Challenging Scenarios Research Articles

Propensity score matched comparison of transperitoneal laparoscopic ureterolithotomy and percutaneous nephrolithotomy for management of large impacted proximal ureteral stones with long-term follow-up.

Impacted proximal ureteral stones (IPUS) present challenging clinical scenarios due to their persistent nature and associated complications. While ureterorenoscopy (URS) lithotripsy is recommended as the primary treatment, controversies exist regarding the optimal management of such stones. In this retrospective analysis, we compared the operative outcomes and long-term results of transperitoneal laparoscopic ureterolithotomy (LU) and percutaneous nephrolithotomy (PCNL) for IPUS larger than 15mm. Propensity score matching (PSM) was employed to mitigate potential selection biases. Following PSM, 83 patients in each cohort exhibited comparable baseline characteristics. LU demonstrated a superior surgical success rate (100% vs. 96.4%, p = 0.244) and significantly lower perioperative hemoglobin decline (0.6 ± 0.4g/dL vs. 1.5 ± 0.7g/dL, p = 0.036) compared to PCNL. Additionally, LU exhibited a higher stone-free rate after 2 months (100% vs. 91.6%, p = 0.043), but a longer duration of catheterization (7.4 ± 1.2 days vs. 3.5 ± 2.2 days vs., p = 0.011). Conversely, PCNL was associated with a higher incidence of total complications (21.7% vs. 9.6%, p = 0.033) and stone recurrence during a mean period of 40-month follow-up (20.5% vs. 8.4%, p = 0.027). Transperitoneal LU and PCNL represent effective interventions for managing IPUS exceeding 15mm. Notably, LU emerges as a preferable option over PCNL, offering superior stone clearance rates, reduced perioperative complications, and lower recurrence rates.

Attribute-guided prototype network for few-shot molecular property prediction.

The molecular property prediction (MPP) plays a crucial role in the drug discovery process, providing valuable insights for molecule evaluation and screening. Although deep learning has achieved numerous advances in this area, its success often depends on the availability of substantial labeled data. The few-shot MPP is a more challenging scenario, which aims to identify unseen property with only few available molecules. In this paper, we propose an attribute-guided prototype network (APN) to address the challenge. APN first introduces an molecular attribute extractor, which can not only extract three different types of fingerprint attributes (single fingerprint attributes, dual fingerprint attributes, triplet fingerprint attributes) by considering seven circular-based, five path-based, and two substructure-based fingerprints, but also automatically extract deep attributes from self-supervised learning methods. Furthermore, APN designs the Attribute-Guided Dual-channel Attention module to learn the relationship between the molecular graphs and attributes and refine the local and global representation of the molecules. Compared with existing works, APN leverages high-level human-defined attributes and helps the model to explicitly generalize knowledge in molecular graphs. Experiments on benchmark datasets show that APN can achieve state-of-the-art performance in most cases and demonstrate that the attributes are effective for improving few-shot MPP performance. In addition, the strong generalization ability of APN is verified by conducting experiments on data from different domains.

Clinical predictors of successful outcomes for couples with nonobstructive azoospermic male partners undergoing micro-TESE.

Nonobstructive azoospermia (NOA) is the most challenging and complex clinical scenario for infertile men. Besides circumstances such as hypogonadotropic hypogonadism, surgical sperm retrieval is typically necessary, and microdissection testicular sperm extraction (micro-TESE) is the procedure of choice for men with NOA desiring to father children with their own gametes. Micro-TESE results in the highest numbers of sperm cells retrieved for use with in vitro fertilization/intracytoplasmic sperm injection (ICSI) in comparison to all other techniques for surgical sperm retrieval in men with NOA. Several factors may affect sperm retrieval rate and ICSI outcomes, including the patient's age, testicular volume, histopathological and genetic profile, and serum hormone levels. This article aims to review the medical literature describing predictors of successful micro-TESE and the outcomes of ICSI in men with NOA.

Bacillus paralicheniformis, an acetate-producing probiotic, alleviates ulcerative colitis via protecting the intestinal barrier and regulating the NLRP3 inflammasome

Ulcerative colitis (UC) presents a challenging scenario in digestive health, characterized by recurrent inflammation that is often hard to manage. Bacteria capable of producing short-chain fatty acids (SCFAs) play a pivotal role in mitigating UC symptoms, rendering them promising candidates for probiotic therapy. In this investigation, we assessed the impact of Bacillus paralicheniformis HMPM220325 on dextran sodium sulfate (DSS)-induced UC in mice. Genomic analysis of the strain revealed the presence of protease genes associated with acetate and butyrate synthesis, with acetic acid detected in its fermentation broth. Administration of B. paralicheniformis HMPM220325 to UC mice ameliorated pathological manifestations of the condition and restored intestinal barrier function. Furthermore, B. paralicheniformis HMPM220325 suppressed the activation of the NLRP3 inflammasome signaling pathway and modulated the composition of the intestinal microbiota. These findings shed significant light on the potential of B. paralicheniformis as a probiotic candidate, offering a novel avenue for the prevention and therapeutic intervention of colitis.

The inner struggle of nurses, exploring moral distress among hospital nurses: A cross-sectional study

BackgroundAs frontline caregivers, nurses often find themselves at the crossroads of complex ethical decisions that can significantly impact patient outcomes and their own well-being. Identifying the areas of experienced moral dilemmas in the workplace and gaining insight into the prevalence of moral distress can lead to a healthier workplace environment. ObjectiveThis study aims to examine the frequency, intensity and level of moral distress among nurses who work in a hospital, and to identify the variables associated with the level of moral distress. DesignCross-sectional study. SettingOne university hospital and six general hospitals. Participants654 of the 1095 nurses working on inpatient units filled out the questionnaire (response rate 60 %). MethodsThe intensity and frequency of moral distress was assessed using the Moral Distress Scale-Revised (MDS-R). We also asked two additional questions about considering leaving their job, and if they could describe a distressing case and how moral distress was discussed. Multivariable regression analysis was conducted to identify the variables associated with the level of moral distress. ResultsThe overall mean MDS-R score of the 654 included nurses was low at 36.4 (SD 26). Nurses reported to have frequent dilemmas regarding organizational aspects and aspects of end-of-life care. The multivariable analyses showed that higher levels of moral distress were experienced by registered nurses, nurses working on a medical ward, and nurses who had ever left or considered leaving their job, or considering leaving their job at the moment. ConclusionsAlthough nurses in our study experiences low levels of moral distress, they do experience moral dilemmas related to organizational topics and end of life care. We all need to pay attention to these dilemmas and how to discuss them in order to achieve a resilient nursing profession at a time of major nursing shortages. Tweetable abstractCaring for increasingly complex patients in a dynamic healthcare system is likely to continue to produce morally challenging scenarios.

RevGNN: Negative Sampling Enhanced Contrastive Graph Learning for Academic Reviewer Recommendation

Acquiring reviewers for academic submissions is a challenging recommendation scenario. Recent graph learning-driven models have made remarkable progress in the field of recommendation, but their performance in the academic reviewer recommendation task may suffer from a significant false negative issue. This arises from the assumption that unobserved edges represent negative samples. In fact, the mechanism of anonymous review results in inadequate exposure of interactions between reviewers and submissions, leading to a higher number of unobserved interactions compared to those caused by reviewers declining to participate. Therefore, investigating how to better comprehend the negative labeling of unobserved interactions in academic reviewer recommendations is a significant challenge. This study aims to tackle the ambiguous nature of unobserved interactions in academic reviewer recommendations. Specifically, we propose an unsupervised Pseudo Neg-Label strategy to enhance graph contrastive learning (GCL) for recommending reviewers for academic submissions, which we call RevGNN. RevGNN utilizes a two-stage encoder structure that encodes both scientific knowledge and behavior using Pseudo Neg-Label to approximate review preference. Extensive experiments on three real-world datasets demonstrate that RevGNN outperforms all baselines across four metrics. Additionally, detailed further analyses confirm the effectiveness of each component in RevGNN.

DDR: A network of image deraining systems for dark environments

In the domain of computer vision, addressing the degradation of image quality under adverse weather conditions remains a significant challenge. To tackle the challenges of image enhancement and deraining in dark settings, we have integrated image enhancement and deraining technologies to develop the DDR (Dark Environment Deraining Network) system. This specialized network is designed to enhance and clarify images in low-light conditions compromised by raindrops. DDR employs a strategic divide-and-conquer approach and an apt network selection to discern patterns of raindrops and background elements within images. It is capable of mitigating noise and blurring induced by raindrops in dark settings, thus enhancing the visual fidelity of images. Through testing on real-world imagery and the Rain LOL dataset, this innovative network offers a robust solution for deraining tasks in dark conditions, inspiring advancements in the performance of computer vision systems under challenging weather scenarios. The research of DDR provides technical and theoretical support for improving image quality in dark environment.

Optimizing microwave heating with slotted metal tubes for cylindrical loads

Cylindrical loads are commonly encountered in microwave heating and often suffer from uneven thermal distribution. Within certain radius and dielectric parameter ranges, cylindrical loads may exhibit central thermal focusing. This paper proposes a novel microwave heating method employing a slotted metal tube (SMT) to encase the cylindrical materials. The SMT alters the electric field distribution and enhances the coupling of microwave energy, thereby improving the heating uniformity and efficiency. We first developed a simulation model for microwave heating, analyzing how permittivity and dimensions affect the thermal focus of cylindrical materials. By optimizing the slot dimensions and positions, we overcome the thermal focusing phenomenon. Then, we conducted microwave heating experiments with mashed potatoes, showing that the use of SMT improved the temperature uniformity by 38 % and increased the microwave energy conversion efficiency by 48 %. Furthermore, we applied SMT to a more challenging scenario, involving the heating of cylindrical canned foods with metal lids, using a dual-source heating setup. The experimental results indicated that SMT remained effective in enhancing heating uniformity and efficiency. This method contributes to the development of microwave energy industrial applications, providing innovative solutions for cylindrical load heating.

Meta-long Papyrus: Meta-analysis of mid to long-term outcomes of PK Papyrus covered stent.

Although covered stents (CS) represent a potentially life-saving intervention for coronary perforation (CAP), their application has expanded to other contexts, including coronary aneurysms (CAA). However, data regarding mid- and long-term outcomes of CS in these settings scenarios remains limited. This meta-analysis aims to evaluate major adverse cardiac events (MACE) from discharge through long-term follow-up in patients undergoing percutaneous coronary intervention with the new generation polyurethane-covered cobalt-chromium PK Papyrus CS. We conducted a meta-analysis of data from three observational trials that included long-term follow-up of patients who underwent PK Papyrus CS implantation: Papyrus-Spain, SOS PK Papyrus, and PAST-PERF registry. 332 patients underwent PK Papyrus CS implantation, 236 (71.1%) for CAP, 70 (21.1%) for CAA and 26 (7.8%) for other indications. After a mean follow-up of 16.2 months, the MACE was 14.3%, with Target Lesion Revascularization (TLR) being the most frequent (8.5%), followed by stent thrombosis (ST), 3.3% and cardiac death (CD), 2.6%. Comparing CAP and CAA subgroups, the MACE rate in CAA was significantly higher than CAP (21.4% vs 9.7%, p < 0.01), primary driven by ST (CAA: 8.6% vs CAP: 1.3%; p = 0.0015). The clinical outcomes following PK Papyrus CS implantation are deemed acceptable, considering the challenging scenarios and the existing alternative treatments. However, MACE rates in patients with CAA who received Papyrus PK CS were significantly higher than in those with CAP, underscoring the importance of meticulous patient selection and optimization of CS in these complex patients and coronary anatomies.

RealFill: Reference-Driven Generation for Authentic Image Completion

Recent advances in generative imagery have brought forth outpainting and inpainting models that can produce high-quality, plausible image content in unknown regions. However, the content these models hallucinate is necessarily inauthentic, since they are unaware of the true scene. In this work, we propose RealFill, a novel generative approach for image completion that fills in missing regions of an image with the content that should have been there. RealFill is a generative inpainting model that is personalized using only a few reference images of a scene. These reference images do not have to be aligned with the target image, and can be taken with drastically varying viewpoints, lighting conditions, camera apertures, or image styles. Once personalized, RealFill is able to complete a target image with visually compelling contents that are faithful to the original scene. We evaluate RealFill on a new image completion benchmark that covers a set of diverse and challenging scenarios, and find that it outperforms existing approaches by a large margin. Project page: https://realfill.github.io.

Clinical outcomes of short dental implants supporting prostheses in the posterior region.

Aim In clinically challenging scenarios with limited bone height and anatomical restrictions, the use of short implants have been proposed as a potential treatment strategy. The purpose of this retrospective study was to evaluate the clinical outcomes of short implants supporting prostheses in the posterior premolar region of the maxilla and mandible.Materials and methods A total of 30 patients requiring short 6 mm length implant placement in the posterior premolar region were included. Following a period of osseointegration, the implants were restored with either single crowns, fixed bridges or implant-supported removable overdentures. Implant and prosthetic survival with technical complications were recorded.Results In total, 45 implants were placed, with four failures reported before loading in two patients, resulting in a patient implant survival rate of 93.3% over the two-year follow-up. There was no statistically significant difference found between implant failure and arch placement. Prosthetic survival was 100% and minor technical complications recorded were low.Conclusion This study showed that short 6 mm implants could provide a viable treatment option, with high survival rates comparable with alternative bone augmentation procedures. Further research with longer observation periods would be required to validate these current findings.

Results of Tendon Transfers in Radial Nerve Palsies: A New Evaluation Protocol.

Radial nerve palsies present a challenging clinical scenario, often leading to substantial functional impairment. This study focuses on evaluating the outcomes of tendon transfer surgeries in patients with post-traumatic radial nerve injuries. The radial nerve, vital for upper limb movements, faces various etiologies, such as trauma, compression, or idiopathy. Patients with radial nerve palsy encounter difficulties in daily activities, emphasizing the need for effective management strategies. The research introduces a novel evaluation protocol, aiming to comprehensively assess tendon transfer outcomes. This protocol incorporates functional movements of wrist and finger joints, encompassing both objective and subjective parameters. The retrospective study includes eleven patients treated between 2010 and 2022, with a minimum follow-up of one year post-surgery. Tendon transfers demonstrated positive results. The evaluation protocol covers a wide range of parameters, including wrist and finger mobility, thumb function, grip strength, and patient satisfaction. The results indicate successful restoration of motor function, with an average grip strength of 70% compared to the healthy arm. The proposed evaluation protocol facilitates standardized and reproducible assessment, minimizing subjective errors in clinical evaluations. Despite the study's limitations, such as a relatively small sample size, the findings underscore the effectiveness of tendon transfers in treating radial nerve palsies. The introduced evaluation scheme provides a comprehensive and reproducible approach to assess outcomes, contributing to the global standardization of tendon transfer assessments in radial nerve injuries.

Breathing Monitoring in Soccer: Part I-Validity of Commercial Wearable Sensors.

Growing evidence suggests that respiratory frequency (fR) is a valid marker of effort during high-intensity exercise, including sports of an intermittent nature, like soccer. However, very few attempts have been made so far to monitor fR in soccer with unobtrusive devices. This study assessed the validity of three strain-based commercial wearable devices measuring fR during soccer-specific movements. On two separate visits to the soccer pitch, 15 players performed a 30 min validation protocol wearing either a ComfTech® (CT) vest or a BioharnessTM (BH) 3.0 strap and a Tyme WearTM (TW) vest. fR was extracted from the respiratory waveform of the three commercial devices with custom-made algorithms and compared with that recorded with a reference face mask. The fR time course of the commercial devices generally resembled that of the reference system. The mean absolute percentage error was, on average, 7.03% for CT, 8.65% for TW, and 14.60% for BH for the breath-by-breath comparison and 1.85% for CT, 3.27% for TW, and 7.30% for BH when comparison with the reference system was made in 30 s windows. Despite the challenging measurement scenario, our findings show that some of the currently available wearable sensors are indeed suitable to unobtrusively measure fR in soccer.

Reinforcement learning with predefined and inferred reward machines in stochastic games

This paper focuses on Multi-Agent Reinforcement Learning (MARL) in non-cooperative stochastic games, particularly addressing the challenge of task completion characterized by non-Markovian reward functions. We employ Reward Machines (RMs) to incorporate high-level task knowledge. Firstly, we introduce Q-learning with Reward Machines for Stochastic Games (QRM-SG), where RMs are predefined and available to agents. QRM-SG learns each agent’s best-response policy at Nash equilibrium by defining the Q-function in augmented state space that integrates the stochastic game and RM states. The Lemke-Howson method is utilized to compute the best-response policies for the stage game defined by the current Q-functions at each time step. Subsequently, we explore a more challenging scenario where RMs are unavailable and propose Multi-Agent Reinforcement learning with Concurrent High-level knowledge inference (MARCH). MARCH uses automata learning to learn RMs iteratively and combines this process with QRM-SG for learning the best-response policies. The RL episodes where the obtained rewards are inconsistent with the rewards from the current RMs trigger the inference of new RMs. We prove QRM-SG and MARCH converge to the best-response policies under certain conditions. Two scenarios are conducted to demonstrate the superior performance of QRM-SG and MARCH compared to baseline methods.

Investigating the crowding effect on letters and symbols in deaf adults

Reading requires the transformation of a complex array of visual features into sounds and meaning. For deaf signers who experience changes in visual attention and have little or no access to the sounds of the language they read, understanding the visual constraints underlying reading is crucial. This study aims to explore a fundamental aspect of visual perception intertwined with reading: the crowding effect. This effect manifests as the struggle to distinguish a target letter when surrounded by flanker letters. Through a two-alternative forced choice task, we assessed the recognition of letters and symbols presented in isolation or flanked by two or four characters, positioned either to the left or right of fixation. Our findings reveal that while deaf individuals exhibit higher accuracy in processing letters compared to symbols, their performance falls short of that of their hearing counterparts. Interestingly, despite their proficiency with letters, deaf individuals didn’t demonstrate quicker letter identification, particularly in the most challenging scenario where letters were flanked by four characters. These outcomes imply the development of a specialized letter processing system among deaf individuals, albeit one that may subtly diverge from that of their hearing counterparts.

Efficacy and safety of trifluridine/tipiracil plus bevacizumab across different subgroups of patients with refractory colorectal cancer: a meta-analysis.

Metastatic colorectal cancer (mCRC) patients who are refractory to initial treatment lines exhibit a challenging clinical scenario characterised by a poor prognosis and constrained therapeutic options. This systematic review and meta-analysis assess the integration of bevacizumab into trifluridine-tipiracil (TFD/TPI) therapy for mCRC, examining its benefits across patient subgroups and evaluating safety relative to TFD/TPI monotherapy. Following preferred reporting items for systematic reviews and meta-analysis statements, we conducted a thorough literature search from 15 October to 11 November 2023, covering MEDLINE, Embase and the Cochrane database. Data extraction and quality assessment followed Cochrane guidelines, and hazard or odds ratios with 95% confidence intervals (CI) were pooled (p < 0.05 significance threshold). The study protocol is registered in PROSPERO (CRD42023484695). Analysing 770 database results, we included two randomised controlled trials and five observational studies covering over 4,000 patients. Combined therapy exhibited significant improvements in overall survival (OS) hazard ratios (HR 0.60; 95% CI 0.49-0.72; p < 0.01) and progression-free survival (HR 0.48; 95% CI 0.40-0.59; p < 0.01). Subgroups, including prior bevacizumab exposure (HR 0.70; 95% CI 0.64-0.77; p < 0.01) and mutated RAS gene (HR 0.64; 95% CI 0.53-0.77; p < 0.01), demonstrated improvements in OSwith bevacizumab. This meta-analysis underscores the heightened efficacy of TFD/TPI combined with bevacizumab for refractory mCRC compared to TFD/TPI monotherapy across diverse subgroups. Combined therapy has increased grade ≥3 neutropenia and hypertension, while monotherapy is associated with fatigue and anemia.

Re-irradiation in High-grade Glioma: An Experience from A Series of Five Patients

ABSTRACT The management of recurrences or residual lesions following radiation therapy for brain tumors poses a challenging clinical scenario, necessitating careful consideration for treatment strategies. There is no standard of care for patients with recurrent high-grade glioma. Treatment strategies include resection, re-irradiation, systemic agents, and intratumoral thermotherapy using magnetic iron-oxide nanoparticles (nanotherapy). A small percentage of patients can undergo repeat surgery and re-radiation is also a matter of concern due to anticipated toxicities. However, advancements in radiation technology have made people more willing to consider re-irradiation. In this study, we retrospectively analyzed patients who underwent re-irradiation for high-grade glioma. In total, five patients were included in the study. All five patients had anaplastic astrocytoma. All patients were considered for surgery, followed by radiation therapy during the initial treatment. Three patients had an average of 4 years of symptom-free survival, while the other two had symptoms ranging from moderate to severe. Three of the five patients died within 1 year of taking the re-radiation; however, two patients are still in follow-up.

A Deep Reinforcement Learning-Based Intelligent Maneuvering Strategy for the High-Speed UAV Pursuit-Evasion Game

Given the rapid advancements in kinetic pursuit technology, this paper introduces an innovative maneuvering strategy, denoted as LSRC-TD3, which integrates line-of-sight (LOS) angle rate correction with deep reinforcement learning (DRL) for high-speed unmanned aerial vehicle (UAV) pursuit–evasion (PE) game scenarios, with the aim of effectively evading high-speed and high-dynamic pursuers. In the challenging situations of the game, where both speed and maximum available overload are at a disadvantage, the playing field of UAVs is severely compressed, and the difficulty of evasion is significantly increased, placing higher demands on the strategy and timing of maneuvering to change orbit. While considering evasion, trajectory constraint, and energy consumption, we formulated the reward function by combining “terminal” and “process” rewards, as well as “strong” and “weak” incentive guidance to reduce pre-exploration difficulty and accelerate convergence of the game network. Additionally, this paper presents a correction factor for LOS angle rate into the double-delay deterministic gradient strategy (TD3), thereby enhancing the sensitivity of high-speed UAVs to changes in LOS rate, as well as the accuracy of evasion timing, which improves the effectiveness and adaptive capability of the intelligent maneuvering strategy. The Monte Carlo simulation results demonstrate that the proposed method achieves a high level of evasion performance—integrating energy optimization with the requisite miss distance for high-speed UAVs—and accomplishes efficient evasion under highly challenging PE game scenarios.

Practical guide to writing cover letters and response letters for scientific journals

Communicating with scientific journals is a central part of the publication process, yet sparsely covered in the medical literature. A cover letter to the editor(s) should always accompany new submissions, whereas response (or rebuttal) letters relate to revisions and replying to referees' comments following peer review. This review describes the two types of letters, focusing on content, style, and structure, and provides helpful tips for handling challenging reviewer scenarios.

Molecular and diffusion features for identification of clinically significant prostate cancer in PI-RADS 3 lesions

BackgroundThe recommendation to perform biopsy of PIRADS 3 lesions has not been adopted with strength as compared to higher scored lesions on multiparametric MRI. This represents a challenging scenario and an unmet need for clinicians to apply a risk adapted approach in these cases. In the present study, we examined clinical and radiologic characteristics in men with PI-RADS 3 index lesions that can predict csPCa on mpMRI-target biopsy. MethodsRevision of a prospective database with patients who underwent targeted and systematic biopsies from 2015 to 2023 for PI-RADS 3 lesions identified on mpMRI. Baseline variables were collected, such as PSA density (PSAd), 4Kscore, prostate size, and the apparent diffusion coefficient (ADC) value of the lesion on mpMRI. Logistic regression, receiver operating characteristic (ROC) and decision curve analyses (DCA) assessing the association between clinic-radiologic factors and csPCa were performed. ResultsOverall, 230 patients were included in the study and the median age was 65 years. The median prostate size and PSA were 50 g and 6.26 ng/mL, respectively. 17.4% of patients had csPCa, while 27.5% had Gleason group 1. In univariable logistic analyses, we found that age, BMI, prostate size, PSAd, ADC, and 4Kscore were significant csPCa predictors (P < 0.05). PSAd showed the best prediction performance in terms of AUC (= 0.679). On multivariable analysis, PSAd and 4Kscore were associated with csPCa. The net benefit of PSAd combined with clinical features was superior to those of other parameters. Within patients with PSAd < 0.15, 4Kscore was a statistically significant predictor of csPCa (OR = 3.25, P = 0.032). ConclusionPSAd and 4Kscore are better predictors of csPCa in patients with PIRADS 3 lesions compared to ADC. The predictive role of 4Kscore is higher in patients with low PSAd. These results can assist practitioners in the risk stratification of patients with equivocal lesions to determine the need of biopsy.