatically decrease the parameter burden on the network and provide a computationally feasible approach for improving genomic prediction conducted with large breeding population numbers and genetic markers., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Objective: To investigate the effect of titanium dioxide nanoparticles (TiO 2 NPs) on the expression profile of circular ribonucleic acid (circRNA) in human hepatocytes through in vitro cell experiments, and to attempt to understand the potential mechanism of hepatotoxicity through bioinformatics analysis., Methods: TiO 2 NPs were characterized from the aspects of particle size, shape and agglomeration state. The cell counting kit-8 (CCK8) was used to detect the cytotoxicity of TiO 2 NPs against human hepatocellular carcinoma cells (HepG2) after exposure to 0, 1.56, 3.13, 6.25, 12.5, 25, 50, 100, and 200 mg/L TiO 2 NPs for 24 h or 48 h. The cells were treated at doses of 0 mg/L TiO 2 NPs (control group) and 100 mg/L TiO 2 NPs (treatment group), and collected after exposure for 48 h, and then RNA from the extracted cell samples was collected and sequenced. The differential circRNAs between the control and the TiO 2 NPs treatment groups were screened, and then the enrichment pathway of the differential circRNA target gene was analyzed by multivariate statistics. According to the sequencing results, significantly altered genes and important genes in the significant enrichment pathways were screened, and real-time reverse transcription-polymerase chain reaction (real-time RT-PCR) was performed to verify the results., Results: TiO 2 NPs were spherical anatase with a hydrated particle size of (323.50±85.44) nm and a Zeta potential of (-21.00±0.72) mV in a serum-free medium. The results of the CCK8 cytotoxicity assay showed that with the increase of TiO 2 NPs concentration, cell viability gradually decreased. A total of 11 478 circRNAs were found by RNA sequencing. Compared with the control groups, TiO 2 NPs treatment groups (100 mg/L) had a total of 89 differential circRNAs, of which 59 were up-regulated and 30 were down-regulated. Analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway showed that the targeted genes of differential circRNAs were mainly enriched in fatty acid degradation, Fanconi anemia pathway, and fatty acid metabolism. The expression levels of circRNA.6730, circRNA.3650 and circRNA.4321 were significantly different between the TiO 2 NPs treatment group and the control group, which were consistent with the sequencing results., Conclusion: TiO 2 NPs can induce changes in circRNA expression profile, and epigenetics may play an important role in the mechanism of hepatotoxicity.

Background: Ongoing symptoms or the development of new symptoms following a SARS-CoV-2 diagnosis has caused a complex clinical problem known as "long COVID" (LC). This has introduced further pressure on global healthcare systems as there appears to be a need for ongoing clinical management of these patients. LC personifies heterogeneous symptoms at varying frequencies. The most complex symptoms appear to be driven by the neurology and neuropsychiatry spheres., Methods: A systematic protocol was developed, peer reviewed, and published in PROSPERO. The systematic review included publications from the 1st of December 2019-30th June 2021 published in English. Multiple electronic databases were used. The dataset has been analyzed using a random-effects model and a subgroup analysis based on geographical location. Prevalence and 95% confidence intervals (CIs) were established based on the data identified., Results: Of the 302 studies, 49 met the inclusion criteria, although 36 studies were included in the meta-analysis. The 36 studies had a collective sample size of 11,598 LC patients. 18 of the 36 studies were designed as cohorts and the remainder were cross-sectional. Symptoms of mental health, gastrointestinal, cardiopulmonary, neurological, and pain were reported., Conclusions: The quality that differentiates this meta-analysis is that they are cohort and cross-sectional studies with follow-up. It is evident that there is limited knowledge available of LC and current clinical management strategies may be suboptimal as a result. Clinical practice improvements will require more comprehensive clinical research, enabling effective evidence-based approaches to better support patients., (© 2023. The Author(s).)

Environmental heterogeneity can not only increase species diversity to some extent but also affect the stability of terrestrial communities. However, how environmental heterogeneity affects species diversity of epilithic diatom communities in aquatic ecosystems is rarely reported. In this study, therefore, epilithic diatoms and their roles in driving species diversity were explored by quantifying and comparing the environmental heterogeneity in Xiangxi River, a tributary of the Three Gorges Reservoir Area (TGR), on a time scale. The results showed that environmental heterogeneity, taxonomic β -diversity, and functional β -diversity in non-impoundment periods were significantly higher than those in impoundment periods. Moreover, the turnover components in the two hydrological periods showed the highest contribution to β -diversity. However, the taxonomic α -diversity in impoundment periods was significantly higher than that in non-impoundment periods. In addition, functional richness in functional α -diversity was significantly higher in non-impoundment periods than that in impoundment periods, whereas there was no significant difference in other functional α -diversity, i.e., functional dispersion and functional evenness, found between the two periods. Multiple regression on (dis)similarity matrices (MRM) analysis indicated that ammonium nitrogen (NH 4 + -N) and silicate (SiO 3 2- -Si) were the key environmental heterogeneous factors affecting the epilithic diatom community in Xiangxi River during the non-impoundment periods, whereas the key heterogeneous factors were ammonium nitrogen (NH 4 + -N), silicate (SiO 3 2- -Si), and total phosphorus (TP) during the impoundment periods. These results suggested that the environmental heterogeneity during different hydrological periods in TGR can significantly affect the community structure of epilithic diatoms, resulting in the differentiation of species within the community and even affecting the stability of aquatic ecosystems.

In order to identify the contamination and health risks of heavy metals in agricultural soils, a total of 56 surface soil samples (0-20 cm) were collected around a Pb-Zn smelter in Yunnan Province, and six heavy metals (Pb, Cd, Zn, As, Cu, and Hg) and pH were analyzed to assess heavy metal status, ecological risk, and probabilistic health risk. The results revealed that the average contents of six heavy metals (Pb:4413.93 mg·kg -1 , Cd:6.89 mg·kg -1 , Zn:1672.76 mg·kg -1 , As:44.45 mg·kg -1 , Cu:47.61 mg·kg -1 , and Hg:0.21 mg·kg -1 ) were higher than their background values in Yunnan Province. Cd had the highest mean geo-accumulation index ( I geo ) of 0.24, the highest mean pollution index ( P i ) of 30.42, and the greatest average ecological risk index ( E r ) of 1312.60, indicating that Cd was the primary enriched and highest-ecological risk pollutant. The mean hazard index (HI) through exposure to six HMs was 2.42E-01 and 9.36E-01 for adults and children, respectively, with 36.63% of HI values for children exceeding the risk threshold of 1. Moreover, the mean total cancer risks (TCR) were 6.98E-05 and 5.93E-04 for adults and children, respectively, with 86.85% of TCR values for children exceeding the guideline value of 1E-04. The probabilistic health risk assessment suggested that Cd and As were the main contributors for the non-carcinogenic risks and carcinogenic risks. This work will provide scientific reference for the precise risk management and effective remediation strategy of soil heavy metal pollution in this study area.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP)., Methods: Thirty participants with PD [Hoehn and Yahr stage I ( n = 1) and II ( n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback., Results: Adherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = -0.560, BCa 95% CI [-0.791, -0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS., Conclusion: This study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP., Competing Interests: FC was CEO and shareholder of Aeqora Ltd. McRoberts is the manufacturer of the DynaPort. MN and JE are employees of McRoberts. SDD reports consultancy activity with Hoffmann-La Roche Ltd outside of this study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Debelle, Packer, Beales, Bailey, Mc Ardle, Brown, Hunter, Ciravegna, Ireson, Evers, Niessen, Shi, Yarnall, Rochester, Alcock and Del Din.)

In order to investigate the relationship between phytoplankton community functional group compositions and resource use efficiency in important tributaries of the Three Gorges Reservoir, phytoplankton and environment parameters were sampled from five tributaries, the Xiangxi River, Daning River, Meixi River, Pengxi River, and Huangjin River, in August and November, 2020. There were 119 species (variants) belonging to 62 genera and 7 phyla identified in summer, whereas 118 species (variants) belonging to 7 divisions of 58 genera were found in winter. According to Padisak's theory, all phytoplankton were divided into 25 functional groups, of which there were six important functional groups in both summer and winter:L0, H1, D, Y, MP, and P in summer and L0, H1, A, M, MP, and Y in winter. The α -diversity of the phytoplankton functional group in summer was higher than that in winter. Moreover, a higher α -diversity was also found in downstream samples relative to that in upstream samples, indicating that the community structure was more complex, and the community stability was relatively better in downstream regions of the rivers. Redundancy analysis (RDA) showed that the environment factors, i.e., ν , pH, permanganate index, WT, and RUE TN , significantly affected phytoplankton functional groups ( P <0.05). Variance partitioning analysis (VPA) indicated that environmental factors had a higher explanatory degree for the change in functional group composition in summer (45.23%); on the contrary, resource use efficiency had a higher explanatory degree in winter (42.33%). The linear fitted model showed that functional groups L0, H1, D, and Y showed a significant positive correlation relationship with RUE TN and RUE TP in summer, whereas only four functional groups (M, MP, Y, and A) had a linear relationship with RUE TP , and all function groups had a good linear relationship with RUE TN in winter. These results indicated that the functional groups belonging to cyanobacteria, dinoflagellates, and cryptophyta were more efficient at using limited resources in summer, whereas the diatoms had a good linear relationship with resource use efficiency and formed a dominant group in the low temperature environment of winter. These results suggest that the impounding of the Three Gorges Reservoir area can significantly change the resource use efficiency of phytoplankton, resulting in changes in the phytoplankton functional group composition and community structure.

Background: This systematic review aims to explore the prevalence of the impact of the COVID-19, MERS, and SARS pandemics on the mental health of pregnant women., Methods: All COVID-19, SARS and MERS studies that evaluated the mental health of pregnant women with/without gynaecological conditions that were reported in English between December 2000 - July 2021 were included. The search criteria were developed based upon the research question using PubMed, Science Direct, Ovid PsycINFO and EMBASE databases. A wide search criterion was used to ensure the inclusion of all pregnant women with existing gynaecological conditions. The Newcastle-Ottawa-Scale was used to assess the risk of bias for all included studies. Random effects model with restricted maximum-likelihood estimation method was applied for the meta-analysis and I-square statistic was used to evaluate heterogeneity across studies. The pooled prevalence rates of symptoms of anxiety, depression, PTSD, stress, and sleep disorders with 95% confidence interval (CI) were computed., Results: This systematic review identified 217 studies which included 638,889 pregnant women or women who had just given birth. There were no studies reporting the mental health impact due to MERS and SARS. Results showed that women who were pregnant or had just given birth displayed various symptoms of poor mental health including those relating to depression (24.9%), anxiety (32.8%), stress (29.44%), Post Traumatic Stress Disorder (PTSD) (27.93%), and sleep disorders (24.38%) during the COVID-19 pandemic., Discussion: It is important to note that studies included in this review used a range of outcome measures which does not allow for direct comparisons between findings. Most studies reported self-reported measure of symptoms without clinical diagnoses so conclusions can be made for symptom prevalence rather than of mental illness. The importance of managing mental health during pregnancy and after-delivery improves the quality of life and wellbeing of mothers hence developing an evidence-based approached as part of pandemic preparedness would improve mental health during challenging times., Other: The work presented in this manuscript was not funded by any specific grants. A study protocol was developed and published in PROSPERO (CRD42021235356) to explore several key objectives., (© 2023. The Author(s).)

Background: Recommendations for psychotherapy have evolved over the years, with cognitive behavioral therapy (CBT) taking precedence since its inception within clinical guidelines in the United Kingdom and United States. The use of CBT for severe mental illness is now more common globally., Aim: To investigate the feasibility and acceptability of a culturally adapted, CBT-based, third-wave therapy manual using the Comprehend, Cope, and Connect approach with individuals from a diverse population presenting to primary and secondary healthcare services., Methods: A pilot study was used to assess the feasibility and acceptability of the manualised intervention. Outcome measures were evaluated at baseline, post-intervention and 12 wk-follow up. 32 participants with mental health conditions aged 20-53 years were recruited. Assessments were completed at three time points, using Clinical Outcomes in Routine Evaluation (CORE), Hospital Anxiety and Depression Scale (HADS), Bradford Somatic Inventory and World Health Organization Disability Assessment Schedule 2.0 (WHODAS). The Patient Experience Ques-tionnaire was completed post-treatment., Results: Repeated measures of analysis of variance associated with HADS depression, F (2, 36) = 12.81, P < 0.001, partial η 2 = 0.42 and HADS anxiety scores, F (2, 26) = 9.93, P < 0.001, partial η 2 = 0.36; CORE total score and WHODAS both showed significant effect F (1.25, 18.72) = 14.98, P < 0.001, partial η 2 = 0.5. and F (1.29, 14.18) = 6.73, P < 0.001, partial η 2 = 0.38 respectively., Conclusion: These results indicate the effectiveness and acceptability of the culturally adapted, CBT-based, third-wave therapy manual intervention among minoritized groups with moderate effect sizes. Satisfaction levels and acceptability were highly rated. The viability and cost-effectiveness of this approach should be explored further to support universal implementation across healthcare systems., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)

The goal of dynamic scene deblurring is to remove the motion blur presented in a given image. To recover the details from the severe blurs, conventional convolutional neural networks (CNNs) based methods typically increase the number of convolution layers, kernel-size, or different scale images to enlarge the receptive field. However, these methods neglect the non-uniform nature of blurs, and cannot extract varied local and global information. Unlike the CNNs-based methods, we propose a Transformer-based model for image deblurring, named SharpFormer, that directly learns long-range dependencies via a novel Transformer module to overcome large blur variations. Transformer is good at learning global information but is poor at capturing local information. To overcome this issue, we design a novel Locality preserving Transformer (LTransformer) block to integrate sufficient local information into global features. In addition, to effectively apply LTransformer to the medium-resolution features, a hybrid block is introduced to capture intermediate mixed features. Furthermore, we use a dynamic convolution (DyConv) block, which aggregates multiple parallel convolution kernels to handle the non-uniform blur of inputs. We leverage a powerful two-stage attentive framework composed of the above blocks to learn the global, hybrid, and local features effectively. Extensive experiments on the GoPro and REDS datasets show that the proposed SharpFormer performs favourably against the state-of-the-art methods in blurred image restoration.

This paper addresses the task of set prediction using deep feed-forward neural networks. A set is a collection of elements which is invariant under permutation and the size of a set is not fixed in advance. Many real-world problems, such as image tagging and object detection, have outputs that are naturally expressed as sets of entities. This creates a challenge for traditional deep neural networks which naturally deal with structured outputs such as vectors, matrices or tensors. We present a novel approach for learning to predict sets with unknown permutation and cardinality using deep neural networks. In our formulation we define a likelihood for a set distribution represented by a) two discrete distributions defining the set cardinally and permutation variables, and b) a joint distribution over set elements with a fixed cardinality. Depending on the problem under consideration, we define different training models for set prediction using deep neural networks. We demonstrate the validity of our set formulations on relevant vision problems such as: 1) multi-label image classification where we outperform the other competing methods on the PASCAL VOC and MS COCO datasets, 2) object detection, for which our formulation outperforms popular state-of-the-art detectors, and 3) a complex CAPTCHA test, where we observe that, surprisingly, our set-based network acquired the ability of mimicking arithmetics without any rules being coded.

Importance: Pain is a silent global epidemic impacting approximately a third of the population. Pharmacological and surgical interventions are primary modes of treatment. Cognitive/behavioural management approaches and interventional pain management strategies are approaches that have been used to assist with the management of chronic pain. Accurate data collection and reporting treatment outcomes are vital to addressing the challenges faced. In light of this, we conducted a systematic evaluation of the current digital application landscape within chronic pain medicine., Objective: The primary objective was to consider the prevalence of digital application usage for chronic pain management. These digital applications included mobile apps, web apps, and chatbots., Data Sources: We conducted searches on PubMed and ScienceDirect for studies that were published between 1st January 1990 and 1st January 2021., Study Selection: Our review included studies that involved the use of digital applications for chronic pain conditions. There were no restrictions on the country in which the study was conducted. Only studies that were peer-reviewed and published in English were included. Four reviewers had assessed the eligibility of each study against the inclusion/exclusion criteria. Out of the 84 studies that were initially identified, 38 were included in the systematic review., Data Extraction and Synthesis: The AMSTAR guidelines were used to assess data quality. This assessment was carried out by 3 reviewers. The data were pooled using a random-effects model., Main Outcomes and Measures: Before data collection began, the primary outcome was to report on the standard mean difference of digital application usage for chronic pain conditions. We also recorded the type of digital application studied (e.g., mobile application, web application) and, where the data was available, the standard mean difference of pain intensity, pain inferences, depression, anxiety, and fatigue., Results: 38 studies were included in the systematic review and 22 studies were included in the meta-analysis. The digital interventions were categorised to web and mobile applications and chatbots, with pooled standard mean difference of 0.22 (95% CI: -0.16, 0.60), 0.30 (95% CI: 0.00, 0.60) and -0.02 (95% CI: -0.47, 0.42) respectively. Pooled standard mean differences for symptomatologies of pain intensity, depression, and anxiety symptoms were 0.25 (95% CI: 0.03, 0.46), 0.30 (95% CI: 0.17, 0.43) and 0.37 (95% CI: 0.05, 0.69), respectively. A sub-group analysis was conducted on pain intensity due to the heterogeneity of the results ( I 2  = 82.86%; p  = 0.02). After stratifying by country, we found that digital applications were more likely to be effective in some countries (e.g., United States, China) than others (e.g., Ireland, Norway)., Conclusions and Relevance: The use of digital applications in improving pain-related symptoms shows promise, but further clinical studies would be needed to develop more robust applications., Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42021228343., Competing Interests: PP has received research grant from Novo Nordisk, and other, educational from Queen Mary University of London, other from John Wiley & Sons, other from Otsuka, outside the submitted work. All other authors report no conflict of interest. TF has received funding from Boston Scientific. AS is the Chief Medical Officer for Nurokor Medical Systems. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Department of Health and Social Care or the Academic institutions., (© 2022 Shetty, Delanerolle, Zeng, Shi, Ebrahim, Pang, Hapangama, Sillem, Shetty, Shetty, Hirsch, Raymont, Majumder, Chong, Goodison, O'hara, Hull, Pluchino, Shetty, Elneil, Fernandez, Brownstone and Phiri.)

The succession of dominant species always occurs during cyanobacterial blooms because there are certain conditions for cyanobacterial blooms formed by different cyanobacteria; this results in more uncertain and complex effects in cyanobacterial blooms. However, the succession pattern and consequences of dominant species and its driving factors have not received enough attention during cyanobacteria blooms. In this study, the phytoplankton community characteristics and water environment factors of Nanpeng Reservoir, a drinking water source in Chongqing, were monitored and analyzed from April to September 2018. The results showed that:① a total of 108 species of phytoplankton belonging to 59 genera and 8 phyla were identified in Nanpeng Reservoir. Of this, 13 species of 4 phyla were identified as dominant species, among which the dominance index of Cylindrospermopsis raciborskii was the highest, followed by that of Pseudoanabaena sp. ② The most dominant cyanobacteria were Pseudoanabaena and Cylindrospermopsis in May and July, respectively, in which cyanobacteria density peaked, whereas the Shannon-Weiner diversity and Pielou evenness were significantly lower than those in the other months. ③ NMDS results showed that the correlation between Cylindrospermopsis or Pseudoanabaena and the ambient phytoplankton community was 0.58 and 0.48, respectively. Moreover, the VPA results showed that 47.51% of the community variation could be explained by environmental factors, and only 12.04% and 12.74% of variation in community composition could be explained by Cylindrospermopsis and Pseudoanabaena , respectively. ④ The abundance of Cylindrospermopsis was significantly positively affected by WT, pH, and RUE N and negatively affected by SD and RUE P . However, the abundance of Pseudoanabaena was significantly positively affected by permanganate index and negatively affected by EC and DO. These results suggested that both dominating cyanobacteria had significant effects on the surrounding phytoplankton community. Relative to that of Pseudoanabaena , however, Cylindrospermopsis had a more obvious impact on the aquatic ecosystem. Moreover, the synergistic effect of N limitation and warming of the water column may have caused the replacement of Pseudoanabaena with Cylindrospermopsis to form a dominant population.

Ipilimumab, a monoclonal antibody that recognizes cytotoxic T-lymphocyte associated protein 4 (CTLA-4), was the first immune checkpoint inhibitor approved by the FDA to treat metastatic melanoma patients. Multiple preclinical studies have proposed that Fc effector functions of anti-CTLA-4 therapy are required for anti-tumor efficacy, in part, through the depletion of intratumoral regulatory T cells (Tregs). However, the contribution of the Fc-independent functions of anti-CTLA-4 antibodies to the observed efficacy is not fully understood. H11, a non-Fc-containing single-domain antibody (VHH) against CTLA-4, has previously been demonstrated to block CTLA-4-ligand interaction. However, in vivo studies demonstrated lack of anti-tumor efficacy with H11 treatment. Here, we show that a half-life extended H11 (H11-HLE), despite the lack of Fc effector functions, induced potent anti-tumor efficacy in mouse syngeneic tumor models. In addition, a non-Fc receptor binding version of ipilimumab (Ipi-LALAPG) also demonstrated anti-tumor activity in the absence of Treg depletion. Thus, we demonstrate that Fc-independent functions of anti-CTLA-4 antibodies contributed to anti-tumor efficacy, which may indicate that non-Treg depleting activity of anti-CTLA-4 therapy could benefit cancer patients in the clinic., (© 2022. The Author(s).)