Comparing reactive versus empiric cerebrospinal fluid drainage strategies for spinal perfusion pressure optimization in patients with acute traumatic spinal cord injuries.

BACKGROUND: Spinal cord hypoperfusion undermines clinical recovery in acute traumatic spinal cord injuries. New guidelines suggest cerebrospinal fluid (CSF) drainage is an important strategy for preventing spinal cord hypoperfusion in the acute post-injury phase. METHODS: This study included participants presenting to a single level 1 trauma center between 2018 and 2022 with cervical or thoracic traumatic spinal cord injury severity grade A-C, as evaluated by the American spinal injury association impairment scale (AIS). The primary objective of this study was to compare the efficacy of two CSF drainage protocols in preventing spinal cord hypoperfusion; 1) draining CSF only when spinal cord perfusion pressure (SCPP) drops below 65 mmHg (i.e. reactive) versus 2) empiric CSF drainage of 5-10 mL every hour. Intrathecal pressure, spinal cord perfusion pressure (SCPP), mean arterial pressure (MAP), and vasopressor utilization were compared using univariate T-test statistical analysis. RESULTS: While there was no difference in the incidence of sub-optimal SCPP (<65 mmHg; p = 0.1658), reactively drained participants were more likely to exhibit critical hypoperfusion (<50 mmHg; p = 0.0030) despite also having lower average intrathecal pressures (p < 0.001). There were no differences in average SCPP, mean arterial pressure (MAP), or vasopressor utilization between the two groups (p > 0.05). CONCLUSIONS: Empiric (vs reactive) CSF drainage resulted in fewer incidences of critical spinal cord hypoperfusion for patients with acute traumatic spinal cord injuries.

Dementia care landscape in Nepal: Understanding the context, barriers, and opportunities for the development of a national dementia care plan.

OBJECTIVE: This study was conducted to comprehensively understand the context, barriers, and opportunities for improving dementia care, treatment, and support. The objective is to guide the development of a national dementia care plan. METHODOLOGY: This document review was conducted by analyzing literature available in the public domain, including scientific publications, project documents/reports, media reports, and hospital records. Additionally, annual reports published by the Department of Health Services, national census and demographic and health survey reports, Old Age Homes, and other relevant government reports were examined. Firsthand information was gathered from relevant stakeholders based on the World Health Organization's situational analysis framework for dementia plans. This framework encompasses four domains: Policy context (national ministries, legislation, policies, strategies, plans related to dementia, mental health, aging, and disability), service delivery assessment (health and social care workforces, services, support and treatment programmes, and promotion of awareness and understanding), and epidemiological indicators (prevalence and incidence rates of dementia, risk factors). Ethical clearance was obtained from the Institutional Review Committee (IRC) of B.P. Koirala Institute of Health Sciences (IRC no.2658/023). RESULTS: Existing policies in Nepal inadequately address the needs of people with dementia and their caregivers. Concerning health services, the Government of Nepal provides financial subsidies to individuals diagnosed with dementia; however, numerous hurdles impede access to care. These obstacles include geographical and structural barriers, an inefficient public healthcare system, weak governance, financial constraints, low awareness levels, stigma, and inadequate workforce. Furthermore, the absence of robust nationally representative epidemiological studies on dementia in Nepal hampers the development of evidence-based plans and policies. Similarly, there are no interventions targeted at caregivers of people with dementia, and no initiatives for dementia prevention are in place. CONCLUSIONS: This review underscores the urgent need to formulate a comprehensive national dementia care plan to address the growing challenges. Key priority action areas include the integration of dementia care into primary healthcare services, training workforce to provide the care, increasing awareness, mitigating stigma, developing caregiver support programs, and initiating high-quality research to inform evidence-based policymaking.

High-risk subgroups were not identified to benefit from thromboprophylaxis after hospitalization for COVID-19.

Background: The Accelerating COVID-19 Therapeutic Interventions and Vaccines-4c (ACTIV-4c) trial investigated prophylactic apixaban for 30 days following hospitalization for COVID-19. The overall incidence of early postdischarge death or thromboembolism was low, and the trial was closed early. Objectives: To identify a high-risk patient population who might benefit from postdischarge thromboprophylaxis through subgroup analyses stratified by age, race/ethnicity, obesity, D-dimer elevation, World Health Organization score, and modified International Medical Prevention Registry on Venous Thromboembolism score on 30-day composite outcome of all-cause death, arterial thromboembolism (ATE), and venous thromboembolism (VTE). Methods: Cumulative incidences of all-cause death, ATE, and VTE within 30 days were described for each subgroup. Time to death, ATE, or VTE by 30 days was analyzed using Cox proportional hazard models with interaction testing for each subgroup. Results: Among 1217 patients randomized to apixaban or placebo group, 32% were >60 years old. Modified International Medical Prevention Registry on Venous Thromboembolism score was ≥4 in 2% and 2 or 3 with an elevated D-dimer in an additional 9% of participants. The overall incidence of the primary endpoint was 2.13% in the apixaban group and 2.31% in the placebo group. At day 30, similar rates of the primary endpoint occurred within subgroups, except for participants aged >60 years. No benefit of thromboprophylaxis was seen in any subgroup. Conclusion: The combined incidence of 30-day death, ATE, and VTE was low in patients who survived COVID-19 hospitalization, except in patients over age 60 years. Due to the limited number of events, the findings remain inconclusive; nonetheless, the study did not identify a high-risk subgroup that would derive benefits from extended thromboprophylaxis.

Impact of Prosigna test on adjuvant treatment decision in lymph node-negative early breast cancer-a prospective national multicentre study (EMIT-1).

BACKGROUND: EMIT-1 is a national, observational, single-arm trial designed to assess the value of the Prosigna, Prediction Analysis of Microarray using the 50 gene classifier (PAM50)/Risk of Recurrence (ROR), test as a routine diagnostic tool, examining its impact on adjuvant treatment decisions, clinical outcomes, side-effects and cost-effectiveness. Here we present the impact on treatment decisions. PATIENTS AND METHODS: Patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative pT1-pT2 lymph node-negative early breast cancer (EBC) were included. The Prosigna test and standard histopathology assessments were carried out. Clinicians' treatment decisions were recorded before (pre-Prosigna) and after (post-Prosigna) the Prosigna test results were disclosed. RESULTS: Of 2217 patients included, 2178 had conclusive Prosigna results. The pre-Prosigna treatment decisions were: no systemic treatment (NT) in 27% of patients, endocrine treatment alone (ET) in 38% and chemotherapy (CT) followed by ET (CT + ET) in 35%. Post-Prosigna treatment decisions were 25% NT, 51% ET and 24% CT + ET, respectively. Adjuvant treatment changed in 28% of patients, including 21% change in CT use. Among patients assigned to CT + ET pre-Prosigna, 45% were de-escalated to ET post-Prosigna. Of patients assigned to ET, 12% were escalated to CT + ET and 8% were de-escalated to NT; of those assigned to NT, 18% were escalated to ET/CT + ET. CT was more frequently recommended for patients aged ≤50 years. In the subgroup with pT1c-pT2 G2 and intermediate Ki67 (0.5-1.5× local laboratory median Ki67 score), the pre-Prosigna CT treatment decision varied widely across hospitals (3%-51%). Post-Prosigna, the variability of CT use was markedly reduced (8%-24%). The correlation between Ki67 and ROR score within this subgroup was poor (r = 0.25-0.39). The median ROR score increased by increasing histological grade, but the ROR score ranges were wide (for G1 0-79, G2 0-90, G3 16-94). CONCLUSION: The Prosigna test result changed adjuvant treatment decisions in all EBC clinical risk groups, markedly decreased the CT use for patients categorized as higher clinical risk pre-Prosigna and reduced treatment decision discrepancies between hospitals.

Testing the amount of nicotinamide mononucleotide and urolithin A as compared to the label claim.

Healthy Longevity Medicine aims to optimize health by targeting aging processes across the lifespan. Addressing accelerated aging involves adaptation of lifestyle and the use of geroprotective drugs and supplements, including nutritional supplements and bioactive compounds. The Food and Drug Administration, under the Dietary Supplement Health and Education Act, categorizes bioactive compounds and medicinal products as dietary supplements. While numerous companies sell ingredients that can be deemed geroprotectors, there's limited oversight in their quality control. Governmental safety authorities only verify the presence of prohibited compounds, not the accuracy of ingredients listed on labels.Here, Nicotinamide mononucleotide and Urolithin A supplements, easily accessible online or in pharmacies, were tested for their active ingredient content. Results showed a significant deviation from the labeled amounts, ranging from + 28.6% to -100%. This indicates a considerable disparity in the quality of geroprotective supplements.To address this variability, collaboration between and within societies representing healthcare professionals, industry and regulatory bodies is imperative to ensure the quality of geroprotective supplements.

Time of day does not impact spinal serotonin levels in humans.

Spinal serotonin enables neuro-motor recovery (i.e., plasticity) in patients with debilitating paralysis. While there exists time of day fluctuations in serotonin-dependent spinal plasticity, it is unknown, in humans, whether this is due to dynamic changes in spinal serotonin levels or downstream signaling processes. The primary objective of this study was to determine if time of day variations in spinal serotonin levels exists in humans. To assess this, intrathecal drains were placed in seven adults with cerebrospinal fluid (CSF) collected at diurnal (05:00 to 07:00) and nocturnal (17:00 to 19:00) intervals. High performance liquid chromatography with mass spectrometry was used to quantify CSF serotonin levels with comparisons being made using univariate analysis. From the 7 adult patients, 21 distinct CSF samples were collected: 9 during the diurnal interval and 12 during nocturnal. Diurnal CSF samples demonstrated an average serotonin level of 216.6 ± $ \pm $ 67.7 nM. Nocturnal CSF samples demonstrated an average serotonin level of 206.7 ± $ \pm $ 75.8 nM. There was no significant difference between diurnal and nocturnal CSF serotonin levels (p = .762). Within this small cohort of spine healthy adults, there were no differences in diurnal versus nocturnal spinal serotonin levels. These observations exclude spinal serotonin levels as the etiology for time of day fluctuations in serotonin-dependent spinal plasticity expression.

Experimental design and analysis of advanced three phase converter for PV application with WCO-P&O MPPT controller.

Photovoltaic (PV)-based power generation systems are becoming increasingly popular as a due to its high performance and cleanliness. Several factors influence the performance of a PV system, including shadowing effects. PV systems employ MPPT methodologies to obtain the power from PV array. Conventional MPPTs works well under normal conditions when there is no shadow effects or partial shading. The presence of partial shading affects the system performance and generates several power peaks. This complicates the process of finding out of the global peak (GMPP) with improved tracking efficiency and reduced settling time including conversion efficiency. This work proposes three hybrid MPPT techniques: Water Cycle Optimisation-Perturb and Observe (WCO-PO), Artificial Neural Network Supported Adaptable Stepped-Scaled Perturb and Observe (ANN-ASSPO), Grey Wolf Optimisation-Modified Fast Terminal Sliding Mode Controller (GWO-MFTSMC), and two conventional MPPT techniques WCO and P&O have been implemented. The proposed system utilizes interleaved boost converter with three phase. The performances of proposed hybrid MPPTs strategies were compared in terms of output voltage, output current and extracted power. The comparison also includes conversion efficiency and average settling time. To analyse the performances, four different cases have been used to test the efficacy of hybrid MPPTs under changing climatic conditions. The MATLAB/Simulink tool has been used to analyze the PV system performances. In the three hybrid MPPT techniques, WCO-PO has performed better when compared to other two hybrid MPPTs in terms of conversion efficiency (99.56%) and settling time (1.4 m).

Designing a deep hybridized residual and SE model for MRI image-based brain tumor prediction.

Deep learning techniques have become crucial in the detection of brain tumors but classifying numerous images is time-consuming and error-prone, impacting timely diagnosis. This can hinder the effectiveness of these techniques in detecting brain tumors in a timely manner. To address this limitation, this study introduces a novel brain tumor detection system. The main objective is to overcome the challenges associated with acquiring a large and well-classified dataset. The proposed approach involves generating synthetic Magnetic Resonance Imaging (MRI) images that mimic the patterns commonly found in brain MRI images. The system utilizes a dataset consisting of small images that are unbalanced in terms of class distribution. To enhance the accuracy of tumor detection, two deep learning models are employed. Using a hybrid ResNet+SE model, we capture feature distributions within unbalanced classes, creating a more balanced dataset. The second model, a tailored classifier identifies brain tumors in MRI images. The proposed method has shown promising results, achieving a high detection accuracy of 98.79%. This highlights the potential of the model as an efficient and cost-effective system for brain tumor detection.

A machine learning approach to predict mortality due to immune-mediated thrombotic thrombocytopenic purpura.

Background: Mortality due to immune-mediated thrombotic thrombocytopenic purpura (iTTP) remains significant. Predicting mortality risk may potentially help individualize treatment. The French Thrombotic Microangiopathy (TMA) Reference Score has not been externally validated in the United States. Recent advances in machine learning technology can help analyze large numbers of variables with complex interactions for the development of prediction models. Objectives: To validate the French TMA Reference Score in the United States Thrombotic Microangiopathy (USTMA) iTTP database and subsequently develop a novel mortality prediction tool, the USTMA TTP Mortality Index. Methods: We analyzed variables available at the time of initial presentation, including demographics, symptoms, and laboratory findings. We developed our model using gradient boosting machine, a machine learning ensemble method based on classification trees, implemented in the R package gbm. Results: In our cohort (n = 419), the French score predicted mortality with an area under the receiver operating characteristic curve of 0.63 (95% CI: 0.50-0.77), sensitivity of 0.35, and specificity of 0.84. Our gradient boosting machine model selected 8 variables to predict acute mortality with a cross-validated area under the receiver operating characteristic curve of 0.77 (95% CI: 0.71-0.82). The 2 cutoffs corresponded to sensitivities of 0.64 and 0.50 and specificities of 0.76 and 0.87, respectively. Conclusion: The USTMA Mortality Index was acceptable for predicting mortality due to acute iTTP in the USTMA registry, but not sensitive enough to rule out death. Identifying patients at high risk of iTTP-related mortality may help individualize care and ultimately improve iTTP survival outcomes. Further studies are needed to provide external validation. Our model is one of many recent examples where machine learning models may show promise in clinical prediction tools in healthcare.

Purification of exopolysaccharide produced from Lactobacillus spp. using ionic-liquid as adjuvant in alcohol/salt-based aqueous two-phase system for its antidiabetic properties.

Diabetes is a chronic, metabolic disease characterized by hyperglycemia resulting from either insufficient insulin production or impaired cellular response to insulin. Exopolysaccharides (EPS) produced by Lactobacillus spp. demonstrated promising therapeutic potential in terms of their anti-diabetic properties. Extraction and purification of EPS produced by Lactobacillus acidophilus and Limosilactobacillus reuteri were performed using ethanol precipitation, followed by alcohol/salt based aqueous two-phase system (ATPS). The purification process involved ethanol precipitation followed by an alcohol/salt-based ATPS. The study systematically investigated various purification parameters in ATPS, including ethanol concentration, type and concentration of ionic liquid, type and concentration of salt and pH of salt. Purified EPS contents from L. acidophilus (63.30 µg/mL) and L. reuteri (146.48 µg/mL) were obtained under optimum conditions of ATPS which consisted of 30 % (w/w) ethanol, 25 % (w/w) dipotassium hydrogen phosphate at pH 10 and 2 % (w/w) 1-butyl-3-methylimidazolium octyl sulfate. The extracted EPS content was determined using phenol sulphuric acid method. In α-amylase inhibition tests, the inhibitory rate was found to be 92.52 % (L. reuteri) and 90.64 % (L. acidophilus), while in α-glucosidase inhibition tests, the inhibitory rate was 73.58 % (L. reuteri) and 68.77 % (L. acidophilus), based on the optimized parameters selected in ATPS. These results suggest that the purified EPS derived from the postbiotics of Lactobacillus spp. hold promise as potential antidiabetic agents.

Changes in confocal microscopy in glaucoma patients after intraocular pressure reduction with medical therapy.

PURPOSE: Topical glaucoma medication is the first line of management to reduce intraocular pressure (IOP) in patients with glaucoma. In this study, we intended to compare the ultrastructural findings of the cornea in patients with glaucoma before and after the reduction of the IOP through confocal microscopy. METHODS: Ten patients (19 eyes) with newly diagnosed glaucoma were recruited from the glaucoma services of our tertiary care center. Demographic parameters were noted, and basic ocular examination, specular microscopy (Topcon SP3000P, Tokyo, Japan), and ultrasonic pachymetry (300 AP, Sonomed Escalon, Stoneham, MA, USA) were performed. In vivo confocal microscopy of corneal sections was performed using the z-ring Confoscan 4.0 (Nidek, Inc., Freemont, CA) at baseline and after 3 months of starting glaucoma medications. RESULTS: The mean age of the patients was 53.53 ± 9.34 years. There was a statistically significant reduction ( P < 0.0001) of IOP from 30.21 ± 7.42 mmHg (baseline) to 16.42 ± 4.14 mmHg (3 months). The mean central corneal thickness at baseline was 533.42 ± 3.96 µm, and it further decreased to 521.94 ± 42.45 µm at the end of 3 months ( P = 0.006). No significant change was noted in the mean epithelial cell density, mean keratocyte density in anterior and posterior stroma, and the mean endothelial cell density and cell area ( P >0.5). There was no significant percentage change in these parameters before and after the lowering of the IOP. CONCLUSION: A short-term (3 months) decrease in IOP using topical glaucoma medications caused a significant reduction in corneal thickness but did not have any significant ultrastructural changes in cornea measured using confocal microscopy.

A Comparative Evaluation of Three Methods of Disinfection of Gypsum Casts and the Changes in Surface Roughness and Dimensional Accuracy after Disinfection-An Ex Vivo Study.

BACKGROUND: One of the major problems of everyday dental practice is cross-contamination. It can place office personnel, dentists, and patients at risk of acquiring serious illness. Disinfection helps in controlling this cross-contamination to an extent. The evaluation was done to find the efficient disinfection method on gypsum casts. AIMS: The aim of this study is to evaluate and compare the efficacy of three methods of disinfection of gypsum casts, namely, chemical disinfection by immersion, spray method, and microwave method, and also to evaluate and compare changes in surface roughness and dimensional accuracy between the three methods after disinfection. MATERIALS AND METHODS: Ex vivo and experimental study. Thirty participants were selected, and impressions of the maxillary arch were made using polyvinyl siloxane impression material. Ninety type IV die stone gypsum casts were poured. It was divided into three groups and was subjected to chemical disinfection by immersion and spray methods, and microwave method. The disinfected casts were evaluated for microbial growth, surface roughness, and dimensional accuracy. It was performed by using the one-way analysis of variance test and paired t-test followed by the Kruskal - Wallis test and Wilcoxon signed rank test (α = 0.05). RESULTS: Microwave disinfection was more effective than both immersion and spray chemical disinfection methods (P < 0.010 and <0.001). The surface roughness of the microwave-irradiated casts had significantly increased after disinfection. However, there were no significant dimensional changes by any of the methods of disinfection. CONCLUSION: Within the limitations of the study, the microwave method of disinfection is more effective in eradicating microorganisms when compared to chemical methods of disinfection by immersion and spray methods.

Development of antibody to virulence factor flagellin and its evaluation in screening Ralstonia pseudosolanacearum.

The bacterial wilt disease caused by Ralstonia pseudosolanacearum presents a notable economic risk to a variety of crucial crops worldwide. During preliminary isolation of this phytopathogen, several colonies of other saprophytic bacteria may be mistaken with it. So, the present study aims to address this issue by proposing the application of immunogenic proteins, particularly flagellin (FliC), to enable a rapid and early identification of bacterial wilt. In this study, a novel approach is unveiled for the early detection of R. pseudosolanacearum. The study exploits the immunogenic attributes of flagellin (FliC), by generating polyclonal antibodies against recombinant FliC within model organisms-rabbits and mice. The efficacy of these antibodies is meticulously assessed through discerning techniques, including DAS-ELISA and Western blot analyses, which elucidate their remarkable specificity in identifying various R. pseudosolanacearum strains. Furthermore, the introduction of antibody-coated latex agglutinating reagents offers an additional layer of confirmation, substantiating the feasibility of establishing a laboratory-based toolkit for swift screening and unambiguous identification of the bacterial wilt pathogen. This study presents a significant stride toward enhancing early diagnostic capabilities, potentially revolutionizing agricultural practices by safeguarding crop yield and quality through proactive pathogen detection and mitigation strategies.

Recent advances in immuno-based methods for the detection of Ralstonia solanacearum.

Ralstonia solanacearum (RS) is a widely recognized phytopathogenic bacterium which is responsible for causing devastating losses in a wide range of economically significant crops. Timely and accurate detection of this pathogen is pivotal to implementing effective disease management strategies and preventing crop losses. This review provides a comprehensive overview of recent advances in immuno-based detection methods for RS. The review begins by introducing RS, highlighting its destructive potential and the need for point-of-care detection techniques. Subsequently, it explores traditional detection methods and their limitations, emphasizing the need for innovative approaches. The main focus of this review is on immuno-based detection methods and it discusses recent advancements in serological detection techniques. Furthermore, the review sheds light on the challenges and prospects of immuno-based detection of RS. It emphasizes the importance of developing rapid, field-deployable assays that can be used by farmers and researchers alike. In conclusion, this review provides valuable insights into the recent advances in immuno-based detection methods for RS.

How Is It Possible to Treat Diseases Without Medicine?: A Qualitative Study on the Attitude and Perceived Benefits of Yoga and Naturopathy Among Patients Admitted at an Inpatient Hospital.

Background: Yoga and naturopathy (Y&N) is a system of medicine primarily focusing on restoration of health and well-being. Objective of this study is to understand the knowledge, attitude, and perception about Y&N among the inpatients of a government Y&N institution in south India. Methods: Focus group discussion was conducted in eight adult patients aged between 30 and 60 years who took Y&N treatments for a period of 10 days or more. Purposive sampling method was adopted. Oral informed consent was obtained. Results: Knowledge about the Y&N system of medicine was primarily through referral or "word of mouth." Perceived benefits were both physical and psychological. Uniqueness of the hospital as mentioned by participants includes individual attention, tailor-made treatment protocols, and one-to-one care to the needy patients. Conclusion: An integrated approach is very much essential that might bring about better treatment outcomes in patients.

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15.

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3rd among 26 CASP15 server predictors and MULTICOM_human ranked 7th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.