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Refractory inguinal lymphatic leakage following groin surgery remains a challenging complication, often resulting in prolonged wound healing, infection, or femoral artery rupture. We established a reliable and minimally invasive strategy combining indocyanine green (ICG) fluorescence imaging with negative pressure wound therapy (NPWT) to identify and manage persistent lymphatic leakage. Four patients with refractory inguinal lymphatic leakage unresponsive to prior ligation received treatment between 2021 and 2024. ICG was administered subcutaneously at 4 sites on the foot to visualize lymphatic pathways using near-infrared imaging. Intraoperative ICG fluorescence enabled precise identification, ligation, and cauterization of leaking lymphatic vessels. NPWT (-75 to -125 mm Hg) was applied immediately postoperatively until wound contraction was observed. All patients (mean age = 69.5 ± 14.7 y, all male) achieved complete healing. The mean duration of NPWT and epithelialization was 18 ± 4.5 and 48 ± 14.0 days, respectively. No recurrence or complications occurred. This approach allowed closure of lymphatic leaks that had persisted despite conventional surgical management. In conclusion, combining ICG-guided lymphatic mapping and NPWT provides a practical, minimally invasive, and reproducible strategy for treating refractory inguinal lymphatic leakage. This technique enables reliable identification of responsible lymphatic vessels and promotes wound healing through continuous drainage and compression, representing an innovative option for complex postoperative lymphatic complications.

Elevated levels of ammonia and nitrate in water bodies contribute to environmental issues such as eutrophication and pose serious risks to human health and aquatic life. Traditional monitoring methods rely on grab sampling, and existing in situ sensor technologies are often prohibitively expensive, which limits their widespread deployment. This study presents a low-cost, in situ, near-real-time sensor and a hand-held device for the detection and monitoring of ammonia and nitrate in water. The hand-held device demonstrated excellent performance during laboratory testing, achieving an R 2 of 0.96 when estimating both ammonia and nitrate concentrations in real environmental samples. It reliably quantified both nutrients across a broad range, with accurate measurements observed up to 10 mg/L. The in situ system showed reliable performance for ammonia in environmental samples (R 2 = 0.76) and detected ammonia down to 0.1 mg/L. However, below this threshold, signal variability increased, and measurements became less consistent. During four field sampling periods, it demonstrated reliable performance in measuring ammonia concentrations, achieving an R 2 of 0.86 and a Nash-Sutcliffe efficiency (NSE) of 0.83. The results showed that the low-cost sensor can operate for 2 weeks by sampling every 40 min using just one kit of low-cost reagents (16 USD per kit, and 0.09 USD per sample).

Pediatric short bowel syndrome (SBS) is often secondary to congenital conditions such as malrotation with midgut volvulus, intestinal atresia, gastroschisis, or necrotizing enterocolitis. Traumatic injury secondary to firearms is a less common cause of SBS encountered in the United States. We aim to describe the morbidity affecting four children (ages 9-16 years) with SBS secondary to firearm injury. All patients had extensive injury directly to the bowel and/or the intestinal blood supply, requiring parenteral and/or enteral nutrition at discharge. All patients had significant extra-intestinal manifestations, including peripheral neuropathy and biliary strictures, but did not exhibit changes seen with intestinal failure-associated liver disease. Two patients identified issues with food insecurity, reliable transportation, and difficulty adhering to the treatment plan due to low health literacy. All four had ongoing post-traumatic psychological needs. Two patients had encounters with law enforcement after discharge, with one patient requiring physicians advocating for continued treatment with parenteral nutrition while incarcerated. Firearm violence is the leading cause of pediatric death in the United States, but the morbidity endured by survivors, particularly those with SBS, is often not described. In addition to intestinal failure, we highlight this vulnerable population's medical, social, and psychological needs.

Breast implant exposure is an uncommon but significant complication in aesthetic and reconstructive breast surgery. Salvage procedures aim to restore soft-tissue coverage while minimizing morbidity. The myocapsular flap offers vascularized tissue already present in the operative field, providing a potential alternative to more complex reconstructive options. A 37-year-old woman with a prior augmentation mastopexy underwent secondary mastopexy with implant exchange. Six weeks later, she developed wound dehiscence, localized infection, and partial left implant exposure. Intravenous antibiotics were initiated. Under general anesthesia, the implant was removed, the pocket irrigated and debrided, and an inferomedial rectangular myocapsular flap elevated and transposed to cover the defect. The sterilized implant was reinserted into the reconstructed pocket. The flap provided reliable vascularized coverage, allowing successful implant salvage. Healing was uneventful, with no recurrent infection or reexposure. The aesthetic result was satisfactory, with adequate contour and no donor-site morbidity. The myocapsular flap is a practical, low-morbidity option for implant salvage in cases of limited exposure, offering effective coverage within the same surgical field.

Cardiovascular diseases remain as a leading cause of mortality and morbidity worldwide, with coronary artery disease (CAD) and its complications, collectively referred to as major adverse cardiovascular events (MACEs), necessitating accurate risk stratification. Coronary computed tomography angiography (CCTA) has emerged as a valuable non-invasive imaging modality, and adipose tissue characteristics derived from CCTA have shown promise as imaging biomarkers for MACE prediction. This systematic review and meta-analysis aimed to evaluate the predictive performance of artificial intelligence (AI)-driven models incorporating CCTA-derived adipose tissue radiomic features for forecasting MACEs. A systematic review and random-effects meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies evaluating predictive models developed using different AI algorithms that utilized adipose tissue radiomics as the primary predictor of MACEs in patients undergoing CCTA were included. Model performance was assessed using pooled area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Eleven studies comprising 47 244 participants were included in the analysis. AI-based models integrating adipose tissue radiomic features with clinical data consistently outperformed conventional risk assessment tools, with pooled AUCs ranging from 82.2% to 87.9%. Among the evaluated approaches, deep learning models demonstrated superior predictive performance compared with traditional machine learning and logistic regression-based models. However, considerable heterogeneity (I² > 96%) was observed across studies, reflecting variations in study design, imaging protocols, and AI methodologies. While AI-enhanced CCTA-based adipose tissue characterization demonstrates considerable potential for improving MACE risk prediction, methodological heterogeneity and limited external validation currently restrict its clinical applicability. Future research should prioritize standardized imaging and analytical methodologies, rigorous clinical and external validation, and transparent reporting to facilitate reliable integration of these AI models into routine cardiovascular risk assessment.

Patients with tuberculosis in the intensive care unit (ICU) face an elevated risk of thrombosis; however, the contributing factors remain incompletely understood. This study aimed to identify independent risk factors for thrombus formation, evaluate the incremental predictive value of inflammatory biomarkers [C-reactive protein (CRP), D-dimer (DDR), and interleukin-6 (IL-6)], and explore the determinants of IL-6 levels in critically ill tuberculosis patients. This retrospective cohort study consecutively enrolled 168 tuberculosis patients admitted to the ICU, including 101 with thrombosis and 67 without. Demographic, clinical, and laboratory data were collected. Univariate and multivariable binary logistic regression analyses were performed to identify independent risk factors. The area under the receiver operating characteristic curve (AUC) and DeLong test were used to compare five logistic models: a base model [age, activated partial thromboplastin time(APTT), and non-TB bacterial/fungal infection status] and four extended models incorporating ln-transformed CRP, DDR, or IL-6, individually or in combination. Multivariable linear regression analysis was employed to identify factors independently associated with IL-6 levels. Advanced age (OR&#x202f;=&#x202f;1.057, p&#x202f;=&#x202f;0.001) and prolonged APTT (OR&#x202f;=&#x202f;1.053, p&#x202f;=&#x202f;0.041) were independent predictors of thrombus formation. In the multivariable model, fungal co-infection (OR&#x202f;=&#x202f;3.185, p&#x202f;=&#x202f;0.006) and non-TB bacterial co-infection (OR&#x202f;=&#x202f;0.336, p&#x202f;=&#x202f;0.038) also reached statistical significance. Age-stratified analysis revealed that among patients aged <70&#x202f;years, only age was independently associated with thrombosis (OR&#x202f;=&#x202f;1.050, p&#x202f;<&#x202f;0.05), whereas no other parameter demonstrated independent predictive value. The base model yielded an AUC of 0.753; the addition of CRP, DDR, or IL-6 did not produce a statistically significant improvement in discriminatory performance (all p&#x202f;>&#x202f;0.05). In multivariable linear regression, only CRP was independently associated with IL-6 levels (&#x3b2;&#x202f;=&#x202f;0.423, p&#x202f;<&#x202f;0.001). Age and APTT are independent risk factors for thrombus formation in patients with tuberculosis. Fungal co-infection confers additional thrombotic risk, whereas non-TB bacterial co-infection exhibits a paradoxical protective effect, the underlying mechanisms of which warrant further investigation. A parsimonious model based on age, APTT, and co-infection status demonstrated moderate predictive accuracy (AUC&#x202f;=&#x202f;0.753), and the incorporation of CRP, DDR, or IL-6 failed to enhance its discriminatory ability. CRP serves as a reliable surrogate marker for IL-6-driven inflammation in this population. Large-scale prospective studies are warranted to validate and extend these findings.

Ensuring the authenticity of edible oils remains a critical challenge in food supply chains, particularly for high-value products susceptible to adulteration. This study investigated the potential of portable near-infrared (NIR) microspectroscopy (750-1050 nm) combined with chemometric and machine learning approaches for the authentication and fraud detection of virgin coconut oil (VCO), coconut oil (CO), palm kernel oil (PKO), and groundnut oil (GNO). NIR spectral fingerprints were acquired using an SCiO portable spectrometer and analysed using both classification and quantification models. For qualitative discrimination, several pattern recognition algorithms, including k-nearest neighbour (KNN), linear discriminant analysis (LDA), support vector machine (SVM), and artificial neural network (NN), were evaluated. The results demonstrated a clear spectral differentiation among the oil types. The NN model achieved the best classification performance, yielding 100% accuracy for the calibration set and 97.19% accuracy for the independent prediction set, outperforming KNN, LDA, and SVM models. For quantitative analysis, partial least squares regression (PLSR) models were developed to predict the level of adulteration of virgin coconut oil with coconut oil. Different variable selection and preprocessing strategies, including backward interval partial least squares (BiPLS), successive projections algorithm (SPA-PLS), and standard normal variate (SNV-PLS), were compared in this study. Among the evaluated models, the SNV-PLS approach provided the best predictive performance, achieving a coefficient of determination (R2) of 0.97, indicating an excellent agreement between the reference and predicted values. The findings demonstrate that portable NIR microspectroscopy combined with advanced chemometric and machine learning models offers a rapid, non-destructive, and reliable approach for both the classification and quantification of vegetable oil fraud. This approach shows strong potential for routine screening and on-site authenticity assessment of edible oils, particularly in resource-limited and decentralised food control environments.

Postoperative cognitive dysfunction (POCD) is a common neurological complication after surgery, associated with increased adverse events and mortality. While studies suggest that Shenmai injection (SMI) or Shenfu injection (SFI) may be associated with reduce POCD, rigorous systematic reviews specifically on these two botanical drug injections are lacking. We comprehensively searched eight databases (PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, CBM) from inception to May 2025 for RCTs on SMI and SFI for POCD. Data were analyzed using RevMan 5.4. Primary outcomes were Mini-Mental State Examination (MMSE) score and POCD incidence. Secondary outcomes included serum S100&#x3b2; protein concentration and postoperative consciousness recovery time. Continuous outcomes used mean difference (MD) or standardized mean difference (SMD) with 95% CI; dichotomous outcomes used relative risk (RR) with 95% CI. This study was registered in INPLASY (registration number: 202470131). A total of 552 records were identified, and after deduplication and screening, sixteen RCTs (N = 1,199 patients) were finally included. Both SMI and SFI were associated with statistically significant higher postoperative MMSE scores at multiple time points (all P < 0.01) and were associated with lower POCD incidence at 3 days (SMI RR 0.38; SFI RR 0.52) and 7 days (SMI RR 0.26; SFI RR 0.47). However, all included trials were at high risk of bias (lack of allocation concealment and blinding). SFI was associated with lower serum S100&#x3b2; at 24&#xa0;h (SMD = -0.40); the effect of SMI could not be evaluated due to missing data. Both injections were associated with shorter consciousness recovery time (MD = -5.67 min, 95% CI: -6.46 to -4.87, P < 0.001). Subgroup analyses showed a trend toward reduced POCD incidence across doses. Most studies did not report detailed preparation composition or chemical characterization. Only three of the 16 included RCTs reported adverse events, and therefore no reliable safety conclusions can be drawn from the current RCT evidence. Sensitivity analysis confirmed robustness. GRADE evidence quality was low for all outcomes. Low-certainty evidence suggests a possible association of SMI or SFI with improved cognitive outcomes, but causality is unproven. These preliminary findings require confirmation in rigorous RCTs with proper blinding and standardized measures. https://inplasy.com/inplasy-2024-7-0131, identifier 202470131.

State-space models (SSMs) provide a flexible framework for modelling time series data, but their reliance on Gaussian error assumptions makes them highly sensitive to outliers. We propose a robust estimation method, ROAMS, that mitigates the influence of additive outliers by introducing shift parameters at each timepoint in the observation equation of the SSM. These parameters allow the model to attribute non-zero shifts to outliers while leaving clean observations unaffected. ROAMS then enables automatic outlier detection, through the addition of a penalty term on the number of flagged outlying timepoints in the loss function, and simultaneous estimation of model parameters. We apply the method to robustly estimate SSMs on both simulated data and real-world animal location-tracking data, demonstrating its ability to produce more reliable parameter estimates than classical methods and other benchmark methods. In addition to improved robustness, ROAMS offers practical diagnostic tools, including BIC curves for selecting tuning parameters and visualising outlier structure. These features make our approach broadly useful for researchers and practitioners working with contaminated time series data. The online version contains supplementary material available at 10.1007/s11222-026-10935-4.

Seroma formation after common femoral artery (CFA) exposure is a recognized complication in vascular surgery, associated with delayed wound healing and graft-related morbidity. Reported seroma rates following CFA exposure using standard electrocautery range from 5% to 15% for cases requiring operative reintervention. The LigaSure bipolar vessel sealing system has demonstrated efficacy in sealing lymphatic channels in other surgical specialties, but its safety and impact in vascular groin surgery have not been well-characterized. We evaluated the safety, feasibility, and postoperative outcomes associated with LigaSure use during CFA exposure. We conducted a retrospective cohort study of consecutive patients undergoing open CFA exposure using LigaSure at a tertiary vascular referral center between June 2023 and November 2025, excluding any trauma cases. Demographic, clinical, operative, and postoperative outcome data were abstracted from the electronic medical record. The primary outcome was postoperative seroma formation, with clinical significance defined as the need for procedural or operative reintervention. Secondary outcomes included hematoma, surgical site infection, and fat necrosis. Observed outcome rates were descriptively compared with historically reported seroma rates after femoral artery exposure. Postoperative follow-up occurred during the index hospitalization and at scheduled outpatient visits. Twenty-eight patients were included. Cardiovascular comorbidities were prevalent: hypertension (86%), hyperlipidemia (75%), and diabetes (50%). Four patients (14.3%; 95% confidence interval [CI], 4.03%-32.67%) developed postoperative fluid collections: two seromas (7.1%; 95% CI, 0.88%-23.50%) and two hematomas (7.1%; 95% CI, 0.88%-23.50%), comparable with historically reported seroma rates of 5% to 15% after standard electrocautery. Critically, no patients required procedural drainage, operative reintervention, or graft excision, and no graft infections or fat necrosis were observed. Only one case of skin infection and one case of skin necrosis were noted. All fluid collections resolved with conservative management, yielding a final rate of 0% for seroma requiring operative reintervention. LigaSure use during CFA exposure was safe and feasible, with postoperative seroma rates comparable with those historically reported for standard electrocautery. Notably, 0% of seromas required procedural or operative reintervention, an important clinical consideration given the morbidity often associated with groin seromas in vascular surgery. Although a decrease in seroma incidence was not observed relative to historical benchmarks, the favorable safety profile and absence of clinically significant lymphatic complications requiring operative reintervention support LigaSure as a reliable adjunct for groin dissection. Larger prospective comparative studies are needed to further define its impact on clinically meaningful groin wound outcomes.

This study provides a detailed description of the technique using a tibial-to-peroneal nerve transfer for the treatment of foot drop patients, along with a retrospective outcome analysis. All consecutive patients undergoing selective motor nerve transfer surgery for severe axonal injury of the common peroneal nerve (CPN) between January 1, 2011, and March 31, 2024, were evaluated. Exclusion criteria included age younger than 16 years, follow-up less than 12 months, unwillingness to participate, or concomitant peripheral nerve conditions (eg, polyneuropathy). Twenty-one patients met the inclusion criteria. The mean patient age was 40&#x2005;&#xb1;&#x2005;18 years, with an average trauma-to-surgery interval of 7.6&#x2005;&#xb1;&#x2005;4.0 months. The mean follow-up was 26.3&#x2005;&#xb1;&#x2005;12.5 months. Median postoperative tibialis anterior muscle strength was 4.1 (interquartile range 3-4.5) on the Medical Research Council scale, with 17 (77%) patients reaching Medical Research Council scores of 3 or higher and being able to walk without an ankle-foot orthosis. There was a significant benefit in terms of final tibialis anterior muscle strength in patients who received 2 or more fascicles transferred compared with a single fascicle and in those who underwent additional CPN neurolysis. The selective motor nerve transfer technique described is a reliable reconstructive option for restoring active dorsiflexion in patients with foot drop. Both the number of transferred fascicles and the addition of CPN neurolysis are important factors associated with improved outcomes.

We present a machine-learning-based workflow to model an unbinned likelihood from its samples. A key advancement over existing approaches is the validation of the learned likelihood using rigorous statistical tests, such as the Kolmogorov-Smirnov test of the joint distribution. Our method enables the reliable communication of experimental and phenomenological likelihoods for subsequent analyses. We demonstrate its effectiveness through three case studies in high-energy physics. To support broader adoption, we provide an open-source reference implementation, nabu.

Mental illness stigma undermines help-seeking, treatment engagement, and social inclusion globally. Although the Gulf Cooperation Council (GCC) region has undergone rapid social and health-system modernization, few studies have simultaneously assessed public knowledge, attitudes, and intended behaviour toward people with mental illness using validated instruments. To examine mental-health knowledge, public stigma, and social acceptance among adults in GCC countries using the Mental Health Knowledge Schedule (MAKS), the Reported and Intended Behaviour Scale (RIBS), and the 40-item Community Attitudes toward the Mentally Ill (CAMI) scale. An Arabic-language online survey was completed by 1, 557 adults (84.1% female; mean age = 26.2 years, SD&#xa0;=&#xa0;10.6; 80.5% from Kuwait). Descriptive statistics, bivariate analyses, and simultaneous-entry multiple linear regression were conducted. Internal consistency was evaluated using Cronbach's &#x3b1; and McDonald's &#x3c9;, supplemented by item-total correlations and confirmatory factor analysis (CFA) of the CAMI. Participants reported moderate mental-health knowledge (MAKS M&#xa0;=&#xa0;41.6, SD&#xa0;=&#xa0;5.9), moderately positive attitudes (CAMI M&#xa0;=&#xa0;135.2, SD&#xa0;=&#xa0;16.2), and moderate behavioural willingness (RIBS M&#xa0;=&#xa0;13.1, SD&#xa0;=&#xa0;3.2). Knowledge and attitudes were moderately correlated (r&#xa0;= .341, p&#xa0;<.001), but the association between attitudes and intended behaviour was weaker (r&#xa0;= .209, p&#xa0;<.001). In regression, social restrictiveness was the strongest predictor of behavioural engagement (&#x3b2; = .374, p&#xa0;<.001), followed by male sex (&#x3b2; = .098) and MAKS total (&#x3b2; = -.103). A confirmatory factor analysis indicated poor fit of the original four-factor CAMI structure (CFI&#xa0;= .673, RMSEA&#xa0;= .141), supporting cautious subscale-level interpretation. A supplementary regression using the more reliable CAMI total score confirmed the primary pattern. Sensitivity analyses following removal of implausible age entries and restricting to Kuwait-only participants produced substantively identical findings. These findings, drawn from a predominantly Kuwaiti, female, and university-educated convenience sample, indicate that respondents endorsed sympathetic and recovery-oriented principles yet showed substantial hesitation regarding close social contact. The disconnect between attitudes and behavioural willingness highlights the need for culturally grounded, contact-based anti-stigma interventions that target social distance specifically, while requiring replication in more representative GCC populations.

Pain assessment is fundamental in pain medicine, anesthesiology, perioperative care, and clinical trials, yet it remains difficult to standardize across diseases, populations, and care settings. This review organizes pain assessment into four interrelated layers: subjective experience, behavioral and functional proxies, mechanistic biosignals, and multimodal integration. Pain characteristics guide many clinical decisions, but they must be interpreted alongside diagnosis, imaging, laboratory findings, treatment context, and regulatory expectations for reliable and interpretable trial endpoints. Patient-reported scales remain central when feasible because they directly capture the experienced dimension of pain; however, in neonates, critically ill patients, and individuals with severe cognitive or communication impairment, behavioral and functional proxies may become the practical baseline rather than merely supplementary measures. Recent advances in observational scales, facial-expression analysis, sleep and activity monitoring, wearable sensing, electroencephalography, neuroimaging, biofluids, autonomic physiology, and artificial intelligence provide complementary information for phenotyping, monitoring, prediction, and treatment evaluation. These tools should not be treated as interchangeable measures of the same construct or as simple replacements for self-report. A task-oriented layered framework may help clarify what each indicator can and cannot answer, while emphasizing feasibility, reproducibility, effect size, external validation, interpretability, and clinical context.

Clomiphene citrate (CC) is the first-line medication for inducing ovulation in women with polycystic ovary syndrome (PCOS). However, approximately 20% of patients with PCOS are resistant to CC. This study aims to identify reliable baseline predictors of CC resistance in infertile women with PCOS. A post-hoc analysis of a large, multicenter randomized controlled trial (PCOSAct trial) conducted in China. The current analysis comprised the 471 participants who were randomized to the active CC arm and completed the requisite follow-up. To identify potential candidate variables, we employed multivariable logistic and LASSO regression analyses. Within the framework of a multivariable logistic regression model, we also estimated the independent associations between the identified candidate variables and resistance to CC. Additionally, we plotted the Receiver Operating Characteristic (ROC) curve and utilized the DeLong method to compare the statistical differences in the area under the curve (AUC). Finally, we constructed a restricted cubic spline (RCS) logistic regression model to illustrate the dose-response relationship between continuous predictor variables and CC resistance. CC resistance was identified in 32 (6.8%) participants. Body Mass Index (BMI), Total Testosterone (TT), and Anti-M&#xfc;llerian Hormone (AMH) were useful predictors of ovarian response to CC. The "T+BMI" dual-factor model demonstrated high discriminative power (AUC&#xa0;=&#xa0;0.801) and was statistically comparable to the three-factor model including AMH (AUC&#xa0;=&#xa0;0.818; P&#xa0;=&#xa0;0.347). TT was the strongest individual predictor (OR&#xa0;=&#xa0;2.73 per 1-unit), while BMI was the most significant modifiable risk factor (OR&#xa0;=&#xa0;2.49 per 1-SD). A simplified "T + BMI" assessment provides comparable prognostic utility without the need for AMH testing. For patients at high risk of CC resistance, we recommend upfront use of aromatase inhibitors or low-dose gonadotropins. This strategy avoids ineffective treatment cycles and enables personalized ovulation induction. The study was registered on ClinicalTrials.gov under the identification number NCT01573858 on July 6, 2012.

Visually Rich Document Understanding (VRDU) has become a pivotal area of research, driven by the need to automatically interpret documents that contain intricate visual, textual, and structural elements. Recently, Multimodal Large Language Models (MLLMs) have demonstrated significant promise in this domain, including both OCR-based and OCR-free approaches for information extraction from document images. This survey reviews recent advances in MLLM-based VRDU, highlighting emerging trends and promising research directions with a focus on two key aspects: (1) techniques for representing and integrating textual, visual, and layout features; (2) training paradigms, including pretraining, instruction tuning, and training strategies. Moreover, we address challenges such as data scarcity, handling multi-page and multilingual documents, and integrating emerging trends such as Retrieval-Augmented Generation and agentic frameworks. Our analysis offers a roadmap for advancing MLLM-based VRDU toward more scalable, reliable, and adaptable systems.

Water scarcity is an escalating global challenge with growing relevance for healthcare systems. Nephrology is particularly affected, as dialysis is a life-sustaining yet highly water-intensive therapy. Climate change, droughts, and infrastructure vulnerabilities increasingly threaten reliable water access, exposing the fragility of water-dependent kidney replacement therapies. We reviewed the available evidence and practical experience on water use in nephrology and dialysis care, with a focus on feasible strategies to reduce water consumption without compromising patient safety or quality of care. We identify key domains of water use in dialysis and nephrology practice and present 10 practical, evidence-informed tips to reduce water consumption. These measures span system-level approaches, technological considerations, staff and patient engagement, behavioral change and are applicable across diverse resource settings. Integrating water stewardship into routine nephrology practice is essential to enhance the long-term resilience of dialysis services. Proactive water conservation represents a clinically relevant, ethical, and achievable component of sustainable kidney care.

In Mecklenburg-Western Pomerania, multidisciplinary round tables bring together stakeholders from the healthcare sector to jointly develop and advance solutions for regional care challenges on a semi-annual basis. In a sparsely populated state with distinct structural and service-related difficulties, these collaborative formats play a key role in improving discharge management. Against this backdrop, the present study explores the main fields of action required to enhance discharge processes in rural areas of Mecklenburg-Western Pomerania. It aims to prioritise the key challenges, objectives, and measures that can contribute to a more efficient and patient-centred continuum of care following hospital discharge. Guideline-based group discussions were conducted at the round tables in Demmin, Pasewalk, Parchim and Ueckerm&#xfc;nde and analysed using qualitative content analysis. To prioritise key topics and measures, a dialogue-based structural mapping method (Strukturlegetechnik) was applied. This approach enables the reconstruction of participants' subjective theories through consensus-oriented discussions and visual mapping of conceptual relationships. In four focus group discussions involving a total of 30 participants, three main areas for action were emphasised: the expansion of networks and binding coordination structures, the use of digital tools such as online platforms and telemedicine, and the development of tailored support services for vulnerable groups. In addition, prevention, health education, citizen participation and public relations were highlighted as essential cross-cutting tasks. To ensure sustainable healthcare provision in rural areas, it is essential to establish stable networks that meet on a regular basis and have reliable funding. The targeted expansion of telemedicine, digital communication platforms and capacity monitoring systems should be pursued to strengthen cross-sector collaboration and reduce gaps in service delivery. In Mecklenburg-Vorpommern bestehen Runde Tische, an denen Akteur*innen des Gesundheitswesens multidisziplin&#xe4;r zusammenkommen, um halbj&#xe4;hrlich gemeinsame L&#xf6;sungsans&#xe4;tze f&#xfc;r regionale Versorgungsprobleme zu entwickeln und deren Umsetzung zu begleiten. Gerade in einem Fl&#xe4;chenland mit geringer Bev&#xf6;lkerungsdichte und spezifischen Versorgungsherausforderungen kommt diesen Strukturen eine zentrale Rolle f&#xfc;r die Weiterentwicklung des Entlassmanagements zu. Vor diesem Hintergrund untersucht der Beitrag, welche Handlungsfelder f&#xfc;r eine Verbesserung des Entlassmanagements in l&#xe4;ndlichen Regionen Mecklenburg-Vorpommerns relevant sind, und zielt darauf ab, zentrale Herausforderungen, Zielsetzungen und Ma&#xdf;nahmen zu priorisieren, um eine effizientere und st&#xe4;rker patient*innenzentrierte Versorgung nach dem Krankenhausaufenthalt zu f&#xf6;rdern. Es wurden leitfadenbasierte Gruppendiskussionen an den Runden Tischen in Demmin, Pasewalk, Parchim und Ueckerm&#xfc;nde durchgef&#xfc;hrt, welche inhaltsanalytisch ausgewertet wurden. Zur Priorisierung zentraler Themen und Ma&#xdf;nahmen wurde die Strukturlegetechnik eingesetzt, ein dialogkonsensbasiertes Verfahren zur Rekonstruktion subjektiver Theorien. In vier Fokusgruppendiskussionen mit insgesamt 30 Teilnehmenden wurden vor allem drei Handlungsfelder betont: der Ausbau von Netzwerken und verbindlichen Koordinationsstrukturen, der Einsatz digitaler Instrumente (z.B. Portale, Telemedizin) sowie passgenaue Unterst&#xfc;tzungsangebote f&#xfc;r vulnerable Gruppen. Erg&#xe4;nzend wurden Pr&#xe4;vention, Aufkl&#xe4;rung, B&#xfc;rgerbeteiligung und &#xd6;ffentlichkeitsarbeit als zentrale Querschnittsaufgaben hervorgehoben. F&#xfc;r eine nachhaltige Gesundheitsversorgung in l&#xe4;ndlichen Regionen sind stabile, regelm&#xe4;&#xdf;ig tagende Netzwerke und eine gesicherte Finanzierung essenziell. Die Integration von Telemedizin, digitalen Kommunikationsplattformen und Kapazit&#xe4;tsmeldesystemen sollte gezielt vorangetrieben werden, um die sektor&#xfc;bergreifende Zusammenarbeit zu st&#xe4;rken und Versorgungsl&#xfc;cken zu schlie&#xdf;en.

Accurate prediction of protein-ligand complexes and binding affinity is critical for hit identification and optimization for structure-based drug design. Traditional docking simulates binding processes with searching algorithms guided by energy-scoring functions, which are quite computationally expensive and time-intensive. In contrast, deep learning approaches offer a cost-effective alternative, yet often generate conformations with limited physicochemical validity and fail to account for protein flexibility. To address these pitfalls, we propose FlowDock, a multitask framework enhanced by Bayesian Flow Networks. FlowDock simultaneously generates accurate protein-ligand complex structures and predicts binding affinity while incorporating protein conformational flexibility. By leveraging multimodal intramolecular representations with a deep equivariant generative model, our method iteratively refines complex in latent space, ensuring rapid and stable generation. Benchmark evaluations demonstrate that FlowDock achieves state-of-the-art performance in binding pose prediction, especially physical plausibility, and virtual screening capability, alongside reliable binding affinity predictions. By providing deeper molecular insights into dynamic protein-ligand interactions, FlowDock represents a robust tool for accelerating the rational development of therapeutics.