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Background. Transplant centers have traditionally relied upon procurement teams from their own programs (transplant program procurement team [TPT]) to recover donation after circulatory death (DCD) livers and rarely use surgical procurement teams not affiliated with the recipient center (nontransplant program procurement team [NTPT]). However, in the era of wider geographic organ sharing, greater reliance on NTPTs is often necessary. Methods. We used national data to study the association between the origin of the donor procurement team (NTPT versus TPT) and the risk of DCD liver allograft failure. Results. Five hundred NTPT and 2257 TPT DCD transplants were identified: 1-y graft survival was 88.9 and 88.6%, respectively (P = 0.962). In a multivariable model, the origin of the procurement team was not associated with graft failure NTPT versus TPT (hazard ratio, 0.92; 95% confidence interval, 0.71-1.22; P = 0.57) but rather with known risks for DCD graft loss including donor age, degree of recipient illness, cold ischemic time, and retransplantation. The overall incidence of retransplantation and ischemic cholangiopathy as an indication for retransplantation were similar between NTPT and TPT. Conclusions. This data suggests that transplant centers may be able to safely use DCD livers recovered by local surgical teams.

The standard of care for non-metastatic muscle invasive bladder cancer is either radical cystectomy or bladder preservation therapy, which consists of maximal transurethral bladder resection of the tumor followed by concurrent chemoradiation with a cisplatin-based regimen. However, for older cancer patients who are too frail for surgical resection or have decreased renal function, radiotherapy alone may offer palliation. Recently, immunotherapy with immune checkpoint inhibitors (ICI) has emerged as a promising treatment when combined with radiotherapy due to the synergy of those two modalities. Transitional carcinoma of the bladder is traditionally a model for immunotherapy with an excellent response to Bacille Calmette-Guerin (BCG) in early disease stages, and with avelumab and atezolizumab for metastatic disease. Thus, we propose an algorithm combining immunotherapy and radiotherapy for older patients with locally advanced muscle-invasive bladder cancer who are not candidates for cisplatin-based chemotherapy and surgery.

The standard of care for non-metastatic renal cancer is surgical resection followed by adjuvant therapy for those at high risk for recurrences. However, for older patients, surgery may not be an option due to the high risk of complications which may result in death. In the past renal cancer was considered to be radio-resistant, and required a higher dose of radiation leading to excessive complications secondary to damage of the normal organs surrounding the cancer. Advances in radiotherapy technique such as stereotactic body radiotherapy (SBRT) has led to the delivery of a tumoricidal dose of radiation with minimal damage to the normal tissue. Excellent local control and survival have been reported for selective patients with small tumors following SBRT. However, for patients with poor prognostic factors such as large tumor size and aggressive histology, there was a higher rate of loco-regional recurrences and distant metastases. Those tumors frequently carry program death ligand 1 (PD-L1) which makes them an ideal target for immunotherapy with check point inhibitors (CPI). Given the synergy between radiotherapy and immunotherapy, we propose an algorithm combining CPI and SBRT for older patients with non-metastatic renal cancer who are not candidates for surgical resection or decline nephrectomy.

Men historically consume more meat than women, show fewer intentions to reduce meat consumption, and are underrepresented among vegans and vegetarians. Eating meat strongly aligns with normative masculinities, decisively affirming that “real men” eat meat and subordinating men who choose to be veg* n (vegan or vegetarian). The emergence of meat alternatives and increasing environmental concerns may contest these long-standing masculine norms and hierarchies. The current scoping review addresses the research question what are the connections between masculinities and men’s attitudes and behaviors toward meat consumption and veg*nism? Using keywords derived from two key concepts, “men” and “meat,” 39 articles were selected and analyzed to inductively derive three thematic findings; (a) Meat as Masculine, (b) Veg*n Men as Othered, and (c) Veg*nism as Contemporary Masculinity. Meat as Masculine included how men’s gendered identities, defenses, and physicalities were entwined with meat consumption. Veg*n Men as Othered explored the social and cultural challenges faced by men who adopt meatless diets, including perceptions of emasculation. Veg*nism as Contemporary Masculinity was claimed by men who eschewed meat in their diets and advocated for veg*nism as legitimate masculine capital through linkages to physical strength, rationality, self-determination, courage, and discipline. In light of the growing concern about the ecological impact of meat production and the adverse health outcomes associated with its excessive consumption, this review summarizes empirical connections between masculinities and the consumption of meat to consider directions for future men’s health promotion research, policy, and practice.

Abstract Food banks have played a crucial role in mitigating food insecurity in affluent countries for over four decades. Throughout the years, academics have researched food banks for a variety of operational problems, resulting in several research papers on the topic. However, despite significant academic interest, the operational challenges and optimization of food bank operations remain under-researched. This study aims to conduct a systematic literature review on food bank operations and provide evidence-based recommendations for addressing prevalent challenges, and provide decision-makers with practical recommendations. In addition, this investigation seeks to investigate the impact of the COVID-19 pandemic on food bank operations. We conducted a comprehensive analysis of academic publications on food bank operations using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in order to get a deeper comprehension of the problems confronting food bank operations. Using a keyword search strategy with the logical operators “AND” and “OR,” two search methods were utilized to identify relevant articles on food bank operations management, supply chain, distribution, and production in our first search. In our second search, we discovered articles in the “Operations Research & Management Science” (OR &MS) category of Web of Science containing food bank-related keywords such as food charity, food donation, and food aid. The database searches yielded 246 hits, and the article content was scanned to eliminate irrelevant articles by removing non-English articles and duplicated studies, leaving 55 articles for further examination. Our extensive examination of Operations Research (OR) methodologies reveals that Mixed-Integer Linear Programming (MILP) models are the most commonly used methodology, followed by Linear Program (LP), Dynamic Program (DP), and Data Envelopment Analysis (DEA) techniques. The key findings of this study emphasize the operational challenges food banks encountered during and after the COVID-19 pandemic, including supply chain disruptions, increased demand, and volunteer shortages. To address these issues, effective solutions, including the management of food donations and volunteer scheduling, were proposed. Our findings have practical implications for decision-makers in food bank management, highlighting the importance of adopting evidence-based solutions. Finally, Limitations and prospective research directions in food bank management are discussed, with an emphasis on the need for ongoing research in this crucial area.

This study examines the impact of welding heat input on the residual stress and welding deformation of large, thin-walled constructions made of ultra-high strength steel using a single shot calculation method. These structures are susceptible to warpage distortion after welding, which negatively affects production precision. The study uses an interactive orthogonal experimental design to optimize welding parameters and investigate their influence on deformation. Results reveal that welding speed has the most significant impact on deformation, followed by welding voltage and current. The optimal welding parameters (v = 60 cm/min, I = 160 A, U = 16 V) are validated through simulation and experiment, which reduce deformation by 5.4%. After optimization, the pump arm's side bending volume and warpage volume decrease by 4.06% and 9.56%, respectively, and welding deformation significantly reduces. Experimental verification shows a maximum error of 2.6%, indicating the accuracy of the finite element model. This study provides a theoretical basis for improving the performance of welding large, thin-walled box structures.

The standard of care for locally advanced rectal cancer is total neoadjuvant therapy followed by surgical resection. Current evidence suggests that selected patients may be able to delay or avoid surgery without affecting survival rates if they achieve a complete clinical response (CCR). However, for older cancer patients who are too frail for surgery or decline the surgical procedure, local recurrence may lead to a deterioration of patient quality of life. Thus, for clinicians, a treatment algorithm which is well tolerated and may improve CCR in older and frail patients with rectal cancer may improve the potential for prolonged remission and potential cure. Recently, immunotherapy with check point inhibitors (CPI) is a promising treatment in selected patients with high expression of program death ligands receptor 1 (PD- L1). Radiotherapy may enhance PD-L1 expression in rectal cancer and may improve response rate to immunotherapy. We propose an algorithm combining immunotherapy and radiotherapy for older patients with locally advanced rectal cancer who are too frail for surgery or who decline surgery.

Abstract Background The mechanisms underlying dysfunction of choroid plexus (ChP) blood–cerebrospinal fluid (CSF) barrier and lymphocyte invasion in neuroinflammatory responses to stroke are not well understood. In this study, we investigated whether stroke damaged the blood–CSF barrier integrity due to dysregulation of major ChP ion transport system, Na+–K+–Cl− cotransporter 1 (NKCC1), and regulatory Ste20-related proline-alanine-rich kinase (SPAK). Methods Sham or ischemic stroke was induced in C57Bl/6J mice. Changes on the SPAK–NKCC1 complex and tight junction proteins (TJs) in the ChP were quantified by immunofluorescence staining and immunoblotting. Immune cell infiltration in the ChP was assessed by flow cytometry and immunostaining. Cultured ChP epithelium cells (CPECs) and cortical neurons were used to evaluate H2O2-mediated oxidative stress in stimulating the SPAK–NKCC1 complex and cellular damage. In vivo or in vitro pharmacological blockade of the ChP SPAK–NKCC1 cascade with SPAK inhibitor ZT-1a or NKCC1 inhibitor bumetanide were examined. Results Ischemic stroke stimulated activation of the CPECs apical membrane SPAK–NKCC1 complex, NF-κB, and MMP9, which was associated with loss of the blood–CSF barrier integrity and increased immune cell infiltration into the ChP. Oxidative stress directly activated the SPAK–NKCC1 pathway and resulted in apoptosis, neurodegeneration, and NKCC1-mediated ion influx. Pharmacological blockade of the SPAK–NKCC1 pathway protected the ChP barrier integrity, attenuated ChP immune cell infiltration or neuronal death. Conclusion Stroke-induced pathological stimulation of the SPAK–NKCC1 cascade caused CPECs damage and disruption of TJs at the blood–CSF barrier. The ChP SPAK–NKCC1 complex emerged as a therapeutic target for attenuating ChP dysfunction and lymphocyte invasion after stroke.

Abstract Background Rural and remote communities faced unique access challenges to essential services such as healthcare and highspeed infrastructure pre-COVID, which have been amplified by the pandemic. This study examined patterns of COVID-related challenges and the use of technology among rural-living individuals during the first wave of the COVID-19 pandemic. Methods A sample of 279 rural residents completed an online survey about the impact of COVID-related challenges and the role of technology use. Latent class analysis was used to generate subgroups reflecting the patterns of COVID-related challenges. Differences in group membership were examined based on age, gender, education, race/ethnicity, and living situation. Finally, thematic analysis of open-ended qualitative responses was conducted to further contextualize the challenges experienced by rural-living residents. Results Four distinct COVID challenge impact subgroups were identified: 1) Social challenges (35%), 2) Social and Health challenges (31%), 3) Social and Financial challenges (14%), and 4) Social, Health, Financial, and Daily Living challenges (19%). Older adults were more likely to be in the Social challenges or Social and Health challenges groups as compared to young adults who were more likely to be in the Social, Health, Financial, and Daily Living challenges group. Additionally, although participants were using technology more frequently during the COVID-19 pandemic to address challenges, they were also reporting issues with quality and connectivity as a significant barrier. Conclusions These analyses found four different patterns of impact related to social, health, financial, and daily living challenges in the context of COVID. Social needs were evident across the four groups; however, we also found nearly 1 in 5 rural-living individuals were impacted by an array of challenges. Access to reliable internet and devices has the potential to support individuals to manage these challenges.

Abstract Machine learning algorithms may address prognostic inaccuracy among clinicians by identifying patients at risk of short-term mortality and facilitating earlier discussions about hospice enrollment, discontinuation of therapy, or other management decisions. In the present study, we used prospective predictions from a real-time machine learning prognostic algorithm to identify two trajectories of all-cause mortality risk for decedents with cancer. We show that patients with an unpredictable trajectory, where mortality risk rises only close to death, are significantly less likely to receive guideline-based end-of-life care and may not benefit from the integration of prognostic algorithms in practice.

ABSTRACT Antibiotics are known to induce gut dysbiosis and increase the risk of antibiotic resistance. While antibiotic exposure is a known risk factor leading to compromised colonization resistance against enteric pathogens such as Clostridioides difficile, the extent and consequences of antibiotic perturbation on the human gut microbiome remain poorly understood. Human studies on impacts of antibiotics are complicated by the tremendous variability of gut microbiome among individuals, even between identical twins. Furthermore, antibiotic challenge experiments cannot be replicated in human subjects for a given gut microbiome. Here, we transplanted feces from three unrelated human donors into groups of identical germfree (GF) Swiss-Webster mice, and examined the temporal responses of the transplanted microbiome to oral clindamycin challenge in gnotobiotic isolators over 7 weeks. Analysis of 177 longitudinal fecal samples revealed that 59% to 81% of human microbiota established a stable configuration rapidly and stably in GF mice. Microbiome responses to clindamycin challenge was highly reproducible and microbiome-dependent. A short course of clindamycin was sufficient to induce a profound loss (∼one third) of the microbiota by disproportionally eliminating minority members of the transplanted microbiota. However, it was inadequate to disrupt the global microbial community structure or function, which rebounded rapidly to resemble its pre-treatment state after clindamycin discontinuation. Furthermore, the response of individual microbes was community-dependent. Taken together, these results suggest that the overall gut microbiome structure is resilient to antibiotic perturbation, the functional consequences of which warrant further investigation. IMPORTANCE Antibiotics cause imbalance of gut microbiota, which in turn increase our susceptibility to gastrointestinal infections. However, how antibiotics disrupt gut bacterial communities is not well understood, and exposing healthy volunteers to unnecessary antibiotics for research purposes carries clinical and ethical concerns. In this study, we used genetically identical mice transplanted with the same human gut microbiota to control for both genetic and environmental variables. We found that a short course of oral clindamycin was sufficient to eliminate one third of the gut bacteria by disproportionally eliminating minority members of the transplanted microbiota, but it was inadequate to disrupt the overall microbial community structure and function, which rebounded rapidly to its pre-treatment state. These results suggest that gut microbiome is highly resilient to antibiotic challenge and degradation of the human gut ecosystem may require repeated or prolonged antibiotic exposure.

Automatic Identification System (AIS) was initially developed for tracking ships and avoiding collisions. As numerous small satellites were launched in recent years, millions of AIS messages are captured by these satellite AIS providers every day. The massive amount of data allow shipping firms and port operators to better predict vessels’ movement. In this study, a computational framework is developed to predict future trajectories and destinations of vessels by applying deep learning to the satellite AIS messages containing self-reporting positioning data. We employed deep learning approaches for large-scale maritime prediction and identifies the most suitable deep neural networks for this specific application. Three prediction models, Convolutional Neural Networks (CNN), Dense Neural Networks (DNN), and Long Short-Term Memory (LSTM) have been tested in the framework. A multi-task learning architecture is implemented based on test results. Through sharing parameters while training, this architecture enables long-term destination predictions by balancing short-term trajectory predictions. The framework is validated globally with the experiments covering five large-scale sea areas. The experimental results demonstrate that the LSTM model with an average accuracy percentage of 85.1% outperforms the CNN and DNN with accuracy percentages of 68.3% and 78.2% respectively. The LSTM model with multi-task architecture can achieve an accuracy of 87.0%. With the proposed computational framework, AIS data can be utilized for maritime predictions, supporting more complex marine applications and covering more expansive geographic areas.

BackgroundWhile health systems have implemented multifaceted interventions to improve physician and patient communication in serious illnesses such as cancer, clinicians vary in their response to these initiatives. In this secondary analysis of a randomized trial, we identified phenotypes of oncology clinicians based on practice pattern and demographic data, then evaluated associations between such phenotypes and response to a machine learning (ML)-based intervention to prompt earlier advance care planning (ACP) for patients with cancer.Methods and findingsBetween June and November 2019, we conducted a pragmatic randomized controlled trial testing the impact of text message prompts to 78 oncology clinicians at 9 oncology practices to perform ACP conversations among patients with cancer at high risk of 180-day mortality, identified using a ML prognostic algorithm. All practices began in the pre-intervention group, which received weekly emails about ACP performance only; practices were sequentially randomized to receive the intervention at 4-week intervals in a stepped-wedge design. We used latent profile analysis (LPA) to identify oncologist phenotypes based on 11 baseline demographic and practice pattern variables identified using EHR and internal administrative sources. Difference-in-differences analyses assessed associations between oncologist phenotype and the outcome of change in ACP conversation rate, before and during the intervention period. Primary analyses were adjusted for patients' sex, age, race, insurance status, marital status, and Charlson comorbidity index. The sample consisted of 2695 patients with a mean age of 64.9 years, of whom 72% were White, 20% were Black, and 52% were male. 78 oncology clinicians (42 oncologists, 36 advanced practice providers) were included. Three oncologist phenotypes were identified: Class 1 (n = 9) composed primarily of high-volume generalist oncologists, Class 2 (n = 5) comprised primarily of low-volume specialist oncologists; and 3) Class 3 (n = 28), composed primarily of high-volume specialist oncologists. Compared with class 1 and class 3, class 2 had lower mean clinic days per week (1.6 vs 2.5 [class 3] vs 4.4 [class 1]) a higher percentage of new patients per week (35% vs 21% vs 18%), higher baseline ACP rates (3.9% vs 1.6% vs 0.8%), and lower baseline rates of chemotherapy within 14 days of death (1.4% vs 6.5% vs 7.1%). Overall, ACP rates were 3.6% in the pre-intervention wedges and 15.2% in intervention wedges (11.6 percentage-point difference). Compared to class 3, oncologists in class 1 (adjusted percentage-point difference-in-differences 3.6, 95% CI 1.0 to 6.1, p = 0.006) and class 2 (adjusted percentage-point difference-in-differences 12.3, 95% confidence interval [CI] 4.3 to 20.3, p = 0.003) had greater response to the intervention.ConclusionsPatient volume and time availability may be associated with oncologists' response to interventions to increase ACP. Future interventions to prompt ACP should prioritize making time available for such conversations between oncologists and their patients.

ObjectiveAirways of children with cystic fibrosis (CF) harbor complex polymicrobial communities which correlates with pulmonary disease progression and use of antibiotics. Throat swabs are widely used in young CF children as a surrogate to detect potentially pathogenic microorganisms in lower airways. However, the relationship between upper and lower airway microbial communities remains poorly understood. This study aims to determine (1) to what extent oropharyngeal microbiome resembles the lung microbiome in CF children and (2) if lung microbiome composition correlates with airway inflammation.MethodThroat swabs and bronchoalveolar lavage (BAL) were obtained concurrently from 21 CF children and 26 disease controls. Oropharyngeal and lung microbiota were analyzed using 16S rRNA deep sequencing and correlated with neutrophil counts in BAL and antibiotic exposure.ResultsOropharyngeal microbial communities clustered separately from lung communities and had higher microbial diversity (p < 0.001). CF microbiome differed significantly from non-CF controls, with a higher abundance of Proteobacteria in both upper and lower CF airways. Neutrophil count in the BAL correlated negatively with the diversity but not richness of the lung microbiome. In CF children, microbial genes involved in bacterial motility proteins, two-component system, flagella assembly, and secretion system were enriched in both oropharyngeal and lung microbiome, whereas genes associated with synthesis and metabolism of nucleic acids and protein dominated the non-CF controls.ConclusionsThis study identified a unique microbial profile with altered microbial diversity and metabolic functions in CF airways which is significantly affected by airway inflammation. These results highlight the limitations of using throat swabs as a surrogate to study lower airway microbiome and metagenome in CF children.

The Linc-p21 locus, encoding a long non-coding RNA, plays an important role in p53 signaling, cell-cycle regulation, and tumor suppression. However, despite extensive study, confusion exists regarding its mechanism of action: is activity driven by the transcript acting in trans, in cis, or by an underlying functional enhancer? Here, using a knockout mouse model and a massively parallel enhancer assay, we delineate the functional elements at this locus. We observe that, even in tissues with no detectable Linc-p21 transcript, deletion of the locus significantly affects local gene expression, including of the cell-cycle regulator Cdkn1a. To characterize this RNA-independent regulatory effect, we systematically interrogated the underlying DNA sequence for enhancer activity at nucleotide resolution and confirmed the existence of multiple enhancer elements. Together, these data suggest that, in vivo, the cis-regulatory effects mediated by Linc-p21, in the presence or absence of transcription, are due to DNA enhancer elements.

Many studies are uncovering functional roles for long noncoding RNAs (lncRNAs), yet few have been tested for in vivo relevance through genetic ablation in animal models. To investigate the functional relevance of lncRNAs in various physiological conditions, we have developed a collection of 18 lncRNA knockout strains in which the locus is maintained transcriptionally active. Initial characterization revealed peri- and postnatal lethal phenotypes in three mutant strains (Fendrr, Peril, and Mdgt), the latter two exhibiting incomplete penetrance and growth defects in survivors. We also report growth defects for two additional mutant strains (linc–Brn1b and linc–Pint). Further analysis revealed defects in lung, gastrointestinal tract, and heart in Fendrr−/− neonates, whereas linc–Brn1b−/− mutants displayed distinct abnormalities in the generation of upper layer II–IV neurons in the neocortex. This study demonstrates that lncRNAs play critical roles in vivo and provides a framework and impetus for future larger-scale functional investigation into the roles of lncRNA molecules.

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The standard of care for locally advanced rectal cancer is total neoadjuvant therapy followed by surgical resection. Current evidence suggests that selected patients may be able to delay or avoid surgery without affecting survival rates if they achieve a complete clinical response (CCR). However, for older cancer patients who are too frail for surgery or decline the surgical procedure, local recurrence may lead to a deterioration of patient quality of life. Thus, for clinicians, a treatment algorithm which is well tolerated and may improve CCR in older and frail patients with rectal cancer may improve the potential for prolonged remission and potential cure. Recently, immunotherapy with check point inhibitors (CPI) is a promising treatment in selected patients with high expression of program death ligands receptor 1 (PD- L1). Radiotherapy may enhance PD-L1 expression in rectal cancer and may improve response rate to immunotherapy. We propose an algorithm combining immunotherapy and radiotherapy for older patients with locally advanced rectal cancer who are too frail for surgery or who decline surgery. [ABSTRACT FROM AUTHOR]