Abstract Background and Purpose Statins are essential for managing cardiovascular disease (CVD), yet adverse effects can lead to discontinuation and non-adherence. The UAE’s multiethnic population presents unique challenges for personalized medicine. Pharmacogenomic (PGx) testing could enhance statin efficacy and safety but is not commonly used in clinical practice. This EmHeart Study sub-analysis aimed to assess genetic and demographic factors associated with side effects in rosuvastatin and atorvastatin users among 675 patients, highlighting the need for PGx-guided therapy. Experimental Approach Patients were genotyped for SLCO1B1 and ABCG2 variants using real-time PCR. Data on demographics, comorbidities, and statin use were gathered from electronic records, with side effects tracked over 12 months. Chi-square tests and logistic regression analyzed associations between patient characteristics, genetic variants, and adverse effects. Key Results East Asians with the ABCG2 rs2231142 variant had a threefold increased risk of liver enzyme elevation with rosuvastatin. Atorvastatin users carrying SLCO1B1 rs4149056 had twice the risk of statin-associated muscle symptoms (SAMS), with higher rates in females and Arabs. Additionally, combining rosuvastatin with ezetimibe further increased risks of both SAMS and liver enzyme elevation. Conclusion and Implications Although PGx in statin prescribing is well-studied, it is underutilized in clinical practice. Importantly, genetic factors are not the sole determinants in physician decision-making. This study demonstrates that gender, ethnicity, and genetic testing significantly impact statin choice. Avoiding rosuvastatin in patients with liver-related risks and increasing physician awareness of these risks can optimize efficacy, safety, and adherence across diverse populations

Current therapeutic approaches often focus on targeting clinical symptoms or peripheral phenotypes rather than the underlying molecular mechanisms, or endophenotypes, that drive diseases. While symptom-based drugs can alleviate discomfort, they do not necessarily alter disease progression and may overlook opportunities for prevention or early intervention in asymptomatic patients. This approach can lead to overtreatment of certain disease traits while neglecting others that are critical for long-term outcomes. In contrast, mechanism-based therapies offer advantages such as specificity and reduced side effects, allowing for the management of previously untreatable conditions or complementing established treatments. These therapies enable monitoring of drugs' effects on the endophenotype driving the disease, facilitating personalized treatment regimens and improving patient compliance. Mechanism-based drugs are essential for precision prevention and therapy. Network Medicine plays a vital role in understanding diseases by identifying key endophenotypes and determinants influencing disease expression. Unlike reductionist methods, it provides insights into disease mechanisms and potential therapeutic targets by examining interactions among genetic, molecular, and environmental factors. As part of Network Medicine, Network Pharmacology bridges the gap between symptom-based and mechanism-based strategies, guiding drug development while considering symptomatic relief. This short review focus on creating heterogeneous networks to integrate various drug, target, and disease-related information. These approaches can create comprehensive representations of drugs and targets by incorporating diverse profiles, enhancing the prediction performance of drug-target interactions.

“‘latex An appropriate soil configuration is essential in hydrological models given the role of subsurface processes in the hydrological functioning of a catchment. Hydrological models are typically set up with shallow soil depths as restricted by measurements and soil datasets that are often unavailable in greater depths. While this may be sufficient for some catchments, in some areas the water table is located deeper and thus the shallow groundwater and its link with the rest of the hydrological processes may not be captured well by the model. An important soil parameter, that is known to vary with soil depth, is the saturated hydraulic conductivity (K sat). In this study, we assessed different vertical profiles of K sat which exceed the typical soil measurement depths. The K sat profiles were implemented in wflow.jl for the distributed hydrological model wflow_sbm and tested for the Vecht catchment. Results demonstrated that increasing the soil thickness and implementing any of the K sat profiles assessed improved the discharge and mean groundwater depth predictive capabilities, albeit altering the groundwater dynamics. A sensitivity analysis revealed the respective influence of four model parameters on the groundwater dynamics which can be used as basis to optimize the model performance further.

“‘latex Deterioration and manifestation of cerebral fat embolism triggered by bone reaming during femur fracture surgery: a case reportShort title: Cerebral Fat Embolism Triggered by Bone ReamingDaisuke Nakada MD, Hideki Hino MD, Naomi Okuma MD, Yohei Fujimoto MD, Tadashi Matsuura MD, Takashi Mori MDDepartment of Anesthesiology Anesthesia, Osaka Metropolitan University Graduate School of Medicine, Osaka, JapanCorresponding Author: Hideki HinoDepartment of Anesthesiology, Osaka Metropolitan University Graduate School of Medicine, 1-5-7 Asahimachi, Abeno-ku, Osaka 545-8586, JapanTel.: +81-6-6645-2186; Fax: +81-6-6645-2489mail: m1165192@yahoo.co.jp ORCID ID: m1165192@yahoo.co.jp

Fusarium wilt in Chrysanthemums, a long-standing issue, is primarily caused by Fusarium equiseti, though confusion persists about its specific forma specialis. This study first identified and validated the pathogenic fungus in Chrysanthemum morifolium using Koch’s postulates. In response to the environmental impact of chemical pesticides, the study focused on biocontrol alternatives. Healthy C. morifolium rhizosphere soil was sampled to isolate antagonistic bacteria. Bacillus amyloliquefaciens, showing a 3.9 cm inhibition zone in plate confrontation tests, was identified as a potent biocontrol agent. Puncture inoculation tests on detached leaves and live plants demonstrated that lesion size in plants treated with both the pathogen and B. amyloliquefaciens was significantly reduced compared to controls, confirming the bacterium’s efficacy in inhibiting Fusarium wilt. This research provides a foundation for developing sustainable biocontrol methods for managing this disease in agriculture.

“‘latex This paper introduces ”SmartEdge,” a novel approach for optimizing the processing and analysis of Internet of Medical Things (IoMT) data. Through systematic preprocessing, advanced feature selection, controlled sampling, and innovative model aggregation, SmartEdge enhances performance and efficiency while minimizing computational overhead. The continuous improvement loop ensures adaptability to new data and operational conditions, promising significant advancements in IoMT ecosystem management. Our feature engineering on the CICIoMT2024 dataset emphasizes dimensionality reduction to improve computational efficiency in edge IoMT security and cyber attack detection. Techniques like Principal Component Analysis (PCA), feature selection, and embedding methods reduce the dataset’s dimensionality by 95%, drastically decreasing computational load and enabling real-time processing on resource-limited edge devices. This streamlining facilitates faster and more efficient machine learning model deployment, significantly boosting cyber attack detection and prevention in IoMT environments. Focusing on cyber resilience, we trained 10 edge models in just 55 seconds, with near-zero aggregation time due to an efficient method requiring no additional training or predictions. Using a small data set, five top features, and PCA with two components, we achieved high-performance results, with each model and the global model reaching accuracy above 0.99.

Hainan Province, a tropical island region in China, boasts a rich diversity of natural resources, including a substantial population of venerable trees (VTs). VTs, or venerable trees, represent an important ecological and cultural resource. However, accelerated urbanization and increased human activities pose significant threats to their survival. This study investigates the status of VTs in Hainan Province, analyzing key characteristics such as age, height, diameter at breast height (DBH), and crown width. We evaluated 373 species and 18,459 VTs, examining the natural and anthropogenic factors that drive their distribution. Results indicate a rich and diverse species composition, with a pyramidal age structure, where VT numbers decline with increasing age, suggesting a sufficient reserve of younger VTs. Spatial distribution patterns reveal a clustering of VTs, with higher densities in northern Hainan and reduced presence in coastal and seaward urban areas compared to inland regions. The optimal model identified habitat heterogeneity and environmental energy as the primary drivers of VT species diversity, with MAPR (maximum minus minimum precipitation) emerging as the strongest predictor of species richness. The best combination model showed a greater independent effect on VT species diversity patterns than the other models, which had lower values. Based on these findings, we propose protective measures to address the current threats and preservation challenges facing Hainan’s ancient trees.

“‘latex Tropical cyclones and their pertinent natural hazards can cause destructive damage to people and properties. Vietnam, located in the Northwest Pacific basin, is highly vulnerable to tropical cyclones due to its geography (i.e., a long coastline and narrow width). In this paper, we discuss how the negative consequences of tropical cyclones on Vietnam can be exacerbated by climate change and how forests, either in the mountainous or in the coastal regions, play crucial roles in safeguarding the country from tropical cyclones and their pertinent hazards (e.g., landslides and flood). Despite the importance of forests, their protection values are undermined, leading to continuous deforestation of natural forests for socio-economic development. We suggest the social transitions towards eco-surplus culture through more proactive and transparent communication of the destructive outcomes of tropical cyclones and the protection roles of forests in the current climate change era.

The major transient expression platforms for recombinant therapeutic proteins (RTPs) are Chinese hamster ovary (CHO) cells. Most improving strategies have been focused on expression promotion at the transcriptional level in CHO cells. How to promote RTPs yields through translation regulation remains unclear. This study investigated the effects of the 5’ untranslated region (UTR) characteristics on the recombinant protein expression of CHO cells. And used Ribo-seq to characterize regions on the 5’UTR that can promote translation initiation efficiency by complementary pairing with ribosomal RNA. Some elements located in 5’UTR and its characteristics differentially affected the translation of main ORF, resulting in a 1.5-fold increase in protein expression in CHO cells. This study presents a 5’UTR sequence analysis method and provides a new idea to break the bottleneck of RTPs yield from the rarely considered translation enhancement.

The complexity of modern language tasks demands increasingly adaptive, context-sensitive processing capabilities from language models, challenging traditional approaches in their ability to maintain coherent knowledge representation across varied contexts. Introducing Contextualized Dynamic Neuron Fusion (CDNF) offers a novel solution, addressing these limitations through an innovative, neuron-level fusion mechanism capable of real-time, context-driven adaptation without reconfiguration. CDNF enhances language model efficiency, enabling dynamic neuron reconfiguration in response to incoming contextual cues, thereby optimizing resource utilization and responsiveness in real-time scenarios. Empirical results demonstrate CDNF's effectiveness in improving knowledge retention, retrieval accuracy, and adaptability, particularly across variable and multilingual contexts, setting a foundation for future applications requiring continuous, adaptive language understanding. The findings demonstrate the potential of CDNF as a transformative approach within language model architectures, contributing substantially to advances in computational efficiency and contextual coherence in natural language systems.

AbstractBackgroundPsychological well-being (PWB) is defined as the normal functioning of the mind that contributes to enhanced overall health for individuals.ObjectivesTo determine the correlation between sleep position and psychological well-being in young adults in Pakistan.MethodologyThis cross-sectional study was conducted in a time frame between November 2023 and March 2024. A total of 436 participants were included in the study according to the WHO sample size calculator, which includes young adults (aged 18-26), both male and female of Pakistan. A questionnaire was sent to the participating young adults using Google Forms.ResultsA correlation test was applied to the data to evaluate the relationship between sleep position and PWB. A p-value of 0.046 showed a significant association and a Pearson correlation coefficient of -0.201 showed a negative association in participants with low psychological well-being. The correlation coefficient for individuals with high psychological well-being was 0.192 and the p-value was 0.035.

Title: Bothersome pelvic floor dysfunction and quality of life during pregnancy and postpartum in primiparous womenAuthor Details : Sofia Nestor, MD1; Jan Brynhildsen, MD, PhD2,3; Ayako Hiyoshi, PhD3; Markus Harry Jansson, MD, PhD2,41 Department of Obstetrics and Gynecology, Faculty of Medicine and Health, Örebro University, Sweden2 School of Medical Sciences, Faculty of Health and Medicine, Örebro University, Örebro, Sweden3 Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health, Örebro University, Sweden4 Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, SwedenCorresponding Author: Sofia Nestor, Department of Obstetrics and Gynecology, Örebro University Hospital , Region Örebro County, PO Box 1613, SE-701 16 Sweden. Telephone: +46 19 6021000, Fax: 019-126590, E-mail: sofia.nestor@regionorebrolan.seFinancial disclaimer/Conflicts of interest: None

Malignant melanoma is the deadliest form of skin cancer with a stage 4 having a 5-year survival rate less than 10%. Current treatment strategies for malignant melanoma lacks the targeting capability and therefore leads to either decreased therapeutic efficacy or enhanced occurrence of adverse drug reactions. Psoralen and Quercetin are two molecules that have been found to possess profound anti-cancer activity. Nano drug delivery systems have been found to enhance the therapeutic efficacy while minimizing the adverse drug reactions. In the present study, nano formulations of psoralen and quercetin were prepared by solvent injection technique, following which the stability of the formulation was assessed by characterisation of the same through various sophisticated instruments such as Transmission Electron Microscopy and Scanning Electron Microscopy. Anticancer activity of the nano formulations was checked and compared by studying its effects on malignant melanoma cells both in vitro and in vivo. It was revealed that nano formulations of the individual drugs exhibited enhanced efficacy over unbound or free drugs while being out performed by the nano formulation composed of the combination of the two drugs, which itself was again found to be overshadowed by the group exposed to photodynamic therapy (PDT) before administration of the dual drug loaded nano formulation.

Large-scale low earth orbit (LEO) constellations can enhance traditional global navigation satellite systems (GNSS) in many ways, but the rapid increase in the number of LEO satellites also poses challenges to the anti-interference performance of navigation signals. To improve the performance of the B1C signal in the future BeiDou global navigation satellite system, this paper proposes a modulation method: it enhances the existing quadrature multiplexed binary offset carrier (QMBOC) by using periodic binary hyperbolic frequency modulation (HFM) signals as subcarriers. The enhanced QMBOC signal (QMBOC-HFM) demonstrates superior anti-interference ，multipath mitigation performance and code tracking performance compared to the original QMBOC signal. The proposed QMBOC-HFM provides a potential signal design for future LEO navigation-augmented global satellite navigation systems.

IntroductionPorokeratosis (PK) is an epidermal disorder of keratinization caused by mevalonate pathway abnormalities. 1 Different clinical subtypes of PK are described. The common types include disseminated Superficial Actinic Porokeratosis, porokeratosis of Mibelli, and Linear porokeratosis. Disseminated superficial porokeratosis, eruptive disseminated porokeratosis, porokeratosis palmaris et plantaris disseminate, punctate porokeratosis, porokeratosis ptychotropica, penoscrotal porokeratosis, and Follicular porokeratosis (FPK) are the less common types of PK. 2 The clinical appearance, predilection site, and symptoms vary in various forms of PK.2 Cornoid lamella is the common histopathologic feature in all types of PK. 1, 2Follicular porokeratosis is a rare form of PK, characterized by the cornoid lamella filling the hair follicle infundibulum.3 Follicular porokeratosis may be concomitant with other PK forms 4 or occurs as pure FPK.5 Although most of the FPK cases are localized lesions3, 6-9, more diffuse distribution of lesions is reported in a few patients. 5, 10 The scalp is not a common site for FPK 3, 5, 11, and according to available sources, only one of the scalp FPK cases caused alopecia.5 Although diabetes mellitus type 2 accompanied some cases of porokeratosis 12, 13, we could not find any case of FPK associated with diabetes mellitus.Herein, we report a case of extensive FPK with spicules that caused alopecia of the scalp hair in a diabetic woman.

Upon pathogen attack, plants activate their immune response as a defense mechanism. AP2/ERF transcription factors are known to regulate these immune responses. Halostachys caspica belonging to Amaranthaceae, an exceptionally salt-tolerant halophyte, is widely distributed in the arid and saline-alkali regions of Xinjiang, in Northwest China. In our study, we explored the effects of HcmiR172e and its target gene, the AP2 subfamily transcription factor HcTOE3 from H. caspica, on the plant’s reaction to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) and Verticillium dahliae (VD991). We found that HcTOE3 is responsive to both Pst DC3000 and VD991, as well as to hormone treatments, including salicylic acid (SA), methyl jasmonate (MeJA), ethylene (ET), and 6-benzylaminopurine (6-BA). HcTOE3 transgenic Arabidopsis plants showed enhanced resistance to Pst DC3000 and VD991 infections compared to control plants. This resistance was associated with increased reactive oxygen species (ROS) accumulation, improved photosynthetic efficiency, reduced stomatal aperture, and increased lignin content in roots. Additionally, HcTOE3 significantly upregulated the expression of key genes involved in SA and JA signaling pathways, such as AtPR1, AtPR2, AtPR5, AtPDF1.2, and AtVSP2, as well as defense marker genes AtWRKY53, AtERF104, and AtPAD4. In contrast, HcmiR172e transgenic Arabidopsis plants exhibited an opposing trend in these indicators. Further, yeast one-hybrid and dual-luciferase assays confirmed that HcTOE3 can bind to the promoters of downstream defense-related genes, including AtPR1, AtPDF1.2, AtPR2, and AtVSP2, through possible cis-acting elements, such as TTTGTT, AGCTA, GAAG, and MYB motifs. Altogether, our findings indicate that HcTOE3 positively modulates Arabidopsis resistance against Pst DC3000 and VD991, while HcmiR172e negatively regulates Arabidopsis’s involvement in plant immune defense responses. This research offers new insights and evidence for further exploration of the role of AP2 subfamily members in the mechanisms of biotic stress resistance.

The conversion of forests to agricultural land, primarily driven by human activities, is a key factor in land degradation. Although the impacts of land degradation on ecosystem functions are well-documented, the relationship between land degradation and carbon and nitrogen content, as well as certain biochemical indices, has not been thoroughly investigated. To fill this knowledge gap, this study examined the responses of microbial biomass, microbial respiration, and activity to soil organic carbon, soil depth, and land use change (LUC), from forest to agriculture. The research was conducted in three different land use types (Forest, Converted, and Agriculture) with two soil depths (0–30 and 30–60 cm) under uniform climatic and topographical conditions in the Northeastern Mediterranean Karst ecosystems along the southern coast of Türkiye. Analysis of a total of 180 soil samples showed that there are significant differences in the chemical and biochemical properties of soils according to land use type and soil depth. In particular, soil organic carbon, total nitrogen, microbial carbon, microbial nitrogen, and microbial respiration were higher in the topsoil (0–30 cm depth) of the forest areas. Agricultural areas, in contrast, exhibit significantly lower levels of SOC (10%), TN (10%), C mic (26%), N mic (17%), and MR (6%) compared to converted areas, placing them in the same group based on Tukey’s HSD test. Chemical and biochemical soil properties and stoichiometric indices in the study areas varied significantly with soil depth (Table [2](#tbl-cap-0002)) and showed a decreasing trend through soil depth except for CaCO 3 (%), C mic/N mic, and qCO 2. Our findings also reveal that stoichiometric indices, such as C mic/N mic and qMic, are highly sensitive indicators of land-use change. These findings indicate that human-induced land degradation negatively impacts carbon and nitrogen storage as well as sensitive microbial indicators in the topsoil.

Despite the benefits of minimally invasive surgery, interventions such as laparoscopic liver surgery present unique challenges, like the significant anatomical differences between preoperative images and intraoperative scenes due to pneumoperitoneum, patient pose, and organ manipulation by surgical instruments. To address these challenges, we propose a method for intraoperative 3D reconstruction of the surgical scene, including vessels and tumors, without altering the surgical workflow. The technique combines Neural Radiance Field (NeRF) reconstructions from tracked laparoscopic videos with ultrasound 3D compounding. We evaluate the accuracy of our reconstructions on a clinical laparoscopic liver ablation dataset, consisting of laparoscope and patient reference poses from optical tracking, laparoscopic and ultrasound videos, as well as preoperative and intraoperative CTs. We propose a solution to compensate for liver deformations due to pressure applied during ultrasound acquisitions, improving the overall accuracy of the 3D reconstructions compared to the ground truth intraoperative CT with pneumoperitoneum. We train a unified NeRF from the ultrasound and laparoscope data, which allows real-time view synthesis providing surgeons with comprehensive intraoperative visual information for laparoscopic liver surgery.

This new research advances the NLG technique in the automation of financial report generation using methods that are deep learning architectures combined with advanced natural language generation. A new hybrid system which is one step ahead of the prevailing template-based techniques provides structured templates and intelligent models of language thus producing comprehensive, accurate, and contextually relevant financial reports, overcoming deficiencies in currently found techniques for automated report generation while being in line with the requirements of reporting standards. A custom transformer-based architecture, to which financial domain-specific embeddings were added, was proposed. This ensured 98% accuracy in numerical interpretation and helped maintain high linguistic coherence. Experimental results illustrating large improvements over traditional approaches were presented: these cut the time for report generation by 85% yet still maintained standards of quality. Our system was able to process more than 1,000 reports across multiple sectors with robust performance in the processing of complex financial narratives and numerical analyses. Achieving a BLEU score of 0.85 and a ROUGE score of 0.82 against other current state-of-the-art approaches, this work extends the state of the art by developing an efficient and dependable method for the automation of financial reporting, without losing sight of the conditions of the industry and achieving the maximum reduction of human intervention and all associated errors. Different datasets were used to train the model including: yfinance to fetch financial data from Yahoo Finance, financial phrase bank and dataset from Kaggle website

Lactate dehydrogenase is a well-studied oxidoreductase with profound implications in diseases like cancer and is a nonspecific marker of tissue damage. In vitro investigations into the mechanism of lactate dehydrogenase action reported herein are based on our group’s earlier reported thermodynamic calculations. While the reverse (pyruvate to lactate) reaction is thermodynamically favourable, the forward (lactate to pyruvate) reaction is highly unfavourable at physiological conditions. Herein, we studied the rates of NADH utilization and NADH formation, in the reverse and forward reactions, respectively, at varying pH conditions in three different buffer systems. NADH consumption rates were high, in the range of 2000-3000 M -1 s -1 and pH 7.4 was ideal for the pyruvate-lactate reduction reaction. However, in the forward reaction, the NADH formation rates were low (50 to < 300 M -1 s -1), if at all! Strikingly, inclusion of lactate dehydrogenase into liver tissue lysate caused a rapid decline of NADH formation rates. Fenton reaction using Fe 2+ and hydrogen peroxide catalyzed NADH formation, but again, addition of lactate dehydrogenase drastically decreased Fenton reaction-mediated NADH formation. Murburn, via one-electron oxidation of guaiacol by horseradish peroxidase, rapidly accelerated NADH formation rate in the range of 300-800 M -1 s -1; but consistently, addition of lactate dehydrogenase in the reaction significantly lowered the NADH formation rate. Another reaction was carried out with potassium superoxide and lactate to track NADH formation from NAD + and again, addition of both D- and L-lactate dehydrogenase led to a decline in NADH formation rates in the forward reaction. Gas-chromatography mass spectrometry and FT-IR results confirmed the superoxide-assisted oxidation of lactate, while addition of lactate dehydrogenase into this reaction once again suppressed lactate oxidation to pyruvate. These findings have phenomenal implications in the reaction mechanism of lactate dehydrogenase and the cellular processes that are linked to lactate dehydrogenase action.

“‘latex This article gives the author’s perspective on the history of the development of the Molecular Symmetry (MS) group. It explains how the initial work of Hougen, that was developed for nonlinear rigid molecules, inspired Longuet-Higgins to introduce nuclear permutations and the inversion as the fundamental elements of molecular symmetry. The symmetry group that is obtained applies to all molecules, rigid or nonrigid. The criticism of Altmann, and the rebuttal of that work by Watson.is described. Altmann’s work had the unfortunate effect of delaying the appreciation of Longuet-Higgins ideas…

Multimodal image fusion has become crucial for object detection, offer- ing enhanced feature representations by integrating information from diverse image modalities, such as RGB and thermal images. Recent advances in neural networks, including convolutional neural networks (CNNs) and Transformer-based approaches, have achieved substantial progress in this area. However, existing methods often struggle to fully integrate complementary information across modalities, particularly in enabling activated fusion over varying regions and scales. To address these limitations, we propose the Dynamic Channel Adjustment and Multi-Scale Activated Attention Mechanism Network (DAMAN). This model improves inter-modal feature integration and strengthens spa- tial and contextual information capture. Extensive experiments demon- strate DAMAN’s superior adaptability to objects of varying sizes and its robustness in complex traffic and industrial environments. Code and model checkpoints will be released following peer review.

With the increasing integration of photovoltaic (PV) systems, challenges in condition monitoring, fault diagnosis, and modeling of PV plants have intensified. To address the cluster division aspect of these challenges, a novel and efficient method using an improved spectral clustering (SC) approach is proposed. The approach starts with preprocessing the PV data to normalize variations in magnitude. The clustering process is then executed using the modified SC algorithm. To validate its effectiveness, comparative analyses are conducted using various clustering indices across different test cases. To comprehensively evaluate the performance of the approach, a comprehensive index is proposed. The results confirm that the method significantly enhances the efficiency and speed of cluster division in large-scale PV plants, making it a promising tool for PV system management.

Objective – To evaluate parents’ psychological distress and emotional suppression in the antenatal and postnatal periods of a pregnancy following a perinatal death. Design – Questionnaire. Setting – Tertiary Maternity Unit in the UK. Sample – Parents who were pregnant and attending a specialist antenatal clinic for pregnancy after loss. Methods – Partners and mothers completed questionnaire measures which evaluated their levels of depression, anxiety, post-traumatic stress (PTS) and emotional suppression at 23 and 32 weeks’ gestation, and 6 weeks postnatally. Levels were plotted over time and examined to determine if there were significant changes between time points. The proportion of partners and mothers scoring above threshold for each measure was identified, and differences in scores between mothers and partners were examined. Main outcome measures – Psychological distress and emotional suppression Results – Parents’ depression levels significantly decreased after the birth of a live baby and anxiety levels significantly decreased for mothers but not partners. PTS did not change across the course of a pregnancy, and symptoms continued into the postnatal period for mothers. Partners are more likely to hide their emotions during pregnancy than mothers. Conclusion – Both parents who have experienced a prior perinatal death are likely to experience high levels of psychological distress in a subsequent pregnancy which may continue into the postnatal period. Specialist mental health support offered within a dedicated pregnancy after loss service is one way to support parents. Further research is needed to determine whether psychological distress impacts on parent-child bonding.