BACKGROUND: Abdominal perineal resection (APR) of rectal cancer, also known as Mile\'s procedure, is a classic procedure for the treatment of rectal cancer. Through the improvement of surgical skills and neoadjuvant therapy, the sphincter-preserving rate in rectal cancer patients has improved, even in patients with ultralow rectal cancer who underwent APR in the past. However, APR cannot be completely replaced by low anterior resection (LAR) in reality. APR still has its indications, when the tumor affects the external sphincter, etc. Good perineal exposure in APR is difficult and can seriously affect surgical safety and the long-term prognosis.
METHODS: We reviewed the records of 16 consecutive patients with rectal cancer who underwent APR at Anqing Municipal Hospital from January 2022 to April 2023, including 11 males and 5 females, with an average age of 64.8 ± 10.3 years. The perineal operation was completed with the Lone-Star® retractor-assisted (LSRA) exposure method. After incising the skin and subcutaneous tissue, a Lone-Star® retractor was placed, and the incision was retracted in surrounding directions with 8 small retractors, which facilitated the freeing of deep tissues. We dynamically adjusted the retractor according to the plane to fully expose the surgical field.
RESULTS: All 16 patients underwent laparoscopic-assisted APR successfully. Thirteen procedures were performed independently by a single person, and the others were completed by two persons due to intraoperative arterial hemostasis. All specimens were free of perforation and had a negative circumferential resection margin (CRM). Postoperative complications occurred in 4 patients, including urinary retention in 1 patient, pulmonary infection in 1 patient, intestinal adhesion in 1 patient and peristomal dermatitis in 1 patient, and were graded as ClavienDindo grade 3 or lower and cured. No distant metastasis or local recurrence was found for any of the patients in the postoperative follow-up.
CONCLUSIONS: The application of the LSRA exposure method might be helpful for perineal exposure during APR for rectal cancer, which could improve intraoperative safety and surgical efficiency, achieve one-person operation, and increase the comfort of operators.

The historical stone heritage that we inherit must be passed on to future generations, not only in the same conditions that we found it but, if possible, in better ones. Construction also demands better and more durable materials, often stone. The protection of these materials requires knowledge of the types of rocks and their physical properties. The characterization of these properties is often standardized to ensure the quality and reproducibility of the protocols. These must be approved by entities whose purpose is to improve the quality and competitiveness of companies and to protect the environment. Standardized water absorption tests could be envisaged to test the effectiveness of certain coatings in protecting natural stone against water penetration, but we found that some steps of these protocols neglect any surface modification of the stones, and hence may not be completely effective when a hydrophilic protective coating (i.e., graphene oxide) is present. In this work, we analyze the UNE 13755/2008 standard for water absorption and propose alternative steps to adapt the norm for use with coated stones. The properties of coated stones may invalidate the interpretation of the results if the standard protocol is applied as is, so here we pay special attention to the characteristics of the coating applied, the type of water used for the test, the materials used, and the intrinsic heterogeneity of the specimens.

In the introduction to his Spalt und Fuge, Hans-Jörg Rheinberger points to the possibility that we are currently experiencing a new turning point regarding forms of experimentation, which is characterized by the growing importance of high-throughput methods and big data analytics. This essay will explore the thesis that data-intensive research indeed constitutes a form of post-experimental research by interrogating research practices in precision medicine. Section 1 will introduce this thesis and highlight salient features of precision medicine as an example of post-experimental research. Section 2 suggests approach as a category that is broader than experimental system, as discussed by Rheinberger, and can serve to analyze and compare diverse forms of research, including experimental and post-experimental practices. The essay concludes with a reflection on how categories developed for the historiography of recent science might require an update when the science or its context changes (section 3).

Health professionals initiating mobile health (mHealth) interventions may choose to adapt apps designed for other activities (eg, peer-to-peer communication) or to employ purpose-built apps specialized in the required intervention, or to exploit apps based on methods such as the experience sampling method (ESM). An alternative approach for professionals would be to create their own apps. While ESM-based methods offer important guidance, current systems do not expose their design at a level that promotes replicating, specializing, or extending their contributions. Thus, a twofold solution is required: a method that directs specialists in planning intervention programs themselves, and a model that guides specialists in adopting existing solutions and advises software developers on building new ones.
The main objectives of this study are to design the Experience Sampling and Programmed Intervention Method (ESPIM), formulated toward supporting specialists in deploying mHealth interventions, and the ESPIM model, which guides health specialists in adopting existing solutions and advises software developers on how to build new ones. Another goal is to conceive and implement a software platform allowing specialists to be users who actually plan, create, and deploy interventions (ESPIM system).
We conducted the design and evaluation of the ESPIM method and model alongside a software system comprising integrated web and mobile apps. A participatory design approach with stakeholders included early software prototype, predesign interviews with 12 health specialists, iterative design sustained by the software as an instance of the method\'s conceptual model, support to 8 real case studies, and postdesign interviews.
The ESPIM comprises (1) a list of requirements for mHealth experience sampling and intervention-based methods and systems, (2) a 4-dimension planning framework, (3) a 7-step-based process, and (4) an ontology-based conceptual model. The ESPIM system encompasses web and mobile apps. Eight long-term case studies, involving professionals in psychology, gerontology, computer science, speech therapy, and occupational therapy, show that the method allowed specialists to be actual users who plan, create, and deploy interventions via the associated system. Specialists\' target users were parents of children diagnosed with autism spectrum disorder, older persons, graduate and undergraduate students, children (age 8-12), and caregivers of older persons. The specialists reported being able to create and conduct their own studies without modifying their original design. A qualitative evaluation of the ontology-based conceptual model showed its compliance to the functional requirements elicited.
The ESPIM method succeeds in supporting specialists in planning, authoring, and deploying mobile-based intervention programs when employed via a software system designed and implemented according to its conceptual model. The ESPIM ontology-based conceptual model exposes the design of systems involving active or passive sampling interventions. Such exposure supports the evaluation, implementation, adaptation, or extension of new or existing systems.

Most studies evaluating self-harm repetition risk factors are from Asia and Europe, use cohorts of people who self-injure without differentiating incident and prevalent self-harm episodes, and do not stratify by suicide method. The current study uses an incident user design to (a) examine case fatality at index self-harm events and at each repeat event, by method, (b) describe method-switching, and (c) identify factors associated with repetition of self-harm among those who survive their index hospitalization. Specifically, this study reports psychiatric history and method-specific case fatality for the initial self-harm event among Utah residents with an index event in 2014 or 2015 and who have no history of prior self-harm in hospital records. For survivors of the index self-harm episode, we use Accelerated Failure Time models to identify risk factors for nonfatal repetition and separately for suicide. Key findings: 10,521 Utah residents with no 3-year self-harm hospital history experienced a 2014 or 2015 index event. Of the 9.5% with index deaths, 53.6% used firearms. Of the 90.5% who survived, 63.1% used drugs. Among the index nonfatal cases, over an average 1-year follow-up, 11.7% experienced a nonfatal repetition and 0.8% died by suicide. Most subsequent nonfatal repetitions (59.7%) and suicides (56.8%) had presented with an index drug poisoning; over half (56.8%) of those who died switched methods. For those who subsequently fatally self-harmed, most used poisoning by drugs (33.8%), hanging/strangulation (28.4%), or firearms (24.3%) in the terminal episode. Nonfatal repetition was associated with younger age, index cutting/piercing instruments, and past-year psychiatric and drug abuse diagnoses. Subsequent suicide was associated with male gender, older age, and index gas poisoning and hanging/suffocation. Of the 56 people who survived an index firearm event, none subsequently died by suicide during the study period.

Based on developing, implementing, and evaluating postgraduate interprofessional case-based learning, we have written these twelve tips for health education planners who wish to apply case-based learning in the clinical setting. Interprofessional case-based learning engages participants in a structured manner towards uncovering decisions processes and patterns of action that resemble the clinical reality in which various healthcare professionals handle multifaceted tasks related to the optimal patient treatment. Postgraduate interprofessional case-based learning has the potential to break down traditional hierarchical structures as interactions generate respectful behaviour. We present two models of case-based learning to assist in standardising, structuring, and systematising postgraduate interprofessional case-based learning. We have created 12 practical tips for the design, implementation, and evaluation of successful postgraduate interprofessional case-based learning integrated into the existing clinical setting.

Excessive intake of caffeine, otherwise known to be a safe and mild central nervous system stimulant, causes nausea, vomiting, convulsions, tachycardia, and eventually fatal arrhythmias and death. Caffeine intoxication, a global problem, has been increasing in Japan since 2013. Thus, there is a need for rapid and accurate diagnosis of caffeine poisoning in forensic and clinical toxicology investigations. Herein, we demonstrate rapid and accurate caffeine quantitation by liquid chromatography tandem mass spectrometry using the standard addition method in a fatal case. Biological samples were diluted 500-100,000-fold and subjected to a simple pretreatment (adding caffeine standard and internal standard and passing through a lipid removal cartridge). The multiple reaction monitoring transitions were 195 → 138 for quantitation, 195 → 110 for the qualifier ion, and 204 → 144 for the internal standard (caffeine-d9). The standard plots were linear over 0-900 ng/mL (r2 = 0.9994-0.9999) for biological samples, and the reproducibility (%RSD) of the method was 1.53-6.97% (intraday) and 1.59-10.4% (interday). Fatal levels of caffeine (332 μg/mL) and toxic to fatal levels of olanzapine (625 ng/mL), along with other pharmaceuticals were detected in the external iliac venous blood. The cause of death was determined to be multi-drug poisoning, predominantly caused by caffeine. Our method is useful for not only forensic cases but also the rapid diagnosis of caffeine overdose in emergency clinical settings.

Gene co-expression networks (GCNs) can be prepared using a variety of mathematical approaches based on data sampled across diverse developmental processes, tissue types, pathologies, mutant backgrounds, and stress conditions. These networks are used to identify genes with similar expression dynamics but are prone to introducing false-positive and false-negative relationships, especially in the instance of large and heterogenous datasets. With the aim of optimizing the relevance of edges in GCNs and enhancing global biological insight, we propose a novel approach that involves a data-centering step performed simultaneously per gene and per sub-experiment, called centralization within sub-experiments (CSE). Using a gene set encoding the plant mitochondrial proteome as a case study, our results show that all CSE-based GCNs assessed had significantly more edges within the majority of the considered functional sub-networks, such as the mitochondrial electron transport chain and its complexes, than GCNs not using CSE; thus demonstrating that CSE-based GCNs are efficient at predicting canonical functions and associated pathways, here referred to as the core gene network. Furthermore, we show that correlation analyses using CSE-processed data can be used to fine-tune prediction of the function of uncharacterized genes; while its use in combination with analyses based on non-CSE data can augment conventional stress analyses with the innate connections underpinning the dynamic system being examined. Therefore, CSE is an effective alternative method to conventional batch correction approaches, particularly when dealing with large and heterogenous datasets. The method is easy to implement into a pre-existing GCN analysis pipeline and can provide enhanced biological relevance to conventional GCNs by allowing users to delineate a core gene network.
UNASSIGNED: Gene co-expression networks (GCNs) are the product of a variety of mathematical approaches that identify causal relationships in gene expression dynamics but are prone to the misdiagnoses of false-positives and false-negatives, especially in the instance of large and heterogenous datasets. In light of the burgeoning output of next-generation sequencing projects performed on a variety of species, and developmental or clinical conditions; the statistical power and complexity of these networks will undoubtedly increase, while their biological relevance will be fiercely challenged. Here, we propose a novel approach to generate a \"core\" GCN with enhanced biological relevance. Our method involves a data-centering step that effectively removes all primary treatment/tissue effects, which is simple to employ and can be easily implemented into pre-existing GCN analysis pipelines. The gain in biological relevance resulting from the adoption of this approach was assessed using a plant mitochondrial case study.

Today, armed conflict affects some twenty countries, covering an area making up 11% of the surface area of the Earth. Any degradation of nature in these areas represents a harmful depletion of the world\'s natural heritage. Despite this, environmental issues are neglected during these periods of conflict, considered secondary to the urgency of restoring peace and safeguarding human life. Yet their consequences are potentially severe. In these areas, it is future generations who will suffer the effects of the current devastation for a very long time. In this context, the method developed in this study, named (Geographic Information System) for Environmental Monitoring in Wartime, can be used to calculate a risk indicator for environmental degradation, spatial monitoring and risk management. This will make it possible to identify the main threats to protected areas, catalogue the damage caused to the environment by armed conflicts and create a dynamic risk map. In this paper, GIS-EMW has been applied to calculate a risk indicator for environmental degradation in Syria.

Studies of the association between children\'s depressive symptoms and obesity treatment response show mixed results. Different measurement may contribute to the inconsistent findings, as children\'s depressive symptoms are often based on parent-report about their child rather than child self-report.
We assessed both child- and parent-report of child depressive symptoms as predictors of children\'s obesity treatment response.
Children with overweight/obesity (body mass index [BMI] ≥ 85th percentile; N = 181) and their parents reported on children\'s depressive symptoms prior to family-based behavioral weight loss treatment.
Child percent overweight reduction from baseline to post-treatment was not predicted by child self-reported depressive symptoms or parent-report of child symptoms (P > 0.80), but was significantly predicted by the interaction between child self-report and parent-report on child (β = 0.14, P = 0.05). In analyses using clinical cutoffs, amongst children with high self-reported symptoms, those whose parents reported low child depressive symptoms had greater reduction in percent overweight (t = 2.67, P = 0.008), whereas amongst children with low self-reported symptoms, parent ratings were not associated with treatment outcome.
Including both child self-report and parent-report of child depressive symptoms may inform obesity care. Research is needed to examine differences amongst child and parent depressive symptom reports and strategies to address symptoms and optimize pediatric obesity treatment.